Do the insiders understand the outsiders
Byron, R.D.
Published: 14/10/2016
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Byron, R. D. (2016). Do the insiders understand the outsiders: the influence of cultural factors and personal
preferences on individual employee behavior Heerlen: Open Universiteit Nederland
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Do the Insiders understand the Outsiders?
The influence of cultural factors and personal preferences on individual employee behavior
Proefschrift
Ter verkrijging van de graad van doctor
aan de Open Universiteit
op gezag van de rector magnificus
prof. mr. A. Oskamp
ten overstaan van een door het
College voor promoties ingestelde commissie
in het openbaar te verdedigen
op vrijdag 14 oktober 2016 te Heerlen om 13:30 precies
door
Ronny Delano Byron
Geboren op 4 januari 1957 te Paramaribo, Suriname
1
Promotores:
Prof. dr. J.M. Ulijn, Open University of the Netherlands.
Prof. dr. J. H. Semeijn, Open University of the Netherlands.
Co-promotor:
Prof. dr. R.S.J. Tuninga, Kingston University, United Kingdom
Overige leden van de beoordelingscommissie:
Prof. dr. H. van Herk, VU University Amsterdam, the Netherlands
Prof. dr. A.M.R. Trompenaars, VU University Amsterdam, the Netherlands
Prof. dr. R.J. Blomme, Open University of the Netherlands and Nijenrode Business University, the
Netherlands
Prof. dr. L.P. Dana, Open University of the Netherlands and University of Canterbury, New Zealand
2
Preface and acknowledgements
The motivation to start this research comes from over 20 years of business management and strategic
planning experience within multinational biopharmaceutical and medical technology companies throughout
the world. In the beginning of my career I believed that, following the companies’ rules and regulations
would be a personal and professional responsibility of every individual employee, irrespective of cultural
background. I quickly discovered that this was a somewhat naive point of view. I also found that the
difficulties of employees to follow company regulatory and legal requirements were identified as being
related to a certain cultural background of the employees involved as opposed to being directly related to
the task orientation of the employee or the familiarity of the employee with a certain process or procedures.
It also seemed that when things went wrong (i.e. breach of rules and regulations) it was always the
“culture” to blame, being it the cultural background (National Culture - NC) of the managers or specific
functionalities involved (Professional Culture - PC) or the culture and location of the company
(Organizational Culture - OC).
The confusion between the influence of cultural background and a person’s attitudes towards certain rules
and regulations created a lot of misunderstanding within culturally and functionally diverse project teams.
This often resulted in stereotyping and misinterpretations of individual behavior of employees, managers of
teams or departments in other geographical locations. In some cases these ‘compliance issues’ escalated
into failure to deliver the required revenues or project objectives.
This doctoral thesis aims to provide clarity in the extent to which cultural factors and personal preferences
are perceived to be influencing individual employee behavior. The aim is to understand these two factors of
influence through the eyes of the individual employee (the insider) and colleagues and superiors they
interact with (the outsiders). This research includes and differentiates multi levels of culture for their
respective influence on individual employee behavior. It further builds on the etic and emic cultural
research approaches, discussing their respective strengths and weaknesses and it explores the use of a
combined etic-emic research approach including self- and mutual perception data collection methods.
The findings from this research suggest that the way co-workers and superiors would tend to behave in a
certain situation would be more related to their thinking styles and behavioral patterns, which is mostly
influenced by personal preferences and then next by cultural factors.
3
This research also found that self-perceptions and the perceptions of colleagues and superiors are of critical
importance to get a broader perspective and understanding of why individual employees behave the way
they do. In regards to cultural factors we found indications that the behavior of a certain professional might
be more driven by the modus operandi of the professional group than by the organization’s culture or the
nationality of that professional. The importance of professional culture is also stressed in the finding that
the loose tight relationship between national and organizational culture is more dependent on how strong
the influence of professional culture is rather than on the company’s organizational culture or geographical
location of the company. Individual personal preferences and professional culture might therefore be of
more importance than organizational culture and national culture when organizational efficiency and
effectiveness are at stake.
This research has strengthened my believe that if we want to prevent misunderstandings and
miscommunications in culturally diverse teams, developing a sensitivity to each other’s ways of life is very
crucial to the success of our social and business interactions in an increasingly more complex and
globalized world. With this research I have aimed to help managers of culturally diverse teams to have the
agility to respond positively and effectively to practices and values that differ from their own cultural
expectations and personal practices.
Acknowledgements
This research was an explorative journey, which would have not been possible without the help and
support of many people who have contributed either directly or indirectly. First of all, I would like to thank
professor Jan Ulijn, who inspired and encouraged me to take a combined etic and emic research approach,
professor Judith Semeijn, for ensuring structure and consistency of my thoughts and professor Ron
Tuninga, for introducing me to the world of science and research. I would like to thank Geil Browning and
Wendell Williams from Emergenetics Inc., for their permission to use the Emergenetics survey and Brad
Hoffman, for providing me with the rough data from the respondents of the Emergenetics survey.
In addition, I would like to thank Megan Hooton, Juliet Mallabo-Palma and Ken Lee from Quintiles
Singapore, for their permission to observe clinical project managers in their day-to-day activities. I am
especially grateful to my fellow PhD students from the PhD School and of the Roundabout group for their
helpful comments and inspirational and positive sessions at the campus of the Open University in Heerlen
and the study center in Eindhoven.
4
In particular I would like to specially thank Jos Pieterse, Dennis Von Bergh, Gert van Brussel, Arjan
Verhoef, Stephan Korporaal, Paul Vossen, Colin Yeow and Wee Liang Tan who provided valuable and
extensive comments on an earlier draft of this manuscript. I also wish to thank Dirk Depril and Anouk
Byron, for their review of the statistical data and advice on the ranking scores, Hanneke Jonker, for
transferring the rough data into an excel format, Maridine Witkam, Zischa Byron and Paul Winsemius, for
proofreading and editing of an earlier version of this manuscript and Esther Verbeek and Errol Byron, for
their help with the printing preparations of the book. Thanks too to all friends and family for their
encouragement and tireless enthusiasm and above all special thanks to my wife Matty, daughters Anouk
and Zischa and my son Errol, for their continues love and support.
Zoelen, August 2016.
5
6
Table of contents
Preface and acknowledgements
3
List of Abbreviations
11
List of Figures
13
List of Tables
15
List of Appendices
16
Chapter 1
Do insiders understand outsiders?
18
1.1
Motivation for the research
18
1.2
Gaps in the literature
20
1.3
Research objectives and research questions
22
1.4
Methods used in this research
23
1.5
Outline of the research
25
Chapter 2
The influence of cultural factors and personal preferences on individual employee behavior:
a literature review
29
2.1
Introduction
29
2.2
Approaches for research into cultural differences; etic and emic
30
2.2.1 Cultural models from an etic approach; the outsiders’ view
30
2.2.2 Cultural models from an emic approach; the insiders’ view
34
2.3
38
Outsiders’ view versus insiders’ view
2.3.1 Etic and emic combined research approach
40
2.3.2 Proposed research framework for further studies
43
2.3.3 Data collection and analysis types from the research framework
50
2.4
62
Conclusions and Discussion
7
Chapter 3
Measuring behavioral intentions in a cultural context: validation of a psychometric instrument 69
3.1
Introduction
69
3.2
Theoretical background
71
3.3
Methods used
78
3.3.1 Sampling and respondents
78
3.3.2 Data sets characteristics
80
3.4
83
Results
3.4.1 Construct validity
83
3.4.2 Face validity
85
3.4.3 Test-retest reliability
85
3.4.4 Cultural and gender differences study
88
3.5
91
Conclusions and Discussion
Chapter 4
Measuring the influence of cultural factors and personal preferences on behavioral intention: an
explorative quantitative study with diverse countries’ and professions’
95
4.1
Introduction
95
4.2
Methods used
97
4.2.1 Sampling and respondents
98
4.2.2 Respondent characteristics
100
4.2.3 Applied statistical analysis
102
4.3
Results
103
4.4
Conclusions and Discussion
116
8
Chapter 5
Self-perceptions on behavioral intentions versus observations during meetings: a comparative study
among clinical project managers from an Anglo-Saxon and Asian cultural background
121
5.1
Introduction
121
5.2
Methods used
122
5.2.1 Sampling and procedures
128
5.3
Respondents characteristics
134
5.4
Results from the online Emergenetics survey
135
5.5
Results from observation session I, II and III
137
5.6
Conclusions and Discussion
147
Chapter 6
Self-perceptions and mutual perceptions on actual behavior: a comparative study among clinical
project managers from an Anglo-Saxon and Asian cultural backgrounds
154
6.1
Introduction
154
6.2
Methods used
156
6.3
Results from self-perception and mutual perception
159
6.4
Conclusions and Discussion
166
Chapter 7
Conclusions and discussion on the influence of cultural factors and personal preferences on
individual employee behavior
171
7.1
Introduction
171
7.2
Overview and discussion of the results: answering the research questions
175
7.3
Limitations of the research
180
7.4
Theoretical and practical relevance of this research
182
7.5
Future studies
186
9
Summary
188
Samenvatting (in Dutch)
196
References
204
List of Appendices
220
About the author
241
10
List of abbreviations and acronyms
AS
Asian cultures
AGN
Anglo-Germanic and Nordic cultures
ANA
Analytical thinking style
ANS
Anglo-Saxon cultures
ANSPAS
Anglo-Saxon cultures: Perception of Asian cultures
ANSOP
Anglo-Saxon cultures: Own Perception
ASPANS
Asian cultures: Perception of Anglo-Saxon cultures
ASOP
Asian cultures: Own Perception
ASEF
Asia-Europe Foundation
ASEM
Asia-European Meeting
ASR
Assertiveness behavior pattern
BI
Behavioral Intention
BFI
Big Five Inventory survey
CF
Cultural Factors
CON
Conceptual thinking style
CPM
Clinical Project Manager
CRA
Clinical Research Associate
COM
Communication survey
COMAS
Communication: perceptions from the Asian cultures
COMANS
Communication: perceptions from the Anglo-Saxon cultures
CPAI
Chinese Personality Assessment Inventory
EG
Emergenetics survey
EEG
Extended Emergenetics survey
EMA
European Medicine Agency
ENG
Engineers culture
EXE
Executive culture
EXP
Expressiveness behavioral pattern
FE
Female respondent
FLX
Flexibility behavioral pattern
FDA
Food and Drug Agency
GM
General Manager
HEXACO
Honesty-Humility (H), Emotionality (E), Extraversion (X), Agreeableness (A), Conscientiousness (C),
HR
Human Resources
HQ
Head Quarters
IB
Individual Behavior
11
ICT
Information and Communication Technology
IEB
Individual Employee Behavior
IDV
Individualism versus Collectivism
IVR
Indulgence versus Restraint
LA
Latin-Asian cultures
LTO
Long-term versus Short-term Orientation
MA
Male respondent
MAS
Masculinity versus Femininity
MP
Mutual Perception survey
MON
Monumentalism versus Self-effacement
NC
National Culture
OC
Organizational Culture
OPR
Operator culture
P1
Participant 1
PC
Professional Culture
PDI
Power Distance
PP
Personal Preferences
RSP
Responsiveness behavior
SD
Standard Deviation
SME
Small Medium Enterprise
SOC
Social thinking style
SPSS
Statistical Package for the Social Sciences
STR
Structural thinking style
SWOT
Strengths, Weaknesses, Opportunities and Threats
UAI
Uncertainty Avoidance
VP
Vice President
12
List of Figures
Figure 1.1
General outline of this thesis
Figure 2.1
Levels of culture and places of socialization (Hofstede, 2001)
Figure 2.2
Onion model with different interconnected cultural layers (Erez and Gati, 2004)
Figure 2.3
Onion model, visible (explicit) and invisible (implicit) part of cultures (Groen et al., 2006)
Figure 2.4
Cultural influence on types of values (Schwartz, 2012)
Figure 2.5
Influence of culture and genetics on individual behavioral domains (Poortinga et al., 1990)
Figure 2.6
An etic and emic cultural influence approach of cultural factors and personal factors on behavioral intention
(Karahanna et al., 2006)
Figure 2.7
Influence of cultural factors and personal preferences on behavioral intention and individual employee
behavior
Figure 2.8
Graphical illustrations of the mean scores for the cultural clusters
Figure 2.9
Professional cultures (Schein, 2012)
Figure 2.10
Organizational cultures and settings (Trompenaars and Woolliams, 2003)
Figure 3.1
Measuring behavioral intentions: based upon thinking styles and behavioral patterns
Figure 4.1
Measuring behavioral intentions and the influence of cultural factors and personal preferences on behavioral
intention
Figure 5.1
Measuring behavioral intentions, compared with tallied observed actual behavior
Figure 6.1
Comparing self-perception of own behavior with perceptions of others behaviors
Figure 6.2
Assertiveness mean values of own perception and perception of others, Asian cultures versus Anglo-Saxon
cultures and vice versa
Figure 6.3
Assertiveness mean values of own perception and mutual perception, Asian cultures versus Anglo-Saxon
cultures and vice versa
Figure 6.4
Responsiveness mean values of own perception and perception of others, Asian cultures versus Anglo-Saxon
cultures and vice versa
Figure 6.5
Responsiveness mean values of own perception and mutual perception, Asian cultures versus Anglo-Saxon
cultures and vice versa
Figure 6.6
Communication mean values of own perception and mutual perception, Asian cultures versus Anglo-Saxon
cultures and vice versa
Figure 7.1
Overview of the research approach taken in chapter 1 and 2
Figure 7.2
Overview of the research approach taken in chapter 3 to 6
13
List of Tables
Table 1.1
Overview of empirical studies conducted in this research
Table 2.1
Influence of the different cultural levels on individual behavior from an etic approach
Table 2.2
Comparison of etic and emic research approaches (Morris et al., 1999)
Table 2.3
Comparison of scores per Hofstede’s dimensions by country (Hofstede et al., 2010)
Table 3.1
Six different thinking styles combinations from the Emergenetics survey report
Table 3.2
Dimensions in percentiles of the behavioral patterns of the Emergenetics instrument
Table 3.3
SWOT of the Emergenetics instrument
Table 3.4
Overview of samples, surveys used, respondents and mode of analysis sub-study 1.A – 1.D
Table 3.5
Overview of sample characteristics of sub-study 1.A
Table 3.6
Overview of sample characteristics of sub-study 1.B
Table 3.7
Overview of sample characteristics of sub-study 1.C
Table 3.8
Overview of sample characteristics of sub-study 1.D
Table 3.9
Convergent and discriminant correlations between thinking styles and behavioral patterns attributes (N = 394)
Table 3.10
Face validity results between cultural groups and gender (N = 116)
Table 3.11
Summary of means and T-test (N = 57)
Table 3.12
Bivariate correlations between the first and the second administration (N = 57)
Table 3.13
Summary of means and T-test reporting Anglo-Germanic/Nordic versus Latin-Asian cultures (N = 330)
Table 3.14
Summary of means and T-test reporting males versus females (N = 330)
Table 4.1
Overview of samples, surveys used, 128 respondents and mode of analysis
Table 4.2.
Sample characteristics of 128 respondents by national culture, professional culture and gender
Table 4.3
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: means and T-test reporting, Anglo-Germanic/Nordic versus Latin-Asian cultures (N = 128)
Table 4.4
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test reporting, AngloGermanic/Nordic versus Latin-Asian cultures (N = 128)
Table 4.5
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: means and T-test reporting, Operator versus Engineers cultures (N = 108)
Table 4.6
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test reporting, Operator
versus Engineers cultures (N = 108)
Table 4.7
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: means and T-test reporting, Operator versus Executive cultures (N = 97)
Table 4.8
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test reporting, Operator
versus Executive cultures (N = 97)
14
Table 4.9
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: means and T-test reporting, Engineers versus Executive cultures (N = 51)
Table 4.10
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test reporting, Engineers
versus Executive cultures (N = 51)
Table 4.11
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: means and T-test reporting, Males versus Females (N =128)
Table 4.12
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test reporting, Males
versus Females (N =128)
Table 4.13
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
and professional cultural group and gender: means and SDs (N =128)
Table 4.14
Comparison of ranking scores of Cultural Factors and Personal Preference on Behavioral Intentions by national
and professional cultural group and gender: multivariate test Wilks’ Lambda reporting multiple group
comparisons (N =128)
Table 4.15
Four factors of influence on behavioral intention: Paired ranking scores
Table 5.1
Overview of quantitative and qualitative data collection methods used in this study
Table 5.2
Distribution of 23 clinical project managers by cultural group, national culture and affiliated office locations
Table 5.3
Distribution of thinking styles from 23 clinical project managers
Table 5.4
Distribution of behavioral patterns from 23 clinical project managers
Table 5.5
Observations total number of participants by cultural group, national culture and affiliated office (N = 6)
Table 5.6
Observations total number of participants by cultural group, national culture and affiliated office (N = 9)
Table 5.7
Observations total number of participants by cultural group, national culture and affiliated office (N = 14)
Table 6.1
Overview of perceptions comparisons between Anglo-Saxon versus Asian cultures for assertiveness,
responsiveness and communication
Table 6.2
Distribution of 10 respondents by cultural group, national culture, affiliated office and number of evaluations
Table 6.3
Summary of the major differences for assertiveness, responsiveness and communication
15
List of Appendices
Appendix 1:
Example of an Emergenetics profile report
Appendix 2:
Example of the different combinations of thinking styles and behavioral patterns
Appendix 3:
Example of the Emergenetics online survey
Appendix 4:
Example email, with an invitation for respondents to complete the Extended EG survey
Appendix 5:
Example of the Extended EG survey
Appendix 6:
Thinking styles and behavioral patterns, 128 respondents, explorative quantitative study
Appendix 7:
Thinking styles and behavioral patterns, of 23 respondents, in-depth case-study
Appendix 8:
Example of the details of the CPMs team meeting agenda
Appendix 9:
Observation score-card for 6 respondents, case study session I
Appendix 10:
Observation score-card for 9 respondents, case study session II
Appendix 11:
Observation score-card for 14 respondents, case study session III
Appendix 12:
Organogram of clinical project managers team, 23 respondents, in-depth case-study
Appendix 13:
Description of the clinical research process, as part of the clinical project managers daily tasks
Appendix 14:
Example of the mutual perception (MP) survey
16
17
Chapter 1
Do insiders understand outsiders?
1.1
Motivation for the research
Globalization has led to an increasing contact between cultures, with a dramatic effect on many societies
on attitudes towards gender, the environment, race, family life, and religion (Mishra, 2008; Habeeb, 2009).
In addition to this, new web-based communication methods and the formation of virtual and network
organizations have led to a tremendous increase in cross-cultural contacts between individuals in
organizations and between cooperating organizations on a global scale (Hermans and Kempen, 1998;
Cowen and Barber, 2003; Heller, Laurito, Johnson, Martin, Fitzpatrick and Sundin, 2010).
The globalization of labor and customer markets and the integration of different organizational structures
and cultures due to mergers and joint ventures have also resulted in an increasing diversity of the
workforce within organizations (Browaeys and Price, 2008). These developments show that multinational
organizational cultures are a dynamic phenomenon providing a context for interpreting and assigning
meaning to how these dramatic global trends influence and shape individual employee behavior on a dayto-day basis (Trice and Beyer, 1993; Denison, 1996; Rafaeli and Worline, 2000).
Because multinational organizations operate within different countries (national cultures) they have various
organizational cultures (Trompenaars and Hampden-Turner, 2001), with professional sub-cultures (Schein,
2010) that are connected and intertwined (Erez and Gati, 2004). These multinational organization cultures
also shape how individuals perceive their superiors and colleagues and often provide the lens through
which they perceive communication and create messages (Sadri and Flammia, 2011; Varner and Beamer,
2015). However, these different cultures have insiders and outsiders; to what extent do they influence and
understand each other within a multinational organizational context?
In most cultures social influence processes appear to be a universal aspect of group behavior (Mann, 1980).
However, comparative studies of social influence found that people in collectivist cultures are relatively
more responsive to influence attempts from others than in individualistic cultures; in other words, they
conform more to social pressure from others (Bond and Smith, 1996).
18
The authors also found that managers from different national cultural backgrounds use different influence
tactics in their attempts to influence subordinates (Sun and Bond, 1999). There is also an added complexity
as different cultural expectations and practices affect how individuals from different national cultural
backgrounds both present and interpret spoken or written information (Ulijn and St Amant, 2000; St
Amant, 2015).
The globalization and the increasing complexity and diversity of the workforce, have required managers to
become more competent in cross-cultural awareness and practices to effectively manage within a culturally
diverse context (Kumar, Anjum and Sinha, 2011). Because people with different national cultural
backgrounds use different languages and communication styles misunderstandings are common when they
attempt to communicate (St Amant, 2015). It is also assumed that the larger the differences in cultural
backgrounds of the sender and receiver are, the larger the difficulty will be to understand and interpret each
other’s words and behaviors (Robbins, 2005). These misunderstandings also arise, when team members
differ in terms of gender, age or different ethnic groups (Jackson, 1992). To overcome these
misunderstandings, managers in multinational companies might want to understand both the insiders and
outsiders within the different cultural contexts.
Why is this a problem? According to Williams and O’Reilly (1998), these workforce differences can lead
to a reduction within group communication, lower levels of cohesiveness, and a lower level of satisfaction
within the team. Other studies have found that if teams fail to manage these disagreements, relationshiporiented conflicts arise with negative effects on team performance (Milliken and Martins, 1996; Williams
and O’Reilly, 1998). As such when national cultural differences result in greater diversity of stereotypes
and mental models, misunderstandings among individual employees are more likely to occur (Levine and
Moreland, 1990).
At a managerial level, the problem of these misunderstandings not only leads to difficulties of effectively
communicating across the different cultural boundaries (Faulkner and Loewald, 2008), but also leads to
inefficiencies within the same organization or between cooperating teams in different geographical
locations (Nardon, Steers and Sanchez-Runde, 2011). Consequently managers are facing significant
challenges to effectively manage their increasingly culturally diverse workforces (Jackson, 1992).
19
Having been a senior manager in different multinational organizations over the past 25 years, I have
experienced similar difficulties in differentiating whether behaviors of my colleagues, co-workers and
superiors were driven by cultural factors or personal preferences. This has often led to stereotyping and the
misinterpretations of behavior of employees and managers and ultimately into failure to deliver the
required revenues or project objectives. It seemed that when things went wrong, culture was always to
blame, be it the manager’s national cultural (NC) background, his professional culture (PC), or the culture
of the organization (OC). These personal observations of cultural blame are rather similar to the so-called
scapegoat effect as found by Hendriks (1991) and Ulijn, Duysters and Fevre, (2010) in their exploratory
cultural differences study into Dutch and German ventures.
To conclude, managers and employees from different cultural backgrounds have a different perception on
the influence of culture and personal preferences on their own behavior. This confusion is causing
inefficiencies to communicate within a diverse workforce and sometimes leads to failures to achieve an
organizations projected goals. Providing clarity in the influence between cultural factors and personal
preferences on individual behavior can help to understand the mutual perceptions of managers and
employees and could facilitate better understanding and communication between these two groups.
1.2 Gaps in the literature
Studies into cultural differences have made a major contribution to the understanding of people’s ways of
life in different cultural contexts. However, mainly two issues have not yet been sufficiently addressed
(Tayeb, 1994). First, little attention has been given to the differentiation between the influence of cultural
factors and personal preferences on employee behavior within a globalized organizational context (also see
Zoogah, Vora, Richard and Peng, 2011). In the next chapter, the literature review will more profoundly
address how these two factors of influence can be theoretically disentangled. Second, so far, most studies
on cultural influence have only focused on the influence of single-level factors of culture, either national or
organizational culture, rather than on national, professional and organizational culture (Ulijn et. al., 2010).
Therefore, in this study these three levels of culture are included and differentiated for their respective
influence on individual employee behavior.
20
The emic and etic research approaches describe how language and culture can be studied (Pike, 1967). The
emic approach into cultural differences research always starts from the 'inside' of a culture, whereas the etic
research approach always starts from the 'outside' (Helfrich, 1999). However, research into cultural
influence, such as by Hofstede (1980, 1991), has predominately used the etic research approach with
quantitative methods (self-perception surveys). But this outsider’s view has received increased criticism
(Leung and Van de Vijver, 1996; Efferin and Hopper, 2006).
Cultural influence research that goes beyond Hofstede takes an insider’s view or emic approach, and
suggests that people are embedded within a social context and that cultural influence can be observed in the
different ways in which people communicate (Adair, Buchan and Chen, 2009). There is however relatively
little cultural influence research that takes an insider’s view and links individual employees and their
adapted behavioral patterns to the social setting in which they work and live.
There is also no evidence of such research in extensive reviews of the attitudes' literature (Gudykunst and
Ting Toomey, 1988; Bohner and Dickel, 2011). In addition, only a few studies have used both etic and
emic methods (e.g. Morris, Leung, Ames and Lickel, 1999), and studies that have used self- and mutualperception data collection methods are even more scares (Ulijn et al., 2010). This study further builds on
the etic and emic cultural research approaches, discussing their respective strengths and weaknesses and
exploring the use of a combined etic-emic research approach including self- and mutual perception data
collection methods.
In sum, this research aims to contribute to the literature by: 1. theoretically differentiating between the
influence of cultural factors and personal preferences on individual employee behavior, 2. considering
three cultural levels of influence, which includes national, professional and organizational cultures, and 3.
using a multi-method research approach. This multi-method approach combines the etic approach
(comparing cultural groups), with complementary fieldwork (within the biopharmaceutical industry)
collected by an emic approach (through the eyes of the individual employee) (Bhimani, 1999). This
research further uses self- and mutual-perception surveys to compare the perceptions of self, with
perception of others and vice versa. Finally, observations are used to compare self-perception on individual
behavior with actual behavior in a culturally diverse organizational setting.
21
For practice the research acknowledges the need within multinational companies to understand why
employees and managers from different functions and different national cultural backgrounds behave the
way they do. Understanding how employee behavior is influenced and shaped by both cultural factors and
personal preferences can help the managers to recognize these differences, and adapt their management
style in the best possible way. This is important, because managers are expected to work effectively in a
complex and culturally diverse context. To do so, they need to have the agility to respond emphatically and
effectively to practices and values that differ from their own cultural expectations and personal preferences
(Javidan and House, 2001, Browaeys and Price, 2008).
1.3 Research objectives and research questions
The above-mentioned managerial confusion in differentiating between cultural factors and personal
preferences and how these factors affect individual employee behavior, is of relevance and importance for
global managers operating in a multinational environment, with a culturally divers workforce. The gaps in
the literature further show the importance to theoretically differentiate between the influence of cultural
factors and personal preferences in order to better understand why individual employees behave the way
they do in a culturally diverse organizational context. This has led us to formulate the following central
research question of this research:
What is the role of cultural factors and personal preferences in the behavior of working individuals
in a culturally diverse organizational environment?
The objective of this research is to answer the central research question, by investigating how cultural
factors and personal preferences differ in their influence on individual employee behavior across different
cultural groups. The following sub-questions are formulated to operationalize the research:
1. To what extent can the influence of cultural factors and personal preferences on individual
employee behavior be theoretically disentangled?
2. Can a research framework be constructed that measures the perceived influence of cultural
factors and personal preferences on individual employee behavior?
22
3. Which measure can be used to validly and reliably measure the perceived influence of cultural
factors and personal preferences on individual employee behavior?
4. To what extent do employees in diverse cultural contexts differ in their self- perception on how
cultural factors and personal preferences influence their own behavior?
5. To what extent do employees in a specific cultural context differ in their self-perception on how
cultural factors and personal preferences influence their own behavior compared to their actual
observed behavior?
6. To what extent do employees in a specific cultural context differ in their self-perception compared
with their perception of others and vice versa (mutual perception)?
This research is about gaining a better understanding why individual employees behave the way they do.
The research is therefore meant to lead to recommendations for management practice that can help to
overcome misunderstandings and misinterpretations in a culturally diverse workforce within a
multinational organizational context.
1.4 Methods used in this research
This research uses a multi-method approach with a combination of exploratory empirical studies and
quantitative methods followed by two in-depth case studies combining quantitative and qualitative methods
in the biopharmaceutical industry. In reference to Silverman, (2011) our research approach tends towards a
more naturalist and explorative research approach where we get insight into social reality and understand
meaning through field notes as snapshots of what is going on. This mixed-method approach (quantitative
and qualitative data collection techniques and analysis procedures) is preferred because it provides better
opportunities to answer our research questions and it is also a method that is increasingly used within
business and management research (Tashakkori and Teddle, 2010).
23
This research approach is selected because it serves the objective of this thesis to theoretically disentangle
the two factors of influence, quantitatively test and measure the perceived influence, and to compare the
perceived influence of both cultural factors and personal preferences with actual behavior in a qualitatively
real life case study setting. This research approach makes it possible to capture different perceptions (selfand mutual) using multiple sources to better understand how cultural factors and personal preferences
influence individual employee behavior. We aim for high ecological validity of our outcomes. Table 1.1
summarizes the following studies and the respective methods and types of analysis used.
Table 1.1 Overview of empirical studies conducted in this research
Empirical study type
Survey used
Mode of analysis
Psychometric study
Emergenetics (EG) self-
Group level analysis
Testing the suitability to use the Emergenetics survey for
perception survey (100
Test retest reliability
cultural differences research comparing cultural groups
items)
Construct and Face validity
Cultural and gender
comparison (statistical
analysis using SPSS)
Explorative quantitative study
Emergenetics (EG) survey
Group level analysis
Measuring individual perception of influence of cultural
and ranking extension
T-test/Mann-Whitney U Test
factors and personal preferences on behavior intention
(400 items)
MANOVA
(based upon thinking styles and behavioral patterns).
Convergent/discriminant
correlation analysis
(statistical analysis using
SPSS)
In-depth bio-pharmaceutical case-studies:
EG survey and Observation
Individual level analysis
Qualitative, observations of 3 teams. Observations based
scorecard.
Descriptive analysis of
upon thinking styles and behavioral patterns of
observations referenced to
participants. Individual observation were verified via face
thinking styles and
to face teleconference with each individual participant
behavioral patterns
Quantitative mutual perception survey
Mutual perception (MP)
Group level analysis
On three dimensions: Assertiveness, responsiveness and
survey (27 items)
Descriptive analysis of mean
communication. Evaluate own perception and perception
scores in a radar diagram,
of two colleagues from other affiliated offices and vice
comparing self- and
versa.
perception of others and vice
versa
24
More details about the research design, methods and data collection approaches are presented in
respectively chapter 3 (psychometric study), chapter 4 (explorative quantitative study), and chapters 5 and
6 (in-depth case studies).
1.5 Outline of the research
The outline of the thesis is presented in figure 1.1 and reads as follows:
Chapter 1 presents the context of the research topic, relevant gaps in the literature, research objectives and
the central research question and sub-questions, the methods used in this research, followed by a general
outline of this research.
Chapter 2 reviews the etic and emic cultural influence models to investigate if and how cultural factors and
personal preferences are differentiated and conceptualized. The pros and cons are compared in a SWOT
analysis and combined etic and emic conceptual models are reviewed. Based on the reviews, a research
framework is proposed that functions as a guideline to conduct further empirical research on the influence
of cultural factors and personal preferences on individual employee behavior across different cultural
groups. This chapter addresses sub-question 1 & 2.
1. To what extent can the influence of cultural factors and personal preferences on individual
employee behavior be theoretically disentangled?
2. Can a research framework be constructed that measures the perceived influence of cultural
factors and personal preferences on individual employee behavior?
Chapter 3 presents a psychometric study that identifies and tests the validity and reliability of a measure for
the perceived influence of cultural factors and personal preferences on individual employee behavior and
for its suitability for further use in this research. This chapter addresses sub-question 3.
3. Which measure can be used to validly and reliably measure the perceived influence of cultural
factors and personal preferences on individual employee behavior?
25
Chapter 4 presents a explorative quantitative study that measures the differences in the perceived influence
of cultural factors and personal preferences on individual employee behavior comparing two national
cultural groups; individualistic-explicit cultures versus collectivistic-implicit cultures (Hofstede G,
Hofstede, Minkov and Vinken, 2008) and three professional cultures, namely operator, engineer and
executive (Schein, 2010). Within this chapter the research framework, developed from the literature review
and cultural influence model analysis in chapter 2, is tested using the instrument presented and discussed in
chapter 3. This chapter addresses sub-question 4.
4. To what extent do employees in diverse cultural contexts differ in their self- perception on how
cultural factors and personal preferences influence their own behavior?
Chapter 5 presents a qualitative self-perception study within an in-depth biopharmaceutical case study
(Yin, 2009), comparing the self-perception scores on behavioral intentions and tallied observations of
actual behavior. The case study was conducted during weekly update meetings in a team of clinical project
managers from different countries in Asia and Australia and New Zealand. This chapter addresses subquestion 5.
5. To what extent do employees in a specific cultural context differ in their self-perception on how
cultural factors and personal preferences influence their own behavior compared to their actual
observed behavior?
Chapter 6 presents a quantitative mutual perception study (Hall, 1995, Ulijn and St Amant, 2000)) within
an in-depth biopharmaceutical case study comparing individual employees own perception with those of
their colleagues and vice versa. This quantitative study was performed with the same group of clinical
project managers from the in-depth case study from chapter 5. This chapter addresses sub-question 6.
6. To what extent do employees in a specific cultural context differ in their (self) perception
compared with their perception of others and vice versa (mutual-perception)?
26
Chapter 7 presents the conclusions and discussion on the results from the previous studies in chapters 2 - 6.
Recommendations are formulated for cultural differences research, and for managerial practice with
respect to a better differentiation of cultural expectations from personal practices in a culturally diverse
organizational environment. This leads to implications for theory and practice. This chapter concludes with
a discussion of limitations of this research and by giving suggestions for future research.
Motivation for
the research
Gaps in
literature
Chapter 1
Objective and
central research
question
Methods used in
this research
Cultural factors
RQ 1 & 2
Etic approach
or outsiders view
Behavioral intention
Emic approach
or insiders view
Chapter 2
Personal preferences
RQ 3
Rather etic
Psychometric study 1
RQ 4
Rather emic
Explorative
quantitative study 2
Chapter 4
RQ 5 & 6
Combined etic/emic
In-depth case study 3
Chapter 5
Chapter 6
Conclusions and
recommendations
Chapter 7
Chapter 3
Figure 1.1 General outline of this thesis
27
28
Chapter 2*1
The influence of cultural factors and personal preferences on individual
employee behavior: a literature review
2.1 Introduction
Individual employees spend most of their (working) lives in organizations. Consequently their
day-to-day activities and behaviors are, at least in part, influenced and regulated by the organizations they
work for (Katz and Kahn, 1978; Pugh, 1990; Northcraft and Neale, 1990; Robbins, 1992). On the other
hand, by their individual behaviors as employees, managers, investors or consumers they can also affect the
organization’s way of doing business (Martin and Siehl, 1992). In reference to the central research
question, knowing how cultural factors and personal preferences influence the way in which individual
employees intend to behave might therefore help to reduce misunderstandings among employees within a
culturally diverse organizational setting. In the previous chapter it was concluded that cultural differences
studies have paid little attention to differentiating between the influence of cultural factors and personal
preferences on employee behavior. And most studies on cultural influence have only focused on the
influence of single-level factors of culture. It was further argued that the majority of studies have taken a
rather etic research approach, or outsider’s view, compared to an insider’s view, or emic approach. This
chapter therefore focuses on the next two sub-questions:
1. To what extend can the influence of cultural factors and personal preferences on individual
employee behavior be theoretically disentangled?
2. Can a research framework be constructed that measures the perceived influence of cultural
factors and personal preferences on individual employee behavior?
1
This chapter is based upon a paper by Byron, R.D., and Ulijn, J.M. (2012). Disentangling Cultural and Personal Factors in Behavior for the Business Context:
Towards a Framework for Future Research, presented at the 2nd International PhD conference Nyenrode Business University and Open University PhD School of
management, Breukelen, Nov 3rd 2012.
29
First, are reviewed and discussed opposite cultural influence models by using two cultural differences
research approaches etic and emic. Next, the strengths and weaknesses of both the etic and emic research
approaches are reviewed, and cultural influence models that differentiate between cultural and personal
factors are explored using a combined etic-emic research context. The aims of this review are to assess
whether the influence of cultural factors and personal preferences can be theoretically distinguished, and to
present a research framework for further empirical research. Next we will then further define the variables
from the research framework and discuss the related influences of the independent variables and the
dependent variables. As this thesis intends to compare the perceptions of individuals belonging to different
national, professional and organizational cultural groups, we present how individual perception data will be
collected and how the data will be analyzed comparing perceptions at a cultural group level. Conclusions
are drawn and discussed on the etic and emic cultural influence models at the end of this chapter.
2.2 Approaches for research into cultural differences: etic and emic
As mentioned in the introduction of chapter 1, to date many empirical culture studies have been
predominantly etic and introspective (Ulijn, van der Heijden and Festen, 2009). This implies that culture is
considered to be characteristic of a group, looking from the outside of an organization of people and it is,
therefore impossible to distinguish cultural aspects from personal ones in management behavior. From the
other end the emic approach looks at culture from within through a personal lens, taking into consideration
the influence of the person and his/her culture on management behavior (for instance the work by
Schwartz, 1990). This emic approach might be more labor intensive and those studies are far less popular
to conduct (Robins, Fraley and Krueger, 2009). In sub-section 2.2.1 cultural models from the etic
perspective will be reviewed. In sub-section 2.2.2 the same will be done from the emic perspective. In subsection 2.3 both research approaches will be discussed on the basis of their strengths and weaknesses.
2.2.1 Cultural models from an etic approach: the outsider’s view
This sub-section reviews cultural models from the etic perspective or from the outsiders’ view of reality.
An etic approach assumes universality; culture is viewed as a factor of influence, which explains
differences in cognition, learning and behavior (Segall, Dasen, Berry and Poortinga, 1990).
30
The etic cultural comparison identifies the degree to which psychological results can be generalized from
one cultural environment to another. It provides a descriptive system, which is equally valid for all cultures
and presents similarities as well as differences between cultures (Helfrich, 1999; Berry, Poortinga,
Breugelmans, Chasiotis, and Sam, 2011). Etic researchers primarily focus on identifying universal aspects
of human behavior, to find universal behavioral processes that can be understood across cultures
(Fukuyama, 1990; Ridley, Mendoza and Kanitz, 1994). The etic approach predominately uses selfperception data by using surveys and questionnaires.
We review and evaluate two widely referenced cultural influence models from an etic perspective. The first
model is Hofstede’s cultural influence model (2001). Figure 2.1 illustrates the influence of the different
levels of culture (NC, PC and OC) on individual values and practices at the socialization level given
(Hofstede, 2001). The practices represent the visible/explicit parts of culture; they are learned ways of
doing things and are subject to change. Values are the invisible/implicit part of culture; they are relatively
stable, difficult to change and are typically acquired through childhood, family and education. Values and
practices are visualized as separate compartments related to a certain cultural level and social context. The
model further assumes that national cultural/country values, for example, have the most effect especially in
our early childhood (within the family), while organizational cultural practices have the most influence
within our workplace. Professional culture and educational background seem to affect our values and
practices within the context of school.
Figure 2.1 Levels of culture and places of socialization (Hofstede, 2001)
31
The model assumes that professional culture and organizational culture have more influence on practices
and less influence on values than national culture. Professional culture has a similar influence on both
values and practices. Organizational culture has the most influence on a person’s practices and less on
his/her values. However, the influence might also depend on the extent in which professionals identify with
their professional discipline or with the organization they work for (Menzel, Aaltio and Ulijn, 2007).
As a consequence, professional culture and organizational culture would primarily influence a person’s
practices, while values are predominately influenced by national culture.
The model gives us a good idea of the sequence and hierarchy of cultural influence on values and practices
within a given social context, but does not demonstrate the interconnectivity between the different levels of
cultural influence. It also does not express if and how the different social contexts (family, school and
workplace) are connected. Furthermore, the model does not show yet how the different cultural levels are
connected and intertwined. It might be the case that the influence of national culture on practices might be
different in a context of a loose-tight relationship between the organizations culture and the national
cultural origin of the company (Ulijn and Kumar, 2000).
The second etic cultural influence model that is reviewed is that of Erez and Gati (2004). They have
conceptualized the influence of culture on individual behavior in an onion model of four cultural layers
(see also Figure 2.2) that includes global, national, and organizational and group culture, which is similar to
professional culture. Erez and Gati (2004) build on the notion that all cultural levels are related and
connected in a dynamic multi-level model of culture. This model consists of structural and dynamic
characteristics, which explain the interplay between the different cultural levels. The structural dimension
is represented by a nested structure of culture that goes from global, national, to organizational, to the
group cultural influence for the individual. The dynamic nature of culture is shown in the top-down and
bottom-up processes (see arrows) in which changes in one cultural level stimulates changes in other
cultural levels. Within this multi-level context, the lower levels of cultures are nested within higher levels,
and changes originating in one level shape changes in other levels. The model further proposes that through
top-down and bottom-up processes, thus behavioral changes of members in various cultures, are influenced
and affected by all different levels of culture. The outer and inner layers of cultural influences are therefore
connected and interrelated.
32
GlobalCultural
Influence
Na1onalCultural
Influence
Top-down
Organisa1onal
CulturalInfluence
GroupCultural
Influence
Individual
Bo=om-up
selfrepresenta1on
Figure 2.2 Onion model with different interconnected cultural layers (Erez and Gati, 2004)
According to Erez and Gati (2004), cultures influence each other through direct contact with other cultures
or via international trade, migration, and invasion. To understand culture you need to peel away the outer
layer of the onion to find that each layer represents a different unit of analysis. From this perspective group
or professional culture is the closest to individual behavior and is therefore assumed to have more influence
on that behavior than organizational, national and global culture that are the furthest away from individual
behavior. The onion model demonstrates the connection and interconnectivity between the cultural layers
but does not distinguish between the implicit and explicit parts of culture. In other words, the visible part of
each cultural layer manifested in language, behavior, lifestyle, ways of expression, and jargon is not
expressed. The model further assumes that global culture includes national culture and organizational
culture to include group/professional culture. However, similarly to Hofstede’s model, it is not clear in this
model, how loose or tight these relationships are between levels of culture.
Nevertheless taking these two etic models of cultural influence into account, we can summarize how the
influence of the different cultural levels is positioned hierarchically, from least to most influence on
individual behavior. Table 2.1 illustrates how the three cultural levels influence values, practices and
individual behavior, from an etic approach.
33
Table 2.1 Influence of the different cultural levels on individual behavior from an etic approach
__________________________________________________________________________________
Model/Author
Independent Variable
Dependent Variable
Cultural levels
Practices/Behavior
___________________________________________________________________________________________________________________________
Least Influence
Medium Most Influence
Cultural influence model, Hofstede and Hofstede, (2005)
Onion Model of cultural layers, Erez and Gati, (2004)
OC
PC
NC
Values
NC
PC
OC
Practices/behavior
NC
OC
PC
Individual behavior
__________________________________________________________________________________
Etic cultural influence models assume a gradual and sequential influence of the different cultural levels on
values and practices that goes from ‘least’ to ‘most’ influence. They also show that the more influence the
cultural levels will have on values, the least influence they will have on practices and vice-versa.
Professional culture is influencing both values and practices and national and organizational culture are
changing positions in relation to their respective influences on values and practices. Cultural influence is a
top-down and bottom-up process, where all cultural levels are influenced by each other and simultaneously
influence individual behavior. National culture has less influence on individual behavior than
organizational and professional culture.
2.2.2 Cultural models from an emic approach; the insiders view
This sub-section investigates how the different levels of cultural influence are perceived to affect individual
behavior through the eyes of the individual employee. This sub-section will address two widely referenced
cultural influence models from the emic perspective, e.g., the insiders view. The emic perspective is eager
to understand how people perceive the world around them. The research approach focuses on individual
answers and is interested in the individual perspective. Emic researchers assume that the individual
perspective allows a more realistic insight into the individual's 'mental map' of cultural understanding
(Helfrich, 1999). Emic researchers see culture as an integral part of individual behavior. As such, culture is
perceived and understood through the eyes of the individual (Gergen, 1985). In this approach, both the
behavior of the individual and his or her values, beliefs and underlying assumptions are inseparable from
the cultural context (Helfrich, 1999; Spering, 2001).
34
The emic researcher attempts to identify culture-specific aspects of concepts and behavior, which cannot be
comparable across all cultures. Emic researchers assume that the best way to understand a culture, is to
regard it as an integrated system that is inseparable from the individual.
The emic approach recognizes the complexity of culture and stresses the importance to pay attention not
only to the visible part of culture (explicit), but also the invisible part (implicit) (Groen, Ulijn and Fayolle,
2006). Within the emic research approach both self-perception and mutual-perception data are used as
research methods. Most theories on cultural differences focus on values, or on the middle level of the
continuum between visible and invisible elements of culture (Hofstede, 1980; Shenkar and Ronen, 1987;
Schwartz, 1992; Inglehart and Baker, 2000; House, Mansour, Hanges and Dorfman, 2002). Fewer theories
focus on the visible and external layer of behaviors and practices (House et al., 2002). Only a few models
focus on the invisible and internal level of basic assumptions. Reflecting the emic approach, the first model
under review is the onion model of Groen et al., (2006), (see also Figure 2.3). This model focuses on the
deepest and invisible level of basic assumptions and beliefs about human nature, and relationship to the
environment.
Figure 2.3 Onion model, visible (explicit) and invisible (implicit) part of culture (Groen, et al., 2006)
In reference to Hofstede’s model (see also section 2.2.1) that focuses on values (invisible elements) and
practices (visible elements) the main difference with this onion model (Groen et al., 2006) is perception.
Within this onion metaphor, cultures are perceived as an explicit expression of and an implicit influencer of
individual behavior (see also Geertz, 1993).
35
Within this onion model, to fully understand cultural influence you need to peel off these layers and look at
cultures from the perception of the individual, from the inside out, or from implicit to explicit components
of culture. The visible and explicit part of culture consists of behaviors, ways of life, laws and customs,
institutions, techniques, rituals, language and cultural influence in daily life. The invisible and implicit part
represents the unspoken rules, emotions, meaning to values and unconscious rules (Ulijn and St Amant,
2000). According to the emic approach, based on this explicit and implicit distinction, national cultures can
be differentiated into (1) low context and explicit cultures for example Anglo-Germanic and Nordic
countries (factual and direct) and (2) high context and implicit cultures for example Latin and Asian
countries (emotional and indirect) (Ulijn and Kumar, 2000).
