ACQUIRING MARKETING KNOWLEDGE
THROUGH INTERNATIONAL JOINT VENTURES
By
Le Nguyen Hau
MCommHons. (UWS), GradDipMgt. (ECU), BEng. (HCMUT)
A thesis submitted for the Degree of Doctor of Philosophy
University of Western Sydney
August, 2004
Revised February, 2005
ACKNOWLEDGEMENTS
This thesis could not have been completed without the support, guidance and
encouragement of many people. In particular, I wish to express my deepest
gratitude to my supervisor, Associate Professor Felicitas Evangelista for her
invaluable academic advice as well as other support beyond her academic duty.
I would like to express my sincere thanks to Prof. Richard Fletcher, Head of
School of Marketing and International Business, University of Western
Sydney, for the administrative and financial support. My sincere thanks are
also extended to Prof. Ian Wilkinson and Prof. Robert March who granted me a
study place in the school.
I am deeply indebted to Dr. Hans Stoessel, Director of the Swiss-AIT-Vietnam
Management Development Programme for the generous financial support
during my course of study.
My appreciation is extended to Dr. Nguyen Dinh Tho, University of
Technology – Sydney, for helping me with SEM/AMOS. I would like to thank
Dr. Nguyen Tien Tam, University of Western Australia and Mr. Hoang Tuan,
Vietnam National University of HoChiMinh City for the proof-reading of the
manuscript of this thesis.
I would also like to express many thanks to my dear colleagues in the School
of Industrial Management, HoChiMinh City University of Technology for their
continuous encouragement and help during the last years.
Last but not least, this is a great time for a son of parents, husband of wife, and
father of two kids to say thanks to his wonderful family.
STATEMENT OF AUTHENTICATION
The work presented in this thesis is, to the best of my knowledge and belief,
original based on raw data collected by me, except where due
acknowledgement is made in the text. I hereby declare that I have not
previously submitted this material, either in full or in part, for a degree at this
or any other institution.
………………………………….
Le Nguyen Hau
TABLE OF CONTENTS
Page
Table of Contents…………………..…………………………………………………i
List of Tables………………………………………………………………………...vi
List of Figures …………………………………………………………………….. viii
Abbreviations ………………………………………………………………………..ix
Abstract ……………………………………………………………………………. x
CHAPTER 1
INTRODUCTION…………………………….……1
1.1. BACKGROUND …..……………..……………………………………….…1
1.2. RESEARCH PROBLEMS AND GAPS ………………………………….....3
1.2.1. The process of knowledge acquisition in strategic alliances ………….3
1.2.2. The tacitness of knowledge……………………………………….…...4
1.2.3. The type of knowledge being transferred...……………………………5
1.2.4. The outcome of learning and knowledge acquisition …………………6
1.2.5. Conceptual versus empirical research……………………………....….6
1.3. RESEARCH OBJECTIVES…………………………………………….……..7
1.4. METHODOLOGY…………………………………………………………….8
1.5. RESEARCH DELIMITATIONS……………………………….……………..8
1.5.1. Marketing know-how…………………………………………………..8
1.5.2. IJV in developing countries………………………………………… ...9
1.5.3. One-way knowledge acquisition……………………………………….9
1.5.4. The first phase of interpartner knowledge acquisition………………..10
1.6. DEFINITIONS OF KEY TERMS……………………………………………10
1.6.1. Knowledge acquisition ……………………………………………….10
1.6.2. Marketing know-how…………………………………………………10
1.6.3. Tacit marketing know-how …………………………………….…….11
1.6.4. Explicit marketing know-how..……………………………………….11
1.6.5. International joint venture (IJV)……………………………………...12
1.7. OUTLINE OF THE THESIS ……………………………………………….12
CHAPTER 2
LITERATURE REVIEW …………………………14
2.1. INTRODUCTION…………………………………………………….…….14
i
2.2. ORGANIZATIONAL LEARNING………………………………….……..15
2.2.1. Knowledge – A firm’s strategic asset………………………….……..15
2.2.2. The concept of organizational learning…………………...................16
2.2.3. Organizational learning and learning organization…………………..19
2.2.4. Organizational learning from different perspectives…………………21
2.2.5. How an organization learns…………………………………….….…23
2.2.6. Organizational learning facilitators………………………….……….27
2.2.7. Debates and issues in organizational learning…………….………….29
2.3. INTERNATIONAL JOINT VENTURE…………………………………....33
2.3.1. Strategic alliance……………………………………………………...33
2.3.2. Joint venture………………………………………………….……….34
2.3.3. Motives of partner firms to to form joint ventures……………….…..37
2.3.4. Motives of partners in developing countries…………………………39
2.4. LEARNING AND KNOWLEDGE ACQUISITION IN IJVs……………...40
2.4.1. Background on learning in strategic alliances…………………….….41
2.4.2. Learning in IJVs between firms in developed
and developing countries……………………………………………..42
2.4.3. Learning in IJVs – Patterns and framework………………….………45
2.5. INTERPARTNER LEARNING FACILITATORS: RESEARCH GAPS….49
2.5.1. Facilitators of knowledge acquisition - previous studies……………..50
2.5.2. Research gaps…………………………………………………………55
2.5.3. Issues addressed by the current research……………………………..57
CHAPTER 3
CONCEPTUAL FRAMEWORK AND
HYPOTHESES…………………………………….59
3.1. INTRODUCTION……………………………………………………….….59
3.2. MARKETING KNOW-HOW……………………………………………....59
3.3. ACQUISITION OF MARKETING KNOW-HOW………………………...65
3.3.1. Acquisition of explicit marketing know-how………………………...66
3.3.2. Acquisition of tacit marketing know-how…………………………....67
3.4. FACILITATORS OF MARKETING KNOW-HOW ACQUISITION….…69
3.4.1. IJV management features……………………………………….……72
3.4.2. Knowledge seeker (local partner)………………………………….…76
3.4.3. Knowledge holder (foreign partner)……………………………….…81
3.4.4. Matching factors……………………………………………………...85
ii
3.4.5. Relationship between the acquisition of explicit and tacit know-how .92
3.5. OUTCOMES OF LEARNING IN IJVs…………………………………….93
3.5.1. Marketing competence improvement……………………………..….94
3.5.2. Marketing dynamism………………………………………….…..….97
CHAPTER 4
RESEARCH METHODOLOGY………………. 101
4.1. INTRODUCTION……………………………………………………..…..101
4.2. MEASUREMENT OF CONSTRUCTS…………………..…………….…102
4.2.1. IJV management commitment………………………………………103
4.2.2. Teamwork………….……………………………………………..…105
4.2.3. Learning intent………………………………………………………106
4.2.4. Learning capability………………………………………………….107
4.2.5. Partner assistance……………………………………………………108
4.2.6. Knowledge protectiveness…………………………………………..109
4.2.7. Relationship strength………………………………………………..110
4.2.8. Cultural distance…………………………………………………….112
4.2.9. Acquisition of explicit marketing know-how……………………….113
4.2.10. Acquisition of tacit marketing know-how…………………………114
4.2.11. Marketing experience improvement……………………………….115
4.2.12. Marketing dynamism………………………………………………116
4.3. AN OVERVIEW OF IJVs IN VIETNAM………………………………...117
4.4. UNIT OF ANALYSIS AND SAMPLING……………………………...…120
4.5. DATA COLLECTION…………………………………………………….120
4.5.1. Questionnaire………………………………………………………..122
4.5.2. Data collection procedure…………………………………………...123
CHAPTER 5
ASSESSMENT AND REFINEMENT OF
MEASUREMENT SCALES..................................129
5.1. INTRODUCTION…………………………………………………………129
5.2. SAMPLE CHARACTERISTICS………………………………………….129
5.2.1. Industry…………………………………………………..…….……129
5.2.2. IJV’s age and duration………………………………………………130
5.2.3. Country of origin of foreign partners………………………………..131
5.2.4. IJV size………………………………………………………………131
5.2.5. Number of foreign and local marketing staff………………………..132
iii
5.2.6. IJV performance……………………………………………………..133
5.2.7. Marketing knowledge of foreign partner……………………………133
5.3. ASSESSMENT OF MEASUREMENT SCALES – BACKGROUND…..133
5.3.1. Unidimensionality, reliability and validity………………………….133
5.3.2. Exploratory and confirmatory factor analyses………………………135
5.4. ASSESSMENT OF MEASUREMENT SCALES USING EFA…………137
5.4.1. Procedure……………………………………………………………137
5.4.2. EFA results………………………………………………………….138
5.5. ASSESSMENT OF MEASUREMENT SCALES USING CFA…………146
5.5.1. Introduction………………………………………………………….146
5.5.2. Test of unidimensionality, reliability and validity using CFA……...147
5.5.3. Procedure……………………………………………………………148
5.5.4. Estimation methods and overall model fit measures………………..149
5.6. RESULTS OF CFA FOR INDIVIDUAL SCALES………………………151
5.6.1. CFA results - satisfactory scales…………………………….………151
5.6.2. CFA results - scales needing refinement……………………………155
5.6.3. Summary of CFA for the 12 individual scales………………………157
5.7. RESULTS OF CFA FOR SELECTED PAIRS OF SCALES……………..157
5.8. CFA FOR THE FULL MEASUREMENT MODEL…………………...…160
5.9. SUMMARY……………………………………………………………….165
CHAPTER 6
TESTING THE THEORETICAL MODEL AND
HYPOTHESES………………………….….……167
6.1. INTRODUCTION………………………………………………….….…..167
6.2. ASSESSMENT OF THE THEORETICAL MODEL……………….…….167
6.2.1. Structural equation modeling and two-step approach………….……167
6.2.2. The theoretical model: estimation and assessment………………….168
6.3. MODEL MODIFICATION……………………………………..................171
6.3.1. Theoretical consideration……………………………………………171
6.3.2. The modified model…………………………………………………173
6.3.3. Further assessment of the modified model………………………….175
6.4. TEST OF HYPOTHESES…………………………………………………178
6.5. DISCUSSIONS………………………………………………………….…186
6.5.1. On the selected model……………………………………………….186
6.5.2. On the antecedents of know-how acquisition……………………….187
iv
6.5.3. On the explanatory power of the eight antecedents…………………189
6.5.4. On the separate examination of tacit and explicit know-how……….189
6.5.5. On the outcomes of marketing know-how acquisition……………...190
CHAPTER 7
CONCLUSIONS…………………………………191
7.1. OVEVIEW………………………………………………………..….……191
7.2. SUMMARY OF THE FINDINGS…………..……………………….……191
7.3. CONTRIBUTIONS AND IMPLICATIONS ..……………………………193
7.3.1. Theoretical contribution………………………..……………………193
7.3.2. Methodological contribution………………………………..……….194
7.3.3. Managerial implications……………………………………..………195
7.4. LIMITATIONS AND FURTHER RESEARCH DIRECTIONS….………197
REFERENCES………………………………………………………..200
APPENDICES ………………………………….…………………… 221
APPENDIX 1: Questionnaire in English ……………………………………..222
APPENDIX 2: Questionnaire in Vietnamese ………………………………...229
APPENDIX 3: Sample covariances matrix …………………………………..236
APPENDIX 4: Sample correlation matrix ……………………………………238
APPENDIX 5: Univariate normality of the composite variables......................240
APPENDIX 6: Standardized residual covariances …………………………...241
v
LIST OF TABLES
Page
Table 2.1
:
Levels of organizational learning
24
Table 2.2
:
Summary of suggested organizational learning facilitators
28
Table 2.3
:
Summary of recent researches on facilitators of knowledge
transfer
52
Table 3.1
:
Examples of explicit and tacit components of marketing
know-how
64
Table 3.2
:
Summary of hypotheses to be tested
100
Table 4.1
:
Indicators of management commitment
104
Table 4.2
:
Indicators of teamwork
105
Table 4.3
:
Indicators of learning intent
106
Table 4.4
:
Indicators of learning capability
108
Table 4.5
:
Indicators of partner assistance
109
Table 4.6
:
Indicators of partner knowledge protectiveness
110
Table 4.7
:
Indicators of relationship strength
111
Table 4.8
:
Indicators of cultural distance
112
Table 4.9
:
Indicators of acquisition of explicit marketing know-how
114
Table 4.10
:
Indicators of acquisition of tacit marketing know-how
115
Table 4.11
:
Indicators of marketing competence improvement
116
Table 4.12
:
Indicators of marketing dynamism
117
Table 4.13
:
Vietnam’s FDI by sector, as at end-2001
119
Table 4.14
:
Top ten sources of FDI inflows in Vietnam
119
Table 4.15
:
FDI formats in Vietnam, as at end-2001
120
Table 4.16
:
Summary of scales for twelve constructs in the model
126
Table 5.1
:
Sample structure by industry
130
vi
Table 5.2
:
IJV’s age
130
Table 5.3
:
Sample structure by foreign partner countries
131
Table 5.4
:
Sample structure by company sales
131
Table 5.5
:
Number of foreign marketing staff in IJVs
132
Table 5.6
:
Number of local marketing staff in IJVs
132
Table 5.7
:
Summary of EFA and CFA for scale assessment and
validation
136
Table 5.8
:
EFA and reliability test results
140
Table 5.9
:
Results of unidimensionality and reliability test – refined
scale
142
Table 5.10
:
Result of joint factor analysis for 12 scales
145
Table 5.11
:
Factor correlation matrix – 12 constructs
146
Table 5.12
:
CFA results of models not requiring any modification
152
Table 5.13
:
Results of CFA for individual scales – Refined scales
156
Table 5.14
:
Assessment of discriminant validity for selected pairs of
constructs
159
Table 5.15
:
Indicators for 12 constructs in the full measurement model
163
Table 5.16
:
Standardized correlation between constructs with 95%
confidence interval
164
Table 5.17
:
Summary of properties of the 12 scales
166
Table 6.1
:
Fit indexes for the theoretical model
168
Table 6.2
:
Modification indexes for the theoretical model
171
Table 6.3
:
Fit indexes for the modified model
173
Table 6.4
:
Modification indexes for the modified model
175
Table 6.5
:
Factor loadings of indicators on respective constructs
176
Table 6.6
:
Selected AMOS text outputs for the modified model
177
Table 6.7
:
Summary of hypothesis test statistics
179
vii
LIST OF FIGURES
Page
Figure 2.1
:
The inter-connection of organizational learning
17
Figure 2.2
:
An explanatory model of organizational learning
26
Figure 2.3
:
Knowledge management in JV
47
Figure 3.1
:
The conceptual framework
70
Figure 6.1
:
SEM results for the theoretical model
170
Figure 6.2
:
SEM results for the modified model
174
viii
ABBREVIATIONS
AMOS
:
Analysis of Moment Structure
CFA
:
Confirmatory Factor Analysis
CFI
:
Comparative Fit Index
dF
:
Degrees of Freedom
EFA
:
Exploratory Factor Analysis
FDI
:
Foreign Direct Investment
GFI
:
Goodness-of-fit Index
HOELTER :
Hoelter’s index
IJV
:
International Joint Venture
JV
:
Joint Venture
KMO
:
Kaiser-Meyer-Olkin
MBA
:
Master of Business Administration
MI
:
Modification Indices
ML
:
Maximum Likelihood
NFI
:
Normed Fit Index
RMSEA
:
Root Mean Square Error Approximation
SE
:
Standard Error
SEM
:
Structural Equation Model
SPSS
:
Statistic Packages for Social Sciences
TLI
:
Tucker-Lewis Index
ix
ABSTRACT
The research stream on interpartner learning in international strategic alliances
has evolved in recent years. Although several research problems have been
addressed, there remain gaps in the literature about the facilitators and outcomes
of knowledge acquisition in international joint ventures. To bridge these gaps,
this research has two main objectives. Firstly, it identifies various antecedents
and tests their effects on the acquisition of marketing know-how by the local
partner from the foreign partner. Secondly, it investigates how the acquired
marketing know-how impacts on the learning outcomes in an IJV.
Based on the literature review, a theoretical model and hypotheses have been
developed. Data was collected from 219 IJVs through a survey in Vietnam. It
was first used to assess and refine the measurement scales through exploratory
and confirmatory factor analyses. Then, it was used to validate the model through
the structural equation modeling with the partial disaggregation technique. Based
on the statistics derived, tests of hypotheses were undertaken and the results were
discussed.
The findings of this study show the effects of the eight antecedents on the
acquisition of tacit and explicit forms of marketing know-how. Learning intent,
learning capability and teamwork facilitate the acquisition of both forms.
Relationship strength, cultural distance and knowledge protectiveness have
effects only on the tacit form; while IJV management commitment and partner
assistance have effects only on the explicit form of marketing know-how
acquisition. Interrelations have also been found between teamwork and
relationship strength; and between learning intent and learning capability.
Furthermore, marketing competence and marketing dynamism are significantly
influenced by the tacit and explicit marketing know-how acquired. Marketing
competence is more sensitive to tacit know-how as compared to explicit knowhow. It also contributes significantly to explain the changes in marketing
dynamism.
This research has bridged the research gaps in several ways. First, it focuses on
marketing know-how, an important but less researched type of knowledge.
x
Second, it provides an integrative conceptual model for the topic in which the
knowledge investigated is under two distinct forms, i.e. explicit and tacit. It helps
explain and predict the separate effects of each antecedent on the acquisition of
explicit and tacit marketing know-how, and the different effects of these two
forms on the learning outcomes. This research has also answered the call for
empirical studies to provide statistical evidence with respect to interorganizational learning in the international arena. It contributes new measurement
scales as well as suggests effective ways of acquiring marketing knowledge from
foreign partners in an IJV.
xi
CHAPTER 1
INTRODUCTION
1.1. BACKGROUND
In recent years, the knowledge-based view of the firm has become an emerging area
of theory and practice (Bollinger and Smith, 2001; Kale et al., 2000; Grant, 1996;
Nonaka, 1994; Kogut and Zander, 1992). In this view, organizational knowledge is
considered as one of the strategic assets that are critical for a firm’s ability to
innovate and compete (Michalisin et al., 1997). It is consequently important that
knowledge must be managed properly if the firm is to be successful. Knowledge
management includes a variety of activities including the acquisition, organization,
dissemination and exploitation of knowledge to create added value to the firm (Gupta
and Aronson, 2000). For the acquisition of knowledge, one of the possible sources is
through organizational learning.
Organizational learning and its twin concept of learning organization represent one
of the important fields in organization theory as reflected by Appelbaum and
Reichart (1997):
“This century has witnessed the emergence of three quite different
organizational paradigms. In the early part of the century Max Weber described
the nature of the bureaucratic organization, organizations that focus on
rationality and efficiency. Then in the mid – 1950’s, Peter Drucker introduced
the concept of the performance-based organization, organizations which
promise results and effectiveness. Now, towards the end of the century with the
release of his book, The fifth discipline: The art and practice of the learning
organization, Peter Senge has helped popularize the concept of the learning
organization, organizations continually striving to adapt to an ever changing
environment” (p. 225).
Organizational learning occurs when the knowledge learned by an individual is
transferred across unit boundaries to others that can benefit the organization as a
whole (Hamel, 1991). Within an organization, learning involves different levels
1
including individual learning, team learning and organizational learning (Solingen et
al., 2000). Moreover, organizational learning can expand further to capture interorganizational learning which focuses on the flow of knowledge across organization
boundaries in the cases of strategic alliances (Tiemessen et al., 1997).
Strategic alliance refers to a long-term business arrangement between firms. It is
based on the view that a firm is a portfolio of core competencies and value creating
disciplines. As competencies are not distributed equally among firms, many have
turned to cooperate with other partners as a strategic response to the increasing
competitive business world (Hamel, 1991). The emergence of strategic alliances
marks a new era of alliance capitalism which is replacing the earlier prevailing
hierarchical capitalism (Sharma, 1998). In the research world, this phenomenon has
drawn the attention of researchers in various fields. Over the last decades, several
researches on various aspects of alliances have been published. Some scholars have
reviewed literature and suggested taxonomies of recent strategic alliance researches
(Gulati, 1999; Koza and Lewin, 1998). They found that establishing strategic alliance
relationships provides the partner firms with several benefits including opportunities
to learn new knowledge from partners (Varadjaran and Cunningham, 1995; GomesCassers, 1996; Kogut, 1988; Sharma, 1983; Baum and Oliver, 1991; Gulati, 1995).
The literature on learning in strategic alliances, or in joint ventures in particular, has
emerged from the development of two contemporary management thoughts: strategic
alliances and organizational learning. It is realized that many firms today are seizing
the opportunity to acquire new knowledge through cross-national collaborative
arrangements and to transform their core competencies. Organizational learning has
become a critical imperative for global strategic effectiveness in the 1990s (Tsang,
1999). The ability of firms to seek, absorb, and transfer knowledge from their
collaborative arrangements back to the parent companies becomes a crucial skill
(Osland and Yaprak, 1995). This leads to the recommendation that a strategic
alliance should be regarded as a learning battlefield (Hamel, 1991). The term
“coopetition” (Zineldin, 1998; Loebecke et al., 1999; Brandenburger and Nalebuff,
1996) and “competitive collaboration” (Hamel, 1991) are used to describe such
interpartner relationships.
One among various research lines within this field is about learning and knowledge
acquisition through joint ventures between firms in different countries.
2
1.2. RESEARCH PROBLEMS AND GAPS
As mentioned earlier, the growing interest in organizational learning and in
international strategic alliances has evolved into a distinct line of research stream.
This stream has investigated into several research problems of which five major
issues are featured as follows:
1.2.1. The process of knowledge acquisition in strategic alliances
Questions being raised include how knowledge is acquired or transferred across
partner firms and what factors facilitate (or inhibit) the process of acquisition or
transfer. In this regard, Makhija and Ganesh (1997) conceded that much research
attention had been directed to trends in alliance formation, determinants of
cooperation, forms of collaborations, and alliance outcomes. The processes through
which inter-partner learning takes place in a joint venture setting have, however,
received limited attention. Recently, a number of authors have attempted to tackle
these problems (Lei et al., 1997; Baughn et al., 1997; Choice and Lee, 1997; Si and
Bruton, 1999; Sharma, 1998, Mohr and Sengupta, 2002; Lyles and Salk, 1996;
Simonin 1999b; Dussauge et al., 2000; Love and Gunasekaran, 1999; Bresman et al.,
1999). Particularly among these authors, Tiemessen et al (1997) proposed a general
knowledge management framework to capture key components and their roles in the
process of organizational learning in strategic alliances. The framework flows from
conditions to structure and process, then to outcomes. They provided a general
analysis of different levels and activities of learning at different learning stages. To a
more specific level, Inkpen (2000) developed a framework to explain the antecedents
of knowledge acquisition from partners. The proposed facilitating factors include
partner knowledge accessibility, partner openness, learning connection, knowledge
acquisition effectiveness, knowledge attributes. Other facilitating factors have also
been suggested by a number of authors, such as learning intent, type of knowledge,
duration and governance structure (Mohr and Sengupta, 2002), knowledge ambiguity
(Simonin, 1999b), partner assistance, and cultural distances (Lyles et al., 1999).
However, a careful review of the literature reveals that most of the mentioned studies
confined themselves to theoretical analyses and propositions (Tiemessen et al., 1997;
Inkpen, 2000; Mohr and Sengupta, 2002). Only a few have proceeded one further
step to empirically test their hypotheses, and of those who did, many have not been
3
successful (Lyles et al., 1999; Simonin, 1999b). Moreover, the suggestion of several
facilitating factors by various authors has led to a demand for studies that would
examine these factors together in a systematic way (Appelbaum and Reichart, 1998).
To study these factors simultaneously within a single framework would help identify
their relative importance as well as the possible interrelationships among them.
1.2.2. The tacitness of knowledge
Authors have been concerned with the transferability of different forms of
knowledge with regard to their tacitness. Their arguments are based on the notion
that some form of knowledge may be more easily acquired than others. Explicit
knowledge such as product technologies, physical distribution methods, and
promotion techniques may be easily transferred interorganizationally. However, tacit
knowledge such as intangible relational skills is more difficult to absorb and share.
For acquiring this form of knowledge, longer-term partnerships and proper
mechanisms must be developed (Loebecke et al., 1999; Osland and Yaprak, 1995).
The notion of different mechanisms required for transferring tacit and explicit
knowledge across partners would lead to the argument that factors facilitating the
acquisition of explicit knowledge may not have the same impact on the acquisition of
tacit knowledge and vice versa. To address this question would require an
investigation of both tacit and explicit knowledge as two distinct constructs within
the same model. To the author’s knowledge, no such research has yet been
undertaken.
The review of the extant literature shows that researchers deal with this issue in
different ways. Some studies of knowledge acquisition in international strategic
alliances examined knowledge acquisition in a general sense i.e. without paying
attention to their tacitness (Lyles and Salk, 1996; Lyles et al., 1999; Hanvanich,
2002; Luo and Peng, 1999). Some treated knowledge as having a single level of
tacitness, or considered knowledge tacitness only as a moderating variable or an
antecedent of knowledge transfer (Hanvanich, 2002; Griffith et al., 2001; Simonin,
1999b).
There have been some authors who distinguished between the acquisition of tacit and
explicit knowledge. But they tended to focus only on tacit knowledge. For example,
Cavusgil et al. (2003) investigated how firms acquire tacit knowledge from partners
4
and how tacit knowledge affects firms’ innovation. Moon (1999) studied tacit
knowledge and found that acquiring tacit knowledge from partners depends on the
partners’ needs and ability to learn.
Many authors accept that the acquisition of both tacit and explicit knowledge across
partners is still relatively unexplored and not fully understood (Zack, 1999; Herrgard,
2000; Augier and Vendelo, 1999; Cavusgil et al., 2003).
1.2.3. The type of knowledge being transferred
Various types of knowledge have been addressed in the context of strategic alliances,
ranging from organization-specific, industry-specific, and market knowledge (Choice
and Lee, 1997). Some researchers investigated the acquisition of industry-specific
knowledge such as technology or manufacturing know-how (Mowery et al., 1996;
Lam, 1997; Bresman et al., 1999), whereas others were interested in market-specific
knowledge such as business environment knowledge and product-market knowledge
(Geppert and Clark, 2003; Griffith et al., 2001). Also some authors have studied the
transfer of organization-specific knowledge such as managerial skills (Wong et al.,
2002). However, the acquisition of marketing knowledge has been relatively less
researched (Simonin, 1999b). As remarked by Wong et al. (2002) in a study of IJVs
in China: “The literature is silent on the transfer to the international joint ventures of
strategic management expertise, a specific type of non-technological know-how.
However, interest in the possible benefit of such transfers is growing” (p.2).
Moreover, studies of knowledge transfer turn almost invariably to technology
transfer when empirical investigation is in order (Simonin, 1999b). The literature,
particularly on the empirical side, has generally dealt with the technology or
technical capability viewpoint (Appleyard, 1996; Hagedoorn and Schakenraad, 1994;
Zander and Kogut, 1995). Indeed, there has been a growing interest on the
acquisition of managerial knowledge in international strategic alliances in developing
countries (Si and Bruton, 1999; Tsang, 2001). Some scholars have recently studied
managerial learning in international joint ventures in China (Si and Bruton, 1999;
Luo and Peng, 1999; Liu and Vince, 1999) but the focus is not on the facilitators of
knowledge acquisition. By its nature, managerial knowledge is different from
technological knowledge in various features related to its transferability such as
codifiability, teachability, system dependence, complexity and product observability
5
(Zander and Kogut, 1995). It is, therefore, thought that factors facilitating the
acquisition of managerial knowledge (e.g. marketing knowledge) are different from
those of technological knowledge and are worthy for scholarly inquiries.
1.2.4. The outcome of learning and knowledge acquisition
The organizational learning literature shows that the outcome of learning is a
debatable issue (Easterby-Smith and Araujo, 1999). This issue becomes more
complicated in the studies of learning and knowledge acquisition in IJVs because of
its collaborative - competitive nature. (Dussauge et al., 2000; Tiemessen et al. 1997;
Levinson and Asahi, 1995; Lyles et al., 1999; Cavusgil et al., 2003).
Due to its complicated nature, this research issue has received less attention from
researchers. The very few studies found in the literature have addressed this issue in
different ways. Some authors used alliance termination as an indicator of alliance
learning (Dussauge et al., 2000). Others used multiple indicators to measure learning
from partners (Lyles et al, 1999). Cavusgil et al (2003) measured the linkage between
tacit knowledge acquired from partners and the firm’s innovation.
Given the separate investigation of tacit and explicit knowledge, it follows that
proper measures are in need for evaluating the direct outcome as a representation of
the effectiveness of learning from partners. The measures would necessarily be able
to differentiate the contribution of each form of knowledge (i.e. tacit versus explicit
knowledge) to the learning outcomes in IJVs.
1.2.5. Conceptual versus empirical research
Easterby-Smith and Araujo (1999), in a comprehensive review of literature on
organizational learning stress that, in contrast with the abundance of conceptual
work, only a limited amount of large sample empirical work has focused on the role
of knowledge in international strategic alliances. Starting with organizational
learning, Fiol (1994) noted that there is a clear need for hypothesis development and
testing. Likewise, Simonin (1999b) further stated that empirical research on the
interpartner learning and knowledge acquisition had been hampered by the
widespread reliance on anecdotes and assertion, rather than statistical evidence.
Therefore, there is a high demand on research using large sample of empirical data to
find statistical evidence supporting various theoretical propositions about interpartner
learning in international strategic alliances (Mohr and Sengupta, 2002).
6
1.3. RESEARCH OBJECTIVES
The identification of the above mentioned research problems and gaps opens
opportunities for scholarly inquiries in the research stream of organizational learning
in international strategic alliances. Within this stream, the current research attempts
to address the following issues. First, it identifies key factors influencing the
acquisition of different forms of knowledge from the foreign partner in international
joint ventures. Secondly, it investigates how the knowledge acquired from the
foreign partner influences the learning outcomes within the context of international
joint ventures.
Particularly, the objectives of the current research are:
̇
To review literature related to the research area in order to identify potential
antecedent factors that facilitate or inhibit the acquisition of tacit and explicit
marketing know-how from the foreign partner in international joint ventures.
̇
To develop a theoretical model and provide relevant arguments leading to
testable hypotheses on the different impacts of each antecedent factor on the
acquisition of tacit and explicit marketing know-how.
̇
To propose measures representing the direct outcomes of the knowledge
acquisition process and investigate the relationships between explicit and tacit
marketing know-how acquired from partners and the proposed measures of
learning outcomes.
̇
To test the theoretical model and hypotheses using empirical data collected by
means of a survey conducted in Vietnam.
By addressing these issues, the current research would contribute to the literature in
various ways. First, it investigates tacit and explicit know-how as two separate
constructs within a single model. The separation of these two focal constructs
enables the identification of the facilitators of each form of the marketing know-how
acquired by the local partner. Moreover, it helps find the contribution of each form of
marketing know-how to the enhancement of learning outcomes. Besides, the use of
large sample survey data would bring about the empirical evidence to reinforce the
understanding of the phenomenon under study.
7
1.4. METHODOLOGY
On the epistemological point of view, the current research follows a positivist
paradigm (Trochim, 2002). It adopts a methodology which is based on a deductive
approach (Neuman, 2000). It first reviews literature related to organizational
learning, international joint venture (IJV) and learning in the joint venture. The
review of literature and logical reasoning process help develop a theoretical model
depicting a relational picture of twelve constructs of interest. Based on this model
and theoretical arguments, hypotheses on the relationships between constructs are
proposed. Then, the model and hypotheses are tested against empirical data with a
sample of 219 cases collected by a survey of international joint ventures in Vietnam.
The main statistical techniques for data analysis are the exploratory factor analysis
and the two-step approach in the Structural Equation Modeling (SEM) with the use
of partial disaggregation technique. The analysis process is carried out with the use
of SPSS 10.0 and AMOS 5.0 computer software packages.
1.5. RESEARCH DELIMITATIONS
To set the scope in relation to the generalizability of the current research findings, the
following four delimitations should be taken as the specific research boundaries.
1.5.1. Marketing know-how
As mentioned in section 1.2.3, researches in the field have paid much attention to the
knowledge of technology and manufacturing. This is particularly true when
reviewing empirical researches. In contrast, the current research is interested in the
study of management knowledge with particular focus on marketing know-how. This
is not only to respond to the research gap described earlier, but also to emphasize the
emerging learning needs of firms in developing countries when partnering with firms
emanating from more developed countries (Tsang, 2001; Danis and Parkhe, 2002).
Moreover, the selection of marketing know-how as a specific focus in the current
research is based on the notion that learning of management knowledge is much
more complicated than that of technology knowledge because management
knowledge is culturally and socially impeded (Wong et al., 2002). In other words,
this type of knowledge is highly system dependent and less product observable
(Zander and Kogut, 1995).
8
1.5.2. IJV in developing countries
Although international strategic alliances exist under several forms, the current
research focuses only on international joint ventures in developing countries. Tsang
(2001) points out that during the past decade or so, thousands of Western companies
have established joint ventures and other forms of strategic alliances in transitional
economies such as China, Russia, and Eastern Europe. The governments of these
countries want to import modern technology by collaborating with Western
companies, which try to take advantage of the low labor cost and sizable market of
these economies.
Particularly, the current research selects Vietnam as a country for observation and
empirical testing. Vietnam is a developing and transitional economy where learning
from partners is one of the partnering objectives in international joint ventures
(Swierczek and Vo, 1997). Indeed, the term marketing only exists in Vietnam after
the Doi moi (Reform) policy in 1987 when the country shifted from a centrally
planned economy to a market economy. Therefore, acquiring marketing knowledge
is an urgent need for local firms when partnering with firms from foreign countries.
The selection of Vietnam provides a good research setting for the observation of
marketing knowledge acquisition.
1.5.3. One-way knowledge acquisition
Partnering firms can learn different types of knowledge in an IJV including learning
the partner’s knowledge and learning the alliance’s knowledge. However, the current
research sets aside the learning of alliance knowledge such as knowledge on how to
form and manage an alliance effectively or learning of newly created knowledge
through collaborative R&D in the alliance (Inkpen, 2000; Tsang, 2001).
Additionally, the current research focuses particularly on the acquisition of
knowledge from the foreign partner. Moreover, it is only interested in the
examination of knowledge acquisition in international joint ventures in a developing
country. This is particularly relevant in joint ventures formed between developing
countries and developed countries where learning is largely a one-way process (Liu
and Vince, 1999; Danis and Parkhe, 2002).
9
1.5.4. The first phase of interpartner knowledge acquisition
The current research adopts the general framework of knowledge management in
strategic alliances proposed by Tiemessen et al. (1997). Accordingly, the acquisition
of knowledge from IJV partners is a multiple-phase process including transfer,
transformation and harvesting. Each phase would be strongly associated with some
salient facilitating factors (Tiemessen et al., 1997; Inkpen, 2000). However, the
current research focuses only on the first phase which is the transfer of know-how
from foreign to local staff within the IJV. That is, the “acquirers” of marketing
know-how are those local staff working in the IJV. The process of transferring the
acquired marketing know-how back to the local parent is beyond the scope of this
current research.
1.6. DEFINITIONS OF KEY TERMS
For clarification, this section presents the definitions of key terms adopted in the
current research. Further conceptualization and explanations are to be addressed in
Chapter 2 and Chapter 3.
1.6.1. Knowledge acquisition
The current research defines knowledge acquisition as the process and amount of
knowledge that is moved from a foreign to a local partner in an IJV. This definition
bears the same implication as the definition of Tiemessen et al. (1997), who refers
the process to the term knowledge transfer in international joint ventures which is
“the movement of knowledge between parent firms” (p.387). In order to emphasize
the learning process from the learner’s point of view (i.e. the local partner), the
current research adopts the term knowledge acquisition (Inkpen, 2000; Tsang, 2002).
However, for conforming to the extant literature, the term knowledge transfer or
learning from partner is still used interchangeably with the term knowledge
acquisition.
1.6.2. Marketing know-how
Marketing know-how is defined as the procedural knowledge which is understood as
knowing how to do something in marketing (Hackley, 1999). It consists of problemsolving procedures in marketing. Examples of marketing know-how include
10
professional expertise to solve problems such as how to gather and select relevant
information from the business environment to make predictions about market
opportunities; how to be innovative at a strategic level seeking new product
opportunities; how to optimize the marketing mix to achieve stated objectives; and so
forth. Based on the classification of knowledge proposed by Polanyi (1958),
marketing know-how is further classified into tacit marketing know-how and explicit
marketing know-how.
1.6.3. Tacit marketing know-how
Tacit marketing know-how refers to those particulars of know-how in marketing
which is intuitive, unarticulated, and nonverbalized or even non-verbalizable
(Polanyi, 1958). It is usually omitted, to varying degrees, from abstracted theoretical
descriptions, yet upon which the successful accomplishment of practical marketing
action depends (Hackley, 1999). In their examples of tacit marketing know-how,
Baughn et al. (1997) point out that know-how learned by experiencing in marketing a
new product or controlling a distribution system may be embedded in the individuals
and social system of the organization. Simonin (1999b) showed that it was rather
difficult to think of an easily-codifiable advertising know-how, explicit success
formulas for product launches, or clear, replicable blueprints for international market
expansions.
1.6.4. Explicit marketing know-how
In contrast to tacit marketing know-how, explicit marketing know-how refers to
those particulars of know-how in marketing which are more objective, rational and
technical (Hackley, 1999). It can be specified verbally or in writing, computer
programs, patents, drawings or the like. Consequently, explicit knowledge is
systematic and easily communicated in the form of hard data or codified procedures.
It is noted that there are two different views of the tacitness of a particular knowledge
body (i.e. technology, manufacturing, marketing, etc.). The first views the whole
body of knowledge can fit into one specific point in the tacit-explicit continuum
(Simonin, 1999a,b; Kogut and Zander, 1993, Cavusgil et al., 2003). In contrast, the
current research adopts the second view of Hackley (1999) who advocates that the
whole body of marketing know-how comprises many particles. Some particles are
tacit and others are explicit. As a result, the body of marketing know-how transferred
11
from foreign to local partner is a mix of two different parts. Consequently, under the
term marketing know-how, the analysis and framework presented in the current
research goes into further details. This is the background for discussions related to
the transfer of each form, the complementary roles of the two forms; value of each
form to local partner and to learning outcomes.
1.6.5. International joint venture (IJV)
A joint venture is defined as an organizational form where at least two companies
pool resources to create a new, separate organization (Anderson, 1990). It is a
specific form of strategic alliance in which each partner has a share of resources and
each thereby may expect an appropriate allocation of dividend as compensation,
representation of the joint venture’s board of directors, and active participation in the
decision-making activities of the venture (Harrigan, 1985). Based on the geographic
location, joint ventures can be classified as international or domestic. A joint venture
is termed international where at least one of the parties (or parents) is based outside
the country where the venture is taking place or if the joint venture is being
administered on a wide level in more than one country (Geringer and Hebert, 1989;
Meschi, 1997; Llaneza and Canal, 1998).
1.7. OUTLINE OF THE THESIS
The thesis is organized as follows. This first chapter, Chapter 1, introduces the
research problems and objectives. It then provides a brief description of the research
methodology and sets out the delimitations and definitions of key terms being used
throughout the research.
Chapter 2 provides a background review of literature and identifies research gaps in
the field. Its first section introduces organization learning, theoretical perspectives to
study organizational learning, how an organization learns and learning facilitators.
The second section presents a review of the essential issues on international joint
ventures (IJVs). It starts with the term strategic alliance, and then goes to
international joint venture including its definition, its forms, and the motives of
partners and business advantages of IJVs. The third section addresses issues relating
to knowledge transfer in the context of international joint ventures, especially IJVs in
developing countries. The last section synthesizes previous studies about the
12
facilitators of knowledge transfer. It then addresses how the current research fits in
these research gaps.
Chapter 3 goes to the specific domain of the current study which focuses on the
acquisition of explicit and tacit marketing know-how from foreign partner in IJVs. It
discusses the concept of marketing know-how and differentiates between explicit and
tacit marketing know-how with respect to their importance in the marketing practice
and their ease of acquisition. It then develops a theoretical model and presents the
arguments which lead to twelve testable hypotheses.
Chapter 4 presents the details of the research methodology in regard to the empirical
part of the current research. It describes and explains how constructs in the
theoretical model are operationalized and measured. It then proceeds to explain why
Vietnam is selected as a specific place for empirical observation and to provide a
brief introduction of Vietnam economy and its IJVs. The succeeding section
discusses issues related to the unit of analysis and sampling. The chapter ends with a
description of the data collection instrument and procedure.
Chapter 5 presents the assessment and refinement of the measurement scales based
on the data set of 219 cases collected for this study. The chapter first describes key
characteristics of the sample. It then presents the results of the exploratory factor
analysis of the measurement scales. The final part of the chapter discusses the results
of the confirmatory factor analysis (CFA) in validating the measures of the
constructs used in this study.
Chapter 6 presents the assessment and modification of the proposed theoretical
model and hypotheses described in Chapter 3. In so doing, the structural equation
modeling (SEM) is employed. Then the standardized regression coefficients derived
from the final model provide the statistical basis for hypothesis testing.
In the last chapter, Chapter 7, the findings are summarized and conclusions are
drawn. Following the introductory section, a summary of main findings is presented.
Then the theoretical and methodological contributions and the managerial
implications of the research are outlined. It is followed by a discussion of the
research limitations and suggested directions for further research.
13
CHAPTER 2
LITERATURE REVIEW
2.1. INTRODUCTION
Given the research questions and objectives, it is realized that the topic under study
covers a number of core concepts and issues that need to be clarified. This chapter
provides a background review of the literature that is relevant to these issues. After
this introductory section, the rest of this chapter consists of four sections.
Section 2.2 reviews the term organizational learning which is the major theme of the
current research. It introduces the knowledge concept and its role as a strategic asset
within a firm. It then presents various terms such as organization learning, learning
organization, theoretical approaches to study organizational learning, how an
organization learns and learning facilitators. This section ends up with a summary of
the debates and issues on organizational learning that deserve further investigation.
Section 2.3 presents a review of the literature on international joint ventures (IJV). It
begins with an introduction to strategic alliance and its nature. The section then goes
to introduce international joint venture, a form of strategic alliance which is of
specific interest in this research. A definition of joint venture, its various forms and
motives of partners of IJV are presented in this section.
Section 2.4 connects the two subject matters presented in sections 2.2 and 2.3. It
addresses issues relating to organizational learning and knowledge acquisition in the
context of international joint ventures, especially international joint ventures between
firms from more developed countries and firms in developing countries. It goes into
the details about the pattern and framework of knowledge transfer in international
joint ventures.
The last section, section 2.5 focuses specifically on the review and synthesis of
previous studies on the facilitators of interpartner learning and knowledge
acquisition. It then identifies research gaps in the field and addresses how the current
research fills in these research gaps.
14
2.2. ORGANIZATIONAL LEARNING
2.2.1. Knowledge – A firm’s strategic asset
Knowledge is defined as the understanding, awareness, or familiarity acquired
through study, investigation, observation, or experience over the course of time. It is
the interpretation of information based on personal experiences, skills, and
competencies (Grant, 1997). Other definitions of the term can also be found in the
literature. For example, Nonaka (1994) views knowledge as an organized flow of
information that is anchored in the commitment and beliefs of its holders; or O’Dell
(in Elliot, 1996) refers knowledge to information that has value.
To an organization, knowledge resides in all the organization’s sources, both internal
and external ones. Accumulated over time, organizational knowledge enables firms
to attain deeper levels of understanding, perception, and all characteristics of wisdom
(Grant, 1997). Grant suggests that organizational knowledge encompasses both
common knowledge and specialized knowledge. Common knowledge comprises
those elements of the knowledge common to all or the majority of the organizational
members: it is the intersection of the individuals’ knowledge sets. Beyond common
knowledge, each member of an organization possesses certain specialized knowledge
that is difficult to share and also needs not to share with other members. It is the
common knowledge including language that is an important vehicle to facilitate the
transferring or dissemination of knowledge among the people in the firm.
Zander and Kogut (1995) offered another view by identifying five dimensions of
organizational knowledge. These dimensions are 1) Codifiability: the degree to
which knowledge can be encoded, even if the individual operator does not have the
facility to understand it. 2) Teachability: the extent to which workers can be trained
in schools or on the job; it reflects the training of individual skills. 3) Complexity:
the inherent variations in combining different kinds of competencies; knowledge, no
matter the education of the worker, is more complex when it draws upon distinct and
multiple kinds of competencies. 4) System dependence: the degree to which a
capability is dependent on many different experienced people for its production and
5) Product observability: the degree to which capable competitors can copy the
manufacturing capability, because they are able to manufacture the innovation once
they have understood the functions of the product.
15
On the strategic point of view, Michalisin et al. (1997) argue that organizational
knowledge is a firm’s strategic asset to develop and sustain its competitive
advantage. It is a strategic asset because it possesses four characteristics: valuable,
rare, inimitable, and non-substitutable. Valuable represents acquiring new knowledge
to remain competitive and viable. It is rare since it depends on the knowledge and
experiences of current and past employees, and it is built on specific organizational
prior knowledge. It is inimitable because organizational knowledge is based on
personal and group interpretation of information, on the unique past history of the
firm. The synergy of specific groups or organizations cannot be replicated; therefore,
their distinctive competence is nonsubstitutable. In the same view, Prusak (1996)
emphasizes that there is no sustainable advantage other than what a firm knows, how
it can utilize what it knows, and how fast it can learn something new.
Being asserted that knowledge is a firm’s strategic asset, it is consequently important
that knowledge must be managed properly if the firm is to be successful. Knowledge
management includes a variety of activities for acquisition, organization,
dissemination and exploitation of knowledge to create added value to the firm (Gupta
and Aronson, 2000). For the acquisition of knowledge, one of the possible sources is
through organizational learning. In essence, organizational learning encompasses
individual learning but not merely so (Kim, 1993; Easterby-Smith, 1997). The
literature on organizational learning shows that this is a complex process
encompassing many different activities which is discussed in the next section.
2.2.2. The concept of organizational learning
According to Easterby-Smith and Araujo (1999), the term organizational learning has
existed in the literature at least since 1960’s by authors such as Argyris (1964),
Cangelosi and Dill (1965), Cyert and March (1963), and so on. However, after more
than thirty years, the organizational learning field has yet to achieve a coherent and
comprehensive view (Tiemessen et al., 1997; Crossan and Inkpen, 1995). The
different views exist right at the definition of the term. As noted by Tsang (1999):
“At the moment definitions are as many as there are writers on the subject” (p. 213).
It can be recognized that the term has been defined from three different views. The
first view emphasizes organizational learning as a process. Authors of this group
view learning as cognition or information processing. They offer definitions such as:
organizational learning is the development of insights, knowledge and associations
16
between past actions, the effectiveness of those actions, and the future actions
(Appelbaum and Goransson, 1997). Tsang (1999) defined organizational learning as
the process by which the organizational knowledge base is developed and shaped.
Robey et al. (2000) referred to organizational learning as an organizational process,
both intentional and unintentional, enabling the acquisition of, access to, and revision
of organizational memory.
In contrast, the second group emphasizes the outcomes of organizational learning i.e.
change of behavior, improvement of organizational effectiveness. For example,
organizational learning was defined as increasing an organization’s capacity to take
effective action (Kim, 1993). Reynolds and Ablett (1998) referred to organizational
learning as a change in the behavior of individuals or groups within an organization,
leading to changes in the behavior of the organization itself. Probst et al. (1997) saw
it as changes in the organizations’ knowledge and value base, leading to improved
problem solving ability and capacity for action. Fiol and Lyles (1985) defined it as
the improving actions through better knowledge and understanding.
Learning
Process
Results in
Knowledge/
skill
Create the
change of
Behavior/
Action
Figure 2.1: The inter-connection of organizational learning components
(Source: Adapted from Hill, 1996)
The third group integrates both views by offering definitions that link the learning
process and it outcomes. For example, Huber (1991) described that an entity learns
if, through its processing of information, the range of its potential behaviors is
changed or an organization learns if any of its units acquires knowledge that it
recognizes as potentially useful to the organization. Buckler (1998) considered
organizational learning as a process that result in changed behavior in ways that lead
to improved performance. According to Sadler-Smith et al. (2001), organizational
learning is the development or acquisition of new knowledge or skills in response to
internal or external stimuli that leads to a more or less permanent change in
17
collective behavior, enhancing organizational effectiveness. Figure 2.1 presents the
integrative frame where three components of interest are linked together.
Accordingly, organizational learning is an iterative process. It involves changes in
the individual and organization. These changes are expressed in terms of a
continuous, and unprompted shift in knowledge, attitudes, skills and behaviors. It
follows that the introduction of timely and appropriate interventions to the process
inputs would enhance the learning outcomes (Hill, 1996).
In addition to the definition of organizational learning, another important issue in the
field is the subject of learning process as a “learner”, individual or collective
learning. To this end, Simon (1991) points out that an organization can only learn
through its members as “all learning takes place inside individual human heads”
(p.125). Yet it would be simplistic to think that organizational learning is the sum of
each member’s learning because lessons learned by a member of an organization
have to be shared by other members and be institutionalized before the lessons can
become part of the organizational knowledge base (Tsang, 1999). Indeed, this issue
was posed earlier by Argyris and Schon (1978) as the main dilemma shared by all
who tackle this issue:
“…There is something paradoxical here. Organizations are not merely
collection of individuals, yet there are no organizations without such collection.
Similarly, organizational learning is not merely individual learning, yet
organizations learn only through the experience and actions of individuals.
What, then, are we to make of organizational learning? What is an organization
that may learn?” (p.9)
Bent et al. (1999) identify that one group of writers such as Senge (1990), Dixon
(1994), and Argyris and Schon (1978; 1996) takes the approach that it is not
meaningful to think of organizational learning. They tend to eschew the notion that
organizations can learn, and look instead at organizational structures and systems
that can hinder, or help, individuals to learn within organizations. Authors such as
Pedler et al. (1991) and Appelbaum and Reichart (1998) expand this perspective and
describe a range of principles and techniques to stimulate individual learning within
an organizational setting. In contrast, Hedberg (1981) and Walsh and Ungson (1991)
focus on aspects of the organizational setting, pointing out that organizational
systems, procedures and structural and cultural artifacts are subject to changes and
18
continue to exist long after many of the individuals involved have left the
organization. The continued influence of systems, structures, cultures and artifacts
can thus act like the organization's memory. Van den Broek (1995) argues that this is
in fact the case: “Learning is people's work, but individual repositories will be
transferred into organizational repositories. These repositories are not dependent upon
individuals. They follow their own lead and in turn influence the learning and
subsequent behavior of individuals'' (p.27).
Some theorists have attempted to bridge this division by linking the two theoretical
streams of individual versus organizational learning. Solingen et al. (2000) suggest that
organizational learning encompasses different levels of learning: individual learning,
team learning and organizational learning. In individual learning, each person takes
responsibility for his or her own learning, has personal learning plans, understands his or
her own learning style, chooses and utilizes different learning options and knows how to
use others, and help others, in the learning process. With respect to team learning, teams
or working groups utilize the capability of each member for the benefit of all. All
members frequently learn and unlearn together to share a common approach, support
each other in individual learning objectives and help other teams and learn from each
other. Organizational learning occurs when new knowledge learned by individual is
transferred across unit boundaries to others that can benefit the organization as a whole
(Hamel, 1991). Tiemessen et al. (1997) expand one further level to capture interorganizational learning which focuses on the flow of knowledge across organization
boundaries in the cases of strategic alliances between firms.
Taking all the views mentioned above, coupled with the research coverage, the
current research follows the third view mentioned earlier, which tries to capture both
learning process and learning outcomes at both individual and collective levels.
Taking various perspectives together provides a more comprehensive understanding
of organizational learning than any view by itself. There are advantages to be derived
from theoretical plurality (Bell et al., 2002). This integrative view helps understand
the process of learning of individuals as well as groups/organizations. It also helps
explain the links between acquired knowledge and its potential outcomes.
2.2.3. Organizational learning and learning organization
Together with organizational learning, the term learning organization has appeared in
the literature as its twin concept. Garvin (1993) defines “a learning organization is an
19
organization skilled at creating, acquiring and transferring knowledge and at
modifying its behavior to reflect new knowledge (p. 80)”. Kim (1993) notes:
“All organizations learn, whether they consciously choose to or not – it is a
fundamental requirement for their sustained existence. Some firms deliberately
advance organizational learning, developing capabilities that are consistent
with their objectives; others make no focused effort and, therefore, acquire
habits that are counterproductive. Nonetheless, all organizations learn” (p. 37).
Inkpen (1998a) reviews descriptions of the learning organization and identifies its
seven key attributes: 1) A learning organization is an organization that has learned
not to make the same mistake twice; 2) A learning organization is one which
consciously seeks to manage and increase its intellectual capital; 3) A learning
organization is one which makes learning a performance indicator; 4) A learning
organization is one where learning is managed systematically and professionally at
every level, rather than occurring randomly; 5) It has a pervading culture of learning
and architecture for managing knowledge; 6) A learning organization has understood
that the ability to learn faster than its competitors may be the only sustainable
competitive advantage; and 7) A learning organization is not a destination; it is a way
of being.
Although the terms organizational learning and learning organization in some cases
are used interchangeably (Boje, 1994; Nevis et al., 1995), most authors differentiate
between them (Easterby-Smith, 1997; Tsang, 1997). The differences are based on
following distinctions:
Firstly, organizational learning is a concept used to describe certain type of process
or activity that takes place in an organization while the learning organization refers to
a particular type of organization in and on itself (Tsang, 1997).
