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Knowledge Management in StrategicAlliances: A Review of Empirical

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Matthias MeierFreie Universität Berlin, Institute of Management, Garystr. 21, D-14195 Berlin, Germany

Corresponding author email: [email protected]

Knowledge-related and organizational learning processes in alliances have receivedmuch attention throughout the last 25 years. The field has generated a rapidly growingbody of empirical evidence on how knowledge is managed in alliances. However, thesphere is highly complex, fragmented, incoherent, and heterogeneous in terms of thetheoretical approaches applied. This paper presents an integrative and organizingframework for the empirical literature on knowledge management in strategic alli-ances. It illustrates how the knowledge management outcomes of knowledge creation,transfer and application are determined by four distinct sets of factors: knowledgecharacteristics, partner characteristics, partner interaction, and active knowledgemanagement. Based on this framework, this review analyses and integrates empiricalevidence in order to identify where findings converge and where results conflict. So far,research has focused strongly on singular interrelations between these four sets offactors and the transfer of knowledge. Conversely, the questions of how knowledge iscreated, retained, retrieved and applied and how the interplay of the different factorsaffects knowledge management in strategic alliances remain widely unexplored. Thereview concludes with a summary of the current state of the art in empirical researchand discusses some promising avenues for future investigation.

Introduction

Over the past 25 years, the number of strategic alli-ances has grown considerably (e.g. Anand andKhanna 2000; Dyer et al. 2004; Grant and Baden-Fuller 2004). In the same vein, the number of relatedstudies in the management literature has increasedtremendously. Various motives for firms entering intoalliances have been discussed: in order to gainmarket power, reduce and share risks and costs,increase efficiency, and access and acquire externalknowledge (Bleeke and Ernst 1991; Grant andBaden-Fuller 2004; Hennart 1988; Kogut 1988;

Osland and Yaprak 1995; Powell 1987). As know-ledge emerges as a central resource critical to thedevelopment of capabilities, products and services,alliances are being recognized increasingly as anorganizational form to acquire and internalize theknowledge needed in the quest for competitiveadvantage (Grant 1996b; Inkpen 1996; Kale et al.2000; Simonin 2004; Spender 1996). Therefore,scholars have asserted that processes such as thecreation, transfer and application of knowledge con-tribute significantly to alliance survival, and organi-zational and alliance performance (e.g. Hamel 1991;Inkpen and Beamish 1997; Kogut and Zander 1992;Lyles and Salk 1996; Nonaka 1994; Steensma andLyles 2000; Tsang et al. 2004).

Knowledge management in alliances has thusbecome a critical management task (Collins and Hitt

This review has benefited greatly from comments and sug-gestions made by Robert DeFillippi and two anonymousreviewers.

International Journal of Management Reviews, Vol. 13, 1–23 (2011)DOI: 10.1111/j.1468-2370.2010.00287.x

© 2010 The AuthorInternational Journal of Management Reviews © 2010 British Academy of Management and Blackwell Publishing Ltd.Published by Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA02148, USA

2006), and a key research area within the allianceliterature (Hamel 1991; Inkpen and Crossan 1995;Kale et al. 2000; Khanna et al. 1998; Lane et al.2001; Mowery et al. 1996; Simonin 2004). This lit-erature is characterized by a wide array of empiricalcontexts, theoretical perspectives and methods. Forexample, theories include the resource-based view,the dynamic capabilities perspective, the knowledge-based view, technology management, economics ofinnovation, transaction cost economics and the orga-nizational learning perspective (Kale et al. 2000;Mowery et al. 1996; Spender and Grant 1996).Owing to the interdisciplinary nature of the phenom-enon, the field is cross-disciplinary, complex andfragmented, and in need of a coherent framework tomap it.

The purpose of this paper is to develop an integra-tive framework which organizes existing empiricalevidence on knowledge management in strategic alli-ances. Furthermore, this paper aims to identify areasof convergence, areas of divergence and salientresearch gaps.

The paper is set out in four sections. First, a frame-work is developed to organize the literature andempirical evidence on knowledge management inalliances. Secondly, the search methodology appliedin this review is outlined. Thirdly, an overview of keyaspects of knowledge management emerging fromempirical work is provided. Areas of convergence aresummarized, and ambiguous findings are translatedinto promising research questions. Finally, the lastsection provides an overview of the key findings andan outlook on future research.

The framework

Knowledge resources have become critical for theachievement of competitive advantage in today’shighly dynamic business environment (e.g. Collinsand Hitt 2006). In particular, the resource-based view(Barney 1991) highlights the central role of intan-gible resources in gaining a competitive advantage.Extending the resource-based view, the knowledge-based view of the firm focuses especially on know-ledge as the strategically most important resource(Grant 1996b). At the core of a knowledge-basedtheory of the firm is the idea that firms are platformsfor the creation and application of knowledge(Spender 1996). Inkpen (2000, p. 1020) builds onthis idea and states that ‘the essence of the firm is itsability to create, transfer, assemble, integrate, and

exploit knowledge assets, a process that has come tobe known as knowledge management’.

In the literature, knowledge management isdescribed using varying sets of knowledge processes.However, these definitions differ only slightly, interms of number and the labelling of processes ratherthan in the underlying concepts (Alavi and Leidner2001). Thus, a classification of knowledge processeshas to be viewed as more informative than definitive,since processes are interlaced and not easily sepa-rable.1 For didactic reasons, this review uses a clas-sification into knowledge creation, transfer andapplication. This classification comprehends know-ledge management across the entire value chain andprovides a categorization suitable to organize exist-ing empirical evidence on the topic in hand. Whileknowledge creation and application have been thecentral processes in formulating the knowledge-based theory of the firm (cf. Spender 1996), know-ledge transfer has been at the focus of existingalliance research (cf. Grant and Baden-Fuller 2004).

The notion of knowledge creation is associatedwith the development of new or novel knowledge(e.g. Argote et al. 2003; Spender and Grant 1996;Teece 1998). Nonaka (1994) depicts knowledgecreation from an organizational perspective as anamplification process in which individuals createknowledge that disseminates throughout the organi-zation. In the alliance context, knowledge creationdescribes the joint development of new knowledgeby alliance partners (cf. Inkpen 1996; Khanna et al.1998; Lubatkin et al. 2001; Reid et al. 2001). Com-pared with this, knowledge transfer refers to thetransmission process whereby existing knowledge istransferred within or across firm boundaries (e.g.Collins and Hitt 2006). While organizations receiveknowledge through knowledge creation and transfer(cf. de Holan and Phillips 2004), knowledge appli-cation describes how such knowledge is embeddedand used to create value (Grant 1996a; Lane et al.2001).

In an era of increasing globalization andknowledge-based competition, strategic alliances are

1The attributional problem described here is common forthe academic discussion of knowledge management. Forexample, the organizational learning reasoning understandsknowledge processes in a more integrative manner and doesnot always clearly distinguish processes (e.g. Inkpen andCrossan 1995). In the remainder of this review, I will inter-pret on the substantive ideas captured by the reviewedstudies rather than on the (arbitrary) labels found in theseworks.

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© 2010 The AuthorInternational Journal of Management Reviews © 2010 British Academy of Management and Blackwell Publishing Ltd.

discussed as an important vehicle for these know-ledge management processes (Hamel 1991; Khannaet al. 1998). Although firms enter alliances for avariety of reasons (see e.g. Kale et al. 2000), thisreview focuses on learning and knowledge-relatedaspects and understands strategic alliances as volun-tary arrangements between firms with the objectiveof jointly creating, transferring or applying know-ledge to commercial ends.2

So far, research on knowledge management in alli-ances has attempted primarily to explain the out-comes of related knowledge management processes.But what are knowledge management outcomes?Reid et al. (2001) cite the accumulation of know-ledge assets such as patents, new products or tech-nologies as one possible embodiment of knowledgecreation in alliances.3 Hence, knowledge outcomesmanifest themselves in knowledge assets and are,according to Teece (1998), the underpinnings of firmcompetences, which in turn make firms capable ofoffering products and services to the market. Thus,knowledge management outcomes assess the extentto which knowledge management processes resultin the accumulation or dissolution of knowledgeassets.

There is a broad consensus that intra- and inter-organizational knowledge outcomes are basicallydetermined by three sets of factors: the characteris-tics of knowledge, those of the alliance partners, andthose of their interaction and relationship (cf. Argoteet al. 2003; Inkpen 2002; Simonin 1999b, 2004;Szulanski 1996). While this well-established classi-fication deals in particular with the question of whatfactors influence knowledge management outcomes,more and more attention is now being given to themechanisms that affect knowledge management out-comes, i.e. the question of how and why certain con-textual factors affect organizational learning andknowledge management outcomes (cf. Argote et al.2003). If knowledge management is understood as aconscious co-ordination and monitoring of know-ledge processes (cf. Inkpen 2000), the means and

measures implemented describe how firms activelymanage knowledge. The governance choice (Kaleet al. 2000) and a wide range of specific organiza-tional routines, control and co-ordination mecha-nisms (e.g. Berdrow and Lane 2003) thus constitutea fourth set of factors, which has not been coveredby the established categorization so far. The way inwhich firms achieve strategic and operational inte-gration, how they develop a valuable alliance rela-tionship, and how mechanisms vary according to theknowledge type handled are of utmost interest forpractitioners and academics, however. To includethis action-oriented aspect, these factors are incor-porated under the heading of ‘Active KnowledgeManagement’.

