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Absorptive Capacity: A
New Perspective on
Learning and Innovation
Wesley M. Cohen
Carnegie Mellon University
Daniel A. Levinthal
University of Pennsylvania
In this paper, we argue that the ability of a firm to recog-
nize the value of new, external information, assimilate it,
and apply it to commercial ends is critical to its innovative
capabilities. We label this capability a firm's absorptive
capacity and suggest that it is largely a function of the
firm's level of prior related knowledge. The discussion fo-
cuses first on the cognitive basis for an individual's ab-
sorptive capacity including, in particular, prior related
knowledge and diversity of background. We then charac-
terize the factors that influence absorptive capacity at the
organizational level, how an organization's absorptive ca-
pacity differs from that of its individual members, and the
role of diversity of expertise within an organization. We
argue that the development of absorptive capacity, and, in
turn, innovative performance are history- or path-depen-
dent and argue how lack of investment in an area of ex-
pertise early on may foreclose the future development of
a technical capability in that area. We formulate a model
of firm investment in research and development (R&D), in
which R&D contributes to a firm's absorptive capacity,
and test predictions relating a firm's investment in R&D to
the knowledge underlying technical change within an in-
dustry. Discussion focuses on the implications of absorp-
tive capacity for the analysis of other related innovative
activities, including basic research, the adoption and dif-
fusion of innovations, and decisions to participate in co-
operative R&D ventures.'
INTRODUCTION
Outside sources of knowledge are often critical to the inno-
vation process, whatever the organizational level at which the
innovating unit is defined. While the example of Japan illus-
trates the point saliently at the national level (e.g., Westney
and Sakakibara, 1986; Mansfield, 1988; Rosenberg and
Steinmueller, 1988), it is also true of entire industries, as
pointed out by Brock (1975) in the case of computers and by
Peck (1962) in the case of aluminum. At the organizational
level, March and Simon (1958: 188) suggested most innova-
tions result from borrowing rather than invention. This obser-
vation is supported by extensive research on the sources of
innovation (e.g., Mueller, 1962; Hamberg, 1963; Myers and
Marquis, 1969; Johnston and Gibbons, 1975; von Hippel,
1988). Finally, the importance to innovative performance of
information originating from other internal units in the firm,
outside the formal innovating unit (i.e., the R&D lab), such as
marketing and manufacturing, is well understood (e.g., Mans-
field, 1968).
The ability to exploit external knowledge is thus a critical
component of innovative capabilities. We argue that the
ability to evaluate and utilize outside knowledge is largely a
function of the level of prior related knowledge. At the most
elemental level, this prior knowledge includes basic skills or
even a shared language but may also include knowledge of
the most recent scientific or technological developments in a
given field. Thus, prior related knowledge confers an ability to
recognize the value of new information, assimilate it, and
apply it to commercial ends. These abilities collectively con-
stitute what we call a firm's "absorptive capacity."
128/Administrative Science Quarterly, 35 (1990): 128-152
? 1990 by Cornell University.
0001 -8392/90/3501-01 28/$1 .00.
We appreciate the comments of Kathleen
Carley, Robyn Dawes, Mark Fichman, Tom
Finholt, Sara Kiesler, Richard Nelson,
Linda Pike, and three anonymous ref-
erees. The representations and conclu-
sions presented herein are those of the
authors. They have not been adopted in
whole or in part by the Federal Trade
Commission, its Bureau of Economics, or
any other entity within the commission.
The FTC's Disclosure Avoidance Officer
has certified that the data included in this
paper do not identify individual company
line-of-business data.

Absorptive Capacity
At the level of the firm-the innovating unit that is the focus
here-absorptive capacity is generated in a variety of ways.
Research shows that firms that conduct their own R&D are
better able to use externally available information (e.g., Tilton,
1971; Allen, 1977; Mowery, 1983). This implies that absorp-
tive capacity may be created as a byproduct of a firm's R&D
investment. Other work suggests that absorptive capacity
may also be developed as a byproduct of a firm's manufac-
turing operations. Abernathy (1978) and Rosenberg (1982)
have noted that through direct involvement in manufacturing,
a firm is better able to recognize and exploit new information
relevant to a particular product market. Production experience
provides the firm with the background necessary both to rec-
ognize the value of and implement methods to reorganize or
automate particular manufacturing processes. Firms also in-
vest in absorptive capacity directly, as when they send per-
sonnel for advanced technical training. The concept of
absorptive capacity can best be developed through an exami-
nation of the cognitive structures that underlie learning.
Cognitive Structures
The premise of the notion of absorptive capacity is that the
organization needs prior related knowledge to assimilate and
use new knowledge. Studies in the area of cognitive and be-
havioral sciences at the individual evel both justify and enrich
this observation. Research on memory development suggests
that accumulated prior knowledge increases both the ability
to put new knowledge into memory, what we would refer to
as the acquisition of knowledge, and the ability to recall and
use it. With respect to the acquisition of knowledge, Bower
and Hilgard (1981: 424) suggested that memory development
is self-reinforcing in that the more objects, patterns and con-
cepts that are stored in memory, the more readily is new in-
formation about these constructs acquired and the more
facile is the individual in using them in new settings.
Some psychologists suggest that prior knowledge enhances
learning because memory-or the storage of knowledge-is
developed by associative learning in which events are re-
corded into memory by establishing linkages with pre-existing
concepts. Thus, Bower and Hilgard (1981) suggested that the
breadth of categories into which prior knowledge is orga-
nized, the differentiation of those categories, and the linkages
across them permit individuals to make sense of and, in turn,
acquire new knowledge. In the context of learning a lan-
guage, Lindsay and Norman (1 977: 517) suggested the
problem in learning words is not a result of lack of exposure
to them but that "to understand complex phrases, much
more is needed than exposure to the words: a large body of
knowledge must first be accumulated. After all, a word is
simply a label for a set of structures within the memory
system, so the structures must exist before the word can be
considered learned." Lindsay and Norman further suggested
that knowledge may be nominally acquired but not well uti-
lized subsequently because the individual did not already pos-
sess the appropriate contextual knowledge necessary to
make the new knowledge fully intelligible.
The notion that prior knowledge facilitates the learning of new
related knowledge can be extended to include the case in
129/ASQ, March 1990