Ulijn and Kumar also state that in general, high context/implicit cultures believe that the focus of a
business meeting is to build relationships. Where as low context/explicit cultures, in general, believe that
the goal of a meeting is to get to the point and discuss issues and solutions. This may lead to
misunderstanding where individuals from high context/implicit cultures might perceive the directness used
by low context/explicit cultures as drifting away from building long-term relationships. Individuals from
low context/explicit cultures on the other hand could perceive the rhetorical style of high context/implicit
cultures as out of focus and beating around the bush.
In sum, the onion model (Groen et al., 2006) gives insights in what is going on in individual’s minds but it
does not differentiate between the influence of national, professional and organizational culture on
individual behavior. This model assumes that the self-perceptions and mutual-perceptions will be
influenced in similar ways in all social contexts, irrespective of the geographical location of the company.
The differentiation between the two opposite national cultures, low context/explicit cultures (AngloGermanic and Nordic) and high context/implicit cultures (Latin-Asian) is useful for understanding self- and
mutual perceptions of cultural influence on individual behavior at an individual level. It allows studying
and comparing perceptions from individuals that tend to behave in a direct and factual manner, with those
of individuals that tend to behave in a more indirect and emotional manner. It might however also be that in
explicit direct and factual cultures, individuals may feel more comfortable to give their perceptions of
themselves and of other colleagues, compared to individuals from implicit indirect cultures who might feel
uncomfortable to evaluate their colleagues and superiors. This notion should be considered when empirical
self-perception and mutual-perception studies are conducted.
36
The second emic cultural influence model is under review is Schwartz’s model (1992, 2012), who studied
influence of culture on values by using the SVI (Schwartz Value Inventory). The focus is on values, or on
the middle level of the continuum between visible and invisible elements of culture (House et al., 2002).
Schwartz (1992, 2012), asked respondents to assess 57 values as to how important they felt these values
were as guiding principles of one’s life. From data collected in 63 countries, with more than 60000
individuals taking part, Schwartz derived a total of 10 distinct value types (power, achievement, hedonism,
stimulation, self-direction, universalism, benevolence, tradition, conformity and security) at an individuallevel analysis. These ten values have close relationships and have been grouped into four larger groups
(Schwartz, 2012, see also Figure 2.4)
•
Openness to change: stimulation, self-direction and some hedonism
•
Self-enhancement: achievement, power and some hedonism
•
Conservation: security, tradition and conformity
•
Self-transcendence: universalism and benevolence
SeekingChange
Self-Direction
FocusbeyondSelf
Universalism
Stimulation
Benevolence
Hedonism
Tradition
Conformity
Achievement
FocusonSelf
Power
Security
SeekingStability
Figure 2.4 Cultural influence on types of values (Schwartz, 2012)
In sum, in Schwartz’s circular model the grouped values have been arranged on a continuum, with the four
variables forming two opposite dimensions of both; Focus on Self versus Beyond Self and Seeking
Stability versus Seeking Change. Schwartz’s model focuses on the influence of national culture on values.
The model however, does not differentiate between the different levels of cultural influence and neither
does it include individual behavior.
37
In addition most cultural influence research related to this model have only used quantitative methods with
self-perception data collections approaches (see for example the study from Vedina, Fink and Vadi, 2006).
2.3 Outsider’s versus the insider’s view
The cultural influence model review in the previous sections (2.2.1 and 2.2.2) indicate that both the etic
and emic approach have their respective pros and cons as it relates to how cultural influence on individual
behavior can be conceptualized. This section compares the strengths and weaknesses of both the etic and
emic research approaches and explores cultural influence models that differentiate between factors of
influence on individual behavior using a combined etic-emic research approach. By comparing the
assumptions of both the etic an emic research approaches, table 2.2 shows the strengths and weaknesses of
each of the research approaches. The etic models make it possible to understand how in general cultural
levels influence individual behavior within different social settings (outsider’s view). The strengths of the
etic research approach are that a particular factor of influence can be assessed and results based on surveys
and questionnaires can be generalized comparing one cultural group with another. The weaknesses are that
culture as an independent variable is difficult to study in isolation and use of self-perception surveys may
lead to favorable impressions of own behavior. The strengths of the emic research approach are that it
makes it possible to understand the perceived influence of culture through the eyes of the individual, using
both surveys and observations. This approach could provide a more in-depth perspective on how
individuals perceive others and their surrounding environment. The weaknesses are that data acquired via
observations might be relatively subjective and the use of self-perception surveys may lead to favorable
impressions of own behavior. In conclusion, the emic approach is therefore more applied in exploratory
research and the etic approach more in testing hypotheses (Greenfield, 1996). As such both etic and emic
models separately only capture part of the picture, either the insider's view or the outsider's view. We may
also conclude that both approaches are using introspective methods, which is similar to the notion that most
current and past cultural studies have used introspection methods, which display common weaknesses
(Ulijn et al., 2009). Common weaknesses of introspection are that; (1) it can lead to distorted perceptions
that do not reflect the true nature of mental activities, (2) perceptions of one person cannot be scientifically
verified and generalized to understand the perceptions of another person (Landy and Conte, 2010). These
conclusions point to a different approach towards cultural differences research. An approach that aims to
simultaneously use the strengths of both approaches and mitigates the risk of the weaknesses to occur.
38
Table 2.2 Comparison of etic and emic research approaches (Morris et al., 1999)
Etic/outsider assumptions
Emic/insider assumptions
Cultural influence on individual behavior can be
Culture viewed as an integral part of individual behavior;
investigated in terms of dependent variables.
individual behavior cannot be separated from the cultural
Emphasis on general laws and causal explanations.
context. Emphasis on the uniqueness of each individual.
Requires a descriptive system, which is equally valid for all
Requires a focus on asking open-ended questions. Culture is
cultures (Valsiner, 1995).
perceived and understood through the eyes of the individual
under investigation (Helfrich, 1999; Spering, 2001).
Strengths
Strengths
Psychological results can be generalized from one cultural
Understanding of individual perspectives and psychological
environment to another.
thoughts within different cultural environments.
External, measurable factors that can be assessed at
Longstanding, wide-ranging observations that provide a rich
different cultural locations.
pool of detailed information.
Multi-setting surveys to assess the influence of a particular
Combination of real-life case studies, behavioral observations
factor on different cultural contexts (Greenfield, 1996).
and individual interviews (Greenfield, 1996).
Weaknesses
Weaknesses
Culture as a set of independent variables cannot be
Culture explained through the eyes of the individual via self-
examined in isolation; it is bundled with other variables
explanation tends to be guided by behavior norms and false
(Hesse, 1998, Matsumoto and Juang 2008).
stereotypes (Helfrich, 1999).
Culture is not clearly specified as a factor of influence, but
Self-reports tend to be biased by the social and personal
is rather a nebulous catchall category (Poortinga, Kop and
desirability, which can lead to favorable impressions and self-
van de Vijver, 1990).
deception (Zerbe and Paulhus, 1987).
The quality and extent of cultural influence varies
Self-report may also lead to misrepresentation and
significantly between individuals because each individual
misinterpretation of own behavior (Paulhus, 1986; Donaldson
construct their own personal culture (Valsiner, 1994).
and Grant-Vallone, 2002).
Dependent variables are only measurable in the form of
Misinterpretation of own behavior may also lead to hindsight
indicators such as performance of a test task or an
bias (Hawkins and Hastie, 1990).
observable behavior; these relationships mostly vary in
culture-specific ways (Helfrich 1999).
Best used for
Best used for
Testing hypotheses (Greenfield, 1996).
Exploratory research (Greenfield, 1996)
39
2.3.1 Etic and emic combined research approach
This sub-section presents cultural models that have conceptualized a combined etic-emic approach, with
the prospect to answer sub-question 1 and 2.
Poortinga et al., (1990), published a model (see Figure 2.5) that has some similarities with Hofstede’s
cultural influence model (see section 2.2.1, Figure 2.1). However in contrast to Hofstede (different levels of
culture have different levels of influence on values and practices), this model recognizes culture and
genetics as two factors influencing five behavioral domains physiology, perception, cognition, personality
Cultural factor
Genetic/Personal factor
and social environment.
Physiologic
Perception
Cognition
Personality
Socially
Figure 2.5 Influence of culture and genetics on individual behavioral domains (Poortinga et al., 1990)
There is a combined but unevenly distributed influence of the two factors on the behavioral domains.
Genetics influences individual physiology and perception more than the culture factor, cognition is
influenced evenly by both factors and Personality. And socially is influence more by the culture factor
than by the genetics factor. Triandis and Suh (2002) however, argue, that although biological factors (e.g.,
genetics) play an important role in shaping personality, they do not account for most of the variance.
40
In Triandis and Suh’s view the environment has a larger influence on one's personality than one's genetic
blueprint. In reference to Hofstede’s model (see section 2.2.1, figure 2.1), it can be argued that the three
cultural levels (NC, PC, and OC) will each separately and simultaneously (Erez and Gati’s model see
figures 2.2) affect each of the behavioral domains within a given social context (family, school and work),
which are not considered in Poortinga’s model. In addition, because of the complexity of human behavior
and the difficulties in understanding how genes are involved, it might also be difficult to measure the
influence of the genetic factor, when comparing individual behavior from two cultural groups.
.
Karahanna, Evaristo and Srite, (2006), have combined the insights of the previous etic models of Hofstede
(2001), Erez and Gati, (2004) and the emic model of Groen et al., (2006). They assume that all cultural
levels are interconnected and mutually influence each other. That there is a hierarchical order and that
individual culture has the most influence on individual behavior. Within this perspective, research on
cultural influence examines cross-cultural interaction; how people think, feel and behave, not in a direct
manner, but through their interpretations of the thoughts, feelings and acts of the people they interact with
and their cultural perceptions of the others. These combined cognitive and social processes can be viewed
as emergent, dynamic and open systems that spread across geographical boundaries and evolve through
time (Hong, Nenet-Martinez, Chiu and Morris, 2003; Myers and Tan, 2003).
To assess the influence of the different layers of culture as compared to personal preferences, Karahanna, et
al., (2006) developed a conceptual framework (see figure 2.6) that is based on the theory of Reasoned
Action (Fishbein and Ajzen, 1975) and the theory of Planned behavior (Ajzen, 1991) and the model of
subjective culture (Triandis, 2002). It is inspired by the cultural influence model from Hofstede (2001). The
theory of reasoned action assumes that an individual’s set of beliefs provides the cognitive foundation from
which attitudes, perceived social norms, and perceptions of control and ultimately intentions are assumed
to follow in a reasonable and consistent fashion. According to this theory, attitudes toward a behavior (or
more precisely, attitudes toward the expected outcome or result of a behavior) and subjective norms (the
influence other people have on a person's attitudes and behavior) are the major predictors of behavioral
intention.
41
Within this theory individual behavior is influenced by a wide variety of cultural, personal, and situational
factors, which may result in differences in beliefs between for example individuals who have an
individualistic and those who have a collectivistic orientation (Ajzen and Fishbein, 2005).
Ajzen and Fishbein, (2005), further assume that individual’s behavior follows from individual’s beliefs,
attitudes, and intentions.
Personality
Traits
Cognitive
Beliefs
Attitude
Practices
Subjective Culture:
Regional
Ethic
Religious
Linguistic
National
Professional
Organizational
Group
Behavioral
Intention
Behavior
Values
Social Norms
Figure 2.6 an etic and emic cultural influence approach of culture factors (CF) and personal factors (PF) on behavioral
intention (BI) ( Karahanna et al., 2006)
The framework of Karahanna et al., (2006) theoretically distinguishes between the influence of cultural
factors and attitudes as influencing variables shaping and molding individual behaviors and interactions
with others across geographical boundaries (Matsumoto and Juang, 2008). Within the context of this
framework, behaviors of individual employees are influenced by a variety of cultural levels in various ways
and by their attitudes and vice versa (Schein, 1990; Martin and Siehl, 1992; Robbins, 1992; Erez and
Earley, 1993).
42
Within this framework cultures and social norms are connected, assuming that both culture and attitudes
directly or indirectly influence behavioral intention and actual behavior. Behavioral intention is the
immediate antecedent of actual behavior (Ajzen and Fishbein, 2005). Behavioral intention, in turn, is
determined by attitudes and social norms. These determinants are themselves a function, respectively, of
cognitive beliefs, practices and values and cultural factors. Furthermore, personality traits vary as a
function of background factor influencing cognitive beliefs and values and practices respectively.
2.3.2 Proposed research framework for further studies
The framework of Karahanna et al., (2006) is based upon the theories mentioned earlier that have been
used extensively in empirical studies in social psychology, cross-cultural psychology and cultural
differences research. The adapted framework makes it possible to study the influence of cultural factors
and personal preferences on behavioral intention through the eyes of the individual person and
simultaneously makes it possible to compare between cultural groups. This framework would therefore be
a suitable option to conduct empirical research using a combined etic-emic research approach. However,
although based upon sound and empirically tested theories, it is rather complex and has not yet been
empirically validated (Straub, Loch, Evaristo, Karahanna and Srite, 2002). To overcome the complexity of
the framework, Gallivan and Srite (2005) suggest examining interactions between just two levels of culture
at a time (e.g., NC and OC, or NC and PC). In reference to this suggestion this sub-section explores this
approach and presents a simplified research framework, which would be more suitable within the context
of this research.
Building on the analysis of the etic and emic models, this section presents a simplified research framework
(see figure 2.7) that is inspired by the framework of Karahanna et al., (2006). The proposed research
framework focuses on three levels of cultural influence, national, professional and organizational culture
that are considered as the influencing factors on behavioral intention. Attitudes have been exchanged for
personal preferences because, personal preferences are considered as attitudes that do not remain stable
over time, since they can change and are influenced by individual decision-making processes, such as
choices (Sharot, Martino and Dolan, 2009), even in an unconscious way (Coppin, Delplanque, Cayeux,
Porcherot and Sander, 2010) or in a different cultural context (Riemer, Shavitt, Koo and Markus, 2014).
Personal preferences/attitudes can therefore be seen as the deepest and invisible level of basic assumptions
and beliefs about human nature, and relationship to the environment (Groen et al., 2006).
43
Behavioral intention has been extensively studied, covering diverse behavioral domains, which
substantiated the predictive validity of behavioral intentions. An example of such a study is a meta-analysis
performed by Sheeran (2002), which reported an overall correlation of .53 between behavioral intention
and actual behavior. Therefore, behavioral intention can be seen as a good predictor of actual behavior
(Ajzen and Fishbein, 2005). Behavioral intention can be viewed as a person’s thinking and behavioral
attributes that constitute the person’s distinctive method of relating to the surrounding environment (Kagan
and Haveman, 1976; Funder, 1997). Within this proposed framework, behavioral intentions are interpreted
as to thinking and behaving that originates from genetics (Jang, Livesley and Vemon, 1996; Bouchard and
McGue, 2003), internal thought processes (Borkenau, Riemann, Angleitner and Spinath, 2001), and
environmental influences (Yamagata, Suzuki, Ando, Ono,`kijima, Yoshimura, Ostendorf, Angleitner,
Riemann, Spinath, Livesley and Jang, 2006). This constant emerging combination of genetics and
environment is called “Emergeneses”, as it refers to thinking styles and behavior attributes that emerge from
one’s genetic blueprint and experiences in the surrounding environment (Browning, 2006). According to
Browning these two distinct dimensions of behavioral intention consist of four thinking styles, namely
Analytical, Structural, Social, and Conceptual thinking, and three behavioral patterns, i.e., Expressiveness,
Assertiveness, and Flexibility.
Cultural Factors (CF)
Thinking styles
National Culture (NC)
Professional Culture (PC)
Behavioral Intention (BI)
Individual Employee
Behavior (IEB)
Organizational Culture (OC)
Behavioral patterns
Personal Preferences (PP)
Figure 2.7 Influence of cultural factors and personal preferences on behavioral intention and individual employee
behavior
The proposed framework makes it possible to test the influence of cultural factors and personal preferences
as the influencing variables shaping and molding the influenced variable behavioral intention as a predictor
of individual employee behavior (Matsumoto and Juang, 2008).
44
The concept that both cultures and personal preferences directly influencing behavioral intention (see
influence of arrows) is adopted from Karahanna et al., (2006) in order to understand how this intended
behavior (based upon thinking styles and behavioral patterns) is influenced by both culture and personal
preferences.
The proposed framework makes it possible to collect data using large-scale surveys, and the measuring of
specific variables (cultural factors and personal preferences) that may influence individual’s related
behaviors (see for example Ferratt and Vlahos, 1998; Hill, Loch, Straub, and El-Sheshai, 1998), while
identifying the importance of various affiliations from the perspective of the individual employee, their
colleagues and superiors (Tayeb, 1994; Myers and Tan, 2003).
The approach taken with this research framework therefore fits within the combined etic and emic research
tradition that uses self- and mutual- perception methods, focuses on individual differences while viewing
cultural factors and personal preferences as influencing variables affecting individual behavior (Aaker,
Bener-Martinez and Garolera, 2001; Benet-Martínez and Karakitapolglu-Aygun, 2003; Diener, Oishi and
lucas, 2003). The research framework is inspired upon a combined etic and emic research perspective that
integrates insights from the various influences on individual cognition and socio-analytic behavioral
theories. It is an attempt to include the mutual relationship between cultural levels of influence, the
individual perspective and the environment as a dynamic interaction unfolding over time. This research
model is therefore a simplified and more focused version of the model of Karahanna et al (2016)
Based on the proposed combined etic-emic research framework we have reformulated the initial broader
central research question presented in chapter 1; “What is the role of cultural factors and personal
preferences in the behavior of working individuals in a culturally diverse organizational environment?” to a
more specific central research question that includes the respective variables that will be studied and
analyzed and that are the key focus of this thesis:
To what extent do personal preferences (PP) influence individual behavioral intention (BI) more
than national culture (NC), professional culture (PC) and organizational culture (OC) do, in a
culturally diverse organizational environment?
45
Next we define the related influencing variables (cultural factors and personal preferences) and influenced
variable (behavioral intentions) of the research framework.
Cultural factors
National culture definition
Hofstede (1980, 2001) defines culture as the collective programming of the mind that distinguishes the
members of one group or category of people from members of another group or category. Within the
research framework we assume three levels of collective programming, individuals are born within a
national cultural context. As they go through the educational system they are exposed to a certain
professional cultural context, and are then exposed to the organizational cultural context of the first
company they start to work for (Hofstede, 2005). We further assume that each cultural level influences
behavioral intention and that all three levels are connected and intertwined (Erez and Gati, 2004)
representing social norms.
Within the research framework Hofstede’s (2001) definition of national culture will be used, because it is
widely referenced in scientific studies, it is easy to understand and contains a more all-inclusive perspective
of people that are either members of a certain country (NC), profession (PC), and company/organization
(OC). We have also adopted the order of cultural levels (NC, PC and OC) because it has been extensively
used in cultural differences research and it allows to analyze and understand, cultural levels in relation to
the effect they have on behavior within different social contexts, family (at home), at school and at work
(Hofstede, 2005).
National cultural influence
At the national cultural level, cultural influence can affect the way in which companies do business, leading
to enhanced productivity, satisfaction and motivation (Spering, 2001; Triandis and Suh, 2002; Karahanna
et al., 2006). National culture can also influence how open or closed the organizational cultures are or how
tight or loose national culture and organizational cultures are connected (Ulijn and Kumar, 2000; Erez and
Gati, 2004). There are also indications that there exits a loose-tight relationship in the organizational
culture of a company that operates within different national cultural contexts. For example the
organizational culture of US companies based in the US, in general would have a loose relationship with
the national culture of the US. On the other end of the spectrum they assumed that in Japanese companies
based in Japan the organizational culture in general is embedded in the national culture and has a tight
relationship with the national culture.
46
In Latin companies the organizational culture is seen to be tightly related to the national culture. In
Northwest European companies, organizational and national cultures have a loose-tight relationship (Ulijn
and Kumar, 2000; Eppink, Ulijn and van der Heijden, 2010).
Professional culture definition
Professional culture is often seen as a sub-culture within organizational culture, because people in different
occupations/functions usually incorporate the professional biases associated with their roles within the
organization. Over time, these professional norms and values might become anchored in employees’
behavior which may lead to feeling more loyal to their professional code of ethics, than to the company’s
code of ethics (Wever, 1990). Individual professional values and practices are first developed through the
socialization process that individuals receive during their education and training in a specific country, at a
specific school, or University (Hofstede, 2001; Jenniskens, Ulijn and Tywuschik, 2011). This notion that
individuals are exposed to the educational system of a country before they are exposed to the values and
practices of an organization, suggests that professional culture can be seen as a separate level of cultural
influence on individual behavior (Hofstede, 2001).
Within the research framework, we acknowledge that professional culture is a separate cultural level that
influences members of a group of professionals (Schein, 2010). Professional culture is defined as a group
of professionals who have a common base of knowledge, a common jargon, similar background and
training, and a sense of being able to identify with each other (Schein, 2010).
Professional cultural influence
At the professional cultural level differences in perception often occur, because employees with a different
professional culture look at problems from different points of view (Groen et al., 2006). Different
professions working within the same organizational culture can have different perceptions and priorities
that are more closely related to their professional values and norms than to those of the company
(Wiebecke, 1987; Ulich, 1990). As a consequence, the behavior of professionals might be more driven or
influenced by their professional culture than by the organizational culture of the company they work for.
Within this view, professional culture is developed through a process of learning and continues
incorporations of professional norms and values, which often have a unifying impact on members
belonging to the same professional group within the organization (Sirmon and Lane, 2004).
47
This process of learning and incorporations of professional norms and values may also lead to differences
in perceptions from various professional groups (for example engineering versus marketing) within the
same organization (Ulijn en Weggeman, 2001). Another example comes from Wiebecke (1987) and Ulich
(1990) who found that professionals with a research and development background have different
perceptions about the relationship of the whole organization to the environment than professionals with a
marketing background. The differences in perception might be because of their differences in educational
and national cultural background, but could also be related to the ways in which they have incorporated and
anchored the values and practices of the organization in their professional codes of conduct (PC).
Organizational culture definition
It is acknowledged in the literature that professional values and practices are indeed first developed through
the educational system of a country (Schein, 1996; Ulijn and Weggeman, 2001). However, an individual
professional’s behavior is simultaneously supported, reinforced, or changed, within the context of an
organization’s culture (Pieterse, 2014). This means that if you have been trained as an engineer and your
profession is engineering, you can only behave in accordance to a set of rules as an engineer within the
organizational cultural context. The organization cultural context provides the operating environment that
perceives the individual as an engineer, without this organizational context, the individual is an outsider
who is not perceived to be behave like an engineer.
Within the research framework, we define organizational culture as culture that reflect the norms and
values that are anchored in the organization; it refers to the shared values, attitudes, standards, and beliefs
that characterize members of an organization and define its nature (Ulijn et al., 2001, p. 25). This definition
of organizational culture will be used, because it relates to how organizational values and beliefs drive the
way working individuals tend to think and behave. The definition acknowledges culture as an influencer
and culture as an expression of individual behavior. This definition also assumes that the national and
professional cultures of an individual employee are influenced by the organization’s values and practices
and vice versa, which is relevant for the context of this research.
Organizational culture influence
At the organizational cultural level, individuals from different national cultures use different languages,
communication styles, leading to potential cross-cultural misunderstanding, which can magnify problems
in communicating across cultures. This can in turn lead to increased absenteeism, staff turnover and
accidents (James and Jones, 1974; Gunter and Furham, 1996; Nardon et al., 2011).
48
Communication, resource sharing and influence are the most important behaviors for understanding how
cultural differences affect organizations (Jackson, May and Whitney, 1995). Cultural differences also shape
who speaks to whom, how often and about what (Park and Luo, 2001; Salk and Shekar, 2001). As a result,
the structure of an organization’s communication network reflects the structure of its cultural diversity
(Lincoln and Miller, 1979; Brass, 1984). As such organizational culture can affect organizational efficiency
and effectiveness (Mason, 1993; Mohr and Spekman, 1994; Barkema and Vermeulen, 1997).
Personal preferences
In a person’s everyday live personal preferences are considered his or her personal 'standards of judgment',
which he/she can apply to different situations and circumstances that occur from time to time (Shapley and
Shubik, 1974). Personal preferences refer to, and are interpreted as, a mean evaluative judgment in the
sense of liking or disliking something or somebody (Scherer, 2005). In different fields of academic
literature, personal preferences are defined in a variety of related, but not identical ways. For example, a
social sciences perspective on personal preferences considers preferences as a set of assumptions related to
ordering some alternatives, based on the degree of happiness satisfaction, gratification, enjoyment, or
utility these provide, a process which results in an optimal 'choice' (whether real or theoretical) (Arrow,
1958).
From a psychological perspective, preferences are described as an individual’s attitude in relation to a set
of objects, typically reflected in an explicit decision-making process (Lichtenstein and Slovic, 2006).
Preferences as 'attitudes' are defined as 'a psychological tendency that is expressed by evaluating a
particular entity with some degree of favor or disfavor' (Eagly and Chaiken, 1993, p. 1). Both definitions
imply that 'attitudes' are strongly linked with personal preferences, or could even be used interchangeably
(Eagly, 1992). Personal preferences are the way in which a person prefers to express him or herself within
a social context. The preferred way of individual expression, leads to differences in leadership styles and
decision-making processes (Brodbeck, 2000), in thinking, and communication styles and other aspects of
individual and group behavior (Triandis and Suh, 2002; Karahanna et al., 2006).
Personal preferences therefore play an important role in how individuals communicate and collaborate with
each other within an organizational context (Dai, Gurău and Ranchhod, 2006). Thus, personal preferences
can indeed be seen as an additional factor of influence on individual behavior next to the cultural levels
(Karahanna et al., 2006). Ajzen and Fishbein (2005), also acknowledge that individual behaviors tend to be
influenced not only by general attitudes, but by additional factors such as culture as well.
49
Within this view, the influence of culture and personal preferences can be theoretically distinguished as
independent variables, influencing individual behavior and vice versa, which is supported by many other
authors (e.g .,Triandis, 1996; Markus and Kitayama, 1998; Allinson and Hayes, 2000, Sutton, Baum and
Johnston, 2004; Van de Acker and Witlock, 2009).
Behavioral intention
In general individuals tend to first think before they behave. Thinking styles are therefore important because
they drive and precede behavior (Zhang, 2001; Browning, 2006), Understanding both thinking and behaving
achieves a better understanding of the individual’s deepest and invisible level of basic assumptions and
beliefs about human nature, and the surrounding environment (Kagan and Haveman, 1976; Funder, 1997,
Yamagata et al., 2006). Knowing a person’s thinking styles (internal thought processes) and behavioral
patterns can therefore better explain and differentiate the behavioral intentions of that person (Borkenau et
al., 2001). Within the context of this framework behavioral intention is a person’s own perception of their
thinking styles and behavioral patterns, which can be measured. Measuring both thinking styles and
behavioral patterns is important as they have a unique value in predicting and explaining individual behavior
(Zhang, 2001, 2002). This part of the research framework therefore aims to identify the perceived individual
thinking styles and behavioral patterns representing behavioral intention of a respondent.
Individual employee behavior
The arrow from behavioral intention to individual employee behavior and the dotted line around these two
elements assume the connection between behavioral intentions as a predictor of actual behavior (see also
Ajzen and Fishbein, 2005). This assumption is supported by studies, which substantiated the predictive
validity of behavioral intentions. This part of the research framework therefore aims to compare the
individual perception of behavioral intentions with actual individual employee behavior in order to better
understand why employees behave the way they do.
2.3.3 Data collection and analysis types from the research framework
With this research framework, we intend to compare the perceptions of individuals belonging to different
national, professional and organizational cultural groups. That is why we present how individual perception
data will be collected and how the data will be analyzed comparing perceptions at a cultural group level.
50
Types of data collections
Self-perception and mutual perception
The issue with self perception is that several individuals may look at the same thing yet perceive it
differently (Robbins 1992). This means that each individual person actually sees a different reality.
According to Robbins, we interpret what we see and call it reality. Reality can become unclear as
interpretations are heavily influenced by the context in which we see the person, object or event and by our
attitudes, personality, motives, interests, past experiences and expectations. As a consequence when we
observe people, we attempt to develop explanations of why they do things in the way they do.
Judgments about others based on self perceptions may lead to significant bias, like inaccurate conclusions,
negative false stereotyping, ‘like me’ effect, and ‘halo effect’ (Bem, 1972; Taylor, 1981). The authors
further suggest that in order to be able to understand individual behavior in the organization we need to
understand (1) the perception of each individual employee to see the way they see it, and (2) mutualperception between employees and (3) the perception of others of employees, to have a more diverse and
complete picture. Ulijn and St Amant (2000) have demonstrated that collecting data via a mutualperception is complementary to self-perception data and provides a more complete picture. Eppink et al
(2009), suggest that cultural differences studies should verify outcomes from self-perceptions with mutual
perceptions and perception of others (observers or external raters).
For these reasons a combination of these three data collection approaches (self-perception, mutual
perception and observations) will be used for further empirical studies in this thesis. This multiple sources
data collection approach allows better insights into what extend cultural factors and personal preferences
influence individual employee behavior.
Group level analysis: National culture
To study, analyze and compare between national cultures in a meaningful way at a group level, the sevenvalue dimension from Hofstede et al., (2008) will be used. These seven-value dimensions are; power
distance, individualism versus collectivism masculinity versus femininity, uncertainty avoidance, shortterm-orientation versus long-term-orientation, indulgence versus restraint, and monumentalism versus selfeffacement.
51
A country is characterized by its own unique score on each of the seven-value dimensions in this construct.
Now, we present a brief description of these seven national cultural dimensions, including examples of
how countries can be differentiated based on a high or low score on each of these national cultural
dimensions.
1). Power distance (PDI) is defined as the extent to which the less powerful members of institutions and
organizations within a country expect and accept that power is distributed unequally (Hofstede, 1994, p.
28). Power distance is often reflected in the hierarchical organization of companies, the respect that is
expected to be shown by students towards teachers, the political forms of decentralization and
centralization, the belief of society that inequalities among people should either be minimized or that they
are expected and desired. Latin American and Arab nations are ranked among the highest in this category,
Scandinavian and Germanic speaking countries the lowest.
2). Individualism versus collectivism (IDV) is a continuum that is described as individualism pertains to
societies in which the ties between individuals are loose: everyone is expected to look after himself or
herself and his or her immediate family. Collectivism as its opposite pertains to societies in which people
from birth onwards are integrated into strong, cohesive in-groups, which throughout people’s lifetime
continue to protect them in exchange for unquestioning loyalty (Hofstede, 1994, p. 51). Latin American
cultures are ranked among the most collectivistic cultures, while the USA is ranked as one of the most
individualistic cultures.
3). Masculinity versus femininity (MAS) is a continuum and is described as masculinity pertains to
societies in which social gender roles are clearly distinct (i.e. men are supposed to be assertive, tough, and
focused on material success whereas women are supposed to be more modest, tender, and concerned with
the quality of life); femininity pertains to societies in which social gender roles overlap (i.e. both men and
women are supposed be modest, tender, and concerned with the quality of life” (Hofstede, 1994, p. 82).
Hofstede considers Japan as one of the most masculine cultures, Sweden as one of the most feminine. The
U.S. and UK are moderately masculine.
52
4). Uncertainty avoidance (UAI) is defined as the extent to which the members of a culture feel threatened
by uncertain or unknown situations (Hofstede, 1994, p. 113). Uncertainty avoidance reflects the extent in
which a society attempts to cope with anxiety by minimizing uncertainty. Cultures that scored high in
uncertainty avoidance prefer rules and structured circumstances, and employees tend to be more loyal
towards their present employer. Mediterranean cultures and Japan rank among the highest in this category.
5). The long-term versus short-term orientation (LTO) dimension is the result of Hofstede’s co-operation
with Bond (1988), who links this dimension to the philosophy of Confucius (551/552-479 BC). Longversus short-term orientation is a continuum that describes a society's ‘time horizon’ or the importance
attached to the future versus the importance of the past and present. In long-term oriented cultures, thrift
and perseverance are valued; in short-term oriented cultures, respect for tradition and reciprocation of gifts
and favors are valued more. Eastern nations tend to score especially high on short-term orientation, while
Western nations score low and the less developed nations very low. China scored among the highest and
Pakistan scored among the lowest.
6). The sixth dimension indulgence versus restraint (IVR) was added based on work carried out by
Hofstede, Hofstede and Minkov (2010). Indulgence versus restraint is a continuum. Societies that are
extremely indulgent allow relatively free gratification of basic and natural human drives related to enjoying
life and having fun. Societies that, on the other hand, score high on restraint, value the suppression of
gratification of needs and regulate it by means of strict social norms. Indulgence tends to prevail in North
and South America, Western Europe and parts of Sub-Sahara Africa. Restraint prevails in Eastern Europe,
Asia and in the Muslim world. Mediterranean Europe takes a middle position on this dimension (Hofstede,
2011)
7). The seventh dimension monumentalism versus self-effacement (MON), was also added based on work
by Hofstede , Hofstede and Minkov (2010). Monumentalism versus Self-effacement is a continuum, in
which monumentalistic cultures appreciate individuals that can be characterized as having unchangeable
values, beliefs and behaviors that are not influenced by changing circumstances. Whereas self-effacing
cultures appreciate individuals that can be characterized as being humble, flexible and adaptable to
changing circumstances. Japan is traditionally regarded as a self-effacement culture. Japanese tend to
attribute success to external factors and failure to internal factors.
53
The United States, on the other hand, is traditionally regarded as a monumentalistic culture. Americans
tend to attribute success to personal ability or talent, and failure to bad luck, other’s errors, or lack of effort.
This thesis aims to look through the eyes of individual employees from different national cultural
backgrounds and compare their perceived influence of cultural factors and personal preferences on their
own perceived behavior (behavioral intentions). The differentiation of national cultural dimensions from
Hofstede is therefore useful to compare individual employees from clusters of countries with similar or dissimilar scores on each of the cultural dimensions. This clustering approach is also supported by work from
Ronen and Shenkar (1985) who performed an in-depth analysis of eight empirical studies using attitudinal
data to cluster countries. This approach is taken because it can help managers to better understand
similarities and differences in managerial practices between countries. Clustering could also provide
guidance for multinational companies, as to how international assignees can be more effectively circulated,
outcomes of policies and practices across national boundaries can be better predicted, and compatible
regional headquarters can be established (Ronen and Kraut, 1977). The clusters can also support research
into cultural differences in identifying variables such as level of influence of culture and personal
preferences that explain the variance in employees and managerial behavior.
Country clusters can therefore help with defining the extent to which results from one country can be
generalized for the entire group of countries sharing a particular variable within the same cluster (Ronen
and Shenkar, 1985).
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The following clustering of countries is based upon the different languages, which are considered a vehicle
for cultural differences as well (Ulijn and Lincke, 2004).
Within this thesis the following clusters are differentiated:
-
Anglo-Saxon, 6 countries (Australia, Ireland, Canada, United Kingdom, United States and NewZealand).
-
Germanic/Nordic, 7 countries (Austria, Denmark, Finland, Germany, The Netherlands, Norway and
Sweden).
-
Latin- European, 5 countries (Belgium, Italy, France, and Spain) - Latin- American cluster, 3
countries (Portugal, Columbia and Venezuela).
-
Asian, 9 countries (China, Hong Kong, India, Japan, Malaysia, Philippines, Singapore, South-Korea
and Taiwan).
Table 2.3 presents an overview of the scores for Hofstede’s cultural dimension for the clusters of countries
with rather similar scores on each of the national cultural dimensions. The Anglo-Saxon cluster on average
tends to score low on the cultural dimensions 1, 4, 5 and 7 and high on the cultural dimensions 2, 3 and 6.
They score the highest for dimension 2 and the lowest for dimension 7.
The Germanic/Nordic cluster on average tends to score low on the cultural dimensions 1, 3 and 7 and high
on the cultural dimensions 2 and 6 and medium on 4 and 5. They score the highest for dimension 2 and the
lowest for dimension 7. The Latin-European cluster on average tends to score low to medium on the
cultural dimensions 1, 3, 6 and 7 and high to medium high on the cultural dimensions 4 and 2. They score
highest for dimension 4, and the lowest for dimension 7. The Latin-American cluster on average tends to
score low to medium on the cultural dimensions 2, 3 and 5 and high to medium high on the cultural
dimensions 1, 4 and 6. They score highest for dimension 4, and the lowest for dimension 2. The Asian
cluster on average tends to score low to medium on the cultural dimensions 2, 3, 4 and 6 and high to
medium high on the cultural dimensions 1 and 5. They score the highest for dimension1, and the lowest for
dimension 2.
55
Table 2.3 Comparison of scores per Hofstede’s dimensions by country (Hofstede et al., 2010)
Cultural Dimensions
PDI
Countries/Cultural clusters
Australia
Ireland
Canada
United Kingdom
United States
New Zealand
Average scores Anglo-Saxon cultures
36
28
39
35
40
22
33
51
35
48
35
46
49
44
90
70
80
89
91
79
83
61
68
52
66
62
58
61
21
24
36
51
26
33
32
71
65
68
69
68
75
69
0
0
0
35
57
0
15
Austria
Denmark
Finland
Germany
Netherlands
Norway
Sweden
Average scores Germanic/Nordic cultures
11
18
33
35
38
31
31
28
70
23
59
65
53
50
29
50
55
74
63
67
80
69
71
68
79
16
26
66
14
8
5
31
60
35
38
83
67
35
53
53
63
70
57
40
68
55
78
62
0
0
0
10
12
0
0
3
Average scores Anglo-Germanic/Nordic cultures
31
47
76
46
42
65
9
Argentina
Belgium
Italy
France
Spain
Average scores Latin-European cultures
49
65
50
68
57
58
86
95
75
86
86
86
46
75
76
71
51
64
56
52
70
43
42
53
20
82
61
63
48
55
62
57
30
48
44
48
0
0
35
17
0
10
Portugal
Columbia
Venezuela
Average scores Latin-American cultures
63
57
81
67
99
86
76
87
27
51
12
30
31
42
73
49
28
48
16
31
33
44
100
59
0
0
0
0
China
Hong Kong
India
Japan
Malaysia
Philippines
Singapore
South Korea
Taiwan
Average scores Asian cultures
80
68
77
54
100
94
74
60
58
74
30
29
40
92
36
44
8
85
69
48
20
25
48
46
22
32
20
18
17
28
66
57
56
95
50
64
48
39
45
58
87
61
51
88
41
27
72
100
93
69
24
17
26
42
57
42
46
29
49
37
0
0
0
4
0
0
0
0
0
0
66
70
67
68
46
29
55
53
62
50
43
48
5
0
Average scores Latin-European-Asian cultures
Average scores Latin-American-Asian cultures
56
UAI IDV MAS LTO IVR MON
In conclusion, national cultural dimensions 1 (power-distance PDI) and 2 (individualism versus
collectivism, IDV), show the most distinct difference in scores between the different country clusters.
Major average score differences are especially striking within the Anglo-Germanic and Nordic cluster with
a average high score of 76 for dimension 2 and an average low score of 31 for dimension 1. The average
scores in the Latin-American and Asian cluster show an opposite trend: an average low score of 29 for
dimension 2 and an average high score of 71 for dimension 1. The Latin-European cluster scores medium
high on both dimension 2 64 and 58 for dimension 1.
Based on these average scores we can conclude that the cluster of Anglo-Saxon and Germanic/Nordic
countries can be characterized as rather individualistic cultures whereas the clusters of Latin American and
Asian countries as rather more collectivistic cultures. Figure 2.8 is a graphical illustration of the mean
average scores for six value dimensions for Anglo-Germanic/Nordic cultures versus Latin-American and
Asian countries.
Anglo-GermanicNordiccultures
Asiancultures
La5n-Americancultures
PDI
90
80
70
60
50
IVR
40
UAI
30
20
10
0
LTO
IDV
MAS
Figure 2.8 Graphical illustrations of the mean scores for cultural clusters
The IDV (individualistic vs. collectivistic) dimension allows for differentiation between the perception of
individuals that are focused on self and immediate family compared to individuals that are focused on the
norms and goals of the group. The IDV dimension can therefore be seen as a key differentiator in the
comparisons of national cultural groups.
57
The IDV dimension is therefore a useful indicator to demonstrate the influence of national culture (NC) on
how individuals might tend to behave within a given environment and will be used to differentiate and
compare cultural groups in this thesis.
The other four dimensions: power distance (PDI), uncertainty avoidance (UAI), masculinity (MAS) and
long-term orientation (LTO), are more related to how cultures generally cope with inequality, uncertainty,
emotional implications of gender issues, and time horizons respectively. This makes these dimensions of
less relevance as the focus of this research is on individual perceptions and perceptions of others within a
given cultural context. Dimensions six and seven, indulgence versus restraint (IVR) and monumentalism
versus self-effacement (MON), are relatively new as a result of which scores for the countries involved are
not available; these dimensions have therefore not been included in this thesis.
Professional culture
Based on empirical research within organizations, Schein (1996) has identified the following three major
inter-connected professional cultures, operator, engineering and executive (see figure 2.9).
Executive
Culture
Operator Culture
Engineers Culture
Figure 2.9 Professional cultures (Schein, 1996)
(1) The ‘operators’ are the line managers and workers who make and deliver the products and services that
fulfill the organization’s basic mission. Within the operator culture, the perception of a company’s success
or failure depends on knowledge, skill, learning ability and commitment of the individual employee.
58
Knowledge and skill required are ‘local’ and are the company’s core business or technology. Operators in
general have the capacity to learn and to deal with surprises and are able to work as a collaborative team in
which communication, openness, mutual trust and commitment are highly valued.
(2) The ‘engineers’ are the technocrats and core designers of any functional group (e.g. engineers,
accountants, information technology and software programmers, and market researchers). Within the
engineer’s culture, the perception of a company’s success or failure is based on science and available
technology. There is generally a preference for ‘people free’ solutions and linear, simple cause and effect,
quantitative thinking. That means that problems are resolved in a pragmatic and perfectionistic way.
(3) The ‘executives’ are the (senior) managers and executives. Within the executive culture, the perception
of success and failure of the company depends on financial survival and growth. There generally is a
preference to look for the ‘lone hero’, a person who is perceived to be in total control, who feels
indispensable and who makes decisions in isolation on his/her own judgment. The orientation is
hierarchical, individualistic and task and control focus, which means that empowerment of others is limited
and staying in control is key. Within this culture, individual employees are a resource like other resources
and the company is managed like a machine. The above distinction between professional cultures further
assumes that when there is sufficient initial alignment between operators (needs of the task), engineers
(needs for reliable and efficient operations) and executives (needs for minimizing costs and maximizing
profits), the company is able to operate successfully.
Ulijn and Weggeman (2001) also acknowledged that professional culture should be recognized as a
separate level of cultural influence on individual behavior within organizations. They have performed an
explorative case study of Dutch SME’s, in which they described the perceptions of different professions on
innovation culture within different organizations in a Dutch-Indonesian national cultural context. Based on
this research, Ulijn and Weggeman concluded that a combined effort of the following professional cultures
is of critical importance for innovation:
(1) Engineering culture
(2) Marketing culture
(3) Manufacturing culture
59
The professional culture differentiation mentioned above, excludes professional cultures referred to as
‘operational management’. These are assumed to be of less influence on the innovation culture of a
company. The professional cultures that were excluded are; medical doctors, lawyers, economists and
politicians. Schein’s professional cultures differentiation (operator, engineering and executive) best fits the
research objective, because it allows inclusion of a broader variety of professional cultures than the focused
(towards innovation) classification of Ulijn en Weggeman (2001), which excludes certain professions.
Organizational culture
Trompenaars and Woolliams (2003) distinguish three organizational drivers that determine organizational
culture:
− relationship between employees and their organizations
− vertical or hierarchical system of authority defining superiors and subordinates
− employee’s perception of the organization's vision, purpose and goals
Based upon these organizational drivers they identified four corporate cultures along two dimensions:
equality versus hierarchy and orientation to the person versus orientation to the task. Within this model
organization are viewed as individuals with different personalities who form and share a culture.
Figure 2.10 shows a framework with an overview of the four organizational cultures and how within each
quadrant organizational cultures are related to the respective two dimensions.
Egalitarian
Guided missile
Fulfilment-Oriented culture
Project-Oriented culture
Family
Task-oriented
Person-oriented
Incubator
Eiffel tower
Power-Oriented culture
Role-Oriented culture
Hierarchical
Figure 2.10 Four types of Organizational Cultures (Trompenaars and Woolliams, 2003) 60
The different organizational cultures can be described as follows:
The family: this culture is personal, but also hierarchical and power-oriented. Relationships are diffuse. The
focus in this culture is not to do things efficiently, but to them effectively. Employees are motivated by
praise and not by money.
The Eiffel Tower: this culture has a bureaucratic division of labor and roles. Relationships are specific and
status is ascribed. Existing power differences within the company are legitimized. Employees see their
work as their duty and an obligation to themselves.
The guided missile: this culture is egalitarian, impersonal and task-oriented. Loyalties to professions and
projects are stronger than loyalties to the company; the employees become enthusiastic about and identify
themselves with the final product.
The incubator: the idea of this culture is that organizations are secondary to the fulfillment of individuals.
Incubators are both personal and egalitarian and leadership is achieved. Incubators are very motivated for
their work, but work on islands of expertise.
Within this organizational culture differentiation, companies can move from one organizational culture to
another. The differentiation also assumes that within each stage of the organizational culture cycle,
companies constantly face dilemmas, and then through innovations, move to the next level and so on.
Through the innovation cycle a company might start within an incubator culture, family culture, Eiffel
Tower culture, and then to a guided missile for the cycle to start all over again.
The above organizational culture classification from Trompenaars and Woolliams (2003) will be used in
further studies conducted in this thesis. This classification was chosen because it assumes that
organizational cultures are a dynamic phenomenon that can change based on internal (personal and
professional values and practices) and external pressures (competition, market innovation and company
location). Furthermore, this organizational culture classification has been widely referenced in cultural
differences research and organizational cultural analysis (see e.g, Škerlavaj, Indihar Štemberger, Škrinjar,
and Dimovski, 2007; Browaeys and Price, 2008; Ulijn et al., 2010; Pieterse, 2014).
