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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 into

the causes and management of interfirm alliances. However, the development of

an effective knowledge-based theory of alliance formation has been inhibited by a

simplistic view of alliances as vehicles for organizational learning in which strategic

alliances have presumed to be motivated by firms desire to acquire knowledge from

one another. We argue that the primary advantage of alliances over both firms and

markets is in accessingrather than acquiringknowledge. Building upon the distinction

between 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 integrated

into 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 knowledge

requirements and where new products offer early-mover advantages. Compared

with alternative learning-based approaches to alliance formation, our proposed

knowledge-accessing theory of alliances offers the advantages of greater theoretical

rigour and consistency with general trends in alliance activity and corporate strategy.

INTRODUCTION

One of the most important trends in industrial organization of the past quarter

century has been the growth of collaboration between independent companies.

As large companies have pulled back their corporate borders through outsourcing

and divestment of non-core activities, they have increasingly cooperated with

other companies in order to engage in activities and access resources outside their

own boundaries.

Journal of Management Studies41:1 January 20040022-2380

Address for reprints: Robert M. Grant, McDonough School of Business, Georgetown University, Wash-


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These interfirm alliances involve cooperative relationships that are not fully

defined either by formal contracts or by ownership. Hence, in terms of the theory

of 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 collaboration

from more casual cooperative arrangements between firms, the term strategic

alliance has been used to refer to agreements characterized by the commitment

of two or more firms to reach a common goal entailing the pooling of their

resources 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 activities

covered include supplier-buyer partnerships, outsourcing agreements, technical

collaboration, joint research projects, shared new product development, shared

manufacturing arrangements, common distribution agreements, cross-selling

arrangements, 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. The

problem is not so much a lack of theory as an overabundance. Theories of alliance

formation 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 network

externalities (Rotemberg and Saloner, 1991), and transaction cost theory (Oxley,

1997; Ring and Van De Ven, 1992; Williamson, 1991). However, the emergence

of resource-based approaches to strategy especially those emphasizing the role

of 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 of

alliances is to facilitate organizational learning. This emphasis on learning the

acquisition of knowledge fails to recognize the central attribute of the strategic

alliance as an organizational mode that can reconcile the benefits of knowledgespecialization with those of flexible integration.

Th f hi i h f i lli h f

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


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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 motives

for strategic alliances within the knowledge-based economy and counter the wide-

spread presumption that the primary motive is knowledge acquisition through

organizational 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 likely

to 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 power

considerations, others may be formed to access resources other than knowledge,

and even within the knowledge-view of alliances some may be created with

the primary intention of acquiring rather than to accessing knowledge. However,

our contention is that knowledge accessing provides the predominant motive for

alliance formation, especially within the knowledge-based sectors where alliance

activity 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 interfirm

alliances. We then outline an analysis of knowledge-based production that permits

us to identify the circumstances in which alliances offer efficiency advantages over

both firms and markets.

KNOWLEDGE AND INTERFIRM ALLIANCES

In the same way that the knowledge-based view of the firm has grown out of

resource-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 of

the firm (Penrose, 1957), several studies (Eisenhardt and Schoonhoven, 1996;

Gulati, 1999; Rothaermel, 2001; Van De Ven and Walker, 1984) have viewed

alliances as a quest for resources. Moreover, certain types of resources appear to

particularly influential in alliance formation. The concentration of alliances in

R&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 of

knowledge management, so alliances have been viewed from a broader knowledge

perspective. Several studies of strategic alliances have identified the sharing ofknowledge (including technology, know-how and organizational capability) as

h i d i bj i (Cib 1 1 D d N b k 000 I k d

Strategic Alliances 63


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1988; Mody, 1993; Mowery et al., 1996, 1997; Simonin, 1997, 1999). Among these

studies, the great majority have adopted an organizational learning perspective:

assuming that the goal of strategic alliances is to acquire the knowledge of alliance

partners. The outcome may be a competition for learning where each alliance

member 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 in

building 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 dimensions

of knowledge management. First, those activities that increase an organizations

stock of knowledge what March (1991) refers to as exploration, and Spender

(1992) calls knowledge generation. Second, those activities that deploy existing

knowledge to create value what March (1991) refers to as exploitation, and

Spender (1992) calls knowledge application. In relation to strategic alliances, this

distinction between knowledge generation and knowledge application corresponds

to a key distinction in the ways in which knowledge is shared among alliance part-

ners. Knowledge generation points to alliances as vehicles of learningin which each

member firm uses the alliance to transfer and absorb the partners knowledge base.