In conclusion, this article proposes a frameworkthat organizes empirical evidence around the twodimensions of knowledge management outcomesand determinants of knowledge management out-comes (Figure 1).4 This framework functions as apoint of departure and clearly outlines the purpose ofthis review. The primary goal of this review is thus toinvestigate the empirically examined determinantsaffecting knowledge management outcomes in stra-tegic alliances. The next section outlines the meth-odology applied in the review.

Methodology

Although a significant number of articles have beenpublished on knowledge management in strategicalliances, there is still no systematic and comprehen-sive overview. Basically, this article follows the prin-ciples for systematic review suggested by Tranfieldet al. (2003). In order to provide a systematic, trans-parent and replicable methodology, the reviewfollows a number of stages:

(1) An initial list of keywords based on the author’sprior experience was discussed with a reviewpanel of three experienced academics in thefield of knowledge management and alliance

2While Gulati (1998, p. 293) broadly defines ‘strategic alli-ances as voluntary arrangements between firms involvingexchange, sharing, or co-development of products, technolo-gies or services’, this review adopts a knowledge-based per-spective and refers to the respective underlying knowledgeprocesses.3Nonaka et al. (2006) cite routines, know-how, concepts,patents, technologies, designs and brands as possibleexamples for knowledge assets.

4The framework presented in this article is to a large extentinspired by the framework of Argote et al. (2003), whichorganizes the literature on learning and knowledge manage-ment in organizations. Due to the different research interestof this article, in particular, the review of empirical evidenceon knowledge management in strategic alliances and fordidactic reasons, the framework presented here is a revisedversion and partly differs from the original framework.

Knowledge Management in Strategic Alliances 3


research. This discussion yielded a total of 25keywords.5

(2) Search strings were constructed with the key-words identified in Stage (1) and discussed withthe review panel. This discussion resulted in atotal of 110 search strings. Examples are:[‘Alliance*’ AND ‘knowledge access*’],[‘Interorgani*’ AND ‘knowledge creat*’],[‘Joint venture*’ AND ‘knowledge appl*’],[‘Cooperation’ AND ‘knowledge transfer’],[‘Dyad*’ AND ‘learning’].

(3) The review was limited to peer-reviewed journalarticles, i.e. leaving out books, book chaptersand conference proceedings. As the IJMR standsfor authoritative statements on research in thefield of business and management (Armstrongand Wilkinson 2007), the review panel suggestedhonouring this claim by confining the search tohigh-quality journals in the domain of businessand management. Following Armstrong andWilkinson (2007), the Social Science CitationIndex (SSCI) was used to identify journals forinclusion. Journals listed in the subject catego-ries business and management of the ISI Web ofKnowledge with a 5-Year-Impact-Factor biggerthan 1.5 were included (for journals establishedlater than 2003, a cut-off value of 1 for the

current Impact Factor was chosen). This selec-tion yielded a list of 83 journals.

(4) The EBSCO host (Business Source Premier) wasthe main database for the literature search. Jour-nals not available on EBSCO were eithersearched manually or via ScienceDirect. Thesearch strings developed in Stage (2) were used tosearch for the title, abstract and author-providedkeywords. A total of 365 articles were retrieved.

(5) The 365 articles were reviewed in order todevelop exclusion and inclusion criteria for thereview (cf. Pittaway et al. 2004). These (seeAppendixes 1 and 2) were discussed with thereview panel and subsequently used to reviewthe initial list. The titles and abstracts6 of the 365articles were reviewed against the exclusion (229articles excluded) and inclusion criteria (67articles excluded), leaving 71 articles as relevant.

(6) In order to assess the search strategy and tocounter its one-dimensionality, the citationrecords of the 10 most frequently cited articles(total citations within the EBSCO host) werereviewed. This procedure yielded 684 additionalarticles for revision. The articles were reviewedaccording to the exclusion and inclusion criteria(Appendixes 1 and 2). At this stage, conceptualand theoretical articles were excluded, and onlyarticles with an empirical basis were kept. Thisprocedure provided ten additional articles, onecase study and nine quantitative empiricalstudies.

5Keywords identified by the review panel: alliance,co-operation, collaboration, dyad, exploitation/exploration,interorganizational, joint venture, knowledge access, know-ledge acquisition, knowledge activity, knowledge activist,knowledge application, knowledge connection, knowledgecreation, knowledge flow, knowledge generation, knowledgegovernance, knowledge management, knowledge retaining,knowledge retention, knowledge sharing, knowledge stock,knowledge transfer, learning

6In cases where the title and abstract were not informativeenough to include or exclude the article straightaway,articles were downloaded and assessed in detail.

Figure 1. Framework mapping empirical evidence on knowledge management in strategic alliances (Source: adapted from Argote et al.2003)

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Altogether, the search methodology yielded a total of81 articles, of which 22 are conceptual/theoretical innature, four provide exploratory analysis, 11 rely onqualitative methods, and 44 articles contain quanti-tative methods. Furthermore, a number of additionalarticles cited in the reviewed studies are included, asthey contribute essential concepts that are necessaryto make sense of the evidence base and to structurethe research findings.

Besides an organizing framework, Figure 1 alsooffers a concise overview of the main areas ofresearch in the field. While Figure 2 provides adetailed grid that classifies the empirical findings ofthe reviewed articles into the framework7, Figure 1aggregates the research on the interrelations betweenknowledge management outcomes and the determi-nants reviewed. The circles in Figure 1 represent thenumber of studies which have analysed these particu-lar interrelations. For example, the first circle in thesecond row illustrates that 16 studies contain analy-ses on the influence of knowledge type on knowledgetransfer. Furthermore, a detailed analysis of Figure 2provides information on every single study and theirrespective research design (i.e. explorative, qualita-tive, quantitative). It becomes obvious that researchhas focused strongly on the outcome of knowledgetransfer. Here, in particular, scholars have analysedhow partner characteristics, partner interactions andmeasures of active knowledge management influenceknowledge transfer. Although a lot of theoreticalthinking has been devoted to the interrelationbetween different knowledge types and knowledgemanagement outcomes, empirical verification clearlylags behind. Figure 2 further demonstrates that thedifferent research designs are not biased towards acertain interrelationship, but are relatively similarlydistributed across the research areas.

To sum up, only a fraction of the articles reviewedempirically examine the way in which knowledge iscreated and applied in alliances. Instead, the maininterest centres on how the partner characteristics,their interaction and the actions they take to manageknowledge can influence knowledge transfer in alli-ance relationships.8

In the following, the four sets of determinants:‘knowledge characteristics’, ‘partner characteris-tics’, ‘partner interaction’ and ‘active knowledgemanagement’ are used to group the discussion of thestudies. First, the four sub-sections aim to analyseand synthesize the key findings. Secondly, this analy-sis is used to derive promising research questions.

Knowledge management in alliances –Empirical evidence

Knowledge characteristics

The interest in defining and classifying knowledgedates back to early Greek philosophers such as Aris-totle and Plato (e.g. Grant 1996a; Spender 1996).Ever since, knowledge has been an elusive conceptand a broad range of different classifications hasbeen proposed in management research (Birkinshawet al. 2002). Rooted in resource-based logic, thetheory of Reed and DeFillippi (1990) allows for anaggregation of the pertinent knowledge characteris-tics, based on the concept of causal ambiguity. Thecausal ambiguity of a firm’s skills and resourcesraises barriers to imitation and, thus, contributes tocompetitive advantage. Furthermore, in terms ofknowledge, it describes the inability of firms tounderstand and imitate the knowledge constitutingthe competitive advantage of a competitor (cf. Reedand DeFillippi 1990; Simonin 1999a,b; Szulanski1996). In the literature, the knowledge dimensions oftacitness, complexity and specificity are discussed assources of competitive advantage and ambiguity(Reed and DeFillippi 1990).

The distinction between tacit and explicit know-ledge goes back to Polanyi (1966). He describesexplicit knowledge as knowledge that can be codifiedin a formal and systematic language, while tacitknowledge is non-verbalizable, intuitive and un-articulated. Nonaka (1994) elaborates on this further,maintaining that tacit knowledge is context-specific,difficult to articulate, personally bounded, and deeplyrooted in action. Since highly explicit knowledge iseasy to codify, its transfer is comparatively easy. Bycontrast, the organizational embeddedness of tacitknowledge makes codification difficult, thus imped-ing its transfer (Kogut and Zander 1992). Zander andKogut (1995) find that the degree of knowledge codi-fication and teachability determines how fast capa-bilities can be transferred. In basic terms, tacitnessdetermines the ease of knowledge transfer (Grant

7Note that Figure 2 includes 48 studies instead of the 59empirical studies identified in the search. One explorativeand ten quantitative studies only indirectly address know-ledge management outcomes. Therefore a classification intoFigure 2 is omitted for these ten studies.8I thank an anonymous reviewer for the suggestion to orga-nize extant empirical evidence in a grid.