61
2.4 Conclusions and discussion
This chapter’s aim was to answer the following sub-questions:
1. To what extend can the influence of cultural factors and personal preferences on individual
employee behavior be theoretically disentangled?
2. Can a research framework be constructed that measures the perceived influence of cultural
factors and personal preferences on individual employee behavior?
We have reviewed and discussed two cultural differences research approaches, etic and emic, to answer
these two research questions. From this etic cultural models review we can now conclude the following:
The etic research approach primarily focuses on identifying universal aspects of human behavior, to find
universal behavioral processes that can be understood across cultures (Fukuyama, 1990; Ridley, Mendoza
and Kanitz, 1994). The etic approach aims of study cultural differences by comparing cultural groups and
generalizing study findings from one cultural environment to another (Helfrich, 1999; Poortinga et al.,
2011). The etic approach predominately uses self-perception data by using surveys and questionnaires.
The etic cultural influence review further indicated that the three cultural levels (NC, PC and OC) are
intertwined and related and can be considered as key influencers of individual employee behavior within a
given social context. Individual employees are simultaneously influenced by different cultures as they
move from one social context to another social context (from home to school and to work), but they in turn
also affect the behaviors of their families, of their fellow students at school and of their colleagues at work.
The different cultural levels therefore play a critical role in personal interactions and individual
relationships of employees, which can affect commitment, collaboration, communication and trust between
employees and ultimately organizational efficiency and effectiveness (Mason, 1993; Mohr and Spekman,
1994; Barkema and Vermeulen, 1997). From this etic review we can further conclude that national culture
seems to have less influence on individual behavior and practices than organizational and professional
culture and more influence on values than organizational and professional culture. The difference of
influence between organizational and professional culture on individual behavior is however still unclear.
62
From the emic cultural models review we can now conclude the following:
The emic research approach primarily focuses on understanding culture through the eyes of the individual,
which gives a more realistic insight into the individual's 'mental map' of cultural understanding (Gergen,
1985; Helfrich, 1999). Emic researchers assume that the best way to understand a culture is to regard it as
an integrated system that is inseparable from the individual (Helfrich, 1999; Spering, 2001). Cultures can
be understood as explicit expressions of individual behavior and implicit influencers of individual
behavior. It is assumed that, the explicit part (artifacts and products) of a culture influences how individuals
behave in their daily life within different social contexts (family, school and work). The implicit part (basic
assumptions) of a culture is assumed to influence individuals perceptions, norms and values through
unspoken rules, emotions, meaning to values, and unconscious rules (Groen et al., 2006).
The aim of studying cultural differences is to compare between individuals that can be perceived as rather
factual and direct (explicit) and individuals that are perceived to be emotional and indirect (implicit).
Individual perceptions for example on how important values are in their day to day life may therefore vary
based on how explicit or implicit they tend to express themselves. The etic approach uses both selfperception and mutual perception data by using surveys and questionnaires.
From the review of the combined etic and emic cultural influence models we concluded that cultural
factors and personal preferences can indeed be disentangled as influencing variables that shape and mold
individual behaviors and interactions with others across geographical organizational settings thereby
answering sub-question 1. Sub-question 2 was answered by proposing a research framework that includes,
three levels of cultural factors and personal preferences as influencing variables on behavioral intention as
the influenced variable. This research framework makes it possible to generalize results from cultural
differences research at group level (etic), but also at an individual level by understanding of cultural
influence from a personal and more subjective standpoint (emic). The framework aims to compare the
difference in perception of the influence of cultural factors and personal preferences on behavioral
intention.
63
Based on the proposed combined etic-emic research framework we have reformulated the initial broader
central research question presented in chapter 1: what is the role of cultural factors and personal
preferences in the behavior of working individuals in a culturally diverse organizational environment?
Into a more specific central research question that includes the respective variables that will be studied and
analyzed and that are the key focus of this thesis:
To what extent do personal preferences (PP) influence individual behavioral intention (BI) more
than national culture (NC), professional culture (PC) and organizational culture (OC) do, in a
culturally diverse organizational environment?
We further concluded that behavioral intention is viewed as a good predictor of actual behavior as it relates
to a person’s own perception of their thinking styles and behavioral patterns. Behavioral intention is
therefore a key concept in the proposed research framework, which makes it important to identify an
instrument that is suitable to validly and reliably measure both thinking styles and behavioral patterns in
order to compare the behavioral intention scores between members from individualistic and collectivistic
cultures, and from different professional cultures; operator, engineers and executive cultures. This led us to
formulate the following sub-question 3:
3. Which measure can be used to validly and reliably measure the perceived influence of cultural
factors and personal preferences on individual employee behavior?
To answer this research question a psychometric quantitative study is conducted, to test the validity and the
reliability of the Emergenetics instrument for further use in this thesis. This study is presented in chapter 3.
The study recruited working individuals from various organizations, from Anglo-Germanic Nordic and
Latin Asian national cultural background.
From the literature review in this chapter we concluded that, employees in different occupations/functions
usually incorporate their own professional norms and values that become anchored in their behavior
leading to employees feeling more loyal to their professional code of ethics than to that of their companies.
It is therefore important to find out if this process of learning and incorporations of professional norms and
values within the context of an organization also influences how different professionals perceive the
influence of cultural factors and personal preferences on behavioral intention.
64
Furthermore, individual perceptions can be different as it relates to national cultural differences, for
example, individualistic cultures/ rather factual and direct versus collectivistic cultures/rather emotional
and indirect, have different perceptions on the purpose of a meeting, which create misunderstandings at an
individual employee level. Furthermore, individual professionals, with a variety in knowledge, jargon and
training, have a diverse perception on their jobs, the company and on many other issues. It is therefore
relevant for our research to find out how individual employees working in these different organizational
contexts with multiple national and professional cultures, differ in their perception on the influence of
cultural factors and personal preferences on individual employee behavior. This has led us to formulate the
following sub-research question 4:
4. To what extent do employees in diverse cultural contexts differ in their self- perception on how
cultural factors and personal preferences influence their own behavior?
To answer this research question an explorative quantitative study, to test the research framework is
presented in chapter 4. This study recruited working individuals from various organizations, 28 different
nationalities and 13 different professions.
With the research framework, behavioral intention is presented as the stage before actual behavior.
Behavioral intention is seen as a person’s own perception of their thinking styles and behavioral patterns or
more specific the intended response of an individual to their surrounding environment. It could therefore be
of interest for our research to find out if individual employees with multiple national cultural backgrounds
from the same company, with the same profession would have rather similar perceptions on how cultural
factors and personal preferences influence behavioral intention. It would also be of interest to investigate if
there is a difference between perceived behavioral intention and the actual behavior of individual
employees within an assumed similar organizational and professional cultural context. This has led us to
formulate the following sub-research question 5:
5. To what extent do employees in a specific cultural context differ in their self-perception on how
cultural factors and personal preferences influence their own behavior compared to their actual
observed behavior?
65
To answer this research question a qualitative study with observations performed in an in-depth
biopharmaceutical case study is presented in chapter 5. The observations were made in a team of clinical
project managers from different countries in Asia and Australia and New Zealand.
The mutual-perception research approach into cultural differences makes it possible to compare selfperception study results with mutual perception surveys, providing a wider perspective and more
opportunities for data analysis and interpretations. It must however also be noted that most of mutualperception studies that have been reviewed had only measured national and organizational cultural
differences (Ulijn and St Amant, 2000; Ulijn et al., 2009). This research includes national, professional and
organizational cultural backgrounds and aims to measure, the self-perceptions and mutual perceptions of
individuals with the same profession, working for the same organization. At a group level we aim to
compare how the Anglo-Saxon cultural group perceives their own behavior compared to how their
colleagues from the Asian cultural group perceive their behavior and vice versa. This has led us to
formulate the following sub-research question 6:
6. To what extent do employees in a specific cultural context differ in their (self) perception
compared with their perception of others and vice versa (mutual-perception)?
To answer this research question a quantitative mutual-perception study is presented in chapter 6. The
compared individual employees own perception with perceptions of their colleagues and vice versa.
The study was done with the same group of clinical project managers from the in-depth case study in
chapter 5.
This thesis looks for a theoretical perspective (etic and emic) on cultural differences that allows both a
cultural group-level analysis and an individual-level analysis. For the purpose of comparing between
country clusters, we differentiate between Anglo-Germanic/ Nordic and Latin-Asian cultures. In regard to
influence of the three cultural levels we differentiate at a national cultural level between individualistic
versus collectivistic, and between low context- explicit and high context-implicit cultures. At a professional
cultural level we differentiate between: operator, engineers and executive cultures, and at an organizational
level between; incubator, family, Eiffel tower and guided missile cultures.
66
This thesis is about better understanding why individual employees in multinational organizations behave
the way they do. The following chapters 3 – 6 present empirical studies that are aimed to answer the central
research question of this thesis. This thesis aims to formulate recommendations for management practice
that can help to overcome misunderstandings and misinterpretations in a culturally diverse workforce
within a multinational organizational context.
67
68
Chapter 3*2
Measuring behavioral intentions in a cultural context: validation of a
psychometric instrument
3.1 Introduction
The research framework proposed in chapter 2 includes the influencing variables cultural factors (defined
as national, professional and organizational culture) and personal preferences defined as attitudes and the
influenced variable, behavioral intentions based upon thinking styles and behavior patterns. From the
previous chapter we further concluded that it is relevant to measure the perception of both thinking styles and
behavioral patterns because they better explain the behavioral intentions of individuals. This study aims to
compare the difference in perception of the influence of cultural factors and personal preferences on
behavioral intentions from individual employees with different national, professional and organizational
cultural backgrounds. It is therefore important to identify an instrument that is suitable to validly and
reliably measure both thinking styles and behavioral patterns.
The chapter presents a psychometric study that zooms in on the influenced variable behavioral intentions
and more specifically on how thinking styles and behavioral patterns can best be measured. This chapter
tests the validity and reliability of a psychometric instrument to find out its suitability for further use in this
thesis. This chapter therefore addresses sub-research question 3.
3. Which measure can be used to validly and reliably measure the perceived influence of cultural
factors and personal preferences on individual employee behavior?
Measuring the behavioral intention scores is the first step in a sequence of empirical studies (explorative
quantitative study and an in-depth case study) that will be conducted to answer the central research question.
This study aims to test the research framework by measuring behavioral intentions based upon individual
thinking styles and behavioral patterns of respondent from diverse cultural backgrounds (see Figure 3.1).
2
This chapter is based upon a paper by Byron, R.D., and Semeijn J.H. (2014). Measuring thinking and behavioral preferences with the Emergenetics instrument:
psychometric characteristics and cross-validation against the NEO-FFI, presented at the IX International Workshop on Human Resource Management,
University of Cadiz Seville Spain Oct 30-31,2014.
69
MeasuringBI
Thinking styles
Behavioral Intentions (BI)
Behavioral patterns
Figure 3.1 Measuring behavioral intentions: based upon thinking styles and behavioral patterns
We first present and review the currently most widely used psychometric instrument the Big Five
Inventory (BFI) from McCrae and Costa, (2010). We then look at the psychometric instrument
(Emergenetics) and explain our choice for this instrument based on the criteria driven by the research
framework. Different aspects of validity will be discussed including, construct validity to demonstrate that
there is sufficient evidence for the instrument to represent what it is intended for by theoretical design, face
validity to confirm that the instrument measures what it is designed to measure, and ecological validity to
confirm that what the instrument measures, within a culturally diverse setting represents real life (Schmuckler
2001; Weiner, 2003). With regards to reliability, a test-retest reliability study was conducted to confirm or
reject high or low variability in repeated measurements taken by a single person on the same item, under the
same conditions, over a period of time. This study aims to find out if the EG instrument demonstrate
satisfactory reliability and validity qualities and if so is the instrument useful for measuring individual
differences in a culturally diverse setting and for further use in an explorative quantitative study and the
in-depth qualitative and quantitative case study from chapter 4, 5 and 6 respectively. First we present the
research method used in these empirical tests, we then describe the characteristics of the samples used.
Finally we present the results from the following studies; test-retest reliability, construct and face validity.
The results from a separate sample of a gender and cultural differences study will also be presented with
the means influence score between individuals from Anglo-Germanic/ Nordic and Latin-Asian cultures and
between males and females. Conclusions and implications for further research are presented at the end of
this chapter.
70
3.2 Theoretical background
It is generally accepted that personality, in terms of an individual characteristic and preferential pattern of
thinking and behavior, is partly based upon a person’s unique genetic blueprint and partly on the influence of
the surrounding environment (Jang, Levesley and Vermon, 1996; Riemann, Angleitner and Strelau, 1997).
The literature also emphasizes similarities in personality structure in a wide variety of cultural groups (McCrae
and Costa 1997; Triandis and Suh, 2001; Yang, McCrae, Costa, Dai, Yao, Cai and Gao, 1999). Thus,
personality traits seem transcultural (McCrae and Costa 1997).
The Big Five personality traits- Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness to
experience (e.g., Digiman, 1990; Costa and McCrae, 2010) are considered to provide a good description of the
variation in human behavioral tendencies across cultural boundaries (John, Naumann, and Soto, 2008). This is
based on its applicability across observers and cultures (De Raad, Perugini, Hrebickova, and Szarota, 1998;
McCrae, Costa, Del Pilar, and Rolland, 1998; Muck, Hell, and Gosling, 2007). Many different studies
conducted with translated versions of the NEO Personality Inventory, found support for the entire Five-Factor
Model in culturally diverse countries, for example China, the Netherlands, Italy, and the Philippines (McCrae
and Costa, 1997; McCrae et al., 1998).
However, studies that compared respondents from different cultures found that the Openness factor is
particularly unsupported in Asian countries (see e.g., Ashton, Lee, Perugini, Szarato, de Vries, Di Blas, Boies
and De Raad, 2004; Cheung, Van de Vijver, and Leong, 2011). Researchers therefore argue that the Five
Factor Model does not entirely capture important aspects of certain cultures. For example, Hungarians do not
appear to have a single agreeableness factor (see e.g., Szirmak and De Raad, 1994; Triandis and Suh, 2002;
Ashton et al., 2004). Other studies confirmed that gender differences on Big Five traits tend to be larger in
developed cultures (such as France and the United States) compared to less-developed cultures (such as
Zimbabwe and Malaysia) (Funder, 1997; Costa, Terracciano and McCrae, 2001).
In reference to Hofstede (2001) this might also be related to the differences in scores between France and the
US as more individualistic cultures versus Zimbabwe and Malaysia as more collectivistic cultures. Based on
these findings it is suggested that personality traits may not entirely validly measure personal differences in
behavior across (all) cultural contexts (Church and Katigbak, 2002; Church, 2010).
71
Researchers have developed and tested alternative instruments to capture personal individual differences that
can be applied in and across different cultural contexts, such as the HEXACO model (Ashton and Lee, 2005),
or the Chinese Personality Assessment Inventory (CPAI) (Cheung, Leung, Fan, Song, Zhang, and Zhang,
1996; Matsumoto and Juang, 2008). Moreover, research indicated that thinking styles could make a unique
contribution to the understanding of human individual differences, next to personality traits (Zhang, 2002).
However, both these alternative instruments (HEXACO and CPAI) have not been considered for use in this
research, as they were specifically developed for certain cultural context. As this research studies three levels
of cultures, an instrument is preferred that can be used for all these cultures. What is also important is that
these two alternative instruments do not differentiate between thinking and behavior and only measure
personality traits as such. They do therefore not fit within the research framework and how we have defined
behavioral intention. Measuring both thinking and behaving is important as it contributes to better
understanding how individuals tend to behave in certain situations, which can help to explain and differentiate
the behavioral intentions of those individuals (see also Zhang, 2002).
Therefore in this chapter, the psychometric quality of the Emergenetics instrument that measures both thinking
styles and behavioral patterns is tested. The Emergenetics instrument is based on research findings from both
nature (genetics) and nurture (socio-analytic behavioral theory) that are assumed to interact similarly across
national cultures (Browning, 2006). The instrument has been developed to reveal insight into personal
differences in thinking styles and behavioral patterns at work that are relevant for interaction, cooperation and
team development with people from diverse and international backgrounds. Thus, the instrument aims to
measure individual differences in thinking and behavior, irrespective of gender and environmental influences.
The Emergenetics (EG) instrument consists of a self-reporting survey of one hundred items on a 7-point Likert
scale to measure two distinct dimensions; four thinking attributes, including Analytical, Structural, Social, and
Conceptual thinking, and three behavioral patterns, i.e., Expressiveness, Assertiveness, and Flexibility.
Each person has, a unique combination of the four thinking styles and three behavioral patterns, which is
called an Emergenetics Profile Report (also see Appendix 1 for a detailed description of each of the thinking
styles and behavior patterns).
72
Thinking styles
A typical Emergenetics survey reports four thinking styles expressed in a score for:
•
Analytical (Blue) - appreciates: problem-solving, analysis, mathematical, & investigative interests (A)
•
Structural (Green) - appreciates: rule following, administrative guidelines, traditional, methodical (T)
•
Social (Red) - appreciates: collaboration, caring, giving, empathy (S)
•
Conceptual (Yellow) - appreciates: unconventional, creative, unique, innovative (C)
Within the context of the EG survey the four thinking styles are defined as follows:
Analytical thinking is rational, inquiring, and clear. The Analytical thinking style tends to look for data and
scientific proof. People with an Analytical thinking style are considered logical, cogent, and objective. They
can appreciate the scientific method, and they learn by mental analysis.
Structural thinking is detailed, practical, and methodical. The Structural thinking style tends to follow rules
and is cautious of new ideas. People with a Structural thinking style are considered disciplined, organized, and
traditional. They like guidelines, and they learn by doing.
Social thinking is relational, collaborative, empathic, and supportive. The Social thinking style tends to be
team-oriented and socially aware. People with a Social thinking style are considered connectors and are
sensitive to the feelings and ideas of others. They are intuitive about people, and they learn from others.
Conceptual thinking is imaginative, unconventional, and visionary. The Conceptual thinking style tends to
like change and is easily bored. People with a Conceptual thinking style are considered inventive, original, and
innovative. They are intuitive about ideas, and they learn by experimenting.
A thinking style plays an important role in thinking processes and 92% of the population has more than one
thinking style (Browning, 2006). Table 3.1 shows the six different Thinking style combinations presented in
the Emergenetics report.
73
Table 3.1 Six different Thinking styles combinations from the Emergenetics survey report
Mono-model - one thinking style:
Dual-model - two thinking styles:
(A***) Analytical
(AT**) Analytical-Structural or convergent thinkers
(*T**) Structural
(**SC) Social-Conceptual or divergent thinkers
(**S*) Social
(A**C) Analytical-Conceptual or abstract thinkers
Conceptual (***C)
(*TS*) Structural-Social or concrete thinkers
_________________________________________
_____________________________________________________
Tri-model - three thinking styles:
Quad-Model – four thinking styles
(ATS*) Analytical-Structural-Social or convergent thinkers
(ATSC) Analytical-Structural-Social-Conceptual convergent and
(*TSC) Structural-Social-Conceptual or divergent thinkers
divergent thinker
Behavioral patterns
In addition to the four thinking styles, three behavioral patterns scores are reported for:
1. Expressiveness ̶ tend to behave: quiet, reserved, outgoing, gregarious
2. Assertiveness ̶ tend to behave: peacekeeper, accepting, competitive, driven
3. Flexibility ̶ tend to behave: focused, firm, accommodating, easy-going
The percentile scores of each behavioral pattern are expressed in thirds to characterize individual’s behavioral
patterns. Table 3.2 shows the behavioral patterns categorized as first-third of the population (0-33%ile),
second-third of the population (34-66%ile), or third- third of the population (67-100%ile).
Table 3.2 Dimensions in percentiles of the behavioral patterns of the Emergenetics instrument
Within the context of the EG survey the behavioral patterns are defined as follows:
Expressiveness is the level of participation in social situations. The degree of Expressiveness indicates how
much interest a person shows in others and in the world around them. Expressiveness is sharing what a person
experiences on the inside with the outside world. People who are at the quiet end of the spectrum for
Expressiveness will sit quietly in a meeting, and listen more than they talk. They are considered reserved and
calm. They avoid the spotlight, keep their feelings to themselves, and are energized by solitude.
74
People who are at the gregarious end of the spectrum for Expressiveness are just the opposite! You can’t miss
them in a meeting, since they are dynamic, talkative, and lively. They are considered outgoing, animated, and
spontaneous. They seek attention, and are energized by interacting with others. People who are in the middle
of the Expressiveness dimension feel comfortable to flex either to the left (more quiet) or either to the right
(more gregarious) depending on the situation they find themselves in.
Assertiveness is the level of interest in controlling tasks and results. The degree of Assertiveness reflects the
amount of energy a person invests in expressing their thoughts, feelings and beliefs. People who are at the
peacekeeping end of the spectrum for Assertiveness will wait patiently and politely for an elevator.
They are considered amiable, deliberate, and diplomatic. On the other hand, people who are at the telling end
of the spectrum for Assertiveness push the elevator button repeatedly, as if that will make it come faster.
They are considered competitive, forceful, and tough. They are ready for action, and prefer a fast pace. People
who are at are in the middle of the Assertiveness dimension feel comfortable to flex either to the left (more
peacekeeping) or either to the right (more forceful) depending on the situation they find themselves in.
Flexibility measures the willingness of a person to accommodate the thoughts and actions of others. The
degree of Flexibility reflects how much a person is willing to conform and flex with the interpersonal needs of
others. People who are at the focused end of the spectrum for Flexibility believe they are right and prefer to be
in control of others. They are considered firm, intent, and absolute. They have strong opinions and prefer to
stay on track. At the other end of the spectrum, people who are at the accommodating end of the spectrum for
Flexibility are receptive, easygoing, and adaptable. They don’t mind interruptions, ambiguity, or change. They
see all points of view, and are accepting of other people’s ideas. There are fifteen distinct combinations, within
6 groupings of thinking styles and behavior patterns (see also Appendix 2).
The instrument has been in use on a global scale since 2005 and is available in validated translations in 19
languages. A 5-step protocol was followed (Prepare, Translate, Pretest, Revise and Document) to validate the
survey for different languages. The process of translation included a team of 2 translators (native speakers) to
perform the translation, an expert reviewer in management consulting, a person knowledgeable in survey
design and adjudicators (also see for requirements on cross-cultural survey validation, Harkness, Van de
Vijver and Mohler, 2003).
75
The survey can therefore be used in Anglo-Germanic cultures (Australia, Canada, UK, US, New Zealand,
Austria, Germany) Nordic cultures (Denmark, Norway, the Netherlands, Sweden), Latin cultures (France,
Italy, Portugal, Romania, Spain), Asian cultures, (China, Indonesia, Japan, Korea, Malaysia, Thailand), FinnoUgrian cultures (Finland) and Slavic cultures (Russia). The above distribution of cultural groups is adapted
from Ulijn and Lincke, (2004) and inspired upon the different languages, which are vehicles for cultural
differences as well. These groupings will be used for further differentiation between cultural groups in this
study and the empirical studies in chapter 4, 5 and 6.
The EG instrument is a commercial product; controlled by a for-profit corporation that expects researchers to
get permission to use it. The company has conducted its own statistical research that demonstrates the validity
and reliability of the instrument, which is publically available on the company website in a technical report
(Williams, 2014). It must however also be noted that we will not present the Cronbach alpha for the reliability
of separate scale of the questionnaire used in this chapter and in chapters 4, 5 and 6.
They are available, but encrypted in our overall data of reliability. Explicit mention of those scores would
infringe with the commercial interests of this firm in this public document, which is a PhD thesis. In addition,
even though used globally in many different cultures the instrument has never been used to measure and
compare thinking styles and behavioral patterns to compare between clusters of countries.
The instrument has been used in several scientific publications (Doctoral studies) in both organizational as
well as educational contexts (see e.g., Epperson, 2007; La Prairie, 2007). The company allowed using the
scores of approximately 1500 managers from around the globe to test the instrument for the use in cultural
differences research, which has not yet been done. Testing the validity and reliability of the instrument to
compare cultural groups, offers an opportunity to contribute to academic and management research.
The EG survey has limitations, that apply to all self-reporting instrument. Self-reports tend to be biased by the
social and personal desirability, which can lead to favorable impressions and self-deception (Paulhus, 1986).
Self-report may also lead to misrepresentation and misinterpretation of own behavior (Paulhus, 1986).
Misinterpretation of own behavior may also lead to hindsight bias (Hawkins and Hastle, 1990). To partly
overcome these limitations, both quantitative methods (mutual-perception surveys) and observations will be
used in the sequential empirical studies conducted in chapter 4, 5 and 6. Table 3.3 shows a summary of the
strengths, weaknesses, opportunity and threats analysis of the instrument.
76
Table 3.3 SWOT of the Emergenetics instrument
Emergenetics (EG) survey
Strength
Weakness
Opportunity
Threat
-
Builds on nature (genetics) and nurture (socio-analytic behavioral theory).
-
Measure’s both thinking styles and behavioral patterns.
-
100 questions, scored on a 7 points Likert-scale.
-
Online available in 19 different languages.
-
Used globally > 20 years in business consulting, training and organizational development.
-
Large global database of more than 400.000 completed surveys.
-
Cronbach alpha for the reliability of each individual item of the survey is available, but encrypted.
-
No validation to compare groups in cultural differences research.
-
Instrument has been used in educational and organizational development research.
-
Opportunity to test the validity of the instrument for the use in cultural differences research.
-
Permission to use the online survey in academic research.
-
Based on self-report surveys that tend to be biased.
-
May lead to favorable impressions and self-deception
-
May lead to misrepresentation and misinterpretation of own behavior.
-
Tends to be guided by behavior norms and false stereotypes (please also see, table 2.2).
Based on the above SWOT analysis of the EG survey we can conclude, why the EG instrument is
functional for the use in further empirical studies: 1. We could test the validity and reliability of the
instrument within cultural differences research in a culturally diverse organizational setting. 2.
Measurements of thinking styles and behavioral patterns provide more insights in the perception of
individuals and how they tend to behave in certain situations and can also function as a good indicator for
actual behavior. 3. The scientific connection between the origins of the EG instrument (nature and nurture) are
aligned to the cultural influence model of Poortinga et al., (1990). 4. The possibility to have direct access to the
instrument and direct access to the scores of each item from the survey. These arguments have led us to select
and study this instrument for potential use in further empirical studies of this research.
77
3.3 Methods used
This study reflects a rather etic approach using surveys to compare between Anglo-Germanic/ Nordic and
Latin-Asian cultures.
3.3.1 Sampling and respondents
The sample consisted of all working individuals (> 23 Years of Age) from multiple national, professional
and organizational cultural backgrounds. The individual scores are consolidated at a group level and
statistically analyzed using SPSS to test the validity and reliability of the EG instrument and its suitability
in a culturally diverse environment. The psychometric quality of the EG instrument is tested with two
different samples for a total of four studies (construct and face validity, test-retest reliability and culture and
gender differences study). Table 3.4 gives an overview of the 4 sub-studies conducted in this chapter. The
table presents, 4 separate sub-studies, the 3 samples, used for each sub-study, the type of surveys used for the
data collections and the respondents per sub-study and the mode of analysis. Please note that sample 2 was
used for both sub-studies 1A and 1 B.
Table 3.4 Overview of samples, surveys used, respondents and mode of analysis sub-study 1A – 1D
Sub-study
Sample
Sub-study 1.A: Construct
validity
Survey used
Respondents
Mode of analysis
EG survey
N = 394
Convergent/discriminant
correlation analysis
EG survey
N = 116
Telephone/teleconference
interview
EG survey
N = 57
Paired sample T-test and
Sample 1:
N = 486
Sub-study 1.B: Face
validity
Sub-study 1.C: Test-
Sample 2:
retest reliability
N = 115
Sub-study 1.D: Cultural
Sample 3:
differences and gender
N = 330
All studies total N
Total samples
N = 931
Bivariate correlation analysis
EG survey
N = 330
Independent T-test
All EG survey
Total respondents
Multi-method of analysis
N = 897
78
Three samples were collected within a period of 4 years (2011- 2015), through an international network of 250
business consultants in Europe, US, Australia, and Asia-Pacific. At the time of the survey, all participants
where working individuals and from a variety of functions and industries (life-sciences and health-care,
education, learning and development, finance and accounting, consulting and engineering). The participants
completed the on-line EG survey as part of a team-building workshop, each participant was given their survey
results with their respective thinking styles and behavioral patterns, to help them understand and learn how to
apply the knowledge of their thinking styles and behavioral patterns in team or group communication, at work
or in day-to-day life.
The results from all participants where anonymized (by a research assistance) for use in each of the substudies. For a total of 931 participants were approached to take the on-line EG survey (see appendix 3 for an
example). The split by sample per sub-study was as follows; a sample of N = 486 is used for the construct and
face validity sub-studies; a sample of N = 115 is used for test-re-test reliability. A separate sample of N = 330
respondents is used for the ecological validity study to test for mean score differences between respondents
from Anglo-Germanic/Nordic cultures (low context and explicit cultures; factual & direct) and Latin-Asian
cultures (high context and implicit cultures; emotional & indirect) and males and females.
All participants were also asked to provide the following demographic information; nationality, profession and
gender. If the demographic information was not provided within the given inclusion period or if the
information was incomplete, respondents where excluded from the study.
All participants were given the choice at the beginning of the on-line EG survey to take the survey in one of
the 19 available validated translations. Taking the survey in English was not required or mandatory, however
all participants in this study completed the survey in English.
79
3.3.2 Data set characteristics
Sub-study 1A: A stratified sample of 486 participants was collected over a period of three years (2011 - 2014).
Table 3.5 below shows the characteristics of the sample used in the construct validity study.
Table 3.5 Overview of sample characteristics of sub-study 1A
Samplesub-study1A
Totalparticipants
486
Respondents %ofTotal Anglo-Germ/Nord %ofTotal Lat-Asian %ofTotal Males %ofTotal Females %ofTotal
394
81%
322
82%
72
18%
231
59%
163
41%
Representing 81% of the total sample of 486, 394 respondents were included in a construct validity study.
This sample consisted of 322 respondents from Anglo-Germanic/Nordic cultures (82%), 72 from Latin-Asian
cultures (18%) and included 231 males (59%) and 163 females (41%). 92 participants were excluded from the
study as they could not be categorized in either the Anglo-Germanic/Nordic or Latin-Asian cultural group.
This study examined the various relationships between the thinking and behavioral attributes and performed a
convergent/discriminant correlation analysis to detect meaningful similarities and differences. All surveys
were completed in the original on-line English version (see also Appendix 5).
Sub-study 1B: The same stratified sample of 486 participants from sub-study 1A was used for the face-validity
study. Table 3.6 below shows the characteristics of the sample used in the face validity study.
Table 3.6 Overview of sample characteristics of sub-study 1B
Samplesub-study1B
Totalparticipants
486
Respondents %ofTotal Anglo-Germ/Nord %ofTotal Lat-Asian %ofTotal Males %ofTotal Females %ofTotal
116
24%
78
67%
38
33%
73
63%
43
37%
Representing 24 % of the total sample of 486, 116 respondents participated in a face validity study.
This stratified sample consisted of 78 respondents from Anglo-Germanic/Nordic cultures (67%), 38 from
Latin-Asian cultures (33%) and included 73 males (63%) and 43 females (37%). All 116 respondents had
taken the survey in English (this was not required or mandatory). All 116 respondents also received their
respective scores of the EG survey in an Excel format. They were debriefed on their results from the
Emergenetics survey either face to face or via telephone sessions of between 20 – 45 min.
80
At the beginning of the debriefing session participants were asked if the questions had been clear to them and
if, from their perspective, the questions of the survey had measured their thinking styles and behavioral
patterns. They could answer in three categories: agree, somewhat agree, or disagree. If they somewhat agreed
or dis-agreed they were invited to explain why. The individual debriefing session, took place over a period of 6
months. The time associated with the personal debriefing sessions and the difficulties to schedule these
sessions might have influenced the relatively low response rate. However, the 116 respondents who were
debriefed after the inclusion period of 6 months seemed to be an acceptable number to draw meaningful
statistical conclusions
Sub-study 1C. The 115 participants of this sub-study were pre-selected through a global network of
management consultants. All of the pre-selected participants had already completed the on-line EG survey as a
requirement to attend a workshop or an individual feedback/coaching session. They received an email with the
question if they were interested in completing the on-line EG survey for a second time to see if there are any
differences between the two outcomes. They were required to complete the survey within a period of 2 months
after having received the email. Table 3.7 below shows the characteristics of the stratified sample used in the
test-retest reliability study.
Table 3.7 Overview of sample characteristics of sub-study 1C
Samplesub-study1C
Totalparticipants
115
Respondents %ofTotal Anglo-Germ/Nord %ofTotal Lat-Asian %ofTotal Males %ofTotal Females %ofTotal
57
49.5%
41
72%
16
28%
26
46%
31
52%
Representing 49.5% of the total sample of 115, 57 respondents participated in a test-retest reliability study.
This sample consisted of 41 respondents from Anglo-Germanic/Nordic cultures (72%), 16 from Latin-Asian
cultures (28%) and included 26 males (46%) and 31 females (52%). The same 57 respondents completed the
on-line survey two times, with a period between the completion of the survey ranging from 7 months
minimum, and 4 years maximum. This window between administration was chosen because it was assumed
that respondents who had taken the survey at least a minimum of 7 months before would not be able to
remember all answers to the questions, given the length of the EG survey (100 questions). All respondents also
receive the results from the second administration via email. However, at the time of the second administration
of the survey, there was no workshop or feedback session performed to explain any differences that might
have appeared between the first and the second administration.
81
The non-respondents were approached several times via email to complete the EG survey for a second time,
but did not reacted or reacted after the deadline for inclusion into the study was expired.
The relatively small sample size of 57 respondents could affect the ability to detect smaller differences
between the two administrations. However in line with Cohen, (1992) a sample of 57 should be sufficient to
detect a meaningful effect size. A paired sample T-test was conducted to check for changes in mean percentile
scores between the two administrations and a bivariate Pearson correlation analysis was performed to test the
linear relationship between two administrations.
Sub-study 1D: A separate stratified sample of 330 participants was collected over a period of three years (2011
- 2014) and all respondents were included to test for mean score differences between respondents from AngloGermanic and Nordic and Latin-Asian cultures and males and females from those cultural groups. The
stratified sample included a total of 28 nationalities with a range of 1-93 respondents per nationality. The
Table 3.8 below shows the characteristics of the stratified sample used in the cultural and gender differences
study.
Table 3.8 Overview of sample characteristics of sub-study 1D
Samplesub-study1D
Totalparticipants
330
Respondents %ofTotal Anglo-Germ/Nord %ofTotal Lat-Asian %ofTotal Males %ofTotal Females %ofTotal
330
100%
251
76%
79
24%
146
47%
184
53%
Like in the previous sub-studies, respondents were split into two groups; Group 1 the Anglo-Germanic and
Nordic (AGN) group consisted of 262 respondents from 13 countries, (Australia, Austria, Canada,
Denmark, Finland, Germany, Ireland, the Netherlands, Norway, Sweden, Switzerland, UK and US)
representing 73% of the total sample.
Group 2 the Latin-Asian (LA) group consisted of 68 respondents from 15 countries (Argentina, Belgium,
China, Columbia, France, Italy, Japan, Korea, Malaysia, Portugal, the Philippines, Singapore, Spain,
Taiwan, and Venezuela), representing 27% of the total sample. There was an even distribution of the
respondents between 146 males (47%) and 184 females (53%). Independent samples T-tests were applied to
check for differences in mean percentile scores between Anglo-Germanic/Nordic (AGN) versus Latin-Asian
(LA) cultures and males versus females. The sampling (convenient) procedure might have caused this
significant difference in sample size (i.e. N = 251 v. N = 79) between the Anglo-Germanic/Nordic and LatinAsian cultures. The different sample size has however not significantly influenced the distribution of the
different combinations of thinking styles and behavioral patterns between the two groups.
82
The cross-tabulated comparison also shows that the males and females were evenly distributed between the
Anglo-Germanic/ Nordic cultures (105 vs. 146) and for Latin-Asian cultures (41-38) respectively. All surveys
were completed in the original on-line English version (also see Appendix 5)
3.4 Results
3.4.1 Construct validity
Table 3.9 presents the results of the data set (N = 394) for convergent/discriminant correlations for factor
independence among the thinking styles and behavioral patterns. The results show low positive (r = .12 .35) correlations between Analytical and all other thinking styles. Conceptual thinking was low positively
correlated to Analytical thinking (r = .12) and Social thinking (r = .24) and negatively correlated (r = -.44) to
Structural thinking. These results show the dissimilar thinking constructs and that measures of the thinking
constructs are observed to a small extant to be related to each other.
Table 3.9 Convergent and discriminant correlations between thinking styles and behavioral patterns (N = 394)
_______________________________________________________________________________________________________
Analytical
Structural
Social Conceptual
Expressiveness Assertiveness
Flexibility
_________
________
______ __________
____________ ___________
________
Thinking styles
STR
.346**
-
-
-
-
-
-
-
-
-
-
-
-.442**
.235** -
-
-
-
-.353**
.509** .385**
-
-
-
-.322**
.215** .386**
.728**
-
-
.759** .319**
.522**
.254**
-
SOC
CON
.115*
Behavioral patterns
EXP
ASR
.175**
FLX
.124*
_______________________________________________________________________________________________________
*. Correlation is significant at the p>=0.05 level (2-tailed), **. Correlation is significant at the p>-0.01 level (2-tailed).
83
Within the behavioral patterns, Expressiveness is positively related to Assertiveness (r = .73) indicating some
overlap between these patterns. But it does not imply that the items on the scale load on the same construct.
Flexibility is positively related to Expressiveness (r = .52) indicating that the two constructs are to some extent
associated. Flexibility and Assertiveness show a lower (r = .25) association, indicating that the patterns only
relate to a small extent. A diverse picture emerged concerning to associations between the thinking styles and
behavioral patterns. Expressiveness is negatively related (r = -.35) to Structural thinking and positively related
with Social (r = 51) and Conceptual (r = .39) thinking. Assertiveness is to a small extent positively related to
Analytical (r = .18), Social (r = .22) and Conceptual (r = .39) thinking and negatively related to Structural (r = .32) thinking. Flexibility is to a small extent positively related to Analytical (r = .12) thinking and Conceptual
(r = .32) thinking and to a large extent to Social (r = .76) thinking.
84
3.4.2 Face validity
Table 3.10 shows if the participants felt that the questions of the survey were clear and if they measured their
perception of their thinking styles and behavioral patterns. Most participants agreed that the survey questions
were obvious and clear and that the survey measures what is supposed to measure. Three participants (in the
Anglo-Germanic/Nordic group/males) somewhat disagreed with the statement that the questions were clear
and obvious. When probed they mentioned that they had the impression that some of the questions were a bit
too American and not always clear to them. One participant felt that some questions were asked twice in a
different way, which he found personally confusing for him. In all, 97% of the respondents confirmed the face
validity of the instrument.
Table 3.10 Face validity results between cultural groups and gender (N = 116)
_____________________________________________________________________________________________________
N= 116
Questions of the survey were clear
Measured my thinking & behavior
Category
Respondents /Percentage Agree Agree
Disagree
Agree Agree
Disagree
Fully Some-what
Fully
Fully Some-what
Fully
_____________________________________________________________________________________________________
AGN
78 (67%)
75
3
0
77
1
0
LA
38 (33%)
38
0
0
38
0
0
Male
73 (63%)
70
3
0
72
1
0
Females
43 (37%)
43
0
0
43
0
0
_____________________________________________________________________________________________________
3.4.3 Test-retest reliability
Table 3.11 presents the mean scores from the first and second administration (interval between 5 months
and 4 years) for the sample of N = 57 and the results from the paired sample T-test.
The overall total mean score for the first administration for the thinking styles were (M = 48.50, SD = 28.12),
ranging from (M = 36.49 – 54.19) for the second administrations they were (M = 47.88, SD = 28.76), ranging
from (M = 34.42 – 59.37).
85
Table 3.11 Summaries of means and T-test (N = 57)
_______________________________________________________________________________________________________
Paired Statistics
Paired Differences
Attributes
N
Thinking styles
________
_
Mean
Std. D
_____
_____
Std.
Err M.
_____
Sig.
(2 tailed)
_____
ANA (1)
ANA (2)
57
57
50.72
47.58
27.07
29.90
3.6
4.0
Pair 1
.146
STR (1)
STR (2)
57
57
36.49
34.42
27.31
27.84
3.6
3.7
Pair 2
.457
SOC (1)
SOC (2)
57
57
52.61
50.37
28.16
27.29
3.7
3.6
Pair 3
.400
CON (1)
CON (2)
57
57
54.19
59.17
29.93
30.00
4.0
4.0
Pair 4
.061
Total M (1)
Total M (2)
57
57
48.50
47.88
28.12
28.76
3.7
3.8
Behavioral patterns
EXP (1)
EXP (2)
57
57
55.61
51.11
30.73
29.86
4.1
4.0
Pair 5
.080
ASR (1)
ASR (2)
57
57
55.82
52.44
28.93
28.81
3.8
3.8
Pair 6
.207
FLX (1)
FLX (2)
57
57
54.95
52.30
30.02
27.89
4.0
3.7
Pair 7
.334
Total M (1)
57
55.46 29.89 4.0
Total M (2)
57
51.95 28.85 3.8
_______________________________________________________________________________________________________
*. Correlation is significant at the p>=0.05 level (2-tailed), **. Correlation is significant at the p>=0.01 level (2-tailed).
ANA=analytical, STR=structural, SOC=social, CON=conceptual; EXP=expressiveness, ASR=assertiveness, FLX=flexibility
The overall total mean scores for the first administration for the behavioral patterns were (M = 55.46, SD
=28.89), ranging from (M = 54.95 – 55.82) for the second administrations they were (M = 51.95, SD = 28.85)
ranging from (M = 51.11 - 52.44). The results from the paired sample T-test show that both the thinking styles
and behavioral patterns from both administrations show no significant differences in the mean scores. 3
3
Footnote p. 84, Subsection 3.4.3 Sub-study 1.C: Reliability. The attentive reader will notice that we have not presented the Cronbach alpha for the reliability
of each individual item of the questionnaire used. They are available, but encrypted in our overall data of reliability. The reason is that we thank this survey to
the willingness of Emergenetics, Inc. that has its headquarters in (Denver, Colorado USA). Explicit mention of those scores would infringe with the commercial
interests of this firm in this public document, which is a PhD thesis. We are very grateful to this firm, which allowed using the scores of approximately 1500
managers from around the globe.
86
Table 3.12 presents the bivariate correlation results for the sample of N = 57. The scores of the two
administrations of all thinking styles positively correlated significantly ranging from .71 to .85. An average .77
correlations for thinking, shows a strong association between the two administrations. The correlations for the
behavioral patterns were all significant and ranged from .75 to .80. The average score of .78 also demonstrate a
strong positive association between the two administrations. The overall combined correlation scores of both
thinking styles and behavioral patterns were all significant and ranged from .71 to .86 (averaging .78).
Table 3.12 Bivariate correlations between first and second administration (N = 57)
___________________________________________________________________________________________________
Administrations Correlations
1st
1st
1st
1st
1st
1st
1st
ANA STR
SOC
CON EXP
ASR
FlX
_______________________________________________________________________________________________________
Thinking Styles
2sd ANA
Pearson Corr
Sig (2-tailed)
2sd
STR
Pearson Corr
Sig (2-tailed)
2sd
SOC
Pearson Corr
Sig (2-tailed)
2sd
CON
Pearson Corr
Sig (2-tailed)
.845**
.000
.713**
.000
-.484** -.471** -.541** -.280*
.000
.000
.000
.035
.740** .317*
.000
.016
-.420**
.001
.533** .357*
.000
.006
.610**
.000
.768** .394** .469** .303*
.000
.002
.000
.022
Behavioral patterns
2sd
EXP
Pearson Corr
Sig (2-tailed)
-.276* .421** .359** .801** .716** .632**
.037
.001
.006
.000
.000
.000
2sd
ASR
Pearson Corr
Sig (2-tailed)
-.307*
.020
2sd
FLX
Pearson Corr
Sig (2-tailed)
.335*
.011
.674** .397*
.000
.002
.583** .759** .333*
.000
.000
.011
.641** .449** .751**
.000
.000
.000
_______________________________________________________________________________________________________
First survey admin is preceded with “Fir”. The second admin is preceded with “Last”. * Corr significant at the p>=0.05 level (2
–tailed). **. Corr significant at the p>=0.01 level (2-tailed).
ANA=analytical, STR=structural, SOC=social, CON=conceptual; EXP=expressiveness, ASR=assertiveness, FLX=flexibility
87
The overall combined correlation scores of both thinking and behavior were all significant and ranged
from .71 to .86 (averaging .78). Other interesting observations are the negative associations between
Structural thinking and Conceptual thinking (-.48) and the behavior attributes Expressiveness (-.47),
Assertiveness (-.54) and Flexibility (-.28). These indicate that, when the score for Structural thinking is higher,
the scores for the respective thinking and behavioral attributes tend to be lower. We further observe positive
associations between Social thinking and Conceptual thinking (.32) and the behavioral attributes
Expressiveness (.53), Assertiveness (.36) and Flexibility (.61). These indicate that, when the score of Social
thinking is higher, the scores for the respective thinking and behavioral attributes tend to be higher as well.
Conceptual thinking is negatively associated with Structural thinking (-.42) and positively associated with all
behavioral attributes with correlations of .40, .47 and .30 respectively. Concerning the behavioral attributes,
Expressiveness is positively related to Assertiveness (r = .72) and Flexibility (r = .63). Assertiveness is
positively related to Expressiveness (r= .58) and to a small extent to Flexibility (r = 33). Finally, Flexibility is
positively related to Expressiveness (r = .64) and Assertiveness (r = .45). These associations are relatively
similar with the results from what we have found in the construct validity study with a substantially larger
sample size of N = 394.
3.4.4 Cultural and gender differences study
Table 3.13 and 3.14 present the percentile mean scores of the seven attributes and the results from the
independent samples T-tests between Anglo-Germanic/Nordic and Latin-Asian cultures and between males
and females from those respective cultural groups. The mean score for Anglo-Germanic/Nordic group for the
thinking styles ranged between (M= 35.71 – 54.27) for the Latin-Asian group the mean score ranged from (M
= 40.25 - 58.16). The mean score for Anglo-Germanic/Nordic group for the behavioral patterns ranged
between (M= 52.12 – 61.72) for the Latin-Asian group the mean score ranged from (M = 50.73 - 59.23). The
results from the independent T-test show no significant difference for both thinking styles and behavioral
patterns between the Anglo-Germanic/Nordic Group compared to the Latin-Asian group.
