knowledge strategy: its relationship to environmental dynamism and complexity in product development

Knowledge and Process ManagementVolume 17 Number 1 pp 36–47 (2010)Published online in Wiley InterScience

.339
(www.interscience.wiley.com) DOI: 10.1002/kpm
& Research Article

Knowledge Strategy: Its Relationshipto Environmental Dynamism andComplexity in Product Development

Elena Revilla1, Isabel Ma Prieto2* and Beatriz Rodriguez Prado2

1Instituto de Empresa, Madrid, Spain2Facultad CC.EE., Universidad de Valladolid, Valladolid, Spain

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Focusing on product development, this study extends the understanding of the environment-strategy framework andinvestigates the relative effect of two environmental variables, dynamism and complexity, on the product devel-opment knowledge strategy. Adopting a knowledge-based view, and assuming that the strategy’s locus is knowledgecreation (exploration) and knowledge application (exploitation), the study suggests that the development of aknowledge strategy is a managerial strategic choice that is related to the environment. The results of a survey onproduct development managers generally indicate that exploration and exploitation must be combined according toenvironmental factors by generating the alternative knowledge strategies of ambidexterity or punctuated equi-librium. Particularly, the study finds that in environments characterized by high levels of both dynamism andcomplexity product development efforts pursue and reinforce both explorative and exploitative activities through aknowledge strategy of ambidexterity. Though not perfectly supported, punctuated equilibrium seems to be a moreplausible knowledge strategy in environmental contexts where either dynamism or complexity prevails. Copyright #2010 John Wiley & Sons, Ltd.

INTRODUCTION

As competition grows and the pace of changeaccelerates, the development of a steady stream ofnew products is seen as the only way to ensure afirm’s survival and success (Mallic and Schroeder,2005). According to the knowledge base view,product development is a key strategic activity innumerous firms since it creates and applies knowl-edge for effectively dealing with their competitiveenvironment. Specially, new product developmentleads firms to renew themselves through both theexploration and the exploitation of knowledge(Floyd and Lane, 2000; Katila and Ahuja, 2002).

The conceptual distinction between explorationand exploitation (March, 1991) has emerged as anunderlying theme in research on organizationallearning and strategy (Levinthal and March, 1993;Bierly and Chakrabarti, 1996; Vera and Crossan,2003), innovation (Rothaermel and Deeds, 2004) and

rrespondence to: Isabel Ma Prieto, Facultad CC.EE., Univer-d de Valladolid, Avda. Valle de Esgueva, 6, 47011-Valladolid,in. E-mail: [email protected]

*CsS

yright # 2010 John Wiley & Sons, Ltd.

organization theory (Holmqvist, 2003). Explorationis a manifestation of organizational learning thatentails activities such as search, variation, exper-imentation, challenging existing ideas and researchand development. It is thus about improving andrenewing the organization’s expertise and compe-tences to compete in changing markets by introdu-cing the variations needed to provide a sufficientamount of choice to solve problems (March, 1991).Exploitation is a different manifestation of organ-izational learning that involves efficiency, selection,implementation, control, refining and extendingexisting skills and capabilities. It reflects how thefirm harvests and incorporates existing expertiseand competences into its operations, not just foreconomizing the efficiency of existing resourcecombinations (Levinthal and March, 1993), but alsofor creating new ones.

Today near consensus exist on the need fororganizations to engage in both exploration andexploitation activities for long run adaptation andpotential success, but there is less clarity on how thebalance between them can be achieved (Gupta et al.,2006). Some studies (Ghemawat and Costa, 1993;

Knowledge Strategy and Product Development 37

Bierly and Chakrabarti, 1996) suggest that explora-tion and exploitation are competing activities,which results in the need for organizations toemphasize one at the expense of the other. This viewis consistent with the combined knowledge strategyof ‘punctuated equilibrium’, or temporal cyclingbetween long terms of exploration and shortexploitation, or vice versa, which represents amechanism that helps organizations to balanceexploration and exploitation. In contrast, otherstudies (Tushman and O’Reilly, 1996; Katila andAhuja, 2002; Auh and Menguc, 2003; He and Wong,2004; Lubatkin et al., 2006) propose that explorationand exploitation are matching activities, so compa-nies can succeed at both of them simultaneously bythe combined knowledge strategy of ‘ambidex-terity’. The logic behind ambidexterity is the abilityto simultaneously pursue the benefits from bothexploration and exploitation (Benner and Tushman,2003). Ambidexterity and punctuated equilibriumstrategies are very different yet both logical andviable ways to a achieve balance between explora-tion and exploitation. The key question is: Do bothstrategies work equally well, or is the appropriate-ness of each mechanism a function of environmentaland organizational context? (Gupta et al., 2006).

In practice, it has been argued that the punctuatedequilibrium and ambidexterity strategies are theresult of two alternative strategic choices. Inessence, firms need to define a ‘knowledge strategy’as a set of strategic options regarding the knowledgeactivities of exploration and exploitation (Zack,1999; Miller et al., 2007). It has been argued that boththe issues of business strategy (Vera and Crossan,2003) and the environmental features that inspire itshape the strategic choices between exploration andexploitation. An organization’s knowledge strategyidentifies their strategic knowledge gaps, and thesubsequent intentions concerning the inclination toexplore and/or exploit knowledge (Zack, 1999; Veraand Crossan, 2003). A knowledge strategy thusdetermines if the balance between exploration andexploitation is intended to be achieved throughambidexterity or through punctuated equilibrium.

However, there are two important gaps in thisliterature stream on knowledge strategies. First, thefocus of research on knowledge strategy has been onlarge and small firms (Ravasi and Turati, 2005;Bierly and Daly, 2007) without addressing specificissues in the domain of product developments.Whether this is relevant to product development ornot has yet to be addressed. Research in the field oftechnology management has discussed how radicaland incremental innovations usually occur atdifferent points of the industry evolution (Tushmanand Anderson, 1986) but, even when radical andincremental innovations can be viewed as outputsof exploration and exploitation, there is no discus-sion on the appropriateness of each specific knowl-edge strategy.

Copyright # 2010 John Wiley & Sons, Ltd.