which the knowledge in question may itself be a set of
learning skills. There may be a transfer of learning skills
across bodies of knowledge that are organized and expressed
in similar ways. As a consequence, experience or perfor-
mance on one learning task may influence and improve per-
formance on some subsequent learning task (Ellis, 1965). This
progressive improvement in the performance of learning
tasks is a form of knowledge transfer that has been referred
to as "learning to learn" (Ellis, 1965; Estes, 1970). Estes
(1970: 16), however, suggested that the term "learning to
learn" is a misnomer in that prior experience with a learning
task does not necessarily improve performance because an
individual knows how to learn (i.e., form new associations)
better, but that an individual may simply have accumulated
more prior knowledge so that he or she needs to learn less to
attain a given level of performance. Notwithstanding what it
is about prior learning experience that may affect subsequent
performance, both explanations of the relationship between
early learning and subsequent performance emphasize the
importance of prior knowledge for learning.
The effect of prior learning experience on subsequent
learning tasks can be observed in a variety of tasks. For in-
stance, Ellis (1965: 4) suggested that "students who have
thoroughly mastered the principles of algebra find it easier to
grasp advanced work in mathematics such as calculus." Fur-
ther illustration is provided by Anderson, Farrell, and Sauers
(1984), who compared students learning LISP as a first pro-
gramming language with students learning LISP after having
learned Pascal. The Pascal students learned LISP much more
effectively, in part because they better appreciated the se-
mantics of various programming concepts.
The literature also suggests that problem-solving skills de-
velop similarly. In this case, problem-solving methods and
heuristics typically constitute the prior knowledge that
permits individuals to acquire related problem-solving capabil-
ities. In their work on the development of computer program-
ming skills, Pirolli and Anderson (1985) found that almost all
students developed new programs by analogy-to-example
programs and that their success was determined by how well
they understood why these examples worked.
We argue that problem solving and learning capabilities are so
similar that there is little reason to differentiate their modes of
development, although exactly what is learned may differ:
learning capabilities involve the development of the capacity
to assimilate existing knowledge, while problem-solving skills
represent a capacity to create new knowledge. Supporting
the point that there is little difference between the two,
Bradshaw, Langley, and Simon (1983) and Simon (1985) sug-
gested that the sort of necessary preconditions for successful
learning that we have identified do not differ from the pre-
conditions required for problem solving and, in turn, for the
creative process. Moreover, they argued that the processes
themselves do not differ much. The prior possession of rele-
vant knowledge and skill is what gives rise to creativity, per-
mitting the sorts of associations and linkages that may have
never been considered before. Likewise, Ellis (1965: 35) sug-
gested that Harlow's (1959) findings on the development of
learning sets provide a possible explanation for the behavioral
130/ASQ, March 1990

Absorptive Capacity
phenomenon of "insight" that typically refers to the rapid so-
lution of a problem. Thus, the psychology literature suggests
that creative capacity and what we call absorptive capacity
are quite similar.
To develop an effective absorptive capacity, whether it be for
general knowledge or problem-solving or learning skills, it is
insufficient merely to expose an individual briefly to the rele-
vant prior knowledge. Intensity of effort is critical. With regard
to storing knowledge in memory, Lindsay and Norman (1977:
355) noted that the more deeply the material is processed-
the more effort used, the more processing makes use of as-
sociations between the items to be learned and knowledge
already in the memory-the better will be the later retrieval
of the item. Similarly, learning-set theory (Harlow, 1949, 1959)
implies that important aspects of learning how to solve
problems are built up over many practice trials on related
problems. Indeed, Harlow (1959) suggested that if practice
with a particular type of problem is discontinued before it is
reliably learned, then little transfer will occur to the next
series of problems. Therefore, he concluded that considerable
time and effort should be spent on early problems before
moving on to more complex problems.
Two related ideas are implicit in the notion that the ability to
assimilate information is a function of the richness of the pre-
existing knowledge structure: learning is cumulative, and
learning performance is greatest when the object of learning
is related to what is already known. As a result, learning is
more difficult in novel domains, and, more generally, an indi-
vidual's expertise-what he or she knows well-will change
only incrementally. The above discussion also suggests that
diversity of knowledge plays an important role. In a setting in
which there is uncertainty about the knowledge domains
from which potentially useful information may emerge, a di-
verse background provides a more robust basis for learning
because it increases the prospect that incoming information
will relate to what is already known. In addition to strength-
ening assimilative powers, knowledge diversity also facilitates
the innovative process by enabling the individual to make
novel associations and linkages.
From Individual to Organizational Absorptive Capacity
An organization's absorptive capacity will depend on the ab-
sorptive capacities of its individual members. To this extent,
the development of an organization's absorptive capacity will
build on prior investment in the development of its constit-
uent, individual absorptive capacities, and, like individuals' ab-
sorptive capacities, organizational absorptive capacity will
tend to develop cumulatively. A firm's absorptive capacity is
not, however, simply the sum of the absorptive capacities of
its employees, and it is therefore useful to consider what
aspects of absorptive capacity are distinctly organizational.
Absorptive capacity refers not only to the acquisition or as-
similation of information by an organization but also to the or-
ganization's ability to exploit it. Therefore, an organization's
absorptive capacity does not simply depend on the organiza-
tion's direct interface with the external environment. It also
depends on transfers of knowledge across and within sub-
units that may be quite removed from the original point of
131 /ASQ, March 1990