Secondly, organizational learning is as natural as learning in individuals while the
learning organization can be distinguished as one that moves beyond this “natural”
learning, and whose goals are to thrive by systematically using its learning to
progress beyond mere adaptation (Dodgson, 1993). As a result, all organizations
learn but only some could be learning organizations (Hawkins, 1994).
The third distinction is about research focuses. Easterby-Smith and Araujo (1999)
point out those authors on learning organization are oriented to the development of
20
normative models or managerial issues to enable organizational learning processes
while organizational learning authors are more descriptive in a sense to understand
the nature and the process of learning in organizations.
The fourth distinction relates to the learning entity. Most of the researches on
organizational learning imply that the individuals learn as agents for the organization
and in order to be valid as organizational learning, the knowledge must be stored in
the organizational memory (i.e. shared mental models). Therefore, the learning
entities are both the individuals and the organization as an individual (Kim, 1993;
Dixon, 1994; Argyris and Schon, 1978). In learning organizations, however, the
knowledge sticks to the individuals and is seldom made organizational. The
knowledge exists mostly on the individuals (i.e. their bodies and brains). The transfer
of knowledge in learning organizations is supposed to go on between individuals, not
between individuals and the memory of the company.
The current study adopts the view of Easterby-Smith and Araujo (1999) that sees the
two terms as closely interrelated to each other. The scientific rationale is that
understanding organizational learning is one of the prerequisite requirements for
further studies on controllable factors influencing the organizational learning
processes which occur purposely in a learning organization (Bohn, 1994). This
would help develop normative approach towards building learning organizations. For
this matter, Easterby-Smith (1997) suggests that the distinctions should be viewed as
stemming from different disciplinary perspectives. To understand the phenomenon,
psychology, sociology, and organization behavior are preferred disciplines whereas
learning organization with normative orientation would be more appropriate to be
referred to management theories such as strategic management, organization
development or technology/ production management.
2.2.4. Organizational learning from different perspectives
According to Chaston et al. (2000), the theoretical foundations of organizational
learning can be traced back to a diverse variety of academic perspectives. The
current study is based primarily on the management science perspective to
understand the phenomenon and on the strategic management perspective to explain
inputs/outcomes issues as well as the strategic implications.
21
2.2.4.1. Management science perspective
The key concerns from the management science perspective are the gathering and
processing of information in an organization. Huber (1991) elaborates the
phenomenon around four main processes: knowledge acquisition, information
distribution, information interpretation, and organizational memory. First, knowledge
can be acquired through the inherited knowledge of a company’s members and by
recruiting new staff with external knowledge. More important, however, is the
potential of the organization to learn through feedback on the consequences of its
actions. This idea has been greatly popularized by Argyris and Schön (1978), through
the concepts of single and double-loop learning. This knowledge then needs to be
distributed and interpreted widely across the organization. Huber (1991) points out
that the distribution of information can lead to the creation of new information
because people may now be able to piece together patterns which were not
previously apparent. Both the distribution and interpretation of information are seen
as limited by the amount of information available, so that total availability of
information may paradoxically lead to ineffective interpretation. The work of
Nonaka (1994) develops the concept further through the distinction between explicit
and tacit knowledge. This has been particularly helpful because it moves beyond the
rationality. In this view, both forms of knowledge are necessary, and it is the
continuous dialogue between the two that leads to the creation of organizational
knowledge.
2.2.4.2. Strategic management perspective
Studies of organizational learning from the strategic management perspective focus
on competition (Easterby-Smith, 1997). Learning is recognized according to whether
it gives an organization an advantage over others. As Hamel and Prahalad (1993)
comment, “being a learning organization is not enough; a company must be capable
of learning more efficiently than its competitors” (p. 80). The bulk of the literature
takes what Whittington (1993) calls the “evolutionary” and the “processual” views of
strategy. The evolutionary view is dominated by work on population ecology. The
key question here is about the evidence that the ability to learn is a significant factor
in the survival of a number of organizations (Hannan and Freeman, 1988, Pennings
et al., 1994) and about the chances of individual companies to gain competitive
advantage through organizational learning (Parkhe, 1991; Miner and Haunschild,
22
1995; Buckler, 1998). The process view (Dodgson, 1991; Elms and Kassouf, 1995;
Inkpen and Crossan, 1995; Lillrank, 1995; Lyles and Salk, 1996; Andreu and
Ciborra, 1996) concentrates on the micro level, and gets insights on how learning
takes place within and between organizations. The relationship between learning and
strategy is seen as reciprocal: the strategic frameworks influence the perception and
interpretation of information from the environment; and the learning style and
capacity of the organization may in turn determine the strategic options that can be
perceived.
2.2.5. How an organization learns
Organizational learning ultimately learns via their individual members (Kim, 1993).
Hence, theories of individual learning are crucial for understanding organizational
learning. However, organizational learning is more complex and dynamic than a
mere magnification of individual learning. The level of complexity increases
tremendously when we go from a single individual to a large collection of diverse
individuals. Although the meaning of the term “learning” remains essentially the
same, the learning process is fundamentally different at the organizational level.
In an effort to understand how an organization learns, Argyris and Schön (1978)
develop a three-fold typology of learning: single-loop, double-loop and deutero
learning (Table 2.1). They describe single-loop learning as the error-detection-andcorrection process. Once the errors are detected and corrected, it permits the
organization to change its methods and rules to improve what is being done within
existing programs or policies. Consequently, the organization achieves its present
objectives more efficiently.
Double-loop learning, in addition to error-detection-and-correction, involves change
of the values of an organization’s theory-in-use. This form of learning occurs when
error is detected and corrected in ways that involve the changes in an organization's
underlying norms, policies and objectives.
Deutero learning or triple-loop learning is learning how to learn. It indicates
organizational members' cognitive change as a result of reflecting and inquiring into
their previous learning experiences. In other words, deutero learning involves how to
carry out single and double-loop learning.
“When an organization engages in deutero-learning, its members learn about
23
previous contexts for learning. They reflect on and inquire into previous
episodes of organizational learning, or failure to learn. They discover what they
did that facilitated or inhibited learning, they invent new strategies for learning,
they produce these strategies, and they evaluate and generalize what they have
produced” (Argyris and Schon, 1978, p. 4).
Table 2.1: Levels of Organizational Learning
Level
Single
Focus
Rules
loop
Features of learning
Changes in existing organizational rules largely at program
levels; general tightening and improvement in current
procedures.
Double
Insight
loop
Rethinking of existing rules according to why things are
being done; involves understanding reasons for current rules
and then questioning these reasons.
Deutero Principles
Questioning the rationale for the organization as a whole,
particularly the mixture of internal desires and identity, and
the relationships with the external environment.
(Sources: Argyris and Schön, 1978)
As far as the sources of knowledge are concerned, Mills and Friesen (1992) suggest
that an organization learns in several ways. It may learn through the individuals who
are its members. Those people may be hired because of their specific competence or
knowledge, which may be gained on the job or received in formal training. In this
point of view, learning is an individual phenomenon, which benefits the organization
entirely through the individual. Organizational learning must involve systemizing
knowledge into its practices, processes and procedures that is the reutilization of
knowledge. If the individual doesn’t use knowledge or leaves the firm, then the
knowledge remains with the organization. It means the organization has learned
something. Moreover, when a firm acquires or merges with another, it also learns
from that firm by absorbing into its own practices and procedures, or adds to its staff,
24
the knowledge embodied in the other firms’ processes and personnel. It is rather like
the acquisition by hiring individuals with desired knowledge.
Regarding the organizational learning process, Nevis et al. (1995) propose a threestage model: knowledge acquisition, knowledge sharing, and knowledge utilization.
Knowledge acquisition refers to the development or creation of skills, insights,
relationships. Knowledge sharing is the dissemination of what has been learned, and
knowledge utilization can be understood as the integration of learning so it is broadly
available, and can be generalized to new situations. Nevis et al. (1995) further stress
that organizational learning may take place in planned or informal ways. Knowledge
and skill acquisition takes place not only in acquisition stage, but also in the sharing
and utilization stages.
Explaining how organizational knowledge is created, Nonaka (1994) suggests four
ways in which new knowledge can be created. This is via the different channels of
interaction between tacit knowledge and explicit knowledge which results in an
augmentation of the knowledge base of an organization.
-
Socialization or tacit-to-tacit knowledge creation, which is a personalized form of
tacit knowledge growth in which one person passes on knowledge to another person;
-
Combination or explicit-to-explicit knowledge creation, by which new
knowledge is gained by combining and synthesizing existing explicit knowledge
from different sources;
-
Externalization or tacit-to-explicit knowledge creation, which occurs when
someone takes existing knowledge, adds their tacit knowledge, and creates
something new that can be shared throughout the organization;
-
Internalization or explicit-to-tacit knowledge creation, which occurs when new
explicit knowledge is internalized within members of the organization to create
new tacit knowledge.
According to Nonaka (1994), the cycle of knowledge creation begins with socialization,
the sharing of tacit knowledge. The next phase is the construction of explicit concepts by
externalizing the tacit knowledge. After that, systemic knowledge is created by
combining and ordering conceptual knowledge. Finally, the created new knowledge is
internalized and converted into operational knowledge. In complex processes such as the
development of new products, this cycle is repeated over and over again.
25
Knowledge
Dissemination
Individual Learning
Shared Knowledge
or
Mental Model
Individual Action
Knowledge
Utilization
Environmental Response or Changes
Knowledge
Acquisition
Individual Mental
Models
Organizational Action
Figure 2.2: An explanatory model of organizational learning
(Source: Adapted from Kim, 1993)
Another model is proposed by Kim (1993) to explain the link between individual
learning and organizational learning (Figure 2.2). In this model, an organization
learns through its individual members and therefore, is affected either directly or
indirectly by individual learning. But organizational learning is not merely a
collective of individual learning. The model specifies the transfer mechanism
between individual and organizational learning: the process through which individual
learning becomes embedded in an organization’s memory and structure.
Accordingly, individual learning affects learning at organizational level through their
influence on the organizations shared mental models. An organization can learn only
through its members, but it is not dependent on any specific members. Individuals,
however, can learn without the organization.
In this integrative model, moreover, the organizational learning process can be
viewed from both collective learning perspective and cognitive-outcome perspective.
The collective learning outcome explains how knowledge learned by individuals
become organizationally shared knowledge. Whereas, the cognitive outcome shows
that the knowledge acquired by an individual can lead directly to individual action or
indirectly to organizational action through knowledge sharing (Kim, 1993).
26
2.2.6. Organizational learning facilitators
Organizational learning is a collective activity that takes place under certain
conditions or circumstances (DiBella, 1995). Therefore, developing a learning
organization is not a random chance but a deliberate intervention by leaders to
establish the necessary conditions for the organization to operate in an organizational
learning mode (Goh and Richards, 1997). This view reflects Garvin (1993) who
stresses that to develop organizational skills, it is required that the organization must
actively manage the organizational learning process to ensure that it occurs by design
rather than by chance.
Therefore, for organizational learning to occur smoothly, it is required that the firm
be aware of and enables factors that facilitate the organizational learning process.
Appelbaum and Reichart (1998) refer facilitating factors or facilitators to
organizational features that support the creation of new knowledge and
organizational learning. Particularly, Stonehouse et al. (2001) define knowledge
facilitators as aspects of an organization incorporating its culture, structure and
infrastructure which play an important role in fostering organizational learning and
knowledge creation.
There are suggestions on the organizational learning facilitators which have been
found in the studies of Teare (1997), Goh and Richards (1997), Appelbaum and
Reichart (1998), Solingen et al. (2000), and Stonehouse et al. (2001). Table 2.2
presents a summary of facilitators as suggested by each study. From the management
perspective, these facilitators can be clustered into five factors. These factors are
organizational factors that can be managed actively so that organizational learning
can occurs by design rather than by chance (Garvin, 1993; Stonehouse et al., 2001).
They are as follows:
27
Table 2.2: Summary of suggested organizational learning facilitators
1. Linkage with
external sources
of knowledge
2. Organizational
vision and
leadership
commitment
3. Organizational
structure
4. Management
systems.
5. Organizational
culture
Teare
(1997)
+ Continuous cycle of
adjustment and realignment to the
external environment.
+ Learning partnership
with external
catalysts.
+ Leadership’s
encouragement
Goh & Richards
(1997)
Appelbaum & Reichart
(1998)
+ Information gathering
about environment
+ Clarity of mission + Ongoing commitment
to members’ growth
and purpose
and development.
+ Leadership
commitment and + Involved leadership
empowerment
+ Relevant
+ Teamwork and
+ Inter-dependence of
organizational
group problem
organizational units,
structure
solving
systemic relationships
among units
+ Experiencing and Self + Experimenting
+ Measuring
reflection
+ Rewards for
performance gap
+ Soft performance
learning
+ Variety of methods,
measures
procedures, systems
and appreciation of
diversity
+ Free sharing of
+ Open communication,
Information/
sharing information,
Communication
debating, error/lesson
sharing
28
Solingen et al.
(2000)
+ Scanning for knowledge
Stonehouse et al.
(2001)
+ Explicit goal definition
+ Involved leadership
+ Recognition of
knowledge value
+ Modeling the system and
identifying possibilities for
control
+ Relevant
organizational
structure
+ Scanning for knowledge from
internal sources
+ Measuring current state of
system and monitoring
performance gap
+ Infrastructure and
system are available
to support learning
+ Organizational environment with + Information
free flow of information, open
dissemination and
communication, shared
relevant culture
problems/lesson learned.
̇
Linkage with the external sources of knowledge which includes continuous cycle
of adjustment and realignment to the external environment, learning partnership
with external partners, information gathering about the environment, scanning for
knowledge from the external environment.
̇
Organizational vision and leadership commitment which include the clarity of
mission and purpose of the firm towards learning, recognition of knowledge
value, leadership commitment and involvement in the learning process and
employees’ development.
̇
Organizational structure that is featured by teamwork, group decision making and
inter-unit dependence
̇
Management systems that are featured by experiencing and experimenting, selfreflection, soft performance measures and rewards for learning, monitoring
performance gaps, appreciation of variety of methods, procedures and diversity
and availability of infrastructure to support learning.
̇
Organizational culture that nurtures a climate of openness, knowledge
orientation, free communication, information sharing, sharing and debating of
problems and lessons.
It is, however, found that all of these suggestions have been based on theoretical
analyses. None of them were supported by empirical evidence. Moreover, the
important issue that which factor has significant impact on which components of
organizational learning process (i.e. creation, dissemination/sharing and utilization)
has not been addressed in these studies.
2.2.7. Debates and issues in organizational learning
For ending up this section on organizational learning, a diverse and controversial
research field (Easterby-Smith and Araujo, 1999), this part summarizes a number of
key issues related to the current literature, which deserve further attention by
researchers.
2.2.7.1. Process versus outcome
Many organizational learning authors treat organizational learning as an
“achievement” while others pay attention to the process and the dynamic of learning.
Researchers who emphasize on the organizational learning outcomes often perceive
29
that learning leads to improvement. This view assumes that organizational learning is
directed towards creating “useful” knowledge for the organization (Easterby-Smith
and Araujo, 1999).
In contrast, other authors direct their research focus on the learning process. To this
view, learning does not necessarily lead to positive outcomes (Huysman, 1999) due
to a number of problematic learning. For example, the conservation caused by
incomplete learning cycle (Kim 1993), inability to think in wholes instead of pieces
(Senge, 1990) or defensive tendency among organizational members to protect
themselves from open communication and critique (Argyris and Schön, 1978).
Moreover, organizational behavior is far from being efficient and effective because
of unexpected events, myopic forces, and confusion of history (Levinthal and March,
1993).
2.2.7.2. Measurement of learning
Corresponding to the two diverse views of organizational learning mentioned above,
its measurement can be anchored with outcome focus or process focus.
Outcome measures: To measure the outcomes of organizational actions and to infer
learning from changes in outcomes over time. The derivation of learning curves is
the most common application of the outcome approach. However, as Robey et al.
(2000) comment, although learning curve studies rigorously estimate the rate of
learning by fitting temporal data to functional forms, they do not observe the learning
process directly.
Process measures: One approach to measure the organizational learning process is
provided by Crossan and Hulland (1997). These researchers developed a
questionnaire designed to measure learning at the individual, group, and
organizational levels as well as the flows among these levels. Another approach is
proposed by Crossan et al. (1999). They developed a framework including four main
events: intuiting, the preconscious recognition of the possibilities inherent in a
personal experience; interpreting, the explanation of an idea to oneself and to others;
integrating, the developing of a shared understanding and coordinated action among
individuals; and institutionalizing, the process of ensuring that actions are made
routine.
Combining the outcome and process measures: It would seem beneficial to combine
30
the outcome and process approaches, thereby establishing a stronger association
between actions that are construed as learning and the outcomes of learning (Robey
et al., 2000).
2.2.7.3. Individual versus organizational action
As mentioned earlier, some authors treat organizational learning as an action of
individuals or groups while others emphasize the structural aspect of organizational
learning. Many authors have reached a consensus concerning an implicit
confirmation that organizational learning is different from a sum of individual
learning. However, there still seems to be a lot of confusion about the nature of the
relationship between the two forms of learning (Nicolini and Meznar, 1995;
Huysman, 1999).
2.2.7.4. Technical versus social process
Easterby-Smith and Araujo (1999) remark that the most significant distinction
between authors who write about organizational learning can be summarized
according to whether they emphasize it as a technical or social process. The technical
view assumes that organizational learning is about the effective processing,
interpretation of, and response to, information both inside and outside the
organization. In contrast, the social perspective on organizational learning focuses on
the way people make sense of their experiences at work. These experiences may be
derived from explicit sources such as financial information, or they may be derived
from tacit sources. In this view, learning is something that emerges from social
interactions, normally in the natural work setting.
The distinction between technical and social perspective of organizational learning
can be linked to one debate and one trend (Easterby-Smith and Araujo, 1999). The
debate is about whether the field is becoming too fragmented and needs more effort
devoted to integration of theory and practice, or whether distinct schools of thought
are complementary and necessary for the development of the field as a whole. The
trend is the strengthening of the social perspective on organizational learning, and the
evolution of methodologies that enable it to be investigated empirically. While much
reliance is already placed on traditional qualitative and ethnographic methods
(Gherardi et al., 1998; Snell and Chak, 1998) there is a growing interest in the use of
other methods for researching learning processes with organizations.
31
2.2.7.5. Other biases
Apart from the issues mentioned, Huysman (1999) points out some further biases.
Firstly, many theories refer to learning as an activity that deliberately takes place and
thus can be planned for (Shrivastava, 1983; Boland et al., 1994). This view underestimates another way of learning which is unsystematic and unintentional (Huber,
1991; March, 1990) such as learning process taking place during day-to-day
activities (Huysman, 1999). Secondly, based on the open system approach,
organizations are said to learn by adapting to their ever-changing environment
(Senge, 1990; Fiol and Lyles, 1985; Weick and Roberts, 1993). However, other
authors argue against this environmental alignment view (Levinthal and March,
1993) by disputing the ability of the organization to align with its environment.
Huysman (1999) further points out that the incentive to learn may also be internally
driven such as plain chance events or a need to make a difference.
2.2.7.6. Research gaps in the field
Based on the above remark, Easterby-Smith and Araujo (1999) propose three issues
as main problems and also research opportunities in the field. The first issue is the
shortage of empirical work (Miner and Mezias, 1996; Goh and Richards, 1997). The
second issue is about theory development. There is a concern that insufficient
attention has been paid to the cumulative development of the field (Huber, 1991;
Miner and Mezias, 1996). This is manifested by a “tendency to take for granted a
small number of existing nostrums without submitting them to critical examination”
(Easterby-Smith and Araujo, 1999, p. 13). The last issue concerns the utilization of
theories and technique around organizational learning by firms and other
organizations. Dodgson (1993) notes that the concept of organizational learning
provides considerable promise - to academics because it may revitalize tired
disciplines, and to managers because it may be the key to corporate competitiveness.
However, the danger is that “it may become over-applied, and hence either exhausted
or discredited, especially among practitioners who have traditionally given very short
shelf lives to corporate panaceas” (Easterby-Smith and Araujo, 1999, p. 14).
32
2.3. INTERNATIONAL JOINT VENTURE
The review presented in the previous section shows that organizational learning can
occur with the knowledge source outside the firm such as inter-organizational
learning through partnering with other firms. This section introduces a brief literature
on international joint venture, a specific form of strategic alliance where learning is
frequently quoted as one of major interests.
2.3.1. Strategic alliance
During the recent decade, the term alliance or strategic alliance has appeared more
and more in the published literature (Sharma, 1998). Dussauge et al. (2000) define
strategic alliances as arrangement between two or more independent companies that
choose to carry out a project or operate in a specific business area by coordinating
the necessary skills and resources jointly rather than either operating on their own or
merging their operations. It is found that there are common underlying themes that
make up the essences of any strategic alliances. Firstly, there are at least two
independent firms making an enduring partnership for cooperation/collaboration.
Secondly, their joint activities encompass a number of functional areas. Thirdly, each
partner contributes part of its resources. Fourthly, they expect to gain benefits or
achievements that are considered to be better than those achieved when doing the
same business individually (Spekman and Sawhney, 1990; Parkhe, 1991; Bronder
and Pritzl, 1991; Burgers et al., 1993; Vyas et al., 1995; Osland and Yaprak, 1995;
Shamdasani and Sheth, 1995; Drago, 1997; Sharma, 1998; Gulati, 1998; Love and
Gunasekasan, 1999; Tsang, 1999).
Several theoretical approaches have been employed to explain the nature of strategic
alliances (Koza and Lewin, 1998). Sorensen and Reve (1998) summarize six
approaches that have been documented. These are resource-dependence, transactioncost, political economy, agency theory, relational contracting theory and interaction
approach. Among these approaches, resources–exchange view is the commonly
employed theoretical background to explain the nature of strategic alliances.
Dussauge et al. (2000) argue that firms’ competitive advantages derive from their
preferential access to idiosyncratic resources, especially tacit knowledge-based
resources. However, firms can hardly create all resources needed to prosper and
grow. Instead, collaboration among businesses that possess complementary resources
33
is often necessary for survival and growth, and provides a means of combining
resources held by different firms in order to exploit new business opportunities
(Sharma, 1998). Collaboration appears to be an effectively way of combining
resources that are subject to a high degree of knowledge-based market failure
(Gulati, 1998). Moreover, collaboration provides a means for firms to protect the
value of their resources through financial and organizational safeguards against
opportunistic behavior (Chi, 1994). Thus, collaboration provides potential benefits to
all partners. In the same vein, Chung et al. (2000) explain that the complementarity
of strengths and assets between firms is often what brings the partners together. By
pooling their resources and capabilities with those of other partners, firms can initiate
projects that they could not have successfully done alone. For a firm attempting such
a project, the consideration of the resource complementarity becomes an important
issue. Ever since the work of Penrose (1959, in Chung et al., 2000), much strategic
management literature has proposed that firms tend to create value if they access
complementary resources. This argument extends to the realm of strategic alliances.
2.3.2. Joint venture
With the underlying attributes identified, strategic alliances between firms can be in
various forms ranging from relatively loose contractual licensing to a joint venture
which is a newly created independent business entity. In this section, joint venture –
a form of strategic alliances that is of specific focus in this research - will be
reviewed in more detail.
2.3.2.1. The concept of joint venture
Historically, joint ventures have existed since the bazaar economy of Babylon.
During some centuries, their existences were relatively obscure, but after the
Industrial Revolution, they became instrumental in bringing together the resources
necessary to develop capital intensive projects such as mines and railroads across the
US (Dana, 1998). During the nineteenth century and until World War II, joint
ventures tended to be limited in geographic scope, and their primary purpose was to
make possible large enterprises which individual firms could not undertake on their
own. During the past few decades, joint ventures have been proliferating and become
increasingly international (Sharma, 1998).
Harrigan (1985) describes a joint venture as a specific form of strategic alliance that
34
is created when two or more partners join forces to create a newly incorporated
company in which each has a share of resources, and each thereby may expect an
appropriate allocation of dividend as compensation, representation of the joint
venture’s board of directors, and active participation in the decision-making activities
of the venture. Glaister and Buckley (1998) further explain that the outcomes of joint
venture may depend on the strategic purpose of the joint venture. For example, many
joint ventures are established as a cost center with the benefit accruing in activities of
the partners. A joint venture may also be established to promote the development of
technology or facilitate learning in other areas, such as marketing, rather than with
specific immediate financial or dividend goals.
Other definitions of joint venture can be found in the published literature. For
instance, Kogut (1988) defines that a joint venture occurs when two or more firms
pool a portion of their resources within a common legal organization. Czinkota et al.
(1989) define joint venture as the participation of two or more companies jointly
participating in an enterprise in which each party contributes assets, owns the entity
to some degree, and shares risks. The venture is also considered long-term. Anderson
(1990) refers to the term joint venture as an organizational form where at least two
companies pool resources to create a new, separate organization. Geringer (1991)
postulates that joint ventures occur when two or more legally separate bodies form a
jointly owned entity in which they invest and engage in various decision making
activities. Lessard (1994) describes that a joint venture typically involves a formal
contract, equity investment and a separate entity, and it may or may not involve
ongoing inter-dependence in the form of tapping the capabilities of one or both
parents, and, perhaps, contributing to those capabilities as well. In many cases, a
joint venture is spun off with an initial stock of capabilities and other assets and is
expected to operate on its own thereafter. Llaneza and Canal (1998) view that a joint
venture exists when two or more firms agree to set up a new entity, owned by them,
to carry out some activities in which they are interested, although not necessarily for
the same reasons. Lyles et al. (1999) refers to a joint venture as an organizational
form in which two or more parents contribute resources, including equity, to form a
semi-autonomous, legally separate entity that exists for more than a short duration of
time. It is found that these definitions of joint venture are quite convergent. Their
core themes are commonly adopted by recent studies including the present study.
35
2.3.2.2. Classification of joint ventures
There have been various ways to classify joint ventures. The criteria for classification
depend on the interest of researchers and its relevant implications to the research
focus. In general, the following features have been commonly used for the
classification of joint ventures:
Based on the equity participation by partners, joint ventures can be classified into
equity and non-equity joint venture. More common is the equity joint venture which
involves a financial investment by the parent companies. Less common is the nonequity venture where one group merely provides a service for another (Griffith et al.,
1998).
In terms of the relative strength of the partners involved, some authors differentiate
between shared joint ventures and dominated joint ventures (Killing, 1983; Salk,
1992; Lyles and Salk, 1996). In a shared joint venture, the equity is shared (say,
50/50) between partners and therefore the power and right to make strategic
decisions are shared between partners. In contrast, in a dominated joint venture, one
partner assumes a dominant role in strategic decisions.
Dussauge et al. (2000), following Hennart (1988), differentiate between scale and
link joint ventures. Scale joint ventures are interfirm partnerships to which partners
contribute similar capabilities while link joint ventures are partnerships to which
nonsymmetrical partners contribute different capabilities. Scale alliances allow
partners to achieve scale economies and to reduce excess capacity. On the other
hand, link joint ventures aim at combining different and complementary skills and
resources that each partner contributes.
Based on the number of partners involved, joint ventures can be two-partner joint
ventures where two companies share resources. In contrast, they can be multi-partner
joint ventures involving several companies (Vyas et al., 1995; Griffith et al., 1998).
In terms of the strategic intent of partners (exploration vs. exploitation), Koza and
Lewin (2000) following March (1991) identifies three basic kinds of joint venture
namely learning joint ventures, business joint ventures and hybrid joint ventures.
Learning joint ventures join companies sharing strong exploration intents. They seek
to reduce information/knowledge asymmetry among the parents and may also
involve the joint creation of new knowledge. Business joint ventures link companies
36
with strong exploitation intents. Typically, these alliances seek to establish a position
in geographic or product market or market segment. The third type involves hybrid
joint ventures, which joins companies with strategic intents that include strong
exploration and exploitation objectives. In these alliances, the companies seek to
simultaneously maximize opportunities for capturing value from leveraging existing
capabilities, assets, and the like, as well as from the opportunity to create new value
through their joint learning activities.
Based on the geographic location, joint ventures can be classified as international or
domestic. A joint venture is termed international (IJV) if at least one of the parties
(or parents) is based outside the country where the venture is taking place or if the
joint venture is being administered on a wide level in more than one country
(Geringer and Hebert, 1989; Meschi, 1997; Llaneza and Canal, 1998).
In terms of the development level of the parent firm’s country of origin, international
joint ventures can be further classified into joint ventures between firms in developed
countries and joint ventures between firms from developed and developing countries
(Liu and Vince, 1999; Inkpen, 1997). Of specific interest in the current study are
joint ventures of the latter type. Researchers suggest that forming joint ventures with
local firms is one of the most effective strategies for firms in developed countries to
expand their business to developing countries (Si and Bruton, 1999; Makino and
Delios, 1996).
2.3.3. Motives of partner firms to form joint ventures
Researchers have identified many specific reasons motivating firms to establish joint
ventures. Although expressed in various ways, these reasons can be categorized into
four groups of motivations: to improve efficiencies, to enhance market power, to
learn and to share risk and/or reduce uncertainty (Lin et al., 1997, Calanton and
Zhao, 2000; Nicholas and Pincell, 2001). It is noted that in many cases, a firm’s
decision to establish a joint venture with other partner(s) is affected by a mixedmotive including more than just one among the four groups.
2.3.3.1. Improvement of efficiency
The improvement of efficiency can be achieved by two ways, synergy of
complementary resources and transaction cost reduction. Scholars in economics and
business strategy emphasize that by bringing complementary resources to the joint
37
ventures, the pool resources can create excess value relative to their value before the
pooling (Chung et al., 2000; Nohria and Garcia-Pont, 1991). Efficiency in joint
ventures can also be achieved through scale economies (Chan and Wong, 1994;
Blitzer, 1998; Gulati, 1998; Beeby and Booth, 2000). Kogut (1988) points out that
transaction costs in joint venture are minimized as a result of a smaller numbers of
bargaining. It is also by the development of social ties and networks in which trust
and commitment are characterized (Gulati, 1998).
2.3.3.2. Enhancement of market power
Early empirical studies on joint ventures focused on the formation of joint ventures
across industries and size of firms entering them (Kogut, 1988). The concentration of
such alliances within particular industries and the propensity of larger firms to enter
them led scholars to conclude that the quest for market power may be an important
motive for such ties (Gulati, 1998). Beeby and Booth (2000) point out one of the
reasons for entering joint venture is to reach new market, to enjoy first-move
advantage by exploiting speed to market and to achieve transformative synergies via
process rationalization. This motive is especially important in the case of
international joint ventures where accessing a local market is controlled by trade or
legal barriers. This point is reinforced by Dussauge et al. (2000), Blitzer (1998) and
other scholars (e.g. Calantone and Zhao, 2000).
2.3.3.3. Risk sharing and uncertainty reduction
Risk sharing and uncertainty reduction are other reasons to drive firms to enter joint
ventures. These reasons become more important in the case of R&D joint ventures,
joint ventures in risky businesses or joint ventures to enter a new market. Swierczek
et al. (1997) points out that new product or new technologies development projects
have a high probability of failure and those that succeed may take years to become
profitable. In such situation, combining the resources and expertise of two companies
helps reduce risk for both parties. Beeby and Booth (2000) echo this view by
suggesting risk sharing as one of the reasons for firms entering a joint venture to
reduce risk by sharing the capital requirements of new product development. In
addition, other scholars emphasize the role of joint venture in reducing demand and
competitive uncertainty (Burgers et al., 1993).
38
2.3.3.4. Learning
Learning to acquire knowledge from partner or to create new knowledge is now one
of the critical motives driving firms to joint ventures. Inkpen (1997) examined USJapanese joint ventures in North America and concluded that North America firms
desired technical and manufacturing knowledge while Japanese firms required local
knowledge. The desire to acquire local knowledge from joint venture partners is also
reflected in Makino and Delios’s (1996) study of Japanese firms in alliances in South
East Asia. According to Mowery et al. (1996), one of the most widely cited motives
for the collaboration is the acquisition of new technological skills or technological
capabilities from partner firms. Joint ventures have advantages over conventional
contract or markets for this task because firm-specific technological capabilities are
frequently based on tacit knowledge and are subject to considerable uncertainty
concerning their characteristics and performance. These features make it difficult to
draft simple contracts governing the sales or licensing of such knowledge or
capabilities (Khanna et al., 1998).
Moreover, when an environment is unstable, managers seek knowledge in order to
develop an increased understanding of the changing market conditions and to
increase their confidence in decision making (Menon and Varadarajan, 1992). In
today’s complex and unstable environment, more and more organizations are
recognizing that an individual firm is insufficient to deal with these changes. It is
likely that the linkages between firms are an attempt by managers to reduce the
uncertainty associated with environmental instability (Anderson, 1990). Knowledge
and skills gained from organizational partners appear to help managers become more
secure in dealing with the complex and dynamic environment (Osland and Yaprak,
1995).
2.3.4. Motives of partners in developing countries
Swierczek et al. (1997) identifies the following specific motives for foreign partners
and for local partners in international joint ventures in developing countries:
Motive of the foreign investors:
̇
̇
Securing, maintaining and/ or developing of a regional base. Mainly to serve
the nearby market;
Securing, maintaining and/ or developing of an overseas market which would
39
̇
̇
̇
otherwise be lost to the company;
Securing, maintaining and/ or developing of raw material suppliers;
The necessity to complement other activities of the organization;
Competitive forces in the local and the international market necessitating the
development of an overseas lower cost base for export back to the home
̇
country and export to a third country;
Other diverse motives like utilization of old machinery, capitalization of
know-how, protection of parents abroad, and taking advantages of offers by
host government.
Motives of local partners include:
̇
To seek foreign investment in order to obtain capital, technology and
management know-how.
̇
To increase in employment and productivity levels and the efficient
utilization of scarce resources such as foreign exchange and imported
material inputs.
̇
To increase its competitive position in the local market by upgrading its
product line and obtaining assistance from foreign firms.
̇
To gain easier access to technology information, particularly from
industrially developed countries (Si and Bruton, 1999).
It is seen that in most of the cases, the learning motive of local partner in developing
countries is more intensive than its counterpart from developed countries. While
foreign partners want to learn about local culture, market behavior and government
behavior, the majority of local partners’ motive is to learn technology and
management know-how (Swierczek et al., 1997; Si and Bruton, 1999).
2.4. LEARNING AND KNOWLEDGE ACQUISITION IN IJVs
The term learning in strategic alliances or in joint ventures in particular, has emerged
from the developments of two contemporary management thoughts that are reviewed
in the previous sections. It is realized that many firms today are seizing the
opportunity to acquire new knowledge through cross-national collaborative
arrangements and to transform their core competencies (Sharma, 1998).
40
Organizational learning has become a critical imperative for global strategic
effectiveness (Tsang, 1999). The ability of a firm to seek, absorb, and transfer
knowledge from their collaborative arrangements back to the parent companies
becomes a crucial skill (Osland and Yaprak, 1995). This leads to the
recommendation that a strategic alliance should be regarded as a learning battlefield
(Hamel, 1991). The term “coopetition” (Zineldin, 1998, Loebecke et al., 1999) and
“competitive collaboration” (Hamel, 1991) have been created to describe such
interpartner relationship.
The contents presented in this section include generals on the organizational learning
in strategic alliances. This is succeeded by learning in international joint ventures
between firms from developed and developing countries. Lastly, patterns and
framework of learning in international joint ventures are presented.
2.4.1. Background on learning in strategic alliances
There are a number of reasons to believe that partnering with other firms may help
promote learning. Barlow and Jashapara (1998) argue that value-adding partnerships
allow firms to improve their knowledge base while traditional hierarchical systems
limit the knowledge and adaptive capacity of firms and raise information costs. Other
scholars almost accept that strategic alliances provide firms with flexibility and
opportunities for innovation and learning (Gulati, 1998; Inkpen, 1998a; Tiemessen et
al., 1997; Tsang, 1999; Lyles et al., 1999).
Forming alliance with other partner, firms can learn the other partner’s skills and
learn from strategic alliance experience. Tsang (1999) expresses that implementing
technology transfer; managing the alliance per se and knowing about a new business
environment constitute the “learning from strategic alliance experience”, and require
an experiential learning process. It is distinct from “learning the other partner’s
skills” that entails a vicarious learning process. Tsang (1999) further identifies
various patterns of learning in strategic alliances. Depending on whether the partners
concerned focus on the same or different objects of learning, four patterns of
learning, namely asymmetrical, non-mutual, competitive and non-competitive, are
identified.
If both partners have the same objective of learning, the resultant pattern is classified
as symmetrical, otherwise asymmetrical. Asymmetrical learning typically takes place
41
in a joint venture set up by a firm from a developed country in a developing country.
There is a large gap of technical competence between the two partners. For an
international joint venture formed in developing countries, the foreign partner usually
tries to benefit from the indigenous experience of the local partner. After the foreign
partner has acquired the needed capabilities from the joint venture’s operation, it will
no longer need the local partner and may convert the joint venture into a wholly
owned subsidiary (Gomes-Cassers, 1987). The development can also be the other
way round. That is, after the local firm has internalized the know-how of the foreign
partner, it may try to operate on its own. However, it is not expected that the effect of
learning asymmetries on the alliance stability is as great as the case in competitive
learning (Dussauge et al., 2000).
Based on the collaborative - cooperative dichotomy of alliance, Love and
Gunasekasan (1999) suggest that the form of alliance formed between organizations
will influence its learning capabilities. Essentially, collaboration refers to working
together for the short-term and cooperation for the long-term. Hamel (1994) suggests
that organizations that enter into collaborative alliances are aware that their partners
are capable of disarming them and that acquiring skills and knowledge from their
partners is not a devious act, rather a commitment from each partner to absorb the
skills of other parties. On the other hand, cooperative alliances encourage partners to
commit their resources to the relationship to gain mutual learning. In addition, there
is a lower level of competition and as a result, partners may feel more committed to
work together and exchange their knowledge and resources. Simply speaking,
strategic alliances are a manifestation of inter-organizational cooperative strategies
and entail the pooling of skills through the cooperation of organizations aiming to
achieve commons goals, as well as goals specific to the individual partners (Love
and Gunasekasan, 1999).
2.4.2. Learning in IJVs between firms in developed and developing countries
Among various forms of strategic alliances, international joint ventures provide an
excellent environment for inter-partner learning to occur. Tiemessen et al. (1997)
identify four categories of knowledge that can be learned in this context. These
include firm-specific knowledge, market-specific knowledge, partnering knowledge,
and resource integration knowledge.
42
Firm-specific knowledge is the knowledge accumulated about the business itself,
such as the technology used, the products and operations, the services provided, the
management of the employees, and the systems supporting the firm's internal
activities. Market-specific knowledge is the knowledge accumulated about the
factors that affect the firm's activities within a particular location or market, such as
the laws and regulations governing business activities, the customer and supplier
base, the availability of raw materials and distribution channels. A third category of
knowledge relevant to international joint ventures is partnering knowledge, or the
know-how required to work with a partner. Lastly, the fourth category is resource
integration knowledge, encompassing the technical know-how required to transform
the available resources so that they function in the IJV context. To their IJV, the
partners contribute resources that they have developed and acquired in their
individual environments. However, the IJV must then integrate these pools of
resources to function cohesively and effectively in the new environment. In essence,
resource integration knowledge is knowing how to combine knowledge that is both
firm-specific and market-specific into a new configuration (Tiemessen et al., 1997).
One particular type of international joint ventures that attracts the attention of
researchers is international joint ventures between firms in developed and developing
countries. Tsang (2001) points out that during the past decade or so, thousands of
Western companies have established joint ventures and other forms of strategic alliances in transitional economies such as China, Russia, and Eastern Europe.
Governments of these countries want to import modern technology by collaborating
with Western companies, which try to take advantage of the low labor cost and
sizable market of these economies. During the years, it has been found that joint
ventures in developing countries are characterized by a high instability rate and less
managerial satisfaction when compared with those in developed countries (Beamish,
1985). Some of the problems stem from learning failures. It seems that foreign
companies have to pay more attention to the asymmetrical learning pattern in
alliances formed with local partners in developing countries (Tsang, 1999).
In a study on international joint ventures between firms in China and Western
countries, Si and Bruton (1999) found that one of the criteria by which a JV’s
success is judged is the knowledge transfer between the parties and the synergy it
brings to the joint ventures. Such knowledge transfer is particularly important in
43
China as Western firms seek to learn about the Chinese market and how to compete
in it, while their Chinese partners desire knowledge about relevant new technologies
or management skills. If the understanding of China is improved, and the parties
achieve better cooperation and communication from better knowledge acquisition,
then the resulting performance of these international joint ventures will improve.
Examining the learning purpose, Si and Bruton (1999) identify ten knowledge goals
that are parts of three broad categories:
Knowledge of Government Issues:
Understanding government behavior
Learning national policies, rules and relevant laws
Understanding the partner’s economic system
Knowledge of Culture:
Learning more about the partner firm’s national culture
Learning the negotiation styles of the partner‘s nation
Gaining knowledge of new managerial types and styles
Knowledge of Market:
Gaining knowledge of partner’s market characteristics
Gaining understanding of labor resources
Gaining understanding of capital resources
Learning new technologies
In another study on joint ventures in China, Liu and Vince (1999), following Child
(1994) identify three levels of learning. The first level is the technical, which
involves the acquisition and implementation of new techniques such as TQM and
market forecasting. The second level is the systemic, which refers to the introduction
and operation of new systems and procedures, like production control and budgeting
systems. Lastly, the third level is the strategic, concerning the mindsets of senior
managers, their criteria of business success and their understanding of significant
factors for achieving the success. Liu and Vince (1999) see technical learning as the
lower level of learning that does not necessarily lead to change in behavior but
learning at the systemic level requires change in workplace behavior and
relationships. As the highest level, learning as strategic understanding is most
44
important for inducing cognitive change in the Chinese managers necessary for the
market economy.
According to Liu and Vince (1999), learning in international joint ventures is
perceived as a means of knowledge acquisition and gaining collaborative know-how
and collective experience. However, in international joint ventures formed between
developing countries and developed countries, learning is largely a one-way process
(Liu and Vince, 1999; Danis and Parkhe, 2002). Western partners tend to assume
superiority in both technology and management, and can feel that they have little to
learn from local partners. In Chinese-Western joint ventures, while the transfer of
technological know-how has been generally smooth, the transfer of Western
management practices has been confronted with the resistance from local employees.
One reason has been that learning is often dominated by the rational drive to achieve
organizational effectiveness without sufficient attention to cultural differences, which
has created problems of mutual understanding (Liu and Vince, 1999).
2.4.3. Learning in IJVs – Patterns and framework
2.4.3.1. Learning patterns
Among four learning constructs proposed by Huber (1991), namely knowledge
acquisition, information distribution, information interpretation, and organizational
memory, Makhija and Ganesh (1997) argue that in relation to JVs, primary emphasis
is placed on the first two because the JV is the partners’ instrument for acquiring and
disseminating crucial information; the JV itself may play a comparatively lesser role
than the parent level that converts the learning into a source of sustained competitive
advantage. This argument is consistent with the notion that the JV is a vehicle
through which capabilities are acquired; ultimately, the use of those capabilities is
likely to take place within the parent as part of competitive advantage.
Osland and Yaprak (1995) maintain that firms can learn through at least four
processes: experience, imitation, grafting, and synergism. Interpartner learning may
entail the use of any of the latter three processes – imitation, grafting, and synergism.
In all three processes of interpartner learning, the major source of knowledge
acquisition is the related organization.
Imitation is an attempt to learn about the strategies, technologies, and management
skills of other firms and to internalize this second-hand experience. Managers are
45
forming alliances with other firms in an attempt to learn by close observation of their
partners’ unique skills. According to Osland and Yaprak (1995), this type of
interpartner learning is particularly relevant among competing firms within
oligopolies.
The term grafting explains how organizations increase their store of knowledge by
formally acquiring another firm or by developing a long-term alliance with another
organization that possesses knowledge not previously available within the
organization. Multinational firms have frequently linked up with host companies in
developing nations in order to possess a means of learning about the local culture and
to receive information flows about dynamic local political developments (Liu and
Vince, 1999).
Synergism occurs as firms collaborate to produce new knowledge. The sharing of
R&D staffs and facilities offers the potential for this process. Through collaboration,
partners can develop innovations that may not have been possible through
independent efforts. Synergistic learning may also involve ongoing, long-term
alliances, such as a joint venture. This kind of learning has the greatest potential to
generate discontinuous innovations which produce new markets (Osland and Yaprak,
1995).
Taking Nonaka and Takeuchi’s (1995) approach to organizational learning, Lyles
and Salk (1996) explain that the knowledge acquired from a foreign parent can be
explicit or tacit, and can be grafted to take root into the IJV organization via
socialization, internalization, and by combining different types of explicit knowledge
to create new knowledge that is useful in the IJV context. They further argue that
though organizational learning is most closely related to internalization, the
organizational learning literature can be applied to suggest underlying organizational
characteristics and structural mechanisms in cases of socialization (converting tacit
knowledge from the parent into tacit IJV knowledge) and combination modes
(combining types of explicit knowledge, which Nonaka and Takeuchi clearly relate
to training and educational programs by firms). Moreover, explicit knowledge
originating from a source organization such as a foreign parent might yield tacit
knowledge in the IJV and vice versa. Moreover, according to Lyles and Salk (1996),
organizations and their members can also acquire knowledge from others through
“grafting” individuals with special expertise, such as using expatriates in
46
international joint ventures and/or through "vicarious learning" from other
organizations. Learning through grafting of cognitive orientations to managerial and
technical matters closely corresponds to Nonaka and Takeuchi's (1995) notions of
socialization and internalization.
2.4.3.2. IJV knowledge management framework
Tiemessen et al. (1997), based on Parkhe (1993) and Toyne (1989) propose a
framework on organizational learning and knowledge transfer in IJVs which follows
an input-process-output model (Figure 2.3). The relevant structures are the individual
entities—two parents and the IJV—and the interactions between them. The resources
are the knowledge resources that both flow through and are created within this
model. The conditions are the context within which the knowledge management
process both operates and establishes parameters that influence the process. The
processes are the ways by which knowledge resources flow into, through, and out of
the structure, and the ways by which existing knowledge is transformed or new
knowledge is created. The outcomes are both learning and performance results
realized by the parents and the IJV.
Conditions
Structure and process
Parent B
Transfer
Joint venture
transformation
Knowledge resources :
Firm-specific
Market-specific
Harvesting
Harvesting
Parent A
Partner choice
Control mechanism
Motivation
Expectation
Experience
Outcomes
Learning outcomes
+ No learning
+ IJV learning
+ Parent learning
Performance outcomes
+ IJV performance
+ Parent performance
Resource-integration
Partnering
Figure 2.3: Knowledge Management in JV (Source: Tiemessen et al., 1997)
47
The conditions, structure, process and outcomes are described in the following:
Conditions: The conditions that have been identified as most salient for JV success
include partner choice, control mechanism, motivation, expectations, previous IJV
experience, nature of cooperation, and cultural context. These conditions, which are
both interactive and dynamic, create the context within which the knowledge
management process operates.
Structure: The structure of an IJV, with at least two parents from different countries
and a new organizational form, provides an excellent opportunity for knowledge
transfer and acquisition. Theoretically, within the context of a JV, resources flow
from the parent firms to the JV, where they are transformed into resources of higher
value, which are then partitioned and flow back to the parent firms. The implication
here is that the structure of the relationship will determine the barriers and gateways
to the interorganizational knowledge flow.
Process: Tiemessen et al. (1997) combine both cognitive and behavioral perspectives
to describe the learning process in IJV including four learning activities (micro
processes) that occur in four learning levels. The interorganizational learning process
can also be identified in three phases, namely transfer, transformation and harvesting
(macro processes).
Outcomes: There are trade-offs inherent in deciding which of the three strategic
objectives: achieving efficiency, managing risk, or learning. The decision is often
presented as a dichotomous choice between doing things efficiently and doing the
right things effectively. The same paradox exists within the learning process.
Continual promotion of innovation, experimentation, and reassessment can hinder
the systematizing and routinizing of factors that have already been tested and
justified. Yet to follow existing procedures to gain efficiencies without assessing
them in the light of new knowledge or improving them by incorporating new
competencies is to follow a short path to competitive disaster.
2.4.3.3. Interpartner learning phases
Tiemessen et al. (1997) describe three explicit phases to be managed to foster
learning. When firms form an IJV, they transfer or contribute resources that reflect
48
their existing stock of competencies. Through joint activities, these competencies can
be transformed and enhanced to reflect the combined pool of knowledge and skills,
as well as new knowledge created from the alliance. However, for firms to draw
upon the new knowledge and skills in other endeavors, they must be harvested and
brought back from the IJV.
Transfer is the movement of knowledge between the parent firms, either directly or
through the IJV, through activities such as buying technology, observing and
imitating technology used by the partner, or changing existing technologies
according to directions given by a partner. Transfer essentially means accepting what
the partner does, integrating it into one's own systems or changing one's own
resources to imitate it.
Transformation of knowledge is the extension of existing knowledge and the creation
of new knowledge, usually within the IJV. Casson (1993) notes that the successful
exploitation of an advantage internationally may require an adaptation of the
technology, the system, or the management practices (or all of these), to the local
environment. Collaborating with a local partner ensures correct adaptation and also
allows the management team to improve its own capabilities. This adaptation process
creates the two kinds of new knowledge previously discussed, resource integration
knowledge and partnering knowledge.
Harvesting involves retrieving knowledge that has already been created and tested
from the JV resources in which it resides, and then internalizing it into the parent
firm so it can be recalled and used in other applications. Although the harvesting of
knowledge sounds like a straightforward activity, it is a completely different process
from those of transfer and transformation, and is neither easy nor automatic. Lyles
(1988) suggests that in order for parent firms to harvest the new knowledge created
by JV activities, top management must play an active role in overseeing the JV and
communicate properly with the JV managers.
2.5. INTER-PARTNER LEARNING FACILITATORS: RESEARCH GAPS
Having reviewed the background of organizational learning and knowledge
acquisition in the context of international joint ventures, this section reviews in depth
the specific topic of the current study, i.e. facilitators of knowledge acquisition/
49
transfer in IJVs. The following section provides a summary of previous research
findings on the topic.
Table 2.3 shows the specific facilitators/inhibitors that were investigated in previous
studies. It can be seen from this table that conceptual studies are predominant over
empirical studies. Among the 33 studies found in the published literature since 1990,
there are only 13 empirical studies as compared to 20 conceptual studies.
In the group of empirical/large sample studies, more attention has been put on factors
related to the recipient of knowledge such as absorptive capacity (5 studies), learning
capacity (2 studies) or prior knowledge/experience (2 studies). In terms of the
knowledge attributes, some empirical studies on the knowledge tacitness (2 studies)
or ambiguity (2 studies) have been found. Other factors have attracted less attention
with only one or no empirical studies found. In terms of the number of factors being
examined simultaneously, there are only two studies dealing with five or more
facilitators. Seven studies deal with 2 to 4 facilitators. Four studies have been found
to investigate only one facilitator.
In contrast, in the group of conceptual studies, almost every factor has been received
due attention of researchers. Moreover, the majority of conceptual studies deal with 3
to 8 facilitators, except 3 studies discuss only one facilitator.
More details about these findings are blended in the analysis of the respective factors
presented in Chapter 3.
2.5.1. Facilitators of knowledge acquisition - previous studies
For structuring purpose, the findings are arranged in five groups, namely the source,
the acquirer of knowledge, the knowledge attributes, the JV characteristics including
ex-ante and ex-post characteristics.
2.5.1.1. Factors related to the source of knowledge
There have been a number of studies which theoretically argue or empirically find
that factors related to the source of knowledge play an important role as antecedents
of knowledge acquisition. Theoretically, Inkpen (1998a, b, 2000) argues that partner
protectiveness would impede, and knowledge connection would facilitate the
acquisition of knowledge from the other partner. Similarly, Hamel (1991) uses the
term partner transparency to address the openness to gain access to partner
50
knowledge. This concept is also echoed by Morrison and Mezentseff (1997) who use
the term ease of access to knowledge to reflect the same issue.
Also, Tsang (2001) suggests that partner assistance and partner explicit contribution
as other representations of the source’s openness and the knowledge connection
between partners which have positive impacts on the inter-partner knowledge
acquisition. Moreover, Baughn et al. (1997) warn that knowledgeability of the staff
at the interface is also critical to the knowledge acquisition. This is assumed to be the
case for the current research which focuses on the flow of management knowledge
(marketing know-how) from a more developed to developing country.
Empirically, it has been found that knowledge connections (Wathne et al. 1996),
secondment of staff (Clarke et al., 1998), partner assistance (Lyles et al., 1999) and
partner contribution (Lyles and Salk, 1996) are antecedents of knowledge acquisition
from the other partner. However, Simonin (1999b) failed to find statistical support
for the hypothesis that partner protectiveness has a negative impact on knowledge
transfer.
51
Table 2.3: Summary of recent researches on facilitators of knowledge transfer.