Knowledge application points to a form of knowledge sharing in which each

member firm accessesits partners 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 sharing

within alliances. Hamel (1991, p. 84) notes, The crucial distinction between

acquiring such skills in the sense of gaining access to them . . . and actually inter-

nalising a partners skills has seldom been clearly drawn. Similarly, Inkpen

(1998, p. 72) observed that: In some alliances, partners aggressively seek to acquire

alliance knowledge while in others, the partners take a more passive approach

to knowledge acquisition. From a transaction cost perspective, Hennart (1988) has

also identified a similar competition/cooperation tension. The distinction between

acquisition and accessing is critically important of the evolution of the alliance

partners knowledge bases. Among Japanese-US joint ventures, Nakamura et al.

(1996) observed technological convergence in joint ventures where the partners

engaged 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 or

divergence between partners technology bases among 792 alliances appearedto disguise the fact that some alliances were converging (implying mutual

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While acknowledging that learning occurs in all alliances and that some

alliances are motivated primarily by the desire to acquire partners knowledge,[4]

our contention is that knowledge accessing rather than knowledge acquisition is

the primary motivation for knowledge-based alliances. This view of alliances is

consistent with the trends in corporate strategy over the past two decades. Theprimary trend since the early 1980s has been towards refocusing: the emergence

of truly focused companies . . . concentrated around a core set of knowledge or

service skills (Quinn, 1992, p. 373). This trend is not obviously consistent with the

firms using alliances to continually broaden their knowledge bases as they acquire

their 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 collaborate

with other firms in order to access additional capabilities. Thus, Daimler-Benzs

initial collaboration with Swatch in designing its Smart car was motivated, not

by Mercedes desire to acquire Swatchs precision engineering and microdesign

capabilities and Swatchs desire to acquire Daimlers automotive know-how, but

by both parties desire to create value through combining their separate knowl-

edge bases. Similarly, Luciano Pavarottis collaboration with the Spice Girls was

for the purposes of combining their different styles and capabilities in a music

album, not about Pavarotti learning how to be a girl band, or the Spice Girls

acquiring 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 takes

place 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 learning

in theoretical discussions of alliance activity and highlighting this as an area ripe

for 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 as

mechanisms for knowledge accessing. We begin with a few precepts concerning

the characteristics of knowledge and its role in economic activity from which we

derive implications for the circumstances under which interfirm alliances are more

efficient 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-

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tional economics that has found it easy to establish the transaction costs associated

with markets and the agency problems inherent within firms, but more difficult to

identify the circumstances under which alliances and other hybrid forms emerge.

Thus, Williamsons (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 more

powerfully the rationale for interfirm alliances.

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

production:

(1) Knowledge is the overwhelmingly important productive resource in terms

of market value and the primary source of Ricardian rents (Grant, 1996;

Machlup, 1980).[5]

(2) Different types of knowledge vary in their transferability: explicit knowledge

can be articulated and easily communicated between individuals and or-

ganizations; tacit knowledge (skills, know-how, and contextual knowledge) is

manifest only in its application transferring it from one individual to

another is costly and slow (Kogut and Zander, 1992; Nonaka, 1994).

(3) Knowledge is subject to economies of scale and scope. Since the costs of

replicating 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 single

product, economies of scale imply economies of scope. The extent of

economies of scale and scope vary considerably between different types of

knowledge. They are especially great for explicit knowledge, information in

particular, which is costly to produce, but cheap to reproduce (Shapiro

and Varian, 1999, p. 3). Tacit knowledge tends to be costly to replicate, but

these costs are lower than those incurred in its original creation (Winter,

1995).

(4) Knowledge is created by individual human beings and to be efficient in

knowledge creation and storage, individuals need to specialize (Simon, 1991,

p. 127).