Figure 2. Classification of empirical evidence. Note: EX = Explorative; QL = Qualitative; QN = Quantitative

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1996a,b). Complexity arises if a wide range ofknowledge is integrated into organizational routines,technologies, and individual- or team-based experi-ence (cf. Grant 1996a; Reed and DeFillippi 1990).Zander and Kogut (1995, 79) argue that knowledge‘is more complex when it draws upon distinct andmultiple kinds of competencies’. Specificity is essen-tially borrowed from transaction cost economics andrefers to investments in skills and resources whichare specific to certain transaction relations (cf. Reedand DeFillippi 1990). In a similar way to tacitness,both complexity and specificity contribute to theambiguity of knowledge, which in turn impedes thetransfer of knowledge.

Although qualitative research confirms the hin-dering effect of tacitness on knowledge transfer (e.g.Hamel 1991; Inkpen 2000; Inkpen and Pien 2006), awidely accepted instrument of measurement is stilllacking (cf. Becerra et al. 2008). However, severalstudies have provided original scales to measureknowledge tacitness (cf. Becerra et al. 2008; Chen2004; Hau and Evangelista 2007; Simonin 1999a,b,2004). Chen’s (2004) study finds support for theassumption that the degree of tacitness determineshow easily knowledge is transferred. In contrast,Simonin (1999a,b, 2004) argues and provides evi-dence that tacitness does not have a direct influenceon knowledge transfer, but is mediated by know-ledge ambiguity. Although Simonin (1999a,b, 2004)proposes a mediation model, his work reaffirms theimportance of knowledge tacitness as a decisivefactor, which complicates the transfer of knowledgein alliances. In comparison, specificity is found tobe insignificant, and the influence of complexityvaries according to certain moderators (Simonin1999a,b). Knowledge complexity increases ambigu-ity in younger alliances, for companies with lowerlevels of collaborative know-how and for firms allo-cating fewer resources to the knowledge transferprocess. Therefore, Simonin (1999b) argues thatfirms are capable of actively facilitating knowledgetransfer by reducing the complexity associated withknowledge.

So far, research has been preoccupied with tacit-ness as a knowledge characteristic (cf. Dyer andNobeoka 2000; Grant 1996a,b; Thuc Anh et al.2006), and the way in which the complexity andspecificity of knowledge directly affects knowledgemanagement processes has remained relativelyunclear. The difficulty in constructing appropriateinstruments of measurement for knowledge charac-teristics such as tacitness, complexity, and specificity

is explained by their interrelations with ambiguity.Knowledge that is embedded in various levels of anorganization (cf. Inkpen and Dinur 1998), difficult toarticulate, deeply rooted in action, complex and spe-cific evades straightforward detection.

Although a mutually exclusive distinction ofknowledge into a tacit and an explicit dimensionsupports theoretical argumentation, the extremetypes of completely tacit or explicit knowledge willbe the exception (cf. Grant 1996a,b; Inkpen andDinur 1998). Knowledge always incorporates bothaspects to a certain degree. Dhanaraj et al. (2004)and Evangelista and Hau (2009) find that the transferof explicit knowledge is accompanied by the transferof tacit knowledge. What are the theoretical implica-tions stemming from knowledge characterized by amedium level of tacitness?

Comparatively little research has been conductedon the direct relationship between knowledge char-acteristics and knowledge transfer. However, existingevidence is contradictory. On the one hand, tacitknowledge promises competitive advantage (Lylesand Salk 1996; Thuc Anh et al. 2006) and thereforerepresents a major motive for alliances. On the otherhand, tacit knowledge is difficult to transfer andinherently impedes capitalizing on the alliance. Weare in need of more research to consolidate previousresults and to further understanding of how know-ledge characterized by different combinations of theaforementioned characteristics affects knowledgemanagement in alliances.

Furthermore, research has examined knowledgetransfer from a relatively general perspective. Infor-mants are asked almost exclusively to evaluate – onrelatively global scales – the extent to which tech-nology, know-how or capabilities are transferred(cf. Lyles and Salk 1996). A more precise survey ofsingle knowledge assets as confined entities ofknowledge (see e.g. Szulanski 1996) would allow amore precise elaboration of the effects of know-ledge characteristics on knowledge managementprocesses.

Partner characteristics

A large amount of research effort has been investedinto analysing how the characteristics of the alliancepartners influence knowledge management out-comes. Besides relatively general factors such asfirm size or nationality, scholars have discussedknowledge-related alliance motives (Grant andBaden-Fuller 2004), as well as learning intention and



absorptive capacity of partners (Hamel 1991) as spe-cific factors having an influence on knowledge man-agement outcomes.

Knowledge-related alliance motives. There isbroad consensus among scholars that alliances serveas a conduit for inter-organizational knowledge cre-ation, transfer and application (see, e.g. Inkpen andCrossan 1995; Kale et al. 2000; Khanna et al. 1998;Lane and Lubatkin 1998; Lane et al. 2001; Larssonet al. 1998; Lyles and Salk 1996; Mowery et al.1996; Simonin 1999a,b, 2004).

In their studies Larsson et al. (1998) and Grantand Baden-Fuller (2004) identify different researchstreams that explain why firms enter into alliances.While Grant and Baden-Fuller (2004) differentiatebetween the desires to access or acquire knowledgefrom the partner, Larsson et al. (1998) distinguishbetween the joint creation of completely new know-ledge and the transfer of existing knowledge amongpartners. Thus, firms seem to be motivated either bythe purpose of creating new knowledge jointly, trans-ferring existing knowledge between partners, orcombining existing complementary knowledge viajoint knowledge application.9

The studies of Mowery et al. (1996) and Rothaer-mel and Deeds (2004) provide some empirical evi-dence to support these assumptions. Mowery et al’.s(1996) study reveals that knowledge bases of alliancepartners either significantly converge or divergeduring the relationship. The authors conclude thatpartners are motivated either by a desire to transferknowledge (converging knowledge bases) or toincrease knowledge specialization (diverging know-ledge bases) and recombine their specific knowledge.Similarly, Rothaermel and Deeds (2004) find thatknowledge-related alliance motives differ during dif-ferent product development stages.

The insight that knowledge-related alliancemotives differ might help explain better the ‘puzzle’of so-called learning races (e.g. Kale et al. 2000;Khanna et al. 1998). Alliance partners might onlyface a serious trade-off between co-operation andcompetition if both are primarily motivatedto transfer the partner’s existing knowledge;

Pérez-Nordtvedt et al. (2008) show that firms in pos-session of valuable tacit knowledge are particularlyattractive as alliance partners. In addition, firms seemto be well aware of their attractiveness due to theirtacit knowledge (Norman 2002). Norman’s (2002)study illustrates that firms are more protective abouttheir knowledge as tacitness increases. Hence,co-operation might turn into competition if one firmis overly persistent in appropriating tacit knowledgefrom its partner while not sharing its own proprietaryknowledge (cf. also Khanna et al. 1998). This rela-tion might even be intensified if alliance partners arecompetitors in the same market. In contrast, jointknowledge creation and complementary applicationwill exert lesser competitive pressures on the alli-ance, as partners are less concerned with unintendedknowledge transfer. Grunwald and Kieser (2007)show that the software product development alli-ances in their case study are motivated by the recom-bination of the existing knowledge of alliancepartners and that knowledge transfer is reduced to aminimum.

A future research question is that of how know-ledge management differs with respect to theknowledge-related motives of partners. Knowledge-related alliance motives might have a signallingeffect on the partner. Norman’s (2002) study pro-vides some evidence that firms perceiving the highlearning intents of their partners are in turn moreprotective of their knowledge. Investigation intohow firms co-ordinate potentially unbalanced learn-ing motives represents an exciting research field.Distinguishing different knowledge-related motivesalso has important methodological implications.Researchers need to be clear about the dependentvariables of interest, since the success of co-specialization alliances is not how much knowledgehas been transferred, but how successful alliancepartners have been in jointly applying existingknowledge.

Learning intent. While the motives describedabove are the reasons for entering into alliances(Beamish and Berdrow 2003), learning intentdescribes the degree of determination to acquire(Tsang 2002) and internalize certain knowledge andskills from the partner and is thus a precondition ofknowledge transfer in the post-formation alliancemanagement phase (Hamel 1991). Norman (2002,pp. 180–181) defines learning intent as ‘the desire ofthe partner to gain access to and learn from the focalfirm’. Pérez-Nordtvedt et al. (2008) demonstrate that

9Grant and Baden-Fuller (2004) present the example of thealliance between Daimler and Swatch to illustrate that alli-ances can also be motivated by the combination of existingknowledge bases, without necessarily having the desire toacquire the knowledge of the alliance partner. Cf. also Hauand Evangelista (2007) and Dussauge et al. (2000).

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the degree of learning intent depends on the potentialcontribution of the partner’s knowledge to the firm’sown competitive advantage. This desire translatesinto the amount of resources that a firm is willing tocontribute to knowledge-related processes. Conse-quently, the learning intent will affect knowledgemanagement outcomes (Beamish and Berdrow2003).

