A knowledge accessing theory of strategic alliance pdf1

A Knowledge Accessing Theory ofStrategic Alliances

Robert M. Grant and Charles Baden-FullerMcDonough School of Business, Georgetown University, Washington, DC; Cass Business School,

City University, London

The emerging knowledge-based view of the firm offers new insight intothe causes and management of interfirm alliances. However, the development ofan effective knowledge-based theory of alliance formation has been inhibited by asimplistic view of alliances as vehicles for organizational learning in which strategicalliances have presumed to be motivated by firms’ desire to acquire knowledge fromone another. We argue that the primary advantage of alliances over both firms andmarkets is in accessing rather than acquiring knowledge. Building upon the distinctionbetween the knowledge generation (‘exploration’) and knowledge application(‘exploitation’), we show that alliances contribute to the efficiency in the applicationof knowledge; first, by improving the efficiency with which knowledge is integratedinto the production of complex goods and services, and second, by increasing the efficiency with which knowledge is utilized. These static efficiency advantages of alliances are enhanced where there is uncertainty over future knowledgerequirements and where new products offer early-mover advantages. Compared with alternative learning-based approaches to alliance formation, our proposedknowledge-accessing theory of alliances offers the advantages of greater theoreticalrigour and consistency with general trends in alliance activity and corporate strategy.

INTRODUCTION

One of the most important trends in industrial organization of the past quartercentury has been the growth of collaboration between independent companies.As large companies have pulled back their corporate borders through outsourcingand divestment of ‘non-core’ activities, they have increasingly cooperated withother companies in order to engage in activities and access resources outside theirown boundaries.

Journal of Management Studies 41:1 January 20040022-2380

© Blackwell Publishing Ltd 2004. Published by Blackwell Publishing, 9600 Garsington Road, Oxford, OX4 2DQ,UK and 350 Main Street, Malden, MA 02148, USA.

Address for reprints: Robert M. Grant, McDonough School of Business, Georgetown University, Wash-ington DC 20057, USA ([email protected]).

These interfirm alliances involve cooperative relationships that are not fullydefined either by formal contracts or by ownership. Hence, in terms of the theoryof economic organization, they fall between the polar models of markets and hier-archies. As a result, cooperative relationships between firms have been viewed as‘intermediate’ or ‘hybrid’ organizational forms (Borys and Jemison, 1989; Powell,1987; Thorelli, 1986). To distinguish longer-term more substantial collaborationfrom more casual cooperative arrangements between firms, the term ‘strategicalliance’ has been used to refer to ‘agreements characterized by the commitmentof two or more firms to reach a common goal entailing the pooling of theirresources and activities’ (Teece, 1992, p. 19). Within such alliances, ‘the parties. . . maintain autonomy but are bilaterally dependent to a non-trivial degree’(Williamson, 1991, p. 271).

Strategic alliances embrace a diversity of collaborative forms. The activitiescovered include supplier-buyer partnerships, outsourcing agreements, technicalcollaboration, joint research projects, shared new product development, sharedmanufacturing arrangements, common distribution agreements, cross-sellingarrangements, and franchising. While the defining governance mode is the infor-mal ‘relational contract’, strategic alliances may involve contractual agreements(e.g. franchising and cross-licensing agreements) and ownership links (e.g. cross-equity holdings and joint ventures).[1]

The increasing importance of strategic alliances has resulted in growing inter-est in theorizing about their causes and consequences. However, the diversity ofthe phenomenon challenges our ability to develop all-encompassing theories. Theproblem is not so much a lack of theory as an overabundance. Theories of allianceformation include the creation of market power to generate monopoly rents (Katz,1986; Schwartz, 1987; Stocking and Watkins, 1946), resource-dependency theory(Barley et al., 1992; Guetzkow, 1966; Van de Ven, 1976), strategic options (Hurry,1993; Kogut, 1991; Sanchez, 1993), product complementarities and networkexternalities (Rotemberg and Saloner, 1991), and transaction cost theory (Oxley,1997; Ring and Van De Ven, 1992; Williamson, 1991). However, the emergenceof resource-based approaches to strategy – especially those emphasizing the roleof knowledge – has provided a broader basis upon which to build a theory of inter-firm cooperation.

At the same time, the usefulness of knowledge-based approaches to the analy-sis of strategic alliances has been limited by cursory analysis of the role of knowl-edge in alliance relationships and the widespread presumption that the goal ofalliances is to facilitate organizational learning. This emphasis on learning – theacquisition of knowledge – fails to recognize the central attribute of the strategicalliance as an organizational mode that can reconcile the benefits of knowledgespecialization with those of flexible integration.

The purpose of this paper is to present a theory of strategic alliances that focusesupon the role of strategic alliances, not in acquiring, but in accessing the knowledge

62 R. M. Grant and C. Baden-Fuller

© Blackwell Publishing Ltd 2004

resources of other firms. In doing so, we offer two main contributions to the lit-erature on interfirm alliances. First, we clarify alternative knowledge-based motivesfor strategic alliances within the knowledge-based economy and counter the wide-spread presumption that the primary motive is knowledge acquisition throughorganizational learning. Second, we develop the knowledge-accessing explanationof strategic alliances by outlining a theory of the efficiency advantages of stra-tegic alliances (relative to both firms and markets) in exploiting knowledge assets.Our theory does not purport to be a comprehensive theory of strategic alliances.We recognize that in as diverse a phenomenon as strategic alliances, there are likelyto be multiple motives and that a single theory cannot address all types of alliances.In particular, we recognize that some alliances may be motivated by market powerconsiderations, others may be formed to access resources other than knowledge,and – even within the knowledge-view of alliances – some may be created withthe primary intention of acquiring rather than to accessing knowledge. However,our contention is that knowledge accessing provides the predominant motive foralliance formation, especially within the knowledge-based sectors where allianceactivity has been especially prevalent (e.g. pharmaceuticals, semiconductors,aerospace, telecommunications, and consumer electronics).[2]

We begin by reviewing knowledge-based approaches to the analysis of interfirmalliances. We then outline an analysis of knowledge-based production that permitsus to identify the circumstances in which alliances offer efficiency advantages overboth firms and markets.

