Measuring Knowledge Exploitation and Exploration:
An Empirical Application in a Technological Development Center in Brazil
Autoria: Silvio Popadiuk, Patrícia Gonçalves Vidal
ABSTRACT: This article presents a literature review on the concepts of exploration and
exploitation of knowledge. From this review, it is showed that the concepts of exploration and
exploitation can be analyzed through internal or external environments perspective, related to
seven dimensions, namely: knowledge, innovation, strategy, costs, efficiency, competition,
and partnership. From this theoretical conception, a closed and structured questionnaire, after
a qualitative research, was developed, that contained attributes related to the dimensions
above. These attributes were assessed through a six-points Likert scale. This questionnaire
was applied in a research and development institute of a major multinational firm in the
telecommunication sector, situated in Northern region in Brazil. The main purpose of this
article is to assess the fit between what have been proposed in the literature on exploitation
and exploration and what have been practiced in the corporate world. The results revealed two
distinct groups of employees in this institute, regarding how these employees perceived their
activities to be innovative. Regarding these two groups, there are significant differences
regarding how these two groups evaluated the attributes related to the exploration and
exploitation of knowledge. This means that the R&D institute needs to develop mechanisms
for improving information sharing between both groups.
INTRODUCTION
The process of decision making to invest resources in an organization has been the key
issue for over decades of organizational studies (MARCH and SIMON, 1958; CYERT and
MARCH, 1963). Lately, one of the focuses of organizational theorists is to understand how to
invest the organizational resources in a way to balance what March (1991) has called
exploration of new knowledge and exploitation of available knowledge (DOSI and
MARENGO, 1997; ROTHAERMEL, 2001). The organization may choose to invest in the
refinement of an existing technology or on any other activity that is oriented toward
increasing efficiency (DOSI and MARENGO, 1997) or it may choose to invest in activities
that search for novel processes or the discovery of new opportunities.
March (1991) argues that the organizations that engage in exploration to the exclusion
of exploitation are likely to be penalized by the experimentation without gaining many of its
benefits, whereas the organizations that engage in exploitation to the exclusion of exploration
are likely to find themselves trapped in a suboptimal equilibrium. Companies thus face a
trade-off between exploration and exploitation: If the company does not reach an appropriate
equilibrium between the two ends of the continuum, the company may end up suffering from
sub-optimization. In sum, firms face a trade-off between the creation of new capabilities
(exploration) and the development of current capabilities (exploitation).
This article has the following research question: what is the fit between the theoretical
considerations regarding exploration and exploitation and the activities being developed and
used in a managerial setting? From this research question, this article has five purposes: to
present a literature review of exploration and exploitation of knowledge; to characterize seven
implicit dimensions regarding the theoretical concepts of exploration and exploitation of
knowledge; to present an exploratory questionnaire using attributes of exploration and
exploitation of knowledge; to apply this questionnaire in a pilot project inside a research and
development institute of a major multinational firm in the telecommunication sector working
in Brazil; and to elaborate analytical considerations regarding the fit or lack of fit regarding
the theoretical context and the organizational context.
This article is structure as follows: next topic presents the strategies of exploitation
and exploration of knowledge (MARCH, 1991), summing up to the seven conceptual
dimensions identified from this literature review. The second part introduces the
methodology used to develop the scale as well as its tests; the third part describes the
results. The final part, presents the discussion of the findings as well as the limitations of the
study and the possible contributions both to practice and to the academia.
LITERATURE REVIEW
Exploration and Exploitation
March (1991), in his seminal article, when looking from an organizational learning point
of view, argues that there is a relationship between exploration and exploitation in the adaptive
process in the organizations. Exploration refers to the actions and activities related to research,
search, risk, experimentation, playing, flexibility, discovery, and innovation. Exploitation refers
to refinement, choice, production, efficiency, selection, implementation and execution.
The essence of exploitation is the refinement and extension of the existing
competencies, technologies, paradigms; a refinement that will lead to returns that are positive,
near and predictable. While exploration is the experimentation of new alternatives, with
returns that are far away on time, uncertain, and usually negative (MARCH, 1991). March
(1991) argues that the organizations make explicit or implicit choices for one or other, since
the resources are scarce and the difficulties associated with the choices lead to complications
in specifying the appropriated trade-offs.
The adaptable systems related to exploration which are excluded from the exploitation
allegedly suffer from the costs related to the experimentation, without obtaining most of its
benefits. Inversely, the systems that are related to the exploitation which are excluded from
exploration are in a stable sub-optimal equilibrium (MARCH, 1991). The organization choice
for the exploration or exploitation resides, according to March (1991), on the rational search
theory. March (1991), cited Radner and Rothschild (1975) and Hey (1982), to explain that
there are several possibilities to invest, which one characterized by the likelihood of
distributing unknown. As time passes, new information about these distributions is
accumulated, but the choices should be done among investing more in new alternatives and
improve the future returns, or to improve the present returns.