Pérez-Nordtvedt et al. (2008), Hau and Evange-lista (2007) and Simonin (1999b) show that higherlearning intent facilitates the transfer of knowledge.But how does a higher degree of learning intentlead to a more efficient and effective transfer ofknowledge?

Wu and Cavusgil (2006) find that firms with astronger learning intent are generally more commit-ted to an alliance relationship. The learning intent ofa firm is reflected in the commitment of the topmanagement to deploy resources to the knowledgetransfer process (Beamish and Berdrow 2003;Norman 2002; Simonin 2004; Tsang et al. 2004; Wuand Cavusgil 2006). Tsang (2002) analyses whetherthe learning intent of firms actually determines howmany resources are deployed to the transfer process.In contrast to theoretical predictions, he finds thatlearning intent has only weak effects on resourceallocation. In a similar vein, Simonin’s (2004) studyprovides no evidence that learning intent influenceshow resources are allocated to knowledge manage-ment practices. However, he finds a significantlypositive effect of learning intent on knowledgetransfer.

While previous findings focus on the link betweenlearning intent, management commitment and theallocation of resources to the transfer process,Norman (2002, 2004) provides a look at learningintent from the other side. The results of her studyillustrate the fact that excessively high degrees oflearning intent may have counterproductive effectson knowledge transfer. Firms which perceive thelearning intent of their partner as high are more pro-tective of their knowledge and will restrict commu-nication and knowledge flows. Recapitulating thesefindings suggests that the relationship between learn-ing intent and knowledge transfer may follow aninverted u-shaped logic. If the learning intent is verylow, firms will not devote resources to knowledgetransfer – and knowledge transfer remains negligible.Further increases in learning intent will stimulateknowledge transfer to a maximum, until additionalincreases eventually lead to a restriction of commu-nication and protection of knowledge, as the partner

perceives the learning intent of its counterpart as apotential threat. Both Tsang (2002) and Simonin(2004) find that, despite the top management’s com-mitment to knowledge transfer, commitment doesnot influence resource allocation. Future researchshould focus on the major agents who translate topmanagement’s learning intent into knowledge man-agement practices (Nonaka et al. 2006). From thisperspective, failure to reach knowledge-related goalsmight be explained by an unsuccessful implementa-tion of the knowledge management agenda ratherthan by insufficient top management commitment. Abreeding ground for this idea is Simonin’s (2004)study, which discloses an additive effect of top man-agement commitment and learning agenda on know-ledge transfer, while the hypothesized mediatedrelationship (commitment → agenda → transfer)finds no support.

Absorptive capacity. While learning intentdescribes the motivation and willingness of anorganization to deploy resources to knowledge man-agement, absorptive capacity describes the organiza-tion’s ability to learn from the partner (Steensma andLyles 2000). In their seminal paper, Cohen andLevinthal (1990, p. 128) define a firm’s absorptivecapacity as ‘the ability of a firm to recognize thevalue of new, external information, assimilate it, andapply it to commercial ends’.10 Empirically, absorp-tive capacity has been approximated by R&D spend-ing (Cohen and Levinthal 1990) in various studies.However, results concerning its impact on know-ledge management outcomes are somewhat mixed.Schoenmakers and Duysters (2006) find a weakeffect of R&D spending on knowledge transfer inalliances, while no effect is found by Mowery et al.(1996). Mowery et al. (1996) introduce some alter-native measurements for absorptive capacity and finda positive effect of pre-alliance knowledge overlapon knowledge transfer. Based on these findings, Dyerand Singh (1998) argue that the capacity to absorbexternal knowledge varies as a function of therespective alliance partner. They assume that a firm’sabsorptive capacity depends on its pre-allianceknowledge overlap with the partner and on the inter-action routines between the partners. Lane andLubatkin (1998) also advocate the idea of a relativeabsorptive capacity and argue that an overlap in basic

10For a comprehensive overview on the concept of absorp-tive capacity see Lane et al. (2006) and Zahra and George(2002).



knowledge supports mutual understanding and even-tually joint knowledge creation and transfer. Further-more, they argue that knowledge creation andtransfer are determined by the degree of dissimilarityin specialized knowledge, since completely identicalbases of specialized knowledge would not offerpotential for the transfer of unknown knowledge.Lane and Lubatkin (1998) find empirical evidencethat an overlap in basic knowledge facilitates know-ledge creation and transfer, whereas the assumptionthat similar specialized knowledge reduces thepotential for knowledge transfer is not confirmed.Thuc Anh et al. (2006) replicate Lane and Lubatkin’s(1998) design, but do not find a significant effect ofknowledge overlap on knowledge transfer. In asimilar way to the logic of Lane and Lubatkin (1998),Schoenmakers and Duysters (2006) argue that theinterrelation of absorptive capacity and knowledgetransfer follows an inverted u-shaped relationship.As long as knowledge overlap is small, firms undergodifficulties in transferring knowledge because theylack an adequate level of absorptive capacity. As theknowledge bases become more similar, the potentialto be exposed to new knowledge decreases. Schoen-makers and Duysters (2006) find support for theinverted u-shaped relationship, which basically indi-cates that the degree of knowledge complementaritybetween alliance partners determines how muchknowledge can be potentially transferred. Moreover,Nooteboom et al. (2007) provide empirical evidencethat the inverted u-shaped logic also holds true forthe knowledge outcome of joint knowledge creation.Contrary to the aforementioned studies, the studiesof Chen (2004) and Hau and Evangelista (2007)employ subjective survey measures to capturedirectly the way in which firms assess their absorp-tive capacity. Their results reaffirm the important roleof absorptive capacity as a facilitator of knowledgetransfer in alliances.

Apart from offering an explanation emerging fromthe particular knowledge endowments of the alliancepartners, Lane and Lubatkin (1998) identify further,more organizational dimensions of absorptive capac-ity. They examine how organizational similarity andan overlap in the firms’ dominant logics influenceknowledge management outcomes. Lane and Lubat-kin (1998) assume that firms with similar organiza-tional structures and dominant logics resemble eachother in the way that they manage knowledge. Theydo not find evidence that similar organizationalstructures facilitate the joint creation and transfer ofknowledge. However, partners with similar dominant

logics achieve significantly higher degrees of jointknowledge creation and transfer in their alliance. In afurther development of the original idea, Lee et al.(2008) assume a u-shaped relationship instead of alinear one between dominant logic overlap andknowledge management outcomes. Their datasupport the assumption. Therein lies a further, as yetunanswered, question which has practical impor-tance: How do firms cultivate the capacity to absorbnew external knowledge? Dyer et al. (2001), Irelandet al. (2002), Lee et al. (2008) and Nielsen (2007)give reason to believe that allying know-how sup-ports knowledge transfer. Firms capable of internal-izing the lessons learned from past alliances will bemore capable of managing knowledge (Simonin1997).

The existing quantitative empirical literature onabsorptive capacity turns out to broadly confirm theimportance of overlap in knowledge and dominantlogic in explaining the joint creation and transfer ofknowledge. However, scholars have only recentlybegun to measure absorptive capacity with originalmulti-item scales; results unanimously support thepositive absorptive capacity–knowledge transferrelation. However, absorptive capacity is by nomeans a carte blanche for knowledge transfer.Norman (2002) finds that firms which perceive theabsorptive capacity of their partners as high are moreprotective of their knowledge. Future research has totake this two-sided effect into account.

From a methodological point of view, existingmeasurement approaches are problematic. Research-ers frequently rely on patent data and measureknowledge overlap by cross-citation patterns. Thisapproach entails assigning the same values to bothalliance partners. If both alliance partners possessthe same mutual absorptive capacity, how do weexplain disproportional knowledge transfer amongpartners? Existing research seems to overlook addi-tional dimensions of absorptive capacity. Simonin(2004) finds that firms with a ‘double-loop’ learningculture are more capable of transferring knowledge.A potential starting point for future research is theconceptual model of Kandemir and Hult (2005)regarding the impact of learning culture on know-ledge management in alliances. Researchers needto think of absorptive capacity as a multifacetedconstruct.

Prominent controls: Firm size and cultural differ-ences. A wide range of other partner characteristicshave been included in prior research, often as control

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variables. Among these characteristics, firm size andcultural differences have been subjects of a livelydebate. Therefore, this review synthesizes the majorfindings on these prominent control variables.

Larger firms are more likely to engage in morecomprehensive interaction, boundary-spanningactivities (Muthusamy and White 2005), and in moresophisticated protection mechanisms (Norman 2002),as they possess more resources deployable to know-ledge management. Findings on the influence of firmsize on knowledge management outcomes and therespective theoretical explanations are highly diverse.Norman (2004) finds that relatively larger firms trans-fer less knowledge and simultaneously lose moreknowledge to their smaller partners in alliances. Incontrast, Mowery et al. (1996), Chen (2004) andMuthusamy and White (2005) do not find evidencethat firm size enables us to predict knowledge man-agement outcomes. How can the varying results beexplained? It is quite conceivable that the strategicimportance (cf. Lee et al. 2008; Tsang 2002) of thealliance relationship determines whether or not largerfirms put their superior absorptive capacity andresources into action. For instance, Norman (2002)and Simonin (2004) demonstrate that larger firms arebetter capable of protecting their proprietary know-ledge. Based on these findings, additional efforts willbe needed to analyse how firm size constrains thearsenal of practices, structures and actions applied tothe knowledge management process.