KNOWLEDGE AND INTERFIRM ALLIANCES

In the same way that the knowledge-based view of the firm has grown out ofresource-based theory of the nature and existence of firms (Grant, 1996), knowl-edge-based explanations of the formation of strategic alliance formation have their roots in resource-based approaches to alliances. Drawing upon resource-dependence theory (Pfeffer and Salancik, 1978) and the resource-based view ofthe firm (Penrose, 1957), several studies (Eisenhardt and Schoonhoven, 1996;Gulati, 1999; Rothaermel, 2001; Van De Ven and Walker, 1984) have viewedalliances as a quest for resources. Moreover, certain types of resources appear toparticularly influential in alliance formation. The concentration of alliances inR&D intensive sectors points to technology as playing a key role in alliance for-mation (Dickson and Weaver, 1997; Dodgson, 1992; Doz, 1988; Hagedoorn,1993). As technology management became absorbed within the wider field ofknowledge management, so alliances have been viewed from a broader knowledgeperspective. Several studies of strategic alliances have identified the sharing ofknowledge (including technology, know-how and organizational capability) as their dominant objective (Ciborra, 1991; Dyer and Nobeoka, 2000; Inkpen andCrossan, 1995; Kale et al., 2000; Khanna et al., 1998; Larsson et al., 1998; Lyles,

Strategic Alliances 63


1988; Mody, 1993; Mowery et al., 1996, 1997; Simonin, 1997, 1999). Among thesestudies, the great majority have adopted an organizational learning perspective:assuming that the goal of strategic alliances is to acquire the knowledge of alliancepartners. The outcome may be a ‘competition for learning’ where each alliancemember seeks to learn at a faster rate than its partner in order to achieve a posi-tive balance of trade in knowledge (Hamel, 1991). This can destabilize the rela-tionship (Inkpen and Beamish, 1997), unless the alliance partners are successful inbuilding ‘relational capital’ that can reconcile reciprocal learning with the protec-tion of core knowledge assets (Kale et al., 2000).

The knowledge-based literature identifies two conceptually distinct dimensionsof knowledge management. First, those activities that increase an organization’sstock of knowledge – what March (1991) refers to as ‘exploration’, and Spender(1992) calls ‘knowledge generation’. Second, those activities that deploy existingknowledge to create value – what March (1991) refers to as ‘exploitation’, andSpender (1992) calls ‘knowledge application’. In relation to strategic alliances, thisdistinction between knowledge generation and knowledge application correspondsto a key distinction in the ways in which knowledge is shared among alliance part-ners. Knowledge generation points to alliances as vehicles of learning in which eachmember firm uses the alliance to transfer and absorb the partner’s knowledge base.Knowledge application points to a form of knowledge sharing in which eachmember firm accesses its partner’s stock of knowledge in order to exploit comple-mentarities, but with the intention of maintaining its distinctive base of special-ized knowledge.

Several prior studies have distinguished these two types of knowledge sharingwithin alliances. Hamel (1991, p. 84) notes, ‘The crucial distinction betweenacquiring such skills in the sense of gaining access to them . . . and actually inter-nalising a partner’s skills has seldom been clearly drawn.’ Similarly, Inkpen (1998, p. 72) observed that: ‘In some alliances, partners aggressively seek to acquirealliance knowledge while in others, the partners take a more passive approach to knowledge acquisition.’ From a transaction cost perspective, Hennart (1988) hasalso identified a similar competition/cooperation tension. The distinction betweenacquisition and accessing is critically important of the evolution of the alliancepartners’ knowledge bases. Among Japanese-US joint ventures, Nakamura et al.(1996) observed technological convergence in joint ventures where the partnersengaged in mutual organizational learning, and the opposite tendency among joint ventures where ‘partner firms’ competitive capabilities have become dissimi-lar but complementary’ (p. 536). A similar dichotomy was detected by Mowery et al. (1996): the lack of significant overall trend towards either convergence ordivergence between partners’ technology bases among 792 alliances appeared to disguise the fact that some alliances were converging (implying mutual learning) while others were diverging (implying specialization and knowledgeaccessing).[3]



While acknowledging that learning occurs in all alliances and that somealliances are motivated primarily by the desire to acquire partners’ knowledge,[4]

our contention is that knowledge accessing rather than knowledge acquisition isthe primary motivation for knowledge-based alliances. This view of alliances isconsistent with the trends in corporate strategy over the past two decades. Theprimary trend since the early 1980s has been towards refocusing: the emergenceof ‘truly focused companies . . . concentrated around a core set of knowledge orservice skills’ (Quinn, 1992, p. 373). This trend is not obviously consistent with thefirms using alliances to continually broaden their knowledge bases as they acquiretheir partners’ knowledge. On the basis of both logic (to be developed more for-mally in subsequent sections) and casual empiricism, we suggest a general ten-dency for firms to concentrate upon a few core competences and to collaboratewith other firms in order to access additional capabilities. Thus, Daimler-Benz’sinitial collaboration with Swatch in designing its ‘Smart car’ was motivated, notby Mercedes’ desire to acquire Swatch’s precision engineering and microdesigncapabilities and Swatch’s desire to acquire Daimler’s automotive know-how, butby both parties’ desire to create value through combining their separate knowl-edge bases. Similarly, Luciano Pavarotti’s collaboration with the Spice Girls wasfor the purposes of combining their different styles and capabilities in a musicalbum, not about Pavarotti learning how to be a girl band, or the Spice Girlsacquiring operatic skills (Pavarotti, 1998).