88
Table 3.13 Summary of means and T-test reporting Anglo-Germanic/Nordic cultures versus Latin-Asian cultures
(N = 330)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Attributes
N
Mean Std. D Std.
Sig.
Err M.
t
df
(2 tailed)
_______________________________________________________________________________________________________
Thinking styles
ANA (AGN)
ANA (LA)
251
79
51.05
49.18
27.13
28.72
1.7
3.2
.527
328
.599
STR (AGN)
STR (LA)
251
79
35.71
40.25
26.03
29.78
1.6
3.6
-1.30
328
.193
SOC (AGN)
SOC (LA)
251
79
54.27
54.37
27.61
28.36
1.7
3.2
-.029
328
.977
CON (AGN)
CON (LA)
251
79
52.80
58.16
28.20
32.57
1.8
3.7
-1.42
328
.157
EXP (AGN)
EXP (LA)
251
79
61.41
59.23
26.35
25.38
1.7
2.9
.649
328
.517
ASR (AGN)
ASR (LA)
251
79
61.72
57.63
25.45
26.32
1.6
3.0
1.23
328
.218
FLX (AGN)
FLX (LA)
251
79
52.12
50.73
27.00
30.54
1.7
3.4
.386
328
.699
Behavioral patterns
_______________________________________________________________________________________________________
*. Correlation is significant at the p>=.05 level (2-tailed).
ANA=analytical, STR=structural, SOC=social, CON=conceptual; EXP=expressiveness, ASR=assertiveness, FLX=flexibility
The mean score for the male group for the thinking styles ranged between (M= 33.05 – 59.66) for the female
group the mean score ranged from (M = 39.78 - 51.44). The mean score for male group for the behavioral
patterns ranged between (M= 57.68 – 65.18) for the female group the mean score ranged from (M = 47.12 59.60). The results from the independent T-test within the male-female group show, statistically significant
difference in scores for Social thinking (r = .002), Structural thinking (r = .022) and the behavioral patterns
Expressiveness (r = .008) and Flexibility (r = .001).
89
Table 3.14 Summary of means and T-test reporting males versus females (N = 330)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Attributes
N
Mean Std. D Std.
Sig.
Err M.
t
df
(2 tailed)
________
_
_____ _____ _____
_
__
________
Thinking styles
ANA (Ma)
ANA (Fe)
146
184
52.50
49.10
28.73
26.44
2.4
1.9
1.12
328
.264
STR (Ma)
STR (Fe)
146
184
33.05
39.78
24.80
28.33
2.1
2.1
-2.30
325
.022*
SOC (Ma)
SOC (Fe)
146
184
59.66
50.05
28.08
26.81
2.3
2.0
3.17
328
.002*
CON (Ma)
CON (Fe)
146
184
57.42
51.44
29.37
29.12
2.4
2.1
1.85
328
.066
Behavioral patterns
EXP (Ma)
EXP (Fe)
146
184
65.18
57.48
25.13
26.41
2.1
1.9
2.69
328
.008*
ASR (Ma)
ASR (Fe)
146
184
62.18
59.60
24.82
26.36
2.1
1.9
.906
328
.365
FLX (Ma)
146
57.68 27.71 2.3
3.48
328
.001*
FLX (Fe)
184
47.12 27.11 2.0
_______________________________________________________________________________________________________
*. Correlation is significant at the p>=.05 level (2-tailed).
90
3.5 Conclusions and discussion
To answer the sub-research question 3 we have tested and discussed the reliability (precision of the
instrument) and validity (accuracy of the instrument) of the EG instrument to determine its value, for
measuring individual differences between Anglo-Germanic/Nordic explicit cultures and Latin-Asian implicit
cultures. The EG instruments have been reviewed on the basis of a set of requirements derived from the central
research question and was chosen because of the potential fit to operationalize the research frame-work
presented in chapter 2.
The results from the construct validity study showed Social and Conceptual thinking are somewhat related as
are Analytical, Structural and Conceptual thinking. The results also confirmed associations between the three
behavioral attributes. Intercorrelations between the thinking and behavioral scores showed a diverse picture
with low to very low correlation scores between Analytical, Structural and Conceptual Thinking on one hand
and Expressiveness, Assertiveness and Flexibility on the other hand, indicating that these sets of measures are
distinguished from each other. The correlations between Social and Flexibility showed the opposite with a
relatively high positive correlation of .76. Indicating that if the score of Social thinking is higher, the scores for
Flexibility will have the tendency to be high. For face validity, 97% of participants agreed that the survey
questions were obvious and clear in their meaning and that the survey measures what is supposed to measure.
This confirms the face validity of the instrument as well. The test-retest results showed no significant
differences between the two mean scores across time for both the thinking styles and behavioral patterns.
Combined with the strong significant association between the thinking styles and behavioral patterns
percentile scores, these results indicate that the instrument has demonstrated acceptable test-retest reliability
Between the Anglo-Germanic/Nordic group and the Latin-Asian group no statistically significant difference
were observed for both thinking styles and behavioral patterns. These results indicate that within this sample,
Anglo-Germanic/Nordic cultures and Latin-Asian cultures have relatively similar scores, implying that the
instrument is suitable for measuring thinking styles and behavioral patterns in a culturally diverse setting,
indicating cross-cultural validity as well. It should be noted that this was a convenient sample with relative
small representation of the countries per cultural group, specifically in the Latin-Asian group, which makes it
difficult to generalize the findings within the sample of this study to a global population.
91
The over representation in the Nordic-Germanic group and the under representation in the Latin-Asian group
might have played a role in the outcomes. It could however be argued that, if the differences in the mean
scores for one or two of the thinking styles or behavioral patterns was significant, that the EG instrument could
still be used within this thesis. We would still have considered using the instrument, because the instrument
has already been used to compare groups within an educational and organizational context (see section 3.2,
Epperson, 2007; La Prairie, 2007). In addition, despite the limitations of our sample, the statistical outcomes in
regard to the validity and reliability of the instrument are relatively similar with statistical data from a global
sample of 45.000 surveys (see technical report, Williams, 2014). Furthermore, the instrument fits within the
aim of this research to perform the study from the perception of the individual employee because it was
specifically developed to provide a useful framework for understanding and accommodating individual
differences in thinking styles and behavior patterns. To validate our findings from the cultural differences
study, we would however, recommend using substantially larger sample sizes within each national cultural
category when comparing at group level.
When comparing males and females, significant differences in mean scores for Social thinking and the
behavioral patterns Expressiveness and Flexibility were observed. These results indicate that within this
sample, males tend to be more social an structural in their thinking and more expressive and flexible in their
behavior. As mentioned earlier the convenient sampling might have played a role in these differences between
males and females. It might also have been the case that the distribution of males and females between the
different cultural groups has played a role. However, when we look at the distribution of males and females
within and across cultural groups we have noticed no large differences in the sizes of the samples. A larger
sample size with a full distribution of thinking styles and behavioral patterns across males and females would
be recommended to see if this tendency manifests itself again. These outcomes should not have been a surprise
as a similar trend of gender differences was found in a study with the Big Five Inventory (BFI) covering over
55 nations (Costa et al., 2001). The authors found significant differences in 49 of the 55 nations surveyed and
argued that these differences can be explained from how females are expected to behave in individualistic,
egalitarian cultures versus collectivistic, traditional cultures. It could also be argued that the difference found
between males and females relate more to how males and females differ in how they code and process
information than to cultural or environmental influences (Haier, Jung, Yeo, Head and Alkire, 2005). It
might also be that it is not only an issue of cultural or genetic influence but that in reality, the situation is
far more complex. It probably involves a combination of nurture (cultural influence), nature (genetics) and
how individuals prefer to code and process information (see also Poortinga et al 1990).
92
Based on the results of several reliability and validity tests, it can be suggested that the EG instrument
meets the criteria for test-retest reliability, construct and face validity within culturally diverse
organizational setting. The relatively similar mean scores of the cultural groups comparison is an
encouraging signal to further investigate the usefulness of the instrument in a study with lager sample sizes.
In all, this is the first time that independently collected datasets have been analyzed for the purpose of testing
the psychometric qualities of the instrument.
The relatively similar mean scores between the Anglo-Germanic/Nordic group and the Latin-Asian group
is an encouraging signal to further investigate the usefulness of the instrument among larger cross-cultural
samples. It is recommended to include different criteria for reliability and validity in future psychometric
evaluations as well, such as the internal consistency of the sub-dimensions and comparative studies with
different instruments for measuring personal differences cross-culturally. For future research it is also valuable
to investigate the possibility to develop a reliable and validated shortened version of the current 100-item
Emergenetics instrument. A shortened version may serve its possible suitability and ease for different types of
future research purposes.
Overall, based on the results from the statistical studies conducted, we may conclude that the EG psychometric
instrument has demonstrated satisfying reliability and validity qualities and can be used within the context of
the research framework for measuring individual differences between individuals from different national, and
professional cultural groups. The findings also demonstrate that thinking styles and behavioral patterns can be
a valid measure for behavioral intentions as such verifying the first part of the research framework. With this
conclusion we have answered research question 3.
In sum, to operationalize the research framework, we have selected an appropriate instrument that has
demonstrated to accurately and precisely measure personal differences, in individuals within a culturally
diverse environment (McCrae and Costa 1997, Yang et al. 1999, Triandis and Suh, 2001). The instrument
allows efficient operationalization of further empirical studies and is easily (on-line) accessible with
validated translated version of the survey available for individuals with an Anglo-Germanic and Nordic
(explicit cultures) and Latin-Asian cultural (implicit cultures) background (Ulijn and Lincke, 2004). Finally
the rough data, meaning that the scores of each item (100) from the survey of each respondent is available
for use to rank the perceived influence of cultural factors and personal preferences on behavioral intentions
(based upon thinking styles and behavioral patterns) in the following empirical studies presented in chapter
4 and 5.
93
94
Chapter 4*4
Measuring the influence of cultural factors and personal preferences on
behavioral intention: an explorative quantitative study with diverse
countries and professions.
4.1 Introduction
From the literature review in chapter 2, we found that the behaviors of individual employees are
simultaneously and sequentially influenced by the country they are born in (national cultural context), by
the educational system they go through (professional culture), and by the organizational culture of the first
company they start to work for. To study how the behaviors of individual employees are influenced by
cultural factors and personal preferences, we analyzed cultural influence models from a combined eticemic perspective and proposed a research framework. The framework distinguishes between the influence
of cultural factors (based upon national, professional and organizational culture) and personal preferences
on behavioral intention (based upon thinking styles and behavioral patterns). Within the framework,
behavioral intention is viewed as a good predictor of actual behavior as it relates to a person’s own
perception of their thinking styles and behavioral patterns (Ajzen and Fishbein, 2005). We further
concluded that it is important to measure the perception of both thinking styles and behavioral patterns
because these attributes better explain and differentiate the behavioral intentions of individuals (Zhang,
2001). In chapter 3 we verified that behavioral intention is a key concept in the proposed research
framework, it refers to a person’s perception of their thinking styles and behavioral patterns, or more
specific, the intended response of an individual to their surrounding environment.
In chapter 3 we found that irrespective of national cultural background, behavioral intentions can be a
reference to compare the perception of individuals from different national, professional and organizational
cultural backgrounds. We further demonstrated that the Emergenetics instrument is a suitable instrument to
validly and reliably measure both thinking styles and behavioral patterns to compare the behavioral
intention scores between individuals from different national cultural backgrounds.
4
This chapter is based upon a paper by Byron, R.D., and Ulijn, J.M. (2012). Disentangling cultural and personal factors in behavior for the business context: A
pilot study with the Emergenetics instrument, presented at the High Technology Small Firms PhD conference, VU University, Amsterdam, May 24-25th 2012.
95
From the psychometric study, we concluded that professionals from Anglo-Germanic/Nordic cultures and
the Latin-Asian cultures have no significant differences as it relates to their mean scores for behavioral
intention (based upon thinking styles and behavioral patterns). Similar results where also found for males
and females. Furthermore, Anglo-Germanic/Nordic cultures are rather individualistic cultures they tend to
behave rather factual and direct versus Latin-Asian cultures, which are rather collectivistic cultures that
tend to behave rather emotional and indirect. In reference to chapter 2, we have noted that the IDV
(individualistic vs. collectivistic) dimension allows for differentiation between the perception of individuals
that are focused on self and immediate family, compared to individuals that are focused on the norms and
goals of the group. These cultural group differences might therefore affect individual perceptions of
members of these cultural groups.
The above findings make it relevant to not only investigate how the national cultural groups (AngloGermanic/Nordic and the Latin-Asian) differ in their perception on the influence of cultural factors and
personal preferences on behavioral intentions, but to also compare professional working within different
organizational cultures. In this chapter we therefore compare how professionals from AngloGermanic/Nordic and the Latin-Asian cultures with a variety in knowledge, jargon and training might
differ in their perception on the influence of cultural factors and personal preferences on behavioral
intention. This chapter therefore addresses sub-question 4:
4. To what extent do employees in diverse cultural contexts differ in their self- perception on how
cultural factors and personal preferences influence their own behavior?
This study aims to test the research framework by first measuring behavioral intentions and then the
perceived influence of cultural factors and personal preferences on behavioral intentions of respondent
from diverse cultural backgrounds (see figure 4.1).
96
MeasuringCF&PPonBI
MeasuringBI
Cultural Factors (CF)
Thinking styles
National Culture (NC)
Professional Culture (PC)
Behavioral Intentions (BI)
Organizational Culture (OC)
Behavioral patterns
Personal Preferences (PP)
Figure 4.1 Measuring behavioral intentions and the influence of cultural factors and personal preferences on behavioral
intentions
The outline of this chapter is as follows: in section 4.2 we present the self-perception methods used and
how the sampling and data collection was done in this study. Next we give an overview of the respondents’
mean scores for behavioral intentions (based upon thinking styles and behavioral patterns), differentiated
by national cultural group, professional cultural group and gender. In section 4.3 we present and discuss the
results from this explorative quantitative study. At the end of this chapter in section 4.4 conclusions and
discussion are presented.
4.2 Methods used
To answer the sub-research question 4, we studied the differences in self-perception on the influence of
cultural factors and personal preferences on individual employee behavior between two national cultural
groups; Anglo-Germanic/Nordic, individualistic-explicit cultures and Latin-Asian, collectivistic-implicit
cultures (Hofstede et al, 2008) and between three professional cultures, operator, engineering and executive
cultures (Schein, 2010). The approach taken in this study is rather similar to a study conducted by Ulijn,
Nagel and Tan, (2007) who compared the impact of national, corporate and professional cultures on the
innovation of German and Dutch firms.
97
The study is conducted within a group of professionals from different national and professional cultural
backgrounds working in a various organizations. An extended Emergenetics instrument is used to measure
individual behavioral intention and the individual perceived influence of cultural factors and personal
preferences on behavioral intentions (based upon thinking styles and behavioral patterns) scores. This study
investigates to what extent individual employees from different professions perceive to be affected by these
cultural levels, within organizations based in countries with rather individualistic versus rather
collectivistic cultures. This study reflects an emic – self-perception survey tradition similar to the studies
from Schwartz (1992) and Vedina, Fink and Vadi (2006). This study measures individual perceptions on
the influence of cultural factors and personal preferences on individual behavioral intention scores and
compares between Anglo-Germanic/Nordic cultures and Latin-Asian cultural groups.
4.2.1 Sampling and respondents
A stratified sample of 383 working individual was recruited from business, academic and personal
networks. Demographic data (nationality, profession and gender) was also obtained from all respondents
and the data set was divided in 3 subsets; national cultural background; (Anglo-Germanic and Nordic and
Latin-Asian), professional cultural background (operator, engineering and executive cultures) and gender
(males and females). When the demographic information was not provided within the given inclusion
period or if the information was incomplete, respondents were excluded from the study.
The behavioral intention (based upon thinking styles and behavioral patterns) from all individuals in the
sample was available as they had already completed the on-line EG survey (see also chapter 3).
Measures
To measure the perceived influence of cultural factors and personal preferences on behavioral intention the
group of 383 participants received an personal email with an invitation to complete the extended EG survey
(an example of the email is included in Appendix 4). The extension of the EG survey, builds on the
demonstrated satisfying reliability and validity qualities of the EG survey presented in chapter 3. We also
concluded that the survey could be used within this study for measuring individual differences between
different national, and professional cultural groups. An example of the extended EG survey is included in
Appendix 5. The extended EG survey included each participants individual scores/answers to each of the
100 questions of the EG survey (based upon thinking styles and behavioral patterns).
98
The participants also received written instructions to 'force rank' on a scale of 1 – 4 (1 most influence – 4
least influence), the influence of cultural factors and personal preferences on each of the 100 answers they
had given in the EG survey.
For example, one of the questions in the first EG survey was - 'I don't mind pushing to the front of the line'
- if the respondent scored a 6 (Likert scale (1) least like me - (7) most like me); the survey requires the
respondent to evaluate if the score of 6 is related to: having a certain national cultural background (NC),
belonging to a certain professional group (PC), or working in a certain organization (OC), or does it relate
to my personal preference/attitude (PP). The definitions of personal preferences and each cultural level
(national, professional and organizational culture) were included in the email and in the survey as a
reference, no further verbal instructions were given to the participants (for the definitions see chapter 2,
section 2.3.2).
Respondents had to make a (forced) choice which of these factors had the most influence on the respective
score of each of the 100 questions from the EG survey. They were also instructed to rank all 400 items in
the Extended EG survey (EEG). In using a force-ranked scale, we aimed for a unique value for each of the
400 items, which would represent the individual perception that matters most (Krosnick, 1999). However,
there are some drawbacks to consider in regard to forced rankings surveys; participants really have to think
hard to rank their choices, which could result in incomplete an incorrect rankings.
Also, the participants may take longer to answer all the questions of the survey (Munson and McIntyre,
1979). On the other hand forced ranking will allow discriminating between the levels of influence on
behavioral intention (thinking styles and behavioral patterns) of personal preferences and cultural factors
and between the cultural factors separately. Force ranking will also allow establishing priorities of what are
the most influential, and how important the items are relative to one another.
99
4.2.2 Respondents characteristics
Out of 383, 154 responded (40%) to the invitation to complete the extended EG survey, out of which 128
(88%) were eligible for analysis, 26 respondents (20%) were excluded, as their forms were incomplete.
For the distribution of the thinking styles and behavioral patterns combinations of the 128 respondents see
appendix 6. Table 4.1 gives an overview of the total sample, the survey used for the data collections, the
respondents eligible for analysis and the mode of analysis used in this study.
Table 4.1 Overview of samples, surveys used, 128 respondents and mode of analysis
Explorative quantitative study
Sample
Survey used
Respondents Type of analysis
Measure individual perception of influence
N = 383
Ext EG
128
Paired-sample T-test
of CF and PP on BI (based upon thinking
survey
Mann-Whitney U test
styles and behavioral patterns
(400 items)
MANOVA
Convergent/discriminant
correlation analysis
From the 128 respondents demographic data (nationality, profession and gender) was also obtained via the
online questionnaire or via separate email. Participants were excluded from the study if they had not
completed all demographic data or if the data could not be verified. The sample consisted of working
individuals aged 23 years and above at the time of the study. Table 4.2 shows the distribution of the
stratified sample by national cultural cluster, professional cultural group and gender.
Within the national cultural group the respondents from the Netherlands and Italy were the majority of the
Anglo-Germanic and Nordic (AGN) group and the Latin-Asian (LA) group respectively. The respondents
came from 17 different nationalities, the Anglo-Germanic and Nordic and the Latin-Asian cultural group
included 7 and 10 different nationalities respectively. Within the Operator professional cultural group, PhD
students and academics were the majority of respondents (18), closely followed by general management
(17) and ICT and engineers (16) for the Executive and Engineers cultures respectively. A total of 10
different categories of professions were included, 6 within the operator culture group and 2 in the
engineering and executive culture group respectively. Within the gender group males represent the
majority, with a nearly 2/3 – 1/3 split between males and females.
100
Overall the sample included a wide spread of nationalities, a large variety of job categories from
individuals active in multiple organizations. Such a sample is rather suitable for use in this cultural
differences study.
Table 4.2 Sample characteristics of 128 respondents by national culture, professional culture and gender
_______________________________________________________________________________________________________
National Cultural Group
Professional Cultural Group
_______________________________________________________________________________________________________
Number/Percentage
Number/Percentage
Netherlands
51
1. Operator culture (OPR) total:
77 (60%)___
USA
12
PhD students and Academics
18
Britain
10
Marketing & Commercial
17
Germany
7
Project management
14
Ireland
1
Consulting and Training
12
Australia
1
Medical and Healthcare*
9
Finland
1
Other professions**
7
Total AGN
Italy
Singapore
China
India
Taiwan
Hong-Kong
Korea
Malaysia
Philippine’s
Japan
83 (65%)
16
11
7
1
1
1
3
2
1
2
Total LA
Gender:
45 (35%)
Males
Females
78 (61%)
50 (39%)
Total (N)
128
2. Engineers culture (ENG) total:
ICT & Engineering
Accounting and Financial services
16
15
31 (24%)___
3. Executive culture (EXE) total:
General management
HR management
17
3
20 (16%)___
Total Professions
128________
Total (N)
128
* = ( includes medical doctors, Physiotherapist’s, Clinical psychologist and Speech therapist’s)** = ( includes, administrative support functions and lawyers)
101
4.2.3 Applied statistical analysis
The mean ranking scores from the extended EG surveys are analyzed using a paired-sample T-test and a
Wilcoxon Mann-Whitney U test, to evaluate whether the ranks for each of the factors significantly differs
within the different groups. Instead of comparing means of the two groups, as is the case with the T-test,
the Mann-Whitney U test compares medians. The test converts the scores on the independent variable to
ranks across the two groups. As the scores are converted to ranks, the actual distribution of scores does not
matter.
The analysis of the ranking scores is performed at the national cultural group level between AngloGermanic/Nordic and Latin-Asian cultures, at the professional cultural group level between operator,
engineers and executive cultures and lastly at the gender level, between males and females. To gain insight
into possible interactions between the ranking scores between the different groups (national and
professional cultural group and gender) a MANOVA (multivariate analysis of variance) is performed. In
reference to the discussed loose-tight relationships between national, professional and organizational
culture, the mutual interdependencies between the different influencing factors are identified and a paired
sample T-test was run pairing national culture with organizational and professional culture and personal
preferences with organizational and professional culture.
In regards to age, we have only included working individuals from above 23 years of age. We have
however verified that the respondents were working individuals from above 23 years of age and came from
a wide spread of job categories in variety of organizations and industries and assumed a similar variety of
organizational cultures (see also Hall, 1995 and Trompenaars and Woolliams, 2003). The differences
between organizational cultural levels are not considered because of the complication to verify the
organizational culture of the organizations for each of the 128 participants.
102
4.3 Results
An paired sample T-test and a Wilcoxon Mann Whitney U test was conducted to assess the differences in
ranking for each of factors on behavioral intentions within the national cultural group, professional cultural
group and gender group. Table 4.3 shows the descriptive statistics including the total mean ranking scores,
standard deviation and T-test comparing, national cultural group (Anglo-Germanic/Nordic and Latin-Asian
cultures). The mean ranking scores could range from 100 (most influence) to 400 (least influence). Table
4.4 shows group statistics, median ranking score, sum of ranks and the Wilcoxon Mann Whitney U test
statistics for Anglo-Germanic/Nordic and Latin-Asian cultures, for each of the factors – national,
organizational, professional culture and personal preferences.
Table 4.3 Comparison of ranking scores of Cultural Factors and Personal Preferences on Behavioral Intention by
national cultural group: means and T-test reporting, Anglo-Germanic/Nordic versus Latin-Asian cultures (N = 128)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Factors
N
Mean
Std. D
________
_
_____
_____
Std.
Err M.
_____
t
_
df
__
Sig.
(2-tailed)
________
NC
AGN
LA
83
45
301.1
311.1
59.03
46.35
6.5
6.9
-1.06
110
.293
OC
AGN
LA
83
45
266.6
270.0
44.90
45.00
4.9
6.7
-.399
126
.691
PC
AGN
LA
83
45
238.4
247.0
46.60
44.40
5.1
6.6
-1.01
126
.313
PP
AGN
83
194.1 59.46 6.5
.473
126
.637
LA
45
189.4 42.13 6.3
_______________________________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
103
Table 4.4 Comparison of ranking scores of Cultural Factors and Personal Preferences of influence on Behavioral
Intention by national cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test statistics
reporting, Anglo-Germanic/Nordic versus Latin-Asian cultures (N = 128)
______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
National
Organizational
Professional
Personal
Culture
Culture
Culture
Preferences
_________________
____________
____________
____________
Median/ Sum of Ranks Median/Sum of Ranks
Median/ Sum of Ranks Median/ Sum of Ranks
Group (N = 128)
_______________________________________________________________________________________________________
NC Group
_________
AGN (83)
62.85 5216.5
63.31 5255.0
61.61 5114.0
64.57 5359.5
LA (45)
67.54 3039.5
66.69 3001.0
69.82 3142.0
64.37 2896.5
_______________________________________________________________________________________________________
Test Statistics
(NC)
National
Culture
(OC)
Organizational
Culture
(PC)
Professional
Culture
(PP)
Personal
Preferences
______________________________________________________________________________________
Mann-Whitney U
1730.5
1769.0
1628.0
1861.5
Wilcoxon W
5216.5
5255.0
5114.0
2896.5
Z
-.684
-.492
-1.195
-.030
Asymp.Sig.(2-tailed)
.494
.623
.232
.976
_______________________________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
The mean ranking scores for the factors (NC, OC, PC and PP) between the national cultural groups ranged
from M = 194 – 301 for the Anglo-Germanic/Nordic group versus M = 189 – 311 for the Latin-Asian
group. Within this group, NC (301/311) had the highest mean ranking score, followed by OC (266/270),
PC (238/247) and PP (194/189) with the lowest mean ranking score. The mean ranking scores for each
factor shows minimal difference between the two groups. The difference between the lowest and highest
mean ranking score is relatively similar for both national cultural groups. The results from both the T-test
and the U test show no statistical significant differences between each factor mean ranking scores for
respondents from Anglo-Germanic/Nordic and Latin-Asian cultures. These results indicate that irrespective
of national cultural background, personal preferences and professional cultures are perceived to have more
influence on behavioral intentions than organizational and national cultures do.
104
Table 4.5 shows the descriptive statistics including the total mean ranking scores, standard deviation and Ttest comparing, professional cultural group (operator and engineers cultures). Table 4.6 shows group
statistics, median ranking score, sum of ranks and the Wilcoxon Mann Whitney U test statistics for
operator and engineers cultures, for each of the factors – national, organizational, professional culture and
personal preferences.
Table 4.5 Comparison of ranking scores of Cultural Factors and Personal Preferences on Behavioral Intention by
national cultural group: means and T-test reporting, Operator and Engineers cultures (N = 108)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Factors
N
Mean
Std. D
________
_
_____
_____
Std.
Err M.
_____
t
_
df
__
Sig.
(2-tailed)
________
NC
OPR
ENG
77
31
308.4
295.0
52.83
58.66
6.0
10.5
1.16
106
.250
OC
OPR
ENG
77
31
263.5
272.0
44.00
49.87
5.0
9.0
-.874
106
.384
PC
OPR
ENG
77
31
240.1
248.0
45.25
44.50
5.2
8.0
-.825
106
.411
PP
OPR
77
193.5 52.72 6.0
-.587 106
.558
ENG
31
200.3 60.50 10.9
_______________________________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
105
Table 4.6 Comparison of ranking scores of Cultural Factors and Personal Preferences of influence on Behavioral
Intention by professional cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test
statistics reporting, Operator versus Engineers cultures (N = 108)
______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
National
Organizational
Professional
Personal
Culture
Culture
Culture
Preferences
_________________
____________
____________
____________
Median/Sum of Ranks
Median/Sum of Ranks
Median/Sum of Ranks
Median/Sum of Ranks
Group (N = 108)
_______________________________________________________________________________________________________
PC Group
_________
OPR (77)
57.36 4416.5
53.65 4131.0
52.34 4030.5
53.54 4122.5
ENG (31)
47.40 1469.5
56.61 1755.0
59.85 1855.5
56.89 1763.5
_______________________________________________________________________________________________________
Test Statistics
(NC)
National
Culture
(OC)
Organizational
Culture
(PC)
Professional
Culture
(PP)
Personal
Preferences
______________________________________________________________________________________
Mann-Whitney U
Wilcoxon W
Z
Asymp.Sig.(2-tailed)
973.5
1469.5
-1.494
.135
1128.0
4131.0
-.445
.656
1027.5
4030.5
-1.128
.260
1119.5
4122.5
-.503
.615
*. Differences are significant at the p <=.05 level (2-tailed).
The mean ranking scores for the factors (NC, OC, PC and PP) between the professional cultural groups
ranged from M = 193 – 308 and M = 200 – 295 for operator and engineers cultures respectively. Within
this group, NC (308/295) had the highest mean ranking score, followed by OC (263/272), PC (240/248)
and PP (193/200) with the lowest mean ranking score. The results from both the T-test and the U test show
no statistical significant differences between each factor mean ranking scores for respondents from
operator and engineers cultures. These results indicate that professional from operator and engineers
cultures perceive personal preferences and professional cultures to have more influence on their behavioral
intentions than organizational and national cultures do.
106
Table 4.7 shows the descriptive statistics including the total mean ranking scores, standard deviation and Ttest comparing, professional cultural group (operator and executive cultures). Table 4.8 shows group
statistics, median ranking score; sum of ranks and the Wilcoxon Mann Whitney U test statistics for
operator and executive cultures, for each of the factors – national, organizational, professional culture and
personal preferences.
Table 4.7 Comparison of ranking scores of Cultural factors and Personal Preferences on behavioral intention by national
cultural group: means and T-test reporting, Operator and Executive cultures (N = 97)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Factors
N
Mean
Std. D
________
_
_____
_____
Std.
Err M.
_____
t
_
df
__
Sig.
(2-tailed)
________
NC
OPR
EXE
77
20
308.4
305.3
52.83
58.00
6.0
13.0
.232
95
.817
OC
OPR
EXE
77
20
263.5
277.7
44.00
39.19
5.0
8.8
-1.31
95
.193
PC
OPR
EXE
77
20
240.1
236.4
45.25
51.25
5.2
11.5
.314
95
.754
PP
OPR
77
193.5 52.72 6.0
1.33
95
.188
EXE
20
176.4 46.13 10.3
_______________________________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
107
Table 4.8 Comparison of ranking scores of Cultural Factors and Personal Preferences of influence on Behavioral
Intention by professional cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test
statistics reporting, Operator versus Executive cultures (N = 97)
______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
National
Organizational
Professional
Personal
Culture
Culture
Culture
Preferences
_________________
____________
____________
____________
Median/Sum of Ranks
Median/Sum of Ranks
Median/Sum of Ranks
Median/Sum of Ranks
Group (N = 97)
_______________________________________________________________________________________________________
PC Group
_________
OPR (77)
49.63 3821.5
47.08 3625.5
49.74 3830.0
50.88 3918.0
EXE (20)
46.58 931.5
56.38 1127.5
46.15 923.0
41.75 835.0
_______________________________________________________________________________________________________
Test Statistics
(NC)
National
Culture
(OC)
Organizational
Culture
(PC)
Professional
Culture
(PP)
Personal
Preferences
______________________________________________________________________________________
Mann-Whitney U
721.5
622.5
713.0
625.0
Wilcoxon W
931.5
3625.5
923.0
835.0
Z
-.433
-1.316
-.508
-1.293
Asymp.Sig.(2-tailed)
.665
.188
.611
.196
_______________________________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
The mean ranking scores between the professional cultural groups ranged from M = 193 – 308 and M =
176 – 305 for operator and executive cultures respectively. Within this group, NC (308/305) had the
highest mean ranking score, followed by OC (263/277), PC (240/236) and PP (193/176) with the lowest
mean ranking score. Operator and executive cultures have relatively similar mean ranking scores for the
NC, OC and PC factor and a somewhat larger difference for the PP factor. The results from both the T-test
and the U test show no statistical significant differences between each factor mean ranking scores for
respondents from operator cultures and executive cultures. These results indicate that professional from
operator and executive cultures perceive personal preferences and professional cultures to have more
influence on their behavioral intentions than organizational and national cultures do.
108
Table 4.9 shows the descriptive statistics including the total mean ranking scores, standard deviation and Ttest comparing, professional cultural group (engineers and executive cultures). Table 4.10 shows group
statistics, median ranking score, sum of ranks and the Wilcoxon Mann Whitney U test statistics for
engineers and executive cultures, for each of the factors – national, organizational, professional culture and
personal preferences.
Table 4.9 Comparison of ranking scores of Cultural factors and Personal Preferences on behavioral intention by national
cultural group: means and T-test reporting, Engineers and Executive cultures (N = 51)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Factors
N
Mean
Std. D
________
_
_____
_____
Std.
Err M.
_____
t
_
df
__
Sig.
(2-tailed)
________
NC
ENG
EXE
31
20
295.0
305.3
58.66
58.00
10.5
13.0
-.614
49
.542
OC
ENG
EXE
31
20
272.0
277.7
49.87
39.19
9.0
8.8
-.429
49
.670
PC
ENG
EXE
31
20
248.0
236.4
44.50
51.25
8.0
11.5
.854
49
.397
PP
ENG
31
200.3 60.50 10.9
1.51
49
.137
EXE
20
176.4 46.13 10.3
_______________________________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
109
Table 4.10 Comparison of ranking scores of Cultural Factors and Personal Preferences of influence on Behavioral
Intention by professional cultural group: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test
statistics reporting, Engineers versus Executive cultures (N = 51)
______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
National
Organizational
Professional
Personal
Culture
Culture
Culture
Preferences
_________________
____________
____________
____________
Mean & Sum of Ranks Mean & Sum of Ranks Mean & Sum of Ranks Mean & Sum of Ranks
Group (N = 51)
_______________________________________________________________________________________________________
PC Group
_________
ENG (31)
25.27 783.5
25.05 776.5
28.13 872.0
28.23 875.0
EXE (20)
27.13 542.5
27.48 549.5
22.70 454.0
22.55 451.0
_______________________________________________________________________________________________________
Test Statistics
(NC)
National
Culture
(OC)
Organizational
Culture
(PC)
Professional
Culture
(PP)
Personal
Preferences
______________________________________________________________________________________
Mann-Whitney U
Wilcoxon W
Z
Asymp.Sig.(2-tailed)
287.5
783.5
-.434
.664
280.5
776.5
-.569
.569
244.0
454.0
-1.274
.203
241.0
451.0
-1.332
.183
______________________________________________________________________________________
*. Differences are significant at the p <=.05 level (2-tailed).
The mean ranking scores between the professional cultural groups ranged from M = 200 – 295 and M =
176 – 305 for engineers and executive cultures respectively. Within this group, NC (295/305) had the
highest mean ranking score, followed by OC (272/277), PC (248/236) and PP (200/176) with the lowest
mean ranking score. Engineers and executive cultures have relatively similar mean ranking scores for the
NC, OC and PC factor and a somewhat larger difference for the PP factor. Within this group the largest
difference between the lowest and highest mean ranking scores is found in the executive cultures (M = 176
-305). The results from both the T-test and the U test show no statistical significant differences between
each factor mean ranking scores for respondents from engineers and executive cultures. These results
indicate that professional from engineers and executive cultures perceive personal preferences and
professional cultures to have more influence on their behavioral intentions than organizational and national
cultures do.
110
Table 4.11 shows the descriptive statistics including the total mean ranking scores, standard deviation and
T-test comparing, gender (males and females). Table 4.12 shows group statistics, median ranking score,
sum of ranks and the Wilcoxon Mann Whitney U test statistics for males and females, for each of the
factors – national, organizational, professional culture and personal preferences.
Table 4.11 Comparison of ranking scores of Cultural factors and Personal Preferences on behavioral intention by
national cultural group: means and T-test reporting, Males and Females (N = 128)
_______________________________________________________________________________________________________
Group Statistics
T-test for Equality of Means
Factors
N
Mean
Std. D
________
_
_____
_____
Std.
Err M.
_____
t
_
df
__
Sig.
(2-tailed)
________
NC
Male
Female
78
50
294.8
320.0
56.08
49.83
6.4
7.0
-2.58
126
.011
OC
Male
Female
78
50
264.4
273.1
47.37
40.30
5.4
5.7
-1.07
126
.284
PC
Male
Female
78
50
248.0
231.1
45.06
45.60
5.1
6.4
-2.06
126
.041
PP
Male
Female
78
50
201.9
177.7
58.19
42.87
6.6
6.1
2.532
126
.013
_______________________________________________________________________________________________________
*. Differences are significant at the p<=.05 level (2-tailed).
111
Table 4.12 Comparison of ranking scores of Cultural Factors and Personal Preferences of influence on Behavioral
Intention by gender: median ranking score, sum of ranks and Wilcoxon Mann Whitney U test statistics reporting Males
versus Females (N = 128)
______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
National
Organizational
Professional
Personal
Culture
Culture
Culture
Preferences
_________________
____________
____________
____________
Median/Sum of Ranks
Median/Sum of Ranks
Median/Sum of Ranks
Median/Sum of Ranks
Group (N = 128)
_______________________________________________________________________________________________________
Gender
________
Male (78)
58.46 4559.5
60.70 4734.5
70.78 5520.5
70.59 5506.0
Female (50)
73.93 3696.5
70.43 3521.5
54.71 2735.5
55.00 2750.0
_______________________________________________________________________________________________________
Test Statistics
(NC)
National
Culture
(OC)
Organizational
Culture
(PC)
Professional
Culture
(PP)
Personal
Preferences
______________________________________________________________________________________
Mann-Whitney U
Wilcoxon W
Z
Asymp.Sig(2-tailed)
1478.5
4559.5
-2.303
.021
1653.5
4734.5
-1.448
.148
1460.5
2735.5
-2.391
.017
1475.0
2750.0
-2.320
.020
*. Differences are significant at the p <=.05 level (2-tailed).
The mean ranking scores in the gender group ranged from M = 201 – 294 and M = 178 – 320 for males and
females respectively. Within this group, NC (294/320) had the highest mean ranking score, followed by
OC (264/273), PC (248/231) and PP (201/178) with the lowest mean ranking score. The T-test further
shows that males and females have statistically significant different scores for the NC (0.11), PC (0.41) and
PP (0.13) factor. The U test shows similar statistical significant differences for the mean ranking scores for
the NC (0.21), PC (.017) and PP (.020) factor between males and females. These results indicate that male
and female professionals perceive personal preferences and professional cultures to have more influence on
their behavioral intentions than organizational and national cultures do. The results further indicate that
female professionals might perceive more distinct differences in the influence of the factors NC, PC and PP
on their behavioral intentions than their male colleagues do.
112
Table 4.13 shows an overall group statistics and the mean ranking score and standard deviation by –
national cultural group (Anglo-Germanic/Nordic and Latin-Asian), professional cultural group (operator,
engineering and executive) – gender (males and females) and the mean overall mean ranking score for the
total sample (N = 128).
Table 4.13 Comparison of ranking scores of Cultural factors of influence on behavioral intention by national and
professional cultural group and gender: Means, SDs (N = 128)
______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
National
Organizational Professional
Personal
Culture
Culture
Culture
Preferences
____________ ____________ ____________ ____________
Mean s.d.
Mean s.d.
Mean s.d.
Mean s.d.
Group (N = 128)
_______________________________________________________________________________________________________
National Cultural Group
__________________
AGN (83)
301.1 59.0
266.6 44.9
238.4 46.6
194.1 59.5
LA (45)
311.1 46.4
270.0 45.0
247.5 44.4
189.4 42.1
Professional Cultural Group
______________
OPR (77)
308.4
ENG (31)
295.0
EXE (20)
305.3
52.8
58.7
58.0
263.5
272.0
277.7
44.0
49.9
39.2
240.1
248.0
236.4
45.2
44.5
51.2
193.4
200.3
176.4
52.7
60.5
46.1
Gender
________
Male (78)
294.8 56.1
264.4 47.4
248.0 45.1
201.9 58.2
Female (50)
320.3 49.8
267.8 44.8
241.4 45.8
192.5 53.9
_______________________________________________________________________________________________________
Overall (128)
304.6 55.0
267.8 44.8
241.4 45.8
192.5 53.9
The overall mean ranking scores for the total sample ranged from (M = 192 - 305). NC (305) had the
highest overall mean ranking score, followed by OC (268), PC (241) and PP (193) with the lowest overall
mean ranking score. Overall the results show that within this sample (N = 128), of male and female
respondents from different national and professional cultural background from a variety of organizations,
that personal preferences is perceived to have the most influence on behavioral intentions, followed by
professional, organizational and national culture.
113
Table 4.14 shows the results from the analysis of the variances of the total mean ranking scores and
multiple comparisons, between the national cultural group (Anglo-Germanic/Nordic and Latin-Asian
cultures), professional cultural group (engineering, operator and executive cultures) and the gender group
(males and females).
Table 4.14 Comparison of ranking scores of Cultural Factors of influence on Behavioral Intention comparing national
and professional cultural group and gender: multivariate test Wilks’ Lambda reporting multiple group comparisons
(N = 128)
______________________________________________________________________________________
Group (N = 128)
Value F
Hypothesis df
Error df
Sig.
_______________________________________________________________________________________________________
Gender
versus
NC Group
.963
1.092 4.0
113
.364
Male (78)
AGN (83)
Female (50)
LA (45)
Gender
Male (78)
Female (50)
versus
NC Group
AGN (83)
LA (45)
versus
PC Group
OPR (77)
ENG (31)
EXE (20)
.877
1.915
8.0
226
.059
PC Group
.910
1.361 8.0
226
.215
OPR (77)
ENG (31)
EXE (20)
_______________________________________________________________________________________________________
*. Differences are significant at the p>=.05 level.
A one-way between group multivariate analysis of variance was performed to provide more insight into the
differences in mean ranking scores for each of the factors (NC, OC, PC and PP), between, the gender group
versus the national and the professional cultural group respectively. A similar analysis is performed
between the national and the professional cultural group. Preliminary assumption testing was conducted to
check for normality, linearity, univariate and multivariate outliers, homogeneity of variance-covariance
matrices, and multicollinearity, with no serious violations noted. The results from the Wilks Lambda test
shows no statistically significant difference between the mean ranking scores for the gender group versus
the national and professional cultural group and between the national and professional cultural groups. The
results from this analysis support the findings from the T-test and the U test that personal preferences is
perceived to have the most influence on behavioral intentions, followed by professional, organizational and
national culture.
114
To identify mutual interdependencies between the different factors (NC, OC, PC and PP) a paired sample
T-test was run pairing national culture with organizational and professional culture and personal
preferences with national, professional and organizational culture. Table 4.15 shows the paired ranking
scores and the respective correlations.
Table 4.15 Four factors of influence on behavioral intention: Paired ranking scores
Paired ranking scores
_______________________________________________________________________________________________________
Factors of Influence
(NC)
(OC)
(PC)
(PP)
N=116
_______________________________________________________________________________________________________
NC
Correlation
1
.324**
-.353**
-.558**
Sig (2 tailed)
.000
.000
.000
OC
Correlation
Sig (2 tailed)
.324**
.000
PC
Correlation
Sig (2 tailed)
-.353**
.000
PP
Correlation
Sig (2 tailed)
-.558**
.000
1
-.434**
.000
1
-.434**
.000
1
-
_______________________________________________________________________________________________________
** Correlation is significant at the 0.01level (2-tailed)
The results show a positive association between national and professional culture (.324, p < .000)
indicating that if the mean ranking scores for national culture were higher, professional culture would have
the tendency to be high. National culture shows a negative association with professional culture (-.353, P
< .000) and personal preferences (-.558, p < .000), indicating that if the mean ranking scores for national
culture were lower, professional culture and personal preferences would have the tendency to be low. Both
national culture and organizational culture are negatively associated with personal preferences (-.558, p
< .000, -.434 p < .000) respectively). These results indicate that when the mean ranking scores for national
culture or organizational cultures are lower, personal preferences would have the tendency to be high and
vice versa.
115
4.4 Conclusions and discussion
In this chapter a part of the research framework proposed in chapter 2 was tested within an explorative
quantitative study design and included male and female respondents from Anglo-Germanic/Nordic and
Latin-Asian cultural groups, from different professions (operators, engineers and executives) and from
different organizations. The aim of this study was to answer research question 4, to what extent do
employees in diverse cultural contexts differ in their self-perception on the influence of cultural factors and
personal preferences on their own behavior? This study was done in the emic research tradition, using a
self-perception survey with open-ended questions, which is rather similar to a cultural differences study
conducted by Vedina et al., (2006). 128 respondents were asked to assess as to how they perceive their
behavioral intention to be influenced by cultural factors (NC, PC and OC) and personal preferences.
All respondents were working individuals from above 23 years of age and came from a wide spread of job
categories in variety of organizations and industries.
The data was analyzed using a paired-sample T-test and a Wilcoxon Mann-Whitney U test, to evaluate
whether the ranks for each of the factors significantly differs within each of the groups. To gain insight into
possible interactions between the ranking scores between the different groups (national and professional
cultural group and gender) a MANOVA (multivariate analysis of variance) was performed. To look for
mutual interdependencies between the factors, a paired sample T-test was run pairing national culture with
organizational and professional culture and personal preferences with organizational and professional
culture.
The results show no significant differences in the mean ranking scores between the Anglo-Germanic and
Nordic cultural group and Latin-Asian cultural. This was a bit of a surprise as it was expected that
collectivistic-implicit-cultures (Latin-Asian cultures) would rank the influence of the culture (group
orientation) above the influence of attitude/personal preferences. It might be that the 16 Italian respondents
included in the Latin-Asian group (45) have affected this outcome. However when we looked at only the
Asian group a similar trend was found.
Furthermore findings show similar mean ranking scores with no significant differences for respondents
from operator, engineers and executive professional cultures. This was expected as the literature already
indicated that professionals in general feel more connected to their own code of conduct than to the
organizational culture of the company they work for.