A second gap in the literature on knowledgestrategies is the no consideration of the environ-mental context of firms (Bierly and Daly, 2007).Traditionally, a large amount of literature onorganization–environment alignment treats theprocess of alignment as a black box (Gnyawaliand Stewart, 2003). Although the environment-strategy alignment is considered important at ageneral strategic orientation level, the knowledge-based view has mainly focused on the process ofknowledge management and its consequences tofirm performance rather than on the influence onenvironmental factors (Cui et al., 2005). Theinfluence of the environment has been onlyexamined as a moderator of the relationshipbetween knowledge management and firm per-formance (e.g. 36, 25, 6 and 9). As a result, almost noresearch has evaluated the propensity to implementdifferent knowledge strategies in different environ-mental contexts.

The lack of evidence on the influence of theenvironmental factors on the knowledge strategyin product development justifies the need ofadditional empirical investigation of this relation-ship. Accordingly, this study applies the environ-ment-strategy framework to examine the relativeeffects of two classical environmental variables,environmental dynamism and environmentalcomplexity, on the knowledge strategy adopted inproduct development.

We begin this paper by characterizing theknowledge strategy in product development interms of the choices between a punctuated equi-librium strategy and an ambidexterity strategyas alternative mechanism for balancing explorationand exploitation. Next, we introduce the roleof environmental dynamisms and environmentalcomplexity as antecedents of the knowledgestrategy in product development, and introducethe proposed hypotheses. Then, we test thehypotheses on the basis of data generated from aquestionnaire survey involving a number of pro-duct development programmes. Results and adiscussion of implications, limitations and futureresearch directions conclude the paper.

KNOWLEDGE STRATEGIES IN PRODUCTDEVELOPMENT

To be successful in product development firms needexploring their existing knowledge and compe-tences while, at the same time, exploring newknowledge to avoid dysfunctional rigidities (Leo-nard Barton, 1992). Product development is there-fore a knowledge intensive process, aimed atcreating new knowledge and recombining existingknowledge to create new products that have valuein the marketplace. Specifically, exploitation andexploration activities must emerge throughout a

Know. Process Mgmt. 17, 36–47 (2010)DOI: 10.1002/kpm

38 E. Revilla, I. Ma Prieto and B. R. Prado

problem resolution process aimed to create newproducts (Mohrman et al., 2003). Knowledgeexploitation occurs with the utilization of existingknowledge for innovative problem solving. Knowl-edge exploration occurs when existing knowledgeis not sufficient to solve a problem, so thatnew knowledge needs to be constructed oracquired to solve it. In other words, individualscreate and apply knowledge through a problemidentification and resolution process (Nonaka et al.,2000).

Exploration and exploitation activities reflectdifferent but complementary knowledge activitiesthat must be addressed through a proper ‘knowl-edge strategy’ (Bierly and Daly, 2007). Authors inthe field of organizational knowledge have recentlydeveloped the idea of the ‘knowledge strategy’. Inexample, Bierly and Chakrabarti (1996) define theknowledge strategy as the set of strategic choicesthat shape and direct the organization’s learningprocesses and determine the firm’s knowledge base.Zack (1999) defines knowledge strategy as ‘theoverall approach an organization intends to take toalign its knowledge resources and capabilities to theintellectual requirements of its strategy’ (p. 135).The knowledge strategy allows the identification ofimportant knowledge gaps as a basis to takedecisions regarding the creation, developmentand use of a firm’s knowledge in alignment withthe requirements of the business strategy. Thesedecisions concern the managerial choices on how tobalance knowledge exploration and knowledgeexploitation, together with choices on the use ofinternal and external knowledge (Vera and Crossan,2003).

Product development involves the choice of aknowledge strategy that determines the relianceon new knowledge versus existing knowledge, asrequired by the problem recognition and resol-ution processes. In other words, product devel-opment requires a knowledge strategy to addressthe question of how to balance knowledgeexploration and knowledge exploitation activi-ties. Following Gupta et al. (2006), there are twodifferent yet both essentially logical strategies toachieve a balance between exploration andexploitation, which are punctuated equilibriumand ambidexterity. Punctuated equilibrium des-cribes a knowledge strategy based on longcycling through periods of exploration andexploitation. Ambidexterity describes a knowl-edge strategy based on the synchronous excel ofboth exploration and exploitation. Existing lit-erature is silent on the question of whether thesetwo strategies are equally viable, and whetherexogenous and endogenous contextual factorsshould drive the choice between them. Thispaper analyses some relevant exogenous factorsand their potential influence on the knowledgestrategy.


FORMULATING THE KNOWLEDGESTRATEGY: THE ROLE OFENVIRONMENTAL CONTEXTS INPRODUCT DEVELOPMENT

The environment-strategy framework states thatenvironmental factors are decisive when a firm isdetermining its strategy (Venkatraman, 1989; Luoand Park, 2001). In fact, literature of both strategicco-alignment (Astley and Van de Ven, 1983) andstrategic choice (Child, 1997, 2004), shown the firmas a proactive participant in the environment able toadapt its strategy in response to environmentalrequirements (Child, 1997).

There is wide discussion in the literature onthe direct influence of the environment on a firm’sstrategic choices (Venkatraman and Camillus, 1984).Using contingency theory, Koufteros et al. (2005)analyse how environmental uncertainty and equivo-cality moderate product innovation. In their study oflearning behaviours in product innovation, Chap-man and Hyland (2004) analyse the role of environ-mental complexity. Knowledge theorists have pro-posed that the choice between exploration andexploitation (or whether they may be combined insome manner) is somehow determined by environ-mental conditions. For example, Teece et al. (1997)have proposed a dynamic competences model rootedin the knowledge-based literature wherein dyna-mism comes from rapidly changing environments.At the same line, Eisenhardt and Martin (2000)suggest that a firm’s development pattern of effectivedynamic capabilities—its reliance on new or existingknowledge—depends upon market dynamism.Researchers such as Jaworski and Kohli (1993) havealso identified a direct relationship between marketdynamisms and the firms’ strategic use of knowledgeresources. Finally, Aragon-Correa and Sharma (2003)explain the moderating role of environmentaluncertainty and complexity in the relationshipbetween dynamic capabilities and sustainable com-petitive advantage.