Whereas firm size is associated with absorptivecapacity and knowledge protection issues, culturaldifferences and misunderstandings are linked to thecommunication between partners. Increasingly, firmsare searching for new knowledge across national andcultural borders (Bhagat et al. 2002). Alliances canprovide access to new markets and critical localknowledge as demonstrated by Makino and Delios(1996). However, alliances between partners fromdifferent national and/or cultural backgrounds faceparticular knowledge management challenges. Com-munication between partners is complicated by dif-ferences in language, opinions, attitudes, beliefs andgeographic distance (e.g. Kale et al. 2000; Lane andLubatkin 1998; Mowery et al. 1996; Simonin 1999b;Thuc Anh et al. 2006). Simonin (1999b) reveals thatcultural distance among partners impedes knowledgetransfer, as it complicates understanding. Similarly,Mowery et al. (1996) find that cross-border alliancesare inferior to alliances with partners of the samenationality in transferring knowledge. Lane et al.(2001) find only partial support for the hampering

effect of cultural misunderstandings on knowledgetransfer.

In contrast to these findings, Kale et al. (2000) andNielsen (2007) do not find a negative effect ofcultural/national differences on knowledge manage-ment outcomes. Lane et al’.s (2001) and Simonin’s(1999b) studies offer some advice on how to inter-pret the contradictory findings. Both studies provideindications that alliance partners are able to bypassthe hampering influence of cultural/national differ-ences if their organizations are flexible and willingto invest into knowledge management. Thus, theimpeding effect of cultural/national differences doesnot necessarily constitute a given fact, but can beovercome with appropriate knowledge managementefforts. Another influencing factor might be the typeof knowledge. Lam’s (1997) study illustrates that thecultural embeddedness of knowledge might impedeknowledge transfer across national borders. Evange-lista and Hau (2009) verify this argumentation andfind that cultural distance has a stronger negativeeffect on the transfer of tacit than of explicitknowledge.

Future research could explore the concrete know-ledge management practices which are implementedto bridge cultural differences. Since prior researchhas relied on rough proxy measures of culturaldifferences, understanding is still limited. Priortheoretical work (e.g. Bhagat et al. 2002; Child andMarkoczy 1993) provides a possible starting pointfor a more fine-grained analysis of the influence ofdissimilar cultural contexts on knowledge manage-ment in alliances. For instance, Bhagat et al. (2002)develop a cluster to categorize alliance partnersalong two cultural dimensions (individualism vs col-lectivism and horizontal vs vertical cultures). Theyassume that the interrelation between knowledgetype and knowledge transfer effectiveness is moder-ated by the relative compatibility of the partners’clusters.

Partner interaction

Besides learning intent and absorptive capacity,Hamel (1991) describes openness as a strong deter-minant of knowledge management outcomes inalliances. By definition, openness refers to the inter-action of alliance partners. It represents the willing-ness and ability of partners to communicate freely,share knowledge, and risk unintended knowledgetransfers (Inkpen 2000; Lane et al. 2001; Steensmaand Lyles 2000). According to Inkpen (2000), rela-



tionship openness is determined by the level of com-petitive overlap and trust among alliance partners,which is influenced in particular by the level of con-flict in the relationship (Lyles and Salk 1996).

Competitive overlap. The competitive overlapbetween alliance partners creates both positive andnegative incentives regarding the willingness andability to transfer knowledge. High competitiveoverlap will generally induce firms to be more pro-tective about their knowledge, because unintendedknowledge transfer to the partner might endangertheir own competitive advantage (Khanna et al.1998), whereas the positive incentive builds uponthe idea of absorptive capacity. Knowledge bases ofcompetitors are more likely to resemble each other,and the potentially negative incentive might thus becounterbalanced by an increased ability to under-stand and absorb the partner’s knowledge (Inkpen2000; Kale et al. 2000).11 To test these assumptions,researchers employ control variables such as SICcodes to check market or industry affiliation (e.g.Chen 2004; Dhanaraj et al. 2004; Mowery et al.1996; Muthusamy and White 2005; Pérez-Nordtvedtet al. 2008). Mowery et al. (1996) find that firmsin so-called learning alliances experience lowerknowledge transfer if they are competitors ontheir end-product markets. In accordance with anabsorptive capacity based argumentation, Schoen-makers and Duysters (2006) find that firms from thesame industry are significantly better at transferringknowledge. Chen (2004) and Muthusamy andWhite (2005), however, do not find this effect ofindustry affiliation on joint knowledge creation andtransfer.

There are two possible explanations for the con-tradictory results. First, the degree of competitiveoverlap seems to be important. The competitiveoverlap will be different in alliances with acommon industry background compared with alli-ances with partners active in a common market.Park and Russo (1996) show that alliances betweendirect competitors are more likely to fail comparedwith alliances among partners which share a similarindustry background but do not compete directly(see also Faems et al. 2007). The latter partnershipsseem to benefit from an adequate level of absorp-tive capacity while simultaneously experiencing

less competitive pressure resulting in a lower levelof knowledge protection. This lower level of know-ledge protection in turn leads to more knowledgetransfer (Nielsen 2007).

Second, so far competitive overlap has been con-sidered in isolation, thereby neglecting a potentialinteraction with trust. Rindfleisch and Moorman(2001) illustrate that trust in alliances among directcompetitors is weaker than that between partnerswho do not compete on the same market. Futureresearch needs to incorporate competitive overlapand trust simultaneously.

Trust. Trust contributes to openness in alliancerelationships in three ways. First, trust directly influ-ences the willingness to risk vulnerability (Inkpen2000) and the confidence that the partner will not actopportunistically (cf. Gulati 1995; Lane et al. 2001).Second, trust mitigates the negative influence ofcompetitive overlap between partners. Third, trustincreases proximity between alliance partners, whichallows firms to interact more closely (e.g. Collins andHitt 2006). Proximity and close interaction are sup-portive of knowledge transfer, as they create acommon identity and communication protocolamong alliance partners (Dhanaraj et al. 2004). Ingeneral, scholars argue that trustworthy, respectful,socially embedded relationships between alliancepartners contribute to knowledge transfer (e.g.Berdrow and Lane 2003; Inkpen 2000; Lane et al.2001; Lee and Cavusgil 2006). Empirical evidenceon this positive relationship is unequivocal (Becerraet al. 2008; Kale et al. 2000; Lane et al. 2001; Leeand Cavusgil 2006; Muthusamy and White 2005;Norman 2004; Pérez-Nordtvedt et al. 2008). Rind-fleisch and Moorman (2001) provide additional evi-dence and report a positive effect of relational capitalon knowledge application.

Muthusamy and White (2005) go deeper into theissue of how different types of trust contribute toknowledge management outcomes. Trust in the abili-ties of the partner and in its integrity contributesto joint knowledge creation and transfer, whilebenevolence-based trust does not show a significanteffect.

While trust appears to be a good predictor ofgeneral knowledge management outcomes, Becerraet al. (2008), Dhanaraj et al. (2004) and Evangelistaand Hau (2009) can provide quantitative empiricalevidence for the argument (Collins and Hitt 2006;Inkpen and Dinur 1998; Kale et al. 2000) that trustis particularly important for the transfer of tacit

11This phenomenon is discussed with diverse notions such aslearning dilemma (Larsson et al. 1998), learning race(Khanna et al. 1998) or boundary paradox (Norman 2002).

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knowledge, as it creates the necessary proximitybetween partners.

However, the mutual relationship between trustand knowledge management outcomes is subject todynamic change (cf. Inkpen and Currall 2004).Cross-sectional analyses are insufficient to capturethis change. As trust between alliance partnersincreases, the transfer of tacit knowledge in particu-lar becomes easier; this might lead to a shift in powerrelations. As one partner ‘outlearns’ the other, thebargaining power will shift and result in less trust andmore control (Inkpen and Beamish 1997; Inkpen andCurrall 2004). In learning alliances, openness con-tinually changes. Future research should address thequestion of whether and how alliance partners inlearning alliances stabilize their relationships. Kaleet al. (2000) give reason to believe that firms canactively engage in such trust building activities.

Conflict. Conflict between alliance partners is adetrimental force. Conflict not only contributes toalliance failure (Steensma and Lyles 2000), it alsoreduces the level of trust between partners and even-tually impedes knowledge transfer (e.g. Tsang et al.2004). Tsang et al. (2004) verify empirically thatintensity of conflict reduces knowledge transfer. Howalliance partners manage conflict in the relationshipis therefore a central question. Kale et al. (2000)analyse joint conflict management processes and findevidence for a positive effect on both the level oftrust between alliance partners and the transfer ofknowledge. As such, joint conflict managementseems to function as a trust-building mechanism andas a knowledge transfer practice in its own right.Berdrow and Lane (2003), Chen (2004), and Collinsand Hitt (2006) reaffirm these findings: firms thatfrequently engage in partner interaction, which inturn is characterized by a high level of communica-tion quality and perceived fairness in the resolutionof conflicts, are found to transfer more knowledgewithin alliances.