entry. Thus, to understand the sources of a firm's absorptive
capacity, we focus on the structure of communication be-
tween the external environment and the organization, as well
as among the subunits of the organization, and also on the
character and distribution of expertise within the organization.
Communication systems may rely on specialized actors to
transfer information from the environment or may involve less
structured patterns. The problem of designing communication
structures cannot be disentangled from the distribution of ex-
pertise in the organization. The firm's absorptive capacity de-
pends on the individuals who stand at the interface of either
the firm and the external environment or at the interface be-
tween subunits within the firm. That interface function may
be diffused across individuals or be quite centralized. When
the expertise of most individuals within the organization
differs considerably from that of external actors who can pro-
vide useful information, some members of the group are
likely to assume relatively centralized "gatekeeping" or
"boundary-spanning" roles (Allen, 1977; Tushman, 1977). For
technical information that is difficult for internal staff to as-
similate, a gatekeeper both monitors the environment and
translates the technical information into a form understand-
able to the research group. In contrast, if external information
is closely related to ongoing activity, then external information
is readily assimilated and gatekeepers or boundary-spanners
are not so necessary for translating information. Even in this
setting, however, gatekeepers may emerge to the extent that
such role specialization relieves others from having to monitor
the environment.
A difficulty may emerge under conditions of rapid and uncer-
tain technical change, however, when this interface function
is centralized. When information flows are somewhat random
and it is not clear where in the firm or subunit a piece of out-
side knowledge is best applied, a centralized gatekeeper may
not provide an effective link to the environment. Under such
circumstances, it is best for the organization to expose a fairly
broad range of prospective "receptors" to the environment.
Such an organization would exhibit the organic structure of
Burns and Stalker (1961: 6), which is more adaptable "when
problems and requirements for action arise which cannot be
broken down and distributed among specialist roles within a
clearly defined hierarchy."
Even when a gatekeeper is important, his or her individual
absorptive capacity does not constitute the absorptive ca-
pacity of his or her unit within the firm. The ease or difficulty
of the internal communication process and, in turn, the level
of organizational absorptive capacity are not only a function of
the gatekeeper's capabilities but also of the expertise of
those individuals to whom the gatekeeper is transmitting the
information. Therefore, relying on a small set of technological
gatekeepers may not be sufficient; the group as a whole
must have some level of relevant background knowledge, and
when knowledge structures are highly differentiated, the req-
uisite level of background may be rather high.
The background knowledge required by the group as a whole
for effective communication with the gatekeeper highlights
the more general point that shared knowledge and expertise
132/ASQ, March 1990

Absorptive Capacity
is essential for communication. At the most basic level, the
relevant knowledge that permits effective communication
both within and across subunits consists of shared language
and symbols (Dearborn and Simon, 1958; Katz and Kahn,
1966; Allen and Cohen, 1969; Tushman, 1978; Zenger and
Lawrence, 1989). With regard to the absorptive capacity of
the firm as a whole, there may, however, be a trade-off in the
efficiency of internal communication against the ability of the
subunit to assimilate and exploit information originating from
other subunits or the environment. This can be seen as a
trade-off between inward-looking versus outward-looking ab-
sorptive capacities. While both of these components are nec-
essary for effective organizational learning, excessive
dominance by one or the other will be dysfunctional. If all
actors in the organization share the same specialized lan-
guage, they will be effective in communicating with one an-
other, but they may not be able to tap into diverse external
knowledge sources. In the limit, an internal language, coding
scheme, or, more generally, any particular body of expertise
could become sufficiently overlapping and specialized that it
impedes the incorporation of outside knowledge and results
in the pathology of the not-invented-here (NIH) syndrome.
This may explain Katz and Allen's (1982) findings that the
level of external communication and communication with
other project groups declines with project-group tenure.
This trade-off between outward- and inward-looking compo-
nents of absorptive capacity focuses our attention on how the
relationship between knowledge sharing and knowledge di-
versity across individuals affects the development of organi-
zational absorptive capacity. While some overlap of
knowledge across individuals is necessary for internal com-
munication, there are benefits to diversity of knowledge
structures across individuals that parallel the benefits to di-
versity of knowledge within individuals. As Simon (1985)
pointed out, diverse knowledge structures coexisting in the
same mind elicit the sort of learning and problem solving that
yields innovation. Assuming a sufficient level of knowledge
overlap to ensure effective communication, interactions
across individuals who each possess diverse and different
knowledge structures will augment the organization's ca-
pacity for making novel linkages and associations-inno-
vating-beyond what any one individual can achieve.
Utterback (1971), summarizing research on task performance
and innovation, noted.that diversity in the work setting "stim-
ulates the generation of new ideas." Thus, as with Nelson
and Winter's (1982) view of organizational capabilities, an or-
ganization's absorptive capacity is not resident in any single
individual but depends on the links across a mosaic of indi-
vidual capabilities.
Beyond diverse knowledge structures, the sort of knowledge
that individuals hould possess to enhance organizational ab-
sorptive capacity is also important. Critical knowledge does
not simply include substantive, technical knowledge; it also
includes awareness of where useful complementary exper-
tise resides within and outside the organization. This sort of
knowledge can be knowledge of who knows what, who can
help with what problem, or who can exploit new information.
With regard to external relationships, von Hippel (1988) has
133/ASQ, March 1990