March (1991) points out that the studies on organizational learning direct the choice
between exploration and exploitation regarding the search for new technologies or the
refinement of existing technologies. The alterations in the environment are also pointed out
since these changes need the generation of new alternatives to the survival of the firm. Due to
the environmental turbulence, organizational diversity and competitive advantage, the
evolutionary dominance of one organizational practice is sensitive to the relation between the
variation related to the exploration reflected by the practice and by the change rate in the
environment.
The learning process is reinforced, either positively or negatively, as a result of the
path chosen by the organizations, consequently the choice between two alternatives is path
dependent (MARCH, 1991). To March (1991), the organizations accumulate experience in its
norms, routines and forms at the individual and organizational level.
Teece, Pisano and Shuen (1997) also argue that the future position the organization
may reach is a function of its current position, a position that suffers influence of the path
chosen before, and the path ahead of it. This is due to the investment made a priori as well as
the routine repertory. Teece et al. (1997) also posit that learning is a process of attempts,
returns and evaluation. This way, the path dependency is amplified when there are conditions
to the increase of returns related to the adoption of a technology. The products and the
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technologies are more attractive as they are adopted, characterized as a demand phenomenon.
The increase in returns can have different sources, as network externalities, the
presence of complementary assets, and the infra-structure support, learning by doing and scale
economies of production and distribution. Since there are several sources to increase returns,
the anterior position of the firm may affect the capacity to exploit increasing returns.
The trade-off between exploration and exploitation occurs simultaneously and involve
conflicts at short and long run, and it also has gains to individual and collective learning. To
Gilsing (2002), there is a social construction of knowledge related to the choice between
exploration and exploitation: the resulting learning is formed by new ideas, changes in beliefs,
new and adapted institutions, change in the design of the structure of the networks and the
adaptation of coordinating mechanisms.
Gilsing (2002) posit that when there is innovation, there is a rupture of the routine,
there is a discontinuity that shows the beginning of a new base of knowledge that is totally
tacit. In a sectorial system, the tacit nature of knowledge pushes the participants to
approximate in a way to obtain a reduction in the cognitive distance, through the near
interaction. There is a surge of varieties of ideas, prototypes, and demos. This variety is
specially formed from the results in the learning processes and it consists of new knowledge
highly tacit, and very specific to a limited number of firms. The environment, in phase of
exploration, is characterized by low selection through the coordinating mechanisms, like the
social norms and reputation; also there is a large variety and learning results that affect mainly
the new base of knowledge (GILSING, 2002). As a consequence, firms start to focus on the
fit between demand needs and new markets for the new knowledge base. Also, the
competition increases once the new knowledge base is already extensive to allow the
development of several types of designs through several networks of exploration, creating
competition among them. The demand and the combination of social and technical norms
reinforce directly the activities of search and, by doing it, create limits to the new knowledge
base. The results from the learning, such as new ideas and knowledge, should be adjusted to
the emerging selective environment. A process of stability begins when a dominant design is
chosen and there is the elimination of competing designs (UTTERBACK, 1994). As a result,
the learning focuses the change from exploration to exploitation. The competition intensifies
and, usually, creates an incentive to focus on cost reduction. From this moment, the technical
norms and formal procedures lead the firms to the search for the “scale effects” (GILSING,
2002), i.e., the economic search for exploiting economy of scale gains.
Li, Schoenmakers and Vanhaverbeke (2006) evaluated the trade-off between
exploration and exploitation from the learning experiences, and observed that, in a context of
Schumpeterian competition, the returns would be diluted through imitation and destructive
innovation. Li et al. (2006) argue that exploration and exploitation are activities related to the
search of knowledge. In a context where a given performance goal must be reached, the firms
need to find solutions to reach the goal. On the other hand, if the current performance is better
than the expected one, so the organization enter in a calm path, and it encourage the search for
activities that are not justifiable in terms of expected returns (LI et al., 2006).
Lundvall (1999) points as a good plan to firms that want to increase learning to
combine indoor activities that are dissimilar and complementary. Lundvall (1999) argues that
if a firm tries to create a disequilibrium between what it can do and what it is required from it
to accomplish its task are good way to stimulate the learning as well as to increase the set of
competencies of the firm. There are three categories related to the basic functions of the firm:
(1) allocate scarce resource, (2) exploit sub-utilized resources when entering new activities
and (3) speed up the learning and the creation of new competencies (LUNDVAL, 1999, p.
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12). The firm will reallocate its resources if there is an alteration of the price of factors. It will
exploit the un-utilized resources and will use its existing knowledge base in connection to the
introduction of new products. Its success will depend upon the construction of new
competencies.
The learning reasons are divided between exploration and exploitation. Exploration is
directly connected to the tacit knowledge that is assumed to be a pre-condition to the
development and acquisition of new knowledge. Learning in exploitation is related to the
explicit knowledge that can be applied to refinement or improvement of current knowledge
(KARLSON, 2005).