Facilitators/Inhibitors
The sources of knowledge
Partner protectiveness
Partner transparency (openess)
Ease of access to knowledge
Knowledge connections
Secondments
Knowledge of staff at the interface
Partner assistance
Partner contribution
The recepient of knowledge
Prior knowledge/experience
Knowledge relatedness
Partner similarities
Absorptive capacity
Learning capacity/ability
Receptivity
Partner learning intention/objective
Need to learn
Learning intent
The knowledge attributes
Tacitness/Codifiability
Theoretical with/without cases
1990 Cohen &Levinthal
1993 Kogut & Zander
1996 Lyles & Salk
1996 Mowery et al.
1996 Wathne et al.
1996 Szulanski
1998 Lane & Lubatkin
1998 Clarke et al.
1999 Simonin
1999 Lyles et al.
1999 Moon
2000 Kale et al.
2003 Cavusgil et al.
1991 Hamel
1997 Inkpen & Beamish
1997 Makhjia & Ganesh
1997 Saxton
1997 Lei et al.
1997 Choi & Lee
1997 Baughn et al.
1997 Morrison&Mezentseff
1998a Inkpen
1998b Inkpen
1999 Love & Gunasekaran
1999 Hansen
1999 Liu & Vince
2000 Inkpen
2000 Nonaka et al.
2000 Beeby & Booth
2001 Parise & Henderson
2001 Tsang
2002 Hurley
2002 Mohr & Sengupta
Empirical/large sample data
o
x x
x
x
x
x
x
x
x
x
x
x
x
x
x
x x
x
x
x
x
x
x
x x
o
x
x
x
x
x
x
x
x
x x
x
x
x
x
x
x
x
x
x
x
x x
x
x
x
Specificity
x
x
Complexity
o
x
x
Ambiguity
x
JVcharacteristics (ex ante)
Cultural distance/difference
x o
x
x
Organizational distance/difference
o
x
Cultural alignment
x x
Asymetric contribution
x
JV characteristics (ex post)
Relationship strength
x
x
x
Relationship openess
x
x
Relational capital
x
x
Informal relationship
x
Trust
o
x
x
x
x
x
Management commitment
x
x x
x
x
Articulated goals
o
Information redundancy
x
x
No performance myopia
x
Conflict management
x
Control mechanism/Flexibility
x
x
x
x x
Reward system
x
x
x
Shared decision making
x
Learning Culture/Climate
x
Age
o
Duration of the partnership
x
Note: For studies using empirical large sample data, (0) denotes no empirical support; (x) denotes empirical support.
For theoretical studies or case studies, (x) denotes untested propositions.
52
2.5.1.2. Factors related to the acquirer of knowledge
Theoretically, the most prominent factor that has been argued to be a determinant of
knowledge acquisition is the prior knowledge or experience of the learner (Saxton,
1997; Inkpen, 1998a, b, 2000; Tsang, 2001). This factor, together with knowledge
relatedness (Inkpen, 2000) and partner similarity (Saxton, 1997) would form the
absorptive capacity (Cohen and Levinthal, 1990; Beeby and Booth, 2000), or
learning capacity (Makhjia and Ganesh, 1997; Parise and Henderson, 2001) or
receptivity (Hamel, 1991; Baughn et al., 1997) of the learner which is argued to play
a critical role in the effectiveness of learning from partner. Another theoretical
suggestion on the influencer of inter-partner learning with regards to the learner side
is the learner’s objectives or intention to learn (Inkpen and Beamish, 1997; Baughn
et al., 1997; Inkpen, 1998a, b; Mohr and Sengupta, 2002).
On the empirical side, prior knowledge and experience are found by Wathne et al.
(1996) and Simonin (1999b) to have positive impacts on the effectiveness of interpartner learning. Moreover, several authors have found that absorptive capacity or
learning capability has positive influences on the learning from partner in JVs
(Cohen and Levinthal, 1990; Lyles and Salk, 1996; Mowery et al., 1996; Szulanski,
1996; Lane and Lubatkin, 1998; Moon, 1999). However, Lyles et al. (1999) did not
find empirical support for this factor in their study of IJVs in Malaysia. As for
learning intent, Moon (1999) finds statistical support for the positive relationship
between learning intent of the learner and the effectiveness of learning from partner.
2.5.1.3. Factors related to knowledge attributes
The majority of recent studies recognize the role of knowledge tacitness in the
process of knowledge acquisition between partners. Makhajia and Ganesh (1997),
Lei et al. (1997), Inkpen (1998a, b, 2000), Parise and Henderson (2001) and Mohr
and Sengupta (2002) essentially agree that the degree of tacitness of knowledge is a
critical antecedent of knowledge acquisition. Explicit knowledge, due to its
codifiability, is easier to be acquired directly from another person or indirectly via
certain media means. In contrast, it is more difficult to acquire tacit knowledge
because it cannot be articulated and codified. Therefore, it can only be acquired
under certain conditions such as direct person-to person interaction, observation or
self-reflection.
53
Although being theoretically accepted by most authors as mentioned above, very few
empirical studies on the impact of the tacitness on the acquisition of knowledge are
found in the extant literature. In addition to the works of Kogut and Zander (1993)
and Szulanski (1996), Simonin (1999b) recently finds that the tacitness of knowledge
has important impact on the effectiveness of knowledge transfer through the
intervening construct of knowledge ambiguity. Moreover, knowledge specificity
which refers to the ease with which knowledge can be redeployed to alternative uses
and by alternative users without loss of productive value, has been found to have a
similar role with knowledge tacitness (Simonin, 1999a; Parise and Henderson, 2001)
but has been studied to a lesser extent.
2.5.1.4. Factors related to ex-ante characteristics
Essentially, the ex-ante characteristic that has been studied in the literature is the
cultural differences between partners at both national and organizational levels.
Authors who argued for the negative relationship between cultural differences (or its
related terms such as cultural distances, cultural alignment, etc.) and knowledge
acquisition include Choi and Lee (1997), Inkpen (1998a, b), Liu and Vince (1999).
This relationship has been supported empirically in the work of Simonin (1999b) for
a group (within a sample of 147 US-based firms) in which alliance partners have low
collaborative experience. However, Lyles et al. (1999) did not find statistical support
for this relationship in a study of IJVs in Malaysia. Choi and Lee (1997) argue for the
positive relationship between the extents of asymmetric contribution of partners to
the JV. This factor has gained empirical support in a study of Dussauge et al. (2000).
2.5.1.5. Factors related to ex-post characteristics
The first factor that is frequently mentioned is the relationship between partners in
which the emphasis is on the social aspect. Many of the previous studies have argued
for the impact of interpartner relationship during the IJV operation and the
effectiveness of knowledge acquisition. Hansen (1999) stresses that a strong
relationship would not only create a channel for knowledge flowing between partners
but also help lift the social barriers that impede the communication of knowledge
between partners. Inkpen (2000) considers relationship openness as one of the
determinants of the knowledge flow between partners. Likewise, other authors
specify inter-partner trust as an important requirement for knowledge transfer
54
(Baughn et al., 1997, Morrison and Mezentseff, 1997, Love and Gunasekaran, 1999,
Inkpen, 2000). The role of these factors on the knowledge acquisition has been
found to have empirical support in a number of studies using slightly different terms
such as relationship strength, relational openness, relational capital, informal
relationship or inter-partner trust (Szulanski, 1996, Wathne et al., 1996, Kale et al,
2000, Clarke et al., 1998, Cavusgil et al., 2003).
Other factors stemming from the organizational learning literature applied to IJV
have also been found. They include articulate goals and management commitment
(Choi and Lee, 1997, Morrison and Mezentseff, 1997, Inkpen, 1998a, Nonaka et al.,
2000, Hurley, 2002), information redundancy (Inkpen and Beamish, 1997, Nonaka et
al., 2000), performance evaluation and reward system (Inkpen, 1998a, Lei et al.,
1997, Love and Gunasekaran, 1999, Hurley, 2002), control flexibility and share
decision making (Makhjia and Ganesh, 1997, Saxton, 1997, Love and Gunasekaran,
1999, Hurley, 2002, Mohr and Sengupta, 2002). However, there are hardly any
empirical results in the extant literature to support the argument for the impact of
these factors on the knowledge acquisition in the IJV context.
Lastly, duration or age of the IJV has been argued to have an impact on interpartner
knowledge transfer (Mohr and Sengupta, 2002). However, Simonin (1999b) failed to
find empirical support for this relationship.
2.5.2. Research gaps
The growing interest in international joint ventures and in the learning organization
has evolved into a distinct line of inquiry which focuses on how organizations learn
from their partners and develop new competencies through strategic alliances
(Simonin, 1999b). The emergence of this stream of research is best captured by
recent investigations of:
-
How knowledge is managed in strategic alliances (Inkpen, 1997; Khanna et al.
1998; Tiemessen et al., 1997; Inkpen, 2000; Tsang, 2001; Wong et al., 2002)
-
How knowledge is transferred across partners (Appleyard, 1996; Baughn et al.,
1997; Choi and Lee, 1997; Dodgson, 1996; Mowery et al., 1996; Tiemessen et
al., 1997; Simonin, 1999b; Si and Bruton, 1999; Mohr and Sengupta, 2002)
-
How knowledge is acquired from the parents by the JV itself (Lyles and Salk,
1996; Lyles et al., 1999, Inkpen, 1998a,b; Love and Gunasekaran, 1999)
55
-
How knowledge about collaborating per se develops over time and impacts
collaborative outcomes (Doz, 1996; Powell et al., 1996; Simonin, 1997, Shenkar
and Li, 1999).
Simonin (1999b) identifies that the growing literature on this phenomenon is limited
on three important issues: 1) theoretical versus empirical, 2) outcome versus process,
and 3) focus on technology versus focus on marketing and other competencies.
Moreover, the current literature review identifies one more issue: 4) the examination
of knowledge in general versus examination of tacit and explicit knowledge
separately. It is realized that these issues are in line with those identified by EasterbySmith and Araujo (1999) which were presented at the end of the review section 2.2.7
on organizational learning in this chapter.
2.5.2.1. Limited amount of large sample empirical work
In contrast with the abundance of conceptual work (see Table 2.3) only a limited
number of large sample empirical work has focused on the role of knowledge in
international strategic alliances. Starting with organizational learning, Huber (1991)
and Fiol (1994) noted that there is an obvious need for hypothesis development and
testing. Likewise, Mowery et al. (1996) and Simonin (1999b) further state that
empirical research on interpartner learning and knowledge transfer has been
hampered by the widespread reliance on anecdotes and assertion, rather than on
statistical evidence.
2.5.2.2. Less attention to the process of knowledge acquisition
While much of the research has dealt with static theories of the firm and
investigations of structural questions, little research has focused on the process of
knowledge acquisition and on the barriers to successful learning (Crossan and
Inkpen, 1994). In the context of strategic alliances, this view is echoed by Doz
(1996), who concedes that much research attention has been directed to trends in
alliance formation, determinants of cooperation, forms of collaborations, and alliance
outcomes instead of process-related questions. Even studies focused on learning and
knowledge acquisition have tended to favor the examination of the role of certain
variables such as strategic intent and motives (Hamel, 1991; Glaister and Buckley,
1996), organizational capabilities (Lyles and Salk, 1996; Pucik, 1988), partner
selection (Makino and Delious, 1996; Tiemessen et al., 1997) and/or trust (Aulakh et
56
al., 1996; Dogson, 1996; Inkpen, 1997). In an effort towards developing a more
integrative framework of facilitators of interpartner knowledge transfer, Lyles et al.
(1999) and Simonin (1999b) have attempted to take a number of factors into account
such as knowledge tacitness, partner protectiveness, assistance, learning capability,
etc. However, the empirical results only support partner assistance in the study of
Lyles et al. (1999) and learning capability, tacitness, specificity and cultural distance
in the study of Simonin (1999b). Other hypothesized factors did not receive
empirical support.
2.5.2.3. The emphasis on technology transfer
Studies of knowledge transfer and acquisition tend to favor technology knowledge
when empirical investigation is in order (Simonin, 1999b). The literature, particularly
on the empirical side, has generally dealt with the technology or technical capability
viewpoint (Appleyard, 1996; Hagedoorn and Schakenraad, 1994; Zander and Kogut,
1995). Of course, various types of knowledge and knowledge partitioning have been
addressed in the context of strategic alliances, ranging from organization-specific,
industry-specific, and market knowledge (Choice and Lee, 1997). Still, studies of
knowledge transfer turn almost invariably to technology transfer when empirical
investigation is in order (Simonin, 1999b). Recently, some authors did study
managerial learning in IJVs in China (Si and Bruton, 1999; Luo and Peng, 1999; Liu
and Vince, 1999) but the focus is not on facilitators of knowledge transfer.
2.5.2.4. Less attention to the codifiability of knowledge
Most of the previous studies have either analyzed knowledge in general as a whole or
have been interested only in tacit knowledge (Cavusgil et al., 2003). Another trend is
that the tacitness of knowledge is considered as a moderating factor (Hanvanich,
2002; Griffith et al., 2001; Simonin, 1999b). The investigation of both explicit and
tacit knowledge, to our knowledge, has not been undertaken simultaneously and
empirically before.
2.5.3. Issues addressed by the current research
The identification of the above mentioned research gaps provide the opportunity for
scholarly enquiries which are addressed in the current research. Specifically, the
current research tackles the following five issues.
57
Firstly, the current research focuses on the acquisition of knowledge from partners.
Specifically, it is interested in the examination of knowledge acquisition from the
foreign partner by the local partner in IJVs in Vietnam, a developing country in the
South East Asian region. Moreover, it attempts to examine several facilitators of the
knowledge acquisition which are taken simultaneously in an integrate model.
Secondly, the knowledge of particular interest in this research is marketing knowhow. This is to emphasize the importance of acquiring this type of knowledge by
firms in developing countries. It also addresses the type of knowledge which is
deemed to be more difficult to learn through IJVs due to its cultural and social
embededness (Wong et al., 2002). Thirdly, the acquired know-how is to be examined
through two distinct constructs, namely explicit marketing know-how and tacit
marketing know-how. An investigation is also made to determine whether theses two
constructs are related with each other. Fourthly, the current research tries to examine
the linkage between knowledge acquisition and its outcomes within the IJV setting.
Given that there are different or even contradictory views on the subject of
organizational learning, this issue becomes more complicated in the case of IJVs due
to the diverse purposes of learning in an IJV (Tsang, 1999). In addition to the
separation of tacit and explicit marketing know-how, it is expected that the results
would give more insights about the impact of each form of knowledge on the
learning outcomes in IJVs. Lastly, the current research adopts a quantitative
approach using a large sample survey. It also tries to test (in a different context i.e. of
IJVs) those hypotheses proposed in previous studies which have a strong theoretical
basis but were either not tested empirically and/or failed to obtain empirical support
(Lyles et al, 1999; Simonin, 1999b).
58
CHAPTER 3
CONCEPTUAL FRAMEWORK AND HYPOTHESES
3.1. INTRODUCTION
The previous chapter has provided a review of the literature related to organizational
learning, IJV, and knowledge acquisition in IJVs. This chapter goes to the specific
domain of the current research which is the acquisition of explicit and tacit marketing
know-how from the foreign partner by the local partner in IJVs.
This chapter is structured as follows. The next section presents a review of marketing
know-how which is the specific knowledge of interest in this current research. Then,
section 3.3 is devoted to the discussion of the acquisition of two distinct forms of
marketing know-how namely, explicit and tacit. The remaining two sections present
the explanations and arguments leading to the proposed hypotheses. Section 3.4
presents the theoretical arguments for the impact of each antecedent construct on the
acquisition of explicit and tacit marketing know-how. It further argues for the
positive relationship between the acquisition of explicit and tacit marketing knowhow. Lastly, section 3.5 argues for the relationships of explicit/tacit marketing knowhow and two proposed constructs representing the outcomes of learning from the
foreign partner in an IJV.
3.2. MARKETING KNOW-HOW
Marketing knowledge is a specific domain of management knowledge, which is
frequently described as a subject of learning intent of partners in JVs (Hamel, 1991;
Si and Bruton, 1999; Danis and Parkhe, 2002). It is a kind of practical knowledge
which consists of declarative knowledge or “know – what” and procedural
knowledge or “know – how” (Simonin, 1999; Hackley, 1999; Gronhaug, 2002). As
for the epistemological dimension, there are two kinds of knowledge: explicit
knowledge and tacit knowledge (Polanyi, 1966).
59
3.2.1. Marketing know-how versus know-what
The dimensions of know-how and know-what are based on the philosophical division
of knowledge suggested by Ryle (1959, cited in Simonin, 1999b). Knowing-how
relates to procedural knowledge, which is understood as knowing how to do
something (Kogut and Zander, 1993, 1995; Nonaka, 1994). In the marketing domain,
procedural knowledge consists of problem-solving procedures (Hackley, 1999). On
the other hand, knowing-what or declarative knowledge refers to information or
factual statements (i.e. knowing what something means). Examples of marketing
know-what include declarative statements such as descriptions of the business
environment, consumer behaviors and/or cultural traditions (Choi and Lee, 1997;
Inkpen and Beamish, 1997). In contrast, examples of marketing know-how include
procedures to launch a new product, to implement a marketing communication
campaign and so on (Hackley, 1999).
Marketing experts must possess knowledge of marketing facts (know-what) and must
also know how to utilize these facts to solve marketing problems (know-how).
Hackley (1999) describes some marketing problems as follows:
− How to gather and select relevant information from the business environment
to make predictions about market opportunities.
− How to be innovative at a strategic level seeking new product opportunities,
which can form part of a strategic vision for the organization.
− How to communicate the benefits of marketing within the organization.
− How to optimize the marketing mix to achieve stated objectives.
These illustrations show that marketing is a field of managerial practice. Professional
expertise in solving these marketing problems requires substantial knowledge
including marketing facts and procedures. Facts (know-what) about the empirical
world may elucidate or furnish the heuristic search, but in and of themselves cannot
solve problems and therefore cannot offer a model for a rational problem-solving
science (Hackley, 1999). In contrast, marketing procedures (know-how) serve as a
guide to solve those problems, which result in certain marketing actions. These
procedural guides are based on normative models in the marketing domain and
specific theories-in-use developed within each firm. They are also based on personal
and/or group experiences which have been accumulated over time. It is noted that,
60
like any other practical discipline, marketing expertise manifests itself through how
effective it drives the firm to deal successfully with the reality so that the firm’s
objective is achieved. To be successful, the firm must be well aligned with its
external environment (Fiol and Lyles, 1985). In so doing, it is first required that the
firm understands the environment where it conducts its business. Then, the relational
relationships between the firm-related input factors and the potential outcomes
should be identified in that specific environment. Once these key relationships have
been established, marketing experts are able to know how to create appropriate
marketing activities for its expected outcomes. For example, upon knowing that
consumers in a specific market are excited by lottery, the marketing expert would
know how to select an effective promotional tool related to lottery so as to increase
the sales in a short time. By this process, the know-how element of marketing
knowledge contributes to the creation of a firm’s marketing competence. Without
marketing know-how, the managerial implications of marketing facts cannot be
interpreted and managerial marketing actions cannot be developed. The integration
of know-what and know-how in marketing is especially meaningful in the context of
IJVs in an emerging economy. While local partners are capable of knowing facts
about the local market including, for example, market demand, consumer preferences
and tastes and who their current competitors are, international partners are often
viewed as possessing procedural knowledge (or management skills) on how to
operationalize the marketing concepts within the firm, how to develop an effective
marketing strategy, how to prepare and execute a marketing plan, etc (Child and
Markoczy, 1993; Tiemessen et al., 1997; Si and Bruton, 1999; Luo, 1999; Tsang,
2001). A complementary integration of marketing knowledge between partners
would enrich the knowledge of the IJV via a transformation process (Tiemessen et
al., 1997), i.e. the local partner can learn marketing know-how and the international
partner can learn marketing know-what from its partner. In this context, the
marketing know-how learned from the foreign partner is of great value to the local
partner.
3.2.2. Explicit versus tacit marketing know-how
Polanyi (1958) classifies knowledge into tacit knowledge and explicit knowledge.
Tacit knowledge is defined as knowledge which is intuitive, unarticulated,
nonverbalized or even non-verbalizable. It is usually in the domain of subjective,
61
cognitive and experiential learning. In working life, there are many epitomes of tacit
knowledge such as intuition, rule-of-thumb, gut feeling and personal skills. It is very
difficult to codify tacit knowledge (i.e. put it into words), therefore, making it
difficult to communicate or share with other people. Its transfer between people is
slow, costly and uncertain (Grant, 1996). Explicit knowledge, in contrast, deals with
more objective, rational and technical knowledge. It is articulated knowledge, which
can be specified verbally or in writing, computer programs, patents, drawings or the
like. Consequently, explicit knowledge is systematic and easily communicated in the
form of hard data or codified procedures.
In the field of marketing, a part of its knowledge can be codified in popular texts.
Another part of the knowledge underpinning practical marketing expertise is tacit.
They are implicit in the day-to-day problem solving of marketing practitioners but
difficult to elicit from experts or to codify in public symbols (Hackley, 1999). This is
a problematic feature not simply of marketing but of every practical discipline
(Goranzon and Josefson, 1988; Polanyi, 1966). Hackley (1999) further points out
that, the tacit component also involves a cognitive dimension of marketing
knowledge. This cognitive dimension of tacit knowledge refers to the beliefs, ideals,
values, schemata, and mental models which are deeply ingrained in the human being
(Nonaka and Konno, 1998). Hackley (1999) argues that the publicly codified
knowledge of marketing provides the conceptual vocabulary for discourse among
practitioners, academics and the wider public. This public knowledge constitutes the
explicit component of marketing knowledge. However, this public knowledge does
not encompass the cognitive dimension of expertise in the marketing domain which
constitutes its tacit component. Hackley (1999) then suggests that besides the explicit
aspect, an appreciation of the tacit aspect of marketing knowledge might contribute
to the comprehensiveness of marketing knowledge.
The tacit dimension of marketing know-how refers to those particulars which are
omitted, to varying degrees, from abstracted theoretical descriptions, yet upon which
the successful accomplishment of practical marketing action depends (Hackley,
1999). Tacit know-how is closely related to the technical dimension of tacit
knowledge which refers to “the kind of informal personal skills or crafts” (Nonaka
and Konno, 1998, p.42).
Due to its socially complex nature, marketing know-how is generally characterized
62
by a high degree of tacitness. For instance, it is rather difficult to think of an easilycodifiable advertising know-how, explicit success formulas for product launches, or
clear, replicable blueprints for international market expansions (Simonin, 1999b).
Various terms have been used by scholars to characterize the tacitness of know-how,
for example, ambiguity - the degree of transferability of information, know-how,
competence, knowledge, or skills (Simonin, 1999b), and stickiness - the difficulty of
transferring knowledge as reflected in the incremental cost of transfer (Von Hippel,
1994; Szulanski, 1996). While some of the terms are defined clearly in the literature
and others are not, all of them reflect the difficulties in transferring, or acquiring tacit
knowledge.
However, it is worthy to note that although the tacit-explicit dichotomy of knowledge
is commonly adopted, there are two different views of tacitness. From the way
tacitness is measured, it seems that some scholars (e.g. Kogut and Zander, 1993;
Simonin, 1999a; Hanvanich, 2002, Cavusgil et al., 2003) view the body of
knowledge under investigation as a general/whole that has only one degree of
tacitness. In other words, the tacitness of the whole body of knowledge transferred
from one partner to the other can fit into one specific point in the tacit-explicit
continuum. In contrast, the current research adopts the view of Hackley (1999) who
advocates that the whole body of marketing know-how comprises many
elements/particles. Some elements/particles are tacit, and others are explicit. As a
result, the body of marketing know-how transferred from foreign to local partner
comprises two different parts. This view is also consistent with Inkpen and Beamish
(1997). In Table 3.1, Hackley (1999) provides examples of tacit and explicit
marketing know-how. It is noted that the term “skill” in the left column of the table is
intended to illustrate the different specificities in marketing practice. No attempt is
made to conceptually differentiate between skill and know-how in this table. The
table shows that to carry out certain marketing managerial task requires appropriate
marketing know-how that can be broken down into explicit and tacit know-how.
63
Table 3.1: Examples of explicit and tacit components of marketing know-how.
Marketing skill
Explicit know-how
Tacit know-how
Commissioning
research
Research methodology,
statistical techniques
Problem sensitive knowledge of when to use a
particular research method to yield a suitable
problem-solving heuristic; ability to negotiate on
internal budget and external research costs; the
political skill to “sell” research findings to
colleagues to justify desired strategy
Environmental
analysis
Analytical tools, data
sources
Intuitive ability to draw predictive inferences from
static models to form dynamic real-world
hypotheses; ability to generate ideas at strategic
level which create meanings for consumers and
which are within the production capability of the
firm
Product/brand
management
Accounting/finance
techniques, production
techniques, knowledge
of legal constraints on
advertising claims,
models of portfolio or
life cycle analysis
Intuitive sensitivity to market changes, creative
qualities in acting in an independent way to
establish product line adaptations/changes and
novel marketing communications themes; political
sensitivity to the personalities within the
organization; sensitivity to the organization’s
strategic vision
Communicating
the benefits of
marketing
within the
organization
Textbook accounts of
the marketing concept,
of marketing as the
“whole business seen
from the view of the
consumer”, of salutary
“marketing myopia”
type case histories
Skills of augmentation, persuasiveness, charm,
verbal analytical intelligence to go beyond
textbook platitudes in discussing marketing issues
(Source: Hackley, 1999)
In the current research, the separation between tacit and explicit forms of marketing
know-how has two implications. The first implication is concerned with the potential
value of each form of marketing know-how in the context of interpartner learning in
IJVs. As mentioned previously, the know-how consists of a combination of both tacit
and explicit knowledge. Because tacit and explicit know-how are mutually
complementary (Nonaka and Takeuchi, 1995), there will be a strong tacit dimension
associated with how to use and implement the explicit knowledge. This tacit
dimension is the “glue” that holds together the organizational routines associated
with the foreign partner's skills (Inkpen and Beamish, 1997). This form of tacit
knowledge is unique to the partner firm, which contributes to its advantage.
64
Therefore, it is very much likely that the tacit marketing know-how has greater value
to the learning firm in comparison with explicit marketing know-how (Inkpen, 1998).
The second implication is concerned with the ways for acquisition or learning of
know-how under the two different forms. Explicit know-how can be codified, and it
tends to be easily documented and more available in public discourse (Hackley,
1999). Therefore, it can be learned via various ways. It is this feature that makes it
easier to disseminate widely and less unique to the knowledge holder in terms of
creating competitive advantage. In contrast, tacit knowledge is obtained by internal
individual processes like experience, reflection, internalization or individual talents.
Therefore, it cannot be managed and taught in the same manner as explicit
knowledge (Herrgard, 2000). These attributes create the major difference in the
learning of the two forms of knowledge. While explicit knowledge can be transferred
via various ways, the transfer of tacit knowledge requires extended social contact
(Nonaka et al., 2000). The next section is devoted to a detailed discussion about this
matter.
3.3. ACQUISITION OF MARKETING KNOW-HOW
The major interest of the current research is the process in which knowledge is
moved from foreign to local partners in IJVs. The commonly used term in the
literature to describe this process is knowledge transfer. “Knowledge transfer is the
most common label used to describe the movement of knowledge between
individuals, groups or organizations” (Carlile, 2002, p.9). The concept of transfer has
its roots in mathematical information theory (Shannon and Weaver, 1949; cited in
Carlile, 2002) and can be found in the information processing approaches. However,
by the description of the process, knowledge transfer essentially means that “the
“receiver” reconstructs his/her version of the “supplier’s” process-of-knowing”
(Sveiby, 1996, p.381). As a result, when being transferred from one person to
another, knowledge is interpreted by the receiver’s existing stock of knowledge and
mental model. By this process, it may have different meaning and value. In other
words, a part of the knowledge may be transformed, and the knowledge may not be
in its original form any more (Brockmann and Anthony, 1998). In order to emphasize
the learning process from the learner’s point of view (i.e. the local partner), the
current research adopts the term “knowledge acquisition” (Inkpen, 2000; Tsang,
65
2002). However, there is no attempt in the current research to disaggregate the
transformation dimension of knowledge from the learning process itself. Therefore,
for conforming to the extant literature, the term knowledge transfer or learning is
used interchangeably with the term knowledge acquisition.
Given the above consideration, the current research defines knowledge acquisition as
the process and amount of knowledge that is moved from a foreign to a local partner
in an IJV. This definition bears the same implication with the definition offered by
Tiemessen et al. (1997), who refers to knowledge transfer in IJVs as “the movement
of knowledge between parent firms” (p.387). Indeed, as being described in section
2.4.3 of Chapter 2, the complete process of knowledge acquisition through IJV is a
multiple-phase process including transfer, transformation and harvesting (Tiemessen
et al., 1997). Each phase would be strongly associated with some salient facilitating
factors (Inkpen, 2000). However, the current research focuses only on the first phase
which is the acquisition of know-how from foreign to local staff within the IJV.
3.3.1. Acquisition of explicit marketing know-how
Makhjia and Ganesh (1997) advocate that the more codifiable the knowledge, the
greater the ability to structure that knowledge into a set of easily communicated rules
and relationships. Knowledge that is amenable to codification is more easily
transmitted in a relatively complete form. Such knowledge embodies all the
necessary information in a manner that can be readily utilized. As a result, explicit
knowledge is systematic and easily communicated in the form of hard data or
codified procedures (Inkpen, 1998). It can also be stored in a mechanical or
technological way, like in handbooks or information systems, databases, textbooks,
manuals or internal newsletters and can therefore be given in lectures for diffusion
(Herrgard, 2000).
In an IJV context, learning of explicit know-how from a foreign partner can be
through various forms such as formal training of local staff, sharing or dissemination
via formal channels, face-to-face informal training through working groups,
guidelines, and documents. The possible difficulties in acquiring explicit know-how
from foreign staff include unfavorable management style (Lyles et al., 1999),
learning capability of the local members (Cohen and Levinthal, 1990), unmotivated
local members, unwillingness of the foreign partner (Simonin, 1999b).
66
Indeed, the literature review shows that explicit learning from JV partners has
recently not attracted much attention from researchers in the field, even from those
who are interested in IJVs in developed countries. This is possible because
structured, explicit knowledge is easy to find, recognize and therefore easy to share.
This type of explicit learning can be undertaken by different methods as described
above (Herrgard, 2000). However, the situation would be different in IJVs involving
firms from developed countries partnering with firms in developing countries. In
these IJVs, explicit know-how does have a high value to the development of the local
workforce (Si and Bruton, 1999; Danis and Parkhe, 2002). In many cases, acquiring
explicit know-how is the aim of the local partner, besides tacit know-how. However,
most researchers did not investigate know-how under two different forms, tacit and
explicit know-how (Si and Bruton, 1999; Luo and Peng, 1999; Lyles et al., 1999;
Griffith et al., 2001; Danis and Parkhe, 2002).
3.3.2. Acquisition of tacit marketing know-how
Tacit know-how is hard to formalize and not easily visible. It is this attribute that
makes the communication of tacit know-how more difficult (Inkpen, 1998;
Brockmann and Anthony, 2002). In organizations, tacit know-how involves
intangible factors embedded in personal beliefs and experiences. It is acquired
through experience, which is often associated with the intensity of exposure to
certain activities (Luo and Peng, 1999). Diversity of experience may lead to more
opportunities for exploration of tacit know-how (March, 1991).
Herrgard (2000) argues that tacit know-how has to be internalized in the human body
and soul. Therefore, methods like apprenticeship, direct interaction and action
learning that include face-to-face social interaction and practical experiences are
more suitable for sharing of tacit knowledge. Similarly, Nonaka et al. (2000) stress
that tacit know-how typically involves a history of training and socialization. It is not
readily disentangled and transferred in codified form. The exchange of tacit
knowledge must rely on extended social contact. Brockmann and Anthony (1998)
even insist that tacit knowledge cannot be taught, trained or educated; it can only be
learned. “To learn tacit knowledge requires active contribution of the learner, and the
learning process takes time. On this road to tacit knowledge, there are many
obstacles that will obstruct or make the journey difficult” (Herrgard, 2000, p.361).
Likewise, Senker and Faulkner (1996) argue that since tacit knowledge cannot be
67
written down, it must be acquired by example or experience; that is, in “personembodied” form. In principle, all knowledge may be learned by personal interaction.
However, personal interaction or movement is (for the most part) the only channel by
which tacit knowledge can be acquired, while codified knowledge can be effectively
transferred in written form.
Herrgard (2000) points out that perception, language and time are considered the
main difficulties in sharing tacit knowledge. Perceptually, the characteristic of
unconsciousness entails a problem of people not being aware of the full range of
their knowledge. This kind of knowledge is so internalized that it has often become a
natural part of human behavior or way of thinking. Moreover, difficulties with
language lie in the fact that tacit knowledge is held in a non-verbal form. To
articulate something that seems natural and obvious is hard for most people. More
experience and deeper knowledge lead to higher tacitness of knowledge and to
greater difficulties in articulating the knowledge (Herrgard, 2000). Time also raises
difficulties for sharing or acquiring tacit knowledge. For developing the tacitness in
an individual’s work, it is necessary to experience and reflect on these experiences.
This process is time consuming. Consequently, the internalization of tacit knowledge
requires a considerable time period (Augier and Vendelo, 1999; Bennett and Gabriel,
1999). The rapid change rate in today's business world and working life calls for
continual lifelong learning. But still few organizations have reserved enough time for
learning to achieve tacitness (Herrgard, 2000).
It is therefore argued that the explicit and tacit components of marketing know-how
are associated with different enabling factors. Moreover, it would be reasonable to
raise the question about the interaction of tacit and explicit knowledge acquired by
the local partner in an IJV. Consequently, the investigation of tacit and explicit
know-how as two separate constructs would not only provide theoretical insights into
the phenomenon but also lead to more meaningful practical implications for IJV
managers.
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3.4. FACILITATORS OF MARKETING KNOW-HOW ACQUISITION
Various factors have been suggested in the literature to have an impact on learning in
IJVs. Inkpen (1998) suggests that several conditions influence alliance learning
which includes partner protectiveness, trust between partners, partner history,
learning connection, leadership commitment, no performance myopia, cultural
alignment. Wathne et al. (1996), in an empirical test of a model of the effectiveness
of learning from partner, find that openness, prior experience on related knowledge,
channel of interaction and trust are positively related to the effectiveness of
knowledge transfer between partners. On the other hand, Tiemessen et al. (1997)
suggest that several barriers are associated with each of the three knowledge
management phases in an IJV. In the knowledge transfer phase, barriers to actual
transfer of knowledge include learning capacity of individuals assigned to the IJV,
differences in organizational or country cultures, partner interaction and systems/
structures of the parent firms. Barriers to the transformation phase may include the
lack of sufficient knowledge to interpret the idiosyncrasies of the context, the
disagreements among local staff in the IJV in interpreting of the learned knowledge.
Barriers in the harvesting phase arise because individuals in the parent organization
have often had very little interaction with the IJV; therefore have difficulty
interpreting its highly specific and newly created assets.
However, most studies examine the impact of those factors on the acquisition of
knowledge in a common form without differentiating tacit from explicit knowledge
(Lyles and Salk, 1996; Inkpen, 1998b). The few studies that take into account the
form of knowledge have mainly emphasized the transfer of tacit knowledge only
(Simonin, 1999 a, b; Hansen, 1999; Cavusgil et al., 2003). Moreover, the acquisition
of knowledge through IJV is a multiple-phase process including transfer,
transformation and harvesting (Tiemessen et al., 1997). While scholars proposed
several facilitating factors, it is argued that not all of them effect the first phase of
knowledge acquisition. Therefore, this section presents factors that are thought to
impact on the acquisition of only one form of knowledge (either tacit or explicit) or
both tacit and explicit knowledge albeit at different levels. An integrative framework
(Figure 3.1) that includes facilitators and the two forms of knowledge would provide
a comprehensive picture. With this framework, the simultaneous effects of the
antecedent factors on each form of acquired knowledge can be tested empirically.
69
IJV
Management
Features
Management
Commitment
H1(+)
H1(+)
Teamwork
H2 (+)
Learning
Intent
Knowledge
Seekers
H3 (+)
H3
Learning
Capability
H2 (+)
H11
(+)
Acquired Explicit
Know-how
H4 (+)
H4
Marketing
Dynamism
(+)
H11 (+)
(+)
H12 (+)
H9 (+)
Partner
Assistance
Knowledge
Holders
H5 (+)
H5 (+)
(-)
H6
Knowledge
Protectiveness
H6 (-)
H7
Relationship
Strength
Matching
Factors
Acquired Tacit
Know-how
(+)
H10 (+)
H10 (+)
Marketing
Competence
Improvement
H7 (+)
H8
(-)
Note: The +/- signs indicate positive or negative associations.
H8 (-)
The arrows with unbroken line indicate stronger causal relations between the
two related constructs; whereas the arrows with broken line represent
weaker (or insignificant) causal relations.
Cultural
Distance
Figure 3.1: The conceptual framework
70
The facilitating factors are grouped into four categories. Borrowing the idea of
Szulanski (1996), the difficulties of knowledge transfer can be rooted to four sets of
factors, namely the characteristics of the source, the recipient, the context in which
the transfer takes place and the characteristics of the knowledge being transferred.
However, modification has been made to fit the objectives of the current research.
Accordingly, the term context is split into two categories. The first is “IJV
management features” to denote factors which can be directly influenced or
controlled by the IJV management. The second is “matching factors” to represent the
social/cultural congruence between the source and the recipient of knowledge that
IJV management has little or indirect influence (McDermott and O’Dell, 2001; Hennart
and Zeng, 2002). Thus, the four sets being introduced in the current research are:
− IJV management features: including IJV management commitment and
teamwork,
− Knowledge seeker or characteristics of the recipient (local partner): including
learning intent and learning capability,
− Knowledge holder or characteristics of the source (foreign partner): including
partner assistance and knowledge protectiveness,
− Matching factors: including relationship strength and cultural distance.
It is argued in the current research that while some factors are assumed to have an
impact on both forms of knowledge acquisition, others may mainly affect either tacit
or explicit learning. In Figure 3.1, the +/- signs indicate the positive or negative
associations. Whereas the broken/ unbroken lines indicate the relative strength of
association. The arrows with unbroken line indicate stronger causal relations between
the two related constructs, in comparison with the arrows with broken line
representing weaker (or insignificant) causal relations.
The framework examines also the relational links between acquired tacit and explicit
marketing know-how and two constructs, namely marketing dynamism and
marketing competence. These constructs represent the direct outcomes of
interpartner learning in IJVs, which will in turn, be antecedents of JV business
performances. A further question to be explored in the current research is whether
explicit or tacit know-how has a greater influence on each outcome construct.
It is noted again that the emphasis here is on the process of knowledge acquisition
71
from the staff of the foreign partner firm to the staff of the local partner firm. Other
phases of inter-partner learning such as transformation or harvesting (Tiemessen et
al., 1997) are beyond the scope of the current research.
3.4.1. IJV management features
The knowledge-based theory of the firm (Grant, 1996) recognizes that some firms
have a greater capacity to absorb, circulate and utilize information than others. In
regard to inter-partner learning in IJVs, Inkpen and Beamish (1997) and other
authors (Nevis et al., 1995; Nonaka and Takeuchi, 1995) agree that specific
organizational conditions can promote the process of learning and knowledge
transfer in IJVs. For example, Stonehouse et al. (2001), following Hedlund (1994)
argue that a flexible organizational approach to management is associated with high
capacity for organizational learning. Organizational flexibility promotes absorptive
capacity and the knowledge transfer process by encouraging greater receptivity of
organization members to new stimuli from the outside, by promoting collaboration
and exchanges of information within the organization, and by granting members
greater latitude in altering activity patterns and ways of doing things. From the
marketing point of view, Slater and Narver (1995) emphasize that a combination of
entrepreneurship, market orientation, organic structure, facilitative leadership,
decentralized strategic planning and a challenging external environment would
promote organizational learning. Likewise, Hurley (2002) summarizes the literature
and provides a list of learning facilitators:
− An emphasis on individual learning and development,
− Top management support of risk taking and treating failure as an opportunity to
learn,
− Management system that provides for an integrated interpretation of
information,
− Facilitative leadership that encourages flexibility,
− Top management nurturing good ideas, and
− Decentralization of decision making and low formalization.
A synthesis of the above-mentioned factors reveals that they can be clustered around
three groups: 1) management commitment to learning (entrepreneurship, facilitative
leadership, market orientation, emphasis on individual learning and development, top
72
management support of risk taking and treating failure as an opportunity to learn,
management system that provides for an integrated interpretation of information,
facilitative leadership that encourages flexibility, and top management nurturing
good ideas); 2) working organization (decentralization of decision making and low
formalization, organic structure, decentralized strategic planning), and 3) challenging
external environment. Based on this synthesis, the current research suggests that two
internal factors, management commitment and teamwork, are key factors
representing organizational features. The third factor, the challenging external
environment is beyond the scope of this research. The following sections present the
analyses on how each of these specific factors affects the acquisition of tacit and
explicit know-how in IJVs.
3.4.1.1. IJV Management commitment
Management commitment refers to the view, attitude and behavior of a firm’s leaders
in relation to knowledge and learning (Senge, 1990). Organizational learning theory
advocates that management commitment has a profound impact on the learning
organization (Lei et al., 1997). The essence of a leader's commitment is to develop
articulated goals and policies or managerial measures related to learning, to provide
the resources needed to achieve the goals, to evaluate performance and to celebrate
successes (Senge, 1990; Appelbaumn and Reichards, 1998; Ulrich et al., 1993).
Although these can be thought to create a favorable climate for interpartner learning,
it is argued in this section that they have stronger impact on the acquisition of
explicit rather than tacit know-how.
Articulated goals and milestones can facilitate knowledge acquisition in IJV (Nonaka
and Takeuchi, 1995; Lyles and Salk, 1996). Articulated goals foster knowledge
acquisition by focusing members upon the same vision or mission. Moreover,
articulated goals and plans provide a specific measure against which to evaluate and
adjust individual and collective actions and their outcomes, while at the same time
allowing JVs the freedom and flexibility to create their own implementation plans
and sub-goals. They also provide mechanisms for evaluating the state of collective
understanding and the efficacy of action and the new knowledge needed to correct
deficiencies or difficulties. Having an explicit, written frame for IJV organizational
goals and plans should selectively focus IJV employees on acquiring potentially
useful knowledge from the foreign partner (Lyles et al., 1999; Solingen et al., 2000).
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In the reality, leaders’ commitment is manifested by practices regarding knowledge
and learning. Mills and Friesen (1992) point out that commitment to learning
involves the development of means to foster learning from both internal and external
sources of knowledge. Internally, firms develop a variety of means such as projects,
seminars and discussions intended for discovering what individuals have learned and
experienced. Firms that are committed to learning tend to systematize its knowledge
base by codifying and documenting knowledge as well as making them accessible to
others through formalized practices and procedures. In addition, they also tend to
develop learning structures and strategies to support the learning process. One of
these structures is the evaluation mechanism and reward system (Love and
Gunasekaran, 1999; Solingen et al., 2000). Failures due to trying new things for
instance should not always be considered as negative performance so that employees
will be encouraged to try new working methods or solutions to problems. Such
measures would create an environment conducive to learning and knowledge
acquisition. However, these are more relevant for knowledge that can be codified
because the learning processes and outcomes are likely to be monitored and
evaluated against certain articulated criteria for management purposes. Whereas,
these are less appropriate when dealing with tacit knowledge because the acquisition
of tacit knowledge requires a social and inter-personal context. Even if there is a tacit
element of knowledge involved in these processes, it needs to be externalized to
become explicit knowledge while sharing with other people (Nonaka et al., 2000). As
a result, it is hypothesized that:
Hypothesis 1: Management commitment has a greater positive influence on the
acquisition of explicit marketing know-how than on the acquisition of
tacit marketing know-how.
3.4.1.2. Teamwork
Teamwork is an important part of an organizational learning process (Solingen et al.,
2000). It means that learning is established within groups that work together towards
a shared vision and mutual objectives. Joint formulation of learning objectives,
communication and information sharing, and drawing conclusions, together take
place within team learning. Simonin (1999b) asserts that knowledge transfer builds
74
on numerous individual exchanges whose success depends on the ease of
communication and ‘intimacy’ between the source and recipient of knowledge. This
section argues that teamwork would enable the acquisition of both explicit and tacit
knowledge.
In organic structured organizations that are featured by teamwork, individuals are
grouped depending upon the knowledge requirements of the task at hand. The
essence of a team-based organization is the recognition that members from each IJV
partner have chances of doing task collaboratively. Coordination is best achieved
through the direction of individual specialists, and the specialist coordinators
(managers) cannot effectively coordinate if they cannot access the requisite specialist
knowledge (Hong, 1999). By working in teams, knowledge can be shared among
members and there is also a better understanding of other individuals, of their needs
and how they work in different parts of the organization, encouraging knowledge
acquisition (Senge, 1990; Garvin, 1993). The flexibility in working processes and
teamwork provide a good environment for discussions among team members about
task-related issues. It therefore facilitates meaningful integration of specialized
knowledge and generalist knowledge to generate behavior (Achrol and Kotler, 1999).
Knowledge sharing in teams would be multiplied if it is associated with participative
decision making. To this end, Grant (1996) advocates that the quality of team
decisions depends upon their being based upon relevant knowledge. If the knowledge
relevant to decisions can be concentrated at an individual in the organization, then
centralized decision making is feasible, and knowledge sharing is consequently
limited. In contrast, empowerment and delegation of decision making are conditions
enabling learning behavior of participants (Hong, 1999). Once delegated, the
accountability and responsibility of knowledge holders are higher. The integration of
knowledge for decision-making occurs at lower levels, among those who possess
closely related knowledge, which provides enabling grounds for meaningful
integration as well as sharing. As a result, learning activities and sharing experiences
would be stronger through participative decision-making processes.
Teamwork creates good opportunities for the interaction of partner’s members within
the IJV. Love and Gunasenkaran (1999) postulate that an important factor of IJV
learning is the encouragement of interaction within IJV members. Partners of the IJV
should be able to receive and transmit information. They further assert that the
75
effectiveness of alliance learning will be dependent on frequent day-to-day contact
between members of the partnership. Moreover, the number of people belonging to
each partner and the intensity of their interaction would enable the coordination of
the effort, which results in better knowledge creation and exchange. A wide contact
area implies a multiplicity of contact points and channels between partner’s
members. As the contact area widens, the tacit knowledge acquired becomes multifaceted, and the relevance and credibility of the exchange would be improved
(Sharma, 1998). Herrgard (2000) points out that the need for face-to-face interaction
is often perceived as a prerequisite for diffusion of tacit knowledge. Through face-toface interaction in IJVs, partners talk to each other using a language and symbols that
they both understand. Also, Solingen et al., (2000) explain that by working in teams,
members have chances to observe and reflect repeatedly the practice of the other
members. As a result, teamwork facilitates both verbal as well as non-verbal
communication opportunities through which they can share both tacit and explicit
know-how.
It could be said that the relatedness of knowledge and experience among team
members (Inkpen, 1998b), the integration of individual knowledge and shared
problems of concern (Grant, 1996), frequent communication (Simonin, 1999a) and
frequent working interactions (Solingen et al., 2000) are key features of team
working that facilitate the exchange of knowledge in both forms among team
members. Therefore, within the specific context of the current research, it is
hypothesized that:
Hypothesis 2: Teamworking between foreign and local marketing staff has a positive
effect on the acquisition of both explicit and tacit marketing knowhow.
3.4.2. Knowledge Seeker (local partner)
The process of transferring and acquiring knowledge certainly involves two key
players, the knowledge holder and the knowledge receiver. The result of knowledge
acquisition depends upon the effort of both sides of which the learners play a more
important role. This is especially the case in adult learning where the learners’ intent
and capability are critical (Hurley, 2002). The review of previous studies show that a
76
number of factors are related to the learner’s side which have been identified as
determinants of learning effectiveness such as absorptive capacity (Cohen and
Levinthal, 1990), learning capacity (Lyles and Salk, 1996), prior knowledge/
experience (Simonin, 1999b; Wathne et al., 1996), learning intention or objective
(Inkpen, 1998), knowledge relatedness (Inkpen, 2000). A closer analysis of the
implications of these terms results in the suggestion of two underlying factors,
learning intent and leaning capability (Tsang, 2001; Baughm et al., 1997; Hamel,
1991; Mowery et al., 1996; Lyles et al., 1999; Moon, 1999; Makhjia and Ganesh,
1997). The following sections argue that the learning intent and the learning
capability of the local partner have a positive impact on the acquisition of both
explicit and tacit knowledge from its foreign partner.
3.4.2.1. Learning intent
Upon knowing that the foreign partner possesses valuable knowledge, the local firm
entering the IJV has different behaviors to that knowledge. In some IJVs, the partners
aggressively seek to acquire knowledge while in others; the partners take a more
passive approach to knowledge acquisition. A firm using an IJV as a substitute for
knowledge which it cannot create on its own may remain dependent on a partner and
thus, may place a relatively low value on knowledge acquisition. According to
Inkpen (1998) and Tsang (1999), a firm may enter into a joint venture with one or
more of the following three knowledge objectives. Firstly, it may want to learn how
to design and manage an alliance. Secondly, it may want to access and exploit certain
type of knowledge without wishing to learn it for their own use; and thirdly, it may
want to acquire knowledge from the other partner to enhance its own capability. The
interest of the current research is on the third type of knowledge objective, which is
the acquisition of knowledge from partner. Especially, it focuses on acquiring
marketing know-how from the foreign partner. Therefore, learning intent reflects the
local firm’s initial propensity to view collaboration as an opportunity to learn the
other firm’s knowledge and skills (Hamel, 1991). For example, in a study of
Hungarian – Western alliances, Danis and Parkhe (2002) stress that for Hungarian
partners, “learning new managerial methods was critical for survival in the
competitive and liberating local environment” (p.444).
In the current research, learning intent is defined as the extent of desire and will of
the local partner with respect to learning of the foreign partner’s marketing
77
knowledge (Tsang, 2002). Sometimes referred to as motivation to learn, learning
intent is an important factor which fosters learning (Mohr and Sengupta, 2002). This
is because “motivation drives cognition, and if cognition is not there, motivation may
help” (Kalling, 2003, p.122). Moreover, learning intent is likely to be the major
driving force behind the resource allocated for learning (Kalling, 2003). Likewise, “a
strong motivation to learn represents the first important step in removing
organizational barriers that may hinder the allocation of resources for the learning
purpose” (p.839).
From the adult learning perspective, when being motivated, local members would
spend their time and effort on learning and making enquiries (Hurley, 2002). They
would take opportunities to participate actively in formal training, to study carefully
documents, procedures and guidelines. They would communicate with foreign
partner and observe the partner’s behavior for knowing what they are doing, how
they handle things. They try to imitate their partner’s skills to improve their own
performance. They take initiative to handle the challenging tasks and problems under
the coach of the foreign staff who is assumed to be more superior. In the
collaborating process they spend time to share experience with their partner (Inkpen,
1998b; Tsang, 2001). All of these activities would help them acquire both tacit and
explicit knowledge from their foreign partner.
In the same vein, Hamel (1991) suggests that a partner's intent to internalize the
other's skills is a key determinant of learning. The stronger the intent, the higher the
chance that the partner will win the learning race because a desire to learn the other
partner's skills is often one of the major motives behind the effort and resources spent
for learning. Similarly, Tsang (1999) asserts that although learning intent is not a
necessary condition for learning, especially experiential learning, to take place, the
presence of learning intent in a company is the first step toward effective learning. A
company can learn better and faster if it has the intent to do so. The articulation of
learning intent would focus on a company's learning effort and heighten its
awareness of the need for learning. Particularly, a local partner with learning intent
would provide strong encouragement to the staff they send to work in the IJV. As an
organization can only learn through its members, personnel assigned to an IJV are
important agents of learning for the partners (Tsang, 1999). Therefore, it is
hypothesized that:
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Hypothesis 3: The learning intent of the local partner has a positive influence on the
acquisition of both explicit and tacit marketing know-how.
3.4.2.2. Learning capability
Besides learning intent, the notion of learning capability is specifically relevant to
knowledge acquisition in IJVs (Makhjia and Ganesh, 1997). In broad terms,
organizational learning capability represents “the capacity of managers within an
organization to generate and generalize ideas with impacts” (Ulrich et al., 1993,
p.60). This definition reflects the organizational process of creation or acquisition,
dissemination and utilization of knowledge to add value to the firm (Nevis et al.,
1995). However, in the context of this specific research which focuses on the
learning from IJV partners, the term learning capability bears a narrower meaning. It
is closely related to the concept of receptivity (Hamel, 1991) which indicates the
acquisition of knowledge from partner. Particularly, the learning capability of a firm
is defined as its ability to absorb new knowledge from its JV partner (Hamel, 1991).
An individual or organization with high learning capability is capable of internalizing
the other partner’s skills more effectively than the one with lower capability. Cohen
and Levinthal (1990) employ the term absorptive capability for a similar meaning.
They argue that the premise of the notion of absorptive capacity is that the
organization needs prior related knowledge to assimilate and to use new knowledge.
Thus, effective learning requires not only the combination of different types of
knowledge, but also the combination of present and past knowledge. Inkpen (2000)
points out that learning performance will be enhanced when the object of learning is
related to what is already known. Similarly, Powell et al. (1996) argue that
knowledge facilitates the use of other knowledge and what can be learned is crucially
affected by what is already known. As expressed by Brockmann and Anthony
(2002): “the more we know, the more we can learn” (p.439). These are congruent to
the term learning capability. In the current research, focusing on the first phase of
interpartner learning (i.e. knowledge transfer), the learning capability of individuals
seconded from local firm to the IJV is very important to the effectiveness of
knowledge acquisition, because this process heavily depends on the learner‘s part as
knowledge can only be learned, not transferred in its original form (Brockmann and
Anthony, 1998). That is, when being transferred from one person to the other,
knowledge is interpreted by the receiver’s existing stock of knowledge and
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experience. It may have different meaning and value in the new contextual setting.