Overall, the empirical results confirm the viewthat trust fosters knowledge management in alli-ances, because firms are less suspicious of theirpartners. Conflict management (Kale et al. 2000)and adjustment (Chen 2004) can be perceived asdeliberate trust-building mechanisms rather thanunintentional or emerging constructs. However,further research is clearly needed to understand thetrust-building interactions that are most effectivein supporting different knowledge managementoutcomes.

Prior ties. While the previously discussed studiesfocus on the actual alliance relationship, Inkpen(1996) directs attention to the pre-alliance relation-ship between the alliance partners. He argues thattop management involvement and prior ties contrib-ute to a trustworthy climate in subsequent relation-ships. Muthusamy and White (2005) report apositive and significant effect of prior ties on jointknowledge creation and transfer. To the contrary,Kale et al. (2000) and Norman (2002) do not findthat prior ties influence knowledge managementoutcomes in the alliance relationship. The study ofSchoenmakers and Duysters (2006) is more fine-grained and distinguishes between prior ties andprior equity-based ties. The authors find partial evi-dence that prior alliances with the same partnerpositively influence knowledge transfer. Surpris-ingly, the seemingly stronger prior equity-based tiesexert a significant negative effect on subsequentknowledge transfer. Schoenmakers and Duysters(2006) argue that the negative effect stems from anover-embeddedness of the partners’ knowledgebases.

Results regarding prior ties vary strongly. If weaccept that firms are not less protective if they knoweach other from prior relationships (Kale et al. 2000;Norman 2002; Sampson 2004) and are more capableof absorbing knowledge from a well-known partnerat the same time (Dhanaraj et al. 2004; Muthusamyand White 2005; Nielsen 2007; Schoenmakers andDuysters 2006), we can conclude that prior ties con-tribute to absorptive capacity, but are no guaranteefor a subsequent trustworthy relationship.

Active knowledge management

The popularity of resource- and knowledge-basedapproaches (e.g. Grant 1996a,b) has directed theresearch focus towards the ability of firms to create,transfer and apply knowledge, thereby providing analternative explanation for their existence (Teece1998). Nowadays, the management of knowledgeassets is at least as important as the management ofphysical assets (Lane and Lubatkin 1998). Twostreams of research classify the work on how firmspurposefully manage knowledge processes in alli-ances. The first stream focuses on the governancestructure that is decided upon during the formationphase of an alliance relationship (cf. Reid et al.2001). The second stream refers to the particularmechanisms that firms use to govern knowledge pro-cesses (Dyer and Singh 1998). While the governance



form of an alliance defines the organizational framein which knowledge-related processes occur (cf.Kogut 1988), knowledge management practicesdescribe the mechanisms that firms use intentionallyto influence knowledge management outcomes (cf.Gray 2001).

Alliance governance. The contractual organizationof alliances ranges from unilateral contractual agree-ments to equity-based alliances (e.g. Oxley 1997).Although a wide range of governance forms exist,the distinction between equity and non-equity-basedalliances prevails (e.g. Das and Teng 1998; Gulati1995; Inkpen 2000). The transaction cost literaturesuggests that equity-based alliances have the poten-tial to align interests among alliance partners, offer-ing opportunities for intended knowledge transferand simultaneous protection against unintendedknowledge leakage (Kale et al. 2000). Organiza-tional embeddedness of equity-based alliances isargued to create more knowledge transfer opportuni-ties and facilitate especially the transfer of tacitknowledge, and has become ‘conventional wisdom’by now (Kogut 1988). This ‘wisdom’ is confirmed byChen (2004) and Mowery et al. (1996), who find thatequity-based alliances are superior to contract-basedalliances in knowledge transfer. Furthermore, Chen(2004) has determined that equity-based alliancesare better in transferring tacit knowledge in compari-son with explicit knowledge. His study shows thattacit knowledge is most efficiently transferred inequity-based alliances (see also Shenkar and Li1999), while explicit knowledge is more efficientlytransferred in contract-based alliances. Oxley andWada (2009) reaffirm previous findings and increaseour understanding of how equity-based joint venturescontribute to knowledge transfer. According to thesefindings, equity-joint ventures positively influenceintended knowledge transfer while limiting theleakage of knowledge that is not related to the alli-ance relationship (see also Norman 2004).

In contrast to these results, neither Kale et al.(2000) nor Muthusamy and White (2005) find anyeffect of alliance governance form on knowledgecreation or transfer and the capacity to protectknowledge. Schoenmakers and Duysters (2006) gainmixed results. They find that a current equity-basedalliance has no effect on knowledge transfer, whileprior repeated equity ties even negatively influenceknowledge transfer. Schoenmakers and Duysters(2006) present a possible explanation for the hetero-geneous findings and argue that, although strong ties

are beneficial to knowledge transfer, alliance part-ners who have become ‘over-embedded’ because ofprior equity alliances reach a knowledge transferthreshold. Sampson’s (2004) discussion follows asimilar logic: firms respond to demanding know-ledge transfer goals by engaging in equity-based alli-ances. However, at a very high level of knowledgediversity, firms lack an adequate level of absorptivecapacity, which makes hierarchical governanceforms obsolete. A non-linear effect is quite conceiv-able: when the partners’ knowledge bases are verydifferent, knowledge transfer is difficult becauseof a lack of absorptive capacity. With very similarknowledge bases, there is hardly any potential for thetransfer of new knowledge. Moderate degrees ofknowledge similarity are thus needed for equity-based alliances to pay off. Chen (2004) provides jus-tification for this reasoning, as he shows thatknowledge transfer is jointly determined by thegovernance form, the type of processed knowledge,and the firm’s absorptive capacity. While existingresearch almost exclusively examines how the gov-ernance form of an alliance influences knowledgetransfer, Jiang and Li (2009) also examine the influ-ence of the governance form on knowledge creation.Besides reaffirming the positive link between theequity-based form and knowledge transfer, theirstudy shows that an equity-based governance struc-ture positively influences knowledge creation.

To sum up, the reviewed studies indicate that thechoice of alliance governance form is not a simpledecision that determines knowledge managementoutcomes, but a relatively complex decisionproblem. For example, Mowery et al. (1996) andOxley and Sampson (2004) have criticized the factthat a singular focus on the governance form ignorescomplementary mechanisms such as relationalcapital, trust or alliance scope. To gain furtherinsights, future research must incorporate these con-cepts. The question of how governance form, trustand alliance scope complement each other representsa promising research field. In this respect, the casestudy by Faems et al. (2007) provides the insight thatgovernance mechanisms (i.e. specific knowledge-related contract clauses) can be important to initiateknowledge transfer, even if an equity-based alliancestructure is present.

However, research from a knowledge managementperspective on governance choices remains a promis-ing area, as the question of the trade-off between thecosts of different governance forms and their benefitsfor knowledge management is seldom addressed (cf.

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Chen 2004; Inkpen 2000), and empirical studies arestill missing. If co-specialization alliances are moti-vate solely by complementary knowledge bases, thereis no need for a governance form particularly condu-cive to knowledge transfer. Thus, one could assumethat co-specialization alliances are more likely to becontract based. Future research on governance formsneeds to incorporate a multitude of influencing factorsin order to obtain a more comprehensive understand-ing of how governance forms influence knowledgemanagement outcomes.

Knowledge management practices. The decisionfor a certain governance form is a fundamental andhardly reversible choice that occurs at the beginningof the relationship. The term ‘knowledge manage-ment practices’ captures the organizational routines,control and co-ordination mechanisms, and systemsthat firms use to manage knowledge managementoutcomes (cf. Gray 2001). In general, prior researchshows that firms actively and purposefully engagingin knowledge management practices are more effec-tive at transferring knowledge.

Inkpen (1996, 2000) ascertains that personneltransfer, technology sharing, alliance–parent interac-tion, linkages between parents, and alliance strate-gies function as knowledge connections betweenalliance partners. Other knowledge managementpractices identified as beneficial to knowledge trans-fer are advisory systems, alliance liaison offices,learning networks, the delegation of expatriates,mutual visits/plant tours, training programmes andon-site meetings (Berdrow and Lane 2003; Collinsand Hitt 2006; Inkpen 2005; Inkpen and Pien 2006).

Lyles and Salk (1996) analyse a number of differ-ent knowledge management practices. They arguethat articulated goals create organizational commit-ment and a point of reference in decision processesfor organizational members. They further assumethat knowledge transfer is enhanced by activeinvolvement such as knowledge transfer agendas,technological and managerial knowledge contribu-tion, emotional support, labour division betweenpartners, and personnel training. Overall, the positiveeffect of articulated goals, delegation of expatriates,and active involvement12 on knowledge transfer has

been supported. Hau and Evangelista (2007), ThucAnh et al. (2006) and Tsang et al. (2004) expandedon Lyles and Salk’s (1996) study, and reaffirmedmany of their findings. Tsang (2002) finds, in moregeneral terms, that the involvement and overseeingeffort of a parent firm’s alliance managers supportsthe transfer of knowledge.