Li et al. (2006) posit that the activities related to the knowledge search have several
dimensions one of them is the timing. Timing Exploitation is the creation of new knowledge
through the search of recent knowledge and timing exploration is the creation of new
knowledge through the search of knowledge far away in time. Considering the limited
rationality and the path dependency, individuals tend to search for alternatives that are related
to their current knowledge, and valuable choices are lost in time. Also, the choice that has
been made was done in lie of complementary assets that were not available at that moment.
Another dimension is the geographic or institutional (LI et al., 2006) which is related
to having the resources in common available at the same geographic area. This proximity
facilitates the transfer of knowledge which in an exploration phase is highly tacit and can be
transfer more easily through interactions and practices.
Li et al. (2006) also consider that the activities involved in exploration and
exploitation are important to the process of innovation. They point out that the process of
innovation involves stages of search of knowledge, knowledge recombination, finding an
innovative solution and its commercialization (LI et al., 2006, p. 11). The authors argue that
starting from an application of one technology until its expansion, problems may accumulate
in the process of differentiation of this technology and the exchange of relevant practices up
to the point where efficiency and returns diminish considerably, At this point, there is no
possibility to generate additions or modifications. This is the necessary incentive to search for
new structures or to generate the Schumpterian creative destruction.
Teece et al. (1997) advances the notion of competitive advantage through the
exploration of possibilities that are external and specific to the firm, as well as the
development of new opportunities (PENROSE, 1959; TEECE, 1986; WERNERFELT,1984),
by developing and explaining the term dynamic capabilities, to strategic manage the
capability of adapting, integrating, reconfiguring abilities, resources and functional
competencies to the environment, specially since the business environment is always
changing. Also, the dynamic capabilities are complemented by the path dependency, i.e., the
firms in several points of their trajectories make choices that are irreversible, investing in one
competency in lieu of another competency. These choices will determine not only the choices
presented today but also in the future. The capability that the firm has should be compatible
with the user needs, unique and difficult to be replicated. Teece et al. (1997) complements
stating that the firm´s current capability could be the base of the diversification to new
markets as well as new products. However, these dynamic capabilities can be obtained only
through the internal development of such a capability.
A valuable consideration to the exploration and exploitation discussion is that the core
competency and capacity of the firm are involved in the organizational processes. These
processes are molded by the firm´s assets (internally or in the market), and through the
evolutionary path that the firm has adopted (TEECE et al., 1997). Gilsing (2002) has also
considered the characteristics of the co-evolutionary path, describing it by the search to
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predict which variables in the system answer to changes in other variables in the system or
changes in the system itself.
Masini, Zollo and Wassenhove (2004) argues that the strategic decision between
product differentiation and cost leadership lead to a trade-off between exploration and
exploitation, since if the organization decides to compete on the differentiation, the
organization will worry about its products being copied or imitated. Therefore, the costs
associated with this strategy will be higher. Following the logic, the organization that
competes on cost leadership is not worried about the risk of having its product being copied or
imitated.
Adner (1999) argues that the tension between exploration and exploitation is not
axiomatic, i.e., the exploration of new technologies does not prevent their exploitation in the
market. The firms could influence the investment in activities in the market to speed up the
process of exploration through the process of exploitation by focusing on the needs
heterogeneity as well as the sources of retro-feeding in the market. Adner (1999) posits that
the technological development can happen inside the boundaries of the firm and can be
structured to influence the market opportunities. The idea here is to demonstrate the
possibility that technology development and its commercialization can guide themselves
mutually. When dealing with emerging technologies, the firms can exploit the market
diversity by allowing the target market to co-evolve with the state of its technology.
Prietula and Weingart (2005) used the terms exploration and exploitation in describing
models of negotiation. Exploration reflects a more risky and uncertainty component of the
joint search of two negotiators, where they try to define, refine, and align their knowledge to
establish a common base between them. This way, the authors define exploration as a process
with wide supply of potential samples. In one hand, they suggest that exploitation is an
activity much more coordinated, that emerge from the common base of knowledge which is
created when the two parts converge to an understanding of what is the possible solution for
the negotiation.
Ahuja e Katila (2002) used the concepts of exploration and exploitation in terms of the
search in the level of deepness that the knowledge is re-used as well as in terms of the scope
of the search, place where the knowledge is searched (near or far). The level of deepness is
defined as the level that the search for knowledge reviews the knowledge already existent in
the firm, i.e., a characteristic of exploitation of knowledge. The scope of the search is the level
that new knowledge is explored and it is what characterizes the exploration of new
knowledge. The firms can vary the levels of use and re-use of existing knowledge, as well as
they can vary the exploration of new knowledge. Ahuja e Katila (2002) argue that the idea of
exploitation can be conceptualized in different levels or deepness of search, since the firms
can be differentiated not only in the extension of exploring new resources, but also in the
extension that they improve their current resources. While the exploration research has a key
role in the creation of knowledge as it leads to completely new solutions, exploitation
research has the role of combining existing solutions in the generation of new combinations.