shown the importance for innovation of close relationships
with both buyers and suppliers. To the extent that an organi-
zation develops a broad and active network of internal and
external relationships, individuals' awareness of others' capa-
bilities and knowledge will be strengthened. As a result, indi-
vidual absorptive capacities are leveraged all the more, and
the organization's absorptive capacity is strengthened.
The observation that the ideal knowledge structure for an or-
ganizational subunit should reflect only partially overlapping
knowledge complemented by nonoverlapping diverse knowl-
edge suggests an organizational trade-off between diversity
and commonality of knowledge across individuals. While
common knowledge improves communication, commonality
should not be carried so far that diversity across individuals is
substantially diminished. Likewise, division of labor pro-
moting gains from specialization should not be pushed so far
that communication is undermined. The difficulties posed by
excessive specialization suggest some liabilities of pursuing
production efficiencies via learning by doing under conditions
of rapid technical change in which absorptive capacity is im-
portant. In learning by doing, the firm becomes more prac-
ticed and hence more capable at activities in which it is
already engaged. Learning by doing does not contribute to the
diversity that is critical to learning about or creating something
that is relatively new. Moreover, the notion of "remembering
by doing" (Nelson and Winter, 1982) suggests that the focus
on one class of activity entailed by learning by doing may ef-
fectively diminish the diversity of background that an indi-
vidual or organization may have at one time possessed and,
consequently, undercut organizational absorptive capacity and
innovative performance.
It has become generally accepted that complementary func-
tions within the organization ought to be tightly intermeshed,
recognizing that some amount of redundancy in expertise
may be desirable to create what can be called cross-function
absorptive capacities. Cross-function interfaces that affect or-
ganizational absorptive capacity and innovative performance
include, for example, the relationships between corporate and
divisional R&D labs or, more generally, the relationships
among the R&D, design, manufacturing, and marketing func-
tions (e.g., Mansfield, 1968: 86-88). Close linkages between
design and manufacturing are often credited for the relative
success of Japanese firms in moving products rapidly from
the design stage through development and manufacturing
(Westney and Sakakibara, 1986). Clark and Fujimoto (1987)
argued that overlapping product development cycles facilitate
communication and coordination across organizational sub-
units. They found that the speed of product development is
strongly influenced by the links between problem-solving
cycles and that successful linking requires "direct personal
contacts across functions, liaison roles at each unit, cross-
functional task forces, cross-functional project teams, and a
system of 'product manager as integrator' " (Clark and Fuji-
moto, 1987: 24). In contrast, a process in which one unit
simply hands off the design to another unit is likely to suffer
greater difficulties.
Some management practices also appear to reflect the belief
that an excessive degree of overlap in functions may reduce
1 34/ASQ, March 1990

Absorptive Capacity
the firm's absorptive capacity and that diversity of back-
grounds is useful. The Japanese practice of rotating their
R&D personnel through marketing and manufacturing opera-
tions, for example, while creating knowledge overlap, also
enhances the diversity of background of their personnel.
Often involving the assignment of technical personnel to
other functions for several years, this practice also suggests
that some intensity of experience in each of the complemen-
tary knowledge domains is necessary to put an effective ab-
sorptive capacity in place; breadth of knowledge cannot be
superficial to be effective.
The discussion thus far has focused on internal mechanisms
that influence the organization's absorptive capacity. A ques-
tion remains as to whether absorptive capacity needs to be
internally developed or to what extent a firm may simply buy
it via, for example, hiring new personnel, contracting for con-
sulting services, or even through corporate acquisitions. We
suggest that the effectiveness of such options is somewhat
limited when the absorptive capacity in question is to be inte-
grated with the firm's other activities. A critical component of
the requisite absorptive capacity for certain types of informa-
tion, such as those associated with product and process in-
novation, is often firm-specific and therefore cannot be
bought and quickly integrated into the firm. This is reflected in
Lee and Allen's (1982) findings that considerable time lags are
associated with the integration of new technical staff, partic-
ularly those concerned with process and product develop-
ment. To integrate certain classes of complex and
sophisticated technological knowledge successfully into the
firm's activities, the firm requires an existing internal staff of
technologists and scientists who are both competent in their
fields and are familiar with the firm's idiosyncratic needs, or-
ganizational procedures, routines, complementary capabilities,
and extramural relationships. As implied by the discussion
above, such diversity of knowledge structures must coexist
to some degree in the same minds. Moreover, as Nelson and
Winter's (1982) analysis suggests, much of the detailed
knowledge of organizational routines and objectives that
permit a firm and its R&D labs to function is tacit. As a con-
sequence, such critical complementary knowledge is acquired
only through experience within the firm. Illustrating our gen-
eral argument, Vyssotsky (1977), justifying the placement of
Bell Labs within AT&T, argued: "For research and develop-
ment to yield effective results for Bell System, it has to be
done by ... creative people who understand as much as they
possibly can about the technical state of the art, and about
Bell System and what System's problems are. The R&D
people must be free to think up new approaches, and they
must also be closely coupled to the problems and challenges
where innovation is needed. This combination, if one is lucky,
will result in insights which help the Bell System. That's why
we have Bell Labs in Bell System, instead of having all our
R&D done by outside organizations."
Path Dependence and Absorptive Capacity
Our discussion of the character of absorptive capacity and its
role in assimilating and exploiting knowledge suggests a
simple generalization that applies at both the individual and
organizational levels: prior knowledge permits the assimilation
l135/ASQ, March 1990