So far, comparatively little is known about howdifferent knowledge management practices areorchestrated to manage different types of know-ledge. Inkpen and Dinur (1998) suggest that differ-ent knowledge types are transferred more effectivelybetween alliance partners with different knowledgemanagement practices. For instance, social networksamong alliance partners are created to establish per-sonal ties that function as knowledge connections tofacilitate the transfer of tacit knowledge. The case ofGM’s and Toyota’s NUMMI project is a viableillustration (Inkpen 2005). Collins and Hitt (2006)similarly argue that frequent communication, on-sitemeetings and partner visits help to build the neces-sary relational capital to transfer tacit knowledge.Since knowledge tacitness also stems from its cul-tural embeddedness (Lam 1997), one could think ofexpatriates as translators of such knowledge. Bycontrast, explicit knowledge is transferred viatechnology sharing practices (Inkpen and Dinur1998).

Although case study research on knowledge man-agement practices provides evidence that more per-sonal and direct face-to-face interaction facilitatesthe transfer of tacit knowledge, the field lacks quan-titative empirical verification of this assumption.The study of Evangelista and Hau (2009) providessome preliminary insights. They find that the com-mitment of top management has a greater positiveinfluence on the transfer of explicit knowledge thanon the transfer of tacit knowledge. Another interest-ing research question arising in this context stemsfrom Simonin (1999b). He finds that alliance part-ners are able to reduce the tacitness and complexityassociated with knowledge by dedicating resourcesto the transfer process. With regard to futureresearch, studies should take notice of the invest-ments in different knowledge management practicesand analyse which practices are used to reduce thetacitness, complexity and specificity of knowledge.For instance, Revilla et al. (2005) argue that firmsblend different knowledge management practicesinto distinct knowledge management styles, depend-ing on the knowledge management objectivesaspired to.

12In a study on IJV failure, Steensma and Lyles (2000) partlyreaffirm the results of Lyles and Salk (1996) concerningactive involvement. They find that higher levels of manage-rial support by the parent firm positively influence learningon the IJV level.



Another emergent research stream is concernedwith the factors that influence the effectiveness ofknowledge management practices. Lane et al. (2001)and Tsang (2002) provide evidence that firms employdifferent knowledge management practices overtime, as both studies corroborate the fact that man-agement involvement is more important in the earlyphase of a joint venture and less important as thealliance matures. Janowicz-Panjaitan and Noorder-haven (2008) reveal that informal knowledge transferpractices have a constant positive effect, while moreformal knowledge management practices showa positive but diminishing effect on knowledgetransfer.

Another promising research area appears to behow the importance of management practiceschanges over time. Similarly, it seems to be of greatinterest to examine how the effectiveness of practiceswill differ over time owing to learning curve effects.In alliances with high degrees of managementinvolvement, valuable knowledge assets are particu-larly exposed at the outset of the relationship.However, the pace of the knowledge transfer is likelyto decrease when the easiest to absorb knowledge hasbeen transferred, and when less obvious knowledgeis sought for extraction.

Discussion, future directionsand conclusion

This paper reviewed empirical evidence on know-ledge management in alliances and proposed a sys-tematic framework which identified common areasand provided an in-depth analysis of empiricalevidence in this field of research. The landmarksidentified are knowledge characteristics, partnercharacteristics, partner interaction and active know-ledge management. Building on the framework andreview, open questions were derived in order toprovide impetus for future research. Table 1 summa-rizes the central issues and research gaps identified inthis review.

Regarding the knowledge management outcomesexamined, the focus has been largely on knowledgetransfer so far (cf. Jiang and Li 2009). Research hasneglected the outcomes of knowledge creation andapplication. There are several possible explanationsfor this shortcoming.

First, the transfer of knowledge might be more‘visible’ and thus easier to observe by comparisonwith the creation and especially with the application

of knowledge. While the manifestation of know-ledge creation in newly developed products, tech-nologies and production routines might requiremore time than the transfer of existing knowledge,the process of joint knowledge application is evenmore time-consuming and, thus, not immediatelymeasurable. For instance, in R&D alliancesbetween biotechnology and pharmaceutical firms,partners almost immediately start creating andtransferring existing basic knowledge. However, thejoint application of knowledge to commercial ends,i.e. the development and clinical testing of a proto-type product, normally follows at a much later pointin time (cf. Rothaermel and Deeds 2004). The soleinterest in knowledge transfer may also originatefrom its importance as a major driver of allianceformation (e.g. Chen 2004).

Furthermore, as the field lacks precise definitionsand delineation of key concepts, the theoretical con-cepts of different knowledge assets, processes andoutcomes remain fuzzy and overlapping. However,these concepts have to be clearly distinguishedtheoretically and empirically. For instance, thereis a subtle, but nevertheless important differencebetween measuring the degree to which an organiza-tion engages in knowledge creation activities and theextent to which knowledge assets such as new prod-ucts or technologies are accumulated as a result ofsuch activities. While the first captures a knowledgemanagement process, the latter assesses a knowledgemanagement outcome.

The literature has distinguished different know-ledge outcomes, but these distinctions are onlyrarely reflected in the operationalization of variables(e.g. Jiang and Li 2009; Lane et al. 2001) and dis-tinct outcomes tend instead to be merged, e.g. as onemeasure of organizational learning (e.g. Janowicz-Panjaitan and Noorderhaven 2008). However, thestudy of Jiang and Li (2009) gives reason to believethat creation and transfer are distinguishable know-ledge outcomes. Furthermore, the partially foundpositive relationship between knowledge transferand performance (e.g. Hamel 1991; Tsang et al.2004), on the one hand, and the existence of the‘NIH’ (not invented here) syndrome in alliance rela-tionships, on the other hand (cf. Inkpen 2005), indi-cate that firms are able to apply new externalknowledge to commercial ends, but that such appli-cation is not an inevitable consequence. The realworld of business provides many informativeexamples of alliances emphasizing distinct know-ledge management outcomes. For instance, creating

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new knowledge in the form of new mobile comput-ing devices and technologies is the major aim of thealliance between Intel and Nokia; the transfer ofexisting knowledge on epigenetics is the majordriving force behind the alliance of Cellzome andGlaxoSmithKline; and the joint commercializationand application of existing market knowledge is themotive of the alliance between Vodafone and ChinaMobile. Joint product and technology development

in R&D alliances (e.g. Norman 2004), exchange ofmarket knowledge in international alliances (e.g.Hau and Evangelista 2007) and joint knowledgeapplication and commercialization (e.g. Rindfleischand Moorman 2001) are certainly indicative of theexistence of distinct knowledge management pro-cesses. However, future research is needed todevelop meaningful measurements of knowledgecreation and application besides well-established

Table 1. Summary of research findings

Research unitof analysis

Findings Research gaps

Landscape ofthe field

Broad range of different industry and national settingsMore than three-quarters of studies are quantitative in

natureFocus on single informants from one partner of the

alliance relationship

Lack of research with a longitudinal design capable ofcapturing dynamic processes

Knowledgemanagementoutcomes

Quantitative and qualitative research focuses almostexclusively on knowledge transfer

Lack of research on other knowledge managementoutcomes, such as joint knowledge creation andapplication

Knowledgecharacteristics

Knowledge tacitness impedes knowledge transferAlliance experience and the devotion of resources can

reduce the impeding effect of knowledge complexity

Lack of testing the influence of knowledge dimensionsother than tacitness on knowledge managementoutcomes

A general lack of empirical research on howknowledge characteristics influence knowledgemanagement processes

Partnercharacteristics

Knowledge-related alliance motives differ significantlyamong each other

Learning intent positively influences knowledgetransfer

Absorptive capacity facilitates the transfer ofknowledge

Cultural differences must not necessarily impedeknowledge transfer

Competitive overlap between partners can both supportand constrain knowledge transfer

Lack of research on how different knowledge-relatedmotives affect how and to what degree alliancepartners collaborate

Lack of research on the factors that mediate therelationship between learning intent and knowledgetransfer

Lack of research on the determinants that constitutethe degree of absorptive capacity

Lack of research on how and why different culturaldimensions influence knowledge managementoutcomes

Lack of research on the interrelation betweencompetitive overlap and trust

Partner interaction Trust between alliance partners facilitates knowledgetransfer and is of particular importance for thetransfer of tacit knowledge

Conflict between partners is a detrimental force totrustworthy relationships and knowledge transfer

Conflict management and mutual adjustment canmitigate the negative effect of conflict on knowledgetransfer

Lack of research that considers trust and conflict asdynamic processes undergoing constant change

Active knowledgemanagement

Governance form choices are complex; they provide aninstitutional frame and cannot simply be reduced toa decision problem for or against a certainknowledge outcome

Structured, proactive, and goal-oriented knowledgemanagement practices can facilitate the transfer ofknowledge

The effectiveness of different knowledge managementpractices varies over time

Lack of research that incorporates relational capitalbetween partners, governance form, and alliancescope in an integrated analysis

Lack of research on which knowledge managementpractices are most useful in order to transferdifferent types of knowledge

Lack of research on which different knowledgemanagement practices are used during the alliancelife cycle



scales for knowledge transfer.13 Such measurementswill help to further our understanding of how firmsgenerate, store, retrieve and apply knowledge inalliances.