A key feature of knowledge-based explanations of alliances is imprecisionaround the concepts of organizational learning, knowledge sharing, and knowl-edge transfer. Mowery et al. (1996) concluded that: ‘The “learning” that takesplace within alliances thus appears to be more complex than most of the litera-ture on this topic suggests, underlying the need for better definitions of learningin theoretical discussions of alliance activity and highlighting this as an area ripefor further study’ (p. 89). Our goal is to develop a more precise theory con-cerning the role of knowledge in alliances, emphasizing the role of alliances asmechanisms for knowledge accessing. We begin with a few precepts concerningthe characteristics of knowledge and its role in economic activity from which wederive implications for the circumstances under which interfirm alliances are moreefficient than both markets and firms in organizing production.

ALLIANCES AND STATIC EFFICIENCY IN KNOWLEDGE APPLICATION

Features of Knowledge-based Production

The key challenge facing any theory of strategic alliances is to specify the cir-cumstances in which interfirm alliances are superior governance structures toeither markets or single firms. This has been a particular problem for organiza-



tional economics that has found it easy to establish the transaction costs associatedwith markets and the agency problems inherent within firms, but more difficult toidentify the circumstances under which alliances and other ‘hybrid’ forms emerge.Thus, Williamson’s (1991) observation that ‘hybrid’ forms are associated with inter-mediate levels of asset specificity, adaptability and incentive intensity presents theproblem that quantitative assumptions are required in order to generate qualita-tive predictions. Knowledge-based theory has the potential to illuminate morepowerfully the rationale for interfirm alliances.

Let us begin with some basic assumptions concerning knowledge and its role inproduction:

(1) Knowledge is the overwhelmingly important productive resource in termsof market value and the primary source of Ricardian rents (Grant, 1996;Machlup, 1980).[5]

(2) Different types of knowledge vary in their transferability: explicit knowledgecan be articulated and easily communicated between individuals and or-ganizations; tacit knowledge (skills, know-how, and contextual knowledge) ismanifest only in its application – transferring it from one individual toanother is costly and slow (Kogut and Zander, 1992; Nonaka, 1994).

(3) Knowledge is subject to economies of scale and scope. Since the costs ofreplicating knowledge tend to be lower than the costs of the original dis-covery of creation of the knowledge, it is subject to economies of scale. Tothe extent that knowledge is not specific to the production of a singleproduct, economies of scale imply economies of scope. The extent ofeconomies of scale and scope vary considerably between different types ofknowledge. They are especially great for explicit knowledge, information inparticular, which is ‘costly to produce, but cheap to reproduce (Shapiro and Varian, 1999, p. 3). Tacit knowledge tends to be costly to replicate, butthese costs are lower than those incurred in its original creation (Winter,1995).

(4) Knowledge is created by individual human beings and to be efficient inknowledge creation and storage, individuals need to specialize (Simon, 1991,p. 127).

(5) Producing a good or service typically requires the application of many typesof knowledge (Kogut and Zander, 1992).

If we accept these (relatively uncontroversial) initial premises, we are immediatelyfaced with some intriguing challenges for economic organization. In particular, thefundamental dichotomy between knowledge creation (exploration) and knowledgeapplication (exploitation) becomes clear: knowledge creation requires specializa-tion (points 3 and 4 above), while knowledge application requires diversity of



knowledge (point 5). Given the limited transferability of knowledge (point 2), thispresents considerable difficulty for the institutions of production. The solution liesin some process of knowledge integration that permits individuals to apply theirspecialized knowledge to the production of goods and services, while preservingthe efficiencies of specialization in knowledge acquisition (Demsetz, 1991).

If we abstract, for the time being, from knowledge generation and focus uponknowledge application, what factors determine the efficiency with which knowl-edge assets are transformed into goods and services? If production requires thecombination of many different types of specialized knowledge (point 5), each ofwhich is subject to economies of scale and scope (point 3), then efficiency in knowl-edge application depends upon, first, the ability to integrate many different types ofknowledge and, second, the ability to utilize knowledge to its full capacity. Let usexplore knowledge integration and knowledge utilization in alternative institu-tional mechanisms: markets, firms, and alliances.

Alliances and the Efficiency of Knowledge Integration

Efficiency of integration relates to the costs of combining multiple types of knowl-edge into goods and services. These costs depend critically upon the mode of inte-gration used. As Demsetz observes, it is highly inefficient for individuals tocombine their knowledge by each learning what the other knows: ‘Although knowl-edge can be learned more effectively in specialized fashion, its use to achieve highliving standards requires that a specialist somehow uses the knowledge of otherspecialists. This cannot be done only by learning what others know, for that wouldundermine gains from specialised learning’ (Demsetz, 1991, p. 172). Efficiency inknowledge integration requires modes of coordination that can avoid the highcosts of extensive mutual learning.

The knowledge-based view of the firm views the critical advantage of firms overmarkets as providing a superior context for supporting knowledge integrationmechanisms. Firms are ‘social communities in which individual and social exper-tise is transformed into economically-useful products and services by the applica-tion of a set of higher-order organizing principles’ (Kogut and Zander, 1992,p. 384). Drawing upon two streams of literature, classical organizational theory(e.g. Hall, 1972) and evolutionary economics (e.g. Nelson and Winter, 1982), weidentify two primary mechanisms through which knowledge is integrated withinthe firm: direction and routine.

Direction provides a ‘low-cost method of communicating between specialists andthe large number of persons who are either non-specialists or specialists in otherfields (Demsetz, 1991, p. 172). Firms convert sophisticated specialized knowledgeinto directives, rules, and operating procedures that can be imposed throughauthority-based relationships.[6]



Organizational routines are complex patterns of co-ordination that permit differentspecialists to integrate their knowledge into the production of goods and serviceswhile preserving the efficiencies of knowledge specialization (Nelson and Winter,1982). Organizational routines require continuity of association and propinquity– conditions most readily provided by firms.

