A knowledge accessing theory of strategic alliance pdf1

A Knowledge Accessing Theory of
Strategic Alliances
Robert M. Grant and Charles Baden-Fuller
McDonough 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 accessing rather than acquiring knowledge. Building upon the distinction
between the knowledge generation (‘exploration’) and knowledge application
(‘exploitation’), we show that alliances contribute to the efficiency in the application
of 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 Studies 41:1 January 2004
0022-2380
© 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 (rgrant2208@aol.com).

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 of
the 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 knowledge
specialization with those of flexible integration.
The purpose of this paper is to present a theory of strategic alliances that focuses
upon 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 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 explanation
of 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 of
knowledge (including technology, know-how and organizational capability) as
their dominant objective (Ciborra, 1991; Dyer and Nobeoka, 2000; Inkpen and
Crossan, 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 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 organization’s
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 learning in which each
member firm uses the alliance to transfer and absorb the partner’s knowledge base.
Knowledge application points to a form of knowledge sharing in which each
member 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 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 partner’s 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 appeared
to disguise the fact that some alliances were converging (implying mutual
learning) while others were diverging (implying specialization and knowledge
accessing).[3]

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. The
primary 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-Benz’s
initial collaboration with Swatch in designing its ‘Smart car’ was motivated, not
by Mercedes’ desire to acquire Swatch’s precision engineering and microdesign
capabilities and Swatch’s desire to acquire Daimler’s automotive know-how, but
by both parties’ desire to create value through combining their separate knowl-
edge bases. Similarly, Luciano Pavarotti’s 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 imprecision
around 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-
cumstances in which interfirm alliances are superior governance structures to
either markets or single firms. This has been a particular problem for organiza-

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, Williamson’s (1991) observation that ‘hybrid’ forms are associated with inter-
mediate levels of asset specificity, adaptability and incentive intensity presents the
problem 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. To
the 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 knowledge
application (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), 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 integrate many different types of
knowledge and, second, the ability to utilize knowledge 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 high
living 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 knowledge
into directives, rules, and operating procedures that can be imposed through
authority-based relationships.[6]

Organizational routines are 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 transactions
across 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 firm’s 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).
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 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 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, 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 Kodak’s transition from chemical to digital imaging.
During its first 100 years of development, Kodak established a highly integrated
corporate 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 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 developed
for 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 company’s 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 imaging’s need for differen-
tiated rules and routines to achieve fast response capability and compressed
product development and manufacturing cycles resulted in Kodak’s 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, knowledge
expands 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 firm’s 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 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 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
knowledge is not product specific and is subject to economies of scope, excess
capacity in knowledge encourages the firm to expand its product scope (Penrose,

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 firm’s 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 A–H) supplied by
ABC Corporation. Figure 1a shows the knowledge inputs (columns 1–18) required
to produce these products. Figure 1b then considers ABC Corporation’s knowl-
edge assets (columns 1–10) and identifies the different products (rows A–N) 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
C
D
E
F
G
H
1 2 3 4 5 6 7 8 9 10
A
B
C
D
E
F
G
H
J
K
L
M
N
I
Figure 1. ABC Corporation’s product and knowledge domains. (a) ABC’s product outputs and their
knowledge requirements. (b) ABC’s knowledge resources and their potential product applications

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 ABC’s 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 relation
to product A, ABC Corporation could supply internally all the knowledge required
for its production. In the case of knowledge types 1–3 and 7 and 8, the ability to
apply these to products B–H as well, means that these types of knowledge can be
utilized fully. But what about knowledge types 11–17 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 A–H. Knowledge types 1–10 could also be used in one of
more 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 of
knowledge 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 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 11–16 from other companies, it can avoid the excess capacity
problems 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 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 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 be
more efficiently provided by other firms (quadrant 2 of Figure 2), and (b) more
fully utilize the firm’s 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 knowledge
required by the firm’s products (breadth of knowledge) and the extent of
economies of scope in that knowledge, which depends upon its lack of product
specificity.[13]

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 firm’s products
and the extent of economies of scope in that knowledge.
Illustration and evidence. Returning to our example of Eastman Kodak’s adaptation
to the digital imaging, the key impact of the digitization of imaging was to upset
the close congruity between Kodak’s 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
Kodak’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 digital
photofinishing printers.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
A
B
C
D
E
F
G
H
I
J
K
L
M
N
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 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 Kodak’s 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:
• Kodak’s 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.
• 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 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 SDC’s 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
and 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 not
static 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 firm’s product range, the greater its propensity to engage in inter-
firm collaborations as a means of accessing and integrating additional
knowledge.
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 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 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 Hewlett
Packard (Phogenix joint venture), Noritsu, Gretag, and Photome (System 88) to
supply competing digital minilab systems. In using the internet for digital image

transmission, Kodak’s initial Picture Network was soon supplemented by alliances
with 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) (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. Fisher’s 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-mover
advantages in a market, then the option value of investments in knowledge-
accessing alliances would be small. Without early mover advantage, a firm faced
with 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 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 in
which 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 discriminating
between 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-
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 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 firm’s potential for man-
aging multiple alliances. If alliances are about acquiring knowledge, then each
firm’s 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
number of observed phenomena including the trend towards increasing numbers
of alliances, and variations across industries and firms in the frequency of
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 of
partners’ 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 partner’s
knowledge
Numbers of alliances A firm can engage in multiple Limited absorptive capacity
alliances 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

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 alliances
is 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. 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 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 the
Cooperative Agreements and Technology Indicators (CATI) database (Hagedoorn et al., 2000),
the National Science Foundation’s CORE database (Link, 1996) and Securities Data
Company’s Joint Venture and Strategic Alliances Database.
[3] Other studies, notably Khanna et al. (1998) and Das and Teng (2000) point to the coexistence
of 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 acquire
Toyota’s operational management skills (Kale et al., 2000, p. 219).

[5] The evidence is fragmented yet overwhelming. For a knowledge-based company such as Cisco
Systems, 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, these
are greatly outweighed by ‘knowledge capital’ (Edvinsson and Malone, 1997). In terms of
employee remuneration, the fivefold difference in average earnings between unskilled workers
and 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 simply
a 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 his
computer 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 which
team-based cooperation gives rise to (Alchian and Demsetz, 1972).
[9] Lloyd’s 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 routines
to 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 assist
the 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 have
examined 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, once
firms 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 for
overall 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 only
superficial. 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 intellectual
property 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 taking
and exercising the option is much higher if the purpose of the alliance is learning as opposed
to knowledge accessing.
[15] A key exception to this generalization is where knowledge is protected by intellectual property
rights; in such cases, market contacts (i.e. licensing) can be effective in appropriating the returns
to knowledge (Teece, 1986).
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