116
Similar to the findings from the national and professional cultural groups, male and female professionals
perceive personal preferences and professional cultures to have more influence on their behavioral
intentions than organizational and national cultures do. However, in comparing males and females mean
ranking scores, we found statistically significant differences for the NC (0.11 versus 0.21), PC (0.41 versus
0.17) and PP (0.13 versus 0.20) factor (T-test and U test, respectively). These results might indicate that
females perceive more distinct difference in the influence of the factors NC, PC and PP on their behavioral
intentions than their male colleagues do. Further research would be recommended to better understand this
finding.
The hierarchy of the cultural levels and their respective sequence of influence (NC, OC and PC) on
individual behavior intention are rather in line with Erez and Gati’s onion model (2004). These differences
of ranking of influence between the different levels of culture could also have an impact on individual and
group interactions and relationships and ultimately on the organization’s values and practices as well
(Martin and Siehl, 1992; Triandis and Suh; 2002, Karahanna et al., 2006). The positive association we
found between national and professional culture can also be related to the interconnectivity between the
different levels of culture suggested by Erez and Gati’s (2004) onion model (see also chapter 2 section
2.2.1, Figure 2.5).
These findings also align with the positive association we found between professional culture and personal
preferences and our findings that employees tend to feel more loyal to their profession than to their national
culture (Wever, 1990). These findings further suggest that the educational system and the professional code
of conduct might have more influence on individual employee behavior than the culture in an organization
(also see Hofstede’s cultural influence model, 2001). The negative associations between national and
organizational culture and personal preferences indicate that, how loose or tight inter-linkages between
national and organizational culture are, might affect how national and organizational culture are negatively
associated with personal preferences (see also Eppink et al., 2010). However, as we have found no
significant differences in mean ranking scores between Anglo-Germanic/Nordic cultural group (rather
loose NC – OC) and the Latin-Asian cultural group (rather tight NC – OC) this association cannot be
confirmed. When we compared the mean ranking scores between the different groups (gender, national and
professional cultural group) no statistically significant difference was found between the gender group
versus the national and professional cultural group and between the national versus the professional
cultural group.
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In conclusion, the mean ranking scores for personal preferences are the lowest, indicating that personal
preferences have the most influence on behavioral intentions, followed by the influence scores of
professional, organizational and national culture. We can therefore conclude that, in general, individual
employee behavior as perceived by employees themselves (from Anglo-Germanic/Nordic and Latin-Asian
cultural background), to be mostly driven first by a person’s attitude, than by his/her professional code of
conduct, followed by the organizations values and practices and finally by the national culture were the
company is based. With this conclusion we have answered research question 4. To what extent do
employees in diverse cultural contexts differ in their self- perception on how cultural factors and
personal preferences influence their own behavior?
What are the practical implications from the findings?
The findings from this study could have implications how new employees and managers are selected,
educated and developed in multinational organizations (Tayeb, 1997; Sirmon and Lane, 2004). It could
imply that internal company training session should not only focus on processes, procedures and skills but
also on thinking styles, behavioral patterns and professional modes operandi, which could positively affect
communication across cultural boundaries. Because a focus on changes in a person’s attitude and the
educational background and training of that person could lead to better management of inter-personal
disagreements with positive effects on team-performance and organizational efficiency (Sirmon and Lane
2004). By focusing on the perceptions of individual employee or manager’s, higher levels of cohesiveness,
and a higher level of satisfaction within the team can be achieved.
In sum a check for professional understanding and mutual understanding of individual thinking styles and
behavioral patterns could reduce stereotyping and misunderstandings among individual employees and
between managers and employees.
Within the context of cross-border joint ventures, mergers and acquisitions, our findings suggest that when
Anglo-Germanic/Nordic and Latin-Asian companies are engaged in these cross-border or cross-cultural
cooperation’s that the personal preferences and the perceptions of the managers involved in the integration
of the two companies should be considered as a key element of a successful cooperation between the
companies. It could also imply that the integration of functional groups or the professional modus operandi
should be preferred focus of attention in order to get faster alignment of the teams and departments and
ultimately the organizational cultures of both companies.
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In sum the knowledge gained from this study could help multinational companies to understand why
employees and managers from different functions and different national cultural backgrounds behave the
way they do. It could help managers of culturally diverse teams to have the agility to respond emphatically
and effectively to practices and values that differ from their own cultural expectations and personal
practices (Javidan and House, 2001). Consequently, senior managers most likely will first check for
understanding at a personal level in order to understand and differentiate what drives employee behavior
more, their attitude or their professional modus operandi.
What are the theoretical implications of our findings?
We tested the part of the framework (see figure 4.1) that aimed to study through the eyes of the individual
employee the individual perceptions on behavioral intentions and how these individual differences in
perceptions have been influenced by cultural factors and personal preferences. The results show that this
study approach using self-perception surveys has provided valuable insights how the various influences
factors might affect individual behavioral intentions and allowed comparison and analysis of these
perceptions at a national and professional cultural group level. The results also demonstrated that the
proposed research framework has not only theoretically disentangled the two influencing factors but that it
can be a helpful construct in providing insights into the mutual relationship between cultural levels of
influence, the influence of personal preferences and how these factors might influence behavioral
intentions within different national, professional and variety of organizational cultural contexts.
The above findings are based upon a rather small sample size of 128 respondents. This could imply that for
future research a larger sample size would be recommended to verify the ranking similarities between the
different cultural groups. The results from this study should be viewed within the limitations of the emic
research approach using self-perception survey, which may have led to favorable impressions of own
behavior. This could imply a more qualitative research approach comparing day-to-day employees
behavior with self-perceptions on own behavior. This research approach could deliver valuable insights on
how individual employees from different cultural background perceive each other’s behavior, which can
result in formulating recommendations for the managerial practice how to prevent misunderstandings
within a culturally diverse workforce. The next chapter 5 will explore this approach.
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Chapter 5*5
Self-perception on behavioral intentions versus observations during
meetings: a comparative study among clinical project managers from
Anglo-Saxon and Asian cultural background
5.1. Introduction
To answer the central research question we analyzed cultural influence models from a combined etic-emic
perspective and proposed a research framework (chapter 2, se also figure 2.7). The research framework
included the influencing factors; cultural factors (based upon national, professional and organizational
culture) and personal preferences and the influenced factor behavioral intention (based upon thinking styles
and behavioral patterns). Within the framework, behavioral intention is viewed as the best predictors of
actual behavior as it relates to a person’s own perception of their thinking styles and behavioral patterns.
The framework is based on the combined etic-emic research approach that allows both a cultural grouplevel analysis and an individual-level analysis. At group level, we have compared between country clusters,
and differentiated between Anglo-Germanic/Nordic and Latin-Asian cultures. We further differentiated at a
national cultural level between individualistic and collectivistic, and between low context-explicit and high
context-implicit cultures. At the professional cultural level we differentiated between operator, engineering
and executive cultures and at the organizational level between, incubator, family, Eiffel Tower and guided
missile cultures. Finally, we differentiated between the loose and tight relationship between the different
cultural levels national and organizational culture and with professional culture as a separate level of
cultural influence.
The findings from the literature review (etic-emic) from chapter 2 indicated that multinational
organizations with many locations and affiliated offices might have various organizational cultures
(Trompenaars and Woolliams, 2003), with professional sub-cultures (Schein, 2010) that are connected and
intertwined (Erez and Gati, 2004).
5
This chapter is based on a paper by Byron, R.D., and Ulijn, J.M. (2016). The influence of cultural factors & personal preferences on individual employee
Behavior: Anglo-Germanic-Nordic and Latin-Oriental cultures compared, presented at the 12th ABC conference of Europe, Africa and Middle East Region
University of Cape Town, South Africa 6-8 January 2016.
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Because of this complexity of overlapping cultures and sub-cultures within an organization, only members
of the organization with sufficient experience will be able to understand this deepest level (interpersonal
relationships) of organizational and professional culture. This cultural and personal complexity makes it
challenging to do empirical work on this subject, where surveys and casual interviews with employees and
managers might not completely reveal the underlying inter-personal motives and behavior of employees
and managers (Yin, 2009; Silverman, 2011). That is why many empirical culture studies have been
predominantly etic and introspective (Ulijn et al., 2009).
In chapter 4, we took a different rather emic research approach to study the extent to which employees in
diverse cultural contexts differ in their (self) perception on the influence of cultural factors and personal
preferences on their own behavior. This explorative quantitative study looked at culture from within
through a personal lens, taking into consideration the influence of the person and his/her culture on
organizational behavior while comparing self-perceptions at group level. A self-perception survey was
used to measure the perceived influence of cultural factors and personal preferences on behavioral intention
from professionals with an Anglo-Germanic/Nordic versus a Latin-Asian cultural background and from a
variety of organizations. The results from this explorative quantitative study indicated that, in general
individual employee behavior will be mostly driven first by a person’s attitude and then by his/her
professional code of conduct followed by the organizations values and practices and the national culture
where the company is based. No major differences in the mean influence scores were found between the
respondents from Anglo-Germanic/Nordic cultures and Latin-Asian cultures and between respondents from
operator, engineering and executive professional cultures and for males and females. It should however be
noted that these results are based upon a rather small sample size of 128 respondents and that the data
acquired via self-perception surveys might have lead to favorable impressions of own behavior.
It is therefore relevant to use a more in-depth qualitative and quantitative research approach to identify and
understand the influence of both cultural factors and personal preferences on individual behavior in a real
life case study setting. This chapter presents a single biopharmaceutical case study of clinical project
managers working for the same organization and located in different countries in Asia and Australia and
New Zealand. The clinical project manager’s main task is to manage and monitor multiple countries
clinical trial project within Asia-Pacific and Australia for external (global) biopharmaceutical companies.
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This study is interested in the individual’s perception, to understand culture from both the insiders and
outsider’s perspective; how people see things (self-perception) and how they actually do things
(observations). This study therefore aims to provide an explorative and descriptive overview of the
observed differences and similarities between how the clinical project managers perceived their own
behavior and how they actually behaved during weekly team-meetings, communicating with colleagues
and superiors. This chapter therefore addresses sub-question 5.
5. To what extent do employees in a specific cultural context differ in their self-perception on how
cultural factors and personal preferences influence their own behavior compared to their actual
observed behavior?
This study aims to test the research framework by measuring behavioral intensions and by then comparing
the behavioral intentions scores with tallied observations of actual behaviors of respondent from diverse
cultural backgrounds (please see Figure 5.1).
MeasuringBI
ComparingBIwith.IEB
Thinking styles
Individual Employee
Behavior (IEB)
Behavioral Intentions (BI)
Behavioral patterns
Figure 5.1 Measuring behavioral intentions, compared with tallied observed actual behaviors
The outline of this chapter is as follows, section 5.2 presents the methods used and the quantitative and
qualitative data collection process performed within this case study. This section also explains the selection
process to identify the selected company for this case study and gives a brief anonymous description of the
company’s major activities. The role of the participants in the case study are explained, starting with an
overview of the role and position of the clinical project managers including the reporting lines.
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The role of the researcher as an observer is also addressed in order to provide clarity on the relationship
between the researcher and company (if any) and to explain the process and setting in which these
observations took place. Section 5.3 gives an overview of the characteristics of the sample. Section 5.4
presents the results from the observation sessions II, II and III. Section 5.5 provides the conclusion and
discussion of this chapter
5.2 Methods used
This section presents the methods used for the data collection of this single in-depth biopharmaceutical
case study. A single case study design is used because it makes it possible to look for an alternative set of
explanations that are complementary to the findings of the quantitative cultural groups comparison from
chapter 4, which may lead to outcomes that have more practical relevance (Yin, 2009). This specific
biopharmaceutical case includes a team of professionals (clinical project managers) with the same task at
hand (single professional culture) operating within the same team from a large Multinational organization
assuming a single organizational cultural context. This research approach is in line with Hall's assumption
(1995) that by keeping the organizational culture stable, the results of self-perception and mutualperception can be compared between groups (see also Eppink et al., 2010). The embedded character makes
a multi-unit of analysis possible in different locations (affiliated offices) and countries (multiple national
cultures), which offers significant opportunities for extensive analysis and enhancing the insights into the
single case (Yin, 2009). This case study reflects a rather etic –emic, surveys and observations tradition
similar to the study from Ulijn and St Amant (2000) which investigated how Chinese, Dutch, German,
French and Italian students of similar educational backgrounds observe behavior in the same videotaped
Dutch–Chinese negotiation.
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Measures
This case study reports on the measuring of the behavioral intentions and actual behavior of individual
clinical project managers. All 23 participants first completed the on-line Emergenetics survey (validated in
the psychometric study from chapter 3 and used in the explorative quantitative study in chapter 4), which
measures behavioral intentions (based upon thinking styles and behavioral patterns). The data was
collected via email with a link to the online EG survey of 100 questions, and instructions how to access and
complete the survey (see Appendix 7, for the distribution of the behavioral intentions scores; thinking style
and behavioral patterns of all 23 respondents). Respondents were given 4 weeks to complete the on-line
EG survey.
Qualitatively data was collected through observations, by tallying the respondent’s actual behavior and
comparing the results with their respective scores from the self-perception EG survey on the behavioral
patterns; expressiveness, assertiveness and flexibility. The data is analyzed at an individual level; major
individual differences within each of the three behavioral patterns are described and discussed. Observed
tallied behavior that is out of the percentile score and confirmed with the respective clinical project
manager is qualified as a major difference. The observations took place during two weekly update
meetings. Each meeting had a standard agenda that consisting of achieved milestones, (potential) budget,
resources or deadline issues, and there is time to discuss solutions and options for next steps. The clinical
trial program director consolidated the status of all the clinical trial projects in the Asia-Pacific region and
reported the consolidated outcomes further up the hierarchy and to the global or regional clients (see
appendix 8 for further details of the meeting agenda).
The observations were focused on two individuals, the presenter clinical project manager (CPM) and the
team-leader (CPM Director) during any period of 30 to 40 minutes. A 10-minute window between
presentations allowed to prepare for the next session and to ask the director for additional clarification from
the previous session if required. In order to prepare for the meeting the researcher was given enough time
(3 weeks in advance) and received the following information: meeting agenda, topics/project covered by
country, the names of the CPMs by project and the country or the affiliated office where they were based.
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With the above in mind a researcher assistance first anonymized the results from the EG survey of the 23
clinical project managers by using an individual code that ranged from P1- P23 representing each of the
individual participants to the update meeting. Next a coded behavioral score card was prepared for each
clinical project manager (see also appendices 9, 10 and 11) to tally their observed behaviors during each
the three respective update meetings. The scores from the EG survey for each participant included a variety
of number combinations ranging from 1-3 for expressiveness, assertiveness and flexibility respectively. For
example a score of 1.2.1 represented a behavior that tends to be rather quiet (1), accepting or competitive
(2) depending on the situation and focused (1). Below is an overview of each of the behavioral patterns that
were included in the individual behavioral score-card (see also chapter 3, section 3.2, table 3.2).
Expressiveness - behaves rather: quiet - reserved/outgoing - gregarious
Assertiveness - behaves rather: peacekeeper- accepting/competitive - driven
Flexibility - behaves rather: focused - firm/accommodating - easy-going
During each of the update meetings the researcher tallied if the observed behavior of the clinical project
manager was within or out of the range of their intended behavior scores on the three behavioral patterns.
Three team meetings were observed; two on site (at the regional HQ of the company) and one via
teleconference for a total of 11.5 hours. The observations were only targeted towards the respondents (total
of 23) who completed the self-perception EG survey. We aimed to get insights into how clinical project
managers actually behave during each of the update meetings. The observations during these update
meetings, can be seen as snapshots of what is going on within the daily practice of the clinical project
managers at the certain time in a certain place (Silverman, 2011). As the company did not allow to either
video or audio tape the observations, the researcher had to rely on meeting notes based on what he hears an
sees during the meeting, which might lead to collecting relatively unreliable field-notes (Silverman, 2011).
To mitigate the risk of researcher bias, all individual behavior self-perception scores (EG survey) were
checked and verified by the researcher with each individual participant via face-to-face individual
teleconferences. The participant was asked if the results from the EG survey reflect how he/she perceives
his/her behavior. All participants agreed with their self-perception scores on expressiveness, assertiveness
and flexibility, to be used to tally their behaviors during the update meetings. To mitigate the risk of
collecting unreliable data, after the three observations the researcher checked and verified his observations
notes with each clinical project manager individually via a face-face teleconference. Clinical project
managers were asked if the observed behavior was in line with how they perceive themselves to behave
when they meet with colleagues, superiors and clients.
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Data collection
Table 5.1 presents an overview of the type of quantitative and qualitative data collection methods used in
this study, the location of the data collection, the sequence and timing of the data collection and the number
of clinical project managers that completed the EG survey and participated in the three observations.
Please note that the project director led all 3 session and 2 senior project managers were present at 2
sessions, which explains the difference between the 23 clinical project managers and the total of 28
participants in the three observation sessions.
Table 5.1 Overview of quantitative and qualitative data collection methods used in this study
Steps of collection/Type of data
Collected at or via
Period of
Number of
collection
participants
01 & 02/015
19 from Oriental
Quantitative, self-perception EG online
Individual email with a link to
survey to identify behavioral intentions
the online EG survey and
cultural background
(based upon thinking styles and behavioral
instructions how to complete the
4 from Anglo-Saxon
patterns). Objective, use the results for
survey. Survey timing 25-30
background
the coded behavioral score card:
minutes
expressiveness, assertiveness and
flexibility
Qualitative, three team- observations of
On location/ teleconference
Mid-February &
Observation session I
behavioral patterns of participants:
clinical trial weekly update
mid-March 2015
N = 6 (teleconference)
expressiveness, assertiveness and
clinical project managers
Observation session II
flexibility. Individual observation were
meetings with 8 affiliated
N = 9 (on site)
checked and confirmed (via face-to-face
offices. Meeting timing 30 – 45
Observation session III
teleconference) with each individual
min. Total observation time: 11
N = 14 (on site)
participant. (Observation scorecard, see
hours 30 min.
Appendix 11, 12 and 13)
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5.2.1 Sampling and procedures
Company selection
This sub-section focuses on the selection process of the company for this biopharmaceutical case study, the
profile of the selected company and explains the role of the clinical project managers and the researcher. A
total of ten companies within the biopharmaceutical and healthcare industry were pre-selected based on a
set of criteria that suited the objectives of this study and their ability to answer the research questions. The
availability of a network of contacts in the biopharmaceutical and healthcare industry was the major reason
for selecting this industry. The pre-selected companies had to fulfill the following requirements to be
considered a candidate for this case study:
1. Multinational company with its headquarters (HQ) in the United States (individualistic, explicit
culture - loose NC - OC) and a regional operational HQ in Asia (collectivistic, implicit culture-tight
NC - OC).
2. The team of professionals (single professional culture, preferably within an operational clinical
research or project management setting, referred to as a operator culture) should come from
different cultural backgrounds (multiple national cultures, preferably within the Asia-Pacific
region) working with colleagues with different nationalities at different geographical locations.
3. The researcher should have access as an observer/interviewer to a team of preferably project
managers or product managers that works from a regional HQ with other affiliates or geographical
locations of the same company.
Within the context of answering sub-question 5, we were looking for one company (assuming one single
organizational culture) that operates within multiple national cultural contexts, and a team of professionals
(assuming a single professional culture) within this company that operates/communicates with multiple
national cultures in different locations (regional function). We further looked for companies that were
preferably headquartered in Anglo-Germanic/Nordic cultures (individualistic-explicit culture) assuming a
loose NC - OC connection and an operational or project team of professionals (task-oriented), preferably in
an Oriental cultural context (collectivistic, implicit culture) assuming a tight NC-OC environment.
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We expected that the contrast between one single organizational culture within an explicit cultural context
and one single professional culture within an implicit cultural context combined with multiple national
culture interaction would give us more insight in the connection between organizational culture and
professional culture and personal preferences in the behavioral influence of working individuals.
The following process was followed to select the company for the biopharmaceutical case study project:
Phase 1. All pre-selected companies, ten in total, with their HQ in the United States were sent an email and
received a follow-up call from the researcher to check their interest in the case study project. If the
company expressed an interest in the PhD case study project, a PowerPoint presentation with the
objectives, requirements, timelines, processes, procedures and potential benefits for the company, was
emailed to the contact person. Based on this presentation a teleconference was arranged to further explain
the objectives, requirements, timelines and deliverables of the project.
Phase 2 A mutual non-disclosure agreement was signed between the company and the researchers in order
to be able to exchange more details and a follow-up face-to-face meeting was planned to further discuss the
case study project and the practical implications for the team that would participate in the project.
Phase 3 A joined proposal was formulated by the company and the researcher, and submitted for approval
by top-management and the legal department at the company’s headquarters in the United States. After
final approval a project agreement was signed to ensure confidentiality of all participants, the right of the
company to have access to the outcomes of the case study and the rights for the researcher to be able to
publish the data and results anonymously.
A total of four companies were initially interested, two allowed us to present our case study research
proposal and ultimately one was willing to enter into an agreement to support the research project. The
company selection process took about two years to complete, from the initial contact via email to the
signing of an agreement. The case study project took four months, starting with the onsite observations on
February 13th, 2015 and the case study ended with the last mutual-perception survey received May 21st ,
2015.
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Company profile
The selected company operates on a global scale and is a typical clinical services provider to the
biopharmaceutical and healthcare industry. The company's global HQ is based in the US and they provide a
fully integrated program of biopharmaceutical and life sciences solutions based on their extensive
therapeutic and scientific expertise. The services are provided to large, medium size biopharmaceutical and
medical devices companies and smaller biotechnology companies.
Their services fall in three major categories:
1. Product development services that enable biopharmaceutical R&D and medical device companies,
government and non-government organizations, and generic and bio-similar customers to outsource
clinical development, from first-in-human studies to post-launch monitoring.
2. Clinical solutions and services that include project management and clinical monitoring functions
for conducting multi-site trials (generally Phase II-IV), collectively known as 'core clinical'.
3. Strategy and management consulting services that are based on life science expertise and advanced
analytics, as well as regulatory and compliance consulting services.
The company has more than 30,000 employees working in approximately100 countries, and they have been
engaged in developing or commercializing all of the top-100, best-selling drugs on the market in 2013.
At a global level the company describes itself as having a matrix organizational structure with operational
divisions supported by staff divisions with a clear divide of roles and responsibilities. This characterization
would fit within an Eiffel Tower organizational culture. The above information was collected from the
company's global website. It is a summarized description that was verified with the leadership team at the
company's regional Asian HQ team consisting of the Vice President clinical research project, the regional
general managers and two senior clinical project directors. The regional HQ team confirms the matrix
structure but describe the regional company culture to be more informal, loyal to their profession and
passionate about delivering the highest quality and value for their global client. This characterization leans
more towards a Guided Missile organizational culture. We will be using this organizational
characterization as a reference within this explorative case study as it is inline with the onsite (at the HQ of
the company) observations of the researcher.
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In this study we will be focusing on the clinical solutions services division of the company with its regional
HQ in Asia. They provide clinical research services in Asia-Pacific and Australia/New Zealand via contract
research alliances within the biopharmaceutical industry (De Rond, 2005). Our key area of study is on the
team of project managers that manage and monitor clinical trials on behalf of the company's clients.
We have chosen this team for the following reasons:
-
It is a team with similar roles and tasks (assuming one single professional culture within a single
organizational culture)
-
Its team members come from diverse cultural backgrounds and are located in a variety of affiliated
offices (assuming multiple national cultures)
-
With all team members, communicating and interacting with colleagues from the regional HQ in
Asia and local colleagues and clients in seven affiliated offices (assuming mutual-perception
opportunities)
-
The team operates within an organizational culture that can be categorized as having a project
oriented organizational culture (guided missile culture)
In addition, as the researcher would not have access to highly confidential third-party client information,
confidentiality and legal requirements could be limited to internal in company communication and
interactions, this made it slightly easier to get access to a team working within an environment with high
confidentiality standards.
Respondents’ profile
As mentioned in the introduction, the main focus in this case study is on clinical project managers who
interacted with colleagues from different affiliated offices in Australia, China, Japan, Korea, Malaysia,
New Zealand, the Philippines, Taiwan and Singapore. The communication and interaction with their
colleagues and superiors was studied during observations in formal group meetings and teleconferences.
This section describes the specific positions and roles and cultural backgrounds of the participants in the
case study including the role of the researcher to predict a possible researcher bias. We first start with the
introduction of the clinical project manager’s team; followed by an overview of the connections and
interactions the clinical project managers have on a daily basis to accomplish their tasks.
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The leadership of the multi-cultural clinical project manager’s team in the case study is located at the
company's regional HQ in Asia, overseeing and managing clinical-trial projects across Asia-Pacific and
Australia and New Zealand. A total of 23 individuals from the clinical research team are included in this
study. The total team consisted of a clinical research leadership team of 3 persons (1 regional vice president
(VP), 1 regional general manager (GM) and 1 regional project director (PD) and 20 clinical project
managers (CPM’s). All 20 clinical project managers reported status updates on the clinical trials projects to
the project director who in turn reported to 2 regional (Asia HQ-based senior vice presidents). The regional
VP and GM reported to a Global Senior VP located in the United States. Being operationally involved and
supportive of the clinical trials, the VP and regional GM were also included in the case study. A total of 9
participants are based at the regional HQ in Singapore. The remaining 14 clinical project managers were
located in the respective affiliated offices in Australia, China, Japan, Korea, New Zealand, Malaysia, the
Philippines, and Taiwan. These 8 countries included in this study, representing approximately 10% of the
countries of the company’s global network of affiliated offices. See appendix 6 for an organogram with the
clinical project managers’ countries of location, the reporting lines and how they are connected.
Respondents’ roles
The 23 clinical project managers (including the leadership team) involved in this case study have a biomedical or medical sciences background, experience in data collection, monitoring and managing of
clinical trials and have completed specific internal project management courses and other specialized,
individually tailored training programs. They are responsible for managing and monitoring one or more
clinical trial projects from start to finish.
The number of projects depends on the size of the project. The 23 clinical project managers interact weekly
with a multifunctional support team located in 8 different countries and on a daily basis with around 16-20
clinical research associates (CRAs). These CRAs actually monitor the day-to-day clinical trial projects via
direct contacts with physicians, research institutions and hospitals that carry out the clinical research. The
regional general manager (GM) mentioned in the previous organogram leads the team of CRAs. The
clinical project managers also have weekly/monthly meetings with the local representatives of the global
client to discuss the progress of the clinical trials.
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At the weekly progress and update meetings/teleconferences, the regional director, monitors, manage and
consolidate the information of all the clinical trials within the Asia-Pacific region. See appendix 6 for an
overview of the pivotal role of the clinical project managers and the different functions they regularly
communicate to manage the clinical trial projects within that specific country. In order to provide specific
insight into the daily activities of the clinical project managers and to better understand the context of the
case a brief description of the clinical research process is given in appendix 7. The information for this
process overview was obtained via internal company data, verified with publically available data sources
(Rasmussen, 2003).
Researchers role
The researcher was allowed access as an observer to a total of three weekly clinical projects update
meetings and teleconferences both on site at the regional Asia HQ and via a digital connection. All clinical
project managers were informed by their superiors about the objectives of the PhD case study project, the
role of the researcher as an observer and consented in the participation of the researcher in the team
meetings. The setting for these observations can be described as closed or a private setting within the
company’s premises at the regional HQ in Asia, controlled by a gatekeeper in this case the clinical project
director and the sponsor of the project the vice president Asia pacific (Silverman, 2011). At the start of
each meeting the project director formally introduced the researcher to the team. The researcher did not
intervene during the exchange of information or discussions during the meetings or teleconferences and
only asked clarification from the leader of the meeting after the meeting had been closed. The researcher
had access to all clinical project managers either face to face, via email, phone or other digital
communication channels if he needed to ask for clarification of a specific observation or issue that was
discussed during the team meeting. Given the high sensitivity of the (client) information that was shared
during the meetings and to protect the privacy of the clinical project managers, the researcher was only
allowed to make notes. Video or audiotaping of the team meetings or individual interviews was not
allowed. As an observer, the researcher pledged complete confidentiality to the company and all
participants and promised that neither the company's and the individuals' real names resulting from surveys
would be used in the research report, and that they would not be substituted by pseudonyms.
The researcher had no business or other interests in relation to the company and the members of the team
within the case study. To minimize researcher bias the researcher has verified his onsite observations with
all participants and the senior leaders of the company.
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In addition the researchers background and professional experience within the biopharmaceutical industry
(see CV in the back of this thesis) safeguard a high ecological validity.
5.3 Respondents characteristics
This section gives an overview of the characteristics of the sample used. Table 5.2 gives an overview of the
number of clinical project managers involved in this case study, by cultural group, country of birth and
their affiliated office location. The 23 respondents were divided on the basis of their country of birth
Anglo-Saxon or Asian cultures, the geographical location of their respective affiliated office and their
gender. The Asian cultural group includes 7 nationalities, the Anglo-Saxon cultural group 2. The clinical
project managers were located in 8 affiliated offices, including the regional HQ in Singapore. The split
between males and females was 6 -17 respectively.
Table 5.2 Distribution of 23 clinical project managers by cultural group, national culture and affiliated office locations.
_______________________________________________________________________________________________________
Cultural group
National Culture Affiliate Location
Respondents/Percentage
N=8
N=8
_______________________________________________________________________________________________________
Anglo-Saxon
Australia
Singapore
1
Australia
Australia
2
New-Zealand
New-Zealand
1
ANS
Total 4 (17 %)
Asian
China
China
Japan
Philippines
Philippines
Singapore
Malaysia
Malaysia
Taiwan
Korea
Singapore
China
Japan
Singapore
Philippines
Singapore
Malaysia
Singapore
Taiwan
Korea
2
4
3
3
1
1
1
1
1
2
AC
Total 19 (83 %)
Males
Total 6 (26 %)
Females
Total 17 (74 %)
_______________________________________________________________________________________________________
Total
23
_______________________________________________________________________________________________________
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5.4 Results from the online Emergenetics survey
This section presents the results from the Emergenetics survey from the 23 participants from this case
study. Table 5.3 below shows an aggregated overview of the thinking styles of the clinical project
managers (N = 23). The participants in the sample included 12 out of a potential 15 thinking styles. The
majority of the of 23 clinical project managers were dual models, (14) individuals with two thinking styles
(AT+SC+AC+TS+AS+TC- 60%), second came tri-models, (8) individuals with three thinking styles
(ATS+ASC+ATC+TSC+ATSC - 33%) and third mono models, (1) individuals with one thinking style
(A+T+S+C - 4%). 67% of the team had at least an analytical thinking style and 66% had at least a
structural thinking style. Of the participants, 13% perceive themselves to have an abstract thinking style
(analytical and conceptual thinking) a similar percentage 13%, perceive themselves to have a concrete
thinking style (structural and social thinking). Furthermore, 18% of the participants perceive themselves to
have a convergent thinking styles (analytical and structural thinking) and 8% a divergent thinking style
(social and conceptual thinking) respectively (see also chapter 4, section 4.2 table 4.2 for the thinking
styles and behavioral patterns of the explorative quantitative study respondents).
Table 5.3 Distribution of thinking styles from 23 clinical project managers
_______________________________________________________________________________________________________
Thinking styles
Sample sub-study 3.A (%)
Sample sub-study 3.A (N)
_______________
_____________________
_____________________
AT** (ANA-STR)
18%
4
**SC (SOC-CON)
8%
2
A**C (ANA-CON)
13%
3
**TS (STR-SOC)
13%
3
A*S* (ANA-SOC)
4%
1
*T*C (STR-CON)
4%
1
ATS* (ANA-STR-SOC)
13%
3
A*SC (ANA-SOC-CON)
4%
1
AT*C (ANA-STR-CON)
8%
2
*TSC (STR-SOC-CON)
4%
1
ATSC (ANA-STR-SOC-CON)
4%
1
*T** (STR)
4%
1
_______________________________________________________________________________________________________
Total
100%
23
_______________________________________________________________________________________________________
ANA=analytical, STR=structural, SOC=social, CON=conceptual (also see Browning, 2006)
135
Table 5.4 represents the aggregated distribution of the percentile scores of the behavioral patterns of the 23
participants. The scores for Expressiveness (EXP) – quiet (33), reserved (33), outgoing – gregarious (33)
shows that the group may have the tendency to feel comfortable behaving across all behavioral categories.
The scores for Assertiveness (ASSR) – peacekeeper (25), accepting (33), competitive – driven (42) shows
that the group may have the tendency to behave in a more driven way. The scores for the behavioral pattern
Flexibility (FLX) – focused (42), firm (21), accommodating - easy-going (38) shows that the group may
have the tendency to be more focused.
Table 5.4 Distribution of behavioral patterns from 23 clinical project managers
______________________________________________
Behavioral Percentiles
EXP
ASR
FLX
______________________________________________
Percentiles (0-30)
33
25
42
Percentiles (34-66)
33
33
21
Percentiles (67-100)
33
42
38
Summary of the results
From the Emergenetics survey results the following interpretations can be formulated as they relate to how
the team of clinical project managers would tend to think and behave (behavioral intention). The majority
of the team has the tendency for analytical and structural thinking or convergent thinking (67%) which
means that they tend to look for data and scientific proof, they are considered logical, cogent, objective,
detailed, disciplined, organized, and traditional. They can appreciate scientific methods, follow rules and are
cautious of new ideas. In general this group might prefer to ask why and how rather than with whom and what
if. When addressing a problem this group might deep-dive in the matter rather than, exploring alternative
options.
When looking at the behavioral patterns the team can be rather quiet or gregarious depending on the situation,
with a preference to drive the process or project in a focused and depending on the situation accommodating
easy going manner. This means that the group might show behaviors that move to either the left or the right of
scale of the three behavioral patterns depending on whom they speak with (see also chapter 3, section 3.2,
table 3.1, dimensions in percentiles of the behavioral patterns of the Emergenetics instrument). Both the
thinking styles and behavioral patterns can be more or less expected from a team who’s primary task is to
initiate and monitor clinical trial program, a rather scientific and structured process to manage involving many
stakeholders. The outcomes of this sub-study form the basis for an individual behavioral score-card that will
be used to tally actual behavior during observations in sessions I, II and III.
136
5.5 Results from the observation session I, II and III
This section presents the results from one teleconference and the two on-site observations at the HQ office
location of the company in Singapore. The focus in these observations was to compare tallied actual
observed individual behavior with the individual behavior scores. The observations were focused on the
interaction between the presenter clinical project manager and the team-leader project director. First we
present an overview with the total number of participants involved in all observations including their
cultural background and their affiliated office location. Then the objective of the team meeting and the
participants involved are presented. For each session the researcher summarizes how the meeting went and
his impressions of the atmosphere during the meeting. Finally we present and conclude on the major
differences between the coded behavioral score card (EG survey) and the participants tallied actual
behavior. The section aimed at answering the research question 5 addressed in the introduction of this
chapter. Conclusion from all the three observation sessions will be drawn at the end of this section.
The total group of 23 participants included 8 different nationalities, located in 8 different countries. From
the 23 participants a total of 23 coded behavioral scores card were completed. Please note that some
participants were present at more team observations sessions and they were scored during each of the
sessions. All coded behavioral score cards and tallied observations were checked and verified with each
participant before and after the session in a face-to-face teleconference between the researcher and the
participant. The researcher informed the participant’s that their information would only be shared with
them and no one else, as agreed between the researcher and the company in a confidentiality agreement.
Session I
The objective of this meeting/teleconference was to touch base with two clinical project managers who
were at the company’s HQ for training and observations and to prepare them for their clinical project
management roles. The purpose was to follow-up on their weekly exposure and to address any questions
they might have arisen from their scheduled training and observations activities. The meeting started on
time and with open-ended questions the clinical project managers were given the opportunity to share their
experiences from the last two weeks of the introductory training. There were no interruptions except when
there was a silence. The team-leader invited either participant to contribute and share information, thoughts
and opinions as it relates to the subject that was presented and discussed.
137
Furthermore specific questions were addressed in relation to both clinical project managers in training how
they would use what they have learned at their local affiliated office and what further support they
expected from their colleagues from the regional HQ. Finally, questions were addressed to all team
members, on what can be done differently to improve this introductory training. At the end the meeting a
summarizing “check for understanding” was done with the team members and actions items confirmed
with all participants, the meeting ended on time. This all happened in a very friendly atmosphere with
much sharing and laughter. After the session the team-leader mentioned that the internal training sessions
at the regional HQ was specifically done to familiarize new members of the team with key processes,
procedures and reporting and how the CPM team operates. This was important because the CPM has a
pivotal role to play in the communication between the clinical research associates who are managing the
clinical trials, the management of the local affiliated and the regional HQ. She also mentioned that
misunderstanding sometimes occur because CPM in the local office are required to be more loyal to the
local management than to the regional HQ.
Table 5.5 shows the total number of participants involved in this teleconference.
Table 5.5 Observations total number of participants by cultural group, national culture and affiliated office (N = 6)
_______________________________________________________________________________________________________
Cultural group
National Culture Affiliate Location
Number of participants
_______________________________________________________________________________________________________
Asian
China
Singapore
2
Japan
Japan
2
Philippines
Singapore
2
_______________________________________________________________________________________________________
Total
3
2
6
_______________________________________________________________________________________________________
This session only included 6 participants from an Asian cultural background (3 nationalities) and 3
affiliated offices. See appendix 9 for an overview of their thinking styles and behavioral patterns and the
comparison between their individual scores on the behavior patterns expressiveness, assertiveness and
flexibility and the actual scores of observed behavior.
138
Findings and conclusions
Expressiveness: Four out of six participants were observed as rather quiet, introspective and reserved. Of
three participants (P1, P2 & P4) the observation scores were completely in line with their first-third
percentile survey score. Participant (1 & 2) the trainees, only spoke when asked specific questions, about,
what they have learned, what would they do different the next time and if the 3 weeks were too long or too
short. They were happy with the program and have learned a lot that they can share with colleagues and
their superior at the affiliated office. Two of the three participants who scored in the third-third of
expressiveness (P3, P5 & P6) expressed the intended or close to the intended behavior during the meeting.
Participant (5) mentioned, “3 weeks might be too short to make yourself familiar with all the processes and
procedures”. Participant (6) mentioned that it might be advisable if trainees would get the process and
procedural information beforehand so they are better prepared. Participant (P3) was more quiet and
introspective which contrasted with the survey score indicating a more talkative –gregarious tendency, with
major tallied difference.
Assertiveness: Some minor differences were found between the observational scores and the percentile
survey scores of each participant concerning assertiveness. Three (P2, P4 & P5) participants tended to
behave in a rather easy-going way; two participants seemed to be comfortable in the peacekeeping mode.
For three participants (P2, P3 & P4) the observation scores were completely in line with their percentile
survey scores. One participant (P3) showed more competitive and forceful behavior, which was inline with
their percentile, survey score (third-third percentile). On the question from the CPM director, what can be
done better the next time, participant (3) suggested that the management in HQ should be “more
proactively engaging” with local management to inform them about the objectives of the training program.
He further suggested that to maximize learning, the trainees should receive more frequent feedback during
the three weeks at the HQ. And finally that trainees should have a specific assignment combined with
personal goals that they have to achieve during the three weeks.
Two participants (P1 & P5) were in the ‘it depends’ bracket of the second-third percentile (34-66%ile) and
flexed to the left showing quiet and easy-going behavior rather than competitive and forceful behavior
during this team session. As a general observation, during the meeting no one interrupted the speaker,
everybody would listen until the speaker is finished. Team members would only speak after the CPM
director has asked a question.
139
Flexibility: Some minor differences were found between the observational scores and the percentile survey
scores of each participant concerning flexibility. Three (P1, P3 & P6) participants tended to be rather
adaptive and accommodating which was within their respective percentile score. Three participants (P2,
P4 & P5) seemed to be comfortable with behaving within the first- third percentile scores, focused mode.
Two participants (P3 & P6) observed to be adaptive and accommodating, which is in line with their thirdthird percentile survey score. One participant in the ‘it depends’ bracket of second-third percentile (3466%ile) flexed to the left and showed both firm and adaptive behavior in this team session. No one in the
team dis-agreed with the suggestions from participant (3) for improvement of the training program. All
team members felt that the recommendations are valuable and should be implemented for the next training
session for trainees at the HQ.
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Session II
This is a regular weekly update meeting of clinical project managers. The objective of this meeting was to
get a progress update of clinical trials performed in four countries, China, Korea, Taiwan and Malaysia
respectively. Within this meeting six different clinical trial projects were presented with about 10-15 min
breaks in between presentations. The leader would start the meeting and mention the projects numbers and
details. The highlights of each project would be presented and discussed by the clinical project managers;
clarification would be quite frequently required and given. Otherwise no further interruptions were
observed, except when there was a problem with the connection or issues needed clarification. Projectspecific questions in relation to logistics, finance or regulatory matters were addressed in relation to
investigators meetings, site selections, patient recruitment or finance related issues like; payments,
invoicing, etc. Finally there were specific questions addressed to all team members; during these questions
and answers stages the leader would “check for understanding” to agree on the solutions and confirm the
new deadlines with the respective clinical project manager. For each project the CPM director would ask
the clinical project manager to explain how he/she would go about involving local management and others
into the agreed solution process. The CPM stressed the importance of getting the “buy-in” from local
management, to guarantee flawless execution of the plan. The meeting was summarized and actions items
confirmed with all participants, the session ended on time. This all happened in a highly professional but
friendly atmosphere with occasional laughter. Table 5.6 shows an overview of the total number of
participants involved in this team observation session. Two participants (P2 & P6) from the previous
sessions I also participated in session II, with seven new participants. The total number of participants in
session II was nine.
Table 5.6 Observations total number of participants by cultural group, national culture and affiliated office (N = 9)
_______________________________________________________________________________________________________
Cultural group
National Culture Affiliate Location
Number of participants
_______________________________________________________________________________________________________
Asian
China
Singapore
1
China
China
2
Philippines
Singapore
2
Malaysia
Malaysia
1
Taiwan
Taiwan
1
Korea
Korea
2
_______________________________________________________________________________________________________
Total
5
5
9
_______________________________________________________________________________________________________
141
Similar to the previous session this session only included 9 participants from an Asian cultural background
(5 nationalities) and 5 affiliated offices. See appendix 10 for an overview of their thinking styles and
behavioral patterns and the comparison between the individual scores on their behavioral patterns
expressiveness, assertiveness and flexibility and the actual scores of observed behavior.
Findings and conclusions
Expressiveness: Six participants (P1, P2, P3, P4, P6 & P9) observation scores were in line with their
respective percentile survey scores. These CPMs only spoke when they were asked to speak. This was the
case when the CPM director asked if anybody wanted to highlight certain issues or problems that need
extra attention of the group. Two participants (P5 & P8) had a slightly different observation score but were
still within their percentile survey score. Participant (5) specifically asked; “ attention for the delays in the
clinical site selection process, which was causing problems with signing of contracts and the timing of the
start of the project”. Participant (8) highlighted the importance of, “ ensuring that the financial parameters
are considered, as the delay would impact the patient enrollment, budget and resource allocation”.
One participant (P7) in the “it depends” bracket flexed to the right and showed talkative behavior rather
than being quiet and reserved. Participant (7) mentioned words like “we are running behind”, and “the
goals of the project are not achievable”. Participant (7) specifically addressed a question to the CPM
director how the risk of the delay will be managed, particularly on how the client or sponsor will be
informed. The CPM director acknowledged the importance of the issue and asked all in the team to comeup with creative solutions to resolve this delay of the project. She further mentioned that it is key to
continue to deliver the highest quality to the client even if the team is under pressure because of the
anticipated delay.
Assertiveness: Five participants (P1, P2, P4, P7 & P9) observation scores were in line with their respective
percentile survey scores. Two participants (P6 & P8) had slightly different observations scores but were
still within their percentile survey scores. Two participants (P3, P5) in the “it depends” bracket flexed to
the left and showed peacekeeping and easy-going behavior rather than competitive, forceful and driving
behavior. Participant (3) mentioned that the team is “working very hard” has already accomplished a lot
and we are doing extremely well. Participant (5) mentioned that she is “really proud” of the team. Other
words used by P (5) are that the team has done “ extremely well” and that the support from other
department was “absolutely amazing”.
142
Flexibility: Three (P1, P3 & P9) participants with a first-third percentile survey score showed to behave
adaptable when considering their observational scores. When they were asked why they have been
adaptable during the meeting they mentioned the following reasons; the importance of the project for the
company, their commitment to deliver and contribute to the project, the information provided and the way
the information was presented by the CPM director. Two participants showed to be focused in line with
their first-third percentile survey score. They did not felt the need to intervene during the meeting because
others have already expressed their views. They were pleased with the solutions suggested and the process
that was agreed upon to mitigate the potential risks associated with the potential delay.
Two participants (P5 & P6) were observed to be adaptive and accommodating, which is in line with their
third-third percentile survey score. Participant (5 & 6) made some suggestions to the team how patient
enrollment can be increased without jeopardizing on quality. Two participants in the “it depends” bracket
of the second-third percentile score flexed to the right showing adaptive and accommodating behavior
during the meeting. All team members agreed with the adjustment program to resolve the delay. They also
agreed that “buy in” from local management and supportive functions like finance was key in order for the
adjustment program to work successfully.
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Session III
This is a review meeting of nine clinical trial projects that were performed for one global client. The
objective of this meeting was to get a consolidated progress update of clinical trials performed in five
countries, Australia, New Zealand, China, Korea and Singapore respectively. Session III was even more
intensive than the previous session II. Session III included nine different update from five countries with 14
participants. A similar structured approach was in place with progress presentations with about 10-15
minutes breaks in between presentations.
The meeting started on time and all sessions had a certain sequence. The leader would mention the projects
numbers and details and would ask the respective clinical project manager to start the presentation with the
highlights of each project. The information presented would be very scientific and specific and there were
no interruptions except when there was a problem with the connection or if thinks were not understood at
the other side of the line. Based on the progress and status of each project specific questions were then
asked by the leader or on invitation by the leader, other functions (finance, regulatory) would provide
clarity or contribute. Furthermore specific questions were addressed in relation to issues weather in
relation to financial parameters, payments, invoicing, budgets, information and documents required or
actions that need to be taken. Issues were discussed in much details and the quality that needed to be
delivered to the client was always the major guidance in the process of resolving the issue at hand.