Garcia and Nair (2005), consider the terms exploration as a synonym of the traditional
research where the result will be innovations, particularly radical and totally new innovations,
where the risk is higher and the return is uncertain. Meanwhile, exploitation is related to the
development of activities where the firm focuses on the improvement of existing processes,
existing products and on the cost efficiency. Exploitation would be related to the development
of incremental innovation, with lower risk and less variation.
The strategic alliance as a form to explore and exploit knowledge has been the focus
of some researchers. Im and Rai (2008) have examined the logistic industry in the United
5
States to determine how the knowledge sharing activities in “long-term interorganizational
relationships (IORs)” (p. 1281) is related to the relationship performance gains. Their work
shows that the sharing is enabled by “ambidextrous management of the relationship” (p.
1281). Holmqvist (2004) used the collaboration between a software company and its partners
in new product development projects to understand the effect of experiential learning
processes of exploitation and exploration within and between organizations. Rothaermel and
Deeds (2004) show that the type of alliance will influence the format and the timing to use the
exploration and the exploitation strategies. Table 1 summarizes the characteristics of
exploration and exploitation found in the literature.
Table 1: Characteristics of exploration and exploitation of knowledge
Author
March
(1991)
Gilsing
(2002)
Li et
(2006)
Karlson
(2005)
al.
Masini et al.
(2004)
Prietula;
Weingart
(2005)
Exploration
Research, search, game, risk, flexibility,
discovery,
radical
innovation,
experimenting with new alternatives with
uncertainty returns, search for new
technology.
Few choices for coordination mechanisms,
such as social procedures and reputation;
large variety of knowledge base. Learning
and knowledge adjusted accordingly to the
emerging environment.
Development of new knowledge through
the search of knowledge remote in time.
Tacit knowledge, with the assumption that
tacit knowledge is necessary to develop and
acquire new knowledge.
A strategy that firm will choose if it is
threaten by the possible copy or imitation of
its products.
High cost of development.
Speculation and uncertainty in terms of
defining, refining and alignment of a
common knowledge base.
Exploitation
Refining, choice, production, efficiency,
selection, implementation, execution, extension
of current competencies, technologies; with
positive, predictable returns, incremental
innovation.
Stability when the dominant design is
established. Learning focus is on what is already
known.
Intensive
competition,
formal
procedures and economy of scale
Development of new knowledge through the
search of recent knowledge.
Explicit knowledge that can be applied to refine
or improve existing knowledge.
Firms that had chosen to follow a cost
leadership strategy, not worried about being
copied.
Low cost of production.
The common knowledge base is already
established.
Source: Elaborated by the authors based on literature review.
Exploration and Exploitation Dimensions
From the literature review, it can be identified that, in the study of the exploration and
exploitation strategies, there are at least two perspectives: one related to the internal
environment, and another related to the external environment. Regarding the internal
environment, the focus is on the organization´s capabilities and, therefore, on the efficient and
the effective use of its resources. This is a function of the fit between organizational activities
and the organization´s strategic planning. The organizational efficiency and effectiveness are
always related, in high and low levels of intensity, translated by the management of the
organizational knowledge, its control mechanisms, its norms and procedures, as well as its
routines (NELSON and WINTER, 1982). From the external environment perspective, the
search for a favorable competitive position means a constant monitoring of competition and a
consistent partnership with several players in the external environment.
From the internal perspective, it has been identified at least five dimensions: (1) the
strategic orientation; (2) the organizational knowledge; (3) the organizational efficiency; (3)
the costs of the organizational activities; and (3) the result of the organizational knowledge
application, i.e., the incremental or radical innovation.
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From the external perspective, two dimensions emerged: (1) the competitive
monitoring and (2) the relationship with the external environment associated with the
partnership/alliances. Table 2 presents a set of attributes related to each dimension, taken
from the literature review.
Table 2: Attributes associated to the dimensions of the exploration and exploitation strategies
Internal Environment
Organizational Knowledge
• New Idea generation; search and use of new sources of knowledge; learning intensity; staff empowerment;
knowledge sharing; social interaction; search for innovation; use of existing innovation; individual
knowledge valorization; use of tacit knowledge, use of existing knowledge in database and documents
Organizational Efficiency
• Creation of detailed routines; centralization level of decisions made; internal communication processes;
organizational control mechanisms; level of formalization; efficiency concerns; focus on economies of
scale; refinement of products and processes, flexibility.
Strategic Orientation
• Strategic vision towards short or long term; path dependence, period of using the same standard for
products and processes; perspective on environmental uncertainties; concerns about organizational
reputation.