(5) Producing a good or service typically requires the application of many types

of knowledge (Kogut and Zander, 1992).

If we accept these (relatively uncontroversial) initial premises, we are immediately

faced with some intriguing challenges for economic organization. In particular, the

fundamental dichotomy between knowledge creation (exploration) and knowledgeapplication (exploitation) becomes clear: knowledge creation requires specializa-

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knowledge (point 5). Given the limited transferability of knowledge (point 2), this

presents considerable difficulty for the institutions of production. The solution lies

in some process of knowledge integration that permits individuals to apply their

specialized knowledge to the production of goods and services, while preserving

the efficiencies of specialization in knowledge acquisition (Demsetz, 1991).If we abstract, for the time being, from knowledge generation and focus upon

knowledge application, what factors determine the efficiency with which knowl-

edge assets are transformed into goods and services? If production requires the

combination of many different types of specialized knowledge (point 5), each of

which is subject to economies of scale and scope (point 3), then efficiency in knowl-

edge application depends upon, first, the ability to integratemany different types of

knowledge and, second, the ability to utilizeknowledge to its full capacity. Let us

explore 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 to

combine 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 other

specialists. This cannot be done only by learning what others know, for that would

undermine gains from specialised learning (Demsetz, 1991, p. 172). Efficiency in

knowledge integration requires modes of coordination that can avoid the high

costs of extensive mutual learning.

The knowledge-based view of the firm views the critical advantage of firms over

markets as providing a superior context for supporting knowledge integration

mechanisms. 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), we

identify two primary mechanisms through which knowledge is integrated within

the firm: direction and routine.

Direction provides a low-cost method of communicating between specialists and

the large number of persons who are either non-specialists or specialists in other

fields (Demsetz, 1991, p. 172). Firms convert sophisticated specialized knowledgeinto directives, rules, and operating procedures that can be imposed through

h i b d l i hi [6]



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Organizational routinesare complex patterns of co-ordination that permit different

specialists to integrate their knowledge into the production of goods and services

while 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 cost

that afflict exchange transactions in knowledge. Information and other forms of

explicit knowledge suffer problems of non-exclusivity of use and the difficulty of

concluding contracts without first revealing the knowledge involved (Arrow,

1962).[7] Tacit knowledge is also problematical because, in order to mesh their areas

of know-how, transacting parties are likely to require a . . . common language or

. . . overlaps in cognitive frameworks . . . This requires time and effort: investments

which are to some extent . . . transaction specific . . . [hence] yield issues of depen-

dence and lock-in (Nooteboom, 1996, p. 331). Within the firm, these problems

are ameliorated by a social context characterized by a common identity of or-

ganizational members (Kogut and Zander, 1996) and the ability of the firm to

appropriate 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 and

less effective in integrating the individuals specialist knowledge than those within

a 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 de

Ven, 1992; Simonin, 1997; Teece, 1992). Yet, inevitably alliances are inferior to

firms in terms of their inability to integrate knowledge through higher-order or-

ganizing principles. They typically lack the authority-based relationships needed

for rules and directives and, although many alliances are very long lasting, most

lack the close, continuous association conducive to developing routines.[10]

Are there circumstances where alliances can be superior to firms in knowledge

integration? The key problem for knowledge integration within the firm is that,

whether integration is by direction or routine, the efficiency of integration tends

to decline as the firms knowledge domain expands. As with any complex system,

the large-scale knowledge integration required for producing goods and services

requires a hierarchy of integration (Simon, 1962). On the basis of intensity of

interdependence (Thompson, 1967), knowledge can be combined into specific

tasks, 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).

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tines: to the extent that they are embedded within organizational values and

norms, the common culture of an organization limits the variety of routines that

can be efficiently performed. Thus, as the range and diversity of knowledge

increases, so integration mechanisms need to be increasingly differentiated, result-

ing in rising marginal costs of knowledge integration within the firm. In thesecircumstances, 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, efficiency

of integration is maximized through separate firms specializing in different areas

of knowledge and linked by strategic alliances.