Finally there were specific questions addressed to all team members; on what are the potential options for a
specific issue were, how this could be resolved, who was going to do what by when. At each stage of the
process the leader would check for understanding, agree on the solutions, and confirm the new deadlines
with the respective clinical project manager. The meeting was summarized and actions items confirmed
with all participants. The meeting ended about 35 minutes later than anticipated due to the need to discuss
some issues in more details and a short hiccup in the teleconference system. This all happened in a highly
professional but friendly atmosphere with sometime laughter. Table 5.7 shows an overview of the total
number of participants involved in this team observation session III. Four participants of the previous
sessions I and II also participated in session III. With ten new participants the total number of participants
in session III was fourteen.
144
Table 5.7 Observations total number of participants by cultural group, national culture and affiliated office (N=14)
_______________________________________________________________________________________________________
Cultural group
National Culture Affiliate Location
Number of participants
_______________________________________________________________________________________________________
Anglo-Saxon
Australia
Australia
3
New-Zealand
New-Zealand
1
Asian
China
Singapore
1
China
China
3
Singapore
Singapore
1
Korea
Korea
2
Philippines
Singapore
2
_______________________________________________________________________________________________________
Total
6
5
14
_______________________________________________________________________________________________________
This session included 14 participants from both an Anglo-Saxon and Asian cultural background (6
nationalities) and 5 affiliated offices. See appendix 11 for an overview of their thinking styles and
behavioral patterns and the comparison between their individual scores on the behavior patterns
Expressiveness, Assertiveness and Flexibility and the actual scores of observed behavior.
Findings and conclusions
Expressiveness: Eight participants (P1, P2, P3, P5, P6, P9, P10 & P12) observation scores were in line with
their respective percentile survey scores. Two participants (P4 & P8) both with a third-third percentile
score had different observation scores. Participant (P8) was still within the percentile survey score and
participant (P4) showed opposite behavior (quiet and introspective) than the percentile score indicated
(talkative and gregarious). Participant (4) mentioned after the meeting that the technical issues with the
phone line have made him kept quiet rather than talkative. He was also comfortable with others expressing
what he wanted to bring to the discussion. Three participants (P11, P13 & P14) in the ‘it depends’ bracket
flexed to the left and behaved quiet and reserved. Participant (P7) showed talkative behavior rather than
quiet and reserved behavior as his percentile survey score showed. Participant (7) mentioned after the
meeting that to show more talkative than quiet and reserved behavior mostly depends on the importance of
topic for his work, the size of the group, or if he agrees or disagrees with the opinions expressed.
145
Assertiveness: Five participants (P4, P6, P7, P9 & P12) observation scores were in line with their
respective percentile survey scores. Three participants (P5, P8 & P10) with a third-third percentile score
had slight different observation scores, but were still within their percentile survey scores. Four participants
(P1, P3, P11, P13 & P14) in the ‘it depends’ bracket all flexed to the left and showed peacekeeping and
easy-going behavior rather than competitive, forceful and driving behavior.
Overall the observational scores of each participant were aligned with their respective percentile scores
from the EG survey, with no major discrepancies. They all felt comfortable with the way the CPM director
presented and discussed the issues and all agreed with the suggested next steps.
Flexibility: Four participants (P6, P12, P13 & P14) observation scores were completely in line with their
respective percentile survey scores. This group included five (P2, P3, P5, P9 & P10) participants with a
first-third-percentile score (focused & firm). However, adaptive behavior was scored during the meeting
for all of these participants. This can be qualified as a major difference. Two participants (P7 & P8) in the
‘it depends’ bracket of the second-third percentile score flexed to the right, showing adaptive and
accommodating behavior during the meeting. For two participants (P13 & P14) tallied behavior scores
were aligned with their second-third percentile scores. It seemed that way the meeting was led had an
impact on the participants to be willing to be rather adaptable and accommodating than to show firm and
focused behavior. The check of understanding at each stage of the discussion and agreement on the
suggested solutions was a “modus operandi” that all team members felt comfortable with. A summary at
the end of each discussion and agreement of the action items made clinical project managers feel confident
and comfortable that new deadlines and milestones area achievable.
146
5.6 Conclusions and discussion
In this chapter we have tested a part of the research framework that studied, if there are differences
between, perceived behavior (based upon thinking styles and behavioral patterns) of the individual clinical
project managers versus their tallied observed actual behaviors during weekly update meetings. These
observations were done during weekly update meetings at one location and via teleconference within a
group of clinical project managers from Asian and Anglo-Saxon cultural background from one
multinational organization. Each participant of the update meetings completed the EG survey and the
perceived behavioral intention scores (based upon thinking styles and behavioral patterns) were verified
with each individual participant via a teleconference or face-to-face session, before it was used during the
observations.
We have taken a combined research approach and have used quantitative (EG-survey) and qualitative
(observations) methods to answer sub-question 5 To what extent do employees in a specific cultural
context differ in their self-perception on how cultural factors and personal preferences influence their own
behavior compared to their actual observed behavior?
This multi-method research approach provided insights into how the clinical project managers perceive
themselves to behave and how they actually behaved during their weekly update meetings with colleagues
and superiors. This approach provided opportunities to look for an alternative set of explanations (through
self-perceptions from the insider and observations from an outsider) why clinical project managers from
diverse cultural backgrounds, based in a variety of countries, behave the way they do within one specific
environment (weekly update meetings). To operationalize our research, we first measured and verified
behavioral intensions of each clinical project manager and then compared the behavioral intentions scores
with tallied observations of actual behaviors during the weekly update meetings.
To minimize the risk of collecting unreliable field data during the observations, the researcher prepared a
prefilled coded behavioral score card that was based upon each participants individual scores for the
behavioral patterns, expressiveness, assertiveness and flexibility. In addition, the scores on the behavioral
observation scorecard were verified with each of the participants in a face-to-face teleconference after the
sessions.
147
The structured process in the meeting has also allowed the researcher to focus his observations on two
individuals i.e. the presenting clinical project manager and the project director who was leading the
meeting/teleconference. However, checking the observations scores with the respective individual clinical
project managers mitigated this difficulty. Furthermore, the role of the researcher as an observer was clear
to all participants and was met with overall consent. By guaranteeing confidentiality to all participants and
the company the researcher could get the insider’s perceptions of the clinical project managers in action. In
addition the researcher could observe a team of very skilled clinical project managers that share highly
sensitive information during their weekly project progress sessions in a multinational cultural, single
organizational cultural and single professional cultural setting.
The results from the three observation sessions show minor individual differences as they relate to the
behavioral patterns; expressiveness, assertiveness scores versus tallied observed behavior during the update
meetings. Some major differences for individuals and as a group were observed as it relates to the
behavioral pattern flexibility. The majority of the clinical project managers from both Asian and AngloSaxon cultural background where mostly willing to be adaptable and accommodating; this was irrespective
of their flexibility percentile survey scores (either firm and focused – adaptable-accommodating).
The willingness of the clinical project managers to show adaptable and accommodating behavior towards
proposed ideas, options and solutions, may have occurred because of the following reasons:
1. Modus operandi of the data and information exchange: it might be related to the fact that the majority of
the team had an analytical thinking style. Individuals with an analytical thinking style tend to look for data
and scientific proof (Browning 2006). This might indicate that this team was satisfied with the data and the
way the information was provided during the meeting. Clinical project managers with a flexibility score in
the firm and focused range, might have felt comfortable enough with the data and arguments that were
provided during the meeting, which have led them to be willing to show adaptable and accommodating
behavior (Rousseau, Aubé and Savoie, 2006).
148
2. Modus operandi of the leader involved: it might also be that due to the transformational leadership style
and the thinking style of the leader, (5ATS*) he/she was able to provide the right data, meaning that the
leader could relate to the majority of the teams thinking style (A), presenting the information in a structured
format (T) in a relational, collaborative, empathic, and supportive manner (S) (Jung Chow and Wu, 2003;
Browning, 2006).
3. Modus operandi of the professionals involved: it may also be that the information and data provided and
exchanged during the meeting, was of critical importance for the clinical project managers to perform their
major tasks. It could therefore be argued that this, task orientation of the ‘operator culture’ has influenced
the clinical project managers to show adaptable and accommodating behavior to demonstrate their
commitment and contribution to the task at hand and to the project as a whole (Sutton, Salas, Burke and
Pierce, 2006).
4. Modus operandi of the organization involved: it could be the tendency of so-called mutual adjusting
behavior as a sign of professionalism of global managers in the biopharmaceutical sector (Sutton et al.,
2006). However, a combination of the role of leadership and the organizations’ culture could have played a
key role in this process of mutual adjusting behavior of the team members (Jung et al., 2003; Rousseau et
al., 2006)
In answering research question 5, we can now conclude that minor differences between tallied actual
observed behavior and individual behavioral intentions scores for expressiveness, assertiveness were
observed as it relates to clinical project managers from Anglo-Saxon explicit cultures versus Asian implicit
cultures. Major differences between tallied actual observed behavior and individual behavioral intentions
scores for flexibility were observed within both groups. These major differences could be explained based
upon the information requirement from the project, the situation in the session, the leadership style and the
modus operandi of this team of professionals. These observations are rather similar to findings in cultural
differences studies that aimed to compare the innovativeness of entrepreneurs from different national and
professional cultural background (Hayton, George and Zahra, 2002; Dodd and Patra, 2002; Bhaskaran,
2006) or the perceptions on leadership of individual employees from different national cultural
backgrounds (Ke and Wei, 2008; Kirkman, Chen, Farh, Chen and Lowe, 2009).
149
We can further conclude that the majority of the clinical project managers from both Asian and AngloSaxon cultural background were mostly willing to be adaptable and accommodating; this was irrespective
of their flexibility scores (either firm and focused – adaptable-accommodating). During all three sessions
the researcher had the impression that all three observed teams tended to be very polite in their
communication. Their interactions were mostly direct and sometimes side tracked by a personal note. The
mostly discussed one project with more issues simultaneously. Information sharing was professional and
open and in a friendly atmosphere.
Theoretical implications
In chapter 2, we proposed a combined etic-emic research framework that assumed that cultural factors and
personal preferences could be theoretically disentangling as two influencing factors on individual
behavioral intention. In chapter 3 we validated an instrument to measure behavioral intention within a
culturally diverse environment as a key construct of the proposed research framework. In chapter 4, we
tested the assumption of the framework that cultural factors and personal preferences influence behavioral
intention. The explorative quantitative rather emic study demonstrated that the research framework
provided valuable insights on how a variety of professionals from Anglo-Germanic/Nordic versus LatinAsian cultural background perceive their behavior to be influenced by the mutually connected cultural
levels of influence and personal preferences. In chapter 5 we further tested the assumption of the
framework that behavioral intention can be seen as a good predictor of actual behavior.
The combined etic-emic case study demonstrated that the framework provided valuable insights into how
behavioral intentions are related to actual behaviors within a diverse cultural context. Within the case study
we observed major differences between tallied actual observed behavior and individual behavioral
intentions scores for flexibility and minor differences for assertiveness and expressiveness between
professionals from Anglo-Saxon explicit cultures and from Asian implicit cultures. We also found that
these major differences in flexibility may be related to the competences, thinking styles and types of
information exchange of the team-leader, the importance of the task at hand and the professional code of
conduct. To conclude the simplified framework made it possible to collect data using surveys to measure
the perceived behavioral intention and observations to tally the actual behaviors. It further allowed
comparison and analysis of these perceptions and observations at a national and professional cultural group
level.
150
In chapter 2, section 2.3.1 we concluded that both etic and emic models separately only capture part of the
picture, either the insider's view or the outsider's view. We further concluded that both approaches are
using self-perception methods, which can lead to distorted perceptions and that perceptions of one person
cannot be scientifically verified and generalized to understand the perceptions of another person.
The combined insiders and outsiders approach used in this study allowed a more in-depth understanding on
how perceptions of own behavior (insiders view) differ with perceptions of an outsider within a culturally
diverse team. It further provided some indications on how cultural factors and personal preferences
influence behavioral intentions and why employees behave the way they do in a culturally diverse context.
These findings point towards a cultural differences research approach that captures a full picture using selfperceptions and observations and by simultaneously combining the strengths of both the etic and emic
methods. As the sample size used in this case study is rather small a study with a larger sample size would
be recommended to confirm the usefulness of the combined etic-emic research framework for future
cultural differences research.
Practical implications
This study surveyed and observed a team of professionals, with a more or less similar educational
background (professional culture) from one organization (organizational culture) located in 8 different
countries (national culture). The findings from this study suggest that professionals from diverse cultural
backgrounds within the same organization will be willing to show adaptive behavior even if it is sometimes
a bit outside of their ‘comfort’ zone, when there is an alignment between:
1
How information about a project is shared and exchanged during the meeting, and how this
information sharing relates to the thinking style of the majority of the team-members.
2
The leadership and thinking styles of the leader and how the data/information is presented and
shared with the team
3
The importance of the data and the associated task that need to be accomplished
4
The so-called mutual adjusting behavior associated with the professional and organizational culture
151
This means that to maximize the effectiveness of a meeting in a culturally diverse environment, managers
and team leaders should be aware of how their team members prefer to receive and process information.
They should also be delivering the right information in the right format and context, as this approach might
facilitate better understanding of the shared information. Finally, they should, do frequent checks for
understanding among the team members in order to get faster alignment of thoughts and agreement on how
issues and problems can be resolved.
It should however be noted, that the practical implications are based upon snapshots of the clinical project
managers day-to-day activities and that Anglo-Saxon clinical project managers where only present at one
meeting. The same accounts for the two other observations sessions, which included only clinical project
managers from Asian cultures. The practical implications might therefore only apply to the
biopharmaceutical industry or similar multinational organizations with highly skilled and educated project
managers. More research in different industries with different professionals is recommended to verify the
results from this study.
Furthermore, in this study we have taken a more qualitative research approach, comparing scores on
behavioral intention with tallied observations during team meetings of clinical project managers from
Anglo-Saxon and Asian cultures. To conduct the study, the researcher relied on self-perception scores on
behavioral intention and observations and notes. There was no possibility for verification of the
observations by a second observer or by video or audio recordings. As suggested by Eppink et al., (2010) a
360 verification of self-perception and perception of others (observer) by mutual perception could provide
further insights how the clinical project managers perceive their own behavior and that of their colleagues
from another country and vice versa. The next chapter 6 will explore this approach.
152
153
Chapter 6*6
Self-perceptions and mutual perceptions on actual behavior: a comparative
study among clinical project managers from Anglo-Saxon and Asian
cultural background
6.1. Introduction
In the previous chapter we have tested the part of the research framework that measured behavioral
intensions and compared the behavioral intentions scores with tallied observations of actual behaviors of
respondent from diverse cultural backgrounds. The aim was to study, if differences can be observed
between, perceived behavior (based upon thinking styles and behavioral patterns) of the individual clinical
project managers versus their tallied observed actual behaviors during weekly update meetings. We
concluded, that no major differences (expressiveness and assertiveness) were observed between the
perceived individual behavioral intention scores and tallied actual observed behavior of the clinical project
managers from both Anglo-Saxon explicit cultures and Asian implicit cultures. Major individual
differences (flexibility) were observed within both groups, but could be explained by a certain requirement
or situation in the meeting session observed. These conclusions are based upon a self-perception survey on
behavioral intentions and tallied observed behaviors on a behavioral score card from snapshots of the
clinical project manager’s day-to-day activities. It may therefore be of interest to compare self-perception
results with mutual-perception results, which can provide a wider perspective on how individual employees
perceive their own behaviors compared to how they see their collogues behaviors and vice- versa. This
approach would allow more opportunities for data analysis and interpretations of why individual from
different cultural backgrounds behave the way they do within an organizational context (Ulijn et al., 2009).
However, so far most of mutual-perception studies only measured national and organizational cultural
differences (Ulijn and St Amant, 2000, Vedina et al., 2006). In addition in a rather similar mutualperception study from Ulijn et al., (2009), they only compared the influence of national cultural differences
from European cultural groups.
6
This chapter is based on a paper by Byron, R.D., and Ulijn, J.M. (2016). The influence of cultural factors & personal preferences on individual employee
Behavior: Anglo-Germanic-Nordic and Latin-Oriental cultures compared, presented at the 12th ABC conference of Europe, Africa and Middle East Region
University of Cape Town, South Africa 6-8 January 2016.
154
This study looks at national, professional and organizational cultural differences and aims to measure, the
self-perceptions and mutual-perceptions of individuals with the same profession (23 clinical project
managers), working for the same organization (multinational biopharmaceutical service provider with its
HQ in Singapore) in the respective affiliated offices in Australia, China, Japan, Korea, New Zealand,
Malaysia, the Philippines, and Taiwan (see also chapter 5, section 5.3, table 5.2). At group level we aim to
compare how the Anglo-Saxon cultural group (Australia and New Zealand) perceive their own behavior
compared to how their colleagues from the Asian cultural group (China, Japan, Korea, Malaysia, the
Philippines, Singapore and Taiwan) perceive their behavior and vice versa. In this chapter we study how
the clinical project managers self-perceptions compares with the perceptions of their respective colleagues
and vice versa. This chapter therefore addresses sub-research question 6.
6. To what extent do employees in a specific cultural context differ in their (self) perception
compared with their perception of others and vice versa (mutual perception)?
This study aims to test part of the research framework by comparing individual employees perception on
their own behavior with the perceptions they have of the behavior of their colleagues and vice versa (please
see Figure 6.1). This approach aims to optimize the ecological validity of the results from chapter 5 and
will contribute to cultural differences research by using mutual-perception methods, which have been to
date very rare (Ulijn et al., 2010).
Self-percep)on
Individual Employee
Behavior (IEB)
Mutualpercep)on
Figure 6.1 Comparing self-perceptions of own behavior with perceptions of others behaviors
155
The outline of this chapter is as follows: section 6.2 gives an overview of the methods and measures used,
the quantitative data collection process performed and the characteristics of the respondents within this
mutual perception study. Section 6.3 presents the results from the mutual-perception surveys, comparing
clinical project managers from Anglo-Saxon and Asian cultural groups in a radar diagram. Section 6.4
provides the conclusion and discussion of this chapter
6.2 Methods used
This study aims to understand the influence of cultural factors and personal preferences from both the
insider’s and outsider’s perspective; how people see things (self-perception), how do others perceive their
behavior and vice versa (mutual perception). Collecting data from multiple sources is a method that is
commonly used to avoid or minimize researcher bias (Miles and Huberman, 1994). This mutual perception
study will be conducted with the same group of 23 clinical project managers from the in-depth case study
from chapter 5. The 23 clinical project managers from the China, Japan, Malaysia, Korea, the Philippines,
Taiwan and Singapore (Asian implicit cultures) were invited to evaluate the colleagues from Australia and
New Zealand (Anglo-Saxon explicit cultures) on the dimensions assertiveness, responsiveness and
communication and vice versa. The same clinical project managers from both Asian and Anglo-Saxon
cultural backgrounds were also invited to evaluate their own perception on assertiveness, responsiveness
and communication. The clinical project managers were instructed how to complete the mutual perception
(MP) survey and asked to return the completed survey via return email to the researcher within 4-6 weeks.
The outcomes have not been discussed with the clinical project managers that have completed the MP
survey. In total each clinical project manager was expected to complete 3 evaluations for a total of 69
evaluations.
156
Measures
For the purpose of this study we have used the same survey as the mutual perception study from Ulijn et al
(2009). The mutual perception survey included a total of 27 items measuring assertiveness (11),
responsiveness (11) and communication (5). Each item was scored on a ten-point scale ranging from
'strongly disagree to strongly agree'. See appendix 9 for an example of the MP survey that was used in this
study. The mean scores for the dimensions assertiveness, responsiveness and communication are scored on
a scale from 1 - 9 and are plotted in a radar diagram similar to Halls (1995) compass diagram.
The radar chart visualizes the aggregate values of mean scores per item by cultural group. The mean values
for assertiveness, responsiveness and communication are compared to look at differences between the
respondents from Anglo-Saxon and Asian cultures. The outcomes are analyzed at group level by describing
and discussing the major differences per dimension between the two cultural groups (Anglo-Saxon versus
Asian cultures) to see to what extent self-perception differs from mutual-perception. A difference of mean
scores of > 3 points for each item of the behavioral dimensions assertiveness, responsiveness and
communication plotted in the radar diagram is qualified as a major difference.
Data collection
The same group of 23 clinical project managers from chapter 5 received an individual email with the
instructions how to complete the MP survey. The clinical project managers were expected to complete each
evaluation of 27 items of the mutual perception survey in 30-40 minutes. The CPM’s needed to complete
three evaluations; their own perception as it relate to assertiveness (ASR), responsiveness (RSP) and
communication (COM) and the perception of two other colleagues from different cultural backgrounds,
based in other affiliated offices. For example, Asian CPM were asked to evaluated Anglo-Saxon colleagues
and vice versa The CPM’s were required to complete the evaluations within 4-6 week after the invitation
email was distributed. Table 6.1 presents an overview of what and how mutual perceptions will be
compared between the clinical project managers from Anglo-Saxon and Asian cultural background. The
table shows the groups that are compared, and the type of perception by behavioral dimension.
157
Table 6.1 Overview of perceptions comparisons between Anglo-Saxon cultures versus Asian cultures for Assertiveness,
Responsiveness and Communication
Dimensions
Radar diagram 1
Radar diagram 2
Assertiveness
Asians perception of Anglo-Saxons
Anglo-Saxons perceptions of
versus Anglo-Saxons self perceptions
Asians versus Asians selfperceptions
Assertiveness
Radar diagram 3
Radar diagram 4
Anglo-Saxons self perceptions
Asians perceptions of Anglo-Saxon
versus Asians self-perceptions
versus Anglo-Saxon perceptions of
Asians
Responsiveness
Responsiveness
Radar diagram 5
Radar diagram 6
Asians perception of Anglo-Saxons
Anglo-Saxons perceptions of Asians
versus Anglo-Saxons self perceptions
versus Asians self-perceptions
Radar diagram 7
Radar diagram 8
Anglo-Saxons self perceptions
Asians perceptions of Anglo-Saxon
versus Asians self-perceptions
versus Anglo-Saxon perceptions of
Asians
Communication
Radar diagram 9
Anglo-Saxons self perceptions
versus Asians self-perceptions
Respondents’ characteristics
The clinical project managers were located in 7 affiliated offices, including the regional HQ in Singapore.
Out of the 23 clinical project managers, 11 (48%) completed the 3 evaluations each for a total of 33
evaluations. Table 6.2 shows the distribution of the total of 33 evaluations by cultural group, country of
birth and affiliated location they work from. The group includes 8 nationalities within the Asian cultural
group and 2 nationalities within the Anglo-Saxon cultural group. Eight clinical project managers with an
Asian cultural background each evaluated themselves and 2 colleagues with an Anglo-Saxon cultural
background located in another affiliated office in another country and vice versa for a total 24 evaluations.
Three clinical project managers with an Anglo-Saxon background each evaluated themselves and 2
colleagues with an Asian cultural background and vice versa for a total of 9 evaluations.
158
Table 6.2 Distribution of 10 respondents by cultural group, national culture, affiliated office and number of evaluations
_______________________________________________________________________________________________________
Cultural group
National Culture Affiliate Location
Respondents
Number of Evaluations
N=8
N=7
N = 11
N= 33
_______________________________________________________________________________________________________
Asian
China
China
2
6
Japan
Japan
1
3
Philippines
Singapore
1
3
Singapore
Singapore
1
3
Malaysia
Malaysia
2
6
Taiwan
Taiwan
1
3
Sub-total Asian
8
24
1
2
3
6
Anglo-Saxon
New-Zealand
Australia
New-Zealand
Australia
Sub-total Anglo-Saxon
3
9
_______________________________________________________________________________________________________
Total
11
33
_______________________________________________________________________________________________________
From the 12 (52 %) non-responding clinical project managers, 7 mentioned (all from Asian cultural
background) that they felt uncomfortable to evaluate the behaviors of their colleagues from other affiliated
offices, 3 mentioned (two from Asian and two from Anglo-Saxon cultural background) their busy schedule
and meetings for not being able to meet the deadline for completion and submission of the survey. Two
clinical project managers did not complete the evaluations in the right way, not all questions scored or
scored wrongly and could not be included to be analyzed. Despite the response rate of 11 respondents (33
evaluations, 48% of total), there was enough variation in nationalities and affiliated offices and both
cultural cluster were represented in the sample.
6.3 Results from self-perception and mutual perception
This section presents the mean scores of self-perceptions, perception of others and mutual perceptions
plotted in a radar diagram. The mean values have been compared to look at differences between the
respondents from Anglo-Saxon and Asian cultures. This analysis aimed at answering the research question
addressed in the introduction of this chapter. A summary of our findings is presented at the end of this
section.
159
Figure 6.2 shows the distribution of the mean values for the behavioral dimension assertiveness (ASR) by
item comparing self-perception – with perception of others (radar diagram 1 and 2) for both cultural
groups. Radar diagram 1 visualizes how individuals from Asian cultures perceive their colleagues from
Anglo-Saxon cultures and self-perceptions of assertiveness. Radar diagram 2 visualizes how individuals
from Anglo-Saxon cultures perceive their colleagues from Asian cultures and the self-perceptions of
assertiveness. Please note that the scores were on a 1-10 scale from strong disagreeing to strongly agreeing.
The higher the score the more the stronger agreement, the lower the score the stronger the disagreement of
the individual respondent with that item.
AsianspercofAng-Sax
Agn-Saxownperc
Ang-SaxpercofAsians
Authorita3ve
Authorita4ve
8
Demanding
9
Cau3ous
7
Demanding
6 7
5 6
Takingcontrol
Challinginggoals
4
4
Takingcontrol
7
2
5
4
5
1
7
8
7
Pushy
6
7
Cau4ous
Challinginggoals
4
5 6
1
0
7
Chargingahead
Quickmoving
4
6
Chargingahead
7
6
6
5
3
2
4
0
Quickmoving
8
8
7
5
5
3
8
8
8
6 7
4
5
Asiansownperc
5
7
6
Compromising
Pushy
5
Individualis3c
Compromising
7
Hardworking
Individualis4c
Diagram1
9
Diagram2
Hardworking
Figure 6.2 Assertiveness mean values of own perception and perception of others, Asian cultures versus Anglo-Saxon
cultures, and vice versa
Major differences (> = 3 points) in diagram 1 are found in the item taking control (Asian CPMs perceive
their Anglo-Saxon colleagues to tending to be less in control than their Anglo-Saxon colleagues perceive
themselves). Major differences (> = 3 points) in diagram 2 are found for the following items; authoritative
(Anglo-Saxon CPMs see their Asian colleagues as less authoritative than their Asian colleagues perceive
themselves); hardworking (Anglo-Saxon CPMs perceive Asian colleagues as tending to be more
hardworking than Asian CPMs perceive themselves) and demanding (Anglo-Saxon CPMs perceive Asian
colleagues as tending to be more demanding than Asian CPMs perceive themselves).
160
Figure 6.3 shows the distribution of the mean values for the behavioral dimension assertiveness by item
comparing self-perception – with self-perception (radar diagram 3) and mutual perception (radar diagram
4) of both cultural groups. Radar diagram 3 visualizes self-perception of Anglo-Saxon cultures versus selfperception of Asian cultures. Radar diagram 4 visualizes how individuals from Asian cultures perceive
their colleagues from Anglo-Saxon cultures and vice versa.
Ang-Saxownperc
AsianspercofAng-Sax
Asiansownperc
8
Demanding
7
6
9
7
8
7
8
Demanding
Cau3ous
Takingcontrol
4
8
5
3
8
3
5
1
Challinginggoals
4
4
2
4
7
5
1
0
0
Quickmoving
4
5
7
6
8
5 6
Takingcontrol
Challinginggoals
2
5
6
8
4
Cau4ous
7
5
5
Ang-SaxpercofAsians
Authorita4ve
Authorita3ve
6
7
7
Quickmoving
Chargingahead
8
5
7
7
Chargingahead
5
7
6
Pushy
5
7
6
6
7
7
6
6
Pushy
Compromising
7
6
Compromising
9
Individualis3c
Individualis4c
Hardworking
Diagram3
Hardworking
Diagram4
Figure 6.3 Assertiveness mean values of own perception and mutual perception, Asian cultures versus Anglo-Saxon
cultures, and vice versa
Major differences (> = 3 points) in diagram 3 are found in the following items: taking control (AngloSaxon CPMs perceive themselves as tending to be more in control while Asian CPMs perceive themselves
as tending to be less in control), cautious (Asian CPMs perceive themselves as tending to be more cautious
while Anglo-Saxon CPMs perceive themselves as tending to be less cautious). Major differences (> = 3
points) in diagram 4 are found in the following items: cautious (Anglo-Saxon CPMs perceive Asian
colleagues as tending to be more cautious and vice versa); demanding (Anglo-Saxon CPMs perceive Asian
colleagues as tending to be more demanding and vice versa); and hardworking (Anglo-Saxon CPMs
perceive Asian colleagues as tending to be more hardworking and vice versa).
161
Figure 6.4 shows the distribution of the mean values for the behavioral dimension responsiveness (RSP) by
item comparing self-perception – with perception of others (radar diagram 5 and 6) for both cultural
groups. Radar diagram 5 visualizes how individuals from Asian cultures perceive their colleagues from
Anglo-Saxon cultures and self-perceptions of responsiveness. Radar diagram 6 visualizes how individuals
from Anglo-Saxon cultures perceive their colleagues from Asian cultures and the self-perceptions of
responsiveness.
AsianspercofAng-Sax
Ang-SaxpercofAsians
Ang-Saxownperc
Consistent(methodical)
7
6
7
7
5
6
5
4
5
5 6
8 7
Factualratherthan
emo=onal
6
Sensi>ve
4
2
5
Preciseratherthan
inexact
TeamPlayers
0
5
8
7
8
6
Trus=ng
7
Preserveharmony
Factualratherthan
emo>onal
5
9
3
8
TeamPlayers
8
6
7
Trus>ng
9
Preserveharmony
Unpredictable
Diagram5
7
3
6
4
6
5
1
0
7
8
6
3
6
1
Preciseratherthan
inexact
Loyal
7
Quan>ta>veratherthan
qualita>ve
Sensi=ve
3
2
8
8
4
6
9
Taskratherthanpeople
oriented
Loyal
8
5
6
Quan=ta=veratherthan
qualita=ve
Consistent(methodical)
8
Taskratherthanpeople
oriented
Asiansownperc
Unpredictable
Diagram6
Figure 6.4 Responsiveness mean values of own perception and perception of others, Asian cultures versus Anglo-Saxon
cultures, and vice versa
In diagram 5 No major differences (> = 3points) are found. Major differences (> = 3 points) in diagram 6
are found in the following items; Anglo-Saxon colleagues perceive their Asian colleagues tending to be
more; Loyal, team player, trusting, preserving harmony, precise rather than inexact and task-oriented rather
than people-oriented and less unpredictable than Asian colleagues perceive themselves to be.
162
Figure 6.5 shows the distribution of the mean values for the behavioral dimension responsiveness (RSP) by
item comparing self-perception – with self-perception (radar diagram 7) and mutual perception (radar
diagram 8) of both cultural groups. Radar diagram 7 visualizes self-perception of Anglo-Saxon cultures
versus self-perception of Asian cultures. Radar diagram 8 visualizes how individuals from Asian cultures
perceive their colleagues from Anglo-Saxon cultures and vice versa.
Ang-Saxownperc
AsianspercofAng-Sax
Asiansownperc
Consistent(methodical)
Consistent(methodical)
8
Taskratherthanpeople
oriented
7
6
8
8
4
5
3
6
4
2
Quan;ta;veratherthan
qualita;ve
Sensi:ve
6 7
5
6
4
4 5
5
Preciseratherthan
inexact
TeamPlayers
3
5
0
9
6
8
TeamPlayers
3
4
6
Factualratherthan
emo:onal
Sensi;ve
7
2
1
0
7
7
5
8
3
6
5
1
Preciseratherthan
inexact
Loyal
7
8
5 6
6
Quan:ta:veratherthan
qualita:ve
9
Taskratherthanpeople
oriented
Loyal
7
Ang-SaxpercofAsians
7
6
Factualratherthan
emo;onal
Trus:ng
7
8
Preserveharmony
8
7
7
Trus;ng
9
Preserveharmony
Unpredictable
Diagram7
8
Unpredictable
Diagram8
Figure 6.5 Responsiveness mean values of own perception and mutual perception, Asian cultures versus Anglo-Saxon
cultures, and vice versa
Major differences (> = 3 points) in diagram 7 are found in the following items: loyalty (Anglo-Saxon tend
to perceive themselves tending to be more loyal than their Asian colleagues perceive themselves to be) and
trusting (Anglo-Saxon tend to perceive themselves as tending to be more trusting than their Asian
colleagues perceive themselves to be). Major differences (> = 3 points) in diagram 8 are found in one item;
team players (Anglo-Saxon perceive their Asian colleagues as tending to be more team players than the
Asian colleagues perceive their Anglo-Saxon colleagues to be team players).
163
Figure 6.6 shows the distribution of the total mean values for the five items for how both cultural groups
(mutual perception) perceive the communication and corporation with each other. There were no major
difference (>=3 points) between the two groups and there was one similar score for messages meaning that
both groups seems to agree that sometimes messages from either side can be sidetracked. CPMs from
Asian cultural background in general rate the communication with their Anglo-Saxon colleagues as Polite
(6); their directness of communication tended to be indirect (4); sometimes tends to be sidetracked (5); tend
to discuss sometimes more than one issue (5) and finally they rate the overall communication with their
Anglo-Saxon colleagues as just right (6).
CPMs from Anglo-Saxon origin tend to rate the communication with their Asian colleagues as very polite
(8); sometimes direct or indirect (5); sometimes tends to be sidetracked (5); mostly one issue that is
discussed (4) and finally they rate the overall communication with their Asian colleagues as good (7). The
overall communication trend between both groups indicates very polite communication, sometimes direct
or indirect and sidetracked, discussing more issues at the same time in a mostly friendly atmosphere.
COM-Asians
Com-AngSax
Politeness
8
7 8
6
5 6
4
Communica>on
3
7
6
Directness
2
1
4
5
0
5
4
5
Issuesdiscussed
Messages
Diagram9
Figure 6.6 Communication mean values of mutual perception, Asian cultures versus Anglo-Saxon cultures, and vice
versa
164
A summary of our findings from this section is presented below in table 6.3. The overview shows that selfperception revealed major differences in perception on 4 (2 ASR and 2 RSP) out of the 22 items. When
comparing self-perception and perception of others major differences are found in 9 items (2 ASR and 7
RSP) out of the 22 items. In addition the mutual perception comparison shows major differences in
perception of both groups on 3 ASR items and 1 RSP item. This mirror effect of mutual perception shows
how people see themselves within a certain organizational and professional cultural context and how they
see others within the same or other organizational and professional cultural context.
Table 6.3 Summary of the major differences for assertiveness, responsiveness and communication
Perceptions
Major differences > 3 ASR
Major differences > 3 RSP
Perception of
Asians perceive Anglo-Saxons to be
Anglo-Saxons perceive Asians to be
others vs. Self-
•
perception
Less in control than Anglo-Saxons
•
perceive themselves to be
More Loyal, team player, trusting,
preserving harmony, precise rather than
Anglo-Saxons perceive Asians to be
inexact and task rather than people
oriented and
•
Less authoritative
•
More hardworking/demanding than
•
Less unpredictable than Asians perceive
themselves to be
Asians perceive themselves to be
Self-perception vs.
Anglo-Saxons perceive themselves to be
Anglo-Saxons perceive themselves to be more loyal
Self-perception
More in control and less cautious
and trusting than their Asian colleagues perceive
Asians perceive themselves to be
themselves to be.
Less in control and more cautious
Asians perceive themselves to be less loyal and
trusting than their Anglo-Saxon perceive
themselves to be.
Mutual perception
Anglo-Saxons perceive Asians to be more
Anglo-Saxons perceive Asians to be more team
cautious, demanding and hardworking.
players than Asians perceive Anglo-Saxons to be
Asians perceive Anglo- Saxons to be less
team players.
cautious, demanding and hardworking
Perceptions: Communication (COM)
Major differences > 3
Mutual perception
Anglo-Saxons and Asians have the tendency to communicate very
politely, sometimes direct or indirect and sidetracked, discussing more
issues at the same time in a mostly friendly atmosphere.
165
6.4 Conclusions and discussion
In this chapter we studied to what extent the clinical project managers’ self-perception differs from the
perceptions of their respective colleagues based in different countries and vice versa. The respondents for
this study came from one multinational company and included a group of 23 clinical project managers from
Asian and Anglo-Saxon national cultural background (see also chapter 5). This chapter aimed to answer
sub-research question 6, To what extent do employees in a specific cultural context differ in their selfperception compared with their perception of others and vice versa (mutual perception)?
.
To answer this research question a mutual perception study was conducted in which 8 clinical project
managers with an Asian cultural background each evaluated themself and 2 colleagues with an AngloSaxon cultural background located in another affiliated office in another country and vice versa for a total
24 evaluations. Three clinical project managers with an Anglo-Saxon background each evaluated them self
and 2 colleagues with an Asian cultural background and vice versa for a total of 9 evaluations. A total of 33
evaluations were included in the analysis.
We found major differences (> 3 points), between Asian implicit cultures and Anglo-Saxons explicit
cultures, in two assertiveness items (taking control and cautious) and in two responsiveness items (loyal
and trusting) when comparing their self-perceptions. When comparing self-perceptions and perception of
others between both cultural groups, major differences were found in 9 items (2 ASR and 7 RSP) out of the
22 items. These findings indicate that collectivistic/implicit cultures (Asians) are perceived by
individualistic/explicit cultures (Anglo-Saxon) on the assertiveness items as tending to be: less
authoritative and more cautious, demanding and hard working. In addition individualistic /explicit (AngloSaxon) cultures are perceived by collectivistic/implicit (Asian) cultures on the assertiveness items as
tending to be: less cautious, demanding and hardworking, demonstrating a similar perception from both
groups of each other. The above findings were all acknowledge by the company’s leadership team. From
the leadership team perspective the lack of taking control and being too cautious was one of the reasons for
the lack of innovation within the company. They were a bit surprised that a relatively small survey
conducted in one of the teams has identified this issue, but were also pleased to notice that their gut-feel
was confirmed.
166
On the responsiveness items collectivistic/implicit cultures (Asians) are perceived by
individualistic/explicit cultures (Anglo-Saxon) as tending to be: less unpredictable and more; loyal, team
players, trusting, preserving harmony, precise rather than inexact and task rather than people oriented.
Furthermore individualistic /explicit (Anglo-Saxon) cultures are perceived by collectivistic/implicit (Asian)
cultures, as tending to be: less team players. This is not a surprise, because in collectivistic cultures people
are from birth onwards integrated into strong, cohesive in-groups, which throughout people’s lifetime
continue to protect them in exchange for unquestioning loyalty compared to individualistic cultures in
which the ties between individuals are loose: everyone is expected to look after himself or herself and his
or her immediate family (Hofstede et al., 2008).
The conclusions from this mutual study are further supported by findings from a large-scale Asia-Europe
mutual perception study (Asia in the Eyes of Europe, Europe in the Eyes of Asia) conducted throughout
2010- 2011. The study included 10 Asian ASEM (Asian European Meeting) participating countries:
Australia, China, India, Japan, Korea, Malaysia, New Zealand, Russia, Singapore, Thailand and 8 EU
(European Union) member states: Austria, Belgium, Denmark, France, Germany, Italy, Romania, United
Kingdom (Bersick, Chaban, Iglesias, Holland and Lenihan, 2012). To capture a detailed perception of Asia
in the EU countries a detailed daily analysis of 29 media outlets across Europe, a public opinion survey of
over 6000 respondents and face-to-face interviews of over 100 top European media professionals was
conducted. For the ASEM countries, 6000 news items were analysed, 7000 public opinion surveys and 200
elite interviews were conducted to paint a very detailed and multi-layered image of the perception of the
EU (Bersick et al., 2012).
The communication radar diagram showed that clinical project managers from Anglo-Saxon and Asian
cultural groups rated their cooperation and communication tending to be very polite, sometimes direct or
indirect and sidetracked, discussing more issues at the same time in a mostly friendly atmosphere. These
findings in relation to the directness and the sidetracking of the communication show similarities with
findings from Ting and Patron (2013). In this sense that mono-culturally, Anglo-Saxons tend to be direct
and discuss a single issue at the time and Asian’s tend to be indirect and somewhat sidetracked and
discussing several issues at once. Clinical project managers from Asia cultures (high context/implicit
cultures) might perceive the directness used by their Anglo-Saxon colleagues (low context/explicit
cultures) as drifting away from building long-term relationships. By contrast Anglo-Saxon clinical project
managers (low context/explicit cultures) could perceive rhetorical style of their Asian colleagues (high
context/implicit cultures) as out of focus and beating around the bush.
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For the communication dimension, it can be concluded that the directness and the sidetracking of the
communication is in line with the notion that members of collectivistic cultures, tend to maintain relational
harmony and emphasize group goals and needs. In contrast, members of individualistic cultures, such as
Australians, value individual autonomy and interests, and encourage competition (Lin and Miller, 2003).
Our findings further show similarities with findings in the literature (Zhu and Sun, 2004; Zhu, Nel and
Bhat, 2006) that in a mutual encounter both cultural groups tend to adjust their communicative behavior to
the other party in a polite way. The structured team meetings as a modus operandi within the clinical
project manager’s team may have played this adjusting role in affecting the directness or indirectness and
sidetracking of the communication as such preventing misunderstanding to happen. It could also be that the
professional code of conduct of the clinical project managers played a behavioral adjusting role in
streamlining the communication between the groups (Pieterse, 2012).
The findings indicate that self-perception alone only reveals part of the snapshot of how people in
organizations tend to behave and communicate. This mirror effect of mutual perceptions shows how people
see themselves within a certain organizational and professional cultural context and how they see others
within the same or other cultural contexts (Ulijn and St Amant, 2000). The leadership team acknowledged
this mirror effect and mentioned their concerns about the perceptions of both cultural groups on loyalty,
trust and being a team player. They felt that these items should have their immediate attention.
The specific information provided by this study helped the leadership team to make decisions, where to
intervene within or between both groups involved. As a result the leadership team initiated a series of
workshops to improve communication effectiveness within the clinical project managers teams and
between the clinical project managers and the management of the affiliated offices and the supportive
function including the finance department, logistics and clinical development functions.
Our finding that a common organizational culture seems to have less influence on how colleagues or
partners perceive each other’s behavior are rather similar to the findings from the mutual perception study
involving affiliated office within Unilever, from Hall, (1995). Individual employee perceptions of
colleagues from another cultural group or affiliated office may therefore be more influenced by individual
personal preferences and the professional cultural group that they are part of. These findings further
suggest that, cooperation among professionals may be more affected by what people think of each other in
a team than by how they perceive themselves (Eppink et al., 2010).
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It must however be noted, that the study from Bersick et al., (2012) suggested that mutual perceptions
between cultural groups can also be influenced by country specific environmental forces like media, key
opinion leaders and policy makers. These influencing factors have not been the focus of this study and
might be considered for future inter-company mutual perceptions studies.
In conclusion, our findings support the notion that the mutual perception research approach into cultural
differences has a valuable contribution. We can further conclude that research into cultural differences
based upon self-perception should be verified by the perception of others and mutual perception to get a
full picture of insider (self) and outsider (other) (Eppink et al., 2010). This study shows that studying
mutual perceptions is a unique approach that can provide a deepened understanding of others and their
expectations within a diverse cultural context (Chan, 2010). An understanding of mutual perceptions can
provide improved communications and guidance for managers in multinational companies and
governmental policy makers (Bersick et al., 2012).
This mutual perception study has used the compass survey involving 23 clinical project managers from one
team operating in one company, rather similar to a Unilever Intra company study conducted by Hall
(1995). The study aimed for ecological validity and provided valuable and insightful information that could
facilitate practical interventions to improve cross-cultural communication, it is however not without
limitations. The small sample in the single case study has delivered a full picture but only a single
snapshot from one team operating in a very large multinational organization. A study design with multiple
cases/teams with a substantially larger sample in the same company could provide both a full picture and
more snapshots that can be compared statistically. It is therefore a recommended next step to verify the
differences found in the assertiveness, responsiveness and communication dimensions between the Asian
and Anglo-Saxon cultural groups. A study that compares mutual perceptions of Asians versus AngloSaxons working in different industries can deliver further statistical validity of our findings.
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Chapter 7
Conclusions and discussion on the influence of cultural factors and
personal preferences on individual employee behavior
7.1 Introduction
Practical managerial problems how to differentiate between the influence of cultural factors and personal
preferences on individual employee behavior have been the main motivation for the start of this research.
We have explained why it is a problem for managers in multinational organizations to understand what
drives the behavior of individual employees and to differentiate between cultural influences and personal
preferences. Findings in the literature confirmed that misunderstanding between individual employees and
misinterpretations of employee behavior can ultimately lead to inefficiencies in organizations (Kumar et al,
2011; Nardon et al., 2011). The literature further shows that cultural differences studies have paid little
attention in differentiating the influence of cultural factors and personal preferences on employee behavior
(Zoogah et al., 2011). Most studies on cultural influence have only focused on the influence of single-level
factors of culture (Ulijn et al., 2010). Moreover the majority of studies have taken a rather etic research
approach or outsider’s view compared to an insider’s view or emic approach (Leung and Van de Vijver,
1996; Efferin and Hopper, 2006). Practical managerial problems and the gaps in the literature have
motivated us to formulate the initial central research question for this research:
What is the role of cultural and personal factors in the behavior of working individuals in a
culturally diverse organizational setting?
To answer this initial central research question, two contrasted cultural differences research approaches etic
and emic were studied. Figure 7.1 visualizes the approach taken for chapters 1 and 2 of this research.
To guide the model analysis two sub-questions were formulated, 1. To what extent can the influence of
cultural factors and personal preferences on individual employee behavior be theoretically disentangled and
2. Can a research framework be constructed that measures the perceived influence of cultural factors and
personal preferences on individual employee behavior?
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To answer these questions, we first reviewed cultural models from the etic perspective or from the
outsider's view of reality. The etic approach assumes that culture is a factor of influence, which explains
differences in cognition, learning and behavior between cultural groups. From the etic literature review, we
found that all cultural levels (national, professional and organizational cultures) are intertwined and related
and can be considered as key influencers of individual employee behavior within a given social context.