Costs associated to R&D
• Risk aversion, concerns regarding R&D costs; focus on costs
Innovation
• Focus on new products and processes, improvement of products and processes; products and processes
diversification, development of prototypes, search for radical innovations; products and processes
discontinuity
FOCUS ON EXTERNAL ENVIRONMENT
Competition
• Competitors with similar characteristics, new entry
Partnership
• Amplitude of external network; alliance creation; interaction with partners; partner´s dependency level;
intensity for the partnership contract
These dimensions will follow a pattern, according to the literature review. One of the
major purposes of this article is to understand the fit between the theoretical considerations
and what is happening in a real company. Table 3 shows the hypothesis made accordingly to
the patterns that the dimensions should follow regarding exploration and exploitation
strategies.
Table 3: Hypothesis regarding the Dimensions
Dimensions
Knowledge
Innovation
Strategy
Efficiency
Competition
Cost
Partnership
Hypotheses
EXPLORATION
High level of focus on the use of new
knowledge
High level of focus on search for
innovations
Long term strategy
Lower level of focus on efficiency
Low levels of competition
Lower level of focus on production cost
Creation of Partnership
EXPLOITATION
Lower level of focus on the use of new
knowledge
level of focus on search for innovations
Short term strategy
High level of focus on efficiency
High levels of competition
High level of focus on production cost
Amplification of partnership
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THE R&D INSTITUTE
The Research and Development Institute (RDI), subject of this study, is a spin out
originated from the separation of this institute from a multinational company in the year 2000.
The RDI is located in the North Region of Brazil, with representation in two other locations in
Brazil. During the conduction of this research project, the only client of this RDI was the
multinational headquarter, that develops activities related to the telecommunications with
global reach. At the time of the study (January to November, 2007), the RDI was divided into
five departments: operations and logistics, software development, mechanics; solutions; and
administrative support. There are 120 employees working in these five departments,
throughout the locations as well as in other sites of the major client, the multinational
company. Most of these employees have college degrees, are male (80%) and have less than
thirty years, 50% percent of these employees have been working in this institute for the past
three years (since its inception).
The Brazilian legislation provided fiscal benefits to companies conducting R&D
activities in the North region of Brazil. Furthermore, the multinational company also
committed a large investment in the development of this institute, a fact revealing a strong
dependency of this institute. Moreover, all the projects developed inside the institute have the
multinational company as the final client.
METHOD
The research presented here is part of a major research effort to understand how the
organizations use the knowledge strategies of exploitation and exploration to increase the
organizational learning and the development of innovations. The complete research was
designed as a qualitative and quantitative research. A structured questionnaire with open
questions as well as a questionnaire with closed questions, were developed, pre-tested with
two managers from different companies, and rewritten according to their comments. The
present article presents the results from the questionnaire with closed questions that was
developed for the respondents to analyze 46 attributes regarding the knowledge strategies of
exploration and exploitation, using a six-point Likert scale. The Likert scale had the two
extreme, lower and higher with different adjectives that best described the strategic
orientation towards exploiting knowledge versus exploring knowledge. The content validity
was identified through the extraction of the attributes from the literature review.
The data, presented here, were obtained during a trip to the RDI in the North Region
of Brazil. In this trip, five researchers spent a week visiting this institute with the purpose of
understanding how this institute used the knowledge strategies of exploration and
exploitation, as well as to examine the context of this institute in terms of its culture,
structure, processes and information technology. The data presented here refer to a survey
passed by the communication department to all employees that were in that site during that
week. Seventy employees answered the survey, a number that correspond to 90% of the
employees located at that site. There were several people traveling for business and vacation,
but the communication department could not report the right amount of people available at
that time.
To examine the hypotheses presented in Table 3, regarding the pattern expected for the
exploration and exploitation strategies dimensions, we first conducted a factor analysis. To
categorize the groups in the sample, we then conducted a cluster analysis. These analyses
were done using SPSS version 13. After doing the cluster analysis, a categorical regression
with optimal scaling (MEULMAN and HEISER, 1999) was performed to determine the
factors more important to determine the innovative behavior.
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Factor Analysis:
The exploratory factor analysis started with the 46 original attributes in the scale. The
first factor extraction, using the principal component model with varimax rotation, revealed
the existence of 17 factors, and some factors had only one attribute. With the help of a matrix
of correlation of these 46 attributes, we were able to discard the attributes that were not
adding to the model. A new factor analysis allowed to the improvement of the model and the
exclusion of other attributes that were not helping explain the model. With 25 attributes, we
run the factor analysis again, and this analysis presented a KMS of 0.811, presenting a good
fit of the sample, and the Bartlett´s test of sphericity was considered significant at the 0.0%
level. Seven factors were extracted from the analysis of 25 attributes that explained 70.9% of
the variance of the model. The eigenvalues and explained variance, as well as the factor
loadings are presented in Table 4.