Illustration and evidence. Prior research points to numerous examples of companies

turning to strategic alliances when they extend their knowledge domains to areas

of know-how that need to be integrated with different rules and routines. The

rapid growth in strategic alliances within biotechnology reflects the advantages of

alliances between dedicated biotechnology companies and large, integrated phar-maceutical companies as compared to mergers and acquisitions. Any benefits of

full 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 (Almeida

et al., 1998), as the range of knowledge required for the design and manufacture

of semiconductors continues to expand, so alliances have proliferated, both

between semiconductor design companies and between designers and fabricators

(Macher, 2001). Even so, for alliances to achieve effective knowledge integration

within networks of alliances typically requires one firm to act as overall system

integrator (Lorenzoni and Baden-Fuller, 1994). This role requires some duplica-

tion of knowledge by the integrating firm. As Prencipe (1997) has shown, the role

of aero engine manufacturers as systems integrators for many hundreds of

suppliers of components and sub-systems requires that they maintain a residual

level of R&D in the component technologies that they are responsible for

integrating.Consider too Eastman Kodaks transition from chemical to digital imaging.

D i i fi 100 f d l K d k bli h d hi hl i d



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polymer, silver halide, technologies; consumer and professional markets; large-

scale, low-cost manufacturing; and worldwide distribution. However, the digital

imaging 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 moving

world of digital imaging (Grant and Neupert, 2003). In particular, when CEO

George Fisher requested the company to introduce a fully digital camera for the

consumer market, he was told that the companys standardized system of phases

and gates would require three years of development. Through an alliance with

Apple Computer, the camera the Apple Quicktake was developed and brought

to market within seven months (Pinto, 2000). Digital imagings need for differen-

tiated rules and routines to achieve fast response capability and compressed

product development and manufacturing cycles resulted in Kodaks widespread

use 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 to

their full capacity represents a key challenge to the firm. These economies of scale

and 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, it

is typically assumed that economies of scale and scope in knowledge are best

exploited within the firm. However, once we explore the problem faced by the firm

in reconciling its product and knowledge boundaries, we can identify circum-

stances where alliances can offer efficiencies in knowledge utilization beyond those

available through full internalization.

Achieving a match between a firms knowledge domain and its product domain

poses a significant problem for most firms because limits to firm growth within

individual markets typically prevent full exploitation of knowledge within a single

market. Hence, for a firm to fully exploit its knowledge resources usually means

diversifying into additional products. However, if different types of knowledge

have different product domains, the problem offitarises between the firms 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 knowledge

that 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. If

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1959). Efficient utilization of knowledge is achieved where the knowledge domain

of the firm matches exactly the knowledge requirements of the product domain

of the firm with no overlap and, thus, no underutilization of knowledge. The

problem is that different types of knowledge are applicable to different sets of

products. 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 firms knowledge domain and its product domain

may be shown as an input-output matrix of knowledge and products, where inputs

of specialized knowledge form the columns, and outputs of products form the

rows. Consider Figure 1 which shows the product and knowledge domains of the

ABC Corporation. Figure 1a begins with the products (rows AH) supplied by

ABC Corporation. Figure 1a shows the knowledge inputs (columns 118) required

to produce these products. Figure 1b then considers ABC Corporations knowl-

edge assets (columns 110) and identifies the different products (rows AN) that

each 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 18

A

B

CD

E

F

G

H

1 2 3 4 5 6 7 8 9 10

AB

C

D

E

F

G

H

J

K

L

M

N

I


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From the point of view of efficient knowledge utilization, the boundaries of

ABC Corporation are determined by a combination of knowledge types and prod-

ucts that permits ABCs knowledge resources to be utilized to the fullest extent

possible. But, if different products have different knowledge requirements, there

will always be a problem of under-utilized knowledge resources. Thus, in relationto product A, ABC Corporation could supply internally all the knowledge required

for its production. In the case of knowledge types 13 and 7 and 8, the ability to

apply these to products BH as well, means that these types of knowledge can be

utilized fully. But what about knowledge types 1117 that are also required to

produce product A? Because these knowledge types can be used in only two or

three of the other products that ABC supplies, the risk is that these knowledge

resources will be under-utilized if ABC owns them.

Similar issues arise when we look at the core knowledge resources that ABC

uses to supply products AH. Knowledge types 110 could also be used in one of

more additional products (IN). These products IN could be produced by ABC;

however, if this was so, ABC would also need access to the additional types of

knowledge required by these products that lie beyond the columns of our table.