It is noticeable that the lack of precise definitionsand limitation of key constructs has blurred the dis-cussion. Since scholars have often avoided the cleardefinition and delineation of theoretical concepts,this review reaffirms prior critique (e.g. Grant andBaden-Fuller 2004; Mowery et al. 1996) and callsfor a more precise and distinct formulation anddevelopment of theoretical concepts and theirempirical operationalization.

Conceptual work on the impact of knowledgecharacteristics on knowledge management outcomeshas clearly outpaced its empirical verification.Although scholars have proposed multiple know-ledge taxonomies, there is only limited empiricalwork (Simonin 1999b). The distinction between tacitand explicit knowledge prevails, and empirical evi-dence is mostly supportive of the suggested relation-ships. In sum, it appears that knowledge tacitnesscontributes to transfer complications for two reasons:tacit knowledge is (1) non-verbalizable, context spe-cific and personally bounded, and (2) alliance part-ners are reluctant to transfer such knowledge freelyto the alliance partner, as it is perceived as particu-larly valuable.

The literature emphasizes the influence of absorp-tive capacity on knowledge management outcomesamong the partner characteristics. There is broadconsensus and empirical evidence that absorptivecapacity facilitates knowledge transfer. Further-more, firms committed to knowledge managementgoals and willing to deploy resources to the achieve-ment of such goals turn out to be more successful attransferring knowledge. However, other partnercharacteristics such as cultural distance have beenless explored, and the results remain vague andinconsistent. Future research is needed to analyse ingreater detail which cultural dimensions influencethe relationship and interaction between alliancepartners and how firms overcome cultural distancewith cultural sensitivity and management pro-grammes (Simonin 1999b).

By comparison with the above conclusions, sum-marizing the influence of partner interaction on

knowledge management outcomes is a morecomplex task. Alliance partner interaction covers adiverse set of dimensions. While the influence ofcompetitive overlap and prior ties on knowledgemanagement outcomes remains fairly inconclusive,the empirical evidence concerning trust and conflictis relatively unambiguous. It turns out that trustwor-thy and amicable partner relationships characterizedby a high quality of communication are supportiveof knowledge transfer. Joint conflict managementand mutual adjustment prove to facilitate knowledgetransfer in two ways: by reducing the impedingeffect of partner conflict, and by functioning as atransfer mechanism in and of themselves. However,future research is needed to elaborate on how alli-ance relationships develop over time, and how apotential shift in power relations (Inkpen andBeamish 1997) might influence the relationshipbetween partners.

Although the governance choice decision hasreceived a lot of theoretical attention, empiricalfindings concerning the influence of this choice onknowledge management outcomes are highlydiverse. The findings suggest that, instead of a simpleand direct relationship, more intricate mechanismsmight be at work. The governance form is thus betterunderstood as a context variable for the knowledgemanagement interaction between the partners. Futureresearch should incorporate the underlying motivesof the alliance partners, the alliance scope and theinteraction between partners.

Although quantitative empirical work on know-ledge management practices exists, our understand-ing is still limited. Articulated goals, the delegationof expatriates, and other practices of active involve-ment generally enhance the transfer of knowledge.However, more research is needed to examine whichknowledge management practices firms employ tomanage different types of knowledge. Similarly,researchers should ask how firms adapt their know-ledge management practices to the specific alliancepartner and specific interaction. The conjecture thatknowledge management practices that create inten-sive face-to-face interaction among partners are posi-tively related to the transfer of tacit knowledge hasbeen supported by various case studies (e.g. Inkpenand Dinur 1998). However, more quantitative empiri-cal testing is needed to disclose further which know-ledge management practices are effective in differentcontexts. For example, how do firms align knowledgemanagement practices to the quality of partner inter-action? If partner interaction is characterized by a

13The original scale of Lyles and Salk (1996) has beenrepeatedly used in other studies (see e.g. Jiang and Li 2008,2009; Lane et al. 2001; Thuc Anh et al. 2006; Tsang et al.2004).

18 M. Meier


high level of trust, communication quality and per-ceived fairness in the resolution of conflicts, firmsmight be more capable of incorporating practicessuch as the exchange of key personnel, and be willingto do so. In addition, further research should be con-ducted on the joint influence of various factors cap-tured by the framework (see Figure 1) on knowledgemanagement outcomes. Research that examineswhich knowledge management practices firmschoose, based on those explanatory factors (charac-teristics of knowledge, partners and their interaction),will be helpful to practitioners and scholars alike.

Empirical research on knowledge managementoutcomes has been conducted in various country,sector and industry settings. Studies providing com-prehensive cross-national and cross-industry testingare still lacking, however. But alliances are embed-ded in a particular context and environment whosecharacteristics affect knowledge management pro-cesses. For example, production or manufacturing-based alliances will show a considerably smallerneed to transfer knowledge (Beamish and Berdrow2003) by comparison with R&D alliances (e.g.Rothaermel and Deeds 2004; Sampson 2004).Furthermore, alliances between partners fromknowledge-intensive industries such as chemicals,computers, biotechnology, electronics, pharmaceuti-cals, semiconductors or telecommunications willfollow a different learning imperative by compari-son with alliances in less knowledge intensiveindustries. Also, alliances involving a Westernpartner and a partner from an emerging countryfollow a different logic from alliances amongWestern firms. Such alliances are often based on themutual agreement that the Western firm functions asteacher to firms catching up within the transitionprocess after social developments (cf. Lyles andSalk 1996; Si and Bruton 2005; Yan and Child2002). Meyer (2007, p. 35) suggests that futureresearch should ‘incorporate contextual variablesexplicitly in the study design, and thus [to] pursuemore cross-context comparative research, and repli-cation of empirical studies in different contexts’.

Another area which has received only limitedtheoretical and empirical attention is the question ofhow environmental factors affect knowledge man-agement in alliances. As a turbulent market environ-ment provides the impetus for allying (Grant andBaden-Fuller 2004; Osland and Yaprak 1995), it issurprising that market and technology uncertaintyhave not been included in the empirical researchagenda yet. In general, firms with a superior ability

to manage knowledge in alliances are assumed to bebetter able to adapt to rapidly increasing innovationpressures and changing market conditions (Richterand Vettel 1995). Wu and Cavusgil (2006) foundthat firms were more committed to an alliance rela-tionship under the conditions of high market uncer-tainty. Analysing how environmental factors such astechnology and market uncertainty affect the rela-tionship between partners, which governance formthey choose, and which knowledge managementpractices they apply is a promising stream of futureresearch.

In conclusion, we need a closer fit between theoryand methodology to advance the convergence andconsensus within the field (e.g. Lane et al. 2001;Mowery et al. 1996; Tsang 2002). The field suffersfrom measurement insufficiency and methodologicalrestrictions. Some of the future research questionsidentified within this review have not been addressedin prior studies because of a lack of longitudinalapproaches. How ‘learning races’ destabilize a rela-tionship (Inkpen and Beamish 1997), how differenttypes of trust develop in alliances, and how firmsreduce knowledge ambiguity: these are dynamic pro-cesses that cannot be captured by cross-sectionalmodels.

The established framework (Figure 1) and thesummary of the empirical evidence presented in thisreview provide a comprehensive overview of theresearch field. As such, this paper hopefully offersimpetus for future research and identifies somemajor avenues of convergence and divergence in thefield.

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Appendix 1. Exclusion criteriaNo. Criteria Reason for exclusion

1. Pre-1996 The award wining paper of Lyles and Salk (1996) is chosen as the point of reference for this review2. Publication type Exclude books, book chapters, conference proceedings, dissertation abstracts, editorials, and working

papers3. Perspective Exclude articles with industry, regional or sector analysis4. Organizational form Exclude articles with an intra-organizational focus, a focus on inter-organizational relationships other

than alliances, a focus on individuals, and a focus on networks. Exclude articles which comparedifferent organizational forms with each other

5. Non-commercial alliances Exclude articles on alliances of governmental organizations, of NGOs, or with the participation ofuniversities

6. Alliance life cycle Exclude articles on alliance formation, on the choice between alternative organizational forms, and onalliance termination. Articles on alliance formation will be included where interrelations tosubsequent knowledge management processes are investigated

Appendix 2. Inclusion criteriaNo. Criteria Reason for inclusion

1. Theoretical papers These articles provide the basis for summarizing and integrating empirical evidencea

2. Quantitative and qualitative empiricalstudies

Extant empirical evidence represents the particular interest of this review

3. All industries Provide a cross-industry overview4. All countries Provide a cross-country overview5. Knowledge management outcomes Examine how knowledge management processes are managed in strategic alliances and

how these influence performance

aNote that conceptual and theoretical papers are gathered in the first round of search and are excluded in the search with the citationsidentified in Stage (5).



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