By contrast, market contracts suffer from the familiar sources of transaction costthat afflict exchange transactions in knowledge. Information and other forms ofexplicit knowledge suffer problems of non-exclusivity of use and the difficulty ofconcluding contracts without first revealing the knowledge involved (Arrow,1962).[7] Tacit knowledge is also problematical because, in order to mesh their areasof know-how, transacting parties are likely to require a ‘. . . common language or. . . overlaps in cognitive frameworks . . . This requires time and effort: investmentswhich are to some extent . . . transaction specific . . . [hence] yield issues of depen-dence and lock-in’ (Nooteboom, 1996, p. 331). Within the firm, these problemsare ameliorated by a social context characterized by a common identity of or-ganizational members (Kogut and Zander, 1996) and the ability of the firm toappropriate knowledge rents through secrecy (Liebeskind 1996).[8] In addition,markets are less able than firms to support either direction or routine. While rou-tines develop within markets, market-based routines are often less adaptable andless effective in integrating the individuals’ specialist knowledge than those withina single firm.[9]

Alliances can avoid many of the costs associated with knowledge transactionsacross markets. Alliances limit opportunism by converting single period into multi-period games and fostering investments in trust (Gulati, 1995; Ring and Van deVen, 1992; Simonin, 1997; Teece, 1992). Yet, inevitably alliances are inferior tofirms in terms of their inability to integrate knowledge through ‘higher-order or-ganizing principles’. They typically lack the authority-based relationships neededfor rules and directives and, although many alliances are very long lasting, mostlack the close, continuous association conducive to developing routines.[10]

Are there circumstances where alliances can be superior to firms in knowledgeintegration? The key problem for knowledge integration within the firm is that,whether integration is by direction or routine, the efficiency of integration tendsto decline as the firm’s knowledge domain expands. As with any complex system,the large-scale knowledge integration required for producing goods and servicesrequires a hierarchy of integration (Simon, 1962). On the basis of intensity ofinterdependence (Thompson, 1967), knowledge can be combined into specifictasks, which can then be integrated in activity-related and functional capabilities(Grant, 1996). With loose coupling of components and sub-systems, such struc-tures permit adaptability and evolutionary development (Sanchez and Mahoney,1996; Weick, 1976).

To be efficient as integrating devices, directives and rules must be standardized(March and Simon, 1957; Thompson, 1967). Similarly with organizational rou-



tines: to the extent that they are embedded within organizational values andnorms, the common culture of an organization limits the variety of routines thatcan be efficiently performed. Thus, as the range and diversity of knowledgeincreases, so integration mechanisms need to be increasingly differentiated, result-ing in rising marginal costs of knowledge integration within the firm. In these circumstances, efficiency of integration may be maximized through separate firms integrating knowledge at the component or subsystem level, with overall integration through an alliance between the firms.

To summarize:

Proposition 1: (a) In integrating knowledge, interfirm alliances are generally superior to market contracts, but are generally inferior to individual firms. (b)Increasing marginal costs of knowledge integration within the firm imply that,where products require a broad range of different knowledge types, efficiencyof integration is maximized through separate firms specializing in different areasof knowledge and linked by strategic alliances.

Illustration and evidence. Prior research points to numerous examples of companiesturning to strategic alliances when they extend their knowledge domains to areasof know-how that need to be integrated with different rules and routines. Therapid growth in strategic alliances within biotechnology reflects the advantages ofalliances between dedicated biotechnology companies and large, integrated phar-maceutical companies as compared to mergers and acquisitions. Any benefits offull merger in terms of closer integration are likely to be offset by the difficulty of reconciling the different routines and operating rules required in the pharma-ceutical business from those required for leading-edge biotechnology research(Barley et al., 1992; Powell, 1998). Similarly in semiconductors, although firms are more effective than alliances in sharing and developing knowledge (Almeidaet al., 1998), as the range of knowledge required for the design and manufactureof semiconductors continues to expand, so alliances have proliferated, bothbetween semiconductor design companies and between designers and fabricators(Macher, 2001). Even so, for alliances to achieve effective knowledge integrationwithin networks of alliances typically requires one firm to act as overall systemintegrator (Lorenzoni and Baden-Fuller, 1994). This role requires some duplica-tion of knowledge by the integrating firm. As Prencipe (1997) has shown, the roleof aero engine manufacturers as ‘systems integrators’ for many hundreds ofsuppliers of components and sub-systems requires that they maintain a residuallevel of R&D in the component technologies that they are responsible for integrating.

Consider too Eastman Kodak’s transition from chemical to digital imaging.During its first 100 years of development, Kodak established a highly integratedcorporate structure that was very effective in integrating knowledge of optical,



polymer, silver halide, technologies; consumer and professional markets; large-scale, low-cost manufacturing; and worldwide distribution. However, the digitalimaging revolution required Kodak to extend its knowledge base into ‘infoimag-ing’ – including new technologies ranging from electronic sensing to file com-pression. Many of the rules and organizational routines that Kodak had developedfor managing traditional photography were not well-suited to the faster movingworld of digital imaging (Grant and Neupert, 2003). In particular, when CEOGeorge Fisher requested the company to introduce a fully digital camera for theconsumer market, he was told that the company’s standardized system of phasesand gates would require three years of development. Through an alliance withApple Computer, the camera – the Apple Quicktake – was developed and broughtto market within seven months (Pinto, 2000). Digital imaging’s need for differen-tiated rules and routines to achieve fast response capability and compressedproduct development and manufacturing cycles resulted in Kodak’s widespreaduse of strategic alliances in its digital imaging business.

Alliances and the Efficiency of Knowledge Utilization

Given economies of scale and scope in knowledge, utilizing knowledge assets totheir full capacity represents a key challenge to the firm. These economies of scaleand scope are reinforced by the fact that, unlike most other resources, knowledgeexpands rather than depreciates when it is used.