Every source of environmental change thus leadsfirms to realize if they possess adequate knowledgefor effectively dealing with that change. Accord-ingly, different environmental contexts requireaddressing appropriate knowledge strategies tocreate and use knowledge. Specifically, productdevelopment requires firms to define a knowledgestrategy to set up how to create and apply knowl-edge in order to achieve a proper alignment with theenvironment. In other words, product developmentrequires a ‘fit’ between the surrounding environ-mental context and the knowledge strategy. There-fore, this research presumes that particular environ-mental factors will induce specific balances ofexploitation and exploration in product develop-ment by formulating a knowledge strategy that goesfor the mechanisms of punctuated equilibrium orambidexterity.



Dynamism and complexity

A significant number of articles in the literature onorganizational environment have studied its dimen-sions focusing on different perspectives (Fuentes-Fuentes et al., 2004). These environmental dimen-sions have allowed authors to investigate howenvironmental factors affect several organizationalstrategic aspects and performance. The key issue isidentifying what environmental dimensions shouldbe considered. Despite the fact that organizationalenvironment is a fundamental concept in manage-ment theory, there is little consensus regarding itsconceptualization and measurement (Fuentes-Fuentes et al., 2004; Bierly and Daly, 2007). Wehave chosen two commonly used dimensions fromenvironmental research that have been shown toinfluence the organization and its internal processes(Dess and Beard, 1984; Daft and Lengel, 1986):dynamism and complexity. Both dimensionsshould have significant effects since they areusually defined as the source of significant environ-mental uncertainty (Thompson, 1967; Gnyawali andStewart, 2003). These dimensions are discussedbelow.

Environmental dynamism describes the rate ofchange in the environment and the unpredictabilityof that change (Dess and Beard, 1984; Bierly andDaly, 2007). Dynamic business environments maybe characterized by changes in various marketelements, such as customer preferences, technologyand competitor structure. The terms ‘turbulence’and ‘volatility’ refer to environmental character-istics similar to environmental dynamism and theyall are related to the degree and speed of changes(Ansoff, 1979). Extreme situations of environmentaldynamism result in conditions of ‘hyper compe-tition’, where the benefits derived from almost allform of competitive advantage are short-lived(Bierly and Daly, 2007). Iansity (1995) suggests thatemergent levels of environmental dynamism lead tomore uncertainty in product development, whichalso reduces the predictability and effects of changethe changes.

Environmental complexity refers to the prolifer-ation and diversity of relevant factors in theenvironment (Duncan, 1972). The higher thenumber of factors and the extent of differencesamong them then the higher the environmentalcomplexity. This dimension shows the level ofcomplexity of knowledge about the environmentthat an organization needs (Fuentes-Fuenteset al., 2004). Several authors compare theconcept of heterogeneity to complexity. Heterogen-eity describes whether the elements in the environ-ment are similar or different from one another(Thompson, 1967). According to Duncan (Duncan,1972), the complexity of the environment isassociated to the heterogeneity of firm’s activities.In this same vein, Lawrence and Lorsch (Lawrence


and Lorsch, 1967) have pointed out that complexenvironments require a high level of internaldifferentiation. In terms of knowledge, complexityrefers both to the variety and sources of knowledgethat needs to be combined in product development.

Hypotheses

In a highly dynamic environment, repeated changesin customer demands, technology and businesspractices require firms to continuously modify theirproducts or services to stay competitive. Changemakes existing product and services obsolete andrequires the development of new ones (Sorensenand Stuart, 2000; Jansen et al., 2006). Likewise,sudden and unpredictable changes may reduce thevalue of a firm’s existing knowledge and evenrender it obsolete (Hitt et al., 2000). To minimize thethreat of obsolescence, firms need to introduce anexploratory strategy and develop new products thatmove away from existing products, services andmarkets. This is possible by solving new problemsthrough knowledge exploration.

The benefits of knowledge exploitation are lessin dynamic environments (Bierly and Daly, 2007).This is the reason why firms operating in dynamicenvironments need to invest in the development oftheir human resources, and depend of theirskills development (Hart, 1995). Managers facingdynamic business environments tend to be moreproactive, taking greater risk and using moreinnovative strategies than managers in less turbu-lent environments (Miles and Snow, 1978) in anattempt to anticipate events and implement pre-ventive actions, rather than merely responding toevents that have already occurred. When environ-mental opportunity is high, there is thus strategicvalue in developing and applying new knowledgeand competencies (Pisano, 1994). In stable environ-ments, customer preferences are relatively stableand, therefore, competition is based on strategiesrelating to efficiency and cost reduction. Therefore,the focus is thus on incremental processes ofproduct developments rather than radical productinnovations (Bierly and Daly, 2007). Also, domi-nant designs are more durable in stable environ-ments. In these circumstances, firms may becomecomplacent, not learning as fast as firms facinghigher environmental dynamisms. As a result,firms invest less in the development of newproducts. When dynamism is not high, significantinvestment in exploration would be probablyinefficient.

In relation to complexity, firms facing complexenvironments have problems to identify the keyfactors strategically important for success (Amit andSchoemaker, 1993). Complexity increases the num-ber of criteria to be specified by different functionswithin the organization, including units focused onthe exploitation and management of technology,



manufacturing and marketing. In addition, environ-mental complexity requires the integration ofknowledge from several knowledge domains. Theneed to integrate an increasing number of thesedomains requires the development of effectivecoordination mechanisms within any productdevelopment initiative.

Complexity also increases dependency amongthe different functional knowledge areas involvedin product development. It thus increases the needof connecting people so they can think together andcreate contexts where knowledge can flow and beinterpreted and leveraged (McDermott, 1999; Ber-drow and Lane, 2003). In these circumstances, aspointed by Henderson and Cockburn (1994), theability to integrate and recombine different knowl-edge streams and competences is a critical success-ful factor. According to their findings, complexity isrelated with communication problems and to theneed of strong feedback between upstream (e.g.design engineers) and downstream knowledgeworkers (e.g. design engineers), users, suppliersand producers due to differences in language,norms and mental models. Basically, environmentalcomplexity raises coordination costs and the needfor greater diversity of knowledge. As a result,extensive risk taking and a strong emphasis oninnovation (exploration) may be hazardous andincrease the probability of failure. High complexitylevels firms difficult to make fundamental changesto any relevant aspect of their business; hence theytend to make simply small adjustments (Smart andVertinsky, 1984). Conversely, product developmentunits react to high complexity by modifying orexpanding current products, services, or markets(exploitation) to build customer loyalty whileavoiding the substantial cost associated to explora-tory strategies.