Hence, if ABC expands to include products IN, this will only exacerbate the

problem of under-utilized knowledge resources.

Strategic alliances can help overcome the problems of under-utilized knowledge

arising from incongruent product and knowledge domains. If ABC can source

knowledge types 1116 from other companies, it can avoid the excess capacityproblems of providing these knowledge inputs internally. If ABC can offer knowl-

edge types 110 through strategic alliances with other firms that specialize in sup-

plying products IN, it can improve the utilization of knowledge types 110.[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 knowledge

from outside the firm. Quadrant 3 shows opportunities for knowledge exports: knowl-

edge within the firm, which has the potential for application to products supplied

by other firms. Quadrant 4 is an empty zone: there is no involvement by ABC.

The greater is the mismatch between the firms 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 be

more efficiently provided by other firms (quadrant 2 of Figure 2), and (b) more

fully utilize the firms own knowledge (quadrant 3 of Figure 2). The extent of the

mismatch 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 firms products (breadth of knowledge) and the extent of

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To summarize our central prediction:

Proposition 2: The greater the incongruity between the product domain of the

firm and its knowledge domain, the greater its propensity to form alliances with

other firms. The incongruity between product and knowledge domains is a

positive function of the breadth of knowledge required by the firms products

and the extent of economies of scope in that knowledge.

Illustration and evidence. Returning to our example of Eastman Kodaks adaptation

to the digital imaging, the key impact of the digitization of imaging was to upset

the close congruity between Kodaks product and knowledge domains. Digital

imaging was based upon a number of areas of electronic knowledge, most of

which including electronic sensing, image storage, file compression, internet-

protocol file transmission, and ink-jet and laser colour printing have wide

domains of application and are subject to substantial economies of scope. Since

internalizing these areas of knowledge would inevitably result in substantial

underutilization, Kodak relied primarily upon strategic alliances to access these

areas of knowledge. Alliance partners included:

Intel for data storage expertise first used in Picture CD and other image

storage devices and later applied to on-line image management systems.

Microsoft for the document and image management know-how used in

Kodaks work management software.

AT&T and Cisco Systems for expertise in internet-protocols and digital net-working for Kodaks online image transmission networks.

H l P k d f h l i kj h l i i d f K d k di i l


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

A

B

C

D

EF

G

H

I

J

K

L

M

N

3. Knowledge exports

1. Internalization 2. Knowledge imports

4. Empty zone

Figure 2. ABC Corporations product and knowledge domains combined


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Lockheed Martin for know-how in integrating massive information systems

in order to develop large scale document management systems required for

censuses, tax returns, and the like.

Motorola for the semiconductor manufacturing expertise required for pro-

ducing Kodaks range of CMOS image sensors.

At the same time, Kodak resorted to alliances in order to increase the utilization

of its internal knowledge resources. For example:

Kodaks knowledge of optics and lens design was shared through alliances

with the manufacturers of telescopes and for the high resolution cameras

required 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.

Kodaks data compression, image storage, and colour management tech-

nologies were deployed in alliances with Hewlett-Packard, Lexmark, Canon,

and Heidelberg.

Kodaks long-established proprietary knowledge of CCD and CMOS image

sensors (its first patents on single sensor colour imagers were granted in 1976)

was supplied to a number of manufacturers of cameras and other forms of

digital imaging equipment.

The incidence of strategic alliances both cross-sectionally and longitudinally is

consistent with Proposition 2. Evidence from both the MERIT-CATI database

(Hagendoorn, 2001; Hagendoorn et al., 2000) and SDCs Joint Venture and

Strategic Alliances Database (Schilling and Steensma, 2001) shows strategic

alliances to be concentrated in relatively few sectors notably computers and office

equipments, communications equipment, consumer electronics, medicines and

pharmaceuticals, and motor vehicles. These are sectors where knowledge require-

ments tend to be broad, and where much of the knowledge tends not to be product

specific, hence giving rise to economies of scope. By contrast, sectors with com-