Therefore, upon being transferred and integrated into the new individual’s mental
model, the knowledge could be transformed. This is the reason why the current
research prefers the term learning capability instead of adopting the term receptivity
although both imply the same meaning.
As indicated above, it is commonly agreed that the prior knowledge, learning skills
and experiences of the individuals selected to the partnership are critical in ensuring
that knowledge is moved smoothly, and that the same meaning and value are retained
during the acquisition. The receptor partner must be competent to receive and be
capable of interpreting and assembling the knowledge gained from the knowledge
holder. The knowledge and benchmarking skills of the receptor should be congruent
with the knowledge that is intended to be absorbed through the IJV (Saxton, 1997).
These conditions are most likely met in those IJVs where partners come from the
same industry or they are potential competitors. Previous researches have cited many
cases of IJV between rival firms in the same industry in developed countries such as
IJVs in the telecom/electronic or automobile industries, between Japanese, European
and US firms (Dussauge et al., 2000; Inkpen, 1997). In these cases, there is only a
small gap in the knowledge and experience of partner staff working together in the
JV. Therefore, with a learning intent, they are likely to be able to imitate their
partner’s knowledge and skills. However, in IJVs involving partners in the same
industry but from developed and developing countries (or between partners in a
vertical chain), the personnel in the latter countries may be significantly less
knowledgeable and experienced than in the former. Without a strong motivation and
a strong learning support, the acquisition of knowledge by the local partners in such
situations may yield only moderate results. In other words, the capability for
interpartner learning tends to be higher in IJVs between rival firms operating in
countries of the same level of economic/technology advancement than between firms
in developing and developed countries. These theoretical arguments have been
supported by an empirical research by Lane and Lubatkin (1998). Following Cohen
and Levinthal (1990), they tested the model of the effects of absorptive capability on
interfirm learning and found that a) the firm’s ability to recognize and value new
knowledge, b) ability to assimilate new knowledge, and c) ability to commercialize
new knowledge have a positive impact on knowledge transfer. Szulanski (1996) also
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found empirical support for the hypothesis that “lack of absorptive capacity of the
recipient” (p.36) is one of the most important barriers to knowledge transfer.
Applying to the learning of marketing know-how, it is hypothesized that:
Hypothesis 4: The learning capability of the local partner has a positive influence on
the acquisition of both explicit and tacit marketing know-how.
3.4.3. Knowledge holder (foreign partner)
The effectiveness of learning through IJVs does not solely rest on the learning intent
and learning capabilities of local members. It also depends on the source of
knowledge. As a prerequisite, the source must be richer in knowledge. That is,
foreign personnel who work at the contact points with the local partner must be
knowledgeable enough to form a knowledge gap between the transferor and the
transferee. Once being knowledgeable, these people are perceived by local members
as reliable and valuable sources of knowledge (Szulanski, 1996; Inkpen, 1998).
Within an IJV between foreign partners from more developed countries and a local
partner in developing or transitional countries, literature shows that there is
commonly a gap between the two in terms of management knowledge, which
includes marketing know-how (Tsang, 2001; Danis and Parkhe, 2002; Si and Bruton,
1999; Lyles and Salk, 1996). Consequently, it is assumed in the current research that
the foreign partner has more valuable marketing know-how than the local partner
(Inkpen, 1998). Apart from the knowledge gap, the effectiveness of knowledge
acquisition depends on the support and willingness of the foreign partner to fully
cooperate (Simonin, 1999b). This is because “knowledge must be accessible before it
can be acquired” (Inkpen, 2000, p.1030). Based on the review of literature, it is
proposed in the current research that two factors are important to the accessibility of
foreign partner’s knowledge: partner assistance (Lyles et al., 1999) and knowledge
protectiveness (Simonin, 1999 a, b).
3.4.3.1. Partner assistance
In the current research, partner assistance refers to the extent to which a foreign
parent provides assistance to the IJV management with respect to marketing
knowledge. It is based on the term parent assistance used by Lyles et al. (1999) who
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maintain that: “the extent to which a foreign parent provides assistance to the IJV
management will influence the effectiveness of the IJV” (p.6). Lyles et al. (1999)
comment that in order to maintain an acceptable level of managerial efficiency,
foreign parents must be prepared to transfer a significant amount of knowledge to the
local workforce. Assistance from the foreign parent is likely to be particularly critical
to human resource development of the local staff in IJVs.
The assistance in training of local employees by a foreign parent can be considered
as a vehicle for the transfer of management knowledge (Nonaka, 1994). As conduits
for knowledge, training programs can be important vehicles for establishing contact
between local employees and foreign employees. The degree to which a foreign
partner has explicit contribution in terms of training of the local workforce should be
positively associated with the degree to which an IJV acquires explicit knowledge
from its foreign parent (Simonin, 1999b).
In IJVs in developing or transitional countries, the foreign parent may be a vital
source of both tacit and explicit knowledge (Danis and Parkhe, 2002). In a study of
IJVs in China, Tsang (2001) suggests that the commitment of human resources made
by foreign investors is an important factor affecting the learning of local partners.
This commitment is evaluated in terms of the quantity and quality of expatriate
managers assigned to China. Likewise, Lyles et al. (1999) empirically found that the
degree to which the explicit contribution of a foreign parent with respect to
managerial know-how is positively associated with the degree to which an IJV has
acquired explicit knowledge from its foreign parents.
In Inkpen’s (1998a, b, 2000) view, the knowledge assistance of the foreign parent to
the IJV is practiced through the knowledge connection between the IJV and the
parent which is represented by foreign managers working in the IJV. Typically,
managers assigned by the foreign partner to the IJV in developing countries hold
various types of knowledge. In many cases of IJV in developing countries, these
managers will provide knowledge assistance by setting up systems and procedures to
solve problems or develop new ideas about the business based on previous
experience as well as newly learned knowledge through the IJV. Apart from those
activities, training and alliance-parent interactions including visits and tours of
alliance are deemed to provide knowledge assistance to the IJV (Inkpen, 1998a).
Moreover, as the quality of foreign personnel is concerned, Saxton (1997) stresses
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that at the interface of an IJV, the more knowledgeable the foreign personnel is, the
more valuable they may be as a source for knowledge assistance to the local partner.
Therefore, knowledgeable personnel accompanied with relevant social competence
would strongly facilitate the acquisition of knowledge by local members in an IJV.
The above-mentioned activities emphasize training and development of local
workforce as formal measures for enhancing the capability of the IJV human
resource. Therefore, it certainly provides facilitating conditions for learning of
explicit knowledge. However, these types of assistance do not provide incentives for
nurturing a climate that is featured by close social interaction and working
collaboration between partners. As a result, it is not associated with the acquisition of
tacit knowledge. Therefore, in this research, it is hypothesized that:
Hypothesis 5: Partner assistance provided by the foreign partner in an IJV has a
greater positive influence on the acquisition of explicit than that of
tacit marketing know-how.
3.4.3.2. Knowledge protectiveness
Knowledge protectiveness refers to the extent of hurdles caused intentionally or
unintentionally by foreign members that disrupt the communications between foreign
and local members in an IJV. Partner’s knowledge protectiveness can be attributed to
two reasons: the competitive nature of the partnership and the motivation of
knowledge holders. It is argued in this section that the level of foreign partner
protectiveness would affect the acquisition of both explicit and tacit knowledge.
When forming a JV, partners contribute their resources and competencies with the
expectation of enjoying the synergy of resource complementarity such as gaining
market power or improving efficiency. However, in a situation of high competitive
overlap between partners, there is a risk of competencies being imitated by the other
partner during the collaboration (Dussauge et al., 2000). Inkpen (2000) addresses this
issue as a concern of knowledge spillover which occurs when valuable firm
knowledge spills out to competitors, and competitors can use the knowledge to gain
competitive advantage. From a competitive viewpoint, a loss of knowledge by one
partner may result in the creation of a new or stronger competitor (Inkpen, 2000).
Therefore, one or all firms may be reluctant to share knowledge with its partner,
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which results in the protection of knowledge. This is particularly critical in situations
where knowledge contributes to the core competencies of the partner such as
technology know-how or management know-how. Thus, if the partner firms are
competitors or potential competitors, it seems reasonable to assume that they would
be protective of their knowledge resources (Inkpen, 1998; Wong et al., 2002). With
knowledge protection in mind, some partners can be less transparent or less open
than others (Hamel, 1991). This less transparency between partners can be achieved
through active means, such as the adoption of strict policies or shielding mechanisms
aiming at protecting key competencies (Inkpen and Beamish, 1997). Gatekeepers can
be assigned to filter information access and disclosure across organizational
boundaries. These mechanisms can restrict the flow of explicit knowledge from one
partner to the other, especially knowledge that is perceived to be valuable to the
holders. Moreover, the protective mind could hinder the acquisition of tacit
knowledge. For instance, through the astute partitioning of tasks and the intentional
arrangement for physical separation of foreign and local members, proprietary
technology can be protected from imitation (Baughn et al., 1997). This is because the
acquisition of tacit knowledge requires “continuous and intense contact between
individual members of the alliance partners” (Kale et al., 2000, p. 232).
Knowledge protectiveness also increases when the knowledge holders lack
motivation to share knowledge. Apart from the fear of losing core competencies to
the potential competitor, lack of motivation may be due to the fear of losing
ownership, losing a position of privilege, and inadequate rewards. Szulanski (1996)
points out that lack of motivation at the source of knowledge is likely a cause of
difficulty in knowledge acquisition. When partner’s members are not interested in
sharing their own knowledge, they are unwilling to devote time and resources
towards that end. This would hinder the sharing of practical know-how at both
explicit and tacit levels due to two reasons. First, this learning process requires time
and effort of foreign partner for knowledge externalization and documentation of
explicit knowledge. Second, it requires the inputs of the knowledge holders into the
iterations of observation-reflection-experiment-feedback of learners. As a result, the
acquisition of knowledge, both tacit and explicit forms, is affected seriously when
the knowledge holders lack motivation.
Although there is theoretical support to the argument that partner protectiveness is
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negatively associated with knowledge sharing between partners, there is a lack of
empirical evidence. Simonin (1999a, b) studied two samples of 147 and 151
multinationals in the US to examine the role played by the “causally ambiguous”
nature of knowledge in the process of knowledge transfer between alliance partners.
However, in both studies he did not find statistically significant evidence to support
his hypothesis that protectiveness is an antecedent of knowledge ambiguity, which,
in turn, contributes greatly to the effectiveness of knowledge transfer between
partners. Simonin (1999a, b) suggests that this result may be due to two factors. First,
partner protectiveness may not always be detectable or observable. Therefore, a
single informant approach to empirical data collection may have only contributed to
a partial view of the construct. Secondly, it may well be rooted in the close interplay
between protectiveness and opportunism and consequently between collaborative
viability and failure. That is, strong protectiveness is likely to lead to irreparable
conflicts and an early termination of the alliance. Whereas “most of the alliances
under study were still active, acute cases of protectiveness associated with failed or
failing alliances may not have been detectable” (p.615).
Apparently, this issue is worthy of further empirical testing. Thus, in the IJV context
of this research, it is argued that there is a negative association between partner
protectiveness and knowledge acquisition of the local partner.
Hypothesis 6: Knowledge protectiveness has a negative influence on the acquisition
of both tacit and explicit marketing know-how.
3.4.4. Matching factors
The term matching factors represents those IJV attributes that bind the partners in an
IJV. As mentioned earlier, the term “matching factors” implies the social/cultural
congruencies between the source and the recipient of knowledge. The literature
review shows that a number of related terms have been studied previously. For
example, cultural alignment and trust between partners (Inkpen, 1998); language and
customs barriers (Hamel, 1991); intimacy (Szulanski, 1996), relationship tie
(Granovetter, 1973), relationship strength (Cavusgil et al., 2003). Based on the
synthesis of these terms, the current research suggests two underlying constructs,
namely relationship strength and cultural distance.
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3.4.4.1. Relationship strength
Relationship strength (Cavusgil et al., 2003), its closely related concept of
relationship tie (Granovette, 1973), and relational capital (Kale et al., 2000) are core
characteristics of interfirm relationships (Morgan and Hunt, 1994). It is noted that the
term relationship strength discussed here has different implications from the
previously discussed concept of teamwork. In the discussion of teamwork, emphases
are placed on those “hard” issues caused by teamwork arrangement as a feature of
organizational structure such as the opportunities for frequent work interaction,
frequency of communication, and sharing of problems. In this section, the discussion
of relationship strength will focus on the “soft” aspects of interpersonal relationship
within the IJV such as trust, social ties, and quality of communication at subtle/noncodified levels (Cavusgil et al., 2003; Mohr and Sengupta, 2002). The following
sections will argue that strong relationships between partners would have a stronger
influence on the acquisition of tacit than explicit knowledge in an IJV. A strong
relationship between firms is necessary for knowledge acquisition because it
facilitates knowledge connections, which occur through both formal and informal
relationships between individuals and groups. These relationships serve as a conduit
particularly for knowledge acquisition to occur in tacit form (Inkpen, 1998). A direct
interface between partner members in an open-minded and a non-defensive climate
permits direct observation of operations and enables the gradual and experiential
learning that are essential for successful transfer of tacit knowledge (Osborn and
Baughn, 1990). Because tacit knowledge cannot be easily specified, partners who
have a close relationship with each other would have a better opportunity to detect
each other’s knowledge deficiencies and needs (Cavusgil et al., 2003). Strong ties are
more likely to promote in-depth communication and to facilitate the exchange of
detailed information between organizations (Kraatz, 1998).
In a strong relationship, both firms are closely integrated and the relationship is
treated as valuable and important by both partners. Both parties are willing to work
together to maintain the relationship and both have a desire to understand and satisfy
each other’s needs. In such a strong relationship, commitment and trust between
partners are key attributes (Morgan and Hunt, 1994) which are, in turn, positively
associated with shared values and open communication. Strong relationship is also
characterized by social ties among partners’ members. Social link enhances the
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opportunities for people in both sides to share feelings, emotions, social concerns,
collaborative experiences, and mental models through physical, face-to-face contacts
(Hutt et al., 2000). These informal engagements would encourage members from
different partners to develop another channel for knowledge connection and mutual
understanding (Awuah, 2001). Through the frequent dialogue among the members of
two firms in a trusting climate, knowledge in one firm is converted into shared terms
and concepts for the other firm. Thus, the tacit knowledge rooted in one firm is likely
to be transformed into another firm’s knowledge (Nonaka, 1994).
Moreover, the acquisition of tacit knowledge depends on the closeness of the two
partners because it is not likely to be complete within the first time of interaction. It
needs the source firm’s assistance at a later time. Based on the feedback from the
recipient, the source could provide more detailed instructions on the nature of the
knowledge and make it easier for the recipient to understand the knowledge
(Cavusgil et al., 2003). This kind of give-and-take requires open-mindedness and a
non-defensive attitude. Open-mindedness is a necessity for the transfer and
acquisition of tacit knowledge. It enables the source to know the problems exactly
and provide suggestions accordingly. If the source does not get an accurate feedback,
the remedy provided would not be proper. The transfer of tacit knowledge is
therefore unlikely to be successful (Mohr et al., 1996). Here, the climate of openness
appears to be one of the most crucial prerequisites for tacit knowledge acquisition
(Inkpen, 2000). It opens a context in which local members are willing to learn from
their foreign members and willing to discuss underlying problems and experience
(Solingen et al., 2000; Love and Gunasekaran, 1999).
Similarly, Hansen (1999) explains that when the knowledge being acquired is tacit
and context dependent, an established strong relationship between the parties
concerned is likely to be beneficial. In a strong tie, the source is likely to spend more
time articulating the complex knowledge because strong ties often allow for a twoway interaction between the source and the recipient. The two-way interaction
afforded by a strong tie is important for assimilating the non-codified knowledge,
because the recipient most likely does not acquire the knowledge completely during
the first interaction with the recipient but needs multiple opportunities to assimilate it
(Polanyi, 1966). Two parties that are strongly tied tend to have developed a
relationship-specific heuristic for processing non-codified knowledge between them.
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In contrast, in weak ties, the necessary interactions for transferring knowledge are
limited. The recipient has to interpret and transform the non-codified knowledge,
often in the absence of further explanations, because the source is less likely to
engage in two-way interactions. When problems occur and questions arise, the
source is not immediately available. Even if the source is available, the parties to the
transfer have not established a relationship-specific heuristic to communicate
knowledge between them, making the transfer effort more difficult. These obstacles
take time. They result in statements like "it would have been faster to do it
ourselves". The transfer may have become a burden, hampering the progress of the
project (Hansen, 1999). This explanation is empirically supported by Szulanski
(1996), who finds that an arduous relationship between the source and the recipient is
a serious barrier to knowledge transfer.
In summary, the discussion on the positive association between relationship strength
and acquisition of tacit knowledge between partner members relies on three
arguments. First, partner communication is more effective due to the exchange of
non-verbal symbols, highly subtle, low/non-codified language. They can understand
each other without using fully articulated language. They can even understand each
other through behavioral observations. This is particularly important in
communicating of contextually dependent messages. The messages can be in half
codified language and haft symbols like a stenography presented in symbols that
members create and share only for their own use in a specific context. Therefore, it is
argued that a strong relationship enables partner members in an IJV to understand
each other by using less or non-codified communication messages (Cavusgil et al.,
2003). The second argument is the openness to share. A strong relationship enables
partner members to be willing and even to feel a need to share and communicate with
each other on matters beyond work issues. This is obviously a prerequisite to the
creation and delivery of messages to the recipient discussed above. As a result, the
sharing would attain the form of tacit knowledge. The third argument is the
willingness to help and to repeat instructions. This is important for acquiring tacit
knowledge because the acquiring process does not always occur smoothly through
direct observations or complex low-codified messages. The observing, imitating, and
practicing loop is more effective when the willingness to give feedback from the
source of tacit knowledge exists. All these three features clearly support the transfer
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of tacit knowledge between members in an IJV.
Applying to the specific context of the current research, it is hypothesized that:
Hypothesis 7. Relationship strength has a greater positive influence on the
acquisition of tacit marketing know-how than that of explicit
marketing know-how.
3.4.4.2. Cultural distance
Cultural distance can be defined as the resulting vector of culture-based factors (i.e.
languages, values, norms or meanings) that impede the flow of information between
partners (Johanson and Vahne, 1997). In fact, Meschi (1997) emphasizes that most of
the problems encountered in international joint ventures can be traced back to
cultural factors, be they nationally or organizationally. For example, cross-cultural
conflicts between parents of different nationalities are often cited as reasons for the
high dissolution rates of IJVs (Hennart and Zeng, 2002). From inception onwards,
the partner’s national and organizational cultures have the potential to affect in depth
all aspects of collaboration, including the process of knowledge management
(Tiemessen et al., 1997). This view is also shared by Lyles and Salk (1996), who
report that not only conflicts but also cultural misunderstandings rooted in cultural
differences can minimize flows of information and learning. Similarly, Mowery et al.
(1996) comment that international alliances result in lower levels of knowledge
transfer than domestic alliances. They point out that cultural distance between
partners is a key obstacle to interfirm knowledge transfer.
Why does culture play such an important role in IJV learning? Hennart and Zeng
(2002) explain that individuals living in a particular country tend to share similar
values, and they bring these values to the firms for which they work. Thus, a firm’s
values are largely a reflection of its national culture, and IJV parents based in
different countries will tend to have different values. These differences in values will
in turn make it more difficult for them to understand and to communicate, especially
in highly subtle or contextual situations. Moreover, JV parents who come from
different countries will also have different mother tongues, and this can be expected
to cause communication difficulties. Verbal communication may suffer from both
perceptual and encoding/decoding gaps. Moreover, while these problems should not
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be underestimated, those involved in interpreting nonverbal cues are even more
serious. Failures of IJV members to quickly learn about each other may lead to
misunderstandings and suspicion, and eventually to lower commitment and trust
(Hennart and Zeng, 2002). As for Simonin (1999), cultural distance matters with
regard to learning for two reasons. First, cultural distance raises barriers for
understanding partners. In this respect, the lack of fluency in a partner’s native
language may constitute the greatest obstacle since even well codified knowledge
remains inaccessible. Second, cultural distance creates difficulties in identifying the
values and meanings of nonverbal behavior of the partner’s members.
According to Lyles et al. (1999), cultural distance is thought to have an influence on
the effectiveness of partner interaction. The cultural distance in terms of meaning,
values, symbols and norms can be a hindering factor to the effectiveness of partner
communication. Since communication is an exchange of information in words, ideas
or emotions, true communication is only possible between people who, to some
extent, share a system of meaning. In the same vein, Simonin (1999b) argues that as
the cultural gap between the knowledge provider and seeker deepens, so does the
level of "noise" surrounding the understanding and communication of valuable
information. The partners' national cultures can significantly impact all aspects of
collaboration, including information flows (Lyles and Salk, 1996) and the process of
knowledge management (Tiemessen et al., 1997). Cultural misunderstandings can
minimize flows of information and learning. Lyles and Salk (1996) propose that the
greater the degree of cultural conflict for an IJV is, the lower the levels of knowledge
acquisition. Likewise, Szulanski (1996) argues that knowledge transfer is built on
numerous individual exchanges based on the communication and ‘intimacy’ between
the source and recipient of knowledge. Consequently, an arduous (i.e. laborious and
distant) relationship creates additional hardship in internal knowledge transfer. In a
broader view, Choi and Lee (1997) argue that the greater the differences between the
partners are in terms of, national and organizational culture, the greater the difficulty
of transferring knowledge through cooperative interorganizational relationships.
There is empirical evidence that cultural distance impacts knowledge acquisition. For
instance, in their study of knowledge acquisition from the parents to the JV, Lyles
and Salk (1996) find that the two-parent shared management joint ventures exhibit
the highest levels of knowledge acquisition. However, they caution that conflicts and
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misunderstandings may quickly erase these gains. Simonin (1999b) conducts an
empirical research on 147 international strategic alliances among which one partner
is a US based company. He finds that in alliances where partners have low
collaborative experience, difference in national cultures is an antecedent of
knowledge ambiguity, which in turn is one of the key inhibitors to the acquisition of
knowledge from partners.
While previous researches did not differentiate between the impact of cultural
distance on the transfer of tacit knowledge and that of explicit knowledge, the current
research tries to go further to argue that cultural distance would have a strong
negative impact on the acquisition of tacit knowledge rather than on that of explicit
knowledge. As previously mentioned, cultural distance creates difficulties in two
aspects, language and shared values/meanings. Although verbal communication may
suffer due to differences in language, this gap could be minimized by additional
efforts in the IJV once this difficulty has been recognized. Remedies such as local
parent sending bilingual staff, bilingual documentation in the IJV, etc. are possible to
help verbal communication between partners to be more effective. In contrast,
partner misunderstanding due to misinterpretation of values and meanings of
nonverbal cues are more serious. First, partner members cannot affirm or be affirmed
whether they are fully understood or agree with each other in a nonverbal
conversation or observation. Consequently, the loop of experimental learning and
feedback for acquiring tacit knowledge is broken out. Secondly, misunderstanding
may lead to suspicion and eventually to lower commitment and trust between
partners (Hennart and Zeng, 2002), which is in turn, harmful for the relationship tie
between them. As previously discussed, this may lead to the unwillingness to share
and interact with each other in the IJV.
In the specific context of this research, it is therefore hypothesized that:
Hypothesis 8. Cultural distance has a greater negative influence on the acquisition
of tacit marketing know-how than on that of explicit marketing
know-how.
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3.4.5. Relationship between the acquisition of explicit and tacit know-how
The process for acquiring explicit and tacit know-how evolves in a complementary
pattern. This section argues that the acquired explicit know-how would also facilitate
the learning of tacit know-how from partners. In other words, there is a positive
effect of the acquisition of explicit know-how on that of tacit know-how.
When members of an IJV first come to work, some type of explicit know-how is
acquired by the local from the foreign members. This is the type of know-how that is
well-structured, high in teachability, codifiability and low in complexity (Kogut and
Zander, 1993). Know-how having these attributes has been found to be acquired
easily at a high speed (Kogut and Zander, 1993). Moreover, explicit knowledge that
is close to the existing knowledge stock and prior experience of the learner is found
to be absorbed easily by the learner (Mohr and Sengupta, 2002). In this case, the
learner can use the existing mental model to understand and internalize the new
knowledge (Cohen and Levinthal, 1990). This results in the increase in an
individual’s stock of explicit know-how.
The increase in explicit know-how acquired from partner will lead to the
development of a more “common language” stock and shared knowledge base within
the specific working environment. This shared knowledge base helps reduce the
knowledge gap between the knowledge transferor and receptor. Consequently, a
wider range of problems can be shared among collaborative members. This creates a
propensity to develop social intimacy between partner members, which is an
antecedent of tacit knowledge sharing (Herrgard, 2000). Hence, with an
improvement of explicit knowledge, the learner is now capable of absorbing tacit
know-how more easily. This results in the increase in tacit knowledge. In addition,
when the stock of explicit knowledge increases, the learner is more capable and
likely to be involved in new and more complex problems. This provides chances for
closer collaborative work with the foreign members. Therefore, he/she has
opportunities to be exposed and to learn tacit know-how that is being practiced by
the foreign members (Cohen and Levinthal, 1990).
The above explanation is consistent with Beeby and Booth (2000) who argue that as
learning is cumulative, and as the learning capacity is dependent on the prior
knowledge and experience of individuals in the organization, knowledge acquisition
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needs to be built up slowly over time. Similarly, Lyles and Salk (1996) note that
knowledge acquisition can arise from the direct experience of the organization and
its members. Thus, history provides an important starting point for knowledge
development (Von Krogh et al. 1994).
Therefore, applying to the context of the current study, it is hypothesized that:
Hypothesis 9: The extent of explicit marketing know-how acquired from the foreign
partner has a positive effect on the acquisition of tacit marketing
know-how.
3.5. OUTCOMES OF LEARNING IN IJVs
As mentioned in the previous chapter, the outcome of learning in IJVs is one of the
issues receiving fewer consensuses in the literature on both strategic alliance and
organizational learning (Gulati, 1998; Calantone and Zhao, 2000; Inkpen, 1995). In
the organizational learning literature, the debate revolves around the notion that
learning should be measured through its process or outcome (Easterby-Smith and
Araujo, 1999). More than that, the measurement of learning in JV is more
sophisticated due to issues like who to measure (the JV or the parent firm) or what to
measure (learning process, learning outcomes or business performance). With the
current research’s focus on the acquisition of marketing know-how from foreign
partner by the local partner in an IJV, the following views are taken into
consideration.
Firstly, for the local firm the ultimate objective of learning from its partner is to
improve the local parent’s capabilities. Therefore, in the long run, learning from
partner in IJV must be able to help the parent develop competencies that have value
in the market. From the overall view, the success of learning from partner should be
addressed at the end of the “harvesting” process where knowledge is retrieved from
the already created and tested sources in the IJV, and then internalized into the parent
firm so it can be recalled and used in other applications (Tiemessen et al., 1997).
However, from the point of view of learning, which includes three phases (transfer,
transformation and harvesting), the short-term and direct measures of learning
outcomes at the end of each phase should be identified to enable the evaluation of the
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learning effectiveness of each phase. The current research focuses on the first phase
of learning from partner, which occurs within the IJV context. Thus, the measures of
learning outcomes for this phase should be related to the IJV context.
Secondly, the direct outcomes of learning should be emphasized (Sinkula et al.
1997). Although there exists the view that organizational learning should be seen to
have occurred when organizations achieve improved performance (Dodgson, 1996),
the changes in behavior could also be seen to be the more appropriate short-term
measure (Reynolds and Ablett, 1998; Sinkula et al., 1997). This is because IJV
performance is definitely a result of multiple antecedents of which changes in
behavior is only one (Glaister and Buckley, 1998; Lyles et al., 1999). Consequently,
the current research adopts the view of Dunphy et al. (1997). This view advocates
that when an individual, group or organization has learned some knowledge,
competence is developed which may be used continuously to achieve certain
purposes. These purposes may relate to the organization’s current and future
performance which is achieved not by the knowledge itself but by actions. The
actions are the manifestation of the competence which has been created by the
knowledge. “Competence underpins the quality of action and enhances the prospect
of improved performance.” (p235).
Based on this view, this research proposes two constructs to represent the direct
outcomes of inter-partner learning of marketing know-how in IJVs. They are
marketing competence improvement and marketing dynamism. The underlying
argument for the employment of these constructs is that once IJV members have
learned from their foreign partner, their improved competencies would be firstly
manifested in the IJV itself. The following sections will discuss the relationships
between each of these constructs.
3.5.1. Marketing competence improvement
The concept of a firm’s marketing competence used in this research is based on the
study of Harvey and Lusch (1997). It refers to the ability to create, gain access to,
and coordinate tangible and intangible assets of the firm to maintain its position in
the market place. Dunphy et al. (1997) contend that competence is a combination of
knowledge, technical skills and performance management skills. In marketing, the
competencies are frequently composed of a firm’s members’ abilities that allow it to
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respond effectively to the changing environment by the creation of appropriate
marketing programs.
Dunphy et al. (1997) argue that organizations are concerned with learning if it helps
them to perform better. Therefore, learning which is valuable to organizations is
embodied in competencies to do things better or do different things. In other words,
organizational learning is closely associated with developing and maintaining
competencies both to perform and to change the organization, to maintain or improve
performance. Similarly, Bogner et al. (1999) stress that organizational learning
processes play a key role in the creation, maintenance and exploitation of
competencies. Both individual and organizational learning processes help the firm to
keep existing competencies distinctive and to allow for the formation of new
competencies. The organizational learning in IJVs through the SECI processes
(Nonaka et al., 2000), including individual and group activities is a foundation for
sustaining and developing distinctiveness in competences (Helleloid and Simonin,
1994). In the same vein, Menon and Varadarajan (1992) utilized one of the most
widely used conceptualizations of knowledge utilization to explain the linkage
between knowledge acquisition and competence improvement in the marketing area.
Accordingly, once knowledge has been acquired or developed within an individual
or group, it can be utilized via three ways, namely instrumental use, conceptual use
and symbolic use. Instrumental use is the direct application of knowledge to solve a
policy problem. Conceptual use of knowledge is more indirect than instrumental use.
Knowledge relates to concepts, assumptions, models, and theories, which can enter
into managers’ orientations toward priorities, the manner in which they formulate
problems, the range of solutions they convey, and the criteria of choice they apply.
Symbolic use refers to the situation where knowledge is used more symbolically
beyond their specific context of creation. As a consequence, knowledge acquired
from partner members in an IJV would enable local members to be more capable in
coping with marketing tasks or problems by utilizing knowledge in one or more of
these three ways. In other words, their marketing competencies are improved along
this line.
Another explanation is provided by Bogner et al. (1999) who note that the outcome
of the learning process is the capacity for organizational action. When individual
knowledge is integrated into a collective knowledge base or organizational memory,
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the stored information from an organization’s history can be retrieved and translated
into action. Action is represented by the incorporation of managerial experiences into
the activities of organizations. The translation of new knowledge into action is the
basis for creating new skills that underpin a firm’s competitive advantage. Thus, as
an organization learns, it strengthens and possibly renews its core competencies
(Inkpen, 1997). Furthermore, continuous learning sustains competence by enabling it
to evolve through iterations of observing, learning and doing. Prahalad and Hamel
(1990) advocate an outcome view of learning that competences are the collective
learning in the organization. It is a snapshot in time of the relationship between
competence and learning. At any instance, existing competences are the outcomes of
the whole learning process. Bogner et al. (1999) further explain that the learning
literature can enrich our understanding of the process by which ongoing
improvement in competence takes place. An important distinction in understanding
when learning sustains competence is the difference between lower-level and higherlevel learning. Lower-level learning will most likely produce outcomes that rest
within a firm’s existing competitive frame of reference. By contrast, higher-level
learning requires changing the overall rules and norms rather than specific activities
and behaviors (Fiol and Lyles, 1985).
Although both tacit and explicit knowledge have been said to help develop
competencies, they play different roles in the process. As explained by Mohr and
Sengupta (2002): “Tacit knowledge forms the basis of core skills and competencies,
which on the one hand is harder to share and imitate than explicit knowledge due to
its deeply embedded nature, but on the other hand, potentially presents the greatest
value to the partners” (p. 291). This is because the tacit dimension is the “glue” that
holds together the organizational routines associated with the foreign partner's skills
(Inkpen and Beamish, 1997). This form of tacit knowledge is unique to the partner
firm, which contributes to its advantage. Therefore, it is very much likely that the
tacit marketing know-how has greater value to the learning firm in comparison with
explicit marketing know-how (Inkpen, 1998). Likewise, Lawson and Lorenzi (1999)
stress that tacit knowledge can be seen as the icing on the cake. Explicit knowledge
is important for competency building, but to achieve excellence in a job, one has to
master higher levels of knowledge, the unstructured and intangible tacit knowledge.
Even if explicit knowledge is easier to diffuse, the role of tacit knowledge is often
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essential for being able to use explicit knowledge. Explicit knowledge can even be
unusable without the augmentation provided by tacit knowledge (Shariq, 1999).
Brown and Duguid (1998) maintain that an organization's core competency is more
than the explicit knowledge of know-what; it requires the more tacit know-how to
put know-what into practice. Tacit know-how makes work go smoothly; it increases
the quality of the work, and it often characterizes a master of profession. The
efficiency of making decisions, serving customers or producing is improved by the
use of tacit know-how. Also the accuracy of task performance is improved by the use
of tacit know-how (Brockmann and Anthony, 1998).
Therefore, it is hypothesized that:
Hypothesis 10: Tacit marketing know-how acquired from foreign partner has a
greater positive impact on the improvement of marketing
competence than explicit marketing know-how.
3.5.2. Marketing dynamism
Most organizational learning theorists agree that organizational learning ultimately
manifests through internal and external organizational actions that reflect the
operationalization of behavioral changes (Fiol and Lyles, 1985; Garvin, 1993; Senge,
1990). In a marketing context, Sinkula et al. (1997) propose the concept of marketing
program dynamism (or marketing dynamism, in short) as a direct outcome of
organizational learning of marketing knowledge. Marketing program dynamism is
defined as the frequency at which marketing program modifications are made.
Sinkula et al. (1997) argue that marketing program dynamism may be the most
appropriate short-term and direct measure of organizational learning in the marketing
area. Whereas marketing performance may be a superior measure in the long run,
short-term market performance measures may be less capable of revealing active
learning behavior than marketing program dynamism because a change in market
performance is not a simple function of absolute organizational learning (Inkpen,
1997). The reasons for this are: First, before market performance changes can be
expected, absolute thresholds of improvement must be surpassed. Therefore, learning
may affect the dynamism of new product development or improvement without
affecting market performance. Second, the rate of learning within an organization
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must be at least equal to that of its competitors if changes in market performance are
to be expected. For these reasons, measures of market performance in the short run
may not reflect real improvements in the learning capabilities of an organization.
In the context of interpartner learning of marketing know-how within IJVs, the use of
marketing dynamism as a representative of the learning outcome of local marketing
staff is sophisticated to some extent. This is because the changes in marketing
program can be tracked back to three sources. Firstly, they may reflect the direct
application of new tacit and explicit know-how that local staff have acquired from
their partners. They represent the outcomes of specific activities and behaviors
resulting from low-level (single-loop) learning which does not necessarily change the
overall rules and norms as in high-level (double-loop) learning (Fiol and Lyles,
1985).
Secondly, marketing dynamism, if initiated or implemented by local staff, can be the
outcomes of learning through the improvement of marketing competencies of the
local members (Dunphy et al., 1997). It can go via two ways. Firstly, each change of
marketing program (initiated by local staff) could be seen as a means for learning
through a loop of feedback and self-reflection. In this situation, marketing dynamism
and improvement of marketing competencies go hand–in–hand within individuals
and within groups. Secondly, the newly learned tacit and explicit marketing knowhow may be integrated into the existing pool of knowledge and expertise that
currently reside within each member. The new inputs would provide new insights
that can cause change in the values of theory-in-use or changes in the underlying
system assumptions (as in double-loop learning) which result in the improvement of
problem-solving capacity (Dunphy et al., 1997). With improved competencies, local
marketing members would have a better ability to identify new marketing
opportunities or threats and develop better marketing actions by changing of
marketing programs.
The last source is marketing environmental changes. When there are changes in the
marketing environment, new knowledge (know-what) is created as a result of
information collection and processing. Therefore, if an IJV is operating in a more
challenging environment, it frequently faces new problems and new situations which
require the firm to respond more frequently by changing its marketing programs.
These changes may be based on the newly learned “know-what” rather than newly
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learned “know-how”, because the procedure applied to solve problems are the same,
only the inputs are changed (Slater and Narver, 1994; Sinkula et al 1997).
Consequently, it is hypothesized that:
Hypothesis 11: Both explicit and tacit marketing know-how acquired from foreign
partner have a positive impact on marketing dynamism.
Hypothesis 12: The improvement of marketing competence has a positive impact on
marketing dynamism.
In summary, sections 3.4 and 3.5 of this chapter have proposed 12 hypotheses
pertaining to the antecedents of the acquisition of explicit/tacit marketing know-how;
and the relationships of acquired explicit/tacit marketing know-how and the two
constructs of learning outcomes in IJVs. The following Table 3.2 concludes Chapter
3 by providing a summary of all 12 hypotheses that have been presented throughout
the discussions and arguments so far.
The next chapters will present how these theoretical hypotheses are supported or
rejected in the empirical world. Following this chapter, Chapter 4 describes the
research methodology. Chapter 5 addresses the process of assessment and refinement
of measurement scales. Chapter 6 presents the test of the whole theoretical model as
well as the hypotheses elaborated in this chapter.
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Table 3.2: Summary of hypotheses to be tested
H.
Statement of hypothesis
1
Management commitment has a greater positive influence on the acquisition of
explicit marketing know-how than on the acquisition of tacit marketing knowhow.
2
Teamworking between foreign and local marketing staff has a positive effect on
the acquisition of both explicit and tacit marketing know-how.
3
The learning intent of the local partner has a positive influence on the acquisition
of both explicit and tacit marketing know-how.
4
The learning capability of the local partner has a positive influence on the
acquisition of both explicit and tacit marketing know-how.
5
Partner assistance provided by the foreign partner in an IJV has a greater positive
influence on the acquisition of explicit than that of tacit marketing know-how.
6
Knowledge protectiveness has a negative influence on the acquisition of both tacit
and explicit marketing know-how.
7
Relationship strength has a greater positive influence on the acquisition of tacit
marketing know-how than that of explicit marketing know-how.
8
Cultural distance has a greater negative influence on the acquisition of tacit
marketing know-how than of explicit marketing know-how.
9
The extent of explicit marketing know-how acquired from the foreign partner has
a positive effect on the acquisition of tacit marketing know-how.
10
Tacit marketing know-how acquired from foreign partner has a greater positive
impact on the improvement of marketing competence than explicit marketing
know-how.
11
Both explicit and tacit marketing know-how acquired from foreign partner have a
positive impact on marketing dynamism.
12
The improvement of marketing competence has a positive impact on marketing
dynamism.
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CHAPTER 4
RESEARCH METHODOLOGY
4.1. INTRODUCTION
The previous chapter presents the model and hypotheses of this study which are
based on established theories and premises. However:
“Theories are required to be empirically testable in order that they be (a)
intersubjectively certifiable, (b) capable of explaining and predicting
phenomena, and (c) differentiated from purely analytical schemata” (Hunt,
2002, p.211).
Then comes the basic question: “To what extent is the theory isomorphic with
reality?” or “To what extent has the theory been empirically confirmed?” (Hunt,
2002, p.211). To address these questions, empirical testing is necessary which in the
current study is undertaken using a quantitative approach. In order to do so, it is first
necessary to operationalize the theoretical constructs so as to provide a basis for
developing the measurement scales. In essence, the operationalization of a construct
“links the language of abstract theory with the language of empirical measures”
(Neuman, 2000, p.160). Those tests are then logically linked back to conceptually
causal relations in the world of theory (Neuman, 2000).
Regarding the selection of empirical research setting, the theoretical deductions in
chapter 3 generally refer to IJVs between firms in developing countries and their
partners from more developed countries. However, it is not necessary to develop a
fully correspondent sample to represent the whole population of such IJVs around
the world. The reason is based on the scientific notion that: “Theories can be
conclusively falsified in the light of suitable evidence, whereas they can never be
established as true… theory acceptance is always tentative. Theory rejection can be
decisive” (Chalmers, 1982, p.60). As a consequence, the empirical setting for the
current research can be any developing country in the world.
Accordingly, the current research selects IJVs in Vietnam for its specific research
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setting. This selection is based on the fact that Vietnam is a developing and
transitional country which has been successful in attracting multinational investors.
Indeed, foreign direct investment (FDI) has been an important part of the economic
transition, business development and economic growth in Vietnam over the last
decade (Freeman, 2002). Furthermore, within the FDI flowing into Vietnam, IJV is
the popular form. In these IJVs, the foreign partners emanate from countries that
differ with respect to their level of economic development and national culture (Le
Dang Doanh, 2002). It is expected that these foreign investors would bring with them
marketing know-how as has been the case with countries such as s Hungary, China,
and Malaysia (Danis and Parkhe, 2002; Tsang, 2001; Si and Bruton, 1999; Lyles et
al., 1999). On the other hand, local firms enter IJVs with partnering motives
including the acquisition of capital, management skills, technical skills and access to
the foreign export markets (Le Dang Doanh, 2002). It is these underlying features of
IJVs in Vietnam that make them a suitable sample for the current research.
The next section describes and explains how the constructs comprising the
conceptual framework are operationalized and measured. It then proceeds to provide
a brief introduction of Vietnam’s economy and IJVs. The succeeding section
discusses the issues related to the unit of analysis and sampling. The chapter ends
with a description of the fieldwork procedure and data collection instrument.
4.2. MEASUREMENT OF CONSTRUCTS
Measurement is defined as “rules for assigning numbers to objects to represent
quantities of attributes” (Churchill, 1999, p.447). Measurement of constructs is
critical in scientific inquiry because the constructs must be related to observable data
if researchers are to accomplish their task of empirical testing. For quantitative
research, the measurement process is a straightforward sequence: “a researcher first
conceptualizes a variable. Next he or she operationalizes it. Lastly, he or she applies
the indicators in the empirical world” (Neuman, 2000, p.161).
Conceptualization of a construct is the process of taking a construct and refining it by
giving it a conceptual definition which is described in abstract, theoretical terms.
This conceptual definition often refers the construct to other ideas or constructs
(Neuman, 2000). In the current research, the conceptual definitions of the constructs
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are based on the process of thinking carefully about their meaning and reading what
others have said or defined (Neuman, 2000).
Operationalization of a construct refers to the process of “moving from the
conceptual definition of a construct to a set of specific activities or measures that
allow a researcher to observe it empirically” (Neuman, 2000, p. 515). This process
provides specific operations or things that people use to indicate the presence of a
construct in reality (Neuman, 2000). In the current research, the operationalization of
a construct is done by identifying what empirical dimensions comprise the construct
as its reflective or formative manifestations (Edwards and Bagozzi, 2000).
Then the next step is to review the extant literature to see what scales were
previously used by other researchers. In this review, the purpose is to assess whether
these scales cover all the dimensions of the construct as defined. Based on this
review, the decision is made regarding as to whether to adopt an existing scale as it
is, or modify it to fit the context of the empirical setting.
4.2.1. IJV management commitment
Management commitment refers to the values, attitudes and behavior of the JV
management towards organizational learning among members in the organization
(Senge, 1990). The measurement of this construct is based on its operationalization
which includes company vision that values learning and knowledge transfer,
developing means to foster learning, provision of resources needed to achieve the
vision, active involvement of company leaders in educational programmes and
celebrating success (Senge, 1990; Ulrich et al., 1993; Appelbaum and Reichart,
1998).
Sinkula et al. (1997), in a study of market-based organizational learning, used a four
item Likert scale to measure management commitment to learning. The scale
captures the extent that learning is recognized as a key organizational value for
survival and improvement, and as an investment, not an expense. However, the term
commitment to learning was used in this study to represent only the value of learning
i.e. “whether the value placed on learning activity can be viewed as axiomatic”
(p.309). Therefore, the current research adopts only one item from Sinkula et al.
(1997). This item is to measure the value of learning as one practical manifestation of
the IJV’s management commitment to learning. The other three items are ignored
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because they are less relevant to the focal construct. Moreover, rewording is
necessary to fit the item to the context of the current research which focuses on the
knowledge sharing or acquisition from partner. As a result, the original item “The
basic values of this organization include learning as a key to improvement” is
reworded to be “Our top management places value on learning as a key to employee
improvement”.
For the other operational manifestations of management commitment, no empirical
measures are found in the extant literature. Therefore, the development of measures
is based on the theoretical discussions on IJV management commitment presented in
chapter 3. Particularly, Mill and Friesen (1992) point out that commitment to
learning involves development of means and policies to foster learning from various
sources of knowledge. Appelbaum and Reichart (1998) emphasize the role of leaders
in the provision of resources needed for achieving the learning vision. Solingen et al
(2000) and Love and Gunasekaran (1999) stress that leaders committed to learning
would develop a mechanism for performance evaluation and reward system. The
evaluation mechanism emphasizes the working process and not the working
outcomes. The reward system encourages learning-related activities in the
organization.
Table 4.1: Indicators of management commitment
Code
Items
COM05
Knowledge transfer among staff has been a stated policy in our
company.
COM06
Our top management has developed a variety of means to facilitate the
transfer of knowledge among staff in the company.
COM07
Our top management has provided adequate resources for knowledge
transfer among staff in the company.
COM08
The reward system in this company encourages knowledge transfer
among staff.
COM09
In this company, staff performance is evaluated mainly on working
process and not on outcomes.
COM10
Our top management places value on learning as key to employee
improvement.
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Taking those reflective characteristics into the specific context of the current
research, the measurement of management commitment is designed to cover six
items measured in a 7 category scale anchored by 1: strongly disagree, 7: strongly
agree. The item wordings and their respective codes are presented in Table 4.1.
4.2.2. Teamwork
As described in chapter 3, the current research conceptualizes teamwork based on the
discussion of Hong (1999) which refers to the extent to which marketing staff are
working in teams and undertaking marketing tasks collaboratively. In operational
terms, teamwork covers two components, namely working arrangements as a result
of organizational structure (Hong, 1999) and the intensity of collaborative practices
(Grant, 1996; Sharma, 1998; Love and Gunasekaran, 1999). As no scale for this
construct was found in the literature, one is developed for this study. Based on the
theoretical discussions, the current research suggests a scale for teamwork which
includes five items. The first two items measure working arrangement (the existence
of a good teamwork and the frequency of undertaking tasks collaboratively). The
other three items capture the intensity of collaborative practices (participative
problem solving, variety of marketing tasks and extent of personal interaction). The
item statements are described in Table 4.2.
Table 4.2: Indicators of teamwork
Code
Item wording
TEA11
There is good teamwork between foreign and local marketing staff in
this company.
TEA12
Marketing tasks in this company are often undertaken collaboratively
between local and foreign staff.
TEA13
Group meetings/discussions involving both foreign and local staff are
a common way of solving marketing problems in this company.
TEA14
Teams involving both foreign and local staff have been dealing with a
large variety of marketing tasks in this company.
TEA15
Face-to-face or personal interaction between local and foreign
marketing staff is rare in this company
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4.2.3. Learning intent
Learning intent refers to the desire and will of the partner firm with respect to
acquiring the other firm’s knowledge and skills (Tsang, 2002; Story and Mohr, 1997;
Inkpen and Beamish, 1997). It is operationalized in terms of a) the extent to which
acquiring knowledge from one’s partner is an objective of the local partner, b) the
encouragement and resources given by local parent to staff working in the IJV and c)
the learning motivation of the local staff (Inkpen, 1998b; Baughn et al., 1997 and
Mohr and Sengupta, 2002).
Little empirical measures have been found in the extant literature. Mowery et al
(1996) used a two-category scale to measure learning intent indirectly. In this study,
Japanese firms were representative of higher-learning intent firms, while US firms
were representative of lower-learning intent firms. Another scale for learning intent
was used by Moon (1999) which was based on historical data. This study measured
the learning intent of marketing knowledge by the advertising intensity (i.e. the ratio
of advertising expenditure to the industry net sales) of the industry of a focal
alliance’s activity. The scales in those studies are inapplicable to the current research
due to the difference in the research settings and data collection methods. As a result,
a new scale is developed for this study.
Table 4.3: Indicators of learning intent
Code
Item wording
INT16
Acquiring marketing knowledge from our foreign partner is one of our
local partner’s objectives.
INT17
Our local partner encourages the local marketing staff to learn and
acquire our foreign partner’s marketing knowledge.
INT18
Our local partner has provided the necessary resources needed to
support the acquisition of marketing knowledge from our foreign
partner.
INT19
Our local staff want to imitate expatriates in how they undertake
marketing tasks in the JV.
INT20
Our local staff feel that they need to learn about marketing from our
foreign staff.
INT21
Our marketing staff have a strong interest in learning from our foreign
partner.
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Based on the operational definition of the construct the current research suggests that
the first item measures the extent that learning from partner is one of the objectives
of the local partner. The next two items measure the extent of encouragement and
resources provided by the local parent to the staff in the IJV for learning from their
partner. The last three items capture the extent of desire, need and interest of the
local staff to learn from the partner. These six items are presented in Table 4.3.
4.2.4. Learning capability
As defined earlier in chapter 3, learning capability refers to the ability of the learner
to absorb new knowledge from its JV partner (Hamel, 1991). It is operationalized in
terms of the closeness and relatedness of existing knowledge with the new
knowledge to be learned (Cohen and Levinthal, 1990; Huber, 1991; Hamel, 1991).
These closeness and relatedness are recognized by the prior knowledge/experience of
local staff working in the JV and their current stock of marketing knowledge.
The capacity to absorb new knowledge in IJVs was previously measured by Lyles et
al. (1999) using a three-item scale capturing the extent to which the IJV is flexible,
creative and adaptable to change. It is found that this scale reflects the empirical
manifestations that are different from the operationalization of the construct used in
the current research (i.e. being referred to prior knowledge/ experience of local staff
working in the JV and their current stock of marketing knowledge). Consequently,
this three-item scale could not be adopted in the current research.
In another study, Hanvanich (2002) used a five-item scale to capture the relatedness
of prior experience, the degree of promotion of creativity and application of newly
learned knowledge, and the diversity of members’ background. The first item
addressing the relatedness of prior experience is adopted in the current research
because it fits the first operational element of the construct. Other items were rooted
to Lyles et al. (1999). They therefore, are not suitable for the current research.
In addition, Simonin (1999b) used a two-item Likert scale which stated: “Your
company has committed a lot of personnel to this alliance” and “Your company has
committed a lot of physical, financial, organizational and logistical resources to
support the seeking, diffusion and sharing of information originating from this
alliance”. Similar to the above mentioned two scales, these items were not adopted in
the current research because they do not match with the defined components of the
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construct as described above. Rather, these two items seem to reflect the learning
intent of the local partner.
Given the specific context of the current research and considering the
operationalization described above, the measure for learning capability in this study
consists of three items. One item is adopted from Hanvanich (2002) to address the
relatedness of prior experience. The second item is newly developed to measure the
current stock of marketing knowledge. The third item is a global item about learning
capability in general. The detailed statements of items are described in Table 4.4.
Table 4.4: Indicators of learning capability
Code
Item wording
CAPA22 In general, our local staff have good learning capabilities.
CAPA23 Our local staff have previous experience in marketing similar products
or services.
CAPA24 Our local marketing staff are well educated (i.e. they have completed
formal university education in marketing).
4.2.5. Partner assistance
In the current research, the definition of partner assistance is based on Lyles et al.
(1999). It refers to the extent of assistance which relates to the marketing knowledge
provided by the foreign partner to the IJV. The construct is operationalized by the
amount and usefulness of marketing guidelines, documents, materials and other
forms of knowledge-related assistance provided by the foreign partner to the JV
(Lyles et al., 1999). It is also determined by the quantity of expatriate managers
assigned to the IJV (Tsang, 2001). Assigning a sufficient number of expatriate
managers to the IJV, especially at the initial stage of operation, seems to be
necessary for facilitating learning among local managers (Tsang, 2001).
In an empirical research, Lyles et al. (1999) measured partner assistance by the
extent to which the foreign partner provides expected support to the IJV in various
areas such as training, sales/ marketing, managerial resources, administration,
emotional support and time. The current research adopts two items from Lyles et al.
(1999) which address the extent of training programs and marketing guidelines,
procedures and materials provided by the foreign partner. Additionally, two more
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items are added so that the scale can cover all aspects of this construct. One item
measures the usefulness of those materials and training programs. The other item
measures the number of marketing staff assigned by the foreign partner to the IJV as
suggested by Tsang (2001). As a result, the scale for partner assistance is made up of
the items described in Table 4.5.
Table 4.5: Indicators of partner assisstance
Code
Item wording
ASS25
During the last three years, our foreign partner has been providing this
company with a lot of materials on procedures and guidelines for
marketing planning and decision making.
ASS26
The guidelines, procedures and training programs provided by our
foreign partner have been very helpful to our local marketing staff.
ASS27
In the last three years, our foreign partner has offered a lot of formal
training programs such as seminars and lectures in marketing to our
local staff.