By combining both dimensions of dynamism andcomplexity it is possible to obtain a two by twomatrix, as presented in Figure 1. Since the effects ofdynamism and complexity on exploration andexploitation are likely to be different as impliedby the preceding arguments, we presume that the

Punctuated equilibexplorative cy

(high exploration aexploitation)

LowAmbidexterit

(low exploration anexploitation)

Low

Low

High

C

DYNAMISM

Figure 1 Knowledge strategie


knowledge strategy within each of the cells of thematrix is likely to vary according to the environ-mental dimensions. Environmental contexts charac-terized by low levels of both dynamism andcomplexity will lead to the formulation of aknowledge strategy of low ambidexterity sincethe required levels of both exploration and exploi-tation are low. On the contrary, an environmentalcontext characterized by high levels of bothdynamism and complexity will simultaneouslydemands high knowledge exploration and knowl-edge exploitation, so the balance between themcharacterizes a knowledge strategy of ambidexter-ity. When the environmental context has highdynamism and low complexity, the appropriateknowledge strategy may be formulated in terms ofpunctuated equilibrium cycling through successivephases of an explorative cycle (high levelsof exploration accompanied by low levels ofexploitation). Conversely, an environmental contextwith low dynamism and high complexity is alsolikely to result in the adoption of a knowledgestrategy in terms of punctuated equilibrium.However, now the punctuated equilibrium strategycycles through phases of an exploitative cycle (highlevels of exploitation accompanied by low levels ofexploration). The preceding discussion allows us toformulate the following hypotheses:

H1: The higher the level of dynamism and complexity,the greater is the likelihood that the knowledgestrategy in product development involves a high levelof exploration and high level of exploitation (highambidexterity).

H2: The lower the level of dynamism and complexity,the greater is the likelihood that the knowledgestrategy in product development involves a low levelof exploration and low level of exploitation (lowambidexterity).

H3: The higher the level of dynamism when complex-ity is low, the greater is the likelihood that theknowledge strategy in product development willinvolve cycling through phases of high levels of

rium in cle nd low

High Ambidexterity (high exploration and

high exploitation)

y d low

Punctuated equilibrium in exploitative cycle (low exploration and

high exploitation)

HighOMPLEXITY

s in product development


Table 1 Profile of participating companies

Per cent

SectorIndustrial 75.7Service 24.3

Number of employees<¼ 499 65.8500–999 9.61000–4999 12.3


exploration and low levels of exploitation (punctuatedequilibrium).

H4: The higher the level of complexity whendynamism is low, the greater is the likelihood thatthe knowledge strategy in product development willinvolve cycling through phases of low levels ofexploration and high levels of exploitation (punctu-ated equilibrium).

5000–9999 6.8>¼ 10000 5.5

Age of the firm1–10 years 24.411–50 years 60.0>50 years 15.6

NationalitySpanish 71.4Multinational 25.7

RESEARCH METHODOLOGY

Sample characteristics and data collection

Survey methodology was used to gather data for theempirical analysis. The questionnaire was useddesigned and developed by the authors on the basisof a thorough literature review, and next validatedthrough a pre-test carried out through severalpersonal interviews with product developmentexecutives. These interviews allowed to improvethe quality of the survey items and rectify anypotential deficiency. Minor adjustments were madeon the basis of specific suggestions.

After the pilot study, the mailing list was obtainedfrom Madriþd (Madrid, Spain). Madriþd(www.madridmasd.org) is a society that groupsfirms and public research organizations with theaim of improving competitiveness by encouragingIþD, innovation and knowledge transfer. Madrid isthe most developed area in Spain, and the onethat concentrates the largest number of firms. Byfocusing on this area, the study gains well-grounded insight into the effectiveness of variouspractices being able to develop more credibleconstructs (Koufteros et al., 2005). Therefore, thepopulation was composed of Spanish firms focusedon R&D and innovation operating in the local areaof Madrid. Madriþd was able to provide a list of3293 organizations (private and public researchorganizations), but not all of them involved in newproduct development. For this reason, we removedpublic research organizations and service compa-nies from the list. We then focused on firms wherethe incidence of product development was strong,providing a final list of 616 companies.

Targeted respondents were product developmentmanagers who agreed to participate in the study.They received the questionnaire by e-mail or byaccessing it on the Web. They answered questionsconcerning a specific product development projectfinished by 2004. A researcher involved in the studyhelped respondents to answer any questions theyhad about the survey.

The data collection process yielded 80 usableresponses (response rate of 12.93%). Table 1 showsthe profile of the participating companies andrespondents. In terms of industry type, answerscovered a wide number of industries, including


food and beverage (20%), chemistry and pharma-ceutical (11.3%), electric systems and electronics(10.1%), computing systems (7.5%), equipmentmanufacture (5%) and transport (5%). Most of therespondents were product development managersfrom firms with less than 500 employees, i.e. smallfirms. To assess control variables bias, the influenceof firm size, firm age and nationality was assessedby means of ANOVA tests. Results show that thenull hypothesis of equal means could not beenrejected and therefore firm size, firm age andnationality did not affect environmental dimensionsor knowledge strategy dimensions.

Since a single response was asked, singleinformant bias in data collection might stem asa result. However, the presence of commonmethod bias was tested by following one of theprocedures described in Podsakoff et al. (2003).More precisely, Harman’s single factor procedurewas applied in such a way that all items from themain constructs were included into an exploratoryfactor analysis to examine the unrotated factorssolution and determine the number of factors thatare necessary to account for the variance in thevariables. In this analysis, no single factor emergedand no general factor accounted for the majority ofthe covariance among the measures, so it may beconcluded that common method bias is not aproblem.

Description of the measures

The measurement of the analysis variables has beenbuilt on a multiple-items method, which enhancesconfidence about the accuracy and consistency ofthe assessment. Each item was based on a five pointLikert scale and all of them are perceptual variables.Table 2 displays items used to measure the analysisvariables.