and exploitation of new knowledge. Some portion of that prior
knowledge should be very closely related to the new knowl-
edge to facilitate assimilation, and some fraction of that
knowledge must be fairly diverse, although still related, to
permit effective, creative utilization of the new knowledge.
This simple notion that prior knowledge underlies absorptive
capacity has important implications for the development of
absorptive capacity over time and, in turn, the innovative per-
formance of organizations. The basic role of prior knowledge
suggests two features of absorptive capacity that will affect
innovative performance in an evolving, uncertain environment
(Cohen and Levinthal, 1 989b). Accumulating absorptive ca-
pacity in one period will permit its more efficient accumula-
tion in the next. By having already developed some absorptive
capacity in a particular area, a firm may more readily accumu-
late what additional knowledge it needs in the subsequent
periods in order to exploit any critical external knowledge that
may become available. Second, the possession of related ex-
pertise will permit the firm to better understand and therefore
evaluate the import of intermediate technological advances
that provide signals as to the eventual merit of a new techno-
logical development. Thus, in an uncertain environment, ab-
sorptive capacity affects expectation formation, permitting the
firm to predict more accurately the nature and commercial
potential of technological advances. These revised expecta-
tions, in turn, condition the incentive to invest in absorptive
capacity subsequently. These two features of absorptive ca-
pacity-cumulativeness and its effect on expectation forma-
tion-imply that its development is domain-specific and is
path- or history-dependent.
The cumulativeness of absorptive capacity and its effect on
expectation formation suggest an extreme case of path de-
pendence in which once a firm ceases investing in its ab-
sorptive capacity in a quickly moving field, it may never
assimilate and exploit new information in that field, regardless
of the value of that information. There are two reasons for the
emergence of this condition, which we term "lockout"
(Cohen and Levinthal, 1989b). First, if the firm does not de-
velop its absorptive capacity in some initial period, then its
beliefs about the technological opportunities present in a
given field will tend not to change over time because the firm
may not be aware of the significance of signals that would
otherwise revise its expectations. As a result, the firm does
not invest in absorptive capacity and, when new opportunities
subsequently emerge, the firm may not appreciate them.
Compounding this effect, to the extent that prior knowledge
facilitates the subsequent development of absorptive ca-
pacity, the lack of early investment in absorptive capacity
makes it more costly to develop a given level of it in a subse-
quent period. Consequently, a low initial investment in ab-
sorptive capacity diminishes the attractiveness of investing in
subsequent periods even if the firm becomes aware of tech-
nological opportunities.1 This possibility of firms being
"locked-out" of subsequent technological developments has
recently become a matter of concern with respect to indus-
trial policy. For instance, Reich (1987: 64) declaims Mon-
santo's exit from "float-zone" silicon manufacturing because
he believes that the decision may be an irreversible exit from
a technology, in that ". . . each new generation of technology
136/ASQ, March 1990
I
A similar result emerges from models of
adaptive learning. Levitt and March (1988:
322) noted that "a competency trap can
occur when favorable performance with
an inferior procedure leads an organization
to accumulate more experience with it,
thus keeping experience with a superior
procedure inadequate to make it re-
warding to use."

Absorptive Capacity
builds on that which came before, once off the technological
escalator it's difficult to get back on."
Thus, the cumulative quality of absorptive capacity and its role
in conditioning the updating of expectations are forces that
tend to confine firms to operating in a particular technological
domain. If firms do not invest in developing absorptive ca-
pacity in a particular area of expertise early on, it may not be
in their interest to develop that capacity subsequently, even
after major advances in the field. Thus, the pattern of inertia
that Nelson and Winter (1982) highlighted as a central feature
of firm behavior may emerge as an implication of rational be-
havior in a model in which absorptive capacity is cumulative
and contributes to expectation formation. The not-invented-
here syndrome, in which firms resist accepting innovative
ideas from the environment, may also at times reflect what
we call lockout. Such ideas may be too distant from the firm's
existing knowledge base-its absorptive capacity-to be ei-
ther appreciated or accessed. In this particular setting, NIH
may be pathological behavior only in retrospect. The firm
need not have acted irrationally in the development of the ca-
pabilities that yields the NIH syndrome as its apparent out-
come.
A form of self-reinforcing behavior similar to lockout may also
result from the influence of absorptive capacity on organiza-
tions' goals or aspiration levels. This argument builds on the
behavioral view of organizational innovation that has been
molded in large part by the work of March and Simon (1958).
In March and Simon's framework, innovative activity is insti-
gated due to a failure to reach some aspiration level. De-
parting from their model, we suggest that a firm's aspiration
level in a technologically progressive environment is not
simply determined by past performance or the performance
of reference organizations. It also depends on the firm's ab-
sorptive capacity. The greater the organization's expertise and
associated absorptive capacity, the more sensitive it is likely
to be to emerging technological opportunities and the more
likely its aspiration level will be defined in terms of the oppor-
tunities present in the technical environment rather than
strictly in terms of performance measures. Thus, organiza-
tions with higher levels of absorptive capacity will tend to be
more proactive, exploiting opportunities present in the envi-
ronment, independent of current performance. Alternatively,
organizations that have a modest absorptive capacity will tend
to be reactive, searching for new alternatives in response to
failure on some performance criterion that is not defined in
terms of technical change per se (e.g., profitability, market
share, etc.).
A systematic and enduring neglect of technical opportunities
may result from the effect of absorptive capacity on the orga-
nization's aspiration level when innovative activity (e.g., R&D)
contributes to absorptive capacity, which is often the case in
technologically progressive environments. The reason is that
the firm's aspiration level then depends on the very innova-
tive activity that is triggered by a failure to meet the aspiration
level itself. If the firm engages in little innovative activity, and
is therefore relatively insensitive to the opportunities in the
external environment, it will have a low aspiration level with
regard to the exploitation of new technology, which in turn
137/ASQ, March 1990