Given that market contracts for knowledge are plagued by transaction costs, itis typically assumed that economies of scale and scope in knowledge are bestexploited within the firm. However, once we explore the problem faced by the firmin reconciling its product and knowledge boundaries, we can identify circum-stances where alliances can offer efficiencies in knowledge utilization beyond thoseavailable through full internalization.

Achieving a match between a firm’s knowledge domain and its product domainposes a significant problem for most firms because limits to firm growth withinindividual markets typically prevent full exploitation of knowledge within a singlemarket. Hence, for a firm to fully exploit its knowledge resources usually meansdiversifying into additional products. However, if different types of knowledgehave different product domains, the problem of fit arises between the firm’s knowl-edge domain and its product domain.

Conventionally, a firm is described by the products it supplies. The knowledge-based view implies that a firm may also be described by the range of knowledgethat it encompasses. The two are closely related, and it is the closeness of this rela-tionship that is a critical determinant of the efficiency of knowledge utilization. Ifknowledge is not product specific and is subject to economies of scope, excesscapacity in knowledge encourages the firm to expand its product scope (Penrose,



1959). Efficient utilization of knowledge is achieved where the knowledge domainof the firm matches exactly the knowledge requirements of the product domainof the firm with no overlap and, thus, no underutilization of knowledge. Theproblem is that different types of knowledge are applicable to different sets ofproducts. This presents difficult choices for the firm over which types of knowl-edge to possess and which products to produce.[11]

The relationship between a firm’s knowledge domain and its product domainmay be shown as an input-output matrix of knowledge and products, where inputsof specialized knowledge form the columns, and outputs of products form therows. Consider Figure 1 which shows the product and knowledge domains of theABC Corporation. Figure 1a begins with the products (rows A–H) supplied byABC Corporation. Figure 1a shows the knowledge inputs (columns 1–18) requiredto produce these products. Figure 1b then considers ABC Corporation’s knowl-edge assets (columns 1–10) and identifies the different products (rows A–N) thateach type of knowledge could be applied to.



(a)

(b)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18ABCDEFGH

1 2 3 4 5 6 7 8 9 10ABCDEFGH

JKLMN

I

Figure 1. ABC Corporation’s product and knowledge domains. (a) ABC’s product outputs and theirknowledge requirements. (b) ABC’s knowledge resources and their potential product applications

From the point of view of efficient knowledge utilization, the boundaries ofABC Corporation are determined by a combination of knowledge types and prod-ucts that permits ABC’s knowledge resources to be utilized to the fullest extentpossible. But, if different products have different knowledge requirements, therewill always be a problem of under-utilized knowledge resources. Thus, in relationto product A, ABC Corporation could supply internally all the knowledge requiredfor its production. In the case of knowledge types 1–3 and 7 and 8, the ability toapply these to products B–H as well, means that these types of knowledge can beutilized fully. But what about knowledge types 11–17 that are also required toproduce product A? Because these knowledge types can be used in only two orthree of the other products that ABC supplies, the risk is that these knowledgeresources will be under-utilized if ABC owns them.

Similar issues arise when we look at the core knowledge resources that ABCuses to supply products A–H. Knowledge types 1–10 could also be used in one ofmore additional products (I–N). These products I–N could be produced by ABC;however, if this was so, ABC would also need access to the additional types ofknowledge required by these products that lie beyond the columns of our table.Hence, if ABC expands to include products I–N, this will only exacerbate theproblem of under-utilized knowledge resources.

Strategic alliances can help overcome the problems of under-utilized knowledgearising from incongruent product and knowledge domains. If ABC can sourceknowledge types 11–16 from other companies, it can avoid the excess capacityproblems of providing these knowledge inputs internally. If ABC can offer knowl-edge types 1–10 through strategic alliances with other firms that specialize in sup-plying products I–N, it can improve the utilization of knowledge types 1–10.[12]

If we overlay Figures 1a and 1b, the basic patterns of knowledge-product rela-tionships become clear. Figure 2 identifies four quadrants. Quadrant 1 shows inter-

nalization: internal knowledge is used to produce goods and services within the firm.Quadrant 2 shows knowledge imports: products supplied by the firm using knowledgefrom outside the firm. Quadrant 3 shows opportunities for knowledge exports: knowl-edge within the firm, which has the potential for application to products suppliedby other firms. Quadrant 4 is an empty zone: there is no involvement by ABC.

The greater is the mismatch between the firm’s product domain and its knowl-edge domain, then the greater are the advantages offered by collaborative arrange-ments with other firms in order to (a) access and integrate knowledge that can bemore efficiently provided by other firms (quadrant 2 of Figure 2), and (b) morefully utilize the firm’s own knowledge (quadrant 3 of Figure 2). The extent of themismatch is indicated by the area of quadrants 2 and 3 relative to quadrant 1.This will be a positive function of the number of different types of knowledgerequired by the firm’s products (breadth of knowledge) and the extent ofeconomies of scope in that knowledge, which depends upon its lack of productspecificity.[13]



To summarize our central prediction:

Proposition 2: The greater the incongruity between the product domain of thefirm and its knowledge domain, the greater its propensity to form alliances withother firms. The incongruity between product and knowledge domains is a positive function of the breadth of knowledge required by the firm’s productsand the extent of economies of scope in that knowledge.

Illustration and evidence. Returning to our example of Eastman Kodak’s adaptationto the digital imaging, the key impact of the digitization of imaging was to upsetthe close congruity between Kodak’s product and knowledge domains. Digitalimaging was based upon a number of areas of electronic knowledge, most ofwhich – including electronic sensing, image storage, file compression, internet-protocol file transmission, and ink-jet and laser colour printing – have widedomains of application and are subject to substantial economies of scope. Sinceinternalizing these areas of knowledge would inevitably result in substantial underutilization, Kodak relied primarily upon strategic alliances to access theseareas of knowledge. Alliance partners included:

• Intel for data storage expertise first used in Picture CD and other imagestorage devices and later applied to on-line image management systems.