Table 2 Items, definition of constructors and internal consistency measures

Construct Measurement item Factorial analysis

Loadingfactor�

Varianceextracted (%)

Reliability(Cronbach’s a)

Environmentdimensions

Dynamism Large of number of new product ideas hasbeen possible through technologicalbreakthroughs in the industry

0.87 39.8 0.73

Rate of technology change that the firmcurrently experiences

0.85

Technological changes provided bigopportunities in the industry

0.83

Customers’ preferences changed quite a bitover time

0.67

Complexity Level of the firm’s product complexity 0.87 28.5 0.84Level of the firm’s process complexity 0.82Knowledge intensity of the productdevelopment process

0.67

Knowledgestrategy

KnowledgeExploration

Product problem areas generatingcustomer dissatisfaction were discoveredand solved through creative ways

0.87 33.55 0.83

Problem areas generating customerdissatisfaction were discovered and solvedthrough creative ways

0.85

New knowledge, methods andtechnological ideas were introduced

0.75

Many new novel and creative ideas wereproduced by ‘thinking outside the box’

0.74

KnowledgeExploitation

Valuable existing knowledge elementswere identified, combined and reused

0.80 28.92 0.73

Existing knowledge and competencesrelated to existing products/services wereused and adjusted

0.76

New and existing ways of doing thingswere integrated without hinderingefficiency

0.70

Lessons learned in other areas of theorganization were put in operation

0.67

�Principal components.


Following previous studies, the environmentalcontext in product development has been definedas a multidimensional construct where environ-mental dynamism and complexity are consideredto be the representative dimensions. The measurewhich was used to capture environmental dynamismis based on four items concerning technology andmarket dynamism. These items were adaptedfrom the works of Gupta and Wilemon (1990),Jaworski and Kohli (1993) and Fuentes-Fuenteset al. (2004). Based on the works of Clark andFujimoto (1991), Clark and Wheelwright (1995) andFuentes-Fuentes et al. (2004), we assessed theenvironmental complexity by assessing the level ofcomplexity of the firm’s products and processes,and the intensity of knowledge during the productdevelopment.

Since this paper has conceptualized knowledgestrategy in product development in terms of thechoices between punctuated equilibrium and ambi-dexterity as alternative mechanism for balancingexploration and exploitation, it is necessary to


construct separate scales for exploration andexploitation. As stated by Crossan et al. (1999),exploration takes place when product developmentgenerates new knowledge. Conversely, exploitationencompasses processes that take and transmitembedded knowledge that has been learnt fromthe past into the product development process.They are thus different knowledge activities of theknowledge strategy, rather than two ends of auni-dimensional scale (He and Wong, 2004).Accordingly, and based on Katila and Ahuja(2002), He and Wong (2004) and Lubatkin et al.(2006), the firm’s knowledge strategy has beenmeasured by developing a scale of eight items, fouritems related to exploration and four items related toexploitation. The first four items measured howproduct development introduces new ideas andnew knowledge by addressing problematic areas.The last four items measured how productdevelopment introduces lessons learnt in the past,existing competences and integration of pastknowledge.



ANALYSIS AND RESULTS

Data analysis involves several steps. First, sinceour research variables were measured throughmultiple-item constructs, we need to verify thatitems tapped into their stipulated construct. Thus,we conduct two independent factorial analyses withvarimax rotation by using SPSS 13.0 for Windows:one for the knowledge strategy items and other onefor the environment dimensions items. Results aretwo factors that condense the original nominalvariable information while providing continuousvariables for each group of variables (Table 2). Theinternal consistency measures (Cronbach’s a)are also obtained to assess the reliability of themeasurement instruments.

Second, we apply a cluster analysis to the enviro-nmental dimensions in order to define differentenvironmental contexts in terms of dynamism andcomplexity. A major issue of the clustering techniqueis determining the number of clusters. In our case, weapplied a Ward’s hierarchical method using theEuclidean distance and an agglomeration schedule todetermine the number of clusters and the initial seeds(centres of the groups) to be used in a second K-means non-hierarchical analysis that provides thefinal categorization of the firms. The decision on thenumber of clusters is guided by an agglomerationcoefficient, which represents the squared Euclideandistance between each case or group of cases (seeTable 3). The agglomeration coefficient increasesnoticeably from clusters 5 to 4, from cluster 4 to3 and from cluster 3 to 2, which in terms of thepercentage change in the clustering coefficient, leadus to determine that the appropriate number ofclusters is four. This final result shows cleardifferences between clusters 1 and 2, and clusters3 and 4, while the distance between centres ofclusters 2 and 3 is quite a lot smaller. Both contextmeasures have discriminatory power. (See ANOVAtest, Table 4).

The characterization of clusters based on the finalcentres is presented in Table 4. Cluster 1 includes28 product developments with low levels in bothenvironmental dynamism and complexity. Highlevels in both dynamism and complexity charac-

Table 3 Analysis of agglomeration coefficients�

Numberof cluster

AgglomerationCoefficient

Change in coefficientin the next level (%)

6 29.18 15.05 33.56 17.34 39.39 37.83 54.28 69.22 91.87 54.61 142

�Hierarchical cluster based on Ward method and Euclideandistance.


terize cluster 2, which comprises 14 productdevelopments. Cluster 3 only includes nine pro-duct development characterized by high levels indynamism and lowest levels in complexity. Finally,the low levels in dynamism and the highest levels incomplexity characterize Cluster 4, with 21 elements.

Next, the relationship between the knowledgestrategy (exploration and exploitation) and theenvironment of product development is analysedwithin each group/cluster. Table 5 shows descrip-tive statistics (mean and deviation values) andANOVA test for the segmented environments. Asindicated by the ANOVA test, our results showdifferences in exploration and exploitation as aresult of differences in the environmental context ofproduct development. These differences are especi-ally significant in terms of exploitation (p¼ 0.95),but also rather significant in terms of exploration(p¼ 0.93).