implies that it will continue to devote little effort to innovation.
This creates a self-reinforcing cycle. Likewise, if an organiza-
tion has a high aspiration level, influenced by externally gen-
erated technical opportunities, it will conduct more innovative
activity and thereby increase its awareness of outside oppor-
tunities. Consequently, its aspiration level will remain high.
This argument implies that reactive and proactive modes of
firm behavior should remain rather stable over time. Thus,
some organizations (like Hewlett-Packard and Sony) have the
requisite technical knowledge to respond proactively to the
opportunities present in the environment. These firms do not
wait for failure on some performance dimension but aggres-
sively seek out new opportunities to exploit and develop their
technological capabilities.2
The concept of dynamically self-reinforcing behavior that may
lead to the neglect of new technological developments pro-
vides some insight into the difficulties firms face when the
technological basis of an industry changes-what Schum-
peter (1942) called "the process of creative destruction." For
instance, the change from electromechanical devices to elec-
tronic ones in the calculator industry resulted in the exit of a
number of firms and a radical change in the market structure
(Majumdar, 1982). This is an example of what Tushman and
Anderson (1986) termed competence-destroying technical
change. A firm without a prior technological base in a partic-
ular field may not be able to acquire one readily if absorptive
capacity is cumulative. In addition, a firm may be blind to new
developments in fields in which it is not investing if its up-
dating capability is low. Accordingly, our argument implies
that firms may not realize that they should be developing their
absorptive capacity due to an irony associated with its valua-
tion: the firm needs to have some absorptive capacity already
to value it appropriately.
Absorptive Capacity and R&D Investment
The prior discussion does not address the question of
whether we can empirically evaluate the importance of ab-
sorptive capacity for innovation. There is a key insight that
permits empirical tests of the implications of absorptive ca-
pacity for innovative activity. Since technical change within an
industry-typically incremental in character (Rosenberg and
Steinmueller, 1988)-is often closely related to a firm's on-
going R&D activity, a firm's ability to exploit external knowl-
edge is often generated as a byproduct of its R&D. We may
therefore consider a firm's R&D as satisfying two functions:
we assume that R&D not only generates new knowledge but
also contributes to the firm's absorptive capacity.3 If absorp-
tive capacity is important, and R&D contributes to it, then
whatever conditions the firm's incentives to learn (i.e., to
build absorptive capacity) should also influence R&D
spending. We may therefore consider the responsiveness of
R&D activity to learning incentives as an indication of the em-
pirical importance of absorptive capacity. The empirical chal-
lenge then is to understand the impact of the characteristics
of the learning environment on R&D spending.
We construct a simple static model of firm R&D intensity,
which is defined as R&D divided by sales. Normalization of
R&D by firm sales controls for the effect of firm size, which
1 38/ASQ, March 1990
2
This argument that such reactive and
proactive behavior may coexist in an in-
dustry over the long run assumes that
there is slack in the selection environment
and that technologically progressive be-
havior is not essential to survival. One can,
alternatively, identify a number of indus-
tries, such as semiconductors, in which it
appears that only firms that aggressively
exploit technical opportunities urvive.
3
We refer readers interested in the details
of the theoretical and subsequent empir-
ical analysis and results to Cohen and Le-
vinthal (1 989a), from which the following
discussion is drawn.

Absorptive Capacity
affects the return per unit of R&D effort. This model is devel-
oped in the broader context of what applied economists have
come to believe to be the three classes of industry-level de-
terminants of R&D intensity: demand, appropriability, and
technological opportunity conditions (Cohen and Levin, 1989).
Demand is often characterized by the level of sales and the
price elasticity of demand. The latter indicates the degree to
which a firm's revenue will increase due to a reduction in
price. For example, in the case of a process innovation that
reduces the cost of production and, in turn, the product price,
the price elasticity of demand reflects the associated change
in total revenue that influences the economic return to inno-
vative effort. Appropriability conditions refer to the degree to
which firms capture the profits associated with their innova-
tive activity and are often considered to reflect the degree to
which valuable knowledge spills out into the public domain.
The emphasis here is on valuable knowledge, because if a
competitor's knowledge spills out but the competitor has al-
ready exploited a first-mover advantage in the marketplace,
this knowledge is no longer valuable to the firm and does not
constitute a spillover by our definition. The level of spillovers,
in turn, depends on the strength of patents within an industry,
the efficacy of secrecy, and/or first-mover advantages. Tech-
nological opportunity represents how costly it is for the firm
to achieve some normalized unit of technical advance in a
given industry. As typically conceived, there are two dimen-
sions of technological opportunity (Cohen and Levin, 1989).
The first, incorporated in our model, refers simply to the
quantity of extraindustry technological knowledge, such as
that originating from government or university labs, that ef-
fectively complements and therefore leverages the firm's
own knowledge output. The second dimension of technolog-
ical opportunity is the degree to which a unit of new knowl-
edge improves the technological performance of the firm's
manufacturing processes or products and, in turn, the firm's
profits. For example, given the vitality of the underlying
science and technology, an advance in knowledge promises
to yield much larger product-performance payoffs in the
semiconductor industry than in steel.4
The basic model of how absorptive capacity affects the de-
termination of R&D expenditures is represented diagramati-
cally in Figure 1. We postulate that learning incentives will
have a direct effect on R&D spending. We also suggest that
where the effect of other determinants, such as technological
opportunity and appropriability, depend on the firm's or rivals'
assimilation of knowledge, absorptive capacity-and there-
fore learning incentives-will mediate those effects. Finally,
we suggest that the effect of appropriability conditions (i.e.,
spillovers) will be conditioned by competitor interdependence.
In this context, we define interdependence as the extent to
which a rival's technical advances diminish the firm's profits.
There are two factors that will affect a firm's incentives to
learn, and, therefore, its incentives to invest in absorptive ca-
pacity via its R&D expenditures. First, there is the quantity of
knowledge to be assimilated and exploited: the more there is,
the greater the incentive. Second, there is the difficulty (or,
conversely, the ease) of learning. Some types of information
are more difficult to assimilate and use than others. We inter-
139/ASQ, March 1990
4
This second dimension is incorporated in
the model developed in Cohen and Le-
vinthal (1989a). We do not incorporate this
second dimension in the present model
because all the qualitative theoretical and
empirical results associated with this
second dimension of technological oppor-
tunity are the same as those associated
with the first considered here.