ASS28
There have been many marketing personnel from our foreign partner
working in this company during the last three years.
4.2.6. Knowledge protectiveness
Knowledge protectiveness is defined in the current research as the extent of hurdles
caused intentionally or unintentionally by the foreign partner that disrupt the transfer
of marketing knowledge between partners. By capturing both intentional and
unintentional causes of information restriction, this conceptualization provides a
broader view than the one suggested by Simonin (1999a) who refers to this construct
as “the conscientious and intended state of information filtering” (Simonin, 1999a,
p.600). The operationalization of this construct, therefore, involves two components,
namely the restrictive policy of the foreign partner in regards to knowledge spilled
over to the other partner and the unwillingness of the foreign staff to share their
marketing expertise with the local staff.
Simonin (1999b) employed a two-item Likert-type scale which states: “Your partner
has intentional procedures, routines, and policies to restrict the sharing of relevant
information concerning its technology/ process know-how” and “Your partner is
very protective of its technology/ process know-how”. These two items are adopted
in the current research to measure the first operational component of the construct.
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Moreover, two newly developed items are added to the scale to reflect the second
component – the unwillingness of foreign staff to share their marketing knowledge.
As a result, the measures for knowledge protectiveness in this study are made up of
the following four items (Table 4.6).
Table 4.6: Indicators of partner knowledge protectiveness
Code
Item wording
PROT29 Our foreign partner has intentionally restricted the sharing of their
marketing know-how with our local staff.
PROT30 Our foreign staff have been very protective of their marketing knowhow.
PROT31 Our foreign staff are not willing to share their marketing know-how
with our local staff.
PROT32 Our foreign staff do not want to show to our local staff the procedures
they use in solving marketing problems.
4.2.7. Relationship strength
Relationship strength is defined as the extent of affective-based closeness between
foreign and local marketing staff in the IJV. The term “affective-based closeness”
refers to the “emotional bonds” suggested by Fryxell et al. (2002) which may be
characterized by the relational dimension of social interaction (Chua, 2002).
Accordingly, this construct is operationalized in terms of the level of relational
dimension of social interaction (Chua, 2002) and affective-based trust (Fryxell et al.,
2002).
Chua (2002) measured the relational dimension of social interaction using a ten-item
scale which captures trust, empathy, help, and lenient judgment of mistake, share
opinion, teamwork and sense of togetherness. Fryxell et al. (2002) measured
affective-based trust by a five-item Likert-type scale including: 1) the IJV partners
have a sharing relationship; they both freely share ideas, feeling and hopes about the
IJV; 2) IJV partner can freely talk to each other about difficulties they encounter with
the venture and both know that their concerns will be addressed; 3) IJV partners
would feel a sense of loss if the IJV were to be dissolved and they could no longer do
business together; 4) IJV partners would respond constructively and care their
partner’s concerns about the venture; and 5) IJV partners have made considerable
110
emotional investments in their working relationship. Moreover, Cavusgil et al.
(2003) measured relationship strength by a three-item Likert type scale capturing the
frequency of interaction, confidence in each other, and the desirability of maintaining
the relationship.
Based on those items, relationship strength is measured in this research by eight
items. Three items measure the relational dimension of social interaction. They are
statements about the desire to maintain a good social relationship (Cavusgil et al.,
2003), the sharing of a sense of togetherness, and the sharing of organizational myths
or stories (Chua, 2002). Five other items are used to measure the affective-based
trust. They are about the sense of trust (Chua, 2002), freely talking to each other,
freely sharing of ideas or feelings, supporting and caring to each other (Fryxell et al.,
2002) and confidence in each other (Cavusgil et al., 2003). The detailed statements
of these eight items are presented in Table 4.7.
Table 4.7: Indicators of relationship strength
Code
Item wording
REL33
Our foreign and local marketing staff have a desire to maintain a good
social relationship between them.
REL34
There is a sense of trust between our local and foreign marketing staff.
REL35
The local and foreign marketing staff in this company can freely talk
to each other about difficulties (in general) they encounter with the JV
and they know that their concerns will be addressed.
REL36
The local and foreign marketing staff in this company are confident in
each other’s marketing capabilities.
REL37
Locals and expatriates in marketing freely share their ideas, feelings
and hopes with each other.
REL38
The local and foreign marketing staff in this company are supportive
of each other. They respond constructively and caringly to their
partner’s concerns about the JV.
REL39
The local and foreign marketing staff in this company share a sense of
togetherness.
REL40
The local and foreign marketing staff in this company share
organizational myths or stories with each other.
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4.2.8. Cultural distance
Cultural distance is defined as the resulting vector of culture-based factors (i.e.
languages, values, norms or meanings) that impede the flow of information between
partners (Johanson and Vahne, 1997). This construct is operationalized by the extent
of problems caused by differences in culture and language between partners (Lyles
and Salk, 1996; Simonin, 1999b).
Lyles and Salk (1996) used a two-item scale that summarizes the extent to which
cultural misunderstandings and cultural differences have become issues of concern in
the IJV organization. Hanvanich (2002) measured cultural differences by partner’s
country of origin and general cultural difference. Partner’s country of origin is
measured by the country of origin. General cultural difference (or cultural
asymmetry) is measured by the extent of communication obstacles due to differences
in language, cultural value and behavior between two parties. Simonin (1999b)
employed two-item scale which stated: “The national culture of your partner greatly
differs from yours” and “Language differences are a major obstacle in
communicating with, and understanding your partner”.
It is found that the items mentioned above fit the operational characteristics of the
construct, except the measure identifying the country of origin used by Hanvanich
(2002). Therefore, in the current research, cultural distance is measured in a similar
way as that of Lyles and Salk (1996) and Simonin (1999b). Two items are to capture
the extent of cultural differences in general. The other two items are to measure the
extent of communication obstacles or misunderstanding due to cultural differences.
The actual statements and their respective codes for this construct are presented in
Table 4.8.
Table 4.8: Indicators of cultural distance
Code
Item wording
CUL41
The national culture of our foreign partner differs significantly from our
own culture.
CUL42
Language differences are a major obstacle in communicating with and
understanding our foreign marketing staff.
CUL43
Cultural differences have been a source of problems in this JV.
CUL44
Misunderstandings due to cultural differences have been a source of
problems in this JV.
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4.2.9. Acquisition of explicit marketing know-how
Acquisition of explicit marketing know-how refers to the extent of explicit marketing
know-how that the local marketing staff have acquired from their foreign partner in
the IJV. This construct is operationalized by the extent to which codifiable marketing
know-how has been acquired from the foreign partners via various ways or modes, as
perceived by the local marketing staff.
Lyles and Salk (1996) measured knowledge acquisition from the foreign parent
across a variety of areas. A seven-item Likert-type scale was used including “To
what extent have you learned from your foreign parent new technological expertise;
new marketing expertise; product development; knowledge about foreign cultures
and taste; managerial techniques and manufacturing processes”. This scale indeed
measured knowledge acquisition in a general sense without specifying any field of
knowledge. Moreover, no distinction was made between the explicit and tacit forms
of knowledge. Similarly, Simonin (1999b) measured the extent of technological
know-how transfer by three items namely “Your company has learned a great deal
about the technology/process know-how held by your partner”; “Your company has
greatly reduced its initial technological reliance or dependence upon the partner since
the beginning of the alliance” and; “The technology/ process know-how held by your
partner has been assimilated by your company and has contributed to other projects
developed by your company”. It is found that these items are related to the whole
process of learning from one’s partner in an alliance which include all the three
stages i.e. transfer, transform and harvesting as described by Tiemessen et al. (1997).
Moreover, Griffith et al. (2001) measured knowledge transfer, also with no
distinction between tacit and explicit, from foreign to local partner using five-items
stating that: “to what extent have you learned from your partner about new
technology expertise, new marketing expertise, new product development
techniques, new managerial techniques and new manufacturing processes”. This
scale is similar to the one developed by Lyles and Salk (1996) as described above.
With the emphasis being on the distinction between tacit and explicit marketing
know-how obtained from foreign partners and as there has been no previously
developed scale for this construct a new scale is developed for this research. This
scale is based on the various ways by which explicit knowledge can be acquired
(Herrgard, 2000; Inkpen, 1998) as discussed in Chapter 3. These ways include
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reading and understanding training materials, attending formal lectures, using
manuals, applying rules and procedures specified in writing. Accordingly, four items
in the scale are developed as shown in Table 4.9.
Table 4.9: Indicators of acquisition of explicit marketing know-how
Code
Item wording
During the last three years (or since the establishment of the JV if it is less than 3
years), our local marketing staff have acquired a lot of marketing know-how
by:
EXPL58
… reading and understanding training materials supplied by our
foreign partner.
EXPL59
… attending formal lectures conducted by our foreign partner
regarding different aspects of marketing.
EXPL60
… using manuals prepared by the foreign partner on how to undertake
different marketing activities such as market analysis, pricing,
advertising or making a sales presentation.
EXPL61
… applying rules and standard operating procedure specified in
writing by our foreign partner through memoranda and other
documents.
4.2.10. Acquisition of tacit marketing know-how
The definition of this construct is consistent with the way in which the acquisition of
explicit marketing know-how is defined. Acquisition of tacit marketing know-how
refers to the extent of tacit marketing know-how that the local marketing staff have
acquired from their foreign partner in the IJV. This construct is operationalized by
the extent to which non-codified marketing know-how has been acquired from the
foreign partners via various ways or modes, as perceived by the local marketing staff.
Cavusgil et al. (2003) measured tacit knowledge transfer by a four-item Likert-type
scale capturing the extent of complexity, codifiability and observability of the
information transferred. This scale could not be adopted in the current research
because it actually measured the extent of tacitness of transferred knowledge while
the current research measures the amount of tacit knowledge being transferred. No
other scale for the construct has been found in the extant literature.
Therefore, the current research develops a scale for this construct based on the
operational and theoretical definitions provided in chapter 3. It is characterized by
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various ways or modes by which tacit know-how can be acquired (Luo and Peng,
1999; Herrgard, 2000; Nonaka et al., 2000). Consequently, the measurement of the
construct is to capture the extent of non-codifiable knowledge acquired from foreign
partner which is addressed by four items as presented in Table 4.10.
Table 4.10: Indicators of acquisition of tacit marketing know-how
Code
Item wording
During the last three years (or since the establishment of the JV if it is less than 3
years), our local marketing staff have acquired a lot of marketing know-how by:
TACL63
… interacting closely with our foreign marketing staff.
TACL64
… collaborating closely with our foreign marketing staff in solving
marketing problems or in conducting joint projects (e.g. developing
new products or a promotion campaign).
TACL65
… observing how our foreign marketing staff solve problems or make
decisions.
TACL66
… adopting the rules of thumb or the intuitive approaches used by our
foreign staff in solving marketing problems.
4.2.11. Marketing competence improvement
As described in the previous chapter, the concept of marketing competence
improvement is based on the study of Harvey and Lusch (1997). It refers to the
improvement of the local staff’s ability to create, gain access to, and coordinate
tangible and intangible assets of the IJV to maintain its position in the market place.
Operationally, this construct is characterized by the extent of improvement of local
staff in their practical ability to undertake various marketing activities. This
operationalization is based on the notion that in marketing, competence is
demonstrated through the firm’s ability to respond effectively to the changing
environment by ways of appropriate marketing programs or actions (Dunphy et al.,
1997).
The current research develops a scale for this construct because no previous scale has
been found in the extant literature. A six item rating scale is proposed. The first four
items capture the extent of capability improvement of local marketing staff in terms
of various specific tasks such as obtaining and analyzing marketing information;
115
identifying market opportunities and threats; developing, implementing and
evaluating marketing programs. The last two items refer to the improvement of
capabilities in solving marketing problems and in making marketing decisions. The
specific statements are described in Table 4.11.
Table 4.11: Indicators of marketing competence improvement
Code
Item wording
Please indicate the extent to which the local marketing staff in your JV have
improved their capabilities during the last 3 years in each of the following
marketing activities:
IMP45 obtaining and analyzing marketing information
IMP46 identifying market opportunities and threats
IMP47 developing marketing programs
IMP48 implementing and evaluating marketing programs
IMP49 solving marketing problems in general
IMP50 making marketing decisions in general
4.2.12. Marketing dynamism
By the definition provided by Sinkula et al. (1997), marketing dynamism (or
marketing program dynamism in full) refers to the frequency at which marketing
program modifications are made. Sinkula et al. (1997) measured this construct
through three-items which capture the extent of changes in the organization’s mix of
products/brands, sales strategies and sales promotion/advertising strategies. The
current research adopts this scale with some modifications. The first modification
involves adding items pertaining to changes in pricing, sales promotion and
advertising programs. Second, two general items are added to capture the changes in
the company’s marketing activities as a whole and in its overall marketing strategy.
Third, in order to focus only on the local staff’s learning, the scale specifies a
condition that those changes are initiated by the local marketing staff. As a result, the
scale consists of seven items in seven-point rating form anchored by 1: never, and 7:
very often (Table 4.12).
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Table 4.12: Indicators of marketing dynamism
Code
Item wording
Please indicate how often the local marketing staff have initiated changes to each
of the following during the last three years:
DYN51 company’s mix of products or brands (e.g. add a new product or delete
an existing product).
DYN52 overall marketing strategy.
DYN53 sales management.
DYN54 pricing.
DYN55 sales promotion.
DYN56 advertising programs.
DYN57 company’s marketing activities as a whole.
In summary, the multi-item scales used to measure the twelve constructs comprising
the theoretical model of this study have been described (Table 4.16). As discussed
above, some of these scales are adopted from previous studies while others are newly
developed for the current research. The assessment of their reliability and validity is
presented in the next chapter (chapter 5). This chapter now turns to provide a brief
background about Vietnam, where the data is collected.
4.3. AN OVERVIEW OF IJVs IN VIETNAM
Vietnam is an emerging market located in the Southeast Asian Region. With a
population of almost 77 million inhabitants, it is the twelfth most populous country
in the world. At the same time, as one among the world’s poorest countries, the
country faces many challenges to get through a successful transition to a vibrant,
outward-oriented, market-based economy (Country Commercial Guide for Vietnam,
2000). In 1986, with its “doi moi” or “renovation” policy, Vietnam first articulated a
desire to undertake meaningful economic reform and integrate into the world
economy. The Vietnamese government has enacted laws to permit foreign-invested
sectors to develop.
Since first promulgating its foreign investment law in 1987, Vietnam has been very
successful in attracting foreign direct investment (FDI) into this developing,
117
transitional economy. Indeed, FDI has been an important part of the economic
transition, business development and macro-economic growth in Vietnam over the
last decade. By the end of the 1990s, although foreign-invested companies employed
less than 1% of the total workforce in Vietnam, they cumulatively accounted for
around 27% of the country’s (non-oil) exports, 35% of the country’s total industrial
output; they constituted almost 13% of Vietnam’s GDP, and contributed around 25%
of total tax revenues (Freeman, 2002).
A number of factors have contributed to the impressive rise in FDI inflow to
Vietnam during the first half of the 1990s. Firstly, foreign investors were stimulated
by the potential of its transitional economy and its largely untapped market of over
77 million people. Moreover, a number of positive attributes were identified,
including the strong work ethos, the high levels of education, yet relatively low labor
rates and plentiful resources. Initially, greater emphasis seemed to be placed on
servicing the domestic market, but over time more FDI activity relating to production
for export became apparent. In terms of sectoral distribution, Vietnam’s FDI stock is
relatively widely distributed. Fairly substantial foreign investment activities have
been found in diverse industries (Freeman, 2002). Table 4.13 shows the sectoral
patterns of FDI in Vietnam as at the end of 2001. It is noted that there may be more
recent data. However, it is very difficult to compile more recent comprehensive data
like those presented in the tables.
In terms of the home country of foreign investors, Table 4.14 shows that FDI flowing
into Vietnam comes from diverse nationalities. Among the ten biggest investors are
firms coming from both Western and other Eastern countries forming a wide variety
of foreign investors in terms of country of origin and national culture.
Regarding the FDI forms, the Law on Foreign Investment allows 4 forms: 100%
foreign, IJV, BOT (Building-Operating-Transferring) and Business Cooperation
Contract. Among these forms, IJV ranks second with 1043 projects as of the end of
2001. This accounts for 34.2% of total number of projects involved (Table 4.15). The
most dominant form is wholly foreign-owned investment projects which account for
61% of total number of projects.
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Table 4.13: Vietnam's FDI by Sector, as at end-2001 (active projects only).
Industry
- crude oil
- light industry
- heavy industry
- foodstuff
- construction
Agriculture
- agri and forestry
- aquatic
Services
- transport and telecomms.
- hotels and tourism
- finance and banking
- culture, health and educ.
- offices and apartment bldgs.
- EPZs and IZs, infrastructure
- others
Total
No. of
projects
1,985
28
791
789
165
212
382
326
56
679
95
120
48
105
112
15
181
3,046
Investment
(US$m)
20,878
3,176
4,383
7,804
2,353
3,162
2,145
1,971
174
14,838
2,786
3,273
543
561
3,694
795
721
37,861
% of
projects
65.2
0.9
26.0
25.9
5.4
7.0
12.5
10.7
1.8
22.3
3.1
3.9
1.6
3.4
3.7
0.5
5.9
100.0
% of
capital
55.1
8.4
11.6
20.6
6.2
8.4
5.7
5.2
0.5
39.2
7.4
8.6
1.4
1.5
9.8
2.1
1.9
100.0
Source: Le Dang Doanh (2002).
Table 4.14: Top Ten Sources of FDI Inflows in Vietnam (as at 2 July 2002)
No. of projects
Singapore
Taiwan
Japan
South Korea
Hong Kong
France
British Virgin Islands
Netherlands
Russia
UK
Total:
254
832
339
403
234
117
144
42
41
40
3,310
Capital pledged
(US$m)
6,908
5,298
4,119
3,462
2,819
2,040
1,759
1,656
1,506
1,172
38,527
Source: UNCTAD.
119
% of total capital
pledged
17.9
13.7
10.7
9.0
7.3
5.3
4.6
4.3
3.9
3.0
100.0
Table 4.15: FDI Formats in Vietnam, as at end-2001 (active projects only).
No. of
Projects
BOT
Bus.
Contracts
100%
owned
JV
Total
0.2
4.6
% of
capital
pledged
3.2
10.7
12,414
61.0
32.8
20,167
37,861
34.2
100.0
53.3
100.0
Coop
6
139
Total
Investment
(USDm)
1,228
4,052
foreign-
1,858
1,043
3,046
% of
projects
Source: Le Dang Doanh (2002).
In summary, IJV is the second most popular form of foreign investment in Vietnam
which numbers to 1043 projects (34.2% of the total number of projects) as at the end
of 2001. However, it ranks highest in terms of total capital investment, which
accounts for 53.26% of total FDI capital. Foreign partners come from diverse
countries in both the East and the West. Business operations are in almost all
industries of the economy. For those IJVs, a dominant part of local partners are stateowned companies. Their partnering motives include the acquisition of technology
and equipment, capital, management skills, technical skills and access to the foreign
export markets (Le Dang Doanh, 2002). These underlying features provide a suitable
setting for the current research.
4.4. UNIT OF ANALYSIS AND SAMPLING
The current research focuses on the first phase of interpartner learning, in which all
learning activities occur in the IJV itself. Therefore, the unit of analysis is the
international joint venture and the population of interest consists of all IJVs in
Vietnam. Moreover, the focal point is the acquisition of knowledge at individual
level from foreign members to local members in the IJV. After this phase, there are
further phases to “bring home” the knowledge acquired from partner and to integrate
them into the existing stock of local parent’s knowledge and then to make them
utilized (Tiemessen et al., 1997). However, these are out of the scope of the current
research. Additionally, being interested only in the marketing area, the focal unit
under investigation in each IJV is marketing. Only those IJVs that have marketing
activities managed and implemented by a marketing unit (division, department,
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group, or team) including both foreign and local staff working together are eligible
for the research.
In terms of the informant in each sampled IJV, the literature shows that there are two
methods, key informant and multiple informant method. Collecting data from
multiple informants within a firm may encounter issues like time, financial resources
and informants’ cooperation. Therefore, this method is less popularly used by
researchers (Wilson and Neilson, 2000). On the other hand, collecting data from a
single key informant is the most commonly used method (Kumar et al., 1993). This
approach deals with gathering data about the firm from a single person who is
knowledgeable about the issues under investigation. Given the nature of the current
research, which is largely based on perceptions, the most appropriate person to be
interviewed is the Vietnamese manager holding the highest position in marketing.
This manager is thought to be appropriate because he or she is the one who is most
knowledgeable about their partner firm, the IJV, its business environment and
particularly, the marketing operation. To ensure that he or she is truly
knowledgeable, it is required that he or she has at least three years experience with
the IJV or being with the IJV from the beginning, if the IJV’s age is less than three
years.
As far as the sample size is concerned, based on large-sample distribution theory,
structural equation modeling (SEM) requires a large sample size to obtain reliable
estimates (Joreskog and Sorbom, 1996). Particularly, Kline (1998) suggests that
sample sizes less than 100 could be considered small; between 100 and 200 is a
medium sample size. Sample sizes that exceed 200 cases could be considered large.
This suggestion provides a rough idea about the sample size for this study. Moreover,
the size should be considered in relation to the number of estimated parameters. An
empirical ratio of at least five observations per estimated parameter is proposed by
Hair et al (1998).
In reality, the 2002 Vietnam Business Directory shows that the number of IJVs
currently operating in Vietnam is 897 all-inclusive (which are slightly less than the
number given in table 4.15). In view of this, it was decided that all IJVs be included
in the survey. This size is considered reasonable and manageable, given the
potentially low response rate common to surveys.
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4.5. DATA COLLECTION
4.5.1. Questionnaire
The questionnaire was firstly designed in English which consists of four parts
(Appendix 1). The first part involves a short general description of the IJV including
industry, year of establishment and duration of the JV contract.
The second part of the questionnaire addresses the main theme, which asked about
all issues mentioned in the measurement of constructs. Scales for all items in this part
are seven-category rating scales in which only two polar points are labeled. The use
of seven categories (instead of the commonly-used five-category scale) is based on
the notion that reliability of the measures increases as the number of scale points
increases (Churchill, 1999). However, “as the number of scale steps is increased
from 2 up through 20, the increase in reliability is very rapid at first. It tends to level
off at about 7, and after about 11 steps, there is little gain in reliability from
increasing the number of steps (Nunnally, 1978, p.521, in Neuman, 2000). Regarding
the labeling of categories, rating scales usually have a pair of anchor labels that
define their two extremes. However, no rule exists for determining the number and
types of labels to include in a scale. Generating a simple and appropriate label for an
intermediate category is difficult. Leaving the category unlabeled is better than
making up an ill-fitting label for it (Parasuraman, 1991).
All constructs are measured by standard items (i.e. no item’s meaning was negated),
except one reversed item (TEA15) on teamwork. The use of reversed coded items is
designed to prevent informants from automatically agreeing or disagreeing with the
questionnaire items regardless of their content (Bagozzi, 1994). However, reversed
items are likely to produce artificial (i.e. unintended) factors in factor analysis
resulting from careless respondents (Schriesheim et al., 1991). In addition, three
items (KNOWLDG1, KNOWLDG2, KNOWLDG3) are included in this part to
measure the knowledgeability of the foreign marketing staff working in the IJV as
perceived by the informant.
The third part seeks demographic information about the IJV and its partners.
Questions on the IJV include foreign partner’s country of origin, capital contribution,
products/services, marketing responsibility and number of marketing staff, JV size
and sales, performance within the last three years. Questions about the local partner
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refer to industry, ownership, other existing businesses and partnerships. Questions
about the foreign partner pertain to country of origin, industry, number of IJVs in
Vietnam and all around the world. In case that the IJV comprised more than two
partners, the foreign partner to be asked about is the one who has joint marketing
collaboration with the local partner.
Lastly, part four of the questionnaire is concerned with information on the informant
him/herself, which includes job title, years with the IJV, and years of working/
marketing experience. The questionnaire ends with a section for free comments on
the interpartner learning practice within his/her IJV.
Before the final questionnaire was administered, a number of tasks were conducted.
Firstly, the English version of the questionnaire was pretested with three experts/
professionals in the field. The purpose of this pretest was to explore whether there
were ideas or aspects that the designed questionnaire had not captured or were
irrelevant.
Secondly, the revised questionnaire was translated into Vietnamese by a procedure of
translation and back-translation to ensure consistency in meaning. The translation
from English to Vietnamese was undertaken by one translator; and the back
translation from Vietnamese to English was done by another translator. The two
translators were university academics who are fluent in both languages. After
comparing the two English versions, mismatched points were discussed among the
two translators and the researcher. The Vietnamese version was then revised
accordingly.
Thirdly, the Vietnamese version (Appendix 2) was pretested on 5 Vietnamese
managers in IJVs, who were taking an evening MBA course in the HoChiMinh City
University of Technology. The purpose of this test was to check the wordings,
structure and configuration of the questionnaire.
4.5.2. Data collection procedure
As mentioned earlier, this was a nation-wide survey of all IJVs in Vietnam. Among
those techniques commonly suggested in the literature, mail survey proves to be most
appropriate given the resources available (Nguyen, 2000). Moreover, in order to
increase the response rate, face-to-face interviews were used for those IJVs located in
HoChiMinh city where the researcher resides.
123
For those IJVs in HoChiMinh city, telephone calls were first made to identify and
initially contact the target informants and to request for an appointment for interview.
Then, personal interviews using the questionnaire were undertaken. The interviewers
were a group of trained students, who were taking the marketing research course at
the School of Industrial Management.
For IJVs in Hanoi and other localities, in the initial stage, survey packages were sent
to target respondents by mail. The package included an introductory letter, which
was enclosed in the questionnaire, and a return stamped envelope. The letter first
introduced the purpose of the research, and requested for assistance by responding to
the survey. It then suggested the person who was most appropriate for answering the
attached questionnaire. Lastly, it assured that the information provided by the
respondent would be kept confidential, and that the results would appear only in
statistical forms. Then, telephone calls were made one week after the questionnaires
were sent to explain again the purpose of the research and to request for their
assistance.
The collected questionnaires were checked for completeness. It was found that some
questionnaires had a number of missing values for demographic questions, and
questions pertaining to company sales, relative growth of the IJV as compared to the
industry which are considered sensitive in Vietnam. But these are not really critical
to the current research. Almost all questions pertaining to the twelve constructs of the
study were answered (section II). This is the result of a monitoring process in which
interviewers were asked to check carefully the main section of the questionnaire
before closing the face-to-face interviews in HoChiMinh City. Consequently, all 194
questionnaires collected in HoChiMinh city were usable and without any missing
values in this section. In Hanoi and other localities, 33 questionnaires were returned
via postal mail. Of these, 6 questionnaires were found to be significantly incomplete
and 2 questionnaires has some missing values in section II. These questionnaires
were therefore discarded. As a result, 219 completed questionnaires were found
usable. The varying administering processes may cause some non-response bias.
However, it would not be significant because there were only 25 out of 219 cases
collected via mail survey (Nguyen, 2000; Nguyen, 2002).
These 219 questionnaires were further checked against the qualifying condition that
the marketing unit must be jointly managed by staff from the two partners. The result
124
shows that in 100% of the sampled IJVs, marketing activities are carried out jointly
by both partners. Other check was on the position of the informants: 43.7% of the
informants are marketing/business directors (or vice-directors), and 56.3% are
marketing/sales managers. On average, they have 5.7 years working in the IJV
(standard deviation = 2.63 years). These results indicate that the informants and the
IJVs in the sample meet the conditions set forth in the research design.
Those questionnaires that passed through this stage were considered eligible for the
data analysis. Data input was carried out using SPSS 10.0 software package.
Extraordinary values caused by mistakes during data entry were checked after this
stage. Exploratory factor analysis (EFA) and Structural equation modeling (SEM) are
the two major statistical approaches being employed for scale purification and data
analysis. These tasks were done using SPSS 10.0 and AMOS 5.0 software packages.
This chapter ends with a table summarizing the scales used for measuring the twelve
constructs in the current research (Table 4.16).
125
Table 4.16: Summary of scales for twelve constructs in the model.
Learning
Capability
Learning Intent
Teamwork
Management
Commitment
Const
Code
COM05
COM06
INT19
INT20
INT21
Item
Knowledge transfer among staff has been a stated policy in our company.
Our top management has developed a variety of means to facilitate the transfer of knowledge among staff in the
company.
Our top management has provided adequate resources for knowledge transfer among staff in the company.
The reward system in this company encourages knowledge transfer among staff.
In this company, staff performance is evaluated mainly on working process and not on outcomes.
Our top management places value on learning as key to employee improvement.
There is good teamwork between foreign and local marketing staff in this company.
Marketing tasks in this company are often undertaken collaboratively between local and foreign staff.
Group meetings/discussions involving both foreign and local staff are a common way of solving marketing
problems in this company.
Teams involving both foreign and local staff have been dealing with a large variety of marketing tasks in this
company.
Face-to-face or personal interaction between local and foreign marketing staff is rare in this company
Acquiring marketing knowledge from our foreign partner is one of our local partner’s objectives.
Our local partner encourages the local marketing staff to learn and acquire our foreign partner’s marketing
knowledge.
Our local partner has provided the necessary resources needed to support the acquisition of marketing knowledge
from our foreign partner.
Our local staff want to imitate expatriates in how they undertake marketing tasks in the JV.
Our local staff feel that they need to learn about marketing from our foreign staff.
Our marketing staff have a strong interest in learning from our foreign partner.
CAPA22
CAPA23
CAPA24
In general, our local staff have good learning capabilities.
Our local staff have previous experience in marketing similar products or services.
Our local marketing staff are well educated (i.e. they have completed formal university education in marketing).
COM07
COM08
COM09
COM10
TEA11
TEA12
TEA13
TEA14
TEA15
INT16
INT17
INT18
126
Source
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Sinkula et al. (1997)
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Hanvanich (2002)
Newly developed
Partner Assistance
Knowledge
Protectiveness
Relationship Strength
Cultural
Distance
ASS25
ASS26
ASS27
ASS28
During the last three years, our foreign partner has been providing this company with a lot of materials on
procedures and guidelines for marketing planning and decision making.
The guidelines, procedures and training programs provided by our foreign partner have been very helpful to our
local marketing staff.
In the last three years, our foreign partner has offered a lot of formal training programs such as seminars and
lectures in marketing to our local staff.
There have been many marketing personnel from our foreign partner working in this company during the last three
years.
Lyles et al. (1999)
Newly developed
Lyles et al. (1999)
Newly developed
PROT29
PROT30
PROT31
PROT32
Our foreign partner has intentionally restricted the sharing of their marketing know-how with our local staff.
Our foreign staff have been very protective of their marketing know-how.
Our foreign staff are not willing to share their marketing know-how with our local staff.
Our foreign staff do not want to show to our local staff the procedures they use in solving marketing problems.
Simonin (1999b)
Simonin (1999b)
Newly developed
Newly developed
REL33
REL34
REL35
Our foreign and local marketing staff have a desire to maintain a good social relationship between them.
There is a sense of trust between our local and foreign marketing staff.
The local and foreign marketing staff in this company can freely talk to each other about difficulties (in general)
they encounter with the JV and they know that their concerns will be addressed.
The local and foreign marketing staff in this company are confident in each other’s marketing capabilities.
Locals and expatriates in marketing freely share their ideas, feelings and hopes with each other.
The local and foreign marketing staff in this company are supportive of each other. They respond constructively
and caringly to their partner’s concerns about the JV.
The local and foreign marketing staff in this company share a sense of togetherness.
The local and foreign marketing staff in this company share organizational myths or stories with each other.
The national culture of our foreign partner differs significantly from our own culture.
Language differences are a major obstacle in communicating with and understanding our foreign marketing staff.
Cultural differences have been a source of problems in this JV.
Misunderstandings due to cultural differences have been a source of problems in this JV.
Cavusgil et al.(2003)
Chua (2002)
Fryxell et al. (2002
REL36
REL37
REL38
REL39
REL40
CUL41
CUL42
CUL43
CUL44
127
Cavusgil et al.(2003)
Fryxell et al. (2002)
Fryxell et al. (2002)
Chua (2002)
Chua (2002)
Simonin (1999b)
Simonin (1999b)
Lyles et al. (1999)
Lyles et al. (1999)
Improvement
MKT Competence
MKT Know-how
Know-how
Marketing Dynamism
Acquired Explicit
Acquired Tacit MKT
Please indicate the extent to which the local marketing staff in your JV have improved their capabilities during the last 3
years in each of the following marketing activities:
IMP45
obtaining and analyzing marketing information
IMP46
identifying market opportunities and threats
IMP47
developing marketing programs
IMP48
Implementing and evaluating marketing programs
IMP49
solving marketing problems in general
IMP50
making marketing decisions in general
Please indicate how often the local marketing staff have initiated changes to each of the following during the last three years:
DYN51
Company’s mix of products or brands (e.g. add a new product or delete an existing product).
DYN52
overall marketing strategy.
DYN53
sales management.
DYN54
pricing.
DYN55
sales promotion.
DYN56
advertising programs.
DYN57
company’s marketing activities as a whole.
During the last three years (or since the establishment of the JV if it is less than 3 years), our local marketing staff have
acquired a lot of marketing know-how by:
EXPL58 … reading and understanding training materials supplied by our foreign partner.
EXPL59 … attending formal lectures conducted by our foreign partner regarding different aspects of marketing.
EXPL60 … using manuals prepared by the foreign partner on how to undertake different marketing activities such as
market analysis, pricing, advertising or making a sales presentation.
EXPL61 … applying rules and standard operating procedure specified in writing by our foreign partner through
memoranda and other documents.
During the last three years (or since the establishment of the JV if it is less than 3 years), our local marketing staff have
acquired a lot of marketing know-how by:
TACL63 … interacting closely with our foreign marketing staff.
TACL64 … collaborating closely with our foreign marketing staff in solving marketing problems or in conducting joint
projects (e.g. developing new products or a promotion campaign).
TACL65 … observing how our foreign marketing staff solve problems or make decisions.
TACL66 … adopting the rules of thumb or the intuitive approaches used by our foreign staff in solving marketing
problems.
128
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Sinkula et al. (1997)
Newly developed
Sinkula et al. (1997)
Newly developed
Sinkula et al. (1997)
Sinkula et al. (1997)
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
Newly developed
CHAPTER 5
ASSESSMENT AND REFINEMENT OF
MEASUREMENT SCALES
5.1. INTRODUCTION
The previous chapter describes the research design, the operationalization of
constructs and the measurement scales used in this study. This chapter presents the
assessment and refinement of these measurement scales based on the data set of 219
cases. The first part describes the key characteristics of the sample. Then sections 5.3
and 5.4 present the background, procedure and results of the exploratory factor
analysis (EFA) and reliability tests. Sections 5.5 through 5.8 of the chapter discuss
the background, procedure and results of the confirmatory factor analysis (CFA)
which was undertaken to validate the measurement model. The final section presents
a summary of the validation process and results.
5.2. SAMPLE CHARACTERISTICS
As mentioned in the previous chapter, all 987 IJVs found in the 2002 Vietnam
Business Directory were contacted through either direct personal interview or postal
mail. After the checking process for usefulness, the sample is made up of 219 usable
cases. The response rate is 22%, which is considered fairly encouraging in the
Vietnamese condition where firms are not familiar with surveys. The following
sections describe the main characteristics of the sample.
5.2.1. Industry
The sample consists of 75 (or 34.2%) manufacturers of industrial goods, 74 (or
33.8%) manufacturers of consumer goods, 58 (or 26.5%) service providers, 9 (or
4.1%) trading companies and 3 (or 1.4%) companies operating in more than one
industry. These percentages reflect the industrial structure of the whole population
which is dominated by manufacturing JVs as described in Table 4.13 of chapter 4.
129
The sample, on one hand, reflects the population of IJVs in a developing country like
Vietnam. On the other hand, the fact that 68% of the cases in the sample are
manufacturing firms (industrial goods plus consumer goods) implies that the results
of data analyses may be more generalizable to manufacturing IJVs rather than
service IJVs.
Table 5.1: Sample structure by industry
Frequency
Percent
Valid Percent
Cumulative Percent
Industrial goods
75
34.2
34.2
34.2
Consumer goods
74
33.8
33.8
68
Trading
9
4.1
4.1
72.1
Services
58
26.5
26.5
98.6
More than one choice
3
1.4
1.4
100.0
100.0
Total
219
100
5.2.2. IJV’s age and duration
As shown in Table 5.2, the majority of IJVs in the sample have been established
within the last 12 years. Of the 219 cases, 13.7% are less than or equal to 3 years old,
39.3% are between 4 and 7 years old, 42% are between 8 and 12 years old, and only
5% are more than 13 years old. These figures reflect the real situation in Vietnam as
Foreign Direct Investment blossomed from the early 1990s, after the official
declaration of a general open policy in 1987 (Freeman, 2002).
With regards to the IJV duration, as stated in the respondents’ JV contracts, 10.4%
are for less than 15 years in duration, 72.5% have duration of between 16 and 30
years, while the rest (17.1%) are for a longer term.
Table 5.2: IJV’s age
≤ 3 years
Frequency
30
Percent
13.7
Cumulative Percent
13.7
3 - 7 years
86
39.3
53.0
8 - 12 years
92
42.0
95.0
> 12 years
11
5.0
100.0
219
100.0
Total
130
5.2.3. Country of origin of foreign partners
The sample consists of IJVs whose foreign partners come from different parts of the
world. Table 5.3 shows that 33.3% of the cases have foreign partners coming from
North America, Europe, or Australia; 34.2% from South East Asia region, including
Singapore, Thailand, Indonesia, Malaysia, Taiwan, ; 22.8% from Japan or Korea; and
9.7% from other countries. This sample structure reflects a good variation in terms of
cultural differences as well as economic and technological advancement compared to
Vietnam (Freeman, 2002).
Table 5.3: Sample structure by foreign partner countries
Categories
Frequency
Percent
Cumulative
percent
North America, Europe & Australia
73
33.3
33.3
South East Asia
75
34.2
67.5
East Asia
50
22.8
90.3
Others
21
9.7
100.0
Total
219
100.0
5.2.4. IJV size
Table 5.4 shows that the size of the sample IJVs, represented by annual sales in the
last three years (average), ranges from less than 1 million to more than 100 millions
USD. Of which, 7.7% have less than 1 million USD of sales, 38.5% from 1 to 5
million(s) USD, 41.7% have sales from 5 to 20 millions USD, 9% have sales from 20
to 100 and 2.3% have sales over 100 millions USD.
Table 5.4: Sample structure by company sales
Frequency
Less than 1 Mil USD
12
5.5
7.7
Cumulative
Percent
7.7
1-5
60
27.4
38.5
46.2
5-20
65
29.7
41.7
87.8
20-100
14
6.4
9.0
96.8
5
2.3
3.2
100.0
63
28.8
219
100.0
More than 100
Missing
Percent
131
Valid Percent
5.2.5. Number of foreign and local marketing staff
In most of the cases, there have been very few marketing expatriates working in the
IJVs. The statistics in Table 5.5 show that during the last three years, 1.5% of the
IJVs have no resident marketing expatriate; 64.3% of the IJVs have 1 - 2 marketing
expatriates; 26.2% have 3 - 5 marketing expatriates; only 4% have 6 -10 expatriates
and 4% have more than 10 marketing expatriates working in the IJVs. The statistics
are not much different at the present time as shown in table 5.5. Regarding the
number of local marketing staff working with the IJV during the last three years,
Table 5.6 shows that nearly one half of IJVs (42.7%) have 5-20 marketing staff;
31.6% of the cases have less than 5 staff and 11.4% of the cases have 20-50 staff;
6.5% of the cases have 50-100 staff. The percentages are similar at the present time.
Table 5.5: Number of foreign marketing staff in IJVs
0
1-2
3-5
6-10
11-20
>20
8
141
41
6
3
3
3.7
64.4
18.7
2.7
1.4
1.4
4.0
69.8
20.3
2.9
1.5
1.5
4.0
73.8
94.1
97.0
98.5
100.0
3
128
52
8
6
2
1.4
58.5
23.7
3.7
2.8
1
1.5
64.3
26.2
4
3
1
Cumulative
Percent
Valid
Percent
Percent
Frequency
Max during the last 3 years
Cumulative
Percent
Valid
Percent
Percent
At present
Frequency
Number
of foreign
marketing
staff
1.5
65.8
91.9
96.0
99.0
100.0
Table 5.6: Number of local marketing staff in IJVs
≤5
5-20
20-50
50-100
100-200
>200
65
86
23
15
10
6
29.6
39.4
10.7
6.9
4.7
2.8
31.6
41.8
11.4
7.3
4.9
3.0
31.6
73.4
84.8
92.1
97.0
100.0
132
62
86
23
13
11
6
28.3
39.4
10.8
5.9
5.1
2.8
30.9
42.7
11.4
6.5
5.5
3.0
Cumulative
Percent
Valid
Percent
Percent
Frequency
Max during the last 3 years
Cumulative
Percent
Valid
Percent
Percent
At present
Frequency
Number
of local
marketing
staff
30.9
73.6
85.0
91.5
97.0
100.0
5.2.6. IJV performance
In terms of the self-assessment of the IJV performance, 80.6% of the informants
think that their companies are doing well with performance ratings of 4 or 5 in a 1-5
rating scale, 18.1% of respondents rated their performance as average (score 3). Only
1.4% thinks that they are doing poorly.
In another rating scale measuring the companies’ growth compared to the average
growth of the industry as a whole, 9.6% think that they are well ahead of (rate 6 or 7)
competitors in the industry; 86.3% are doing fairly well (rate 4 or 5) and 4.1% think
that they are in a poor situation (rate 3). This result demonstrates that the majority of
IJVs in the sample are doing well, and enjoying better than average growth. This
may be an illustration of the outcome of various advantages of IJVs, such as
improving efficiencies, enhancing market power, sharing risk and learning (Calanton
and Zhao, 2000; Nicholas and Pincell, 2001).
5.2.7. Marketing knowledge of foreign partner
There was an unstated assumption in chapter 3 that the foreign partner and staff are
more knowledgeable than their local counterpart, so that the local partner has
something to learn from the foreign partner. The data collected supports the
validation of this assumption. Only 10.5% of respondents do not agree that their
foreign marketing staff is more knowledgeable than the local marketing staff. The
mean value is 5.22 and standard deviation is 1.11 (in a 1 to 7 scale). With 95%
confidence, this mean value falls between 5.07 and 5.37. Hence, this assumption can
be seen as reasonable.
5.3. ASSESSMENT OF MEASUREMENT SCALES - BACKGROUND
5.3.1. Unidimensionality, reliability and validity
Prior to model estimation, the multi-item scales developed in chapter 4 have to be
evaluated for their reliability, unidimensionality, and validity. Reliability of a scale
refers to how consistent or stable the ratings generated by the scale are likely to be
(Parasuraman, 1991). There are three main methods for assessing reliability. They
are test-retest, alternative-forms, and internal consistency methods. Within the
current research, however, the practicality and logic of administering the
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measurements make the test-retest (or stability reliability) and alternative-form
methods less feasible. Rather, the third method, internal consistency reliability was
used to assess the reliability of the scales. The most commonly used approach to this
method is the use of Cronbach alpha. Cronbach alpha will be high if the scale items
are highly correlated (Hair et al., 1998).
However, another test that must be undertaken before the reliability test is the test for
unidimensionality of a measurement scale. Unidimensionality is defined as the
existence of one construct underlying a set of items (Garver and Mentzer, 1999). It is
the degree to which a set of items represent one and only one underlying latent
construct. The test for unidimensional scales is important before undertaking
reliability tests because reliability such as Cronbach alpha does not ensure
unidimensionality but instead assumes it exists (Hair et al., 1998). More importantly,
achieving unidimensional measurement is a crucial undertaking in theory testing and
development. A necessary condition for assigning meaning to estimated constructs is
that the measures that are posited as alternate indicators of each construct must be
acceptably unidimensional (Anderson and Gerbing, 1988, p.414).
Thus, “the
researcher is encouraged to perform unidimensionality test on all multiple-indicator
constructs before assessing their reliability (Hair et al., 1998, p.611). It is therefore,
necessary to ensure that each set of indicators designed to measure a single construct
achieves unidimensionality.
Validity of a measurement scale is the extent to which the scale fully captures all
aspects of the construct to be measured (Parasuraman, 1991). In a general sense, a
measurement scale is considered to be valid if it measures what it is intended to
measure. Among several types of validation procedures suggested in the literature,
three types are considered as being appropriate to the current research. They are
content validity, convergent validity, and discriminant validity.
Content validity (also known as face validity) is defined as the extent to which the
content of a measurement scale appears to tap all relevant facets of the construct it is
attempting to measure (Parasuraman, 1991). It refers to the degree that the construct
is represented by items that cover the domain of meaning for the construct (Garver
and Mentzer, 1999). Content validity is essentially a subjective agreement among
concerned professionals (Parasuraman, 1991). Content validity of the scales used in
the current research is established by their origins from the extant literature. The new
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items that are used for the first time have been developed through a careful review of
the extant literature on the practical manifestations of the respective construct.
Convergent validity is a form of construct validity which refers to the degree to
which multiple attempts to measure the same concept are in agreement (Campbell
and Fiske, 1959). It deals with the question “do the items intended to measure a
single latent construct statistically converge together” (Garver and Mentzer, 1999,
p.35). Operationally, convergent validity is assessed by the extent to which the latent
construct correlates to items designed to measure that same latent construct.
On the other hand, discriminant validity is also a form of construct validity but it
represents the extent to which measures of different concepts are distinct (Campbell
and Fiske, 1959). Discriminant validity is assessed by the extent to which the items
representing a latent construct discriminate that construct from other items
representing other latent constructs (Garver and Mentzer, 1999, p.35). Convergent
validity and discriminant validity together form the construct validity.
5.3.2. Exploratory and confirmatory factor analyses
To assess and refine the measurement scales in terms of unidimensionality, reliability
and validity, there are two main approaches that are commonly used in the literature
(Hurley et al., 1997). They are exploratory factor analysis (EFA) and confirmatory
factor analysis (CFA). The issue on which type of factor analysis (i.e. EFA or CFA)
to use in a particular situation is the subject of a debate among organizational
researchers (Hurley et al., 1997). In general, proponents of CFA believe that
researchers need to have a strong theory underlying their measurement model before
analyzing data (Williams, 1995). CFA is often used in data analysis to examine the
expected causal connections between variables. Supporters of EFA believe that CFA
is over applied and used in inappropriate situations. They argue that EFA is often
considered to be more appropriate than CFA in the early stages of scale development
because CFA does not show how well the items load on the nonhypothesized factors
(Kelloway, 1995). In spite of different views, the majority of researchers agree that
EFA is more appropriate for scale development and CFA is for scale validation:
“EFA helps develop scales that show good internal consistency while
minimizing overlap with other scales. Moreover, there is nothing to stop one
from using CFA in scale development to test whether the newly written items
135
conform to the hypothesized structure the scale architect had in mind”
(Brannick, 1997, in Hurley et al., 1997, p. 672).
“EFA may be appropriate for scale development while CFA would be
preferred where measurement models have a well-developed underlying
theory for hypothesized patterns of loadings. A line of research would start
out with studies utilizing EFA while later work would show what can be
confirmed” (Hurley et al., 1997, p.668).
Given the above views, the current research employed a combination of both EFA
and CFA to form a two-phase approach. The first phase involved employing EFA for
scale assessment and refinement. The second phase involved employing CFA for
scale validation (Fabrigar et al., 1999, p.277). The reason for applying both EFA and
CFA in this research is that it involves the development of new scales to measure
several constructs under investigation. As described in Table 4.16 in the previous
chapter, more than a half of the measurement items (39 out of 61) are newly
developed for the current research. Hence, using EFA is an appropriate approach to
preliminary assessment and refinement of these scales (Kelloway, 1995; Brannick,
1997; Hurley et al., 1997). Moreover, as described in chapter 4, the development of
those items was based on a careful operationalization of constructs and a strong
theory underlying their measurement model. They need to be confirmed that they
well conform to the hypothesized structure of the scales before the structural model
is tested. Thus, undertaking CFA is necessary to achieve this purpose (Brannik,
1997; Hurley et al., 1997). In addition, CFA would be applied after the preliminary
assessment by EFA because CFA is more rigorous and precise compared to EFA
(Anderson and Gerbing, 1988; Steenkamp and Van Trijp, 1991).
Table 5.7: Summary of EFA and CFA for scale assessment and validation
Phase
Preliminary
Assessment
Step
Factor analysis
1
EFA for individual scale
2
EFA for all scales together
3
CFA for individual scale
4
5
CFA for selected pairs of scales
CFA for all scales together
Confirmation
136
Type of test
Unidimensionality
Reliability (Cronbach alpha)
Convergent validity
Discriminant validity
Unidimensionality
Convergent validity
Composite reliability
Discriminant validity
Overall measurement model
For each phase of EFA and CFA, the application procedure consists of hierarchical
steps depending on whether the test to be conducted is for unidimensionality,
reliability, convergent or discriminant validity. The whole procedure for scale
refinement and validation is summarized in Table 5.7. The next section will describe
these steps and results in detail.
5.4. ASSESSMENT OF MEASUREMENT SCALES USING EFA
5.4.1. Procedure
In the current research, the applications of EFA were carried out using SPSS10.0.
There are two basic methods used for extracting factors in EFA, common factor
analysis and principal component factor analysis. While principal component factor
analysis is used mainly for item reduction, common factor analysis is for exploring
the latent dimensions represented in the original variables (Conway and Huffcutt,
2003). It is, therefore, appropriate for the current research to employ common factor
analysis (principal axis factoring) with eigenvalue ≥ 1 as a criterion for determining
the number of extracted factors. These criteria were selected because the main
objective of this step was to identify the latent dimensions represented in the original
variables for each construct in the model. Moreover, the oblique rotation (e.g.
PROMAX) was chosen because it reflected more accurately the underlying structure
of data than that provided by an orthogonal solution such as VARIMAX (Hair et al.,
1998). The analyses were undertaken through the two hierarchical steps:
In the first step, EFA with principal axis factoring, eigenvalue ≥ 1 and PROMAX
rotation was applied to each of the 12 constructs under investigation (Conway and
Huffcutt, 2003). The main purpose of this step is to see whether the scale for each
construct under investigation is unidimensional (i.e. first-order construct) or
multidimensional (i.e. second-order construct). For a scale to be empirically
unidimensional, the factor analysis must result in only one factor extracted. This is
necessary because all latent constructs in the theoretical framework are
operationalized as unidimensional constructs. Moreover, items with low factor
loadings (< 0.50) were eliminated because they do not converge properly with the
latent construct they were designed to measure (Hair et al., 1998; Garver and
Mentzer, 1999). Then, reliability analysis (Cronbach Alpha) was applied to each set
137
of indicators (i.e. each scale) to assess and refine the measurement items. Items
having low item-to-total correlation coefficients (<0.50) were eliminated. Moreover,
as a standard for this preliminary assessment, the scale for each construct must
achieve a minimum alpha of 0.70 (Hair et al., 1998). A more precise evaluation of
the reliability (i.e. composite reliability) will be estimated later in the application of
CFA to measurement scales (Hair et al, 1998).
In the second step, a joint EFA with the same setting (i.e. principal axis factoring,
eigenvalue ≥ 1 and PROMAX rotation) was performed on all items of all constructs
put together to have a preliminary assessment of unidimensionality, convergent and
discriminant validity (Kline, 1998). Given the result of step 1 where each item loads
highly on the factor representing its underlying construct, this joint EFA allows all
items to correlate with every factor without being constrained to correlate only with
its underlying factor (Kline, 1998, p.56). Consequently, it allows the investigation of
the general correlation pattern of the measurement items (Fabrigar et al., 1999).
Based on this general pattern, various assessments can be made. First, no item load
highly on more than one factor to indicate unidimensional measurement, i.e. one item
measures only one construct (Anderson and Gerbing, 1988). Second, all items
comprising a scale must load highly on one factor representing the underlying
construct. High loadings of all items indicate convergent validity, while loading on
only one factor indicates unidimensional construct (i.e. first order construct). Third,
no factor consists of two sets of items loading highly on it to indicate discriminant
validity (Hair et al., 1998; Garver and Mentzer, 1999).
5.4.2. EFA Results
5.4.2.1. EFA for individual scales
Following the procedure and criteria described above, the EFA results show that out
of the total twelve scales, eight were immediately acceptable while four scales
needed some refinements.
The scales that did not require any modification are shown in Table 5.8. These
include teamwork (5 items), learning intent (6 items), learning capability (3 items),
knowledge protectiveness (4 items), cultural distance (4 items), competence
improvement (6 items), explicit knowledge acquisition (4 items) and tacit knowledge
acquisition (4 items). Using the latent root or eigenvalue greater than 1 criterion, the
138
results show that only one factor was extracted for each of these scales. The variance
explained by the extracted factor ranges from 59.8% to 81.21% while the factor
loadings are all above the threshold of 0.50. These results indicate that all of the eight
scales listed above are at this preliminary stage, unidimensional.
After establishing that these scales are unidimensional, the reliability of the
composite score was assessed. As shown in Table 5.8, the Cronbach alpha of these
eight scales are all well above the threshold of 0.70 (range is from .892 to .928). The
item-total correlation values, which range from 0.539 to 0.862, are also all above the
threshold of 0.50. All items comprising these eight scales were therefore retained.