To better analyse the differences, we have plottedthe mean values of both knowledge exploration andexploitation in Figure 2. Both Table 5 and the plot inFigure 2 show that those environments with lowdynamism and complexity (cluster 1) lead to thelowest mean values in both exploration (2.59) andexploitation (2.74), thus characterizing productdevelopments with a knowledge strategy of lowambidexterity as predicted by hypotheses H2. Onthe contrary, the environments with high dyna-mism and complexity (cluster 2) lead to the highestmean values in exploration (3.41) and a similarmean value in exploitation (3.08), which may beinferred as a knowledge strategy of high ambidex-terity, as predicted by hypothesis H1.

Further, the environmental context with a highlevel in dynamism but low complexity (cluster 3)shows a mean value for exploration (2.99) higherthan for exploitation (2.80). However, as we mayobserve in Figure 2, the levels of exploration andexploitation are quite similar, so there is no clearsupport for hypothesis H3. Finally, environmentalcontext characterized by low dynamism and highcomplexity (cluster 4) lead to the highest meanvalues in exploitation (3.60) and a moderate meanvalue in exploration (2.72), which corresponds to aknowledge strategy of punctuated equilibriumcycling on exploitation as predicted by hypothesesH4.

Together with exploration and exploitation wehave included the analysis within each cluster of themultiplicative interaction of both exploration andexploitation to evaluate their joint effects, whichspecially make sense in terms of ambidexterity(p¼ 0.96) (Bierly and Daly, 2007). As we wouldexpect, Table 5 shows important differences forcluster 1 (which showed similar low mean valuesfor both exploration and exploitation) and cluster 2(which showed similar high mean values for bothexploration and exploitation). So, it is appropriate tocharacterize the knowledge strategy for cluster 1 as


Table 5 ANOVA test for effects of environment dimensions on knowledge strategies

Clusters Exploration Exploitation Exploration �exploitation

Cluster 1: Low dynamism-Low complexity 2.59 (1.0) 2.74 (0.9) 6.99 (4.1)Cluster 2: High dynamism-High complexity 3.41 (0.7) 3.08 (1.0) 10.38 (4.2)Cluster 3: High dynamism-Low complexity 2.99 (1.3) 2.80 (0.9) 9.07 (6.34)Cluster 4: Low dynamism-High complexity 2.72 (0.8) 3.60 (1.1) 9.72 (3.64)Total 2.84 (1.0) 3.07 (1.0) 8.70 (4.46)F (Signif.) 2.41 (0.07)�� 3.53 (0.01)� 2.57 (0.06)��

Main Group differences (Tuckey test) (1-2) (1-4)�

Homogenous groups (Duncan Test) (1-4-3)(4-3-2) (1-3-2)(2-4)�

In brackets standard deviation.�p< 0.05; ��p< 0.1.

Table 4 Results of cluster analysis of context dimensions (K-means)

Cluster 1Low–Low

Cluster 2High–High

Cluster 3High–Low

Cluster 4Low–High

Total F (ANOVA)

Dynamism 2.36 (0.6) 3.79 (0.4) 4.16 (0.5) 1.96 (0.5) 2.75 (1.0) 54.87 (0.00)�

Complexity 2.06 (0.5) 3.75 (0.5) 2.38 (0.4) 3.81 (0.6) 2.94 (1.0) 52.81 (0.00)�

N 28 14 9 21 72

In brackets: standard deviation.�Significance level. �p< 0.05; ��p< 0.1.

1

2

3

4

5

Cluster 1: Lowdynamism-Low

complexity

Cluster 2: Highdynamism-High

complexity

Cluster 3: HighDymanism -Low

complexity

Cluster 4: LowDymanism-High

complexity

Exploration Exploitation

Figure 2 Mean values of knowledge strategies in fourenvironmental contexts


low ambidexterity and the knowledge strategy forcluster 2 as high ambidexterity. These results arefully consistent with the hypotheses H1 are H2 andFigure 1.

DISCUSSION

Knowledge is the fundamental basis of competitionand competitive advantage. Successful competitionrequires aligning the knowledge strategy of the firmto the characteristic of its environment. Research onknowledge strategy based on the concepts ofknowledge exploration and knowledge exploitationis still evolving, but the understanding of theantecedents of both knowledge activities remainsunclear. Although past research has suggested that


environmental factors influence on the choice ofthe knowledge strategy that shapes the balance ofexploration and exploitation, empirical investi-gation has produced mixed results. Focusing onproduct development, this study extends theunderstanding of the environment-strategy frame-work and investigates the effects of two classicalenvironmental variables, dynamism and complex-ity, on the knowledge strategy in product develop-ment.

First of all, this study supports that productdevelopment does not involve a trade off betweenthe exploration and the exploitation of knowledgein such a way that one would occur at the expense ofthe other. On the contrary, product developmentefforts simultaneously develop both knowledgeexploration and exploitation, so that the balancebetween them is intended to be achieved throughtwo alternative strategies, namely: ambidexterity orthrough punctuated equilibrium. Specifically, it isargued that exploration and exploitation arecombined in accordance with environmental factorsthrough the adoption of the alternative knowledgestrategies of ambidexterity or punctuated equi-librium.

Since all firms compete in particular environ-ments, they must define a knowledge strategylinked to the intellectual requirements of theseenvironments. Our findings indicate that theenvironmental factors influence a firm’s productdevelopment’s strategy for generating and using



knowledge. Our results confirm that the knowledgestrategy in product development is a managementchoice related to the environmental context. Assuch, this study corroborates the direct effects ofdynamism and complexity on the knowledgestrategy. Specially, our findings suggest thatproduct development efforts operating in dynamiccomplex and dynamic environments choose anambidexterity strategy by pursuing both explora-tion and exploitation simultaneously. Although itseems that environmental dynamism and complex-ity stimulate a higher level of knowledge gener-ation, this situation leads to ambidexterity bysimultaneously reinforcing exploration and exploi-tation.