The RDI was structured in four departments with activities totally distinct, as well as a
support department, we expected to find a large variation regarding the evaluation of the
attributes shown in this survey. For this reason, we checked the dimension related to
innovation, to see if there was significant difference in the groups. The option to examine the
innovation dimension is explained by the fact that, in an R&D institute, the focus is on the
search for innovation, either radical or incremental. To analyze the difference in groups, we
used cluster analysis and identified two separated groups of employees in this institute. The
first group was formed by 36 individuals. These individuals had the higher evaluation for the
four attributes related to innovation, and, therefore, were classified as the Higher Innovators.
The second group, Low Innovators, formed by 34 individuals, had the lower score for the
innovation dimension.
Table 5 shows the statistics related to the factor analyses, the Cronbach´s alpha (its
values are in parentheses), as well as the mean scores for each attribute evaluated, according
to the dimension resulting from the factor analysis, as well as the cluster analysis of high and
low innovators. The factor loadings are presented in the first column, associated with the
mean scores for each attribute, considering the whole sample.
For each attribute, but three (competition, cost, and partnership), the Mann-Whitney U
non-parametric test tended to be significant at the 1% level. This test compares two
independent samples for distributions that do not meet the normality assumption. What this
test revealed was that there were two groups of employees working at the RDI with total
different view regarding the attributes investigated here. For the high innovator group the
means tended to be close to the upper limit in the scale, i.e. positioning more favorably in
agreeing with the attribute. For the dimensions knowledge, innovation and strategy, the
tendency revealed that this group evaluated the RDI with an orientation tending more to the
exploration of knowledge. However, the same group evaluated the dimensions efficiency,
competition, cost and partnership with high values, i.e. the same group evaluated the RDI as
tending to exploitation in these dimensions.
Table 5 presents the means associated to the seven dimensions, according to the two
groups identified in this research. Table 5 also presents the significant correlations for the
dimensions (significance level of 5% or lower). The top of the Table 5 presents the
correlations for the High Innovator group, and lower part presents the correlations related to
the Low Innovator group. Table 5 also presents the means for the dimensions for both groups:
the Low Innovator (in the final column) and the High Innovator (in the line that reads means).
The values for test of Mann-Whitney U for two independent samples are presented in the final
line of Table 5. All the dimensions are significantly different, at 5% level of significance, but
two of them: the dimensions of competition and of partnership. These two dimensions being
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Table 4 – Statistics for the Attributes associated to the dimensions
Factor 1 – Knowledge dimension (0.875)
Volume of new ideas generation (Low – High)
Use o new sources of knowledge (Low – High)
Learning intensity (Low- High)
Form of capaciting the team (Sporadic – Continuous)
People development intensity (Low – High)
There is a constant knowledge sharing (Disagree – Agree)
Social interaction is part of organizational culture (Disagree – Agree)
Individual knowledge appreciation (Low – High)
Factor 2 – Efficiency dimension (0.780)
Degree of existing knowledge utilization (Low – High)
Importance level of efficiency (Low - High)
Concerns about economy of scale (Low – High)
Level of knowledge exploitation (Minimum – Maximum)
Factor 3 - Innovation dimension (0.814)
Focus on products and process totally new (Low – High)
Products improvement (Sporadic – Continuous)
Diversity of generating product or processes (Low – High)
Prototype development (Sporadic – Continuous)
Factor 4 – Strategy dimension (0.713)
Information technology orientation (Weak – Strong)
Strategic view focused on (Present – Future)
Time horizon for the organizational strategy (Short time – Long time)
Factor 5 – Competition dimension (0.766)
Emerging competitors with similar characteristics (Limited – Intense)
Competitor´s activities with similar characteristics (Reduced – Intense)
Factor 6 – Cost dimension (0.764)
Preoccupation with R&D cost (Low – High)
Cost focus (Low – High)
Factor 7 – Partnership dimension
Alliances forming (Situational – Durable)
The intensity level of the partnership contracts (Low – High)
Loadings
Means
Level of innovation
High
Low
Significance
Whitney U
0.619
0.780
0.491
0.784
0.520
0.453
0.420
0.673
3.50
4.03
4.27
4.06
3.96
3.59
3.61
3.77
4.28
4.39
4.89
4.36
4.28
4.14
4.00
4.22
2.68
3.65
3.62
3.74
3.62
3.00
3.18
3.27
0.000
0.013
0.000
0.008
0.010
0.000
0.006
0.002
0.576
0.794
0.663
0.331
3.99
4.39
3.67
3.62
4.44
4.78
4.17
4.16
3.50
3.97
3.15
3.03
0.000
0.008
0.000
0.000
0.572
0.747
0.583
0.774
4.53
4.75
4.14
4.22
2.82
3.18
3.14
2.53
0.000
0.000
0.000
0.000
0.841
0.525
0.528
4.36
4.47
4.11
3.79
3.39
3.12
0.022
0.001
0.000
0.832
0.819
3.69
3.83
3.38
3.12
0.391
0.018
0.875
0.855
4.39
4.50
3.72
3.94
0.036
0.124
0.585
0.787
3.64
3.64
3.32
3.03
0.318
0.025
Mann
-
10
Table 5 – Spearman´s rho coefficients and summated scale means for dimensions
Variables
Means
(Low
innovators)
3.28
MannWhitney U
significance
0.000
1
2
3
4
5
6
1 - Knowledge
Means
(High
innovators)
4.31
2 - Efficiency
4.32
3.47
0.000
3 - Innovation
4.41
2.92
0.000
4 - Strategy
4.31
3.44
0.000
5 - Competition
3.76
3.26
0.060
6 – Cost
4.44
4.44
0.037
7 -Partnership
3.64
3.18
0.060
0.506**
0.630***
0.214
0.462**
0.356*
0.557***
0,072
0,137
0,209
0,113
0.481**
0.403*
0.597***
0.363*
0,319†
0.540***
0,157
0,287
0,069
0,232
0.685***
0.401*
0,137
0.423†
0,295†
-0,120
0,140
-0,53
0.560***
0.191
-0,156
0,151
0.284
0.415*
0,127
0,163
0.204
0.350*
0.049
-0.049
7
Note: The correlation for the low innovators group (N=34) is in light gray, while the
correlations for the high innovators group (N=36) is in bold.