139
Table 5.8: EFA and reliability test results
Construct / Items
Teamwork
TEA11
TEA12
TEA13
TEA14
TEA15
Learning Intent
INT16
INT17
INT18
INT19
INT20
INT21
Learning Capability
CAPA22
CAPA23
CAPA24
Knowledge
Protectiveness
PROT29
PROT30
PROT31
PROT32
Cultural Distance
CUL41
CUL42
CUL43
CUL44
Competence
Improvement
IMP45
IMP46
IMP47
IMP48
IMP49
IMP50
Explicit Knowledge
Acquisition
EXPL58
EXPL59
EXPL60
EXPL61
Tacit Knowledge
Acquisition
TAC63
TAC64
TAC65
TAC66
Factor loading
%
Variance
Extracted
71.25
Eigenvalue
Item-total
correlation
3.56
.878
.865
.865
.837
.771
Cronbach
Alpha
.923
.832
.821
.825
.794
.741
65.28
.918
3.92
.794
.822
.798
.756
.830
.844
.756
.780
.758
.722
.789
.800
81.21
2.44
.914
.884
.905
.928
.862
.841
.856
75.96
.926
3.04
.817
.839
.815
.844
.857
.884
.855
.890
69.43
2.77
.884
.758
.868
.817
.896
.821
.713
.807
.756
59.80
3.59
.795
.803
.801
.838
.803
.568
.892
.746
.754
.745
.769
.754
.539
71.74
2.87
.854
.812
.853
.868
.909
.801
.757
.802
.813
74.77
.892
.858
.818
.889
2.99
.922
.842
.814
.781
.840
140
The scales that needed some refinements are shown in Table 5.9. All these scales
yielded only one factor with variances explained ranging from 53.70% to 64.31%.
The Cronbach alpha are all well above the threshold of .70. However, the factor
loading coefficients and item-total correlations of five items in these four scales are
below the acceptable thresholds.
As shown in Table 5.9, these items and their corresponding constructs are:
Management commitment: Item COM09 (In this company, staff performance is
evaluated mainly on working process and not on outcomes) and COM10 (Our top
management places value on learning as a key to employee improvement) have low
factor loadings (0.450 and 0.366, respectively) and low item-total correlations (0.424
and 0.348, respectively). These two items did not provide consistent results with the
other four items in the scale. It is observed that the four items (COM06 through
COM09) address directly the manifestations of management commitment: policy,
measures, resource provision and reward system to foster knowledge transfer. As for
COM09, it addresses the base for employee performance evaluation (i.e. process or
outcomes). This manifestation is less directly related to the management commitment
to knowledge transfer. As a result, its item-total correlation is lower than the
threshold of 0.50. Thus, COM09 is deleted.
COM10 tries to capture the value of learning which could be the basis or reason for
management commitment. The other 4 items on the other hand reflect management’s
actions as a result of its commitment to learning. As such, COM10 is a formative
measure while the other items (policy, resources, and reward system) are reflective
measures represents manifestations of the construct (Edwards and Bagozzi, 2000).
Consequently, COM10 is not well aligned with other items and is thus deleted
together with COM9. The modified scale, now consisting of four instead of six
items, shows satisfactory factor loadings (0.805 to 0.888), and explains 72.2% of the
total variance with an eigenvalue of 2.89. The reliability test shows a Cronbach alpha
of 0.911 (>0.70) and the item-total correlations are all above the 0.50 threshold
(range is from 0.761 to 0.833).
141
Table 5.9: Results of unidimensionality and reliability test – refined scales
Items
Management
Commitment
COM05
COM06
COM07
COM08
COM09
COM10
Variance extracted
Eigenvalue
Cronbach Alpha
Partner
Assistance
ASS25
ASS26
ASS27
ASS28
Variance extracted
Eigenvalue
Cronbach Alpha
Relationship
Strength
REL33
REL34
REL35
REL36
REL37
REL38
REL39
REL40
Variance extracted
Eigenvalue
Cronbach Alpha
Marketing
Dynamism
DYN51
DYN52
DYN53
DYN54
DYN55
DYN56
DYN57
Variance extracted
Eigenvalue
Cronbach Alpha
Original scale
Factor loading
Item-total
correlation
.871
.891
.797
.836
.450
.366
.780
.803
.781
.760
.424
.348
Refined scale
Factor loading
Item-total correlation
.888
.883
.805
.820
eliminated
eliminated
72.2%
2.89
.911
53.7%
3.22
.847
.902
.910
.829
.330
.800
.809
.755
.315
.904
.912
.825
eliminated
60.94%
2.44
.832
eliminated
.768
.806
.836
.847
.837
.844
.768
eliminated
.791
.831
.864
.877
.865
.874
.794
64.31%
5.14
.929
71.07%
4.97
.944
.488
.731
.807
.795
.746
.709
.672
.513
.789
.848
.850
.799
.759
.726
.839
.845
.784
eliminated
77.65%
2.33
.911
.404
.782
.796
.824
.833
.836
.830
.763
.413
.803
.829
.861
.872
.869
.869
.794
.833
.827
.761
.775
eliminated
eliminated
58.13%
4.07
.893
eliminated
.797
.824
.847
.799
.765
.741
eliminated
.753
.776
.798
.754
.729
.707
63.41%
3.80
.910
142
Partner assistance: The factor loading coefficient and item-total correlation of Item
ASS28 (There have been many marketing personnel from our foreign partner
working in this company during the last three years) are 0.330 and 0.315,
respectively which are below the acceptable thresholds. It is found that this item is
practically inappropriate in this specific research because in most of the cases, the
number of expatriate marketing managers working in the IJV is very small (only one
or two managers in 65.8% of the cases). This item was therefore eliminated from
further analysis. EFA and Cronbach alpha were then applied to the refined scale
consisting of three items, and as shown in Table 5.9, the results are above the
threshold values.
Relationship strength: Item REL33 (Our foreign and local marketing staff have a
desire to maintain a good social relationship between them) also rates poorly in turns
of factor loading and item-total correlation (0.413 and 0.404, respectively). Perhaps,
when being translated into Vietnamese the word “have a desire” causes a confusion
of its normative and descriptive meaning. Therefore, this item was eliminated. The
remaining seven items in the refined scale were subjected to EFA and reliability test.
As shown in Table 5.9, they now are all acceptable in terms of factor loading and
item-total correlation.
Marketing dynamism: Item DYN51 measures the frequency of changes in the
“company’s mix of products or brands” as initiated by the local marketing staff
during the last three years. This item has a low item-total correlation (0.488). In the
reality of IJVs in developing/transitional countries, perhaps the changes in the
company’s mix of products or brands occur in a longer term and are beyond the
authority of local marketing staff (Danis and Parkhe, 2002). As a result, this item did
not provide consistent result with the other items in the scale. It was thus eliminated.
The EFA and reliability test of the refined scale of 6 items (DYN52 through DYN57)
yielded satisfactory levels of factor loadings and item-total correlation.
In summary, 5 items were eliminated (COM09, COM10, ASS28, REL33 and
DYN51), and the remaining 56 items for the 12 scales were retained. All the twelve
scales are now acceptable.
143
5.4.2.2. EFA for all scales together
After establishing the unidimensionality and reliability of each scale, all 56 items
were jointly subjected to a common factor analysis. This approach allows all items to
correlate with every factor without being constrained to correlate only with its
underlying factor (Kline, 1998, p.56). The results of this procedure are shown in
Table 5.10. As shown in the table, 12 factors were extracted which together explain
77.7% of the total variance. The factor loadings of each of the 56 items vary from
0.601 to 0.918 which are higher than the threshold of 0.50. No item load highly on
more than one factor and no item load highly on a factor other than its designate
factor representing its latent construct. Regarding the issue of appropriateness, the
result of the Bartlett’s Test of Sphericity and KMO measure (Harris and Halpin,
2002) indicated that the degree of intercorrelations among the items was suitable for
EFA procedures (Chi-square = 10003, dF = 1540 and sig. = 0.000, KMO = 0.900).
Although not being finally confirmed, this result supports a preliminary justification
of the unidimensionality, discriminant validity, and convergent validity of the scales
for the 12 constructs. The final validation of these scales will be analyzed in the next
sections, using confirmatory factor analyses (Hair et al, 1998).
144
Table 5.10: Result of joint factor analysis for 12 scales
Factor
REL37
REL39
REL38
REL36
REL35
REL34
REL40
DYN56
DYN54
DYN53
DYN52
DYN57
DYN55
INT21
INT17
INT20
INT18
INT19
INT16
TEA11
TEA13
TEA12
TEA15
TEA14
PROT32
PROT30
PROT29
PROT31
COM05
COM07
COM06
COM08
CUL41
CUL43
CUL44
CUL42
IMP46
IMP48
IMP45
IMP49
IMP50
IMP47
CAPA24
CAPA22
CAPA23
ASS26
ASS25
ASS27
EXPL58
EXPL60
EXPL61
EXPL59
TACL66
TACL64
TACL63
TACL65
1
.891
.863
.851
.848
.834
.813
.772
2
3
4
5
6
7
8
9
10
11
12
.855
.833
.763
.743
.724
.671
.838
.834
.826
.806
.763
.747
.893
.847
.844
.823
.774
.910
.892
.850
.841
.918
.841
.826
.769
.871
.854
.852
.829
.806
.736
.728
.705
.703
.601
.890
.882
.881
.910
.894
.831
.823
.819
.754
.737
.847
.827
.746
.707
145
In addition, it can be seen in the factor correlation matrix (Table 5.11) that the four
endogenous constructs, namely competence improvement (factor 8), marketing
dynamism (factor 2), explicit know-how acquisition (factor 11) and tacit know-how
acquisition (factor 12) have considerable correlations with several other factors.
Moreover, all of the eight exogenous constructs have considerable correlations with
at least one of the two focal endogenous constructs, i.e. explicit and tacit know-how
acquisition. This result signifies a support to the theoretical model where explicit
know-how acquisition, tacit know-how acquisition, competence improvement and
marketing dynamism are endogenous constructs and the others are exogenous
constructs.
Table 5.11: Factor Correlation Matrix – 12 constructs
Factor Correlation Matrix
Factor
1
2
3
4
5
6
7
8
9
1 (Relationship)
1.00
2 (MKT Dynamism) .310 1.00
3 (Learning Intent) .106 .322 1.00
4 (Teamwork)
.280 .386 .124 1.00
5 (Protectiveness) -.061 -.229 -.044 -.014 1.00
6 (Commitment)
.138 .361 .160 .109 -.072 1.00
7 (Culture)
-.092 -.116 -.092 -.120 .079 .042 1.00
8 (Competence)
.397 .688 .324 .413 -.216 .283 -.133 1.00
9 (Lrning Capability) .155 .377 .207 .112 -.155 .123 -.014 .364 1.00
10 (Assistance)
.129 .202 .099 .067 -.086 .163 .018 .225 .178
11 (Explicit Learning .096 .626 .348 .385 -.238 .463 -.071 .599 .388
12 (Tacit Learning) .449 .628 .361 .435 -.323 .266 -.274 .657 .420
10
11
1.00
.332 1.00
.198 .551
12
1.00
5.5. ASSESSMENT OF MEASUREMENT SCALES USING CFA
5.5.1. Introduction
Traditional approaches such as Cronbach alpha and EFA are useful for the
assessment and refinement of measurement scales. However, they only serve as
preliminary tools (Hair et al, 1998). For a confirmative approach, it is necessary to
employ Confirmatory factor analysis (CFA) (Garver and Mentzer, 1999, Hurley et
al., 1997). As commented by Williams (1997): “EFA provides important diagnostics
which should be considered along with the results of CFA in judging a scale and its
items” (in Hurley et al., 1997, p. 674). This is because CFA provides a test of
hypotheses about population factor structures based on sample data, i.e. the
146
relationships of the construct with its measures; while EFA attempts to describe,
summarize or reduce data to make them easily understood (Brannik, 1997, in Hurley
et al., 1997, p.680).
The following section describes the use of CFA for the confirmative validation of
key properties of measures including unidimensionality, reliability, convergent
validity and discriminant validity (Hair et al, 1998).
5.5.2. Test of unidimensionality, reliability and validity using CFA
Unidimensionality of a scale is defined as the existence of one latent trait underlying
the data (Hair et al, 1998; Anderson and Gerbing, 1988). In CFA, the
unidimensionality of a scale is judged by the overall fit of the model including the
latent construct and its designate items (Steenkamp and Van Trijp, 1991; Garver and
Mentzer, 1999).
Reliability as being evaluated in CFA is the composite reliability. Composite
reliability is a better indicator than Cronbach alpha because it is free from the
assumption of equal item reliabilities (Gerbing and Anderson, 1988; Hair et al,
1998). Composite reliability of a scale is calculated by the following (Hair et al,
1998):
Composite reliability = (∑standardized loading)2/((∑standardized loading)2 + ∑εj )
The standardized loadings are obtained directly from the program output; and εj is
the measurement error for each indicator. The measurement error is 1.0 minus the
square of the indicator’s standardized loading.
Convergent validity of a measure is the degree to which multiple attempts to measure
the same construct are in agreement (Hair et al, 1998). It is achieved if 1) the model
receives a satisfactory level of fit, and 2) the regression coefficients (factor loadings)
of all indicators are statistically significant, i.e. greater than twice its standard error
(Anderson and Gerbing, 1988; Dunn et al., 1994). However, Steenkamp and Van
Trijp (1991) argue that the statistically significant coefficient on a particular item is a
weak condition for convergent validity. A stronger condition is that the factor
regression coefficient is substantial. The condition of substantial regression
coefficient helps detect items that have significant but trivial effect (Brannik, 1997,
in Hurley et al., 1997). A benchmark value of substantial coefficient of the parameter
estimate indicating convergent validity is 0.70 (Kline, 1998; Hair et al, 1998; Garver
147
and Mentzer, 1999).
Discriminant validity of a measure is “the degree to which measures of different
concepts are distinct” (Bagozzi, 1994, p. 20). There are two types of discriminant
validity, namely within-construct validity and across-construct validity. However,
only the across-construct validity is applicable in the current research because all the
investigated constructs are unidimensional. In CFA, items from one scale should not
load or converge too closely with items from a different scale (Garver and Mentzer,
1999). In essence, across-construct discriminant validity is achieved when the model
receives a satisfactory level of fit; and the 95% confidence interval of the correlation
does not include unity (Anderson and Gerbing, 1988; Bagozzi and Heatherton,
1994).
5.5.3. Procedure
The test of measurement scales using CFA consists of three hierarchical steps as
described previously in Table 5.7. This hierarchical procedure helps to step by step
identify and eliminate the unacceptable items. Otherwise, these items may cause
cross-factor loading, or general scatter of discrepancies that lead to a low overall
measurement model fit (Garver and Mentzer, 1999; McDonald and Ho, 2002).
In the first step, each of the 12 scales was subjected to CFA to evaluate
unidimensionality, composite reliability, and convergent validity.
In the second step, discriminant validity was evaluated among selected pairs of
constructs. These pairs of constructs were tested separately before testing the whole
measurement model because they are theoretically related to each other. Recall that
the eight antecedents of knowledge acquisition stem from four categories: 1) IJV
management features, which consists of management commitment and teamwork; 2)
knowledge seeker, which consists of learning intent and learning capability; 3)
knowledge holder, which consists of partner assisstance and knowledge
protectiveness; and 4) matching factors, which consists of relationship strength and
cultural distance. It is necessary to confirm that the two constructs within each
category are distinct to each other. A similar reason is applicable to the test for the
distinction between explicit and tacit know-how acquisition; and between marketing
competence improvement and marketing dynamism. Totally, 6 pairs of constructs
were tested for the discriminant validity in this step.
148
In the third step, the full measurement model including the 12 constructs all put
together was subjected to CFA. The purpose of this test is to evaluate the acrossconstruct discriminant validity and the overall measurement model. In testing this
model, partial disaggregation (or item parceling) was employed. The results of each
step are presented in sections 5.6 through 5.8.
5.5.4. Estimation methods and overall model fit measures
Among several methods for estimating parameters in SEM/CFA, maximum
likelihood (ML) is the most commonly used (Anderson and Gerbing, 1988; Kline,
1998). This is because ML has several important properties such as being
asymptomatically unbiased, efficient, consistent, and scale free (Bollen, 1989). Two
inconvenient issues in using ML are: 1) it is based on the assumption that the
distribution of observed variables is multivariate normal; and 2) it requires a large
sample size (Byrne, 2001). However, researches have shown that when the data has a
slight or moderate deviation from multinormality, ML has been the preferable
method (Bollen, 1989; Joreskog and Sorbom, 1996).
Regarding the measures of the overall model fit, there are “dozens of fit indexes
described in SEM literature, more than any single model-fitting program reports”
(Kline, 1998, p.127). However, “there was little consistency in the choice of fit
indexes or criteria for their evaluation” (McCallum and Austin, 2000, p.219). Among
those indexes, chi-square statistic is the fundamental measure of overall fit (Hair et
al, 1998). A low chi-square value indicates that the actual and predicted input
matrices are not different. In this instance, the researcher is looking for a nonsignificant difference (i.e. p>0.05) because the test is between the actual and
predicted matrices (Hair et al. 1998). However, the disadvantage of this measure is
that theoretically it has no upper bound although its lower bound is always zero.
Thus, its values are not interpretable in a standardized way (Kline, 1998). In addition,
chi-square value is very sensitive to the sample size. When the sample size becomes
large enough (>200), a significant chi-square (p<0.05) is likely to be found for any
specific model. On the contrary, when the sample size is small (<100), acceptable fit
can be obtained (Hair et al, 1998). To reduce the sensitivity of chi-square value to the
sample size, some researchers divide its value by the number of degrees of freedom
(chi-square/dF). However, there is also no clear-cut guideline about the critical value
for this relative index. Its suggested upper bound value for an acceptable fit model
149
ranges from 2 to 5 (Byrne, 1989; Carmines and McIver, 1981; Marsh and Hocevar,
1985; Wheaton et al., 1977, cited in Arbuckle and Wothke, 1999; Kline 1998).
To overcome the shortcoming of the chi-square statistic, additional fit indexes need
to be examined. The selection of additional fit indexes should be based on three
criteria: 1) relative independence of sample size; 2) accuracy and consistency to
assess different models; and 3) ease of interpretation aided by a well designed
continuum or pre-set range (Marsh et al., 1988; Garver and Mentzer, 1999). Based on
these criteria, Garver and Mentzer (1999) suggest the use of Tucker-Lewis index
(TLI or NNFI), the comparative fit indexes (CFI) and the root mean squared
approximation of error (RMSEA). This suggestion is largely consistent with Kline
(1998). Who suggests that the minimum set of indexes should include 1) chi-square,
dF and p value; 2) an index that describes the overall proportion of explained
variance (i.e. CFI, GFI or NFI); 3) an index that adjusts the proportion of explained
variance of the model complexity (i.e. TLI); and 4) an index based on the
standardized residuals (i.e. SRMR).
Accordingly, the following indexes and thresholds will be used in this study, in
addition to chi-square (and its associated statistics i.e. dF, p, chi-square/dF):
̇ Tucker-Lewis index – TLI (also known as NNFI – non-normed fit index)
compares a proposed model’s fit to a nested baseline or null model. Additionally,
TLI measures parsimony by assessing the degrees of freedom from the proposed
model to the degree of freedom of the null model. TLI also seems resilient against
variations in sample size (Marsh et al., 1988, cited in Garver and Mentzer, 1999).
Its value typically ranges from 0 to 1, but it is not limited to that range (Hair et al.,
1998; Arbuckle and Wothke, 1999). TLI ≥ 0.90 being indicative of good fit (Hair
et al., 1998; Garver and Mentzer, 1999).
̇ Comparative fit index – CFI is based on the comparison of the hypothesized
model against the null model. Moreover, it is less affected by the sample size
(Kline, 1998). CFI values range from 0 to 1. For a model fit, CFI should be
greater than 0.90 (Hu and Bentler, 1999).
̇ Root mean square error approximation – RMSEA measures the discrepancy
between the observed and estimated covariance matrices per degree of freedom, in
terms of the population, not the sample (Hair et al., 1998). This index has been
150
recognized as “one of the most informative criteria in covariance structure
modeling” (Byrne, 2001, p.84). It is sensitive to the number of estimated
parameters in the model, i.e. the complexity of the model (Byrne, 2001). RMSEA
of less than 0.06 indicates good fit; from 0.06 to 0.08 indicates acceptable fit;
from 0.08 to 0.10 indicates mediocre fit and those greater than 0.10 indicate poor
fit (Arbuckle and Wothke, 1999; Hu and Bentler, 1999; MacCallum et al, 1996).
5.6. RESULTS OF CFA FOR INDIVIDUAL SCALES
Following the procedure and criteria addressed above, this section presents the
results of the CFA applied to each of the 12 scales used in this study. The results
show that 10 of the 12 measurement scales do not need any further refinements.
However, within these 10 scales, there are two scales that are just-identified models.
5.6.1. CFA results - satisfactory scales
5.6.1.1. Satisfactory scales with over-identified models
The eight scales that are over-identified and do not need any modification or
refinement are management commitment (4 items), teamwork (5 items), knowledge
protectiveness (4 items), relationship strength (7 items), cultural distance (4 items),
marketing dynamism (6 items), explicit know-how acquisition (4 items), and tacit
know-how acquisition (4 items). The first part of Table 5.12 provides a summary of
the estimated models and their fit indexes.
Given the unidimensionality of each scale, the standardized regression coefficients of
all items are above 0.70 (from 0.737 to 0.892). Therefore, it can be concluded that all
of these scales achieve convergent validity.
The results also show that the composite reliability of these eight scales range from
0.910 to 0.945 which are all well above the threshold of 0.70. It is thus concluded
that all these scales meet the required level of reliability.
151
Table 5.12: CFA Results of models not requiring any modification
Construct / Items
Regression coefficient
Standard
Unstandardized Standardized Error
p
χ2
(p)
dF
χ2/dF
TLI
CFI
RMSEA
Composite
Reliability
5.631
(.060)
2
2.816
.982
.994
.091
.913
10.954
(.052)
5
2.191
.985
.993
.074
.924
.684
(.710)
2
.342
1.006
1.000
.000
.927
25.288
(.032)
14
1.806
.987
.991
.061
.945
SCALES WITH OVER-IDENTIFIED MODELS
Management Commitment
COM05
COM06
COM07
COM08
Teamwork
TEA11
TEA12
TEA13
TEA14
TEA15
Knowledge Protectiveness
PROT29
PROT30
PROT31
PROT32
Relationship Strength
REL34
REL35
REL36
REL37
REL38
REL39
REL40
1.000
1.175
1.014
1.006
.876
.885
.807
.828
Na
.068
.068
.065
1.000
0.984
1.147
0.978
1.011
.880
.865
.859
.842
.771
Na
.057
.067
.059
.071
1.000
1.101
1.023
1.083
.856
.885
.854
.891
Na
.064
.063
.062
1.000
0.926
0.994
1.099
1.131
1.053
0.886
.791
.828
.864
.878
.864
.875
.797
***
***
***
***
***
***
***
***
***
***
Na
.067
.068
.073
.077
.070
.067
***
***
***
***
***
***
152
Cultural Distance
CUL41
CUL42
CUL43
CUL44
Marketing Dynamism
DYN52
DYN53
DYN54
DYN55
DYN56
DYN57
Explicit Knowledge Acquisition
EXPL58
EXPL59
EXPL60
EXPL61
Tacit Knowledge Acquisition
TAC63
TAC64
TAC65
TAC66
4.594
(.101)
2
2.297
.987
.996
.077
.914
18.001
(.035)
9
2.001
.981
.989
.068
.913
.583
(.747)
2
.291
1.007
1.000
.000
.910
2.610
(.271)
2
1.305
.997
.999
.037
.923
1.163
(.281)
1
1.163
.999
1.000
.027
.928
.809
1
.809
1.001
1.000
.000
(.368)
***
.044
.893
***
.044
.922
Na
.824
Na: non-applicable because the unstandardized regression coefficient is fixed to 1
.912
1.000
0.874
0.982
0.987
.870
.816
.857
.857
Na
.066
.054
.060
0.798
1.000
1.010
0.959
0.958
0.873
.802
.826
.846
.799
.761
.737
.058
Na
.068
.070
.075
.072
1.000
0.965
0.887
1.032
.855
.812
.853
.867
Na
.067
.057
.064
1.000
0.981
0.879
0.981
.892
.856
.817
.892
Na
.057
.055
.052
.906
.892
.906
.045
.045
.Na
***
***
***
***
***
***
***
***
***
***
***
***
***
***
SCALES WITH JUST-IDENTIFIED MODELS
Learning Capability
CAPA22
CAPA23
CAPA24
Partner Assistance
ASS25
ASS26
ASS27
Note: *** significant at p < 0.001
1.024
1.024
1.000
1.145
1.145
1.000
***
***
153
5.6.1.2. Satisfactory scales with just-identified model
Among the 12 scales subjected to CFA, there are two three-item scales, namely
learning capability and partner assisstance that are just-identified models (i.e. dF =
0). A just-identified model provides enough information to estimate all parameters,
but the chi-square test always indicates a perfect fit (Bagozzi and Heatherton, 1994).
Therefore, the just-identified model is not scientifically interesting because it has no
degree of freedom and can never be rejected (Byrne, 2001, p.35).
To overcome the problem of just-identified models, a number of approaches are
available. The first approach suggested by Bagozzi and Heatherton (1994, p.45), is
to test how well the single-factor model fits the data while constraining all three
factors loadings, or selected subsets of two, to be equal. This will yield a chi-square
with dF = 2 (or dF = 1 if a pair of loadings is constrained to be equal).
The second approach is based on Anderson and Gerbing (1988) for dealing with a
single indicator construct. By this approach, one additional constraint is imposed on
the model. The imposed constraint can be a value for the error variance of an
indicator (e.g. set error variance = 0.1 indicator variance). The third approach is
based on Garver and Mentzer (1999). With this approach, the two three-item scales
are assessed together in a single model and constraining the two constructs to be
correlated. This would result in the two-construct model with 6 indicators, 13
parameters estimated and dF = 8 which is over-identified.
The current research adopts the first approach in which the unstandardized factor
loadings of two indicators are set to be equal (Bagozzi and Heatherton, 1994). This
approach is preferred to the other approaches because the second approach is very
conservative (Anderson and Gerbing, 1988) and the third approach actually does not
deal with a single-factor model (i.e. the yielded fit indexes are not for the singlefactor but for the two-factor model). With this selected approach, CFA was applied
to the two single-factor models with three items each. As shown in the second part of
Table 5.12 all the fit indexes indicate a good fit. Moreover, the standardized
regression coefficients of all items are above 0.70. Thus, unidimensionality and
convergent validity are indicated. Lastly, composite reliabilities of the two scales are
above 0.70, ensuring the reliability.
154
5.6.2. CFA results - scales needing refinement
Among the 12 individual scales subjected to CFA, two scales needing further
refinements, namely learning intent and competence improvement.
5.6.2.1. Learning intent
As shown in Table 5.13, the measurement model for this construct does not achieve a
good fit because RMSEA = 0.102 which is above the threshold of 0.08. For
improving the model fit, the modification index MI is used. MI represents the
expected drop of chi-square value if a fixed parameter in the model were to be freely
estimated in a subsequent estimation (Byrne, 2001). A substantial MI value is 7.88
which, if adopted, will lead to a significant model improvement (Joreskog and
Sorbom, 1993).
It is revealed that the error term of the indicator INT17 (Our local partner
encourages the local marketing staff to learn and acquire our foreign partner’s
marketing knowledge) covaries highly with the error term of INT21 (Our marketing
staff have a strong interest in learning from our foreign partner) and the error term
of the indicator INT18 (Our local partner has provided the necessary resources
needed to support the acquisition of marketing knowledge from our foreign partner).
The MI values are 12.6 and 7.8, respectively. To improve the model fit, INT17 was
eliminated. The remaining 5 items are still capable of capturing the two facets of the
learning intent including that of the local firm (2 items) and the local staff in the IJV
(3 items). Thus, this elimination does not significantly affect the measuring domain
of the construct.
The CFA applied for the refined scale results in a chi-square of 6.906 (p = 0.228) and
chi-square/dF of 1.381. In addition, the fact that TLI = 0.994, CFI = 0.997 and
RMSEA = 0.042 indicate that the refined model achieves significant improvement in
the overall fit. The standardized regression coefficients of the five remaining
indicators are all above 0.70 (range is from 0.750 to 0.847). These statistics ensure
the unidimensionality and convergent validity for this refined scale. The composite
reliability for this scale is 0.902 which is well above the critical value of 0.70.
155
Table 5.13: Results of CFA for individual scales – Refined scales
Regression coefficient
Construct / Items
Learning Intent
INT16
INT17
INT18
INT19
INT20
INT21
Learning Intent (Refined scale)
INT16
INT17 (eliminated)
INT18
INT19
INT20
INT21
Competence Improvement
IMP45
IMP46
IMP47
IMP48
IMP49
IMP50
Competence Improvement
(Refined scale)
IMP45
IMP46
IMP47
IMP48
IMP49
IMP50 (eliminated)
Unstandardized
Standardized
Standard
Error
1.000
1.108
1.128
1.015
1.057
1.193
.792
.826
.796
.756
.828
.846
Na
.082
.088
.084
.078
.086
1.000
1.171
1.009
1.084
1.145
.790
.825
.750
.847
.810
Na
.089
.086
.080
.089
1.000
0.953
1.126
1.089
1.035
0.808
.795
.799
.803
.848
.798
.561
Na
.074
.087
.079
.081
.096
1.000
0.949
1.132
1.111
1.032
-
.791
.792
.804
.862
.792
-
Na
.075
.088
.080
.082
-
P
Composite
RMSEA Reliability
χ2
(p)
dF
χ2/dF
TLI
CFI
29.413
(.001)
9
3.268
.960
.976
.102
-
6.906
(.228)
5
1.381
.994
.997
.042
.902
27.264
(.001)
9
3.029
.959
.975
.096
-
11.678
(.039)
5
2.336
.979
.990
.078
.903
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
156
5.6.2.2. Competence improvement
The model for this construct achieved a mediocre fit with a chi-square of 27.264 (p =
0.001) and RMSEA = 0.096. One indicator (IMP50) has a low regression coefficient
of 0.56 which is below the critical value of 0.70. By its meaning, IMP50 measures
the extent of improvement of the local staff capabilities in making marketing
decisions in general. This manifestation of the competency improvement may not be
relevant in this specific sample as the general marketing decisions may be beyond the
responsibility of the majority of the local marketing staff (Danis and Parkhe, 2002).
It is possibly for this reason that IMP50 converges weakly with the other 5 items
comprising this construct.
For refinement, the indicator IMP50 was eliminated. The refined scale without
IMP50 achieves a good fit, i.e. chi-square of 11.678 (p = 0.039) and chi-square/dF of
2.336, TLI = 0.979, CFI = 0.990 and RMSEA = 0.078. Table 5.13 also shows that all
standardized regression coefficients are above 0.70. The composite reliability is
0.903 based on a separate calculation. In short, the refined scale now comprising five
indicators coded IMPL45 through IMPL49 is acceptable.
5.6.3. Summary of CFA for the 12 individual scales
To this point, the scales for the 12 constructs have been assessed and refined using
CFA. Through this process, two more items (INT17 and IMP50) have been
eliminated
to
ensure
that
those
scales
achieve
satisfactory
levels
of
unidimensionality, reliability and convergent validity. The statistics for the 12 scales
and 54 indicators are summarized in Tables 5.12 and 5.13. They are now ready for
testing the across-construct discriminant validity as described in the next section.
5.7. RESULTS OF CFA FOR SELECTED PAIRS OF SCALES
Although the joint EFA demonstrated that the 12 scales represent 12 underlying
constructs, CFA is needed to confirm that these constructs are distinct from one
another. This is particularly necessary for the constructs emanating from the same
categories that are theoretically related to each other. Hence, six pairs of constructs
were tested for discriminant validity in this step. In these CFAs, each of the six
models was composed of the two latent constructs being tested, their respective
observed indicators, and the correlation between them which was freely estimated.
157
The results are shown in Table 5.14. Accordingly, all six models have good fit
indexes. The loading coefficients of all indicators are stable in comparison with those
estimated in the models for individual scales (Tables 5.12 and 5.13). Among the
correlation coefficients between the six pairs of constructs, three values are nonsignificant (p > 0.05) which indicate a strong discriminant validity (Bagozzi and
Heatherton, 1994). The other three values also demonstrate discriminant validity
because their 95% confidence intervals do not contain 1.0.
In summary, the result confirms the discriminant validity of those constructs that
initially seemed to be theoretically related i.e.: 1) management commitment and
teamwork; 2) learning intent and learning capability; 3) partner assisstance and
knowledge protectiveness; 4) relationship strength and cultural distance; 5) explicit
know-how acquisition and tacit know-how acquisition; and 6) marketing competence
improvement and marketing dynamism. The discriminant validity of the other
constructs will be discussed in the next section.
158
Table 5.14: Assessment of discriminant validity for selected pairs of constructs
95%
Correlation between
Estimate
S.E.
confidence interval
Lower
Upper
p
Model fit indexes
χ2
p
dF
χ2/dF
TLI
CFI
RMSEA
Commitment ↔ Teamwork
.113
.070
-.025
.250
.124 39.53
.043
26
1.520
.987
.990
.049
Learning intent ↔ Learning capability
.209
.069
.068
.327
.009 18.50
.489
19
.974
1.001
1.000
.000
Partner assistance ↔ Knowledge protectiveness
-.085
.070
-.227
.052
.223 11.05
.606
13
.850
1.003
1.000
.000
Relationship strength ↔ Cultural Distance
-.093
.064
-.230
.033
.130 51.80
.168
43
1.205
.994
.995
.031
Explicit ↔ Tacit Know-how acquisition
.591
.054
.482
.693
.004 20.96
.339
19
1.103
.998
.998
.022
Competence improvement ↔ MKT dynamism
.755
.038
.682
.825
.004 53.81
.125
43
1.251
.991
.993
.034
159
5.8. CFA FOR THE FULL MEASUREMENT MODEL
In the full measurement model, there are 12 constructs and 66 between-construct
correlations to be estimated using the information from 54 observed indicators. The
number of free parameters to be estimated is 173 which are excessively large, given
the sample size of 219. This would cause a problem in the model estimation because
“an excessive number of variables, especially in relation to sample size, can result in
misleading findings and invalid conclusions regarding the factor structure” (Nasser
and Wisenbaker, 2003, p.730). To overcome this problem, different solutions have
been suggested in the literature. Some practitioners use only a subset of observed
items for CFA, i.e. other items are discarded (Nasser and Wisebaker, 2003). This is
not recommended because the eliminated items may contain valuable information
about the estimators and tests concerning the structural model (Yuan et al., 1997).
Another commonly employed solution is the use of partial disaggregation (Bagozzi
and Heatherton, 1994) or item parcels (Nasser and Wisebaker, 2003).
According to Bagozzi and Heatherton (1994), the use of each item as a separate
indicator of the relevant construct (i.e. total disaggregation) provides the most detail
level of analysis. But “in practice, it can be unwieldy because of likely high levels of
random error in typical items and the many parameters that must be estimated”
(p.42). In contrast, the total aggregation of items (i.e. only one composite item is
formed by summing the scores on all items) does not offer much advantage over
traditional multivariate analysis, although it does provide fit indexes. Between these
two extremes, the partial disaggregation technique is a compromise. “It allows one to
proceed with meaningful research by combining items into composites to reduce
higher levels of random error and yet it retains all the advantages of structural
equations” (Dabholkar et al, 1996, p.9).
Partial disaggregation would produce parcels. A parcel is referred to an indicator,
which is a simple sum or mean of several items assumed to be conceptually similar,
unidimensional, and which is used to assess the same construct (Kishton and
Widaman, 1994). Parcels are often preferred to single items as indicators of latent
constructs (i.e. total disaggregation) for several important reasons. First, they are
more likely to be normally distributed than single items. Consequently they are more
likely to meet the assumption of the commonly used maximum likelihood estimation
method. Second, the resulting reduction in the complexity of the measurement model
160
leads to more precise parameter estimates. Finally, because parcels reduce the
number of indicators involved in modeling, researchers are able to use more realistic
models that better capture increasingly complex theories of human behavior (Nasser
and Wisebaker, 2003, p.730).
The current research employed this technique for reducing the number of indicators
in the model. In applying this technique, three issues that needed to be addressed
were as follows:
The first issue concerns with the unidimensionality of items to be parceled. In this
regard, Yuan et al. (1997) assert that when the observed variables are dependent on
only one latent construct, averaging variables will keep the same factor structures as
that of the original variables being averaged. However, if the unidimensionality has
not been met, the use of item parcels may obscure rather than clarify the structure of
the data (West et al., 1995). In the current research, the unidimensionality of all 12
scales have been confirmed in the previous steps.
The second issue is related to the number of parcels to be formed per construct.
Dabholkar et al. (1996) suggest that 2 or 3 parcels should be formed for each latent
construct. Bagozzi and Heatherton (1994) suggest that if we have 5 – 7 original
items, 2 composites (i.e. parcels) should be formed; if the number of original items is
more than 9, then 3 composites should be formed. Nasser and Wisebaker (2003)
compare different alternatives of the number of parcels per construct (from 1 to 4)
and strongly recommend that three parcels per construct should be formed. In the
current research, all constructs have from 4 to 7 items, except learning capability and
partner assisstance which have 3 items each. Applying the above principle, 2 parcels
were formed for those scales containing 4 to 7 items. The two three-item scales were
kept i.e. no parceling was undertaken.
The third issue concerns with the method by which items are combined into a parcel.
Some authors suggest a random grouping of items into parcels (Dabholkar et al.,
1996). Others suggest several criteria for averaging items to form parcels. For
example, Yuan et al. (1997) suggest to group items that have roughly equal loadings
(based on the result of previous CFA step) or equal relative errors. Thompson and
Melancon (1996) suggest to group items that are skewed to different directions. For
simplicity, the current research adopted the first approach. Another reason for this
selection was that “all items related to a latent variable should correspond in the
161
same way to that latent variable; thus any combination of the items should yield the
same model fit” (Dabholkar et al., 1996, p.10). As a result, the two parcels in each
scale were formed by randomly arranging the original items into two groups and
averaging the scores of items in each group to form the parcel’s score.
By this approach, 26 composite indicators (i.e. parcels) were created from the 54
original indicators. Their covariances and correlations matrices are presented in
Appendices 3 and 4. The resulting scales for the 12 constructs are described in Table
5.15. The distributions of these 26 composite indicators (Appendix 5) show that all
of them have kurtosis values within (-0.798 to +0.251). Their skewness values are
within (-0.557 to +0.345). Thus, all indicators can be considered as normally
distributed because all the values are less than 3.0 for skewness and 10.0 for kurtosis
(Kline, 1998). It is therefore appropriate for maximum likelihood method to be
applied for estimation.
The CFA resulted in the estimates of standardized correlation between 66 pairs of
constructs formed by the 12 constructs under consideration (Table 5.16). The
resulting fit indexes indicate that the full measurement model achieves a good fit
with the data. (Chi-square = 235.31; dF = 233; p = 0.445; χ2/dF = 1.010; TLI =
0.999; CFI = 0.999; RMSEA = 0.007). Moreover, the HOETLER index has a value
of 250 which is above threshold value of 200 indicating that the sample size of 219 is
satisfactorily large enough for this analysis (Byrne, 2001).
162
Table 5.15: Indicators for 12 constructs in the full measurement model
Construct
1
2
3
4
5
6
7
8
9
10
11
12
Management
Commitment
(COMMITMENT)
Teamwork
(TEAMWORK)
Learning Intent
(INTENT)
Learning Capability
(LEARNCAPA)
Partner Assistance
(ASSISANCE)
Knowledge
Protectiveness
(PROTECT)
Relationship Strength
(RELATIONSHIP)
Cultural Distance
(CULTURE)
Explicit Learning
(EXP LEARNING)
Tacit learning
(TACIT LEARNING)
Competence
Improvement
(COMPETENCE)
Marketing Dynamism
(DYNAMISM)
12 Constructs
Original indicator
COM05
COM06
COM07
COM08
TEA11
TEA12
TEA13
TEA14
TEA15
INT16
INT18
INT19
INT20
INT21
CAPA22
CAPA23
CAPA24
ASS25
ASS26
ASS27
PROT29
PROT30
PROT31
PROT32
REL34
REL35
REL36
REL37
REL38
REL39
REL40
CUL41
CUL42
CUL43
CUL44
EXPL58
EXPL59
EXPL60
EXPL61
TACL63
TACL64
TACL65
TACL66
IMP45
IMP46
IMP47
IMP48
IMP49
DYN52
DYN53
DYN54
DYN55
DYN56
DYN57
54 original
indicators
163
Composite Indicator/Parcel
Com1= (COM05 + COM06)/2
Com2= (COM07 + COM08)/2
Tea1= (TEA11 + TEA14)/2
Tea2= (TEA12 + TEA13 + TEA15)/3
Int1= (INT16 + INT18 + INT20)/3
Int2= (INT19 + INT21)/2
Keep as original indicators
Keep as original indicators
Prot1= (PROT29 + PROT31)/2
Prot2= (PROT30 + PROT32)/2
Rel1= (REL34 + REL35 +
+ REL36 + REL37)/4
Rel2= (REL38 + REL39 + REL40)/3
Cul1= (CUL41 + CUL43)/2
Cul2= (CUL42 + CUL44)/2
Expl1= (EXPL58 + EXP59)/2
Expl2= (EXPL60 + EXP61)/2
Tacl1= (TACL63 + TACL65)/2
Tacl2= (TACL64 + TACL66)/2
Imp1= (IMP45 + IMP46)/2
Imp2= (IMP47 + IMP48 + IMP49)/3
Dyn1= (DYN52 + DYN54 + DYN56)/3
Dyn2= (DYN53 + DYN55 + DYN57)/3
26 composite indicators
Table 5.16: Standardized correlations between constructs with 95% confidence interval
Correlation between
TACIT LEARNING
<--> EXP LEARNING
COMPETENCE
<--> DYNAMISM
COMPETENCE
<--> EXP LEARNING
DYNAMISM
<--> TACIT LEARNING
COMPETENCE
<--> TACIT LEARNING
DYNAMISM
<--> EXP LEARNING
RELATIONSHIP
<--> CULTURE
RELATIONSHIP
<--> LEARNCAPA
LEARNCAPA
<--> INTENT
INTENT
<--> PROTECT
ASSISTANCE
<--> PROTECT
ASSISTANCE
<--> TEAMWORK
COMMITMENT
<--> TEAMWORK
COMMITMENT
<--> EXP LEARNING
RELATIONSHIP
<--> TACIT LEARNING
LEARNCAPA
<--> CULTURE
RELATIONSHIP
<--> INTENT
LEARNCAPA
<--> PROTECT
ASSISTANCE
<--> INTENT
TEAMWORK
<--> PROTECT
COMMITMENT
<--> ASSISTANCE
TEAMWORK
<--> EXP LEARNING
RELATIONSHIP
<--> EXP LEARNING
INTENT
<--> CULTURE
RELATIONSHIP
<--> PROTECT
ASSISTANCE
<--> LEARNCAPA
TEAMWORK
<--> INTENT
COMMITMENT
<--> PROTECT
ASSISTANCE
<--> EXP LEARNING
TEAMWORK
<--> TACIT LEARNING
DYNAMISM
<--> TEAMWORK
DYNAMISM
<--> COMMITMENT
COMPETENCE
<--> RELATIONSHIP
Estimate
.589
.751
.690
.701
.743
.661
-.095
.133
.208
-.002
-.098
.054
.100
.507
.503
-.001
.111
-.149
.097
-.005
.174
.442
.137
-.098
-.079
.191
.132
-.088
.344
.462
.414
.364
.378
Lower
.491
.676
.608
.611
.653
.538
-.193
-.027
.032
-.189
-.224
-.081
-.037
.300
.388
-.138
-.032
-.300
-.057
-.168
.016
.319
-.009
-.256
-.203
.035
-.046
-.243
.177
.338
.256
.217
.228
Upper
.689
.823
.763
.778
.812
.753
.068
.314
.341
.155
.056
.179
.249
.616
.607
.164
.293
.042
.258
.172
.353
.572
.296
.061
.089
.313
.287
.056
.467
.597
.562
.478
.503
p
.010
.010
.010
.010
.010
.010
.295
.189
.020
.927
.286
.425
.180
.010
.010
.953
.177
.177
.226
.848
.028
.010
.070
.380
.400
.016
.141
.250
.010
.010
.010
.010
.010
164
Correlation between
PROTECT
<--> CULTURE
ASSISTANCE
<--> RELATIONSHIP
TEAMWORK
<--> LEARNCAPA
COMMITMENT
<--> INTENT
EXP LEARNING
<--> PROTECT
DYNAMISM
<--> ASSISTANCE
COMPETENCE
<--> TEAMWORK
COMPETENCE
<--> COMMITMENT
DYNAMISM
<--> CULTURE
DYNAMISM
<--> RELATIONSHIP
COMPETENCE
<--> LEARNCAPA
TEAMWORK
<--> RELATIONSHIP
COMMITMENT
<--> RELATIONSHIP
COMMITMENT
<--> CULTURE
TEAMWORK
<--> CULTURE
ASSISTANCE
<--> CULTURE
COMMITMENT
<--> LEARNCAPA
COMMITMENT
<--> TACIT LEARNING
EXP LEARNING
<--> CULTURE
DYNAMISM
<--> PROTECT
COMPETENCE
<--> PROTECT
TACIT LEARNING
<--> PROTECT
TACIT LEARNING
<--> LEARNCAPA
TACIT LEARNING
<--> INTENT
ASSISTANCE
<--> TACIT LEARNING
COMPETENCE
<--> INTENT
COMPETENCE
<--> ASSISTANCE
DYNAMISM
<--> INTENT
DYNAMISM
<--> LEARNCAPA
EXP LEARNING
<--> INTENT
EXP LEARNING
<--> LEARNCAPA
TACIT LEARNING
<--> CULTURE
COMPETENCE
<--> CULTURE
Estimate
.084
.122
.111
.192
-.201
.207
.451
.329
-.132
.318
.400
.286
.120
.041
-.112
.034
.134
.289
-.057
-.220
-.260
-.318
.449
.413
.195
.345
.237
.349
.413
.387
.438
-.248
-.147
Lower
-.090
-.052
-.010
.007
-.334
.072
.306
.162
-.287
.148
.254
.142
-.061
-.109
-.280
-.121
-.008
.136
-.200
-.342
-.384
-.440
.289
.200
.055
.157
.089
.176
.289
.143
.287
-.377
-.271
Upper
.188
.251
.223
.373
-.009
.338
.568
.444
.048
.439
.512
.423
.287
.186
.035
.196
.294
.406
.079
-.011
-.035
-.022
.584
.535
.308
.470
.365
.495
.528
.533
.587
.000
.043
p
.431
.160
.079
.047
.033
.010
.010
.010
.176
.010
.010
.010
.255
.646
.220
.704
.069
.010
.486
.029
.026
.013
.010
.010
.010
.010
.010
.010
.010
.010
.010
.064
.142
It is also noted that the findings are proper because no offending estimates are found
(Hair et al, 1998).
Table 5.16 shows that all 66 estimates of correlations between pairs of constructs
have values ranging from -0.318 to 0.751. All of the 95% confidence intervals of
these correlations do not contain 1.0. Consequently, discriminant validity is achieved
for the whole measurement model. This means all 12 constructs in the current
research are distinct from one another.
5.9. SUMMARY
This chapter first describes the sample characteristics. It then reports the procedure
and results of EFA and CFA to assess and refine the measurement scales of the 12
constructs composing the measurement model.
The application of EFA consists of two steps. Firstly, EFA and reliability analysis
were applied to assess and refine each of the 12 original scales. Through this process,
5 items were eliminated from the original 61 items. Then, the remaining 56 items
were subjected to a common factor analysis for the preliminary assessment of
unidimensionality, convergent and discriminant validity. This process resulted in a
set of the 12 satisfactory scales of which the number of indicators for each scale
ranges from 3 to 8 items.
The application of CFA consists of three further steps. Firstly, CFA was applied to
each of the 12 scales to affirm the unidimensionality and convergent validity. The
composite reliability of each scale was also calculated based on their factor loadings.
As a result, two more items were eliminated from further analyses. The 12 scales in
consisting
of
the
54
remaining
items
achieved
satisfactory
levels
of
unidimensionality, convergent validity and reliability. Secondly, discriminant
validity was tested among six pairs of constructs that are theoretically related to each
other. The results affirmed the discriminant validity of the investigated constructs.
Lastly, CFA was applied to the full measurement model where all possible
correlations between any pairs of the 12 constructs were freely estimated. In this
model, 26 indicators for the 12 scales were constructed from the 54 original
indicators using the item parceling technique. The CFA resulted that correlations
between each pair of constructs are significantly different from unity. Thus,
165
discriminant validity of the 12 scales in the measurement model is supported by the
data set.
In conclusion, unidimensionality, reliability, convergent validity and discriminant
validity of the 12 scales are confirmed by the data set. The 26 composite indicators
for the 12 scales are acceptable for further analyses. Table 5.17 presents a summary
of the properties of the 12 scales.
Table 5.17: Summary of properties of the 12 scales
Construct
Management Commitment
(COMMITMENT)
Teamwork
(TEAMWORK)
Learning Intent
(INTENT)
Learning Capability
(LEARNCAPA)
Partner Assistance
(ASSISANCE)
Knowledge Protectiveness
(PROTECT)
Relationship Strength
(RELATIONSHIP)
Cultural Distance
(CULTURE)
Explicit Learning
(EXP LEARNING)
Tacit learning
(TACIT LEARNING)
Competence Improvement
(COMPETENCE)
Marketing Dynamism
(DYNAMISM)
No of Indicators
original parcel
Reliability
Cronbach Composite
Validity
(unidimensional,
convergent &
discriminant)
4
2
.911
.913
Satisfied
5
2
.923
.924
Satisfied
5
2
.901
.902
Satisfied
3
3
.928
.927
Satisfied
3
3
.911
.909
Satisfied
4
2
.926
.927
Satisfied
7
2
.944
.945
Satisfied
4
2
.896
.914
Satisfied
4
2
.909
.910
Satisfied
4
2
.922
.923
Satisfied
5
2
.903
.903
Satisfied
6
2
.910
.913
Satisfied
166
CHAPTER 6
TESTING THE THEORETICAL MODEL
AND HYPOTHESES
6.1. INTRODUCTION
As concluded in the previous chapter, all measurements of the investigated
constructs are satisfactory after some refinements. They represent the results of the
first step in a two-step approach in the Structural Equation Modeling (Hair et al,
1998; Baumgarner and Hamburg, 1996). This chapter proceeds to the second step
which involves the application of AMOS/SEM to estimate the structural model.
This chapter is organized as follows. After this introduction, Section 6.2 reports the
statistical estimation and assessment of the structural model. Section 6.3 describes
the model modification. Section 6.4 provides the results of the tests of hypotheses.
Finally, the last section is devoted to discussing the empirical results.
6.2. ASSESSMENT OF THE THEORETICAL MODEL
6.2.1. Structural equation modeling and the two-step approach
Structural Equation Modeling (SEM) is widely used in theoretical research in various
disciplines (Garver and Mentzer, 1999). It is one of the most popular and well-known
advanced approaches used in marketing research (Steenkamp and Baumgarner,
2000). It provides researchers with flexibility to (Chin, 1998):
̇
Model relationships among multiple predictor and criterion variables;
̇
Construct unobservable latent constructs;
̇
Model errors in measurements for observed variables; and
̇
Statistically test a priori substantive/ theoretical and measurement assumptions
against empirical data.
SEM allows researchers to investigate the measurement model and structural model
simultaneously (one-step modeling) or separately (two-step modeling). The separate
167
estimation of measurement model and structural model has been found to be the
commonly adopted technique (Baumgarner and Hamburg, 1996). This is because “in
the presence of misspecification, the usual situation in practice, a one-step approach
in which the measurement and structural submodels are estimated simultaneously
will suffer interpretational confounding” (Anderson and Gerbing, 1988, p. 418). To
avoid this misleading interpretation, the current research adopted the two-step
approach. The first step, i.e. the estimation of the measurement model, has already
been reported in section 5.8 of the previous chapter. This section focuses on the
second step, i.e. the application of AMOS to estimate the theoretical model.
6.2.2. The theoretical model: estimation and assessment
AMOS software was used to estimate the theoretical model based on the information
provided by the covariances matrix of the 26 composite indicators (Appendix 3). The
estimation method was the maximum likelihood (ML). As mentioned in Section
5.5.4, ML is based on the assumption that the observed variables are normally
distributed. This assumption has been shown to be met by the data (Section 5.8). To
repeat, all 26 composite indicators have kurtosis values ranging from –0.798 to
+0.251, and skewness values ranging from -0.557 to +0.345 (Appendix 5). All
indicators can be considered as normally distributed because all the values are less
than 3.0 for skewness and 10.0 for kurtosis (Kline, 1998). Another condition is that
ML requires a large sample size (Byrne, 2001). In this model estimation, this
requirement has also been met because HOELTER index is 224 which are above the
threshold of 200 (Table 6.1)
Table 6.1: Fit indexes for the theoretical model
Fit Indexes
Chi-square ( χ )
2
Estimates
312.91
dF
P
Chi-square/dF
TLI
CFI
RMSEA
HOELTER
281
.092
1.114
.992
.993
.023
224
168
Critical Value
>.05
<2
≥ .90
≥ .90
≤ .08
≥ 200
The resulting statistical estimates of the model are shown in Table 6.1. All indexes
indicate that the model achieves a satisfactory level of overall fit (Please refer to
Section 5.5.4 for model fit measures). The model and regression coefficients for the
hypothesized paths between constructs are shown in Figure 6.1.