On the contrary, when the environment is mostlydynamic or mostly complex, the knowledgestrategy will tend to a punctuated equilibrium.Specially, we find support to the fact that productdevelopments functioning in highly complex butlow dynamic environments follow exploitation,thus characterizing a knowledge strategy basedon punctuated equilibrium (cycling on exploita-tion). Therefore, the higher the level of complexity,the higher the level of exploitation as there isstrategic value in using and combining existingknowledge for innovative solving problem activities.So, it is possible to infer that product developmentsfacing complex situations exhibit an experience effectthat includes the application and integration of pastexperience and competences. Results do not fullysupport that high environmental dynamism and lowcomplexity lead to a knowledge strategy based onexploration cycling (punctuated equilibrium). In thissituation exploration is higher than exploitation, butthe gap between them is small, maybe due to the factthat the study mostly focus on small firms whereavailable opportunities need to be exploited anytimeto maintain the competitive position of the firm.

In terms of managerial practice, this studysuggests that organizations and managers confrontan increasingly contradictory word, and productdevelopment is not an exception. Managers shouldrecognize and accept a paradoxical approach tomanagement in product development and put theireffort on sustaining rather than avoiding it.Additionally, this study provides various manage-rial implications regarding how product develop-ment copes with different environmental conditionsand selects certain strategic options. The findingsof this study shed light on the importance ofproduct development strategic flexibility. Since thevalue of exploitation and/or exploration is differentunder different environmental conditions, it isimportant for product development managers tounderstand the knowledge strategies (ambidexter-ity or punctuated equilibrium) most appropriate foreach environmental conditions. Combinations ofexploration and exploitation occur then in align-ment with patterns of environmental factors to


generate a powerful mechanism for competitiveadvantage. In conclusion, since product develop-ment determines firm’s profits, growth, marketshare and other key metrics, the knowledge strategycannot be formulated in isolation of factors thatcharacterize the environmental context.

LIMITATIONS

Although this study has provided several newinsights, it has several limitations. First, the scope ofthis study is limited to firms located in Madrid area.In addition, sample size is not large. Extending thestudy to other geographic areas may lead toconceptual refinement and insight. Second, thisstudy has tried to define their constructs as preciselyas possible by drawing on relevant literature andthrough a careful process of item generation andrefinement. Evidently, this measurement effortrepresents an advance for research but, nonetheless,the items are far for being perfect as long as theymeasure facts that are neither fully nor easilymeasurable. Third, this article studies productdevelopment function given its prominence incompetitiveness and knowledge management lit-erature. Future studies need to examine otherfunctions important to operation management(e.g. supply chain). Fifth, all data were collectedfrom the same respondent using the same percep-tual measurement technique. Although the pre-sence of common method is tested and results showthat common method bias should not be a problem,multiple respondents should be considered infuture research on to rule out potential drawbacks.Finally, it is also important to note that this work isonly a preliminary step towards a better under-standing of the effects of two environmentaldimensions on the knowledge strategy choice inproduct development and, on the basis of previouslimitations, it naturally points out avenues forfuture research.

REFERENCES

Amit R, Schoemaker PJ. 1993. Strategic assets and organ-izational rent. Strategic Management Journal 14: 33–45.

Ansoff HI. 1979. Strategic Management. The McMillanPress Ltd.: London.

Aragon-Correa JA, Sharma S. 2003. A contingent resource-based view of proactive corporate environmentalstrategy. Academy of Management Review 28: 71–88.

Astley WG, Van de Ven AH. 1983. Central perspectivesand debates in organization theory. AdministrationScience Quarterly 28: 245–273.

Auh S, Menguc S. 2003. A test of strategic orientationformation vs. strategic orientation implementation: theinfluence of TMT functional diversity and inter-func-tional coordination. Journal of Marketing Theory andPractice 13: 4–19.



Benner MJ, Tushman ML. 2003. Exploitation, explorationand process management: the productivity dilemmarevisited. Academy of Management Review 28: 238–256.

Berdrow I, Lane H. 2003. International joint ventures:creating value through successful knowledge manage-ment. Journal of World Business 8: 15–30.

Bierly P, Chakrabarti A. 1996. Generic knowledgestrategies in the U.S. pharmaceutical industry. StrategicManagement Journal 17: winter special issue 123–135.

Bierly PE, Daly PS. 2007. Alternative knowledge strat-egies, competitive environment, and organizationalperformance in small manufacturing firms. Entrepre-neurship Theory and Practice 31: 493–516.

Chapman R, Hyland P. 2004. Complexity and learning beha-viours in product innovation. Technovation 24: 553–561.

Child J. 2004. (1972) Organizational structure, environ-ment and performance: the role of strategic choice.Sociology 6: 1–22.

Child J. 1997. Strategic choice in the analysis of action,structure, organizations and environment: retrospectand prospect. Organizations Studies 18: 43–76.

Clark KB, Fujimoto T. 1991. Product Development Pefor-mance. Harvard Business School Press: Boston.

Clark KB, Wheelwright SC. 1995. Leading Product Devel-opment. The Free Press: New York.

Crossan MM, Lane HW, White RE. 1999. An organiz-ational learning framework: from intuition to institu-tion. Academy of Management Review 24: 522–537.

Cui AS, Griffith DA, Cavusgil ST. 2005. The influence ofcompetitive intensity and market dynamism on knowl-edge management capabilities of multinational corpor-ation subsidiaries. Journal of International Marketing 13:32–53.

Daft RL, Lengel RH. 1986. Organizational informationrequirement, media richness and structural determi-nants. Management Science 32: 554–571.

Dess R, Beard DW. 1984. Dimensions of organizationaltask environments. Administrative Science Quarterly 29:52–73.

Duncan RB. 1972. Characteristics of organizationalenvironments and perceived environments uncer-tainty. Administrative Science Quarterly 17: 313–327.

Eisenhardt KM, Martin JK. 2000. Dynamic capabilities:what are they? Strategic Management Journal 21: 1105–1121.

Floyd SW, Lane PJ. 2000. Strategizing throughout theorganization: managing role conflict in strategicrenewal. Academy of Management Review 25: 154–177.

Fuentes-Fuentes MM, Albacete-Saez CA, Lloreis-MontesFJ. 2004. The impact of environmental characteristicson TQM principles and organizational performance.Omega 32: 425–442.

Ghemawat P, Costa JE. 1993. The organizational tensionbetween static and dynamic efficiency. Strategic Man-agement Journal 14: 59–73.

Gnyawali DR, Stewart AC. 2003. A contingency perspect-ive on organizational learning: integrating environmen-tal context, organizational learning processes, and typesof learning. Management Learning 34: 63–89.