The cultural influence review also revealed that professional culture should be considered as a separate
level of cultural influence, next to national culture and organizational culture.
Motivation for
the research
Gaps in
literature
Chapter 1
Objective and
central research
question
Methods used in
this research
Cultural factors
RQ 1 & 2
Etic approach
or outsiders view
Behavioral intention
Emic approach
or insiders view
Chapter 2
Personal preferences
Figure 7.1 Overview of the research approach taken in chapters 1 and 2
Based on the analysis of cultural influence models we adopted the following cultural levels for this
research:
1. At the national level, we distinguished between, the rather individualistic Anglo- Germanic/Nordic
explicit cultures and the rather collectivistic Latin-Asian implicit cultures (Hofstede, 2008).
2. At the professional cultural level, we distinguished between, the operator, engineering and executive
cultures (Schein, 1994)
3. At the organizational cultural level, we distinguished between the incubator, family, Eifel Tower and
guided missile cultures (Trompenaars and Hampden-Turner, 2001).
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The cultural models review further suggested that individual employees behavior is not only affected by
the workplace but that the influence on individual employee behavior happens sequentially (first family,
then school then work), and simultaneously (by all three cultural levels at the same time). As such, cultural
factors play a critical role in personal interactions and individual relationships of employees. Consequently
they might affect commitment, collaboration, communication and trust between employees and ultimately
organizational efficiency and effectiveness. The way in which these cultural levels influence individual
employee behavior varies, depending on the geographical location of the company and the loose or tight
relationships between the cultural levels. For example, in the United States based companies, the influence
of organizational culture is assumed to be different from the influence of the national culture. Compared to
for example in Japan, where organizational and national cultural influence are assumed to be similar.
This notion drove us to address the question how individual employees perceive to be affected by these
cultural levels.
To answer this question we reviewed cultural influence models from the emic perspective or from the
insider's view of reality or through the eyes of the individual. An emic perspective is fundamental to
understanding how people perceive the world around them. Emic researchers assume that the best way to
understand a culture is to regard it as an integrated system. From the emic literature review, we found that
personal preferences can indeed be seen as an additional factor of influence on individual behavior next to
the cultural levels (national, professional and organizational). As such, within a combined etic-emic
perspective, the influence of culture and personal preferences can be theoretically distinguished as separate
variables of influence on individual employee behavior.
Within the etic research approach, mostly self-perception approaches are used as method for data
collection. This is in contrast to the emic research approach that uses both self-perception and mutualperception methods. We have recognized that in order to be able to understand individual employee
behavior, we need to understand not only the perception of each individual to see the way they see it
(insider’s view), but also the perception of others (outsider’s view) and mutual-perception (insider’s and
outsider’s) to have a more diverse and integrated complete picture. We concluded that the mutualperception research approach into cultural differences has additional value to offer than what selfperception studies have delivered so far. We have also looked at the strengths and weaknesses of both the
etic and emic research approaches and explored cultural influence models that differentiate between factors
of influence on individual behavior using a combined etic-emic research approach.
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Inspired by the models of Poortinga et al., (1990) and the conceptual framework of Karahanna et al.,
(2006), a simplified research framework was proposed for this research, that theoretically distinguishes
between the influence of cultural factors and personal preferences on behavior intention, assuming that
both cultural factors and personal preferences directly or indirectly influence behavioral intention and
actual behavior. Within this research behavioral intention is based upon thinking styles and behavioral
patterns that are originating from genetics, internal thought processes and environmental influences. The
thinking styles include analytical, structural, social, and conceptual thinking, and the behavioral patterns
include expressiveness, assertiveness, and flexibility. The research framework has also been proposed in
order to overcome the previously discussed weaknesses of both the etic and emic approaches. It is based
upon a combined etic and emic research perspective that integrates insights from the various influences on
individual cognition and socio-analytic behavioral theories. It is an attempt to include the mutual
relationship between cultural levels of influence, the individual perspective and the environment as a
dynamic interaction unfolding over time. Findings from the literature review have also resulted in an
adjusted central research question and a set of related sub-research questions that have shaped the structure
of this research and the sequence of the empirical studies performed.
To what extent do personal preferences (PP) influence individual behavior intentions (BI) more than
national culture (NC), professional culture (PC) and organizational culture (OC) do?
By answering this adjusted central research question and the related sub-questions we aimed to formulate
recommendations on how unintended misunderstandings between employees and managers within a
culturally divers organizational setting can be avoided. This research also aimed to contribute to the
cultural differences research by using a mutual-perception study set-up with a combined etic approach
(quantitative), with complementary fieldwork collected by an emic approach (qualitative).
This final chapter summarizes the results from the respective studies presented in the chapters 3, 4, 5 and 6
and in doing so answers the main research question of this research. In section 7.2 an overview of the
results is presented and discussed based on the research questions. In section 7.3 the limitations of this
research are addressed. The theoretical and practical relevance is discussed in section 7.4. Future studies
are presented in section 7.5.
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7.2 Overview and discussion of the results: answering the research questions
Figure 7.2 visualizes the approach taken in chapters 3, 4, 5 and 6 of and how within a combined etic and
emic research approach, the empirical studies were executed. By performing the empirical studies, this
research aimed to answer the respective sub-questions and the central research question. In doing so we
aimed to provide clarity of the role of cultural factors and personal preferences on working individuals’
behavior with the prospect to formulate practical suggestions how to avoid unintended misunderstandings
in a culturally diverse organizational environment.
RQ 3
Rather etic
Psychometric study 1
RQ 4
Rather emic
Explorative
quantitative study 2
Chapter 4
RQ 5 & 6
Combined etic/emic
In-depth case study 3
Chapter 5
Chapter 6
Chapter 3
Figure 7.2 Overview of the research approach taken in chapters 3 to 6
In chapter 3 we selected and tested the validity and reliability of a psychometric instrument to find out its
suitability for further use within the proposed simplified research framework proposed in chapter 2. This
chapter addressed sub-research question 3.
3. Which measure can be used to validly and reliably measure the perceived influence of cultural
factors and personal preferences on individual employee behavior?
For answering sub-question 3, we have reviewed the most widely used psychometric instrument the Big
Five Inventory (BFI) and an alternative the less known Emergenetics instrument. The following set of
criteria that derived from the research framework was used for instrument selection: 1. The ability of the
instrument to measure both thinking styles and behavior patterns. 2. Available and accessible via an online
link. 3. Available in translated version to use within Anglo-Germanic/Nordic and Latin-Asian cultures. 4.
Availability of score per item (100) per individual.
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The Emergenetics survey was used because it fulfilled the above requirements and therefore fitted best for the
use in the empirical studies conducted in this research. To use the instrument for empirical studies in a
culturally diverse environment we conducted several reliability and validity tests, of which the results
indicated that the instrument met the criteria for test re-test reliability, construct and face validity within a
culturally diverse setting.
The instrument was also tested in a culture and gender differences study for the usefulness of the
instrument in cultural different context. The relatively similar mean scores (no statistically significant
differences) between the Anglo-Germanic/Nordic group and the Latin-Asian group indicated validity in a
culturally diverse setting. We concluded that the instrument was therefore useful for measuring individual
behavioral intention (based upon thinking styles and behavioral patterns) in the empirical studies conducted
in this research and suitable to test the research framework proposed from the literature review in chapter 2.
However for further validation at group level we recommended to use substantially larger sample sizes as the
instrument was developed for understanding and accommodating individual differences in thinking and
behavior and not to compare nomological differences between groups.
In chapter 4 we tested the research framework and compared the self-perception on the influence of
cultural factors and personal preferences on behavioral intentions between two national cultural groups;
individualistic-explicit cultures versus collectivistic-implicit cultures (Hofstede et al, 2008) and between
three professional cultures, operator, engineering and executive (Schein, 1996). The chapter addressed subresearch question 4.
4. To what extent do employees in diverse cultural contexts differ in their self-perception on how
cultural factors and personal factors influence their own behavior?
For answering sub-research question 4, we conducted a quantitative explorative study that tested the
research framework by measuring the individual perceptions of the influence of cultural factors and
personal preferences on behavioral intention. To this end we compared two cultural groups AngloGermanic/Nordic and Latin-Asian cultural groups, with different professions (operators, engineering and
executives) and from various organizations. The overall results indicated that the personal preferences
mostly influences behavioral intention, followed by professional, organizational and national cultures.
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No major differences were found in the mean influence scores between the Anglo-Germanic/Nordic
cultural group and the Latin-Asian cultural group. The observed mean influence scores between operators,
engineering and executives and males and females were also rather similar. We concluded that personal
preferences and professional culture might be more important than organizational culture and national
culture in regard to why individual employees behave the way they do within the organization. This finding
might help to prevent misunderstandings and miscommunications between individual employees. We
further concluded that, changes in personal preferences and professional culture may affect organizational
efficiency and effectiveness more than changes in organizational culture. This finding may also have
consequences for how problems of organizational change can be resolved or prevented or how during
mergers and acquisitions better and more efficient organizational integration and alignment can be best
accomplished.
In chapter 5 we tested the research framework by studying the differences between, the self-perception of
individual employee behavior and tallied observed day-to-day behavior of these individual employees. This
chapter addressed sub-research question 5.
5. To what extent do employees in a specific cultural context differ in their self-perception on how
cultural factors and personal preferences influence their own behavior compared to their actual
observed behavior?
For answering question 5, we conducted an in-depth biopharmaceutical case study with a team of clinical
project managers from different countries in Asia and Australia and New Zealand. Three observations were
conducted, where the individual behavior intention scores (based upon thinking styles and behavioral
patterns) were compared with the scores of tallied observed behavior of the clinical project managers from
both cultural groups during weekly team meetings. The focus of these observations was on the interaction
and communication between the presenting clinical project manager and the project director.
We concluded, that minor differences were observed within the expressiveness and assertiveness
behavioral patterns. However, within the flexibility behavioral patterns major individual differences were
observed. The majority of participants were willing to be adaptable and accommodating irrespective of
their behavioral intention scores. This was observed in the behavioral patterns of clinical project managers
from both Asian and Anglo-Saxon cultural backgrounds.
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This corresponds with the earlier remark on mutual adjusting as a sign of professionalism of global
managers in the biopharmaceutical sector. These observations might also be related to the fact that the
majority of the group had an analytical thinking style. Individuals with an analytical thinking style tend to
look for data and scientific proof. This might indicate that this group was satisfied with the data and the way
the information was provided during the meeting and felt comfortable enough to flex out of showing their
‘normal’ behavior of focused and firm. It might also be that due to the thinking style of the leader, (5ATS*)
he/she was able to provide the right data, meaning that the leader can relate to the majority (seven of out
nine) of the groups thinking style (A), in a structured way (T) and presented in a relational, collaborative,
empathic, and supportive way (S). It might also be that the importance of the meeting has influenced the
participants to show adaptable and accommodating behavior to demonstrate their commitment and
contribution to the project. Overall the observational scores of each individual participant was more or less
in line with the percentile scores from the EG survey with some major individual deviations that could be
explained based upon a certain requirement or situation in the session. These observations indicate that
behavioral intention (based upon thinking styles and behavioral patterns) is a good predictor of actual
individual employee behavior as suggested by Zhang (2001, 2002) and Karahanna et al (2006)
In chapter 6 we compared the clinical project managers own perceptions with perceptions of their
colleagues and vice versa. This chapter addressed sub-research question 6.
6. To what extent do employees in a specific cultural context differ in their self-perception compered
with their perception of others and vice versa (mutual perception)?
To answer question 6 we conducted a quantitative mutual perception study by comparing self-perception,
perception of others, and mutual perceptions on behavioral dimensions assertiveness, responsiveness and
one communication dimension between respondents from Anglo-Saxon and Asian cultural backgrounds.
We found major difference in mutual perception scores in the behavioral dimensions assertiveness and
responsiveness between respondents from Anglo-Saxon explicit cultures and Asian implicit cultures. In
regard to the communication dimension, we concluded that the directness and the sidetracking of the
communication between the two cultural groups show similarities with findings in the literature.
We also found support in the literature that in a mutual encounter both cultural groups tend to adjust their
communicative behavior to the other party in a polite way.
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We further suggested that the professional culture within the clinical project manager’s team might have
played a behavioral adjusting role in streamlining the communication between the groups.
The findings indicated that self-perception alone only reveals part of the snapshot of how people in
organizations tend to behave and communicate. This mirror effect of mutual-perceptions shows how people
see themselves within a certain organizational and professional cultural context and how they see others
within the same or other contexts. Other indications from this study are that research into the influence of
personal and cultural factors on employee behavior should be based upon mutual perception to get a full
picture of insiders (self) and outsider (others). Because the mutual-perception approach provides a
deepened understanding of others and their expectations within a diverse cultural context, it can be a
guidance for managers in multinational companies and governmental policy makers to improve inter
cultural mutual communications.
Now that we have addressed all the sub-questions we can now answer the main research question of this
research. Main research question:
To what extent do personal preferences influence individual behavioral intentions more than
national culture, professional culture and organizational culture do?
From this research’s problem statement we noted that managers in a multinational companies, often had
difficulties understanding when and how employee behavior was influenced by culture and how to act
accordingly. We have learned from this research that in some cases when individual employee behavior
may, depending on the situation, indeed be culturally driven but in some cases it seemed to be more
personally driven. The findings from this research suggest that the way co-workers and superiors would
tend to behave in a certain situation, would be more related to their thinking style and behavioral patterns
which are mostly influenced by personal preferences first and then next by cultural factors.
With that in mind we could now assume that the behavior of the majority of individual employees their
colleagues and superiors would probably be first driven by their personal preferences and their individual
perceptions of the colleagues involved in the situation and then next by cultural factors. This research also
found that self-perceptions and the perceptions of colleagues and superiors are of critical importance to get
a broader perspective and an understanding why an individual person behave the way he/she does and how
colleagues and superiors behave the way they do.
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In regards to cultural factors we found indications that the behavior of a certain professional might be more
driven by the modus operandi of the professional group than by the organizations culture or the nationality
of that professional. The importance of professional culture is also stressed in the finding that the loosetight relationship between national and organizational culture is more dependent on how strong the
influence of professional culture is rather than on the company’s organizational culture or geographical
location of the company. Individual personal preferences and professional culture might therefore be more
important than organizational culture and national culture when organizational efficiency and effectiveness
are at stake. Based on the above findings from the empirical studies the central research question can be
answered as follow: personal preferences and professional culture have more influence on behavioral
intention and Individual employee behavior than organizational culture and national culture.
7.3 Limitations of this research
This research was based on a multi-method approach combining quantitative and qualitative data collection
methods. With this approach we aimed to look for an alternative set of explanations that are complimentary
to a classical sociological surveys and provides more practical relevance. This approach was also chosen
because the multi-method approach is increasingly used within business and management research and it
supported the objectives of this research, which is to look for high ecological validity of our outcomes.
While we believe that this research contributes to furthering cross-cultural research, it is not without its
limitations.
The research framework supported by validated theories and the multi-method approach made it possible to
theoretically differentiate and empirically study the influence of cultural and personal factors on behavior
intention and to compare behavioral intention with actual observed behavior. The first challenge faced was
selecting an appropriate instrument that could measure behavior intention (based upon thinking styles and
behavioral patterns) to translate the theoretical framework into operationable empirical research that takes
the personal perception, perceptions of others and mutual perception into account.
The Emergenetics (EG) instrument was selected and used with the permission of Emergenetics Inc.
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However there was a restriction to explicitly mention the Cronbach alpha for the reliability of each individual
item of the questionnaire, because that would have infringed on the commercial interests of this firm in this
PhD thesis. We have acknowledge and respected this limitation, and where able to demonstrate encouraging
signals of validity and reliability of the EG instrument (self-perception) and for the usefulness of the EG
instrument in a culturally diverse environment. However, although based on sound statistical analysis the
results were based on relatively small sample sizes. A study with larger sample sizes comparing cultural
groups would be recommended to confirm the validity of the EG instrument for the use in cross-cultural
research.
To look for meaningful outcomes for both theory and managerial practice of this research the quantitative
surveys (self-perception, perception of other and mutual perception) and qualitative (observations) have
been closely linked. This allowed us to link the results from the quantitative explorative study with the
quantitative and qualitative results from the in-depth case study. We were therefore able to compare selfperceptions with actual behavior and self-perception with mutual perceptions within a cultural diverse
context. However this data collection method caused the following research operational challenges. In the
explorative study and the case study respondents were invited to first complete the online EG survey that
included 100 items and the extended EG survey with 400 items. The amount of items and the requirement
to force-rank the 400 items might have negatively affected response rates. In addition the mutual
perception questions used in the case study were sometimes seen as too personal, which have also lowered
the response rates, specifically amongst the participants with an Asian cultural background. Another
limitation was that the explorative study included slightly different cultural group (Anglo-Germanic/Nordic
versus Latin-Asian cultures) than the in-depth case study that included only Anglo-Saxon and Asian
cultures. This non-representation of the Germanic Nordic cultures and Latin cultures in a case study setting
has however not greatly affected the conclusions of this research. For the qualitative data collection we
could only rely on notes (hearing and seeing) during the observations, since video and audiotaping was not
allowed, due to the sensitivity of the information that was shared during the update meetings. This
limitation to crosscheck observations might have affected the tallied behavior scores.
To mitigate the lack of a second observer, all behavioral intention scores and tallied behavioral
observations have been checked by the researcher in individual face-to-face meetings and calls between
researcher and clinical project managers.
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The above-mentioned limitations of the combined approach should be considered in relation to the
conclusions and findings from this research. However, despite the limitations we believe that we have
made a contribution in serving the international business community as a whole and the very relevant
biopharmaceutical sector.
7.4 Theoretical and practical relevance of this research
Despite the increased criticism on the etic cultural differences research approach (Leung and Van de
Vijver, 1996; Efferin and Hopper, 2006) this outsider’s perspective is still mostly used to compare and
analyze cultural differences at group level. The emic research approach, takes an insider’s view and links
individual employees and their adapted behavioral patterns to the ecological setting in which they work and
live. This approach has received less attention and is therefore less used in cultural differences research that
compares and analyzes cultural differences at an individual level (Gudykunst and Ting Toomey, 1988;
Bohner and Dickel, 2011). Due to their different research perspectives the etic (outsider’s) research
approach is used for the testing of hypotheses and the emic (insider’s) approach is used for exploratory
research. However, both the etic and emic research approach are predominately using self-perception
methods. In reference to Morris et al., (1999) and Ulijn et al., (2010), cultural differences research that
have used a combined etic (outsider’s) and emic (insider’s) perspective with self-perception and mutual
perception data collection methods are very rare.
This research explored the possibilities to conduct cultural differences studies with a combined etic-emic
approach, which can provide both theoretical clarity and suggestions for managerial practice. For the data
collection, the self-perception Emergenetics (EG) and extended (EG) surveys, a mutual perception (MP)
survey and coded behavioral observation score cards (based on the EG survey) were used. The data was
analyzed both quantitatively using SPSS and qualitatively through descriptions of mutual perceptions and
observed behavior. We have first used a self-perception (EG) survey to identify individual behavior
intention (based upon thinking styles and behavioral patterns) to then measure the perceived influence of
cultural factors and personal preferences on behavior intention (see Browning 2006). The next step in the
research process was through observations; comparing self-perception on behavior intention with actual
behavior (see Ulijn and St Amant, 2000). The final step in the research process was comparing the
individual perceptions of self, with perception of others and vice versa using mutual-perception surveys
(see also Hall, 1995 and Eppink et al., 2010).
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Our findings show that the proposed research framework made it possible to compare and analyze the
influence of cultural factors and personal preferences at an individual level, through the eyes of the
individual employees, their colleagues and superiors and vice versa. Differentiating the samples at a
national, professional and organizational cultural level, allowed us to compare and analyze the selfperceptions and mutual perceptions at a cultural group level. This research approach provided richer data
that goes beyond generalizations at a cultural group level. The insider’s view of the perception of each
individual to see the way they see it, the perception of others and the researchers perceptions via
observations (outsider’s view) led to a sort of triangulation approach that provided a more diverse and
complete picture (Van Brussel, 2012).
It must be noted that we have combined, quantitative and qualitative methods not for the purpose of cross
validating the outcomes but for complementary purposes. The insider’s and outsider’s views provided these
complimentary insights from different angles, which have enriched our understanding. The first angle (the
explorative quantitative study) is an understanding how individuals from the different cultural groups
perceived the influence of cultural factors and personal preferences on behavioral intention. This study
showed statistical indications that personal preferences have the most influence on behavioral intentions
and that these outcomes apply for both of Anglo-Germanic/Nordic and Latin-Asian culture. However,
through the second angle of understanding (case study) we were able to find out how individuals from
these cultural groups perceive their own behavioral intention, compared to how they actually behave.
This angle revealed that how individuals actually behave relates to both their behavioral intentions (based
upon their unique thinking style and behavioral patterns), influenced by the performed leadership style, the
task at hand, the importance of the issue or the meeting or the international organizational context
(biopharmaceutical industry).
The third angle, allowed understanding of how individuals within these cultural groups perceive each
other’s behavior. This perspective showed that on some behavioral dimensions, the Anglo-Saxon and Asia
cultural groups are more or less aligned with Hofstede’s individualistic and collectivistic dimension scores,
but on some they are not aligned which is in line with the findings from the mutual perception study
conducted by Ulijn et al., 2009. The indication of our finding that Anglo-Saxon explicit cultures and Asian
implicit cultures have major differences in the behavioral dimensions assertiveness and responsiveness are
supported by findings from a large-scale Asia-Europe mutual perception (Asia in the Eyes of Europe,
Europe in the Eyes of Asia) study that was conducted throughout 2010-2011(Bersick et al., 2012).
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This alignment of findings from the single in-depth case study with other mutual perception studies
demonstrates that, measuring and assessing the influence on behavioral intention and actual employee
behavior derives from knowledge of the setting gained by field experience, again suggesting the value of
combining qualitative and quantitative methods. However, despite this alignment of the results a largescale mutual perception case study, that includes multiple companies and from multiple countries would be
recommended to further verify the differences in assertiveness and responsiveness scores between the two
cultural groups.
This research has contributed to cultural differences research: by linking quantitative data collection
methods (self or others and mutual perception surveys) with qualitative data collection methods
(observations) we were able to compare self-perceptions of behavior intention with actual observed
behavior and mutual perceptions using the same sample. We have demonstrated that it is possible to
operationalize cultural differences research by combining the strengths of both the etic-emic research
approach while mitigating their respective weaknesses. We also showed the added value of comparing
outcomes from self-perception surveys with perception of others, mutual-perceptions and observations to
allow richer data analysis options in cultural differences research. The above findings support a more
frequent use of the combined etic-emic multi-method approach in cultural differences research, based upon
self-perception and mutual perception data collection methods. The research further suggests the need to
move beyond outcome evaluations and suggest a more holistic cultural differences research approach,
which makes it possible to complement, self-perception outcomes with mutual perception and
observations.
This research acknowledges the practical need within multinational companies to understand why
employees and managers with different functions and from different national cultural backgrounds behave
the way they do. Understanding how employee behavior is influenced and shaped by both cultural and
personal factors could help manager to recognize these differences, and adapt their management style
accordingly. This is important because if managers are to work effectively in a complex and culturally
diverse context, they will have to have the agility to respond emphatically and effectively to practices and
values that differ from their own cultural expectations and personal practices (Javidan and House, 2001).
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The results from this research further suggest that an individual employees personal preferences and
professional background mostly influence that person’s individual behavior, irrespective of the
organizational or national cultural context. From a more practical perspective personal preferences and
professional cultures should therefore be considered when organizational change within a culturally diverse
environment is at stake. The concept of behavior intention defined in this research as an individual person’s
unique thinking styles and behavior patterns might be an alternative vehicle to help individual employees
to efficiently communicate beyond national, organizational and professional cultural boundaries. By
mutually understanding their colleagues or superiors thinking styles and behavioral patterns individual
employees might be able to better relate, connect and engage with each other.
In daily practice this means that colleagues with an analytical thinking style (appreciating; mathematics,
analysis and data) who are generally quiet reserved and focused can relate to and understand a colleague
with a social thinking style (appreciating caring, giving and empathic) who is generally outgoing, driven
and easy-going. As such understanding the insider’s perception and the outsider’s perception might help to
prevent misunderstandings and miscommunications in a culturally diverse organizational environment.
For the managerial practice it means that in order to present and interpret spoken and written information in
a similar manner, managers and employees might need to first understand their own perceptions and
preferences and those of their colleagues. The mutual understanding of how each team member collects
and digest information based upon thinking styles might result in a common communication style (modus
operandi), resulting from a common professional modus operandi. This common communication style can
create a common platform that facilitates effective and efficient communication between individual
employees, irrespective of different professional, organizational and national cultural backgrounds,
geographical location and languages used.
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7.5 Future studies
Culture is a complex and dynamic phenomenon, which has been mostly studied from an etic perspective
using self-perception methods. We have assumed that by theoretically differentiating between the influence
of cultural and personal factors on behavior intention that we could better understand why individual
employees behave the way they do in a culturally diverse setting. From a more practical point of view this
insight in the self-perception, perception of others and mutual-perception could help managers to
understand why behaviors of colleagues and superiors can be rather more culturally driven or more
personally driven. Our findings indicate that personal preferences/attitudes and the education and training
affects colleagues and superiors behavior more than the organization they work for or the country of birth.
Implicating that personal preferences and professional culture should be taken into consideration when
organizational efficiency and effectiveness is at stake. This could mean that if, for example, companies are
engaged in joint ventures, mergers and acquisitions or strategic alliances, the alignment of personal
preferences and professional modus operandi or professional cultural fit might have more impact to get
alignment of organizational cultures within the joint venture or strategic alliance (Duysters et al., 2010).
It could be argued that personal preferences alignment and professional cultural fit should be part of the
cultural fit process besides strategic fit and operational fit, if it concerns cross-border merger and
acquisitions and strategic alliances. Future research could focus on this organizational alignment in order to
understand the role of personal preferences and professional cultural fit in the case of cross-cultural or
cross-border cooperation’s between multinational organizations.
In reference to Silverman (2011) this research aimed to provide an insider’s and outsider’s snapshot of
individual employees perception of how both cultural factors and personal preferences influence individual
behavior and how these perceptions differ between cultural groups. Future studies that go beyond that
snapshot could continue to explore the combined etic-emic approach to further expand the knowledge
gained from this research. For example it could be recommended to consolidate and verify our findings
from the biopharmaceutical case study within a large scale multiple case study setting covering different
companies in different locations using mutual perception surveys involving multiple professions similar to
the Unilever study performed by Hall (1995). Alternatively a similar case study could be done in a more
low-technology industry (commodities or retail) environment to see if outcomes are similar or different
from a high-technology industry environment.
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Future studies could also further explore testing the concept of behavioral intention (based upon thinking
styles and behavioral patterns) as a predictor for actual behavior using other psychometric instruments and
larger sample sizes within individualistic versus collectivistic cultures to allow analysis at a cultural group
level.
A final thought: connecting and engaging at an individual level might bring the insider’s into closer contact
with the outsider’s. It may lead to better understanding of each other’s self-perceptions and mutualperceptions, which might help developing a sensitivity to each other’s ways of life which is very crucial to
the success of our social and business interactions in an increasingly more complex and globalized world.
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Summary
We live in an increasingly more complex and globalized world, which has led to a tremendous increase in
cross-cultural contacts. The diversity of the workforce, the use of different languages and communication
styles has created many difficulties to effectively communicate within multinational organizations.
The differences in cultural backgrounds of the sender and receiver, made it even more difficult to
understand and interpret each other’s words and behaviors, leading to miscommunication at an individual
level, misinterpretations at a team level and inefficiencies at an organizational level. As a consequence,
managers in multinational organizations are mainly confused how the behavior of individual employee’s
with different professions and national cultural background is influenced by cultural expectations and
personal practices of others within the organization. Because of this confusion they struggle to effectively
manage their increasingly culturally diverse workforces. The literature shows that there is not one universal
way to manage or influence these complex and intertwined processes. As such, work methods that seem to
be working in one cultural environment might not work in another cultural environment. That is why
managers in multinational organizations are facing many challenges, for example how to become
competent in cross-cultural awareness and practices and how to master a variety of modus operandi to
connect and engage with their teams of professionals and superiors. Developing a mutual sensitivity and
understanding of each other’s perceptions, might lead to less confusion in what is culturally or personally
influenced behavior. Providing some clarity in how employee behavior is influenced and shaped by either
cultural factors or personal preferences might help managers to recognize these differences and to have the
agility to respond positively and effectively to practices and values that differ from their own cultural
expectations and personal practices. This research has aimed to look for answers to help clarify the
managerial confusion between rather culturally or personally influenced employee behavior.
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Central research question
These practical managerial problems and the gaps in the literature have motivated us to formulate the initial
central research question for this research, “what is the role of cultural and personal factors in the behavior
of working individuals in a culturally diverse organizational setting”. To answer this initial central research
question, two sub-questions were formulated, 1. To what extent can the influence of cultural factors and
personal preferences on individual employee behavior be theoretically disentangled and 2. Can a research
framework be constructed that measures the perceived influence of cultural factors and personal
preferences on individual employee behavior?
Two contrasting cultural research approaches were
analyzed and provided an insiders and outsiders perception on how the different cultural levels (national,
organizational and professional culture) influence individual employee behavior. The analysis also revealed
that cultural factors and personal preferences could be differentiated as two factors influencing behavioral
intention as a predictor of actual behavior. Based on these finding a research framework was proposed to
operationalize further empirical research.
The research framework included the influencing factors; cultural factors (based upon national,
professional and organizational culture) and personal preferences and the influenced factor behavioral
intention (based upon thinking styles and behavioral patterns). Within the framework, behavioral intention
is viewed as the best predictors of actual behavior as it relates to a person’s own perception of their
thinking styles and behavioral patterns. The framework is based on the combined etic-emic research
approach, which allows both a cultural group-level analysis and an individual-level analysis. At group
level, we have compared between country clusters, and differentiated between Anglo-Germanic/Nordic
versus Latin-Asian cultures. We further differentiated at a national cultural level between individualistic
and collectivistic, and between low context-explicit versus high context-implicit cultures. At the
professional cultural level we differentiated between operator, engineering and executive cultures and at
the organizational level between, incubator, family, Eiffel Tower and guided missile cultures. Finally, we
differentiated between the loose-tight relationship between the different cultural levels national and
organizational culture and with professional culture as a separate level of cultural influence.
From the learning’s and insights derived from the etic and emic literature review the following revised
central research question was formulated: To what extent do personal preferences influence individual
employee behavior more than national culture, professional culture and organizational culture do?
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Research methods
The motivation for this research comes from personal managerial experiences in multinational
organizations combined with the objective to take a nuance view as a cross-cultural research. This research
therefore preferred using multi-method combining exploratory empirical studies and quantitative methods
followed by an in-depth biopharmaceutical case study combining quantitative with qualitative methods.
First, a rather etic psychometric study was conducted, using self-perception surveys to test an instrument
that measures behavioral intention. Second, an emic explorative study was conducted, using self-perception
surveys to identify the influence of cultural factors and personal preferences on behavioral intention. Third,
a rather combined etic and emic in depth case study was conducted, using observation score cards to
compare outcomes from the self-perception on behavioral intention with tallied actual behavior in a
culturally diverse setting. Within the same case study participants a mutual-perception survey was used to
compare self-perception and perception of others.
This sequential research approach allowed us to capture different perceptions with richer data resulting in a
better understanding of the influence of cultural factors and personal preferences on behavioral intention
and simultaneously provided an explorative and descriptive overview of how perceived behavioral
intention compares with actual individual employee behavior from respondents with a similar professional
and organizational cultural background and from Anglo-Saxon and Oriental national cultures.
Answering the research questions
In order to drive the operationalization of the empirical studies and answer the central research question, 4
additional sub-questions were formulated. To answer sub-question 3, which measure can be used to validly
and reliably measure the perceived influence of cultural factors and personal preferences on individual
employee behavior? We studied, if the selected Emergenetics psychometric instrument showed satisfying
reliability and validity qualities, measuring behavioral intention (based upon thinking styles and behavioral
patterns). We further investigated if the instrument could be used for measuring individual differences
between Anglo-Germanic/Nordic cultures and Latin-Asian cultures. The results from several reliability
and validity tests, indicated that the instrument met the criteria for, construct and face validity, test re-test
reliability and could be used for measuring behavioral intention.
We further concluded that there were relatively similar mean scores for behavioral intention between the
two cultural groups, indicating that the instrument was useful for measuring individual behavioral intention
(based upon thinking styles and behavioral patterns) within a culturally diverse setting.
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To answer sub-question 4, to what extent do employees in diverse cultural contexts differ in their selfperception how cultural factors and personal factors influence their own behavior?”
We studied, how Anglo-Germanic/Nordic cultures and Latin-Asian cultures and members from operator,
engineering and executive cultures differ in their perception on the influence of cultural factors and
personal preferences on behavioral intention. The results from this quantitative explorative study showed
that personal preferences had the lowest mean influence score indicating that it has the most influence on
behavioral intention, followed by professional, organizational and national culture. Furthermore, no major
differences were observed in the mean influence scores between the two cultural groups. The mean
influence scores between the three professional cultures were also rather similar. We concluded that
personal preferences and professional culture might be more important than organizational culture and
national culture in regard to how different professional groups behave within an organization.
To answer sub-question 5, to what extent do employees in diverse cultural contexts differ in their selfperception on how cultural factors and personal factors influence their own behavior compared to their
actual observed behavior? We studied, how the perceived individual behavioral intentions scores compare
with actual observed behavior between respondents from Anglo-Saxon cultures and Asian cultures. No
major discrepancies were observed within the expressiveness and assertiveness behavioral patterns.
However, the observations for the flexibility behavioral patterns showed that the majority of participants
were willing to be adaptable and accommodating irrespective of their behavior intention scores. This was
observed in the behavioral of clinical project managers with an Asian and Anglo-Saxon cultural
background. We further concluded that, to demonstrate their commitment and contribution to the project,
the clinical project managers, showed adaptable and accommodating behavior which might be related to
the tendency of analytical thinking in the team, the thinking style of the team-leader or the importance of
the information shared in the meeting to perform a certain task.
To answer sub-question 6, to what extent do employees in a specific cultural contexts differ in their selfperception compared with their perception of others and vice versa (mutual perception)? We studied, how
the perceived mutual perception scores (based upon assertiveness, responsiveness and communication)
differ between respondents from Anglo-Saxon and Oriental cultures. We found major difference in mutualperception scores in the behavioral dimensions assertiveness and responsiveness between respondents from
Anglo-Saxon and Oriental cultures.
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In regard to the communication dimension, we concluded that the directness and the sidetracking of the
communication show similarities with findings in the literature that in a mutual encounter both cultural
groups tend to adjust their communicative behavior to the other party in a polite way. We further suggested
that the professional culture within the clinical project manager’s team might play a behavioral adjusting
role in streamlining the communication between the groups. The findings indicated that self-perception
alone only reveals part of the snapshot of how people in organizations tend to behave and communicate.
Conclusions and recommendations
From the research conducted in this research, we can conclude that, personal preferences and professional
culture have more influence on behavioral intention and on individual employee behavior than
organizational culture and national cultures do. This conclusion applies within both rather individualistic
cultures and collectivistic cultures. We further found indications that personal preferences and professional
culture may also influence the loose-tight relationship between national culture and organizational culture
irrespective of company’s geographical location. The theoretical recommendations focus around the eticemic multi-method research approach taken in this research. This research demonstrated the possibility to
operationalize cultural differences research by combining the strengths of both the etic and emic research
methods while mitigating their respective weaknesses.
The combined research approach, allowed to do research through the eyes of the individual to see it the
way they perceive it. By verifying outcomes from self-perception surveys with perception of others, mutual
perceptions and observations we obtained richer data more background information about the respondents
and a variety of analysis options. It also allowed comparing the self-perceptions and mutual-perceptions
between different cultural groups. It is therefore recommended to conduct more mutual perception studies
in cultural differences research. However, this combined approach may require some further development,
specifically in regard to the data collection challenges associated with the relatively sensitivity of the
questions, sensitivity to review colleagues and superiors and the relative long surveys (100- 400 items)
associated with mutual perception studies. It is therefore recommended to conduct more mutual perception
studies in order to explore how this type of multi-method cultural differences research can be further
developed.
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The practical recommendations focus around results from this research, which suggest that in order to
present and interpret spoken and written information in a similar manner, managers and employees might
need to first understand their own perceptions and preferences and those of their colleagues. The mutual
understanding of how each team member collects and digest information based upon thinking styles might
result in a common communication style (modus operandi), resulting from a common professional modus
operandi. This common communication style can create a common platform that facilitates effective and
efficient communication between individual employees, irrespective of different professional,
organizational and national cultural backgrounds, geographical location and languages used.
Research limitations
Within this research we came across research limitations that are associated with the complexity to collect
self-perception and mutual perception data from respondents from 28 different countries and the
observations done on location in Asia. The respondents from the quantitative explorative study needed to
complete, three surveys for a total of 535 questions. The amount of questions might have lowered the
response rate. Furthermore, the researcher could only rely on notes (hearing and seeing) during the
observations, which might have influenced the scores of the observed behavior.
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195
Samenvatting (Dutch)
De wereld waarin wij leven wordt steeds complexer en geglobaliseerder en dit leidt tot een enorme
toename in crossculturele contacten. De diversiteit van de beroepsbevolking alsmede het gebruik van
verschillende talen en communicatiestijlen leveren veel moeilijkheden op die een effectieve communicatie
binnen multinationale organisaties in de weg staan.
De verschillen in de culturele achtergrond van de zender en de ontvanger bemoeilijken het begrijpen en
interpreteren van elkaars woorden en gedragingen zelfs nog meer, wat leidt tot miscommunicatie op
individueel niveau, misinterpretaties op teamniveau en inefficiëntie op organisatorisch niveau. Hierdoor
kampen managers in multinationale organisaties voornamelijk met verwarring over hoe het gedrag van
individuele werknemers met verschillende beroepen en nationale culturele achtergronden wordt beïnvloed
door culturele verwachtingen en persoonlijke praktijken van anderen in de organisatie. Deze verwarring
maakt dat zij moeite hebben om hun in cultureel opzicht steeds diversere werknemers effectief te managen.
Uit de literatuur blijkt dat er niet één universele manier is waarop deze complexe en met elkaar verweven
processen kunnen worden beheerd. Werkmethoden die in de ene culturele omgeving effectief lijken,
hoeven dit daarom nog niet per se in een andere omgeving ook te zijn. Daarom zien managers in
multinationale omgevingen zich voor veel uitdagingen gesteld, bijvoorbeeld hoe zij competentie verwerven
in crosscultureel bewustzijn en crossculturele praktijken, en hoe zij een verscheidenheid aan modus
operandi onder de knie krijgen waarmee zij kunnen omgaan met hun teams van professionals en
superieuren. Het ontwikkelen van een wederzijdse gevoeligheid voor en begrip van elkaars percepties zou
kunnen leiden tot minder verwarring over wat cultureel of persoonlijk beïnvloed gedrag is. Het bieden van
enige helderheid in hoe het gedrag van werknemers wordt beïnvloed en gevormd door culturele factoren
dan wel persoonlijke voorkeuren, zou managers van pas kunnen komen bij het herkennen van deze
verschillen en hun de behendigheid kunnen geven om positief en effectief te reageren op de praktijken en
waarden die afwijken van hun eigen cultureel bepaalde verwachtingen en persoonlijke praktijken. Dit
onderzoek heeft tot doel het zoeken naar antwoorden en het helpen wegnemen van de verwarring bij
managers met betrekking tot cultureel dan wel persoonlijk beïnvloed gedrag van werknemers.
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Centrale onderzoeksvraag
Deze praktische managementproblemen en de lacunes in de literatuur hebben ons gemotiveerd tot het
formuleren van de eerste centrale onderzoeksvraag: 'welke rol spelen culturele en persoonlijke factoren in
het gedrag van werknemers in een cultureel diverse organisatorische setting?' Voor het beantwoorden deze
vraag zijn twee subvragen geformuleerd, te weten: 1) in welke mate kan de invloed van culturele factoren
en persoonlijke voorkeuren op het gedrag van een individuele werknemer theoretisch worden ontrafeld? en
2) kan er een onderzoekskader worden geconstrueerd waarmee de waargenomen invloed kan worden
gemeten van culturele factoren en persoonlijke voorkeuren op het gedrag van een individuele werknemer?
De analyse van twee contrasterende benaderingen van cultureel onderzoek heeft een insiders perceptie en
een outsiders perceptie opgeleverd op hoe de verschillende culturele niveaus (nationaal, organisatorisch en
professioneel) het gedrag van een individuele werknemer beïnvloeden. Uit de analyse kwam ook naar
voren dat culturele factoren en persoonlijke voorkeuren konden worden onderscheiden als twee factoren
die van invloed zijn op gedragsintentie als voorspeller van daadwerkelijk gedrag. Op basis van deze
conclusies is er een onderzoekskader voorgesteld voor verder empirisch onderzoek.
Het onderzoekskader omvatte de volgende beïnvloedingsfactoren: culturele factoren (op basis van
nationale, professionele en organisatorische cultuur) en persoonlijke voorkeuren, alsmede de beïnvloede
factor gedragsintentie (op basis van denkstijlen en gedragspatronen). In het onderzoekskader wordt
gedragsintentie gezien als de beste voorspeller van daadwerkelijk gedrag omdat dit is gerelateerd aan de
perceptie van die persoon van zijn of haar eigen denkstijlen en gedragspatronen. Het kader is gebaseerd op
de gecombineerde etic-emic onderzoeksbenadering, die een analyse mogelijk maakt op zowel
cultuurgroepsniveau als op individueel niveau. Op groepsniveau hebben we een vergelijking gemaakt
tussen landenclusters en hierbij onderscheid aangehouden tussen Anglo-Germaanse/Noordse culturen en
Latijns-Aziatische culturen. Verder hebben we op nationaal cultureel niveau onderscheid gemaakt tussen
individualistische en collectivistische culturen en tussen culturen met een lage context (expliciet) en een
hoge context (impliciet). Op professioneel cultureel niveau hebben we onderscheid gemaakt tussen
operator-, engineering- and executive-culturen en op organisatorisch niveau tussen incubator-, family-,
Eiffel Tower- and guided missile-culturen. Tot slot hebben we onderscheid gemaakt tussen de losstrakrelatie tussen nationaal en organisatorisch als culturele niveaus en met professioneel als een
afzonderlijk niveau van culturele invloed.
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Op basis van het geleerde en de inzichten die zijn ontleend aan de studie van de etic- en emic-literatuur is
de volgende gereviseerde centrale onderzoeksvraag geformuleerd: 'in welke mate zijn persoonlijke
voorkeuren meer van invloed op het gedrag van een individuele werknemer dan nationale cultuur,
professionele cultuur en organisatorische cultuur dit zijn?'
Onderzoeksmethoden
De motivatie voor dit onderzoek vloeit voort uit persoonlijke managementervaringen in multinationale
organisaties, gecombineerd met het doel van een genuanceerde blik op crosscultureel onderzoek. Voor dit
onderzoek ging de voorkeur uit naar een multimethode-aanpak waarin verkennende empirische studies zijn
gecombineerd met kwantitatieve methoden gevolgd, door een diepgaande casus in de biofarmaceutische
industrie. Hierin zijn kwalitatieve en kwantitatieve methoden gecombineerd.
Ten eerste is er een psychometrische etic-studie uitgevoerd, waarin zelfbeoordelingsenquêtes zijn gebruikt
voor het testen van een meetinstrument voor gedragintentie. Ten tweede is een verkennende emic-studie
uitgevoerd, waarin aan de hand van zelfperceptie-enquêtes de invloed werd vastgesteld van culturele
factoren en persoonlijke voorkeuren op gedragsintentie. Ten derde is er een gecombineerde etic- en emicdieptecasus uitgevoerd waarbij met waarnemingsscorekaarten uitkomsten van de zelfperceptie op
gedragsintentie werden vergeleken met geregistreerd daadwerkelijk gedrag in een cultureel diverse setting.
Onder dezelfde casusdeelnemers werd er via een enquête over wederzijdse perceptie een vergelijking
uitgevoerd naar zelfperceptie en perceptie van anderen.
Deze sequentiële onderzoeksaanpak heeft ons in staat gesteld om verschillende percepties met rijkere data
vast te leggen. Het heeft geleid tot een beter begrip van de invloed die culturele factoren en persoonlijke
voorkeuren hebben op gedragsintentie. Tegelijkertijd heeft deze aanpak een verkennend en beschrijvend
overzicht geboden van hoe waargenomen gedragsintentie zich verhoudt tot daadwerkelijk individueel
werknemergedrag van respondenten met een overeenkomende professionele en organisatorische culturele
achtergrond en uit Angelsaksische en Aziatische nationale culturen.
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Beantwoorden van de onderzoeksvragen
Voor het stimuleren van de operationalisering van de empirische studies en het beantwoorden van de
centrale onderzoeksvraag, zijn er vier extra subvragen geformuleerd. Voor het beantwoorden van subvraag
3 (met welke methode kan de waargenomen invloed van culturele factoren en persoonlijke voorkeuren op
individueel werknemergedrag op een geldige en betrouwbare manier worden gemeten?) hebben we
bestudeerd of het geselecteerde psychometrisch instrument van Emergenetics bevredigende
betrouwbaarheid en validiteit opleverde bij het meten van gedragsintentie (op basis van denkstijlen en
gedragspatronen). Verder hebben we bestudeerd of het instrument toegepast zou kunnen worden voor het
meten van individuele verschillen tussen Anglo-Germaanse/Noordse culturen en Latijns-Aziatische
culturen. Uit de resultaten van verschillende betrouwbaarheids- en validiteitstests bleek dat het instrument
voldeed aan de criteria voor construct- en indruksvaliditeit, test/hertestbetrouwbaarheid en geschikt was
voor het meten van gedragsintentie.
Ook concludeerden we dat er tussen de twee culturele groepen relatief overeenkomende gemiddelde scores
voor gedragsintentie voorkwamen, wat aangaf dat het instrument geschikt was voor het meten van
individuele gedragsintentie (op basis van denkstijlen en gedragspatronen) in een cultureel diverse setting.