In addition to the overall fit, it is necessary to identify any areas of misfit in the
model (Byrne, 2001). In this regard, AMOS yields the modification indexes that are
helpful for detecting the model misspecification. Modification indexes (MI) reflect
the extent to which the model is appropriate. For each fixed parameter specified in
the model, AMOS provides an MI value. This value represents the expected drop in
overall chi-square value if the parameter were to be freely estimated in a subsequent
run (Byrne, 2001). A substantial MI value is 7.88 which, if adopted, will lead to a
significant model improvement (Joreskog and Sorbom, 1993).
Table 6.2 shows that there are two parameters with MI values that are approximately
equal or greater than 7.88. These are the covariances of a) relationship strength and
teamwork (MI = 14.288); and b) learning intent and learning capability (MI = 7.789).
Model modification to improve its fit is therefore required.
169
Ass25
Ass26
Ass27
Prot2
.82
Capa23
.90
.88
.91
.89
.96
ASSISTANCE
.99
Int2
.91
LEARNCAPA
.21
Rel1
Int1
.91
.92
Prot1
Rel2
Capa24
Capa22
.25
.86
Tea1
.30
PROTECT
Tea2
INTENT
.23
.93
.91
-.12
.89
.24
-.23
RELATIONSHIP
TEAMWORK
.23
.39
.39
CULTURE
COMMITMENT
-.17
.98
Cul1
.40
.98
.88
TACIT LEARNING
Cul2
.51
Tacl2
COMPETENCE
.84
.88
.24
.37
Com1
.92
.38
.87
Tacl1
EXP LEARNING
.25
.27
.93
Expl1
DYNAMISM
.95
Imp1
.89
.94
Imp2
Dyn1
Figure 6.1: SEM Results for the theoretical model.
170
Expl2
Dyn2
.87
Com2
Table 6.2: Modification indexes for the theoretical model
M.I.
Par Change
Covariances:
RELATIONSHIP <-->
TEAMWORK
14.288
.240
INTENT
<-->
LEARNCAPA
7.789
.185
INTENT
<-->
COMMITMENT
6.750
.184
ASSISTANCE
<-->
LEARNCAPA
6.740
.257
ASSISTANCE
<-->
COMMITMENT
5.488
.247
eCom2
<-->
RELATIONSHIP
5.252
.092
eCom1
<-->
erel2
6.007
-.054
eexpl1
<-->
res4
6.628
-.046
erel1
<-->
etea1
5.176
.042
e26
<-->
eCom1
6.441
.071
Regression Weights:
Com2
<---
RELATIONSHIP
5.252
.100
Com2
<---
Rel2
5.519
.088
Int1
<---
Tea1
5.049
.083
Int1
<---
Tacl1
5.019
.089
Int1
<---
Rel1
5.914
.083
Com1
<---
Prot2
6.094
-.113
Dyn1
<---
Com1
5.045
.051
Rel1
<---
Capa23
7.025
.079
6.3. MODEL MODIFICATION
Although the statistics signify a model modification, this should only be done with
necessary theoretical support (Garver and Mentzer, 1999). The theoretical
justification for the suggested modification is explained as below.
6.3.1. Theoretical consideration
Teamwork and relationship strength: the literature shows that teamwork and
relationship strength reflect two dimensions of a broader construct of relationship
(Granovetter, 1973). In a study on the sharing of knowledge within an organization,
Hansen (1999) refers to them as instrumental relation and affective relation. In an
171
organization, if works are assigned and undertaken by teams in flexible ways, team
members have chances for frequent interaction and collaboration. By this repetitive
process, knowledge is shared and information exchanged. The frequency and quality
of information sharing signal the closeness of the relationship and the respect that
parties have for each other (Mohr et al., 1996). According to Cavusgil et al. (2003),
mutual frequent information sharing in close relationship includes formal and
informal exchange of meaningful and timely information. This kind of give-and-take
nurtures an open-minded and a non-defensive attitude which gradually develops a
team spirit characterized by trust and mutual understanding. In the presence of this
spirit, personal interaction among members would go beyond the working scope
which enhances the opportunities for people to share feelings, emotions,
collaborative experiences and mental models through physical, face-to-face contact
(Cavusgil et al., 2003). These characteristics are eventually the attributes of a strong
social relationship between partners’ staff.
Therefore, the path from teamwork to relationship strength as indicated by the MI is
theoretically justifiable.
Learning intent and learning capability: Management theory establishes that in an
organization, managerial actions are oriented towards achieving the organization’s
objectives (Stott and Walker, 1992). This principle is the base to justify the path from
learning intent to learning capability. Once the local partner has an intention to learn
from the foreign partner, they employ staff who are capable of learning to work in
the IJV (Tsang, 1998, 2001). These staff should be good at learning through both
formal training and practical work. They would have an appropriate educational
background in the field of marketing and/ or prior experience in the products/
services in the IJV’s industry/ market (Inkpen, 1998b). A group of staff with these
characteristics will enhance the learning capability of the local partner in an IJV. If
they are motivated by the local partner to learn from the foreign partner, the
knowledge acquisition will be effective (Hurley, 2002).
Therefore, it is reasonable to assume a causal relationship from learning intent to
learning capability.
172
6.3.2. The modified model
Given the above-mentioned theoretical and statistical considerations, the modified
model is formed by adding two relational paths to the original theoretical model. One
path is from teamwork to relationship strength; the other path is from learning intent
to learning capability. In other words, two regression parameters that are constrained
to zero in the original theoretical model are now freely estimated (Figure 6.2).
As shown in Table 6.3, all the fit indexes of the modified model are better than those
of the original model. Moreover, Table 6.4 shows that no MI value is greater than
7.88, which indicates that no further modifications are required. Thus, it can be
concluded with 95% confidence that the modified model is more closely aligned with
the data than the original theoretical model.
Table 6.3: Fit indexes for the modified model
Fit Indexes
Chi-square ( χ 2 )
Estimates
289.94
dF
P
Chi-square/dF
TLI
CFI
RMSEA
HOELTER
279
.314
1.039
.997
.998
.013
240
173
Critical Value
>.05
<2
≥ .90
≥ .90
≤ .08
≥ 200
Ass25
Ass27
Prot2
.82
Capa23
Ass26
.90
Capa22
.91
.92
Prot1
.89
.96
Rel2
Capa24
.88
ASSISTANCE
Int1
Int2
.91
.91
LEARNCAPA
.86
Tea1
.21
.21
Rel1
.23
.29
PROTECT
.97
Tea2
INTENT
.22
.93
.91
-.12
.90
.23
-.22
.28
RELATIONSHIP
TEAMWORK
.22
.38
.37
CULTURE
COMMITMENT
-.16
.98
Cul1
.40
.98
.88
.24
TACIT LEARNING
Cul2
.28
.94
.51
Tacl2
COMPETENCE
.84
.88
.24
.37
Com1
.93
.37
.88
Tacl1
EXP LEARNING
Expl1
DYNAMISM
.95
Imp1
.89
.94
Imp2
Dyn1
Figure 6.2: SEM Results for the modified model
174
Expl2
Dyn2
.87
Com2
Table 6.4: Modification indexes for the modified model
M.I.
Par Change
Covariances
INTENT
<-->
COMMITMENT
6.866
.187
ASSISTANCE
<-->
COMMITMENT
5.481
.247
Res6
<-->
ASSISTANCE
5.799
.234
eCom1
<-->
erel2
5.810
-.053
eexpl1
<-->
res4
6.622
-.046
e26
<-->
eCom1
6.426
.071
Regression Weights
LEARNCAPA
<---
ASSISTANCE
5.799
.157
Com2
<---
Rel2
5.533
.088
Int1
<---
Rel1
5.305
.078
Com1
<---
Prot2
6.091
-.113
Dyn1
<---
Com1
5.043
.051
Rel1
<---
Capa23
6.861
.078
6.3.3. Further assessment of the modified model
Another assessment of the modified model is related to the factor loadings of all
indicators in the model (Garver and Mentzer, 1999). Table 6.5 shows that the
standardized factor loadings of all indicators are above the threshold of 0.70 (the
range is from 0.825 to 0.981). On the other hand, the high factor loadings of the
composite indicators demonstrate that the use of item parcels through partial
disaggregation helps reduce random errors of the measuring items. This is because
the averaging (or summation) of original items to form composite indicators tends to
smooth out the random errors of the original items (Bagozzi and Heatherton, 1994).
175
Table 6.5: Factor loadings of indicators on respective constructs
Indicator / construct
Com1
Com2
Tea1
Tea2
Int1
Int2
Capa22
Capa23
Capa24
Ass25
Ass26
Ass27
Prot1
Prot2
Rel1
Rel2
Cul1
Cul2
Expl1
Expl2
Tacl1
Tacl2
Imp1
Imp2
Dyn1
Dyn2
<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<---
COMMITMENT
COMMITMENT
TEAMWORK
TEAMWORK
INTENT
INTENT
LEARNCAPA
LEARNCAPA
LEARNCAPA
ASSISTANCE
ASSISTANCE
ASSISTANCE
PROTECT
PROTECT
RELATIONSHIP
RELATIONSHIP
CULTURE
CULTURE
EXP LEARNING
EXP LEARNING
TACIT LEARNING
TACIT LEARNING
COMPETENCE
COMPETENCE
DYNAMISM
DYNAMISM
Unstandardized
loading
Estimate
p
1.000*
.853
1.000*
1.032
1.000*
1.007
1.000*
.943
.950
1.000*
.952
.851
1.018
1.000*
1.000*
1.117
1.038
1.000*
1.000*
1.001
1.000*
.975
1.000*
1.173
1.000*
1.089
...
.004
...
.003
...
.003
...
.005
.006
...
.003
.002
.004
...
...
.005
.004
...
...
.007
...
.004
...
.005
...
.006
Standardized loading
Estimate
p
.981
.871
.928
.910
.911
.859
.915
.882
.906
.904
.913
.825
.958
.892
.899
.975
.977
.881
.881
.926
.936
.877
.845
.938
.893
.949
.005
.005
.005
.004
.007
.004
.003
.004
.008
.005
.006
.005
.004
.005
.004
.006
.004
.004
.005
.005
.005
.002
.002
.007
.005
.006
Note: *: constrained to 1 for the unstandardized regression weights.
Regarding offending estimates, the AMOS results do not reveal any negative value
of variances. The standardized residuals of covariances show a few values greater
than 2.58, indicating a possible existence of a path from management commitment to
tacit learning (Appendix 6). However, this regression coefficient is not significant (β
= 0.058, p = 0.342) as shown later in Table 6.7.
When multiple explanatory factors are included in the same model to investigate
their association with a dependent variable, one of the issues of concern to
researchers is the possible inter-relationships among these explanatory factors (Hair
et al., 1992). In the current research, such relationships have been identified between
176
1) teamwork and relationship strength, and 2) between learning intent and learning
capability. There might be other possible relationships. But they may be trivial as
there are only two substantial MI values as described above.
Statistical estimates show further that all the squared multiple correlations, which
indicate the proportion of total variance of an endogenous construct explained by
their hypothesized antecedents, are above 0.50 (Chin, 2000). Particularly, the total
variance explained for tacit know-how acquisition is 0.624 (p = 0.023); for explicit
know-how acquisition is 0.531 (p = 0.030); for competence improvement is 0.604 (p
= 0.006) and for marketing dynamism is 0.592 (p = 0.011). These results indicate
that the majority of antecedents of the four focal constructs have been identified and
captured in the selected model.
Lastly, the standardized regression coefficients (Table 6.6) of all specified
relationships have been found ranging from 0.164 to 0.515 (absolute value) with p
≤0.05, except the non-significant coefficient of -0.119 (p = 0.063) from knowledge
protectiveness to explicit know-how acquisition. This result provides a base for the
tests of hypotheses which are discussed in the next section.
Table 6.6: Selected AMOS text outputs for the modified model
Regression weights
EXP LEARNING
EXP LEARNING
EXP LEARNING
EXP LEARNING
EXP LEARNING
EXP LEARNING
RELATIONSHIP
LEARNCAPA
TACIT LEARNING
TACIT LEARNING
TACIT LEARNING
TACIT LEARNING
TACIT LEARNING
TACIT LEARNING
TACIT LEARNING
COMPETENCE
COMPETENCE
DYNAMISM
DYNAMISM
DYNAMISM
<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<--<---
Unstandardized
Estimate
P
.242
.275
.219
.345
.143
-.121
.289
.287
-.149
.258
-.239
.345
.211
.187
.242
.296
.382
.216
.389
.199
INTENT
COMMITMENT
LEARNCAPA
TEAMWORK
ASSISTANCE
PROTECT
TEAMWORK
INTENT
CULTURE
EXP LEARNING
PROTECT
RELATIONSHIP
TEAMWORK
LEARNCAPA
INTENT
EXP LEARNING
TACIT LEARNING
TACIT LEARNING
COMPETENCE
EXP LEARNING
177
.017
.003
.008
.002
.005
.066
.003
.003
.006
.004
.002
.005
.004
.006
.003
.004
.002
.005
.002
.005
Standardized
Estimate
p
.234
.398
.291
.383
.209
-.119
.276
.209
-.164
.239
-.219
.373
.217
.231
.217
.370
.515
.276
.368
.236
.014
.003
.005
.003
.005
.063
.005
.003
.006
.004
.003
.004
.004
.005
.005
.005
.003
.006
.003
.008
6.4. TESTS OF HYPOTHESES
In this section, the standardized regression coefficients obtained from the modified
model are used to test the hypotheses stated in Chapter 3. As shown in Table 6.7, 11
out of the 12 hypotheses are fully supported (or not rejected, for a more strictly
statistical term), and one hypothesis (H6) is partially supported by the empirical data.
It should be noted that, all parameters with an (**) in Table 6.7 have been
constrained to zero because there is no hypothesized paths between those pairs of
constructs. For the illustration purpose, they have been estimated by rerunning
AMOS for the selected model. But in this time, those parameters with (**) are
relaxed for free estimation. Results show that all the regression correlations with an
(**) are not significant at p = 0.05. Therefore, the addition of these paths in the
model would not have improved the model fit significantly but made it less
parsimonious (Byrne, 2001). The detailed explanation about the test results of each
of the 12 hypotheses is presented below:
Hypothesis 1: “Management commitment has a greater positive influence on the
acquisition of explicit marketing know-how than on the acquisition
of tacit marketing know-how”.
The standardized coefficient of the path from management commitment
(COMMITMENT) to the acquisition of explicit marketing know-how (EXP
LEARNING) is significantly greater than zero ( β = 0.398, p = 0.003); whereas,
there is a non-significant relationship (β = 0.058, p = 0.342) between management
commitment and the acquisition of tacit marketing know-how (TACIT-LEARNING)
as indicated in Table 6.7. Therefore, H1 is supported by the empirical data. The
commitment of IJV management is evidently a determinant of the acquisition of
explicit marketing know-how from the foreign partner, while a non-significant effect
on the acquisition of tacit know-how has been found.
It should be noted that two items COM09 and COM10 had to be dropped from the
original scale for management commitment. Consequently, the interpretation of
management commitment should not include the process-based performance
evaluation and the management perception of the value of learning as addressed by
these two items. Instead, management commitment should include managerial
behavior such as policy, measures, and resources related to knowledge acquisition.
178
Table 6.7: Summary of hypothesis test statistics
H
H1
H2
H3
H4
H5
H6
H7
H8
Structural path relationship
COMMITMENT å EXP LEARNING
COMMITMENT å TACIT LEARNING
TEAMWORK å EXP LEARNING
TEAMWORK å TACIT LEARNING
INTENT å EXP LEARNING
INTENT å TACIT LEARNING
LEARNCAPA å EXP LEARNING
LEARNCAPA å TACIT LEARNING
ASSISTANCE å EXP LEARNING
Standardized
regression
coefficient
p
Hypothesis
test
+.398
.003
Supported
+.058 (**)
.342
+.383
.003
+.217
.004
+.234
.014
+.217
.005
+.291
.005
+.231
.005
+.209
.005
Supported
Supported
Supported
Supported
ASSISTANCE å TACIT LEARNING
-.009 (**)
.852
PROTECT å EXP LEARNING
-.119 (*)
.063
Partially
-.219
.003
Supported
-.096(**)
.156
Supported
+.373
.004
-.013(**)
.902
PROTECT å TACIT LEARNING
RELATIONSHIP å EXP LEARNING
RELATIONSHIP å TACIT LEARNING
CULTURE å EXP LEARNING
CULTURE å TACIT LEARNING
-.164
.006
Supported
H9
EXP LEARNING å TACIT LEARNING
+.239
.004
Supported
H10
EXP LEARNING å COMPETENCE
+.370
.005
Supported
+.515
.003
+.236
.008
+.276
.006
+.368
.003
H11
H12
TACIT LEARNING å COMPETENCE
EXP LEARNING å DYNAMISM
TACIT LEARNING å DYNAMISM
COMPETENCE å DYNAMISM
Note: (*): Not-significant at 0.05 level
(**): Results from additional estimation
179
Supported
Supported
Hypothesis 2: “Teamworking between foreign and local marketing staff has a
positive effect on the acquisition of both explicit and tacit marketing
know-how”.
The standardized regression coefficient of teamwork on the acquisition of explicit
marketing know-how is significantly greater than zero ( β = 0.383, p = 0.003). The
regression coefficient of teamwork on the acquisition of tacit marketing know-how is
also significantly greater than zero ( β = 0.217, p = 0.005). These figures indicate
that H2 is supported by the data.
The results empirically confirm that in an IJV where marketing activities are carried
out in teams, the local partner’s staff (i.e. the learners) have favorable conditions for
learning both explicit and tacit know-how from their partners. In such situation,
learning is facilitated by the underlying characteristics of teamwork such as open
communication, collaboration, group problem solving and personal interaction as
reflected by the indicators of this construct.
Teamwork also has an indirect impact on the acquisition of tacit know-how (see
Figure 6.2). That is, its impact through relationship strength ( β = 0.276, p = 0.005)
which, in turn is a predictor of the acquisition of tacit marketing know-how. This
result again confirms the distinction between the two constructs: teamwork and
relationship strength. Although the two are significantly correlated, the former
captures the coordination mechanism and structural arrangement of tasks, while the
latter emphasizes the social ties between partners’ staff as members of an
organizational community.
Hypothesis 3: “The learning intent of the local partner has a positive influence on
the acquisition of both explicit and tacit marketing know-how.”
The SEM results indicate that H3 is supported as the standardized regression
coefficient of INTENT on EXP LEARNING is 0.234 (p = 0.014) and that of
INTENT on TACIT LEARNING is 0.217 (p = 0.004) which are both significant at
p< 0.05. These resulting values confirm the positive effect of learning intent on the
amount of marketing know-how acquired in both tacit and explicit forms.
The effect of learning intent on tacit and explicit marketing know-how acquisition is
further strengthened by the indirect path from learning intent to learning capability
180
( β = 0.209, p = 0.003) and then from learning capability to tacit and explicit knowhow acquisition. This result again emphasizes the role of learning intent as a driver
for learning behavior.
The five items in the measurement scale of learning intent implies that it must exist
in both individual and organizational levels. At the organizational level, the learning
objective and related supportive resources should be defined and provided by the
local partner. At the individual level, the attitude and behavior of the local marketing
staff working in the IJV should be positively directed towards learning from the
foreign partner. The fact that all five items converge well suggests that researches in
organizational learning should consider both organizational and individual learning
views as advocated by authors such as Hamel (1991), Nevis et al. (1995), Tiemessen
et al. (1997) and Solingen et al. (2000). This is because organizations learn only
through their individual members (Argyris and Schön, 1978).
Hypothesis 4: “The learning capability of the local partner has a positive influence
on the acquisition of both explicit and tacit marketing know-how”.
As shown in Table 6.7, the standardized regression coefficient of learning capability
on the acquisition of explicit know-how is 0.291 (p = 0.005), and that of learning
capability on the acquisition of tacit know-how is 0.231 (p = 0.005). Both
coefficients are significant at p< 0.05. Thus, learning capability of local staff has a
positive effect on the acquisition of both explicit and tacit marketing know-how. In
other words, H4 is supported by the empirical data.
In interpretation, it should be noted that learning capability in this study is
constructed around prior experience of the learners with marketing and the marketing
knowledge obtained through formal education, i.e. university degree. This construct
is broader than the concept of absorptive capacity proposed by Cohen and Levinthal
(1990) which emphasizes on prior experience only.
Hypothesis 5: “Partner assistance provided by the foreign partner in an IJV has a
greater positive influence on the acquisition of explicit than that of
tacit marketing know-how”.
The standardized regression coefficient of marketing assistance (ASSISTANCE) on
the acquisition of explicit marketing know-how (EXP LEARNING) is 0.209 (p =
181
0.005). In contrast, no significant regression coefficient ( β = -0.009, p = 0.852) is
found for the path from ASSISTANCE to TACIT LEARNING. Thus, it can be
concluded that H5 is supported by the empirical data. In other words, the provision
of training assistance by the foreign partner to the IJV would mainly have a positive
influence on the acquisition of explicit marketing know-how. As described in
Chapter 3, the assistance could include formal training of local marketing staff,
provision of guideline, procedure, rule of thumb or database to the IJV so that the
local marketing staff could learn from explicit documents (Lyles et al, 1999). In this
study, the item measuring the number of foreign marketing personnel working in the
IJV is not a relevant indicator of foreign partner assistance (Inkpen, 1998; Tsang,
2001). The data shows that in the majority of cases (65.8%), the number of foreign
marketing staff working in the IJV is very limited, typically one or two.
Hypothesis 6: “Knowledge protectiveness has a negative influence on the
acquisition of both tacit and explicit marketing know-how”.
The results in Table 6.7 have led to the conclusion that H6 is only partially
supported. The standardized regression coefficient of PROTECT on TACIT
LEARNING (β = -0.219, p = 0.003) indicates a significant negative causal
relationship, while the regression coefficient of PROTECT on EXP LEARNING (β
= -0.119, p = 0.063) shows no significant relationship at 95% confidence level. This
result seems to imply that a certain extent of explicit marketing know-how is
transferred to the IJV by the foreign partner whether deliberate or not. The stronger
the marketing assistance, the higher level of explicit marketing knowledge acquired
by the local partner. This result is consistent with the empirical result of a study of
IJV in Malaysia (Lyles et al., 1999).
Hypothesis 7: “Relationship strength has a greater positive influence on the
acquisition of tacit marketing know-how than that of explicit
marketing know-how”.
The result shows an empirical support to H7. As described in Table 6.7, the
standardized regression coefficient of RELATIONSHIP on TACIT LEARNING is
0.373 (p = 0.004); while no significant relationship is found between this antecedent
and EXP LEARNING ( β = -0.096, p = 0.156).
Compared to those of the other antecedents of tacit know-how acquisition, the
182
coefficient for relationship strength is the highest. This means that strength of the
relationship between the foreign and local staff has the strongest effect on how much
the local staff learn from the foreign partner in terms of undocumented know-how.
The result emphasizes the importance of maintaining a good social or personal
interaction between partners’ staff. Characteristics such as a sense of trust and
confidence in each other, a supportive attitude and a climate of free sharing of
feelings and ideas are very important and necessary for the acquisition of tacit knowhow because they are the manifestation of a strong relationship between partners’
staff.
Hypothesis 8: “Cultural distance has a greater negative influence on the acquisition
of tacit marketing know-how than on that of explicit marketing
know-how”.
The figures in Table 6.7 show that the standardized regression coefficient of
CULTURE on TACIT LEARNING is -0.164 (p = 0.006). But no significant
relationship is found for the path from CULTURE to EXP LEARNING ( β = -0.013,
p = 0.902). Therefore, it could be said that H8 is supported.
The relatively small (absolute) regression coefficient of -0.164 for the path from
CULTURE to TACIT LEARNING and the non-significant coefficient of CULTURE
on EXP LEARNING imply that the difference in partners’ cultures is not a key
inhibitor of the acquisition of marketing know-how. This result reflects the effect of
acculturation (i.e. learning about the partner’s culture) or cultural adjustment process
(i.e. an individual becomes adjusted to the partner’s culture) in the global business
nowadays (Lueke and Svyantek, 2000; Parker and McEvoy, 1993). If this process
occurs in both partners’ staff, cultural distance only plays a modest role in
determining tacit marketing know-how acquisition, and a non-significant role in the
case of explicit know-how acquisition from the foreign partner.
Hypothesis 9: “The extent of explicit marketing know-how acquired from the
foreign partner has a positive effect on the acquisition of tacit
marketing know-how”.
The standardized regression coefficient of EXP LEARNING on TACIT LEARNING
is significantly greater than zero ( β = 0.239, p = 0.004). That is, the extent of
explicit marketing know-how acquired from foreign partner has a positive effect on
183
the extent of tacit marketing know-how acquired. Consequently, it can be concluded
that H9 is supported empirically.
This result confirms that the acquired explicit marketing know-how facilitates the
acquisition of tacit marketing know-how. Although tacit know-how cannot be
learned through codified marketing materials, written guidelines or documents, an
increase in the explicit know-how in the same area (i.e. marketing) would enhance
the existing stock of knowledge, which in turn, improves the cognitive process of the
learner (Hackley, 1999). This is because “the more we know, the more we can learn”
(Brockmann and Anthony, 2002, p.439). Additionally, the increase in explicit knowhow would improve the tacit know-how through the process of knowledge
internalization, i.e. the new explicit knowledge is internalized to create new tacit
knowledge (Nonaka, 1994).
Hypothesis 10: “Tacit marketing know-how acquired from foreign partner has
greater positive impact on the improvement of marketing
competence than explicit marketing know-how”.
As shown in Table 6.7, the standardized coefficient representing the effect of the
acquisition of tacit marketing know-how on the improvement of marketing
competence is 0.515 (p = 0.003); whereas, that value for the relationship between the
acquired explicit marketing know-how and marketing competence improvement is
0.370 (p = 0.005). These figures indicate that both tacit and explicit marketing knowhow acquired from the foreign partner would lead to a significant improvement in the
marketing competence of the local members working in the IJV. Moreover, these
statistics also show that the accumulation of tacit marketing know-how ( β = 0.515)
leads to a greater improvement of marketing staff, in comparison with the effect
caused by the accumulation of explicit marketing know-how ( β = 0.370). Thus, it
can be concluded that H10 is supported.
This finding provides evidence to the view that learning helps increase the capacity
to take effective action (Kim, 1993; Probst et al., 1997). It also demonstrates
empirically the greater value of tacit know-how relative to explicit know-how value
as an element contributing to the competences of a firm (Inkpen, 1998; Mohr and
Sengupta, 2002; Cavusgil et al., 2003).
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Hypothesis 11: “Both explicit and tacit marketing know-how acquired from foreign
partner have positive impact on marketing dynamism”.
The standardized regression coefficient of explicit marketing know-how acquisition
on marketing dynamism is 0.276 (p = 0.006). That values for tacit marketing knowhow acquisition is 0.236 (p = 0.008). These two values are significant at p < 0.05.
Thus, H11 is supported in this empirical test. This result indicates that tacit and
explicit marketing know-how acquired from the foreign partner has a significant
direct impact on marketing dynamism which is initiated by the local staff.
The direct impact could be the result of single-loop learning (Argyris and Schon,
1978) which is characterized by continuous improvement/ adjustment through
experience and feedback. By its operational manifestations, marketing dynamism is
reflected by changes in marketing programs such as sales programs, pricing policy,
sales promotion, advertising programs. Once the local staff acquire more marketing
know-how in both explicit and tacit forms, they are more capable of diagnosing the
existing marketing activities, identifying areas of inappropriateness, and developing
corrective marketing actions. These behavioral changes reflect a direct impact of
knowledge acquisition, i.e. single-loop learning. In this situation, this finding
supports the notion that learning is the change in the individual or group behavior
leading to the change in the behavior of the organization itself (Reynolds and Ablett,
1998; Bogner et al., 1999).
Hypothesis 12: “The improvement of marketing competence has a positive impact
on marketing dynamism”.
The figures in Table 6.7 show that the standardized regression coefficient of
COMPETENCE on DYNAMISM is 0.368 (p = 0.003) which is significant at p<
0.05. Therefore, H12 is also supported.
This hypothesis indicates the indirect impact of the marketing know-how acquired
from the foreign partner on the observable outcomes through the intermediate
construct of marketing competence improvement. The results show that both
constructs representing the learning outcomes (marketing dynamism and marketing
competence improvement) are appropriate in this research. The former represents the
result of direct / single-loop effect of the knowledge acquired from partner. It reflects
the result of the instrumental use of the acquired know-how (Menon and
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Varadarajan, 1992). The latter is more latent. It represents an improvement in the
capability of the learner in coping with marketing tasks or problems. The utilization
of the competence that has been accumulated along with the conceptual or symbolic
use of the acquired know-how will lead to changes in marketing programs (Menon
and Varadarajan, 1992).
In summary, of the 12 hypotheses being tested, 11 have been found full support
from the data. The extent of the linear relationships has been shown to be statistically
significant with p value less than 0.05. Only one hypothesis (H6) is found to have
partial support. In this hypothesis, the negative effect of knowledge protectiveness on
the tacit know-how acquisition is found to be statistically significant; while the
hypothesized effect on the explicit know-how acquisition is not statistically
significant.
6.5. DISCUSSIONS
The results presented in the previous sections are discussed further in this section.
The discussion is organized around five issues: the selected model, the antecedents of
know-how acquisition, the explanatory power of the eight antecedents, the separate
examination of tacit and explicit know-how, and the outcomes of know-how
acquisition.
6.5.1. On the selected model
It is first confirmed that the initially hypothesized model did achieve a satisfactory
level of fit. However, the modified model is found to be superior to the initial model.
A detailed comparison reveals that the test results of all hypotheses remain
unchanged in the modified model. With the view to build the best possible model to
reflect the data, the modified model is the final choice. Given the substantive theory
base, all significant linear relationships among the 12 constructs are identified and
estimated in this model. Two additional relationships have been identified, i.e. from
teamwork to relationship strength, and from learning intent to learning capability.
They represent the interrelationships between the antecedents of know-how
acquisition. This finding addresses one of the research issues raised previously in
Section 1.2.1 and Section 2.5.2 about the demand for examining several antecedent
factors at the same time to see whether they interact with each other or not.
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The modified model also demonstrates the state of parsimony. More parameters
being relaxed for free estimation would contribute trivially to the fit of the model
with the data (i.e. the improvement of fit indexes is non-significant). This state is
achieved because no MI value is greater than the threshold of 7.88. Some values of
the standardized residuals are slightly greater than 2.58 but they can be ignored as
they do not imply a significant relation (as in the case of partner assistance and
learning capability described previously).
6.5.2. On the antecedents of know-how acquisition
The eight antecedents have been found to have important facilitating/inhibiting
impact on the acquisition of marketing know-how in IJVs. The findings show that
they have different effects on the acquisition of tacit and explicit marketing knowhow. In Chapter 3, the eight facilitators were framed to represent four structural
dimensions of IJVs: a) IJV features (management commitment and teamwork), b)
knowledge holders (partner assistance and knowledge protectiveness), c) knowledge
seekers (learning intent and learning capability), and d) matching factors
(relationship strength and cultural distance). The findings in this research show that
with some adjustments, this conceptual frame provides a relevant background to
develop the theoretical model, because all of the eight antecedents are found to have
significant effects on one or both forms of know-how acquisition.
In addition, the findings in this research can enrich the literature on organizational
learning by suggesting a different typology of the facilitators/ inhibitors of
knowledge acquisition in IJVs. Based on the form of know-how that a factor has a
significant impact on, three groups of facilitators can be identified.
̇
The first group includes factors that significantly influence the acquisition of only
explicit marketing know-how. They are management commitment and partner’s
marketing assistance. Compared to previous studies, the finding that management
commitment only facilitates explicit know-how acquisition provides a deeper
insight into the knowledge acquisition. So far in the extant literature, studies of
the impact of management commitment have been dominated by theoretical
propositions or case studies, in which the acquisition of knowledge was discussed
in general sense without specifying explicit or tacit form (Choi and Lee, 1997;
Morrison and Mezentseff, 1997; Inkpen, 1998a; Hurley, 2002). In contrast, the
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result in this research provides both theoretical and statistical evidence to indicate
that IJV management commitment indeed has an effect only on explicit learning.
Therefore, if the local partner intends to learn tacit know-how from the foreign
partner, then the commitment of IJV management is not enough to facilitate this
form of learning. With regard to the partner’s marketing assistance, this finding
provides an empirical support to the theoretical proposition of Tsang (2001). It
also furthers the empirical finding by Lyles et al. (1999) by indicating which
form of knowledge acquisition is facilitated by the partner assistance.
̇
The second group includes factors that significantly influence the acquisition of
only tacit marketing know-how. They are relationship strength, knowledge
protectiveness and partner’s cultural distance. This empirical result is consistent
with the finding of Cavusgil et al. (2003) in an empirical study of 182
manufacturing and service firms in the US. It reinforces the importance of
relationship strength in facilitating knowledge acquisition which is found in
previous studies (Szulanski, 1996; Wathne et al., 1996; Kale et al., 2000; Clarke
et al., 1998). It further indicates that relationship strength has a strong impact
only on the acquisition of tacit know-how. This result again shows that the
separate investigation of teamwork and relationship strength would provide more
insights into the different facilitators of knowledge acquisition. While their
difference in the conceptual domain has already been discussed in the previous
chapters, the result in this chapter demonstrates their empirical difference.
Previous researches found that if knowledge is investigated in a general sense,
cultural distance has trivial impact (Simonin, 1999b) or non-significant impact
(Lyles et al., 1999) on the knowledge acquisition. By investigating separately
tacit and explicit know-how acquisition, this research shows that cultural distance
has impact only on the transfer of tacit know-how. Therefore, this result is not
contradictory but it provides a deeper explanation of the impact of cultural
distance.
̇
The third group includes factors that have significant influence on the acquisition
of both explicit and tacit marketing know-how. They are teamwork, learning
intent and learning capability. Particularly, the results in this research provide one
among very rare empirical evidences on the importance of teamwork as an
antecedent of knowledge acquisition in an IJV context (Simonin, 1999b).
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Moreover, the result on the impact of learning intent and learning capability on
the knowledge acquisition in both forms reinforces previous findings about the
important roles of these antecedents (Mowery et al, 1996; Moon, 1999; Lyles and
Salk, 1996; Szulanski, 1996, Lane and Lubatkin, 1998). It is an empirical
evidence for the notion in the adult learning theory that the motivation and
learning capacity of the leaner are most important for effective learning (Kalling,
2003; Hurley, 2002; Brockmann and Anthony, 2002).
6.5.3. On the explanatory power of the eight antecedents
The model specifies five significant antecedents facilitating/inhibiting the acquisition
of explicit marketing know-how (management commitment, teamwork, learning
intent, learning capability and partner assistance). It also indicates seven significant
antecedents of the acquisition of tacit marketing know-how (teamwork, learning
intent, learning capability, knowledge protectiveness, relationship strength, cultural
distance and explicit know-how acquisition). Although the purpose of this research is
not to identify an exhaustive list of the antecedents, the empirical results show that
these antecedents capture a significant part of the variance of the two focal
constructs. The five antecedents of explicit marketing know-how explain 53.1% (p =
0.030) of its variance. The seven antecedents of tacit marketing know-how explain
62.4% (p = 0.023) of its variance. The integration of several factors into the model
provides a picture in which the contribution of each factor to explain the variance of
each focal construct can be identified. Moreover, through simultaneously examining
these factors in the model, the interaction among them can also be identified. Thus,
the comprehensive structure of all involved constructs can be drawn.
6.5.4. On the separate examination of tacit and explicit know-how
The result of the empirical test supports the separate examination of tacit and explicit
marketing know-how. They are distinct from each other from conceptual,
measurement and managerial points of view. Firstly, they are conceptually two
different constructs representing two forms of marketing knowledge. Each has its
own features that determine the conditions for its acquisition (Polanyi, 1966).
Secondly, from the measurement point of view, these two constructs are measured
separately by theirs own scales and they achieve discriminant validity to support the
notion that they are separate constructs. When being put together in the same model
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they are found to be distinct but related constructs. The findings show that the
acquisition of explicit marketing know-how also has an influence on the acquisition
of tacit marketing know-how. Thirdly, the identification of two different sets of
antecedents for each form (tacit versus explicit) of marketing know-how would
provide different backgrounds for managerial implications of each form. Moreover,
each of these constructs has different role and value in the contribution to the
learning outcomes as discussed in the following section.
6.5.5. On the outcomes of marketing know-how acquisition
The second part of the tested model is about the learning outcomes. It specifies the
relationships between the two forms of know-how acquired and two constructs
representing the learning outcomes (i.e. competence improvement and marketing
dynamism). The findings show that the selection of these two constructs is
empirically relevant. Theoretically, they reflect both conceptual outcome and
instrumental outcome of organizational learning (Preskill and Torres, 1999).
Empirically, both tacit and explicit know-how acquisition have significant effects on
each of these two constructs. The statistics show that the tacit and explicit know-how
acquired can explain 60.4% (p = 0.006) of the variance of marketing competence
improvement of local staff.
The findings provide empirical evidence to support the theoretical discussions of
several authors in the literature (Dunphy et al, 1997; Bogner et al, 1999; Menon and
Varadarajan, 1992; Inkpen, 1997). It also supports the notion that tacit knowledge
has potentially greater value to the local partner than explicit knowledge (Mohr and
SenGupta, 2002; Lawson and Lorenzi, 1999).
The current research finds that tacit and explicit marketing know-how acquired from
the foreign partner have significant influence on the marketing dynamism as a result
of single-loop learning (Sinkula et al., 1997; Fiol and Lyles, 1985). Together with the
contribution of marketing competence improvement which represents the result of
double-loop learning, these antecedents explain 59.2% (p = 0.011) of the variance of
marketing dynamism. Although these outcomes of inter-partner learning do not
directly reflect the benefit of the local partner because they measure the outcomes
within the IJV, they provide relevant constructs for measuring the learning outcomes
at the first stage of interpartner learning as described by Tiemessen et al (1997).
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CHAPTER 7
CONCLUSIONS
7.1. OVERVIEW
The purpose of the current research is twofold. Firstly, it is aimed at identifying and
testing various antecedents of the acquisition of tacit and explicit marketing knowhow from the foreign partner in IJVs. Secondly, it investigates how different forms
of the marketing know-how acquired from the partner impact the two constructs of
learning outcomes.
To achieve the above-stated purpose, this research adopted the process as follows.
Firstly, literature related to organizational learning, international joint ventures and
learning in joint ventures was reviewed. Based on this review and the identification
of research gaps, the theoretical model and hypotheses were developed. Then, the
methodology to test the model was formulated. In this methodology, the quantitative
approach with large sample survey was employed. The data was collected from 219
IJVs in Vietnam. The collected data was first used to assess and refine the
measurement scales of all constructs under study. This was done primarily by the
exploratory and confirmatory factor analyses. Then, the data was subjected to
structural equation modeling to obtain statistics for testing and modifying the
structural model.
In this final chapter, after this introductory section, the main findings are summarized
in section 7.2. Then the theoretical and methodological contributions are outlined in
section 7.3, which also discusses the managerial implications of the research. The
chapter ends with section 7.4 discussing the research limitations and the directions
for further researches.
7.2. SUMMARY OF THE FINDINGS
The findings are summarized around three key issues mentioned in the research
objectives: explicit versus tacit marketing know-how acquisition, facilitators of
explicit/tacit marketing know-how acquisition, and learning outcomes.
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Firstly, the current research examines the acquisition of two distinct but related
constructs, namely tacit and explicit marketing know-how. Results suggest that these
two forms of know-how should be studied separately in a single model in terms of
their theoretical relationships with other constructs, measurement scales and
managerial implications. It is further emphasized that the current research departs
from the common view that the whole body of knowledge under investigation is
“homogeneous” in terms of tacitness. In this research, the whole body of marketing
know-how is seen as comprising many particles: some are purely tacit and others are
purely explicit. This distinction is supported both conceptually and empirically. It
provides a deeper level of analysis of the knowledge under study.
Secondly, eight facilitators have been identified and tested their impact on the tacit
and explicit marketing know-how acquisition. On the local partner part, learning
intent and learning capability are two critical factors influencing the acquisition of
both tacit and explicit marketing know-how. Moreover, learning intent has an effect
on learning capability. On the foreign partner part, knowledge protectiveness has a
significant negative effect on the acquisition of tacit marketing know-how. In
contrast, partner assistance in marketing has a positive effect on the acquisition of
explicit marketing know-how. Within the IJV, management commitment is the most
critical determinant of the acquisition of explicit know-how. Teamwork provides a
favorable condition for the acquisition of both explicit and tacit marketing knowhow. Teamwork also has a positive effect on relationship strength. In the matching
factors, the stronger the social relationship between partner staff, the larger the
amount of tacit marketing know-how acquired. In contrast, the wider the cultural
distance between partners’ staff, the more difficult for tacit know-how to be
acquired.
Thirdly, both marketing competence improvement and marketing dynamism are
significantly influenced by the amount of tacit and explicit marketing know-how
acquired. Of these two constructs, marketing competence improvement is more
latent. Its extent of improvement is more sensitive to the acquisition of tacit
marketing know-how compared to that of explicit marketing know-how. In turn, the
marketing competence improvement, together with the acquired tacit and explicit
know-how, contributes significantly to the explanation of changes in marketing
programs.
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7.3. CONTRIBUTIONS AND IMPLICATIONS
In this section, the contributions and implications of the research findings are
presented in reference to the research gaps identified in Chapter 1 (Section 1.2.1
through 1.2.5).
7.3.1. Theoretical contributions
The current research is among the attempts to link organizational learning
perspective and strategic alliance literature. It extends the understanding of interorganizational learning to the transnational situation where organizational learning
with an international perspective is an under-researched area (Easterby-Smith, 1997).
Particularly, the importance of learning of management knowledge in IJVs has only
recently emerged in the literature (Liu and Vince, 1999).
Firstly, as identified previously (in Section 1.2.3), “the literature is silent on the
transfer to the IJVs of management expertise, a specific type of non-technological
know-how” (Wong et al, 2002. p.2). Particularly, the acquisition of marketing
knowledge has been relatively less researched (Simonin, 1999b). The current
research has bridged this gap by focusing on the investigation of marketing knowhow acquisition through IJVs. It also contributes to tackle the type of knowledge that
is deemed to be more difficult to learn through IJVs (as compared to technological
knowledge) due to its social and cultural embededness (Wong et al., 2002).
Secondly, Section 1.2.1 identified a demand for studies that examines several
antecedent factors simultaneously. By the simultaneous examination of the eight
factors, this research provides an integrated conceptual model of the antecedents of
marketing know-how acquisition from foreign partner in an IJV. It helps explain and
predict the separate effect of each antecedent on the acquisition of marketing knowhow. It also allows the identification of relevant interrelationships among the
antecedent factors.
Thirdly, by investigating separately the two forms of marketing know-how (i.e. tacit
and explicit) in a single model, the current research has addressed the gap on
knowledge tacitness which was raised in Section 1.2.2. It provides evidence that tacit
and explicit marketing know-how are distinct but related to each other from both
conceptual and empirical points of view. Moreover, this research empirically
confirms that tacit know-how is more valuable than explicit know-how in developing
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the marketing competence of the learners, who are the local marketing staff working
in the IJV.
Fourthly, the use of competence improvement and marketing dynamism has been
shown to be an appropriate solution to the issue raised in Section 1.2.4 on the
learning outcomes (Easterby-Smith and Araujo, 1999). These two measures are able
to capture the results of the process of learning from the foreign partner in IJVs.
They reflect the different effects of each form on the know-how acquired as a result
of the single-loop (i.e. marketing dynamism) and double-loop learning (i.e.
competence improvement). At the same time, they provide appropriate measures for
the learning outcomes of the local partner but immediately and directly at the site and
context of learning.
7.3.2. Methodological contribution
The last gap described in section 1.2.5 was about the lack of empirical research in the
field. The current research has addressed this gap by the adoption of a research
methodology which is characterized by a large sample survey.
Firstly, the current research constitutes an empirical attempt to answer the call for
statistical evidence to test theoretical propositions about organizational learning
(Easterby-Smith and Araujo, 1999). With 219 cases of IJV in Vietnam, the sample
comprises a large variety of characteristics such as foreign partners’ country of
origin, national culture, IJVs’ industry and age. These attributes would help
minimize possible biases caused by specific demographic features. Moreover, the
current research provides empirical evidence from Vietnam, a developing country
where a market economy has just emerged for less than two decades. Therefore, the
results in this research would contribute to the validation of theories on interpartner
learning in the international arena.
Secondly, through careful design and validation, the current research provides a set
of measurement scales for the 12 constructs under investigation. Of these 12 scales,
five were adopted from previous studies after relevant adjustments, and seven have
been newly developed. The newly developed scales are those for 1) management
commitment, 2) teamwork, 3) learning intent, 4) learning capability, 5) marketing
competence improvement, 6) explicit marketing know-how acquisition, and 7) tacit
know-how acquisition. Through the processes of careful operationalization of
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constructs and the hierarchical approaches using EFA and CFA, these scales have
been tested and refined to meet criteria of unidimensionality, reliability, content
validity, convergent validity and discriminant validity. The creation and validation of
these scales contribute to address one of the major obstacles in answering the high
demand on research using large sample data in studying interpartner learning in
international strategic alliances (Mohr and Sengupta, 2002).
Thirdly, the use of item parceling based on the partial disaggregation technique in
the SEM model has been shown to be a good approach. This is particularly helpful
when the model consists of a large number of indicators per construct. It is also
strongly recommended when the number of parameters to be estimated is large in
relation with the sample size (Bagozzi and Heatherton, 1994; Dabholka et al., 1996;
MacCallum and Austin, 2000).
7.3.3. Managerial implications
Among a number of knowledge types that a local partner in a developing country can
learn through IJVs, the findings in this research show that the acquisition of both
tacit and explicit marketing know-how from the foreign partner is valuable to
improve marketing competencies. Additionally, of the two forms, tacit marketing
know-how has been found to have a greater value to the learning outcomes.
Therefore, it is suggested that local firms should take the IJV opportunity to acquire
marketing know-how from its foreign partner. Especially resources and effort should
be focused on acquiring tacit know-how.
Moreover, the findings indicate that explicit marketing know-how is one of the
determinants of the tacit know-how acquisition. This implies that, if the local
marketing staff have limited learning capability due to the lack of prior experience or
formal marketing education, both explicit and tacit know-how should be the focus of
the learning process. This is because when the explicit know-how is accumulated, the
acquisition of tacit know-how would be more efficient along the time.
To be successful in the learning process, the local marketing staff should go beyond
the state of “natural learning”, i.e. learning that occurs randomly, to the state of
“skillful learning” (Garvin, 1993, Kim, 1993). That is, learning should be managed
systematically and professionally at both organization and individual levels (Inkpen,
1998). Unlike technological know-how, marketing know-how is a type of
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management know-how which is more difficult to learn from partner because of its
cultural and social embededness (Wong et al. 2002). In such a situation, the research
findings suggest that the local partner should pay more attention to several factors.
The relative importance of these factors depends on whether the focus is only on the
acquisition of tacit marketing know-how or on that of both tacit and explicit
marketing know-how.
For local partners that focus on the acquisition of tacit marketing know-how:
Attention should be paid to the learning intent, learning capability, teamwork,
partner’s knowledge protectiveness, relationship strength and cultural distance.
Firstly, the local partner should define a clear learning objective and provide
appropriate resources for the learners to acquire knowledge. It should develop an
incentive policy so that the organizational learning intent becomes individual
learning intent and interest. Secondly, as the effectiveness of learning depends very
much on the learning capability of the individual learners, local marketing staff who
are involved in marketing decision making in the IJV should be well educated in
marketing and/or have prior experience in the products/ services of the IJV. More
importantly, local staff should develop and nurture a strong relationship between
partners’ staff. Management should provide work-related opportunities such as
teamwork arrangement through collaboration, personal interaction, participative
decision making, open communication and information sharing; and non-workrelated opportunities such as socialization for building strong social ties with
expatriates. An open mind should also be paid to the cultural distance between
partners’ staff. Cross-cultural adjustment should be encouraged and practiced to
minimize problems caused by differences between partners’ staff in terms of
language, cultural value, norm and meanings.
Among the facilitators described above, the relative weight of each antecedent
indicates that the development of a strong relationship between partners is the most
important factor of successful learning of tacit marketing know-how from the foreign
partner. Other important factors are, in descending order: teamwork, learning intent,
learning capability, partner’s knowledge protectiveness and cultural distance. From a
controlling view, learning intent and learning capability are within the full control of
the local partner, teamwork depends on the IJV management, while relationship
strength and cultural distance depend on both partners. Lastly, partner’s knowledge
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protectiveness is within the full control of the foreign partner.
For local partners that want to learn both explicit and tacit marketing knowhow: In order to acquire both explicit and tacit marketing know-how, all the eight
investigated factors are important. The key factors determining the acquisition of
tacit marketing know-how have already been discussed above. For an effective
acquisition of explicit marketing know-how, further two factors should be taken into
account. They are IJV management commitment and partner marketing assistance.
The practice of knowledge management in the IJV is an important enabling factor for
explicit know-how acquisition. A commitment of IJV leaders is the most critical
determinant of the explicit know-how acquisition from the foreign partner. This issue
should be articulated in the agreement when establishing the IJV because in most of
the IJVs in developing countries, the real management power is in the foreign
partner’s control (Danis & Parkhe, 2002; Wong et al., 2002). The local partners have
little decision power on this matter once the IJV has been established. Furthermore,
the local partner should request as much knowledge assistance from the foreign
partner as possible. Because explicit knowledge acquisition can be through certain
media, these requested assistances can be in the form of formal/informal training of
local staff, providing written documents and guidelines for business operation,
sending more knowledgeable staff to work in the IJV, and so on. These assistances
are not only necessary for the success of the IJV business itself, but provide a good
condition for the local learners to acquire explicit know-how.
Given the relative importance of these facilitators, three factors are more critical
because they have significant effects on the acquisition of both explicit and tacit
marketing know-how. They are the learning intent and learning capability of the
local partner, and the level of teamwork in the IJV. Besides, relationship strength is
the most critical determinant of tacit know-how acquisition, and IJV management
commitment is the most critical determinant of explicit know-how acquisition.
7.4. LIMITATIONS AND FURTHER RESEARCH DIRECTIONS
Within the intrinsic epistemological premises, the current research has been
conducted with certain assumptions and delimitations.
Firstly, the specified knowledge under investigation is marketing know-how as a
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representative of the type of knowledge. This research can be replicated by replacing
marketing knowledge by other types of knowledge such as management knowledge
in general or technology knowledge. Such researches would help in generalizing the
findings, or increasing the external validity of the research model which has been
validated in this specific research.
Secondly, given the dyadic nature of interpartner learning, the current research has
only investigated the flow of knowledge from the foreign to the local partner. In a
broader sense, the model can be employed in the other way around where the foreign
partner learns from the local partner about local market knowledge. With some
adjustments, the starting base which includes knowledge holders, knowledge seekers,
IJV features, matching factors and the eight antecedents can also be relevant for such
researches.
The third limitation is related to the stage of learning from partner. The current
research focuses only on the first of the three phases of interpartner learning which
includes transfer, transformation and harvesting (Tiemessen et al, 1997). In this
research, all the learning and knowledge-related activities are examined within an
IJV. No theoretical and empirical investigations have been made in relation to the
two remaining phases. This calls for further studies to understand completely the full
process.
The forth limitation is about the research design with survey data. By the nature of
the learning process, the causal effect relationships involve certain time lag.
Although attempt has been made in the questionnaire (such as asking about the last
three year time) to minimize this effect, possible mismatch in time between the
causes (i.e. antecedent factors) and the effects (know-how acquisition or learning
outcomes) may exist.
In addition, the model for the acquisition of explicit and tacit knowledge in IJVs can
also be developed further by investigating the effects of control factors such as the
environmental condition, the industry and the age of the IJV. First, some authors
(Sinkula et al., 1997; Simonin, 1999b) show that a highly challenging environment in
terms of hostility and dynamism would cause potential influences on the interpartner
knowledge transfer (Luo and Peng, 1999). Second, the industry (e.g. manufacturing
vs. service) in which the IJV operates may also be considered, especially when
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technology knowledge is under investigation (Simonin, 1999a,b). In the current
research, no significant difference between the two groups i.e. manufacturing and
service companies was found in terms of the variables covered in the model. Third,
the age of the IJV may also be taken into account to reflect the dynamic process and
the nature of interpartner learning in IJVs (Dussauge et al. 2000). There has been
empirical evidence showing that the age of the IJV has certain influence on the
amount of knowledge transferred in IJVs (Simonin, 1999b). In this research, the
IJV’s age was originally a part of the model. Then it was realized that the model was
too complicated to test, given the sample size of 219 cases. A preliminary analysis
resulted that the correlations between age and all indicators of the acquired
tacit/explicit know-how are insignificant (i.e. less than 0.143). Therefore, age was
eliminated from the model. However, it still deserves attention in future studies.
In conclusion, the current research has achieved its objectives as stated in Chapter 1.
It provides a meaningful contribution to the literature of organizational learning and
strategic alliance. Its results also bear practical implications for local partners in IJVs
desiring to learn from their foreign partners.