Figure 1. Model of absorptive capacity and R&D incentives.
Technological Competitor l pla l
Opportunity Interdependence I
|Capacity r
|R&D Spending|
pret this to mean that per unit of knowledge, the cost of its
absorption may vary depending on the characteristics of that
knowledge. As learning is more difficult, more prior knowl-
edge has to have been accumulated via R&D for effective
learning to occur. As a result, this is a more costly learning
environment. In such a setting, R&D is more important to
building absorptive capacity and the more R&D effort the firm
will need to have expended to achieve some level of absorp-
tive capacity. Thus, for a given level of a firm's own R&D, the
level of absorptive capacity is diminished in environments in
which it is more difficult to learn. In addition, we are sug-
gesting that a more difficult learning environment increases
the marginal effect of R&D on absorptive capacity. In con-
trast, in environments in which learning is less demanding, a
firm's own R&D has little impact on its absorptive capacity. In
the extreme case in which external knowledge can be assim-
ilated without any specialized expertise, a firm's own R&D
would have no effect on its absorptive capacity.
We have argued that the ease of learning is in turn deter-
mined by the characteristics of the underlying scientific and
technological knowledge. Although it is difficult to specify a
priori all the relevant characteristics of knowledge affecting
the ease of learning, they would include the complexity of the
knowledge to be assimilated and the degree to which the
outside knowledge is targeted to the needs and concerns of
the firm. When outside knowledge is less targeted to the
firm's particular needs and concerns, a firm's own R&D be-
comes more important in permitting it to recognize the value
of the knowledge, assimilate, and exploit it. Sources that pro-
duce less targeted knowledge would include university labs
involved in basic research, while more targeted knowledge
may be generated by contract research labs, or input sup-
pliers. In addition, the degree to which a field is cumulative, or
the field's pace of advance, should also affect how critical
R&D is to the development of absorptive capacity. The more
that findings in a field build on prior findings, the more neces-
sary is an understanding of prior research to the assimilation
of subsequent findings. The pace of advance of a field affects
the importance of R&D to developing absorptive capacity be-
cause the faster the pace of knowledge generation, the larger
140/ASQ, March 1990

Absorptive Capacity
the staff required to keep abreast of new developments. Fi-
nally, following Nelson and Winter (1982), the less explicit and
codified the relevant knowledge, the more difficult it is to as-
similate.
To structure the analysis, we assumed that firms purposefully
invest in R&D to generate profit and take into account R&D's
dual role in both directly generating new knowledge and con-
tributing to absorptive capacity. Knowledge is assumed to be
useful to the firm in that increments to a firm's own knowl-
edge increase the firm's profits while increments to rivals'
knowledge diminish them. We posit a simple model of the
generation of a firm's technological knowledge that takes into
account the major sources of technological knowledge uti-
lized by a firm: the firm's own R&D knowledge that originates
with its competitors' R&D, spillovers, and that which origi-
nates outside the industry. Figure 2 provides a stylized repre-
sentation of this model in which, first, the firm generates
new knowledge directly through its own R&D, and second,
extramural knowledge, drawn from competitors as well as
extraindustry sources such as government and university
labs, also contribute to the firm's knowledge. A central fea-
ture of the model is that the firm's absorptive capacity deter-
mines the extent to which this extramural knowledge is
utilized, and this absorptive capacity itself depends on the
firm's own R&D. Because of this mediating function, absorp-
tive capacity influences the effects of appropriability and
technological opportunity conditions on R&D spending. Thus,
the effects of appropriability and technological opportunity are
not independent of R&D itself.
Figure 2. Model of sources of a firm's technical knowledge.
Absorptive Capacity
Own R Technical -- I ~~~~~~~~Knowledge
Spilloversof Competitors' Knowledge
Extraindustry Knowledge
A key assumption in the -model is that exploitation of com-
petitors' research findings is realized through the interaction
of the firm's absorptive capacity with competitors' spillovers.
This interaction signifies that a firm is unable to assimilate
externally available knowledge passively. Rather, to utilize the
accessible R&D output of its competitors, the firm invests in
its absorptive capacity by conducting R&D. Figure 2 also illus-
trates that, like its assimilation of competitors' R&D output, a
firm's assimilation of extraindustry knowledge-the dimen-
sion of technological opportunity considered here-is con-
strained by its absorptive capacity. According to our model,
therefore, the factors that affect learning incentives (i.e., the
ease of learning and the quantity of available knowledge) in-
fluence the effects of appropriability and technological oppor-
tunity conditions on R&D.
141/ASQ, March 1990