• Microsoft for the document and image management know-how used inKodak’s work management software.

• AT&T and Cisco Systems for expertise in internet-protocols and digital net-working for Kodak’s online image transmission networks.

• Hewlett-Packard for thermal inkjet technologies required for Kodak’s digitalphotofinishing printers.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18ABCDEFGHIJKLMN

3. Knowledge exports

1. Internalization 2. Knowledge imports

4. Empty zone

Figure 2. ABC Corporation’s product and knowledge domains combined

• Lockheed Martin for know-how in integrating massive information systemsin order to develop large scale document management systems required forcensuses, tax returns, and the like.

• Motorola for the semiconductor manufacturing expertise required for pro-ducing Kodak’s range of CMOS image sensors.

At the same time, Kodak resorted to alliances in order to increase the utilizationof its internal knowledge resources. For example:

• Kodak’s knowledge of optics and lens design was shared through allianceswith the manufacturers of telescopes and for the high resolution camerasrequired for satellite imaging systems.

• Kodak supplied digital scanning and colour management software technol-ogy to Heidelberger Druckmachinen AG for its range of digital colour print-ing presses.

• Kodak’s data compression, image storage, and colour management tech-nologies were deployed in alliances with Hewlett-Packard, Lexmark, Canon,and Heidelberg.

• Kodak’s long-established proprietary knowledge of CCD and CMOS imagesensors (its first patents on single sensor colour imagers were granted in 1976)was supplied to a number of manufacturers of cameras and other forms ofdigital imaging equipment.

The incidence of strategic alliances both cross-sectionally and longitudinally isconsistent with Proposition 2. Evidence from both the MERIT-CATI database(Hagendoorn, 2001; Hagendoorn et al., 2000) and SDC’s Joint Venture andStrategic Alliances Database (Schilling and Steensma, 2001) shows strategicalliances to be concentrated in relatively few sectors – notably computers and officeequipments, communications equipment, consumer electronics, medicines andpharmaceuticals, and motor vehicles. These are sectors where knowledge require-ments tend to be broad, and where much of the knowledge tends not to be productspecific, hence giving rise to economies of scope. By contrast, sectors with com-paratively few alliances include wood and wood products, steel and non-ferrousmetals, yarn and textiles, metal fasteners, and small tools. In these sectors knowl-edge requirements are narrower and the knowledge deployed tends to be com-paratively product specific.

Over time (certainly since the early 1980s), the number of alliances hasincreased greatly in Europe and North America. This growth coincides with abroadening of the range of knowledge requirements for most goods and services,and increasing importance of knowledge that is not specific to particular productsand sectors – e.g. digital technologies and management sciences.



ALLIANCES AND DYNAMIC EFFICIENCY IN KNOWLEDGE APPLICATION

Uncertainty in Knowledge-Product Linkages

In reality, input-output relationships between knowledge and products are notstatic but dynamic: knowledge is continually being created, refined, discarded,and reconfigured into new products. If the firm is uncertain as to the future knowl-edge requirements of its current products, and if acquiring and integrating newknowledge takes time, its knowledge investments are risky. In these circumstances,interfirm alliances offer two additional benefits to those outlined above. The firstis pure risk spreading. The second is the option value of small initial investmentsin new areas of knowledge (Kogut, 1988; Sanchez, 1993). Investments in newproducts and technologies can be segmented in time; the condition is that to investin any particular phase requires that the firm invests in the prior phases. In theface of uncertainty, investments in early phases of a project derive the major partof their value from the fact that they create the options to invest in the next andsubsequent phases (Dixit and Pindyck, 1994).[14]

To summarize:

Proposition 3: The greater the uncertainty as to the future knowledge require-ments of a firm’s product range, the greater its propensity to engage in inter-firm collaborations as a means of accessing and integrating additionalknowledge.

Illustration and evidence. The risk spreading and option creating benefits of alliancesare evident from the widespread propensity of firms to form alliances when facedwith technological uncertainty. In 1988, faced with uncertainty over the future ofmicrocomputer operating systems, Microsoft was investing not only in its propri-etary MS-DOS and Windows systems but, through alliances, was developingOS/2 for IBM, writing Mac applications for Apple Computer, and collaboratingin the launch of a PC version of UNIX (Beinhocker, 2000).

Similarly with Kodak’s development of digital imaging, when faced with technological uncertainty Kodak used alliances to take positions in rival tech-nologies. For example, in sensors, Kodak, long a leader in CCD sensors, allied with Motorola in order to develop a range of CMOS sensors. Similarly, in man-aging the transition from photochemical to digital imaging, uncertainty over theevolutionary path has encouraged Kodak to use alliances to invest in alternativetechnologies and designs in different stages of its ‘digital infrastructure’. At thephotofinishing stage of the value chain, Kodak has partnered with HewlettPackard (Phogenix joint venture), Noritsu, Gretag, and Photome (System 88) tosupply competing digital minilab systems. In using the internet for digital image



transmission, Kodak’s initial Picture Network was soon supplemented by allianceswith AOL (You’ve Got Pictures image delivery service), PictureVision (PhotoNet),Fotowire.com (to link consumers to link with Kodak’s retail photolabs), and AT&T (to develop broadband and internet protocol applications) (EastmanKodak, 2001).

Early-Mover Advantage in New Products

In appropriating the returns to knowledge, we have noted that, in general, alliancesare superior to market contracts but inferior to internalization within the firm.[15]

However, where knowledge is advancing rapidly, appropriating its returns oftendepends upon achieving early-mover advantage. Such advantage derives less fromthe generation of new knowledge, as from recombining knowledge into innova-tory products (Fleming, 2001; Galunic and Rodan, 1998). If early-mover advan-tage rests upon the ability to quickly identify, access, and integrate across newknowledge combinations, strategic alliances can greatly increase the speed withwhich a company can access the new combinations of knowledge needed to bringnew products to market. Hence:

Proposition 4: The greater the benefits of early-mover advantage in technologi-cally-dynamic environments, the greater the propensity for firms to establishinterfirm collaborative arrangements in order to access new knowledge.