† p < .10. *p < .05. **p < .01. ***p < .001.
11
not different makes sense if we think about the competition for the whole institute as well as
the partnership with the major client (the multinational company) as well as with the major
universities.
Regression with Optimal Scaling (CATREG)
As the previous results revealed that almost all attributes and the mean values for the
dimensions are statistically significantly different between the two groups, two regressions for
categorical data were performed, using the optimal scaling model from the SPSS, version 13.
Regression with optimal scaling is also known by the acronym CATREG, for categorical
regression with optimal scaling. Categorical variables serve to separate groups of cases, and
the technique estimates separate sets of parameters for each group. The estimates coefficients
reflect how changes in the predictor affect the response. Prediction of the response is possible
for any combination of predictor values (MEULMAN and HEISER, 1999). The purpose of
this procedure was to determine if the dimensions that explained the innovation dimension
were the same for both groups. Since the focus of this research project is an R&D institute
that serves a multinational company, we can argue that such type of institute focuses on
developing innovation, and that the innovation depends on all the activities that the institute
performs. Therefore, we can say that the innovation has the following relationship with the
different dimensions: Innovation = F (knowledge, efficiency, strategy, competition, cost,
partnership)
Table 6 presents the results for the two regression equations using the optimal scaling
model (MEULMAN and HEISER, 1999). For the High Innovator group, the dimensions that
are the most important to explain innovation are the knowledge (β=.503; p-value<0.01) and
costs (β=-.465; p-value<0.001), this equation explain 64% of the variance (R2=.64, Adj. R2
=.399). The coefficient for knowledge is positive, indicating that more focus on knowledge
will increase the innovation, while the coefficient for cost is negative, indicating an inverse
relationship: more focus on cost, less innovation. For the Low Innovator group, the
dimensions that are the most important to explain innovation are efficiency (β=.324; pvalue<0.05), competition (β=.618; p-value<0.00), and cost (β=.317; p-value<0.05), this
equation explain 74.5% of the variance (R2=.745, Adj. R2 =.56).
Table 6 - Categorical Regression with optimal scaling
Knowledge
Efficiency
Strategy
Competition
Cost
Partnership
N
R²
Adjusted R²
F
High Innovator
Low Innovator
0.503***
0.226
0.201
0.097
-0.465***
-0.25*
-0.042
0.324**
-0.244*
0.618***
0.317**
0.012
36
0.64
0.399
2.661
34
0.745
0.56
4.04***
Note: standard error in parentheses
*** p < .01 **p < .05 *p < .10
These results show that there is a substantial difference between the two groups
regarding the innovation dimension in the RDI. Moreover, the two regression results are very
consistent to the theory. It seems natural that the group that is more innovative would be more
12
focused on knowledge than in cost. In the other hand, the less innovative group could also be
considering efficiency, competition and cost to be restricting innovation.
March (1991) and his followers (CHENG and VAN de VEN, 1996; HE and WONG,
2004) argue that exploration is related to new sources of knowledge, generation of new ideas,
intense learning processes and organizational empowerment, sharing and valorization of
individual and collective knowledge, as well as a high level of social interaction. This
tendency towards valorization of knowledge should lead to search for totally new products
and processes, product diversification, experimentation with new products and development
of prototypes. Following these stream of thought, it seems that an organization that focus on
exploration will also have a long-term strategic planning as well as a vision towards the
future.