Voor het beantwoorden van subvraag 4 (in welke mate verschillen werknemers in verschillende culturele
contexten in hun zelfperceptie van hoe culturele factoren en persoonlijke factoren hun eigen gedrag
beïnvloeden?) hebben we bestudeerd hoe Anglo-Germaanse/Noordse culturen en Latijns-Aziatische
culturen en leden van operator-, engineering- en executive-culturen verschillen in hun perceptie van hoe
culturele factoren en persoonlijke voorkeuren van invloed zijn op gedragsintentie. De resultaten van deze
kwantitatieve verkennende studie lieten zien dat persoonlijke voorkeuren de laagste gemiddelde
invloedscore had, wat aangeeft dat het de meeste invloed heeft op gedragsintentie, gevolgd door
professionele, organisatorische en nationale cultuur. Daarnaast zijn er geen belangrijke verschillen
waargenomen in de gemiddelde invloedscores tussen beide culturele groepen. Ook de gemiddelde
invloedscores tussen de drie professionele culturen kwamen nogal overeen. We hebben geconcludeerd dat
persoonlijke voorkeuren en professionele cultuur wellicht belangrijker zijn dan organisatorische cultuur en
nationale cultuur als het erom gaat hoe verschillende professionele groepen zich in een organisatie
gedragen.
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Voor het beantwoorden van subvraag 5 (in hoeverre verschillen werknemers in uiteenlopende culturele
contexten in hun zelfperceptie van hoe culturele factoren en persoonlijke factoren van invloed zijn op hun
eigen gedrag in vergelijking met hun daadwerkelijk waargenomen gedrag?) hebben we bestudeerd hoe
individuele gedragsintentiescores zich verhouden tot daadwerkelijk waargenomen gedrag tussen
respondenten uit Angelsaksische en Aziatische culturen. Er zijn geen belangrijke discrepanties
waargenomen in de gedragspatronen voor expressiviteit en assertiviteit. Echter, de waarnemingen voor de
gedragpatronen voor flexibiliteit toonden aan dat deelnemers in meerderheid bereid waren om flexibel en
meegaand te zijn, ongeacht hun scores op het gebied van gedragsintentie. Dit werd waargenomen in het
gedrag van klinisch projectmanagers met een Aziatische en een Angelsaksische culturele achtergrond.
Verder concludeerden we dat, om hun betrokkenheid bij en bijdrage aan het project te tonen, de klinisch
projectmanagers flexibel en meegaand gedrag lieten zien, wat gerelateerd kan zijn met de neiging tot
analytisch denken binnen het team, de denkstijl van de teamleider of het belang van de informatie die in de
bijeenkomst werd gedeeld om een bepaalde taak uit te voeren.
Voor het beantwoorden van subvraag 6 (in hoeverre verschillen werknemers in een specifieke culturele
context in hun zelfperceptie, vergeleken met hun perceptie van anderen en vice versa (wederzijdse
perceptie)?) hebben we bestudeerd hoe de waargenomen scores voor wederzijdse perceptie (gebaseerd op
assertiviteit, responsiviteit en communicatie) verschillen tussen respondenten uit Angelsaksische en
Oosterse culturen. We hebben tussen respondenten uit deze Angelsaksische en Oosterse culturen in de
gedragsdimensies assertiviteit en responsiviteit aanzienlijke verschillen aangetroffen in de scores voor
wederzijdse perceptie.
Voor wat betreft de dimensie communicatie, concludeerden we dat de directheid en omslachtigheid in
communicatie overeenkomsten laten zien met resultaten in de literatuur dat in een ontmoeting met elkaar,
beide culturele groepen geneigd zijn om hun communicatief gedrag ten opzichte van de andere groep op
beleefde wijze aan te passen. Verder stelden we voor dat de professionele cultuur binnen het team van de
klinisch projectmanagers een gedragsaanpassende rol zou kunnen spelen in het stroomlijnen van de
communicatie tussen de groepen. De resultaten gaven aan dat zelfperceptie op zich slechts een deel laat
zien van de momentopname van hoe werknemers in organisaties geneigd zijn om zich te gedragen en te
communiceren.
200
Conclusies en aanbevelingen
Uit dit onderzoek kunnen we concluderen dat persoonlijke voorkeuren en professionele cultuur meer van
invloed zijn op gedragsintentie en op gedrag van individuele werknemers dan het geval is met
organisatorische cultuur en nationale culturen. Deze conclusie geldt zowel voor redelijk individualistische
culturen als voor collectivistische culturen. Verder hebben we aanwijzingen gevonden dat persoonlijke
voorkeuren en professionele cultuur ook van invloed kunnen zijn op de los-strakrelatie tussen nationale
cultuur en organisatorische cultuur, ongeacht de geografische locatie van het bedrijf. De theoretische
aanbevelingen richten zich op de etic-emic multimethode-benadering die in dit onderzoek is toegepast. Het
onderzoek heeft aangetoond dat het mogelijk is om onderzoek naar cultuurverschillen te operationaliseren
door de sterke kanten van de etic- en emic-onderzoeksmethoden te combineren en tegelijkertijd hun
respectieve zwakke punten te verzwakken.
De gecombineerde onderzoeksbenadering heeft ons in staat gesteld onderzoek te verrichten vanuit het
perspectief van het individu en te zien hoe hij/zij waarneemt. Door de resultaten van zelfperceptie-enquêtes
te verifiëren met de perceptie van anderen, wederzijdse percepties en waarnemingen, hebben we rijkere
data en meer achtergrondinformatie over de respondenten en verschillende analyseopties vergaard. Dit
maakte het ook mogelijk om de zelfpercepties en wederzijdse percepties tussen verschillende culturele
groepen met elkaar te vergelijken. Het is daarom raadzaam om in het onderzoek naar cultuurverschillen
meer de nadruk te leggen op de studie van wederzijdse perceptie. Deze gecombineerde benadering vergt
voor deze studie waarschijnlijk meer ontwikkeling, met name voor wat betreft de uitdagingen bij het
verzamelen van gegevens in relatie tot de relatieve gevoeligheid van de vragen, de terughoudendheid om
collega's en superieuren te beoordelen en de relatief lange enquêtes (100 - 400 items). Het is daarom
raadzaam om verdere studies naar wederzijdse perceptie uit te voeren en te bestuderen hoe dit soort
multimethode-onderzoek naar cultuurverschillen verder kan worden ontwikkeld.
De praktische aanbevelingen richten zich op de resultaten van dit onderzoek. Deze wijzen dat om
gesproken en geschreven informatie op eenzelfde manier te presenteren en te interpreteren, managers en
werknemers eerst hun eigen percepties en voorkeuren en die van hun collega's moeten begrijpen.
Wederzijds begrip van hoe elk teamlid op basis van denkstijl informatie verzamelt en verwerkt, zou kunnen
leiden tot een gezamenlijke communicatiestijl (modus operandi) die voortvloeit uit een gezamenlijke
professionele modus operandi.
201
Via deze gezamenlijke communicatiestijl kan een gezamenlijk platform worden gecreëerd waarmee
effectieve en efficiënte communicatie mogelijk is tussen individuele werknemers, ongeacht verschillende
professionele, organisatorische en nationale culturele achtergronden, geografische locaties en gebruikte
talen.
Beperkingen in het onderzoek
Tijdens dit onderzoek zijn we op beperkingen gestuit die te maken hebben met de complexiteit van het
verzamelen van gegevens over zelfperceptie en wederzijdse perceptie onder respondenten uit 28
verschillende landen en de waarnemingen die zijn verricht op locatie in Azië. De respondenten van de
kwantitatieve verkennende studie moesten in totaal 535 vragen, verdeeld over drie enquêtes,
beantwoorden. De hoeveelheid vragen heeft mogelijk het responspercentage gedrukt. Verder kon de
onderzoeker tijdens de waarneming alleen vertrouwen op aantekeningen (horen en zien), wat van invloed
zou kunnen zijn geweest op de scores van het waargenomen gedrag.
202
203
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List of Appendices
Appendix 1:
Example of an Emergenetics profile report
Appendix 2:
Example of the different combinations of thinking styles and behavioral patterns
Appendix 3:
Example of the Emergenetics online survey
Appendix 4:
Example email, with an invitation for respondents to complete the Extended EG survey
Appendix 5:
Example of the Extended EG survey
Appendix 6:
Thinking styles and behavioral patterns, 128 respondents, explorative quantitative study
Appendix 7:
Thinking styles and behavioral patterns, of 23 respondents, in-depth case-study
Appendix 8:
Example of the details of the CPMs team meeting agenda
Appendix 9:
Observation score-card for 6 respondents, case study session I
Appendix 10:
Observation score-card for 9 respondents, case study session II
Appendix 11:
Observation score-card for 14 respondents, case study session III
Appendix 12:
Organogram of clinical project managers team, 23 respondents, in-depth case-study
Appendix 13:
Description of the clinical research process, as part of the clinical project managers daily tasks
Appendix 14:
Example of the mutual perception (MP) survey
220
Appendix 1: Example of an Emergenetics profile report
EMERGENETICS | GROUP
EGLSC2001 - JANUARI 19, 2012
HOW YOU THINK: PERCENTAGES
ANALYTICAL = 20%
Clear thinker
Logical problem solver
Enjoys math
Rational
Learns by mental analysis
CONCEPTUAL = 34%
Imaginative
Intuitive about ideas
Visionary
Enjoys the unusual
Learns by experimenting
STRUCTURAL = 16%
Practical thinker
Likes guidelines
Cautious of new ideas
Predictable
Learns by doing
SOCIAL = 29%
Intuitive about people
Socially aware
Sympathetic
Empathic
Learns from others
How you Behave: Percentiles
How you Think: Percentiles
HOW GROUP COMPARES TO THE GENERAL POPULATION
31
Analytical
31
24
Structural
45
Social
53
Conceptual
65
Expressiveness
Quiet
Alone
Reserved
Peacekeeper
Amiable
Easy-Going
Competitive
Driving
Telling
26
Flexibility
Emergenetics, LLC, 1991 2010.
Gregarious
66
Assertiveness
General Population
Defined Situations
0
10
20
Strong Opinions
30
40
50
Diff POV
Others Before Self
60
80
70
Geil Browning, Ph.D. / Wendell Williams, Ph.D.
221
Spontaneous
90
100
Appendix 2: Example of different combinations of thinking styles and behavioral patterns
Percentage Chart by Emergenetics Profile Types
Cert Amsterdam Sept 2013 - 2013-09-13
Population-at-Large
AT**
17%
23%
**SC
12%
23%
A**C
11%
0%
*TS*
11%
15%
A*S*
6%
8%
*T*C
2%
0%
ATS*
13%
8%
A*SC
13%
15%
AT*C
5%
0%
*TSC
4%
0%
ATSC
1%
0%
A***
1%
0%
*T**
2%
0%
**S*
1%
8%
***C
2%
0%
Behavior Percentages
EXP
ASR
Percent (0 - 33)
8
15
8
Percent (34 - 66)
38
38
69
Percent (67 - 100)
54
46
23
Emergenetics, LLC, 1991.
222
This Group
FLX
Appendix 3: Example of the Emergenetics (EG) online survey
Emergenetics Questionnaire
Instructions
Answer the questions in a way that best describes how you perceive or think about yourself at this moment in time
This is not a test, and there are no right or wrong answers. You are only indicating your preferences
Do not consider how others think about or perceive you
Do not consider how you were, on average, over the past years
All questionnaire information will be kept confidential.
Rate each of these statements on a scale from 1 to 7: 1=least like me 2 3 4 5 6 7=most like me
Please answer ALL 100 questions of the following survey
1. When faced with a problem, I seek the opinions of friends.
2. I would like a job with a lot of rules and regulations.
3. People would describe me as someone who has a lot of common sense.
4. I openly express affection for other people.
5. I enjoyed studying algebra and math.
6. I easily handle ambiguous or uncertain situations.
7. I argue for my point of view.
8. I actively seek-out social situations.
9. I enjoy reading articles about scientific subjects.
10. I don't mind pushing to the front of the line.
11. People would describe me as easy to get along with.
12. One of my goals is building the self-esteem of people I meet.
13. I tend to be very sensitive to the feelings of people around me.
14. I am skeptical and cautious of new or untried ideas.
15. I am highly predictable.
16. I get bored easily.
17. I enjoy solving problems that require a lot of thinking.
18. I am artistic.
19. I am cheerful and even-tempered in most situations.
20. I wish things would stay the same.
21. I often search for new ways to solve old problems.
22. I am very conscious of time.
23. I find it easy to be patient with difficult people.
24. I easily understand complex subjects.
25. I often start conversations with strangers.
26. I am musical.
27. I often use examples from personal experience in conversation.
28. I get excited when something is new and different.
29. I put human feelings and needs before my own success and achievement.
30. I am a leader more often than I am a follower.
31. I enjoy being admired by others.
32. I like to listen to music.
33. I like working for long periods of time on one thing.
34. My friends come from all races, beliefs and cultures.
35. I enjoyed studying geometry in school.
36. I acknowledge errors and move on.
37. I enjoy a good intellectual discussion.
38. I find it hard not to be competitive.
39. I like bold colors and textured materials.
40. People usually know how I'm feeling just by looking at me.
41. I enjoy producing ideas more than drawing conclusions.
42. I find humor in most situations.
43. I occasionally get in trouble because I act on impulse.
44. When I get involved in a new subject, I study it thoroughly.
45. Imagination is the key to the future.
46. I prefer to learn a new task by having someone show me.
47. I tend to make decisions based on feeling more than analysis.
48. I put a lot of energy into handling several tasks at the same time.
49. I have to get my hands on something in order to really understand it.
50. I enjoy reading business articles.
223
51. It's easy for me to get along with people who are very different.
52. I probably have more friends than most people.
53. I keep my feelings to myself.
54. I frequently speak in generalities.
55. I usually know my bank balance.
56. Most of my decisions are based on rigorous analysis.
57. I enjoy activities which require organizing.
58. I have a driving personality.
59. I tend to look at things as black and white as opposed to shades of grey.
60. I learn better by listening to an explanation than by reading a book.
61. I prefer to follow established rules and guidelines.
62. I always consider other people's feelings before acting.
63. I enjoy challenging people to see what they are made of.
64. I am good at reading maps.
65. I become easily upset by unexpected events.
66. I often draw pictures and diagrams when describing things.
67. I like to play it safe and go by the book.
68. I pick up on the vibrations of people around me.
69. I am a practical-minded, logical person.
70. I often recognize relationships between seemingly unrelated objects.
71. I can make people laugh.
72. I enjoy reading romance novels.
73. I am more supportive than most people.
74. I can intuitively sense solutions to problems.
75. I always want to know how something works.
76. I'm usually poor at details but grasp the big picture.
77. I treat mistakes as learning opportunities rather than failures.
78. I have a strong interest in science and mathematics.
79. I sometimes know things without knowing how I know.
80. People often seek my advice when faced with difficult social situations.
81. I tend to talk in specific terms.
82. I enjoy problems that require logical thinking.
83. I don't like to draw attention to myself.
84. I will go to almost any length to avoid confrontation.
85. I am interested in abstract concepts and ideas.
86. Keeping peace is more important than being right.
87. I prefer to keep a fast pace.
88. I have a very active imagination.
89. I am usually very agreeable to suggestions.
90. I like to work alone.
91. I like telling people what to do.
92. I find it hard to sit still longer than 30 minutes at a time.
93. I like quiet chats with friends and neighbors.
94. I am most comfortable with slow, methodical progress.
95. I enjoy working with things more than with people.
96. I tend to make decisions based on a sensory (visceral) sensation in my stomach.
97. I am very comfortable in new and unusual surroundings.
98. It's easy for me to see pictures in my mind's eye.
99. I remember people by the sound of their voice.
100. I like to have reading material prior to any class, lecture or meeting I'm attending.
224
Appendix 4: Example email, with an invitation for respondents to complete the Extended EG survey
Van : [email protected]
Datum : 12/04/2015 01:41
Aan : Participant
Onderwerp : PhD project; Second cultural influence questionnaire
Dear Participant,
Via this email I am seeking your support for the second part of my PhD research project. Enclosed is a
excel document with your scores/answers in (numbers) of the first Emergenetics questionnaire. Please
follow the instructions below to complete the attached questionnaire (Excel document).
Based upon the definitions of national, professional and organizational culture and personal preferences
(see below), you will be asked to review your answers to the 100 questions from the previous Emergenetics
(online) questionnaire. Please rate on a scale from 1 to 4 the influence of the Cultures and Personal
Preferences on your answer to the specific question
1 = the most influence and 4 = least influence
To ensure the validity of the survey, I do ask you to go through all 100 questions. Please note that you need
to complete all of the 400 boxes. Numbers 1- 4 can only be used one time per question.
Please save and return the completed form to the following email address: [email protected]. If you have
any questions please do not hesitate to contact me directly at +3162235 1074. I would appreciate if you
could return the form within the next ten days, preferably before April 24th, 2015.
Please be assured that confidentiality is guaranteed. Your contribution to my research is greatly
appreciated. Thanks again. Ron Byron (PhD Candidate)
Ron Byron, PhD Candidate
Faculty of Management, Science & Technology
Valkenburgerweg 177 P.O. Box 2960 6401 DL Heerlen The Netherlands
M +31 622351074
[email protected]
http://www.linkedin.com/in/ronbyron
225
Appendix 5: Example of the Extended Emergenetics survey
CPP Survey: Respondent #
Pleasereviewyouranswerstothe100questionsseefirstcollum(yourscore),baseduponthedefinitionofCulture(NC.OC&PC)&Personalfactors(PF)(seeemail) Example: Influence of
Pleaserateonascalefrom1to4theinfluenceofCulture(NC,OC&PC)&PersonalPreferences(PP)onyouranswertothespecificquestion
1=themostinfluence234=leastinfluence
Please find below the scores/answers in (numbers) you have given at the first Emergenetics questionaire
You have rated each of these statements on a scale from 1 to 7: 1=least like me 2 3 4 5 6 7=most like me.
1. When faced with a problem, I seek the opinions of friends.
2. I would like a job with a lot of rules and regulations.
3. People would describe me as someone who has a lot of common sense.
4. I openly express affection for other people.
5. I enjoyed studying algebra and math.
6. I easily handle ambiguous or uncertain situations.
7. I argue for my point of view.
8. I actively seek-out social situations.
9. I enjoy reading articles about scientific subjects.
10. I don't mind pushing to the front of the line.
11. People would describe me as easy to get along with.
12. One of my goals is building the self-esteem of people I meet.
13. I tend to be very sensitive to the feelings of people around me.
14. I am skeptical and cautious of new or untried ideas.
15. I am highly predictable.
16. I get bored easily.
17. I enjoy solving problems that require a lot of thinking.
18. I am artistic.
19. I am cheerful and even-tempered in most situations.
20. I wish things would stay the same.
21. I often search for new ways to solve old problems.
22. I am very conscious of time.
23. I find it easy to be patient with difficult people.
24. I easily understand complex subjects.
25. I often start conversations with strangers.
26. I am musical.
27. I often use examples from personal experience in conversation.
28. I get excited when something is new and different.
29. I put human feelings and needs before my own success and achievement.
30. I am a leader more often than I am a follower.
31. I enjoy being admired by others.
32. I like to listen to music.
33. I like working for long periods of time on one thing.
34. My friends come from all races, beliefs and cultures.
35. I enjoyed studying geometry in school.
36. I acknowledge errors and move on.
37. I enjoy a good intellectual discussion.
38. I find it hard not to be competitive.
39. I like bold colors and textured materials.
40. People usually know how I'm feeling just by looking at me.
41. I enjoy producing ideas more than drawing conclusions.
42. I find humor in most situations.
43. I occasionally get in trouble because I act on impulse.
44. When I get involved in a new subject, I study it thoroughly.
45. Imagination is the key to the future.
46. I prefer to learn a new task by having someone show me.
47. I tend to make decisions based on feeling more than analysis.
48. I put a lot of energy into handling several tasks at the same time.
49. I have to get my hands on something in order to really understand it.
50. I enjoy reading business articles.
51. It's easy for me to get along with people who are very different.
52. I probably have more friends than most people.
53. I keep my feelings to myself.
54. I frequently speak in generalities.
55. I usually know my bank balance.
56. Most of my decisions are based on rigorous analysis.
57. I enjoy activities which require organizing.
58. I have a driving personality.
59. I tend to look at things as black and white as opposed to shades of grey.
60. I learn better by listening to an explanation than by reading a book.
61. I prefer to follow established rules and guidelines.
62. I always consider other people's feelings before acting.
63. I enjoy challenging people to see what they are made of.
64. I am good at reading maps.
65. I become easily upset by unexpected events.
66. I often draw pictures and diagrams when describing things.
67. I like to play it safe and go by the book.
68. I pick up on the vibrations of people around me.
69. I am a practical-minded, logical person.
70. I often recognize relationships between seemingly unrelated objects.
71. I can make people laugh.
72. I enjoy reading romance novels.
73. I am more supportive than most people.
74. I can intuitively sense solutions to problems.
75. I always want to know how something works.
76. I'm usually poor at details but grasp the big picture.
77. I treat mistakes as learning opportunities rather than failures.
78. I have a strong interest in science and mathematics.
79. I sometimes know things without knowing how I know.
80. People often seek my advice when faced with difficult social situations.
81. I tend to talk in specific terms.
82. I enjoy problems that require logical thinking.
83. I don't like to draw attention to myself.
84. I will go to almost any length to avoid confrontation.
85. I am interested in abstract concepts and ideas.
86. Keeping peace is more important than being right.
87. I prefer to keep a fast pace.
88. I have a very active imagination.
89. I am usually very agreeable to suggestions.
90. I like to work alone.
91. I like telling people what to do.
92. I find it hard to sit still longer than 30 minutes at a time.
93. I like quiet chats with friends and neighbors.
94. I am most comfortable with slow, methodical progress.
95. I enjoy working with things more than with people.
96. I tend to make decisions based on a sensory (visceral) sensation in my stomach.
97. I am very comfortable in new and unusual surroundings.
98. It's easy for me to see pictures in my mind's eye.
99. I remember people by the sound of their voice.
100. I like to have reading material prior to any class, lecture or meeting I'm attending.
Thank you for your patience and support of my research
226
Culture/Personal factors
Score
3
7
Pleaserateall100questions
Allyourquestionnaireinformationwillbekeptconfidential.
Your
Score
NC
OC
2
3
NC
PC
1
4
PP
3
1
OC PC
4
2
PP
Appendix 6: Thinking styles and behavioral patterns, 128 respondents quantitative explorative
study
Percentage Chart by Emergenetics Profile Types
Pilot PhD Group 2 - 2013-01-10
Population-at-Large
AT**
17%
8%
**SC
12%
18%
A**C
11%
17%
*TS*
11%
6%
A*S*
6%
2%
*T*C
2%
3%
ATS*
13%
9%
A*SC
13%
21%
AT*C
5%
6%
*TSC
4%
2%
ATSC
1%
1%
A***
1%
1%
*T**
2%
1%
**S*
1%
2%
***C
2%
3%
Behavior Percentages
EXP
ASR
FLX
Percent (0 - 33)
20
18
34
Percent (34 - 66)
27
29
40
Percent (67 - 100)
53
53
26
227
This Group
Emergenetics, LLC, 1991.
Appendix 7: Thinking styles and behavioral patterns, 23 respondents, In-depth case-study
Percentage Chart by Emergenetics Profile Types
PhD Case-study Project - June 2015
Population-at-Large
AT**
17%
21%
**SC
12%
8%
A**C
11%
13%
*TS*
11%
13%
A*S*
6%
4%
*T*C
2%
4%
ATS*
13%
13%
A*SC
13%
4%
AT*C
5%
8%
*TSC
4%
4%
ATSC
1%
4%
A***
1%
0%
*T**
2%
4%
**S*
1%
0%
***C
2%
0%
Behavior Percentages
EXP
ASR
FLX
Percent (0 - 33)
33
25
42
Percent (34 - 66)
33
33
21
Percent (67 - 100)
33
42
38
Emergenetics, LLC, 1991.
228
This Group
Appendix 8: Example of the details of the CPMs team meeting agenda in-depth case-study
Details of the CPM team meeting agenda
The objective of these weekly update meetings was for the clinical project managers to report the status
and progress of one or more clinical trials they manage and monitor within a specific country or group of
countries. The clinical project managers would normally report on clinical trial projects that are about to
start, have already started or are about to be completed. The observations during these update meetings, can
be seen as snapshots of what is going on within the daily practice of the clinical project managers at the
certain time in a certain place.
Based on the agenda, specific information is shared, budget, resource allocation and other important issues
are addressed and if required an intervention is advised or suggested or the issue is escalated further up the
hierarchy. Each meeting would normally start at 13:00 hours local time and ends at around 18:00 hours. A
total of 12-18 clinical trial projects in 7-9 countries are normally reviewed during each of these team
meetings and teleconferences. The project director of the clinical project management team and colleagues
from other department, finance or regulatory affairs were physically present at the HQ office and the
clinical project managers located in the different affiliated office in Asia Pacific and Australia and New
Zealand would call in to an internal teleconference system that includes both audio and video capabilities.
Every session would start with personal greetings to each other and in a professional and polite manner.
The project director would then open the power-point presentation and ask the respective clinical project
manager to present the status update of each of the clinical trial projects under her/his management. In a
structured process, each clinical project manager based on a scheduled time would dial into the
teleconference system and would have approximately 15-20 min to present (via power point) a progress
update on the clinical trial projects that he/she is managing. There is another 10-15 min available for the
director to ask for clarification or address specific issues questions related to contracts, timelines, budgets
and processes and procedures. Questions were addressed in a gentle manner and in a certain pattern for
example; why there is a change of deadlines, what are the reasons, and how can we help or support to
ensure on time delivery to the client.
229
Appendix 9: Observation score-card for 6 respondents, in-depth case-study session I
Case%Study+behavioral+observation+Score%Card/Behavioral+Patterns Expressiveness
Q Int Re Talk Greg
Assertiveness
Peace EG Comp Force Drive
Flexibility
EG+Survey
Focus Firm Adapt Accom Wel+Change Thinking Behavior
Participant+&+Cultural+Group++++++
P1+Oriental
EG+Survey+results
Observations+scores
P2+Oriental
EG+Survey+results
Observations+scores
P3+Oriental
EG+Survey+results
Observations+scores
P4+Oriental
EG+Survey+results
Observations+scores
P5+Oriental
EG+Survey+results
Observations+scores
P6+Oriental
EG+Survey+results
Observations+scores
53
X
62
X
X
X
22
X
60
X
22
X
X
X
16
X
X
X
X
X
X
X
111
4*TS*
321
5ATS*
333
X
72
X
1AT**
29
X
68
X
333
X
41
X
2ATS*
X
5
81
X
111
87
5
X
1*T**
X
72
X
222
5
91
X
5A*SC
X
X
X
82
X
X
X
General+observations
Good+friendly+atmospere
Everybody+listens+and+only+speaks+when+asked+a+question
Foscus+on+experiences+of+the+trainees
What+have+they+learned,+how+are+they+going+to+use+it
What+could+have+be+done+better
Conslusion+are+formulated+and+recommendations+shared
Meeting+info:+Teleconference
Date/time:February+13th+2015
Thinking styles
This group included; three tri-model thinkers (three thinking styles), two dual-model thinkers (two thinking
styles) and one mono-model thinker (one thinking style). Three participants (P3, P5 & P6) had at least a TS
(Structural & Social thinking style) or in reference to the EG classification tend to be “Concrete Thinkers”.
The concrete thinker tends to be disciplined, organized, team-oriented and socially aware. When it
concerns a task they tend to ask - how do we need to do this- and -who do we have to engage or cooperate
with to accomplish the task at hand? Three participants (P3, P4 and P6) in this session had an AT
(Analytical & Structural thinking style), which indicates that they tend to be more “Convergent Thinkers”.
The convergent thinker is rational, data driven, and likes to follow guidelines. When it concerns a task they
tend to ask – why do we need to do this? - What is the logic behind it and how can we do this in a
methodological manner? Three participants (P1, P3 and P6) in this session had a combination of three
thinking styles or tri-models. The tri-model thinkers can relatively easy relate to colleagues with any of the
three thinking styles, which is a plus.
230
The tri-models thinkers can sometimes be perceived as indecisive because they are considering all angle of
a problem or issue. Two participants (P3 P6) had an ATS* thinking style or a tri-model-convergent
thinking style, combining “divergent thinking “ (AT) with “concrete thinking” (TS). One participant (P1)
had an A*SC thinking style or tri-model divergent thinker, combining an “abstract thinking styles ” (AC)
with a “divergent thinking” style (SC). Abstract thinker (AC) are the opposite of concrete thinkers (TS) and
convergent thinkers (AT) are opposite of divergent thinkers (SC). One participant (P2) only had one
thinking style (mono-model)
Behavioral pattern expressiveness (EXP)
The percentile score for EXP (expressiveness) was in the third-third percentile (67-100%ile) bracket for
three participants (P3, P5 & P6) in this session, indicating that in general these participants would be
comfortable to talkative and gregarious. Two participants (P2 & P4) in this session scores are in the firstthird percentile (0-33%ile) bracket indicating that in general these participants would be comfortable to be
quiet and introspective. One participant (P1) was in the “it depends” bracket of the second-third percentile
(34-66%ile), which means that depending on the situation the participant can either flex to be
quiet/reserved or talkative and gregarious.
Assertiveness (ASR)
The percentile score for ASR (assertiveness) was in the third-third percentile (67-100%ile) bracket for two
participants (P3 & P6) in this session, indicating that in general these participants would be comfortable to
be talkative and gregarious. Two participants (P2 & P4) in this session scores are in the first third
percentile (0-33%ile) bracket, indicating that in general these participants would be comfortable to be
peacekeepers and easy going. Two participant (P1 & P5) were in the “it depends” bracket of the second
third percentile (34-66%ile), which means that depending on the situation the participants might flex to be
peace keepers or more forceful and driving.
Flexibility (FLX)
The percentile score for FLX (flexibility) was in the third-third percentile (67-100%ile) for two participants
(P3 & P6) in this session, indicating that in general these participants would be comfortable to
accommodate and welcome change. Three participants (P2, P4 & P5) in this session scores were in the
first-third percentile (0-33%ile) indicating that in general these participants tend to be focused and firm.
One participant (P1) was in the “it depends” bracket of the second third percentile (34-66%ile), which
mean that depending on the situation the participant might flex to be focused and firm or accommodation
and welcoming change.
231
Appendix 10:
Observation score-card for 9 respondents, in-depth case-study session II
Case%Study+behavioral+observation+Score%Card/Behavioral+Patterns Expressiveness
Q Int Re Talk Greg
Assertiveness
Peace EG Comp Force Drive
Flexibility
EG+Survey
Focus Firm Adapt Accom Wel+Change Thinking Behavior
Participant+&+Cultural+Group++++++
P1+Oriental
EG+Survey+results
Observations+scores
P2+Oriental
EG+Survey+results
Observations+scores
P3+Oriental
EG+Survey+results
Observations+scores
P4+Oriental
EG+Survey+results
Observations+scores
P5+Oriental
EG+Survey+results
Observations+scores
18
X
X
X
X
11
X
22
X
22
X
X
X
X
5
X
X
P7+Oriental
EG+Survey+results
Observations+scores
X
X
X
X
P8+Oriental
EG+Survey+results
Observations+scores
X
X
X
X
X
X
X
223
5ATS*
333
1AT**
222
X
2A*S*
332
X
3A**C
111
X
X
X
52
X
X
20
X
2AT*C
52
95
28
X
X
X
95
X
111
X
66
X
1AT**
82
X
38
X
121
72
72
X
2*T*C
X
48
68
X
111
X
64
X
1*T**
8
X
X
111
18
5
X
1AT**
X
X
34
X
X
X
5
22
P6+Oriental
EG+Survey+results
Observations+scores
P9+Oriental
EG+Survey+results
Observations+scores
15
X
X
26
X
X
X
General+observations
Good+friendly+atmospere+exchange+of+much+information
Everybody+listens+and+some+interruptions
Foscus+on:+site+selection,+site+initiation,+contracts+and+start%up
Patient+enrollment+status+and+follow%up
Financial+parameters,+payments+and+invoicing
Budget+and+resources+allocation
Risk%management,+mitigation+and+corrective+actions
Meeting+info:+Onsite+via+Teleconference
Date/time:February+24th+2015
Thinking styles
This group included; five dual-model thinkers (two thinking styles), two tri-model thinkers (three thinking
styles) and one mono-model thinker (one thinking style). Five participants (P1, P4, P5, P6 & P7) of this
group had at least an AT (Analytical & Structural thinking style), which indicates that they tend to be more
“Convergent Thinkers”. One participants (P6) had an ATS* thinking style or a tri-model-convergent
thinking style, combining “divergent thinking “ (AT) with “concrete thinking” (TS). One participants (P9)
of this group had an AC (Analytical & Conceptual thinking style) indicating a tendency to be an “abstract
Thinkers”.
232
The behavioral patterns expressed in numbers representing the behavioral percentile score can be a
combination of (1) first-third of the population (0-33%ile), (2) second-third of the population and (3466%ile), and (3) third- third of the population (67-100%ile). Below the purple bars are the observed
behavior (X) scored during the session. On the right hand side of the table each participants thinking styles
are expressed in a code.
Behavioral pattern expressiveness (EXP)
The percentile score for EXP (expressiveness) was in the first-third percentile (0-33%ile) bracket for five
participants (P1, P2 P3, P4 & P9) in this session, indicating that in general these participants tend to be
quiet and introspective. Two participants (P6 & P8) in this session scored in the third-third percentile (67100%ile) bracket, indicating that in general these participants tend to be talkative and gregarious. Two
participant (P5 & P7) scored in the “it depends” second-third percentile (34-66%ile) bracket meaning that
depending on the situation the participant they tend to either flex to be quiet/reserved or talkative and
gregarious.
Assertiveness (ASR)
The percentile score for ASR (assertiveness) was in the first-third percentile (0-33%ile) for four
participants (P1, P2, P4, P20) in this session, indicating that in general they would tend to be behaving in a
peacekeeping and easy-going way. Two participants (P6 & P8) in this session scores were in the third-third
percentile (67-100%ile) bracket indicating that in general they would tend to act forceful and driving.
Three participant (P3, P5 & P7) were in the “it depends” bracket of the second third percentile (34-66%ile),
which means that depending on the situation the participants might flex towards peacekeeping or more
forceful and driving behavior.
Flexibility (FLX)
The percentile score for FLX (flexibility) was in the first-third percentile (0-33%ile) bracket for five
participants (P1, P2, P3, P4 & P9) in this session, indicating that in general these participants would tend to
behave in a focused and firm way. Two participants (P5 & P6) in this session scores are in the third-third
percentile (67-100%ile) bracket, indicating that in general these participants tend to be accommodating and
welcoming change. Two participants (P7 & P8) were in the “it depends” second third percentile (3466%ile) bracket, which means that depending on the situation the participants might flex towards focused
and firm or accommodating and welcoming change behavior.
233
Appendix 11:
Observation score-card for 14 respondents, in-depth case-study session III
Case%Study+behavioral+observation+Score%Card/Behavioral+Patterns Expressiveness
Q Int Re Talk Greg
Assertiveness
Peace EG Comp Force Drive
Flexibility
EG+Survey
Focus Firm Adapt Accom Wel+Change Thinking Behavior
Participant+&+Cultural+Group++++++
P1+Oriental
EG+Survey+results
Observations+scores
P2+Oriental
EG+Survey+results
Observations+scores
P3+Oriental
EG+Survey+results
Observations+scores
P4+Oriental
EG+Survey+results
Observations+scores
P5+Oriental
EG+Survey+results
Observations+scores
64
X
X
X
X
X
X
X
X
X
X
X
68
X
X
X
X
38
X
X
X
X
X
X
28
X
X
P11+Anglo%Sax
EG+Survey+results
Observations+scores
X
X
X
X
X
X
X
X
X
53
X
X
X
X
X
X
X
X
X
X
X
General+observations
Good+friendly+atmospere+very+focused+on+objectives+and+timelines
Concerns+about+running+behind+and+not+achieving+the+set+goals
Discussion+around+issues+are+addressed+professionaly
Many+complements+are+given+for+work+that+is+already+done
Foscus+now+is+on:+Timely+delivery+with+the+highest+quality
Lead+CPM+summerises+issues,+risks+and+agreed+corrcetive+actions
Meeting+info:+Onsite+via+Teleconference
Date/time:February+27th+2015
234
332
3A**C
111
3A**C
131
2ATS*
223
4*TS*
323
5A*SC
222
5*TSC
222
75
X
X
X
2A*S*
75
X
X
X
60
X
X
X
48
X
222
6
62
53
X
X
41
X
1AT**
X
37
75
X
333
X
X
X
72
X
5ATS*
X
26
38
X
X
X
X
X
X
52
X
28
X
X
X
20
X
231
52
X
X
1AT**
82
95
X
333
X
x
95
X
2ATS*
5
66
X
121
X
72
X
2*T*C
87
88
X
111
X
72
X
1*T**
X
X
X
223
18
42
X
X
34
X
2AT*C
X
5
91
P10+Latin
EG+Survey+results
Observations+scores
P14+Anglo%Sax
EG+Survey+results
Observations+scores
X
X
X
P8+Oriental
EG+Survey+results
Observations+scores
P13+Oriental
EG+Survey+results
Observations+scores
X
22
X
72
22
X
P7+Oriental
EG+Survey+results
Observations+scores
P12+Anglo%Sax
EG+Survey+results
Observations+scores
X
22
P6+Oriental
EG+Survey+results
Observations+scores
P9+Oriental
EG+Survey+results
Observations+scores
48
40
X
X
X
Thinking styles
This group included; seven dual-model thinkers (two thinking styles), six tri-model thinkers (three thinking
styles) and one mono-model thinker (one thinking style). Ten participants (except P2, P3 & P12) in this
group had at least an Analytical thinking style (rational, data driven and research oriented), which is not a
surprise as they are all involved in monitoring clinical research projects.
Six participants (P1, P4, P5, P6, P7 and P11) in this group had at least an AT (Analytical & Structural
thinking style), which indicates that they tend to be more “Convergent Thinkers”. Five participants (P4, P6,
P11, P12 & P13) of this group had at least an TS (Structural & Social thinking style) indicating that they
tend to be “Practical Thinkers”. Three participants (P4, P6 & P11) had an ATS* thinking style or a trimodel-convergent thinking style, combining “divergent thinking “ (AT) with “concrete thinking” (TS).
Two participants (P9 & P10) of this group had an AC (Analytical & Conceptual thinking style) indicating
that they tend to be “abstract thinkers”.
The behavioral patterns expressed in numbers representing the behavioral percentile score can be a
combination of (1) first-third of the population (0-33%ile), (2) second-third of the population and (3466%ile), and (3) third- third of the population (67-100%ile). Below the purple bars are the observed
behavior (X) scored during the session. On the right hand side of the table each participants thinking styles
are expressed in a code.
Behavioral pattern expressiveness (EXP)
The percentile score for EXP (expressiveness) was in the first-third percentile (0-33%ile) for four
participants (P2, P3, P9 & P10) in this session, indicating that in general these participants tend to be quiet
and introspective. Four participants (P4, P6, P8 & P12) in this session scored in the third-third percentile
(67-100%ile) indicating that in general these participants tend to be talkative and gregarious. Six
participant (P1, P5, P7, P11, P13 & P14) which is the largest group scored in the “it depends” second-third
percentile (34-66%ile) bracket meaning that depending on the situation they tend to either flex to be
quiet/reserved or talkative and gregarious.
Eight participants (P1, P2, P3, P5, P6, P9, P10 & P12) observation scores were in line with their respective
percentile survey scores. Two participants (P4 & P8) both with a third-third percentile score had different
235
observation score. Participant (P8) was still within the percentile survey score and participant (P4) showed
opposite behavior (quiet and inspective) than the percentile score indicated (talkative and gregarious).
Three participant (P11, P13 & P14) in the “its depends” bracket flexed to the left and behaved quiet and
reserved and participant (P7) showed talkative behavior rather than being quiet and reserved. Overall the
observational scores of each participant within their percentile scores from the EG survey with no large
discrepancies.
Assertiveness (ASR)
The percentile score for ASR (assertiveness) was in the first-third percentile (0-33%ile) for two participants
(P2 & P9) in this session, indicating that in general they would tend to be behaving in a peacekeeping and
easy-going way. Five participants (P4, P5, P6 & P8) scores were in the third-third percentile (67-100%ile)
indicating that in general they would tend to act forceful and driving. The majority of the participant seven
(P1, P3, P7, P11, P12, P13 & P14) were in the “it depends” second third percentile (34-66%ile) bracket,
which means that depending on the situation the participant might flex towards peacekeeping or more
forceful and driving behavior.
Five participants (P4, P6, P7, P9 & P12) observation scores were in line with their respective percentile
survey scores. Three participants (P5, P8 & P10) with a third-third percentile score had slight different
observation scores but were still within their percentile survey scores.
Four participant (P1, P3, P11, P13 & P14)) in the “its depends” bracket all flexed to the left and showed
peacekeeping and easy-going behavior rather than competitive, forceful and driving behavior. Overall the
observational scores of each participant were within their respective percentile scores from the EG survey
with no large discrepancies.
Flexibility (FLX)
The percentile score for FLX (flexibility) is in the first-third percentile (0-33%ile) for five participants (P2,
P3, P5, P9 & P10) in this session, indicating that in general these participants would tend to behave in a
focused and firm way. Five participants (P1, P4, P6, P11 & P12) scores were in the third-third percentile
(67-100%ile) indicating that in general these participants tend to be accommodating and welcoming
change. Four participant (P7, P8, P13 & P14) were in the “it depends” second third percentile (34-66%ile),
which means that depending on the situation the participant may flex towards focused and firm or
accommodating and welcoming change behavior.
236
Appendix 12: Organogram of clinical project managers team, 23 respondents in-depth case-study
1
1
2
1
4
2
3
1
4
2
CPM
RegionalHQ
Singapore
1
CPMaffiliate
NewZealand
237
1
1
Appendix 13: Description of the clinical research process as part of the CPMs daily tasks
The clinical research process is part of the bio-pharmaceutical product development phase and includes
practical research in animals and humans to investigate product properties, product features and possible
use in humans.
CPMs monitor and manage three types of clinical research project:
•
Phase I studies are conducted to establish a safe dose, conducted in normal healthy
volunteers.
•
Phase II studies are conducted in persons with a disorder with the purpose to gain
evidence of safety and efficacy and to establish the proper dose and dosing intervals.
Safety and tolerance data are obtained in patients with the target disease to provide a
measure for the drugs true effects, when used in the respective patient group
•
Phase III studies are the definitive trials that will establish the safety and efficacy of
the new drug in the actual patients for which it is intended. These trials are quite
large, often involving treatment of several hundred or several thousand patients.
Large numbers of patients are required to perform statistical analysis of the clinical
data. For some diseases this may require long-term follow-up studies of at least a
year or more.
CPMs normally perform the following tasks within the clinical research process:
1. Designing of the clinical protocol, case report forms, ordering of clinical supplies.
2. Investigator and site selection, trail monitoring, data collection and data analysis.
3. Reporting the results in a form suitable for the submission to the regulatory authorities.
The results of these clinical research studies will decide if the new drug application is ever submitted to a
Board of Health like the Food and Drug Administration (FDA) for the US and the European Medicine
Agency (EMA) for the European community for approval to market the drug.
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Appendix 14: Example of the Mutual Perception (MP) survey
PhD Case Study Mutual perception survey
QuestionsaboutyourexperiencewithyourKoreanColleagues
Quantitativeratherthanqualitative
Preciseratherthaninexact
Factualratherthanemotional
Demandingratherthanobliging
5.ColleguesfromtheKoreanofficetendto(be,act)
Authoritative
Cautious(indecisive)
Striveforchallenginggoals
Chargingahead
Compromising
Consistent(methodical)
Hardworking
Individualistic
Loyal
Pushy
Quickmoving
Sensitive
Takingcontrol
Teamplayers
Trusting
Unpredictable
Preserveharmony
4.Doyouhavethefeelingonlyonethingormoreissuesarebeingdiscussedatthesametime?
3.Dotheyincidentallyuseaside-trackintheirmessage?
2.Wouldtheycomestraighttothepoint(direct)orcirclearoundtherealissue(indirect)?
1.HowwouldyourateyourcolleaguesfromKoreaonascaleofpoliteness
people
1
qualitative
1
2
inexact
1
emotional
1
obliging
1
2
2
always1issue
1
2
direct
1
2
stronglydisagree
1
2
1
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never
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2
veryimpolite
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perfect
10
task
10
quantitative
10
precise
10
factual
10
demanding
10
stronglyagree
10
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alwaysmoreissues
10
always
10
indirect
10
extremelypolite
10
Numberofyearsofworkexperiencewithaffiliatedoffice?
Taskratherthanpeopleoriented
2
HownaturaldoyouratethecooperationorcommunicationwithpeoplefromtheKoreanoffice
difficult
Perfectlynaturallikewithyourbestfriend;ordifficult:fullofsurprises,annoyancesandmisunderstandings?
1
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About the author
Ron brings with him over 20 years of strategic business development and marketing communication
experience from various small and large organizations throughout the world. His qualifications include
business development and operational management experience in medical technology and biopharmaceutical companies. He has implemented multi-channel marketing approaches to maximize
customer engagement and commercial effectiveness and successfully launched new products on a regional
and global scale. He enjoys working in a culturally diverse environment and can bridge the gaps between
functions and cultures. Connecting and engaging with a variety of critical functions and decision makers in
an organization is part of his second nature.
Over the last six years he has combined his PhD research with an entrepreneurial focus on maximizing
international business communications in culturally and functionally diverse leadership teams. During this
period he established a network of management consultants in Europe and facilitated lasting partnerships
with fortune 500 companies. Ron has an MBA from Glasgow University Business School and an MSc in
Strategy & Organization (Open University, The Netherlands). He graduated with a teaching degree in
Sports Science & Physical Education (Sports Academy, Arnhem), in The Netherlands.
He currently is one of the managing partners of Ekoy Investment Partners (EIP). EIP creates value by
providing talented entrepreneurs with resources and tools to achieve success in transforming intellectual
capital and scientific knowledge into successful companies. EIP does not only provide the financial means
but also takes an active role in strategic processes. EIP’s core expertise is in M&A, partnerships and private
placements, with a focus on life science companies including biotechnology, medical devices and
diagnostics. For more information please contact Ron Byron via:
Mobile-phone: +31622351074
Email: [email protected]
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