Illustration and evidence. Finally, Kodak has been explicit in recognizing the value ofalliances in speeding its development and introduction of new digital imagingproducts. Fisher’s digital imaging strategy for the consumer market was built upona flow of new digital and hybrid products that linked its well-established chemicalimaging knowledge to the electronic hardware and imaging software expertise pos-sessed by existing IT companies. In establishing leadership in digital image storageproducts, Kodak has increased speed to market through alliances with Intel andSeagate, while relying upon a joint venture with Matsushita to provide rapid accessto the manufacturing capacity needed for speedy market penetration. In seekingto gain early mover advantage in the market for sensors, Kodak has moved quicklyfrom prototype to mass manufacture using the manufacturing capabilities ofMotorola and Texas Instruments. Similarly with internet-based transmission ofdigital images, Kodak alliances with AOL, Cisco, Yahoo! and AT&T enabledKodak to build a market presence faster than would be possible than by internaldevelopment.

Note that Propositions 3 and 4 are complementary; if there were no early-moveradvantages in a market, then the option value of investments in knowledge-accessing alliances would be small. Without early mover advantage, a firm facedwith technological uncertainties could simply wait to see how technology unfolds.



DISCUSSION AND CONCLUSION

The ability of the knowledge-based view of the firm to provide insight into thenature, formation and on-going management of interfirm alliances has beenlimited by two factors. First, lack of clear specification of the role of knowledgein alliance formation. Second, the widespread presumption that the purpose ofalliances is organizational learning. This study addresses both these issues. Start-ing from basic principles concerning knowledge and its use in production, we havepresented a knowledge-based analysis of interfirm alliances that distinguishesbetween the knowledge generation (exploration) and knowledge application (exploita-

tion) goals of alliances. This distinction corresponds to the difference between‘knowledge acquisition’ and ‘knowledge accessing’ observed in previous studies ofalliances. On the basis that knowledge accessing takes precedence over knowledgeacquisition in most strategic alliances, the paper establishes the circumstances inwhich strategic alliances are more efficient than internalization within a single firmin integrating and utilizing knowledge. Although firms are generally superior toboth alliances and markets in integrating knowledge to produce goods and ser-vices, alliances can overcome the limits of firms in encompassing highly differen-tiated knowledge integration processes, while offering efficiencies in knowledgeutilization. The advantages of alliances are especially apparent under conditionsof uncertainty and early mover advantages.

The goal of our study has been the development of better theory concerningthe role of alliances in the knowledge-based economy and the circumstances conducive to their formation. In several places in the paper we have shown whereour propositions yield predictions that are consistent with observations of recentalliance activity, but we offer little in the way of new or systematic empirical evi-dence. Nevertheless, we contend that the illustrative examples that we offer – forexample, of Eastman Kodak, Microsoft, biotechnology, and semiconductors –together with more general observations of trends in alliance formation over timeand across industry sectors, points to the plausibility of our propositions. Clearlythere is a need for systematic empirical testing directed towards discriminatingbetween alternative theories of alliances. To this end, the knowledge accessingtheory we have developed offers predictions that can be compared with those ofthe knowledge acquisition approach. Table I summarizes these.

The predictions of the two approaches contrast sharply with regard to the evo-lution of firm boundaries. The alliances-as-learning thesis predicts that the knowl-edge bases of alliance partners will tend to converge as each partner learns fromthe other. The alliances-as-knowledge-accessing thesis predicts that alliance part-ners will maintain, and possibly increase their knowledge specialization. Theapproach taken by Mowery et al. (1996, 1997, 2001) in analysing convergence anddivergence of alliance partners’ knowledge bases has made progress in unravel-ling these two processes.



In terms of alliance longevity and stability, the alliances-as-learning thesis pre-dicts that alliances will have finite lives, their very success in learning causing theirdemise, and will be unstable as a result of competition for learning. The alliances-as-knowledge-accessing thesis predicts that alliances will tend to be longer-termand, other things remaining equal, their stability will increase rather than declinewith time.

The approaches also have differing predictions about a firm’s potential for man-aging multiple alliances. If alliances are about acquiring knowledge, then eachfirm’s number of alliances will be limited by its absorptive capacity. Conversely,knowledge accessing alliances would permit a firm to engage in extensive networksof alliances.

In terms of the external factors conducive to alliances, the greater is the rate ofchange of knowledge and uncertainty over future changes, then the greater therisk spreading and option values of alliances under the knowledge accessingapproach. However, there is no reason to suppose that the value of learningincreases under such circumstances; indeed, uncertainty might discourage invest-ments in learning.

On the empirical front, our theory appears to have the potential to explain anumber of observed phenomena including the trend towards increasing numbersof alliances, and variations across industries and firms in the frequency of



Table I. Contrasting the predictions of knowledge-accessing and knowledge acquisition theories ofinterfirm alliances

Knowledge accessing approach Knowledge acquisition approach

Development of the alliance Alliances increase knowledge Alliances cause broadening ofpartners’ knowledge bases specialization each firms’ knowledge base

Partners’ knowledge bases Partners’ knowledge basesremain differentiated converge over time

Stability of alliances If successful, alliances become As each partner absorbsincreasingly stable over time knowledge from the other,

alliances become less stable

Longevity of alliances Can be long term Life span limited to the time ittakes to acquire partner’sknowledge

Numbers of alliances A firm can engage in multiple Limited absorptive capacityalliances simultaneously implies a limit to the number without sharply declining of alliances a firm can marginal benefit pursue simultaneously

Impact of uncertainty over Increases the value of alliances No substantial increase in thefuture links between substantially value of alliancesknowledge inputs and product outputs

alliances. There is a particular need for empirical tests capable of discriminatingmore precisely between the proposed knowledge-accessing view of alliances andthe alternative organizational learning view.