On the other hand, in an organization more oriented towards exploitation, it can be
argued that the control mechanism should be more flexible (BURNS and STALKER, 1961).
The level of efficiency, the economies of scale, the use of explicit knowledge, the use of
information technology, the costs of research and development should not be restrictive
influence in the search for innovation. Regarding competition, during the exploration phase of
an industry, the theory considers that there are few competitors with similar characteristics
which makes it more difficult to develop alliances with partners. At this phase, the
organization is still looking for specific partners to initiate its innovation generation process.
Therefore, the alliances tend to be sparse and the alliance contracts can be established with
less level of details regarding the technical and timing specifications.
One of the main purposes of this research project was to develop of a questionnaire
that could assess the type of strategic orientation towards exploration and exploitation of
knowledge (exploiter or explorer of knowledge). We started with 46 attributes, discarded 19
after the exploratory factor analysis. The final result of this factor analysis showed seven
factors, which are interpreted as the dimensions commented previously.
From the results, the theoretical considerations about exploration and exploitation
need to be bounded. What has been proposed by March (1991) and other researchers refers to
an attempt to create a general model about the implications associated with the exploration
and exploitation strategies and, probably, to specific business situations. The context of the
discussion about the exploration and exploitation strategies needs to be well defined and
explicit for one to argue that exploration involves more risks, more costs, emphasis on the
development of activities to create organizational knowledge as well as to develop
partnerships. Even in one organization, its departments may act in different manner regarding
the exploration and exploitation strategies. Due to its specificities, some departments due to
its activities need to be more explorer, as it should be the case for a P&D department, while
other departments need to be more exploiter, for example the production department.
Also, it is necessary that the discussion uses the two perspectives to analyze the
institute, the internal and external, considering the potential seven dimensions, as identified in
this study. Moreover, this delimitation contribute to make explicit which situations can be
characterized as present in an orientation towards explorer, exploiter, or, even, for a situation
of equilibrium as proposed by March (1991).
Regarding the RDI, object of our study, the theoretical considerations about
exploration and exploitation were not completely verified. For the High Innovator group, the
theoretical expectation related to exploration regarding the dimensions (Table 3) was not
confirmed for two dimensions: efficiency and costs. It was expected that in a situation of
exploration, the preoccupation with efficiency and costs would be relatively lower than in a
situation of exploitation. However, for both dimensions the contrary was true. This fact can be
13
explained by the context that the RDI is in, where it needs to provide its only client with the
lowest cost solution at the fastest time.
For the Low Innovator group, there were also some diverse results comparing to what
was expected. For this case, it was expected that the efficiency dimension would have a
significant influence, the competition dimension would be more intense, and the emphasis on
cost would be higher, as well as the use of partnerships. However, the results showed that the
Low Innovator group had inversed orientation, which translate in a divergent view from the
theoretical considerations.
These divergent findings related to the current theory on exploration and exploitation
should not be taken as conclusive, and they can also be explained by some possibilities, some
of them related to the limitations of this research.
The first limitation refers to the conceptual model developed for this research. Since it
is a first attempt to assess exploration and exploitation, in the proposed format, i.e., to verify
the fit between theory and practice, the formulation of the attributes may have influenced the
results, probably due to lack of definition for the attribute, or they may not be exactly what we
were trying to measure. In this way, the respondents of this research may have had difficulties
in understanding some attributes.
A second limitation refers to the sample used here. Only one institute of research was
used in this assessment. Since the results presented here come from this institute, which has a
very specific range of activities, basically one client, the multinational company that it spinout from; these results are not generalizable to other organizations.
Another limitation refers to the operationalization of the indicators to verify the
model´s hypotheses. Since it was not possible to gather data from a larger number of
organizations and, therefore, to classify them as High and Low Innovators, to analyze the
tendencies of the dimensions developed in this research, we assumed that there was two sets
of employees in the institute analyzed, according to their vision regarding innovation,
assessed by the four attributes of these dimension proposed in this research. In an ideal
situation, it would also be wise to have other attributes to measure innovation, for example, a
measure of the number of innovations developed in the year.
Future studies could be developed focusing on improving the set of attributes related
to exploration and exploitation, as well as the dimensions obtained in this experimental
model. The samples should contemplate organizations in different sectors of activities, aiming
to verify if the theoretical model can be generalized or if there are contingencies that need to
be specified accordingly to the idiosyncrasies inherent to the specific segments of each
organization.
From the academic perspective, the major contribution of this study is related to the
experimental model developed here, which offers elements to start a process of identifying if
the practices of exploration and exploitation are in line with what is expected in theory. From
the practitioner perspective, the model allows to diagnose the elements of the management
process as well as the process of organizational learning, the essence of exploration and
exploitation, given that it offers an ample set of attributes related to the internal and external
environment likely to be measure by the developed scale and, therefore, likely to be compared
over time, as the organization promote actions to change the course in order to fulfill its
strategic and operational objectives.
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