paratively few alliances include wood and wood products, steel and non-ferrous

metals, 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 has

increased greatly in Europe and North America. This growth coincides with a

broadening of the range of knowledge requirements for most goods and services,and increasing importance of knowledge that is not specific to particular products

d di i l h l i d i



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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 new

knowledge takes time, its knowledge investments are risky. In these circumstances,

interfirm alliances offer two additional benefits to those outlined above. The first

is pure risk spreading. The second is the option value of small initial investments

in new areas of knowledge (Kogut, 1988; Sanchez, 1993). Investments in new

products and technologies can be segmented in time; the condition is that to invest

in any particular phase requires that the firm invests in the prior phases. In the

face of uncertainty, investments in early phases of a project derive the major part

of their value from the fact that they create the options to invest in the next and

subsequent phases (Dixit and Pindyck, 1994).[14]

To summarize:

Proposition 3: The greater the uncertainty as to the future knowledge require-

ments of a firms 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 alliances

are evident from the widespread propensity of firms to form alliances when faced

with technological uncertainty. In 1988, faced with uncertainty over the future of

microcomputer operating systems, Microsoft was investing not only in its propri-

etary MS-DOS and Windows systems but, through alliances, was developing

OS/2 for IBM, writing Mac applications for Apple Computer, and collaborating

in the launch of a PC version of UNIX (Beinhocker, 2000).

Similarly with Kodaks 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 the

evolutionary path has encouraged Kodak to use alliances to invest in alternative

technologies and designs in different stages of its digital infrastructure. At the

photofinishing stage of the value chain, Kodak has partnered with HewlettPackard (Phogenix joint venture), Noritsu, Gretag, and Photome (System 88) to

l i di i l i il b I i h i f di i l i



16/25

transmission, Kodaks initial Picture Network was soon supplemented by alliances

with AOL (Youve Got Pictures image delivery service), PictureVision (PhotoNet),

Fotowire.com (to link consumers to link with Kodaks retail photolabs), and

AT&T (to develop broadband and internet protocol applications) (Eastman

Kodak, 2001).

Early-Mover Advantage in New Products

In appropriating the returns to knowledge, we have noted that, in general, alliances

are superior to market contracts but inferior to internalization within the firm.[15]

However, where knowledge is advancing rapidly, appropriating its returns often

depends upon achieving early-mover advantage. Such advantage derives less from

the 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 new

knowledge combinations, strategic alliances can greatly increase the speed with

which a company can access the new combinations of knowledge needed to bring

new 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 establish

interfirm collaborative arrangements in order to access new knowledge.

Illustration and evidence. Finally, Kodak has been explicit in recognizing the value of

alliances in speeding its development and introduction of new digital imaging

products. Fishers digital imaging strategy for the consumer market was built upon

a flow of new digital and hybrid products that linked its well-established chemical

imaging knowledge to the electronic hardware and imaging software expertise pos-

sessed by existing IT companies. In establishing leadership in digital image storage

products, Kodak has increased speed to market through alliances with Intel and

Seagate, while relying upon a joint venture with Matsushita to provide rapid access

to the manufacturing capacity needed for speedy market penetration. In seeking

to gain early mover advantage in the market for sensors, Kodak has moved quickly

from prototype to mass manufacture using the manufacturing capabilities of

Motorola and Texas Instruments. Similarly with internet-based transmission of

digital images, Kodak alliances with AOL, Cisco, Yahoo! and AT&T enabled

Kodak to build a market presence faster than would be possible than by internal

development.

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-

i lli ld b ll Wi h l d fi f d



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DISCUSSION AND CONCLUSION

The ability of the knowledge-based view of the firm to provide insight into the

nature, formation and on-going management of interfirm alliances has been

limited by two factors. First, lack of clear specification of the role of knowledge

in alliance formation. Second, the widespread presumption that the purpose of

alliances is organizational learning. This study addresses both these issues. Start-

ing from basic principles concerning knowledge and its use in production, we have

presented a knowledge-based analysis of interfirm alliances that distinguishes

between 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 of

alliances. On the basis that knowledge accessing takes precedence over knowledge

acquisition in most strategic alliances, the paper establishes the circumstances inwhich strategic alliances are more efficient than internalization within a single firm

in integrating and utilizing knowledge. Although firms are generally superior to

both 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 knowledge

utilization. The advantages of alliances are especially apparent under conditions

of uncertainty and early mover advantages.