Clearly there is a need for further theoretical development. The dichotomybetween knowledge accessing and knowledge acquisition in strategic alliances is not clear-cut and requires further clarification. To integrate separate areas ofspecialist knowledge, there needs to be some intersection of the separate knowl-edge sets in the form of ‘common knowledge’ (Grant, 1996, pp. 115–16). In addi-tion, this integration may require a distinct level of ‘architectural knowledge’(Henderson and Clark, 1990). Prencipe and Brusconi’s research into aero enginesand other complex production systems identifies the critical importance of over-laps between partners’ knowledge bases, particularly where the firm acts as overallknowledge integrator (Brusoni and Prencipe, 2001; Brusoni et al., 2001; Prencipe,1997). This need of knowledge duplication between alliance partners means thata key issue for the efficiency of alliances relative to individual firms is the amountof common knowledge required for effective knowledge integration.

This role of common knowledge is one among a broader set of issues con-cerning knowledge integration in the development and production of goods andservices. It is clear that a knowledge-based approach to economic organization canenrich and extend transaction cost explanations of optimal modes of organiza-tion. The knowledge-based approach also links with other research streams in thealliance literature: the emphasis on co-ordination links with social network theory(e.g. Axelrod, 1984; Gulati, 1995; Hakansson and Johansson, 1992), and the knowledge-accessing role of alliances ties in with resource-dependence theory (e.g.Barley et al., 1992; Van de Ven, 1976). At the same time there is considerablescope for refining and extending our bare bones analysis. If knowledge is the mostimportant resource of firms and if the primary task of production is to integratea broad range of knowledge, we need to understand better the organizationalprocesses to achieve this. Such extensions are important if we are to develop normative recommendations for the selection, design and on-going managementof strategic alliances from our positive analysis.

NOTES

[1] Oxley (1997) presents a sequence of alliance types arranged from the least hierarchical (uni-lateral contractual agreements) to the most hierarchical (equity-based alliances).

[2] Evidence on the growth of alliances over time and their sectoral distribution is available in theCooperative Agreements and Technology Indicators (CATI) database (Hagedoorn et al., 2000),the National Science Foundation’s CORE database (Link, 1996) and Securities DataCompany’s Joint Venture and Strategic Alliances Database.

[3] Other studies, notably Khanna et al. (1998) and Das and Teng (2000) point to the coexistenceof both cooperative (i.e. mutual knowledge accessing) and competitive (i.e. learning races)among alliance partners.

[4] General Motor’s NUMMI venture with Toyota has been viewed as GM’s attempt to acquireToyota’s operational management skills (Kale et al., 2000, p. 219).



[5] The evidence is fragmented yet overwhelming. For a knowledge-based company such as CiscoSystems, tangible assets account for less than 4 per cent of the company’s market value.Skandia, the Swedish insurance company, estimates that despite its huge financial assets, theseare greatly outweighed by ‘knowledge capital’ (Edvinsson and Malone, 1997). In terms ofemployee remuneration, the fivefold difference in average earnings between unskilled workersand higher degree holders within the USA is indicative that knowledge is the primary deter-minant of income from employment.

[6] Connor and Prahalad (1996) use the term ‘knowledge substitution’ to describe the process ofdirection of an employee by a superior in the hierarchy. In practice, such direction is not simplya case of substituting the superior’s knowledge for that of the subordinate. The essence of direc-tion is that it permits different individuals’ specialist knowledge to be integrated. Thus, the com-puter technician can give directions to the CEO as to what do in when a virus infects hiscomputer hard disk.

[7] Patent and copyright law does establish property rights in some forms of knowledge, but typi-cally only a small fraction of the knowledge used by firms is protected.

[8] A further advantage of firms is in overcoming the problems of metering and shirking whichteam-based cooperation gives rise to (Alchian and Demsetz, 1972).

[9] Lloyd’s of London, the international insurance market, has well-established routines, many ofwhich can be traced back to Lloyds origins as a seventeenth-century coffee house. Lloyds’ prob-lems of the late 1980s and early 1990s can be attributed, in part, to failure of these routinesto adapt and to the inefficiency of these routines in integrating information and know-how.

[10] The presence of common production processes and dominant designs within a sector can assistthe establishment of organizational routines within between cooperating firms. More gener-ally, the presence of an ‘institutional field within which members are located’ will assist the‘social processes that constitute collaboration’ (Phillips et al., 2000).

[11] The problem is well known in the technology management field; both Boeing and Xerox haveexamined the problem of defining optimal technology portfolios in the face of complementary,overlapping development projects (Dickinson et al., 2001; Loutfy and Belkhir, 2001).

[12] This analysis does not take account of Henderson and Clark’s (1990) distinction between com-ponent knowledge and architectural knowledge. Busoni and Prencipe (2001) show that, oncefirms collaborate with one another in loosely-coupled networks, then the firm that acts as the‘systems integrator’ within the network must maintain the architectural knowledge needed foroverall product integration and design.

[13] This framework showing internal and external exploitation of knowledge bears some similar-ities to that developed by Teece (1986) which identifies the conditions under which new tech-nologies are best exploited internally or through contract. However, any similarities are onlysuperficial. The Teece framework explores conditions for appropriating the returns to innova-tions where the central issue is the extent to which the innovation is protected by intellectualproperty rights.

[14] It is worth noting that the option value of strategic alliances is greater within our knowledge-accessing model than in the alternative knowledge acquisition model, because the cost of takingand exercising the option is much higher if the purpose of the alliance is learning as opposedto knowledge accessing.

[15] A key exception to this generalization is where knowledge is protected by intellectual propertyrights; in such cases, market contacts (i.e. licensing) can be effective in appropriating the returnsto knowledge (Teece, 1986).

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