Gupta AK, Wilemon DL. 1990. Accelerating the develop-ment of technology-based new products. CaliforniaManagement Review 32: 24–44.

Gupta AK, Smith KG, Shalley CE. 2006. The interplaybetween exploration and exploitation. Academy ofManagement Journal 49: 693–706.

Hart SL. 1995. A natural-resources-based view of the firm.Academy of Management Review 20: 874–907.

He Z, Wong P. 2004. Exploration vs. exploitation: anempirical test of the ambidexterity hypothesis. Organ-ization Science 15: 481–494.


Henderson R, Cockburn I. 1994. Measuring competence:exploring firm effects in pharmaceutical research.Strategic Management Journal 15: 63–84.

Hitt MA, Ireland RD, Lee H. 2000. Technological learning,knowledge management, firm grow, and performance:an introductory essay. Journal of Engineering and Tech-nology Management 10: 231–246.

Holmqvist R. 2003. A dynamic model of intra- and inter-organizational learning. Organization Studies 24: 95–123.

Iansity M. 1995. Shooting the rapids: managing productdevelopment in turbulent environments. CaliforniaManagement Review 38: 37–58.

Jansen J, Van Den Bosch F, Volberda HW. 2006. Explora-tory innovation, exploitative innovation, and perform-ance: effects of organizational antecedents andenvironmental moderators. Decision Science 52: 1661–1674.

Jaworski BJ, Kholi AK. 1993. Market orientation: antece-dents and consequences. Journal of Marketing 57: 53–70.

Katila R, Ahuja G. 2002. Something old, something new: alongitudinal study of search behaviour and new pro-duct introduction. Academy of Management Journal 20:1183–1194.

Koufteros X, Vonderemse M, Jayaram J. 2005. Internal andexternal integration for product development: the con-tingency effects of uncertainty, equivocality and plat-form strategy. Decision Science 36: 97–133.

Lawrence PR, Lorsch JW. 1967. Organization and Environ-ment. Harvard Business School Press: Boston, MA.

Leonard Barton D. 1992. Core capabilities and core rigid-ities: a paradox in managing new product develop-ment. Strategic Management Journal 13: 111–125.

Levinthal DA, March JG. 1993. The myopia of learning.Strategic Management Journal 14: 95–112.

Lubatkin MH, Simsek Z, Ling Y, Veiga JF. 2006. Ambi-dexterity and performance in small to medium-sizefirms: the pivotal role of top management team beha-vioral integration. Journal of Management 32: 646–672.

Luo Y, Park SH. 2001. Strategic alignment and perform-ance of market-seeking MNCs in China. Strategic Man-agement Journal 22: 141–155.

Mallic DM, Schroeder RG. 2005. An integrated frameworkfor measuring product development performance inhigh technology industries. Production and OperationsManagement 4: 142–158.

March JG. 1991. Exploration and exploitation in organiz-ational learning. Organization Science 2: 71–87.

McDermott R. 1999. Why information technologyinspired but cannot deliver knowledge management.California Management Review 41: 103–117.

Miles R, Snow C. 1978. Organizational Strategy, Structureand Process. McGraw-Hill: New York.

Miller BM, Bierly PE, Daly PS. 2007. The knowledge strategyorientation scale: individual perceptions of firm-levelphenomena. Journal of Managerial Issues 19: 414–435.

Mohrman SA, Finegold D, Mohrman AM. 2003.An empirical model of the organization knowledgesystem in new product development firms. Journal ofEngineering and Technology Management 20: 7–38.

Nonaka I, Toyama R, Nagata A. 2000. A firm as a knowl-edge-creating entity: a new perspective on the theory ofthe firm. Industrial and Corporate Change 9: 1–20.

Pisano GP. 1994. Knowledge, integration, and locus oflearning: an empirical analysis of process development.Strategic Management Journal 15: 85–100.

Podsakoff PM, MacKenzie B, Lee J-Y, Podsakoff NP. 2003.Common method biases in behavioural research: acritical review of the literature and recommended reme-dies. Journal of Applied Psychology 88: 879–903.

Ravasi D, Turati C. 2005. Exploring entrepreneuriallearning: a comparative study of technology develop-



ment projects. Journal of Business Venturing 20: 137–174.

Rothaermel RT, Deeds DL. 2004. Exploration and exploita-tion alliances in biotechnology: a system of new productdevelopment. Strategic Management Journal 25: 201–221.

Smart C, Vertinsky I. 1984. Strategy and the environment:an study to corporate responses to crisis. Strategic Man-agement Journal 5: 199–213.

Sorensen JB, Stuart TE. 2000. Aging, obsolescence andorganizational innovation. Administrative Science Quar-terly 45: 81–113.

Teece DJ, Pisano G, Shuen A. 1997. Dynamic capabilitiesand strategic management. StrategicManagement Journal18: 509–533.

Thompson JD. 1967. Organization in Action. McGraw-Hill:New York.

Tushman ML, Anderson P. 1986. Technological disconti-nuities and organizational environments. Administra-tive Science Quarterly 31: 439–465.

Tushman M, O’Reilly C. 1996. Ambidextrous organiz-ations: managing evolutionary and revolutionarychange. California Management Review 38: 8–30.


Venkatraman N. 1989. The concept of fit instrategy research: toward verbal and statisticalcorrespondence. Academy of Management Review 14:423–444.

Venkatraman N, Camillus JC. 1984. Exploring the conceptof fit in strategy management. Academy of ManagementReview 9: 513–525.

Vera D, Crossan M. 2003. Organizational learningand knowledge management: toward an integrativeframework. In Handbook of Organizational Learning andKnowledge Management. Easterby-Smith M, Lyles M(eds). Blackwell: Oxford; 123–141.

Zack MH. 1999. Developing a knowledge strategy. Cali-fornia Management Review 41: 125–145.

Zahra SA. 1996. Technology strategy and financial per-formance: examining the moderating role of the firm’scompetitive environment. Journal of Business Venturing11: 189–219.

Zahra SA, Bogner WC. 1999. Technology strategy andsoftware new venture’s performance: exploring effectof the competitive environment. Journal of BusinessVenturing 15: 135–173.


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