The goal of our study has been the development of better theory concerning

the role of alliances in the knowledge-based economy and the circumstances

conducive to their formation. In several places in the paper we have shown where

our propositions yield predictions that are consistent with observations of recent

alliance 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 for

example, of Eastman Kodak, Microsoft, biotechnology, and semiconductors

together with more general observations of trends in alliance formation over time

and across industry sectors, points to the plausibility of our propositions. Clearly

there is a need for systematic empirical testing directed towards discriminatingbetween alternative theories of alliances. To this end, the knowledge accessing

theory we have developed offers predictions that can be compared with those of

the 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 from

the other. The alliances-as-knowledge-accessing thesis predicts that alliance part-

ners will maintain, and possibly increase their knowledge specialization. The

approach taken by Mowery et al. (1996, 1997, 2001) in analysing convergence and

divergence of alliance partners knowledge bases has made progress in unravel-



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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 their

demise, 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-term

and, other things remaining equal, their stability will increase rather than decline

with time.

The approaches also have differing predictions about a firms potential for man-

aging multiple alliances. If alliances are about acquiring knowledge, then each

firms number of alliances will be limited by its absorptive capacity. Conversely,

knowledge accessing alliances would permit a firm to engage in extensive networks

of alliances.

In terms of the external factors conducive to alliances, the greater is the rate of

change of knowledge and uncertainty over future changes, then the greater the

risk spreading and option values of alliances under the knowledge accessing

approach. However, there is no reason to suppose that the value of learning

increases under such circumstances; indeed, uncertainty might discourage invest-

ments in learning.On the empirical front, our theory appears to have the potential to explain a

b f b d h i l di h d d i i b


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

interfirm 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 bases

remain differentiated converge over time

Stability of alliances If successful, alliances become As each partner absorbs

increasingly stable over time knowledge from the other,

alliances become less stable

Longevity of alliances Can be long term Life span limited to the time it

takes to acquire partners

knowledge

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 the

future links between substantially value of alliances

knowledge inputs and

product outputs


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alliances. There is a particular need for empirical tests capable of discriminating

more precisely between the proposed knowledge-accessing view of alliances and

the alternative organizational learning view.

Clearly there is a need for further theoretical development. The dichotomy

between knowledge accessing and knowledge acquisition in strategic alliancesis not clear-cut and requires further clarification. To integrate separate areas of

specialist knowledge, there needs to be some intersection of the separate knowl-

edge sets in the form of common knowledge (Grant, 1996, pp. 11516). In addi-

tion, this integration may require a distinct level of architectural knowledge

(Henderson and Clark, 1990). Prencipe and Brusconis research into aero engines

and other complex production systems identifies the critical importance of over-

laps between partners knowledge bases, particularly where the firm acts as overall

knowledge integrator (Brusoni and Prencipe, 2001; Brusoni et al., 2001; Prencipe,

1997). This need of knowledge duplication between alliance partners means that

a key issue for the efficiency of alliances relative to individual firms is the amount

of 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 and

services. It is clear that a knowledge-based approach to economic organization can

enrich and extend transaction cost explanations of optimal modes of organiza-

tion. The knowledge-based approach also links with other research streams in the

alliance 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 considerable

scope for refining and extending our bare bones analysis. If knowledge is the most

important resource of firms and if the primary task of production is to integrate

a broad range of knowledge, we need to understand better the organizational

processes to achieve this. Such extensions are important if we are to develop

normative recommendations for the selection, design and on-going management

of 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 Foundations CORE database (Link, 1996) and Securities DataCompanys 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



20/25

[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 companys 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 of

direction of an employee by a superior in the hierarchy. In practice, such direction is not simplya case of substituting the superiors 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] Lloyds of London, the international insurance market, has well-established routines, many of

which 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 thesocial 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 Clarks (1990) distinction between com-ponent knowledge and architectural knowledge. Busoni and Prencipe (2001) show that, once

firms collaborate with one another in loosely-coupled networks, then the firm that acts as thesystems 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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