199
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APPENDICES
APPENDIX 1: Questionnaire in English
APPENDIX 2: Questionnaire in Vietnamese
APPENDIX 3: Sample covariances matrix
APPENDIX 4: Sample correlations matrix
APPENDIX 5: Univariate normality of variables
APPENDIX 6: Standardized residual covariances
221
APPENDIX 1. QUESTIONNAIRE IN ENGLISH
QUESTIONNAIRE
Please answer the following questions by writing out the figures or ticking Rthe answer that applies to
you, and return this questionnaire to us using the enclosed stamped envelope or by fax (Fax no. 8660 899).
I.
GENERAL INFORMATION ABOUT YOUR JOINT-VENTURE (JV) COMPANY:
1. Industry of your JV business (you can tick more than one choice):
+ Manufacturing of industrial goods: ,
+ Manufacturing of consumer goods:
+ Trading:
,
+ Services:
+ Others (please specify):…….
,
,
2. Year of establishment: …………………………3. Duration of JV term: ………………….years
II. ORGANIZATIONAL FACTORS AND LEARNING IN THE JV:
Please indicate the extent to which you agree or disagree with each of the following statements. In this
section, please take into account your situation in the last three years or since the establishment of your JV
whichever is more recent…
PLEASE CIRCLE THE NUMBER CORRESPONDING TO YOUR ANSWER. CIRCLING A “1” MEANS THAT
YOU STRONGLY DISAGREE WITH THE STATEMENT, AND CIRCLING A “7” MEANS THAT YOU
STRONGLY AGREE. YOU MAY CIRCLE ANY OF THE NUMBERS IN BETWEEN THAT SHOWS HOW
STRONG YOUR FEELINGS ARE. THERE ARE NO RIGHT OR WRONG ANSWERS – ALL WE ARE
INTERESTED IN IS A NUMBER THAT BEST SHOWS YOUR PERCEPTIONS ABOUT THE MENTIONED
ISSUES.
Strongly
disagree
Strongly
agree
About the business environment…
Competitors, customers and/or legal issues as a whole:
1
… have an important impact on our company’s performance.
1
2
3
4
5
6
7
2
… have been a threat to the growth of our company.
1
2
3
4
5
6
7
3
… have undergone major changes over the last three years.
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1 Knowledge transfer among staff has been a stated policy in our JV 1
company.
2
3
4
5
6
7
2 Our top management has developed a variety of means to facilitate the 1
2
3
4
5
6
7
4
… have been unpredictable.
About the management of IJV…
222
Strongly
disagree
Strongly
agree
transfer of knowledge among staff in the company.
3 Our top management has provided adequate resources for knowledge 1
transfer among staff in the company.
2
3
4
5
6
7
4 The reward system in this company encourages knowledge transfer 1
among staff.
2
3
4
5
6
7
5 In this company, staff performance is evaluated mainly on working 1
process and not on outcomes.
2
3
4
5
6
7
6 Our top management places value on learning as key to employee 1
improvement.
2
3
4
5
6
7
7 There is good teamwork between foreign and local marketing staff in 1
this company.
2
3
4
5
6
7
8 Marketing tasks in this company are often undertaken collaboratively 1
between local and foreign staff.
2
3
4
5
6
7
9 Group meetings/discussions involving both foreign and local staff are a 1
common way of solving marketing problems in this company.
2
3
4
5
6
7
10 Teams involving both foreign and local staff have been dealing with a 1
large variety of marketing tasks in this company.
2
3
4
5
6
7
11 Face-to-face or personal interaction between local and foreign marketing 1
staff is rare in this company
About the local partner…
2
3
4
5
6
7
1 Acquiring marketing knowledge from our foreign partner is one of our 1
local partner’s objectives.
2
3
4
5
6
7
2 Our local partner encourages the local marketing staff to learn and 1
acquire our foreign partner’s marketing knowledge.
2
3
4
5
6
7
3 Our local partner has provided the necessary resources needed to support 1
the acquisition of marketing knowledge from our foreign partner.
2
3
4
5
6
7
4 Our local staff want to imitate expatriates in how they undertake 1
marketing tasks in the JV.
2
3
4
5
6
7
5 Our local staff feel that they need to learn about marketing from our 1
foreign staff.
2
3
4
5
6
7
6 Our marketing staff have a strong interest in learning from our foreign 1
partner.
2
3
4
5
6
7
7 In general, our local staff have good learning capabilities.
1
2
3
4
5
6
7
8 Our local staff have previous experience in marketing similar products 1
or services.
2
3
4
5
6
7
9 Our local marketing staff are well educated (i.e. they have completed 1
formal university education in marketing).
2
3
4
5
6
7
223
Strongly
disagree
Strongly
agree
10 The foreign staff in this company are more knowledgeable than our local 1
staff in terms of marketing.
About the foreign partner…
2
3
4
5
6
7
1 During the last three years, our foreign partner has been providing this 1
company with a lot of materials on procedures and guidelines for
marketing planning and decision making.
2
3
4
5
6
7
2 The guidelines, procedures and training programs provided by our 1
foreign partner have been very helpful to our local marketing staff.
2
3
4
5
6
7
3 In the last three years, our foreign partner has offered a lot of formal 1
training programs such as seminars and lectures in marketing to our
local staff.
2
3
4
5
6
7
4 There have been many marketing personnel from our foreign partner 1
working in this company during the last three years.
2
3
4
5
6
7
5 Our foreign marketing staff are well-experienced.
1
2
3
4
5
6
7
6 Our foreign partner has intentionally restricted the sharing of their 1
marketing know-how with our local staff.
2
3
4
5
6
7
7 Our foreign staff have been very protective of their marketing know- 1
how.
2
3
4
5
6
7
8 Our foreign staff are not willing to share their marketing know-how with 1
our local staff.
2
3
4
5
6
7
9 Our foreign staff do not want to show to our local staff the procedures 1
they use in solving marketing problems.
2
3
4
5
6
7
1
2
3
4
5
6
7
1 Our foreign and local marketing staff have a desire to maintain a good 1
social relationship between them.
2
3
4
5
6
7
2 There is a sense of trust between our local and foreign marketing staff.
2
3
4
5
6
7
2
3
4
5
6
7
4 The local and foreign marketing staff in this company are confident in 1
each other’s marketing capabilities.
2
3
4
5
6
7
5 Locals and expatriates in marketing freely share their ideas, feelings and 1
hopes with each other.
2
3
4
5
6
7
6 The local and foreign marketing staff in this company are supportive of 1
each other. They respond constructively and caringly to their partner’s
concerns about the JV.
2
3
4
5
6
7
10 The foreign marketing staff in this company are very competent.
About the relationship and cultural factors
1
3 The local and foreign marketing staff in this company can freely talk to
each other about difficulties (in general) they encounter with the JV and
1
they know that their concerns will be addressed.
224
Strongly
disagree
̌
̌
Strongly
agree
7 The local and foreign marketing staff in this company share a sense of 1
togetherness.
2
3
4
5
6
7
8 The local and foreign marketing staff in this company share 1
organizational myths or stories with each other.
2
3
4
5
6
7
9 The national cultures of our foreign partner differs significantly from our 1
own culture.
2
3
4
5
6
7
10 Language differences are a major obstacle in communicating with and 1
understanding our foreign marketing staff.
2
3
4
5
6
7
11 Cultural differences have been a source of problems in this JV.
1
2
3
4
5
6
7
12 Misunderstandings due to cultural differences have been a source of 1
problems in this JV.
2
3
4
5
6
7
Please indicate the extent to which the local marketing staff
in your JV have improved their capabilities during the last 3 years
in each of the following marketing activities:
To a
great extent
Not at all
1 obtaining and analyzing marketing information
1
2
3
4
5
6
7
2 identifying market opportunities and threats
1
2
3
4
5
6
7
3 developing marketing programs
1
2
3
4
5
6
7
4 implementing and evaluating marketing programs
1
2
3
4
5
6
7
5 solving marketing problems in general
1
2
3
4
5
6
7
6 making marketing decisions in general
1
2
3
4
5
6
7
Please indicate how often the local marketing staff have initiated
changes to each of the following during the last three years:
Very often
Never
1 company’s mix of products or brands (e.g. add a new product or delete 1
an existing product).
2
3
4
5
6
7
2 overall marketing strategy.
1
2
3
4
5
6
7
3 sales management.
1
2
3
4
5
6
7
4 pricing.
1
2
3
4
5
6
7
5 sales promotion.
1
2
3
4
5
6
7
6
advertising programs.
1
2
3
4
5
6
7
7
company’s marketing activities as a whole.
1
2
3
4
5
6
7
225
In the following questions, the term “Marketing know-how” refers to knowing how to do marketing
tasks or procedures to solve marketing problems in the JV, such as how to analyse market situation,
how to deal with customers’ complaints, how to set a product’s price, how to design a promotion
plan, etc….
̌
During the last three years (or since the establishment of
the JV if it is less than 3 years), our local marketing staff have
acquired a lot of marketing know-how by:
̌
Strongly
agree
1 … reading and understanding training materials supplied by our 1
foreign partner.
2
3
4
5
6
7
2 … attending formal lectures conducted by our foreign partner 1
regarding different aspects of marketing.
2
3
4
5
6
7
3 … using manuals prepared by the foreign partner on how to undertake 1
different marketing activities such as market analysis, pricing,
advertising or making a sales presentation.
2
3
4
5
6
7
4 … applying rules and standard operating procedure specified in writing 1
by our foreign partner through memoranda and other documents.
2
3
4
5
6
7
During the last three years (or since the establishment of the JV
if it is less than 3 years), our local marketing staff have acquired
a lot of marketing know-how by:
1 … interacting closely with our foreign marketing staff.
̌
Strongly
disagree
Strongly
disagree
Strongly
agree
1
2
3
4
5
6
7
2 … collaborating closely with our foreign marketing staff in solving 1
marketing problems or in conducting joint projects (e.g. developing
new products or a promotion campaign).
2
3
4
5
6
7
3 … observing how our foreign marketing staff solve problems or make 1
decisions.
2
3
4
5
6
7
4 … adopting the rules of thumb or the intuitive approaches used by our 1
foreign staff in solving marketing problems.
2
3
4
5
6
7
During the last three years
(or since the establishment of the JV if it is less than 3 years);
A lot
Very little
1 How much marketing know-how, as a whole, have your local staff 1
learned from your foreign marketing staff ?
2
3
4
5
6
7
2 How much marketing know-how, that is explicit or articulate, have 1
your local staff learned from your foreign staff?
2
3
4
5
6
7
3 How much marketing know-how, that is tacit or non-articulate, have 1
your local staff learned from your foreign partner ?
2
3
4
5
6
7
226
III. INFORMATION ABOUT THE JOINT VENTURE AND PARTNERS:
̌
About the Joint venture company:
1. Partners and capital contributions:
Partner 1:
country of origin: ……………………………
capital contribution: ………….%
Partner 2:
country of origin: ……………………………
capital contribution: ………….%
Partner 3:
country of origin: ……………………………
capital contribution: ………….%
Partner4:
country of origin: ……………………………
capital contribution: ………….%
2. Products/ Services of the JV company: …………………………………………………………..…
3. The overall activities of the JV company are managed by:
jointly ,
other ,
4. JV marketing activities in Vietnam are carried out by:
jointly ,
other ,
local partner only ,
foreign partner only ,
local partner only ,
foreign partner only ,
5. Please give the average number of staff working in the marketing function during the last three years (or
since the establishment of the JV if it is less than 3 years old):
Local staff: ………………. Foreign staff:…………………..
The highest number of marketing staff in the last 3 years: Local staff: ………Foreign staff: ……….
Average length of stay of foreign marketing staff with the JV in Vietnam in months: ……..…
6. What is the number of full time employees of your company?: …….….
7. Approximately, what percent of your total sales in the last three years was derived from exports? _____%
8. What is the annual sales of your company? (Mil.USD):
<1,
1-5 ,
5-20 ,
20-100 ,
>100 ,
9. How would you rate the overall performance of your company during the last three years (or since
establishment if the company is less than 3 years old):
very poor ,
poor ,
so so ,
good ,
very good ,
10. How would you rate the overall growth of your company relative to that of your industry as a whole
(over the last three years of from the time it was established if the company is less than 3 years old)?
Very much lower [1]
̌
[2]
[3]
[4]
[5]
[6]
[7] Very much higher
About the Local partner:
1. Industry of the local partner’s business (you can tick more than one choice):
+ Manufacturing of industrial goods: ,
+ Manufacturing of consumer goods:
+ Trading:
,
+ Services:
+ Others (please specify):…….…
227
,
,
2. Ownership:
state owned
,
private
,
others (please specify): …………….…….
3. Number of international joint ventures the company currently has in Vietnam………………
4. The company has businesses (in Vietnam) other than this JV:
̌
Yes ,
No ,
About the Foreign partner: (In case that the JV has more than one foreign partners, please describe
the one that involves directly in marketing activities)
1. Country of origin: …………………………
2. Industry of the foreign partner’s business (you can tick more than one choice):
+ Manufacturing of industrial goods: ,
+ Manufacturing of consumer goods:
+ Trading:
,
+ Services:
+ Others (please specify):……………………………………………………………….
3. Number of JVs the foreign partner currently has in Vietnam: ……
4. Other JVs the foreign partner currently has in the world:
Yes ,
,
,
No ,
IV. INFORMATION ABOUT YOURSELF:
1. For the purpose of classification, please give us brief information about yourself:
Your position/job title: .……….……………………………………………………….
Number of years you have been working for this JV: ………… years
Number of years you have been working for local partner before joining this JV: ………… years
Number of years you have been working for other international JV/foreign company before joining this
JV:…….…years
2. In general, approximately how much of the improvement in the marketing competence or capability of
your local staff during the last three years would you attribute to each of the following?
+
Own personal experience of staff
…….%
+
Acquired from foreign partner:
…….%
+
training outside the company:
…….%
+
Training within the company :
…….%
+
Others (please specify): _______________
……%
4. In general, what comments can you make about the transfer of marketing knowledge/skills from foreign to
local staff in this JV company?
………………………………………………………………………………………………………………
………………………………………………………………………………………………………………
………………………………………………………………………………………………………………
Thank you very much for your assistance!
228
APPENDIX 2. QUESTIONNAIRE IN VIETNAMESE
BAÛNG CAÂU HOÛI
Xin traû lôøi caùc caâu hoûi sau ñaây baèng caùch ñaùnh daáu R hoaëc ñieàn vaøo choã troáng thích hôïp. Sau ñoù, xin vui
loøng göûi veà cho chuùng toâi theo soá Fax 8660 899 hoaëc söû duïng bì thö coù saün tem vaø ñòa chæ keøm theo.
I. CAÙC THOÂNG TIN CHUNG VEÀ COÂNG TY LIEÂN DOANH (töø ñaây xin vieát taét laø Cty):
1. Ngaønh ngheà hoaït ñoäng cuûa Cty: (coù theå ñaùnh daáu vaøo nhieàu oâ choïn)
+ Saûn xuaát haøng coâng nghieäp: ,
+ Saûn xuaát haøng tieâu duøng:
+ Thöông maïi:
,
+ Dòch vuï:
+ Ngaønh khaùc (xin ghi roõ):…….
,
,
2. Naêm thaønh laäp: …………………………3. Soá naêm lieân doanh theo hôïp ñoàng: ………………….naêm.
II. CAÙC YEÁU TOÁ LIEÂN QUAN ÑEÁN VIEÄC HOÏC TAÄP TRONG COÂNG TY LIEÂN DOANH:
Xin lieân heä hoaït ñoäng cuûa Cty trong ba naêm vöøa qua (hoaëc töø luùc thaønh laäp neáu thôøi gian hoaït ñoäng döôùi
ba naêm) vaø cho bieát möùc ñoä taùn thaønh/ khoâng taùn thaønh cuûa OÂng/ Baø ñoái vôùi caùc phaùt bieåu sau.
Xin löu yù: thuaät ngöõ “nhaân vieân” ñeå chæ taát caû nhöõng ngöôøi ñang laøm vieäc trong Cty, khoâng phaân bieät
chöùc vuï vaø coâng taùc.
HAÕY KHOANH TROØN VAØO CON SOÁ TÖÔNG ÖÙNG VÔÙI CHOÏN LÖÏA CUÛA OÂNG/ BAØ. CHOÏN SOÁ 1
NGHÓA LAØ OÂNG/ BAØ HOAØN TOAØN KHOÂNG ÑOÀNG YÙ VÔÙI CAÂU PHAÙT BIEÅU; CHOÏN SOÁ 7 NGHÓA
LAØ OÂNG/ BAØ HOAØN TOAØN ÑOÀNG YÙ VÔÙI CAÂU PHAÙT BIEÅU. OÂNG/ BAØ COÙ THEÅ CHOÏN BAÁT KYØ SOÁ
NAØO ÔÛ KHOAÛNG GIÖÕA ÑEÅ CHÆ MÖÙC ÑOÄ ÑOÀNG YÙ CUÛA MÌNH. KHOÂNG COÙ CHOÏN LÖÏA NAØO LAØ
ÑUÙNG HAY SAI. CHUÙNG TOÂI CHÆ MUOÁN BIEÁT NHAÄN XEÙT CUÛA OÂNG/ BAØ VEÀ CAÙC PHAÙT BIEÅU.
Hoaøn toaøn
khoâng
Hoaøn toaøn
ñoàng yù
ñoàng yù
Veà moâi tröôøng kinh doanh
Ñoái thuû caïnh tranh, khaùch haøng hoaëc luaät leä – qui ñònh cuûa nhaø nöôùc noùi chung:
1
… coù aûnh höôûng lôùn ñeán keát quaû hoaït ñoäng cuûa Cty.
1
2
3
4
5
6
7
2
… laø moái ñe doïa cho söï phaùt trieån cuûa Cty.
1
2
3
4
5
6
7
3
… coù nhöõng thay ñoåi ñaùng keå trong hai naêm vöøa qua.
1
2
3
4
5
6
7
4
… khoâng theå löôøng tröôùc ñöôïc.
1
2
3
4
5
6
7
229
Hoaøn toaøn
khoâng
Hoaøn toaøn
ñoàng yù
ñoàng yù
Veà lieân doanh
1 Cty coù chính saùch chuyeån giao kyõ naêng/kieán thöùc giöõa nhaân vieân caùc 1
phía ñoái taùc.
2
3
4
5
6
7
2 Laõnh ñaïo Cty ñaõ coù nhieàu bieän phaùp khuyeán khích vieäc chuyeån giao 1
kyõ naêng/kieán thöùc giöõa nhaân vieân cuûa caùc phía ñoái taùc.
2
3
4
5
6
7
3 Laõnh ñaïo Cty ñaõ hoã trôï nguoàn löïc thoûa ñaùng cho vieäc chuyeån giao ñoù.
1
2
3
4
5
6
7
4 Chính saùch ñaõi ngoä - khen thöôûng cuûa Cty khuyeán khích vieäc chuyeån 1
giao kyõ naêng/kieán thöùc giöõa nhaân vieân cuûa caùc phía ñoái taùc.
2
3
4
5
6
7
5 Trong Cty, nhaân vieân ñöôïc ñaùnh giaù chuû yeáu döïa treân quaù trình laøm 1
vieäc chöù khoâng döïa vaøo keát quaû cuoái cuøng.
2
3
4
5
6
7
6 Laõnh ñaïo Cty xem troïng vieäc nhaân vieân hoïc taäp trau doài ñeå phaùt trieån.
1
2
3
4
5
6
7
7 Trong caùc hoaït ñoäng kinh doanh/tieáp thò, hình thöùc laøm vieäc theo 1
toå/nhoùm giöõa caùc nhaân vieân VN vaø nöôùc ngoaøi laø raát toát.
2
3
4
5
6
7
8 Coâng taùc kinh doanh/tieáp thò trong Cty ñöôïc caùc nhaân vieân VN vaø phía 1
ñoái taùc cuøng coäng taùc thöïc hieän.
2
3
4
5
6
7
9 Hoïp hoaëc thaûo luaän giöõa caùc nhaân vieân VN vaø nöôùc ngoaøi laø caùch thöùc 1
thöôøng duøng ñeå giaûi quyeát caùc vaán ñeà kinh doanh/tieáp thò trong Cty.
2
3
4
5
6
7
10 Caùc nhoùm phuï traùch kinh doanh/tieáp thò bao goàm nhaân vieân VN vaø 1
nöôùc ngoaøi ñaõ giaûi quyeát nhieàu vaán ñeà ña daïng khaùc nhau.
2
3
4
5
6
7
11 Vieäc trao ñoåi coâng taùc tröïc tieáp giöõa caùc nhaân vieân kinh doanh/tieáp thò 1
VN vaø phía ñoái taùc raát ít khi xaûy ra.
Veà ñoái taùc trong nöôùc
2
3
4
5
6
7
1 Hoïc hoûi kyõ naêng veà kinh doanh/tieáp thò töø ñoái taùc nöôùc ngoaøi laø moät 1
trong nhöõng muïc tieâu cuûa phía VN khi hình thaønh lieân doanh.
2
3
4
5
6
7
2 Coâng ty ñoái taùc phía VN khuyeán khích caùc nhaân vieân kinh doanh/tieáp 1
thò VN laøm vieäc trong Cty hoïc taäp kyõ naêng cuûa ñoái taùc nöôùc ngoaøi.
2
3
4
5
6
7
3 Coâng ty ñoái taùc phía VN ñaõ cung caáp nguoàn löïc ñeå hoã trôï nhaân vieân 1
VN laøm vieäc trong lieân doanh hoïc hoûi kyõ naêng cuûa ñoái taùc nöôùc ngoaøi.
2
3
4
5
6
7
4 Caùc nhaân vieân VN muoán baét chöôùc ñoái taùc nöôùc ngoaøi veà caùch thöùc 1
giaûi quyeát caùc coâng vieäc kinh doanh/tieáp thò trong Cty.
2
3
4
5
6
7
5 Caùc nhaân vieân VN thöïc söï coù nhu caàu hoïc taäp veà kyõ naêng kinh 1
doanh/tieáp thò töø phía ñoái taùc nöôùc ngoaøi.
2
3
4
5
6
7
6 Caùc nhaân vieân VN raát quan taâm ñeán vieäc hoïc hoûi töø caùc nhaân vieân 1
nöôùc ngoaøi.
2
3
4
5
6
7
7 Noùi chung, caùc nhaân vieân VN coù khaû naêng naém baét vaø tieáp thu toát.
1
2
3
4
5
6
7
8 Caùc nhaân vieân VN laøm vieäc trong Cty ñaõ coù kinh nghieäm töø tröôùc veà 1
kinh doanh/tieáp thò saûn phaåm/dòch vuï cuûa Cty.
2
3
4
5
6
7
9 Caùc nhaân vieân VN laøm vieäc trong Cty ñaõ ñöôïc ñaøo taïo toát veà lónh vöïc 1
kinh doanh/tieáp thò (ñaõ toát nghieäp ÑH ngaønh Tieáp thò).
2
3
4
5
6
7
230
Hoaøn toaøn
khoâng
Hoaøn toaøn
ñoàng yù
ñoàng yù
10 Caùc nhaân vieân kinh doanh/tieáp thò nöôùc ngoaøi gioûi hôn caùc nhaân vieân 1
VN veà kyõ naêng kinh doanh/tieáp thò.
Veà ñoái taùc nöôùc ngoaøi
2
3
4
5
6
7
1 Trong 3 naêm qua, ñoái taùc nöôùc ngoaøi ñaõ cung caáp cho Cty nhieàu taøi 1
lieäu höôùng daãn veà qui trình laäp keá hoaïch vaø ra quyeát ñònh veà kinh
doanh/tieáp thò.
2
3
4
5
6
7
2 Caùc taøi lieäu höôùng daãn ñoù raát höõu ích cho caùc nhaân vieân kinh 1
doanh/tieáp thò VN.
2
3
4
5
6
7
3 Trong 3 naêm qua, ñoái taùc ñaõ toå chöùc nhieàu chöông trình huaán luyeän veà 1
kinh doanh/tieáp thò cho nhaân vieân VN.
2
3
4
5
6
7
4 Ñaõ coù nhieàu nhaân vieân veà kinh doanh/tieáp thò cuûa ñoái taùc ñeán laøm vieäc 1
trong Cty trong hai naêm vöøa qua.
2
3
4
5
6
7
5 Trong Cty, caùc nhaân vieân kinh doanh/tieáp thò cuûa ñoái taùc nöôùc ngoaøi laø 1
nhöõng ngöôøi coù kinh nghieäm vaø kyõ naêng toát.
2
3
4
5
6
7
6 Phía ñoái taùc chuû tröông haïn cheá vieäc chia seû kyõ naêng kinh doanh/tieáp 1
thò cuûa hoï.
2
3
4
5
6
7
7 Caùc nhaân vieân nöôùc ngoaøi giöõ rieâng kyõ naêng veà kinh doanh/tieáp thò 1
cuûa hoï.
2
3
4
5
6
7
8 Caùc nhaân vieân nöôùc ngoaøi khoâng muoán chia seû kyõ naêng kinh 1
doanh/tieáp thò cuûa hoï vôùi caùc nhaân vieân VN.
2
3
4
5
6
7
9 Caùc nhaân vieân nöôùc ngoaøi khoâng muoán cho nhaân vieân VN bieát caùch 1
thöùc hoï giaûi quyeát caùc vaán ñeà veà kinh doanh/tieáp thò.
2
3
4
5
6
7
10 Caùc nhaân vieân kinh doanh/tieáp thò nöôùc ngoaøi laøm vieäc trong Cty raát 1
thaïo vieäc.
Veà caùc moái quan heä vaø yeáu toá vaên hoùa
2
3
4
5
6
7
1 Caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi trong Cty mong 1
muoán duy trì moái quan heä xaõ hoäi toát vôùi nhau.
2
3
4
5
6
7
2 Coù söï tin caäy laãn nhau giöõa caùc nhaân vieân kinh doanh/tieáp thò VN vaø 1
nöôùc ngoaøi.
2
3
4
5
6
7
2
3
4
5
6
7
4 Caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi trong Cty tin 1
töôûng vaøo naêng löïc cuûa nhau.
2
3
4
5
6
7
5 Caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi trong Cty töï do 1
chia seû caùc yù töôûng, caûm nghó vaø kyø voïng cuûa hoï veà Cty.
2
3
4
5
6
7
6 Trong Cty, caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi quan 1
taâm hoã trôï vaø giuùp ñôõ laãn nhau moat caùch chu ñaùo.
2
3
4
5
6
7
7 Caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi trong Cty coù 1
chung tinh thaàn gaén boù nhau.
2
3
4
5
6
7
3 Caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi trong Cty töï do
trao ñoåi vôùi nhau veà nhöõng khoù khaên gaëp phaûi trong Cty vaø hoï bieát
1
ñieàu ñoù seõ ñöôïc chia seû.
231
Hoaøn toaøn
khoâng
Hoaøn toaøn
ñoàng yù
ñoàng yù
̌
̌
8 Caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi trong Cty thöôøng 1
hay keå chuyeän coâng vieäc cho nhau nghe.
2
3
4
5
6
7
9 Vaên hoùa quoác gia cuûa ñoái taùc nöôùc ngoaøi vaø VN laø khaùc nhau nhieàu.
1
2
3
4
5
6
7
10 Khaùc bieät veà ngoân ngöõ laø trôû ngaïi chính trong giao tieáp vaø thaáu hieåu 1
giöõa caùc nhaân vieân kinh doanh/tieáp thò VN vaø nöôùc ngoaøi.
2
3
4
5
6
7
11 Söï khaùc bieät veà caùc giaù trò vaên hoùa laø nguoàn goác cuûa caùc maâu thuaãn 1
trong Cty.
2
3
4
5
6
7
12 Giöõa caùc ñoái taùc trong Cty ñaõ coù söï hieåu laàm nhau do khaùc bieät veà giaù 1
trò vaên hoùa.
2
3
4
5
6
7
Xin OÂng/Baø cho bieát möùc ñoä caûi tieán naêng löïc cuûa caùc nhaân vieân
kinh doanh/tieáp thò VN laøm vieäc trong Cty trong ba naêm vöøa qua
(hoaëc töø luùc thaønh laäp neáu Cty hoaït ñoäng döôùi ba naêm) veà:
Khoâng coù gì
Raát nhieàu
1 thu thaäp vaø phaân tích caùc thoâng tin veà kinh doanh/tieáp thò.
1
2
3
4
5
6
7
2 nhaän daïng caùc nguy cô vaø cô hoäi thò tröôøng.
1
2
3
4
5
6
7
3 xaây döïng caùc keá hoaïch kinh doanh/tieáp thò.
1
2
3
4
5
6
7
4 trieån khai vaø ñaùnh giaù caùc chöông trình kinh doanh/tieáp thò.
1
2
3
4
5
6
7
5 giaûi quyeát caùc vaán ñeà kinh doanh/tieáp thò noùi chung.
1
2
3
4
5
6
7
6 ñöa ra caùc quyeát ñònh veà kinh doanh/tieáp thò noùi chung.
1
2
3
4
5
6
7
Xin OÂng/Baø cho bieát möùc ñoä thöôøng xuyeân maø caùc nhaân vieân
kinh doanh/tieáp thò VN ñeà xöôùng caùc thay ñoåi trong ba naêm vöøa qua
(hoaëc töø luùc thaønh laäp neáu Cty hoaït ñoäng döôùi ba naêm) veà:
Raát thöôøng xuyeân
Khoâng coù
1 saûn phaåm/ nhaõn haøng cuûa Cty (ñöa theâm hoaëc boû bôùt saûn phaåm cuõ)
1
2
3
4
5
6
7
2 chieán löôïc kinh doanh/tieáp thò noùi chung.
1
2
3
4
5
6
7
3 chieán löôïc baùn haøng.
1
2
3
4
5
6
7
4 chính saùch giaù baùn.
1
2
3
4
5
6
7
5 caùc chöông trình khuyeán maõi.
1
2
3
4
5
6
7
6
caùc chöông trình quaûng caùo.
1
2
3
4
5
6
7
7
caùc hoaït ñoäng kinh doanh/tieáp thò noùi chung
1
2
3
4
5
6
7
232
Trong caùc caâu hoûi sau, thuaät ngöõ “Kyõ naêng kinh doanh/tieáp thò” lieân quan ñeán caùch thöùc thöïc
hieän caùc coâng vieäc kinh doanh/tieáp thò trong Cty; chaúng haïn nhö caùch thöùc phaân tích tình hình thò
tröôøng, caùch thöùc xöû lyù phaøn naøn cuûa khaùch haøng, caùch thöùc ñònh giaù saûn phaåm, caùch thöùc thieát keá
moät chöông trình khuyeán maõi, ….
̌
̌
Trong ba naêm vöøa qua (hoaëc töø luùc thaønh laäp neáu Cty döôùi ba naêm),
caùc nhaân vieân kinh doanh/tieáp thò VN ñaõ hoïc ñöôïc nhieàu kyõ naêng/
kieán thöùc thoâng qua vieäc:
Hoaøn toaøn
khoâng ñoàng yù
ñoàng yù
1 Ñoïc vaø hieåu (naém baét) ñöôïc caùc taøi lieäu huaán luyeän do phía ñoái taùc 1
cung caáp.
2
3
4
5
6
7
2 Tham döï caùc khoùa hoïc/huaán luyeän veà tieáp thò/kinh doanh do phía ñoái 1
taùc thöïc hieän.
2
3
4
5
6
7
3 Söû duïng caùc soå tay höôùng daãn (manuals) do phía ñoái taùc soaïn thaûo 1
veà caùch thöùc tieán haønh caùc hoaït ñoäng kinh doanh/tieáp thò. (Phaân tích
thò tröôøng, ñònh giaù, quaûng caùo, baùn haøng)
2
3
4
5
6
7
4 Aùp duïng caùc nguyeân taéc (rules) vaø quy trình hoaït ñoäng (procedures) 1
do phía ñoái taùc soaïn thaûo vaø ñöôïc theå hieän döôùc daïng vaên baûn, ghi
nhôù vaø caùc taøi lieäu khaùc.
2
3
4
5
6
7
Trong ba naêm vöøa qua (hoaëc töø luùc thaønh laäp neáu Cty döôùi ba naêm),
caùc nhaân vieân kinh doanh/tieáp thò VN ñaõ hoïc ñöôïc nhieàu kyõ naêng/
kieán thöùc thoâng qua vieäc:
1 Giao tieáp/töông taùc (interacting) chaët cheõ vôùi nhaân vieân phía ñoái taùc.
̌
Hoaøn toaøn
Hoaøn toaøn
khoâng ñoàng yù
Hoaøn toaøn
ñoàng yù
1
2
3
4
5
6
7
2 Coäng taùc chung (collaborating) vôùi nhaân vieân phía ñoái taùc ñeå giaûi 1
quyeát caùc vaán ñeà kinh doanh/tieáp thò hoaëc cuøng trieån khai caùc döï
aùn/chöông trình nhö phaùt trieån saûn phaåm môùi, nhaõn hieäu môùi, môû chi
nhaùnh hay ñaïi lyù môùi, v.v.
2
3
4
5
6
7
3 Quan saùt caùch thöùc nhaân vieân ñoái taùc giaûi quyeát caùc vaán ñeà kinh 1
doanh/tieáp thò hoaëc ñöa ra caùc quyeát ñònh kinh doanh/tieáp thò.
2
3
4
5
6
7
4 Chaáp nhaän caùc phöông phaùp kinh nghieäm hoaëc caùc phöông phaùp tröïc 1
giaùc ñöôïc nhaân vieân phía ñoái taùc söû duïng khi giaûi quyeát caùc vaán ñeà
kinh doanh/tieáp thò.
2
3
4
5
6
7
Noùi chung, trong 3 naêm qua (hoaëc töø luùc thaønh laäp neáu Cty döôùi ba naêm):
Raát ít
Raát nhieàu
1 Caùc nhaân vieân Cty ñaõ hoïc ñöôïc nhieàu kyõ naêng kinh doanh/tieáp thò noùi 1
chung
2
3
4
5
6
7
2 Caùc nhaân vieân Cty ñaõ hoïc ñöôïc nhieàu kyõ naêng kinh doanh/tieáp thò maø 1
coù theå dieãn taû daïng vieát hoaëc noùi
2
3
4
5
6
7
3 Caùc nhaân vieân Cty ñaõ hoïc ñöôïc nhieàu kyõ naêng kinh doanh /tieáp thò 1
daïng aån taøng, chæ coù theå bieåu hieän qua giaûi quyeát coâng vieäc kinh
doanh/tieáp thò.
2
3
4
5
6
7
233
III. CAÙC THOÂNG TIN CHUNG VEÀ COÂNG TY LIEÂN DOANH VAØ CAÙC ÑOÁI TAÙC:
̌
Veà coâng ty lieân doanh:
1. Ñoát taùc vaø voán goùp:
Ñoái taùc 1:
thuoäc quoác gia: : ……………………………
voán goùp : ………….%
Ñoái taùc 2:
thuoäc quoác gia: : ……………………………
voán goùp : ………….%
Ñoái taùc 3:
thuoäc quoác gia: : ……………………………
voán goùp : ………….%
Ñoái taùc 4:
thuoäc quoác gia: : ……………………………
voán goùp : ………….%
2. Saûn phaåm / dòch vuï cuûa Cty:
…………………………………………………………..…
3. Hoaït ñoäng chung cuûa Cty ñöôïc thöïc hieän bôûi:
Chæ coù ñoái taùc VN ,
Chæ coù ñoái taùc nöôùc ngoaøi ,
4. Hoaït ñoäng kinh doanh/ tieáp thò cuûa Cty ñöôïc thöïc hieän bôûi:
Chæ coù ñoái taùc VN ,
Chæ coù ñoái taùc nöôùc ngoaøi ,
Caû 2 phía ,
Daïng khaùc ,
Caû 2 phía ,
Daïng khaùc ,
5. Xin cho bieát soá löôïng nhaân vieân bình quaân laøm vieäc trong boä phaän tieáp thò trong 3 naêm qua (hoaëc töø khi
thaønh laäp neáu Cty hoaït ñoäng döôùi ba naêm.
Vieät nam: ………………. Nöôùc ngoaøi:…………………..
Soá nhaân vieân tieáp thò cao nhaát trong 3 naêm qua: VN: ………
Nöôùc ngoaøi: ……….
Thôøi gian laøm vieäc trung bình cuûa moät nhaân vieân kinh doanh/tieáp thò nöôùc ngoaøi taïi Cty:____thaùng
6. Soá löôïng nhaân vieân Cty: …….….
7. Tæ leä doanh thu xuaát khaåu chieám trong toång doanh thu trong 3 naêm vöøa qua (öôùc tính): _____%
8. Doanh thu haøng naêm cuûa Cty: (Trieäu USD):
<1,
1-5 ,
5-20 ,
20-100 ,
>100 ,
9. OÂng/Baø ñaùnh giaù theá naøo veà hoaït ñoäng cuûa Cty trong 3 naêm qua (hoaëc töø khi thaønh laäp neáu Cty hoaït
ñoäng döôùi 3 naêm):
raát keùm ,
keùm ,
bình thöôøng ,
toát ,
raát toát ,
10. OÂng/Baø ñaùnh gía theá naøo veà söï phaùt trieån chung cuûa Cty so vôùi toaøn ngaønh (trong 3 naêm qua hoaëc töø
khi thaønh laäp neáu thôøi gian hoaït ñoäng döôùi 3 naêm):
Raát thaáp
̌
[1]
[2]
[3]
[4]
[5]
[6]
[7]
Raát cao
Veà ñoái taùc VN:
1. Ngaønh ngheà hoaït ñoäng (coù theå ñaùnh daáu vaøo nhieàu choïn löïa):
,
+ Saûn xuaát haøng tieâu duøng
+ Saûn xuaát haøng coâng nghieäp
+ Thöông maïi
,
+ Dòch vuï
+ Ngaønh khaùc (xin ghi roõ):…….…
234
,
,
2. Hình thöùc sôû höõu:
Nhaø nöôùc
,
,
Tö nhaân
Daïng khaùc (xin ghi roõ): …………….…….
3. Soá lieân doanh vôùi nöôùc ngoaøi Cty hieän coù ôû VN………………
4. Ngoaøi lieân doanh naøy, ñoái taùc VN coøn coù nhöõng hoaït ñoäng saûn xuaát/kinh doanh khaùc:
Coù ,
̌
Khoâng
,
Veà ñoái taùc nöôùc ngoaøi: (trong tröôøng hôïp lieân doanh coù nhieàu ñoái taùc, xin cho bieát veà ñoái taùc tham gia
tröïc tieáp vaøo hoaït ñoäng kinh doanh /tieáp thò cuûa lieân doanh)
2. Thuoäc quoác gia: …………………………
2. Ngaønh ngheà hoaït ñoäng (coù theå ñaùnh daáu vaøo nhieàu choïn löïa):
+ Saûn xuaát haøng coâng nghieäp
,
+ Saûn xuaát haøng tieâu duøng
+ Thöông maïi
,
+ Dòch vuï
+ Ngaønh khaùc (xin ghi roõ):…….…
3. Soá lieân doanh hieän coù ôû Vieät Nam: ……
4. Lieân doanh ôû caùc nöôùc khaùc:
Coù ,
,
,
Khoâng ,
IV. CAÙC THOÂNG TIN KHAÙC
1.Xin OÂng/ Baø cho bieát moät soá thoâng tin rieâng veà OÂng/ Baø:
Chöùc vuï coâng taùc: .……….……………………………………………………….
Soá naêm laøm vieäc cho lieân doanh: ………… naêm
Soá naêm laøm vieäc cho coâng ty cuûa ñoái taùc VN tröôùc khi tham gia lieân doanh (neáu coù): ………… naêm
Soá naêm laøm vieäc cho Cty nöôùc ngoaøi hoaëc lieân doanh khaùc tröôùc nay (neáu coù) . …naêm
2. Nhìn chung, söï caûi tieán naêng löïc kinh doanh/tieáp thò cuûa caùc nhaân vieân VN trong 3 naêm qua laø do:
+
Ruùt kinh nghieäm qua coâng vieäc
…….%
+
Hoïc töø ñoái taùc nöôùc ngoaøi
…….%
+
Hoïc töø caùc lôùp ngoaøi Cty
…….%
+
Hoïc töø caùc lôùp trong Cty
…….%
+
Baèng caùch khaùc
……%
(xin ghi roõ): _______________
4. Cuoái cuøng, OÂng/ Baø coù nhaän xeùt gì veà vieäc chuyeån giao kieán thöùc/ kyõ naêng veà kinh doanh/ tieáp thò töø
caùc nhaân vieân nöôùc ngoaøi cho caùc nhaân vieân VN trong Cty cuûa oâng/ Baø?
…………………………………………………………………………………………………………………………………………………………………………………………………………
…………………………………………………………………………………………………………………………………………………………………………………………………………
………………………………………………
Xin caûm ôn söï hôïp taùc cuûa OÂng/ Baø!
235
APPENDIX 3. SAMPLE COVARIANCES MATRIX
Rel2
Cul1
Tea2
Com2
Tea1
Int1
Capa23
Capa24
Com1
Prot1
Prot2
Int2
Dyn2
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
Rel2
1.240
-.086
.291
.192
.273
.092
.124
.105
.104
-.078
-.059
.046
.272
.114
.498
.143
.525
.209
.234
1.054
.084
.175
.317
.327
.150
-.110
Cul1
Tea2
Com2
Tea1
Int1
Capa23
Capa24
Com1
Prot1
Prot2
Int2
1.107
-.120
.022
-.120
-.068
-.030
-.005
.038
.068
.042
-.064
-.111
-.046
-.302
-.080
-.219
.005
-.069
-.094
.005
.004
-.128
-.062
.005
1.017
1.106
.164
.888
.122
.090
.049
.119
.014
.007
.054
.330
.375
.433
.390
.412
.100
.288
.266
.058
.049
.363
.248
.064
-.073
1.395
.095
.182
.122
.174
1.241
-.029
-.043
.188
.289
.520
.316
.446
.318
.210
.309
.193
.207
.254
.277
.258
.188
.070
.999
.120
.145
.132
.089
-.013
-.025
.048
.314
.393
.431
.364
.423
.099
.287
.287
.061
.028
.372
.284
.153
-.108
.785
.175
.189
.170
.026
-.018
.656
.232
.263
.308
.319
.353
.103
.220
.144
.091
.120
.250
.198
.189
-.087
1.407
1.105
.157
-.104
-.165
.176
.353
.378
.453
.437
.452
.128
.320
.216
.188
.156
.357
.278
1.162
-.018
1.355
.180
-.143
-.198
.172
.355
.409
.476
.460
.470
.244
.316
.181
.267
.277
.336
.272
1.168
-.003
1.512
-.096
-.137
.194
.328
.583
.286
.490
.339
.179
.376
.158
.259
.228
.320
.294
.152
.055
.765
.689
-.036
-.157
-.133
-.265
-.181
-.249
-.082
-.125
-.068
-.105
-.116
-.189
-.151
-.120
.076
.850
-.094
-.154
-.148
-.266
-.204
-.281
-.036
-.128
-.026
-.056
-.087
-.175
-.134
-.151
.086
.895
.235
.285
.272
.351
.309
.058
.198
.071
.018
.102
.217
.166
.179
-.109
236
APPENDIX 3 (CONTINUED)
Dyn2
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
Dyn2
.732
.493
.534
.465
.568
.218
.612
.280
.180
.194
.511
.464
.382
-.123
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
.960
.497
.844
.516
.315
.495
.133
.354
.355
.519
.441
.447
-.037
1.138
.542
.934
.182
.470
.479
.198
.189
.593
.470
.475
-.285
1.041
.556
.357
.459
.159
.387
.433
.555
.454
.478
-.067
1.070
.212
.527
.498
.214
.262
.619
.513
.478
-.225
1.584
.192
.222
1.206
1.266
.229
.223
.219
.036
.689
.243
.199
.166
.450
.406
.340
-.096
1.167
.104
.167
.303
.303
.184
-.111
1.621
1.417
.238
.185
.260
.086
1.821
.220
.194
.288
.076
.785
.598
.397
-.152
.689
.321
-.073
1.469
.028
1.263
237
APPENDIX 4. SAMPLE CORRELATIONS MATRIX
Rel2
Cul1
Tea2
Com2
Tea1
Int1
Capa23
Capa24
Com1
Prot1
Prot2
Int2
Dyn2
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
Rel2
1.000
-.073
.249
.146
.246
.094
.094
.081
.076
-.080
-.057
.043
.286
.104
.419
.125
.456
.149
.254
.876
.059
.117
.322
.354
.111
-.088
Cul1
Tea2
Com2
Tea1
Int1
Capa23
Capa24
Com1
Prot1
Prot2
Int2
1.000
-.109
.018
-.114
-.073
-.024
-.004
.029
.074
.044
-.065
-.123
-.044
-.269
-.075
-.201
.003
-.079
-.083
.004
.003
-.137
-.070
.004
.861
1.000
.132
.845
.131
.072
.040
.092
.015
.008
.055
.367
.364
.386
.364
.379
.076
.330
.234
.043
.035
.389
.284
.050
-.062
1.000
.080
.174
.087
.127
.855
-.028
-.039
.168
.287
.449
.251
.370
.261
.141
.316
.151
.138
.159
.265
.263
.131
.053
1.000
.136
.123
.114
.072
-.014
-.027
.051
.367
.401
.404
.357
.409
.079
.346
.266
.048
.021
.420
.343
.126
-.096
1.000
.166
.183
.156
.033
-.022
.783
.306
.303
.326
.353
.386
.092
.299
.150
.081
.101
.319
.269
.176
-.087
1.000
.800
.108
-.100
-.151
.156
.347
.325
.358
.361
.369
.086
.325
.169
.125
.098
.340
.283
.808
-.014
1.000
.126
-.141
-.184
.157
.356
.359
.384
.387
.390
.167
.327
.144
.180
.176
.326
.281
.828
-.002
1.000
-.089
-.121
.167
.312
.484
.218
.391
.267
.116
.368
.119
.165
.138
.294
.288
.102
.040
1.000
.855
-.044
-.210
-.155
-.284
-.203
-.275
-.075
-.172
-.072
-.095
-.098
-.244
-.208
-.114
.077
1.000
-.107
-.195
-.164
-.270
-.217
-.294
-.031
-.168
-.026
-.048
-.070
-.214
-.175
-.135
.083
1.000
.290
.307
.270
.364
.315
.049
.252
.070
.015
.080
.259
.212
.156
-.103
238
APPENDIX 4 (CONTINUED)
Dyn2
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
Dyn2
1.000
.588
.585
.533
.642
.203
.863
.302
.165
.168
.675
.654
.368
-.128
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
1.000
.476
.844
.510
.255
.609
.126
.284
.268
.598
.542
.376
-.033
1.000
.498
.846
.135
.530
.416
.146
.131
.628
.531
.368
-.237
1.000
.527
.278
.542
.145
.298
.315
.614
.536
.387
-.059
1.000
.163
.614
.446
.163
.188
.676
.598
.381
-.193
1.000
.184
.164
.753
.745
.206
.213
.144
.025
1.000
.272
.188
.148
.613
.589
.338
-.103
1.000
.075
.114
.316
.338
.140
-.092
1.000
.825
.211
.175
.169
.060
1.000
.184
.173
.176
.050
1.000
.813
.370
-.153
1.000
.319
-.078
1.000
.020
1.000
239
APPENDIX 5
UNIVARIATE NORMALITY OF THE COMPOSITE VARIABLES
Variable
min
max
skew
c.r.
kurtosis
c.r.
Rel2
1.000
6.667
-.094
-.567
-.488
-1.474
Cul1
1.000
6.000
-.148
-.894
-.518
-1.564
Tea2
1.333
6.667
.021
.129
-.147
-.445
Com2
1.000
7.000
.054
.325
.009
.027
Tea1
2.000
7.000
.345
2.086
-.011
-.033
Int1
1.667
6.333
-.158
-.956
-.280
-.846
Capa23
1.000
7.000
-.049
-.296
-.357
-1.077
Capa24
1.000
7.000
-.113
-.683
-.117
-.352
Com1
1.000
7.000
-.068
-.412
-.476
-1.439
Prot1
1.500
6.500
-.038
-.230
-.006
-.019
Prot2
2.000
6.000
-.045
-.273
-.410
-1.238
Int2
1.500
7.000
-.267
-1.615
-.060
-.181
Dyn2
1.667
6.333
-.401
-2.425
.022
.067
Expl2
1.500
7.000
-.061
-.366
.028
.084
Tacl2
2.000
7.000
-.086
-.520
-.485
-1.466
Expl1
2.000
7.000
.130
.786
-.398
-1.203
Tacl1
1.500
6.500
.035
.213
-.499
-1.507
Ass27
1.000
7.000
-.138
-.832
-.388
-1.173
Dyn1
1.333
6.000
-.299
-1.808
.077
.232
Rel1
1.250
6.500
-.085
-.514
-.571
-1.725
Ass26
1.000
7.000
-.199
-1.203
-.633
-1.911
Ass25
1.000
7.000
-.115
-.693
-.798
-2.410
Imp2
1.333
5.667
-.512
-3.092
.164
.494
Imp1
1.500
5.500
-.557
-3.367
.251
.757
Capa22
1.000
7.000
-.114
-.688
-.449
-1.355
Cul2
1.500
7.000
.160
.968
-.131
-.397
3.432
.665
Multivariate
Note: c.r. – Critical Ratio
240
APPENDIX 6. STANDARDIZED RESIDUAL COVARIANCES (Modified model)
Rel2
Cul1
Tea2
Com2
Tea1
Int1
Capa23
Capa24
Com1
Prot1
Prot2
Int2
Dyn2
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
Rel2
.000
-1.079
.058
2.154
-.059
1.383
1.389
1.194
1.119
-1.188
-.848
.639
.991
.263
.771
.652
.993
2.201
.674
.000
.876
1.721
1.295
2.098
1.639
-1.293
Cul1
Tea2
Com2
Tea1
Int1
Capa23
Capa24
Com1
Prot1
Prot2
Int2
.000
-1.606
.266
-1.688
-1.077
-.355
-.062
.435
1.092
.644
-.956
-.877
-.709
-2.143
-1.188
-.973
.051
-.250
-1.221
.059
.046
-1.008
-.065
.056
.000
.000
1.954
-.006
1.934
1.062
.595
1.361
.221
.113
.806
1.404
1.017
1.169
1.191
.789
1.119
1.076
.119
.634
.514
1.573
.375
.745
-.915
.000
1.185
2.566
1.284
1.870
.000
-.411
-.579
2.479
2.100
2.347
2.868
1.319
2.988
2.088
2.661
2.234
2.037
2.354
1.759
1.926
1.938
.783
.000
2.005
1.810
1.681
1.068
-.213
-.402
.750
1.328
1.493
1.347
1.004
1.143
1.164
1.227
.515
.708
.303
1.943
1.179
1.862
-1.417
.000
-.030
.153
2.309
.493
-.330
-.002
1.348
1.143
1.131
2.056
1.824
1.359
1.404
2.222
1.190
1.487
1.400
.949
.018
-1.292
.000
.013
1.588
-1.483
-2.230
-.029
1.751
1.066
1.492
1.777
1.437
1.267
1.598
2.493
1.838
1.442
1.493
.947
.003
-.203
.000
1.855
-2.078
-2.720
-.089
1.790
1.483
1.781
2.080
1.651
2.463
1.533
2.120
2.658
2.600
1.181
.839
-.013
-.032
.000
-1.311
-1.787
2.466
2.196
2.275
2.218
1.080
2.935
1.712
3.181
1.759
2.439
2.032
1.911
2.039
1.510
.593
.000
.000
-.644
-1.129
-.925
-1.383
-1.731
-1.073
-1.101
-.654
-1.068
-1.397
-1.449
-1.531
-1.167
-1.677
1.144
.000
-1.587
-1.047
-1.174
-1.376
-2.059
-1.592
-.460
-.717
-.379
-.706
-1.032
-1.231
-.799
-1.997
1.227
.000
1.297
1.423
.497
2.434
.989
.716
.885
1.031
.223
1.176
.681
.257
-.124
-1.519
241
APPENDIX 6 (CONTINUED)
Dyn2
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
Dyn2
1.229
1.702
1.408
1.176
1.805
1.993
1.248
1.509
1.278
1.338
1.501
1.961
1.933
-1.054
Expl2
Tacl2
Expl1
Tacl1
Ass27
Dyn1
Rel1
Ass26
Ass25
Imp2
Imp1
Capa22
Cul2
1.868
1.635
1.964
1.817
1.714
2.408
.710
1.912
1.689
1.683
1.523
1.705
-.535
1.454
2.222
1.724
1.597
.993
1.149
1.701
1.483
1.610
.897
1.493
-1.854
1.692
2.346
2.161
1.683
1.059
2.224
2.512
2.223
1.707
2.027
-.936
1.656
2.020
1.809
1.305
1.952
2.359
1.851
1.469
1.465
-1.065
.000
1.750
2.415
.002
-.002
2.042
2.243
2.123
.373
1.089
1.196
1.697
1.090
1.063
1.434
1.665
-.705
.000
1.114
1.690
1.496
2.117
2.072
-1.353
.000
.000
1.997
1.534
2.491
.883
.000
1.591
1.522
2.603
.739
1.339
1.336
1.810
-1.359
1.085
1.374
-.281
.000
.301
.000
242