Direct effect of ease of learning. As shown formally in
Cohen and Levinthal (1989a), this model implies that as the
ease of learning diminishes, learning becomes more depen-
dent on a firm's own R&D, and R&D spending increases be-
cause of two effects. First, the marginal impact of R&D on
absorptive capacity is greater in more difficult learning envi-
ronments. As the learning environment becomes more diffi-
cult, however, there is a second, more subtle effect. Since,
ceteris paribus, a more difficult learning environment lowers
firms' absorptive capacities, R&D activity becomes more of a
private good in the sense that competitors are now less able
to tap into the firm's R&D findings that spill out.
Technological opportunity. We predict that an increase in
technological opportunity-the amount of available relevant
external technical knowledge-will elicit more R&D in more
difficult learning environments. Greater technological oppor-
tunity signifies greater amounts of external information,
which increase the firm's incentive to build absorptive ca-
pacity, and a more challenging learning environment in-
creases the level of R&D necessary to build absorptive
capacity.
Appropriability. We predict that spillovers will provide, in
part, a positive incentive to conduct R&D due to the interac-
tion of spillovers with an endogenous absorptive capacity.
Traditionally, spillovers have been considered only a deterrent
to R&D activity (e.g., Nelson, 1959; Arrow, 1962; Spence,
1984). In the standard view, a firm's incentive to invest in
R&D is diminished to the extent that any findings from such
activities are exploited by competitors and thereby diminish
the innovator's own profits. In our framework, however, this
negative appropriability incentive associated with spillovers is
counterbalanced by a positive absorptive-capacity-building in-
centive. The more of its competitors' spillovers there are out
there, the more incentive the firm has to invest in its own
R&D, which permits it to exploit those spillovers.
We have shown elsewhere (Cohen and Levinthal, 1 989a) that
when this absorption incentive is large, as when learning is
difficult, spillovers may actually encourage R&D. The relative
magnitude of the absorption incentive is greater when firms
within an industry are less interdependent in the sense that
rivals' technical advances have less of an effect on the firm's
own profits. With less interdependence, the degree to which
rivals gain from the firm's R&D spillovers at the firm's ex-
pense diminishes relative to the benefit of being able to ex-
ploit the rivals' spillovers. Either a more competitive market
structure or a higher price elasticity of demand for the firm's
product can diminish interdependence in an industry.
METHODS
Data and Measures
To test the predictions of our framework for R&D activity, we
used cross-sectional survey data on technological opportunity
and appropriability conditions in the American manufacturing
sector collected from R&D lab managers by Levin et al. (1983,
1987), and the Federal Trade Commission's Line of Business
Program data on business unit sales, transfers, and R&D ex-
penditures. The dependent variable, R&D intensity, was de-
142/ASQ, March 1990

Absorptive Capacity
fined as company-financed business-unit research and
development expenditures, expressed as a percentage of
business unit sales and transfers over the period 1975
through 1977. The data on interindustry differences in tech-
nological opportunity and appropriability are industry (line of
business) mean scores computed as an average over all re-
spondents within a given industry. The sample consists of
1,719 business units representing 318 firms in 151 lines of
business.
The data pose two estimation issues. First, some 24 percent
of the firms performed no R&D in at least one year. If the in-
dependent variables reflect both the probability of conducting
R&D, as well as the amount of R&D spending, then a Tobit
analysis would be appropriate. Alternatively, a firm may re-
quire some initial level of absorptive capacity before it is in-
fluenced by the characteristics of the learning environment. In
this case, the variables reflecting the ease of learning only af-
fect the amount of R&D conducted by firms engaging in
R&D activity and not the probability of engaging in R&D ac-
tivity. In light of the uncertainty over the appropriate estima-
tion technique, we explored the robustness of the results by
analyzing a Tobit and an OLS (or GLS) specification. The
second estimation issue is the presence of heteroscedasti-
city. We found the assumption of homoscedasticity to be vio-
lated, with the logarithm of the error variance being a linear
function of the exogenous variables and the number of re-
spondents to Levin et al.'s (1983, 1987) survey. Unless other-
wise noted, the results we report in this section reflect
robust effects that hold across three different estimation
methods, including ordinary least squares (OLS), generalized
least squares (GLS) in which we adjust for heteroscedasticity,
and Tobit, which was used when we included the observa-
tions for which R&D expenditures were zero.
We tested our predictions in the context of an empirical
model of business unit R&D intensity in which technological
opportunity, appropriability, and demand conditions are con-
sidered as the principal industry-level determinants of firms'
R&D spending. While data constraints do not permit observa-
tion of the direct effect of the ease of learning or its deter-
minants on firms' R&D spending, we were able to examine
how these variables condition the influence on R&D of tech-
nological opportunity and appropriability conditions.
Technological opportunity was assessed with variables mea-
suring the "relevance" or "importance" for technological
progress in each line of business of what are considered to
be two critical sources of technological opportunity-the
science base of the industry and extraindustry sources of
knowledge (Cohen and Levin, 1989). These measures are
drawn from Levin et al.'s survey, in which R&D managers in-
dicated on a 7-point Likert scale the relevance of eleven basic
and applied fields of science and the importance of external
sources of knowledge to technological progress in a line of
business. The basic fields of science include biology, chem-
istry, mathematics, and physics, and the applied fields of
science include agricultural science, applied math/operations
research, computer science, geology, materials science,
medical science, and metallurgy.5 The five extraindustry
143/ASQ, March 1990
5
Although geology was classed as a basic
science by Levin et al., we classed it as
an applied science because of its inductive
methodology and intensive use by firms
in the extractive sector.

sources of knowledge considered here included equipment
suppliers (EQUIPTECH), materials suppliers (MATERIAL-
TECH), downstream users of the industry's products (USER-
TECH), government laboratories and agencies (GOVTECH),
and universities (UNIVTECH). We interpreted the measures of
the relevance or importance of each field or knowledge
source to index the relative quantity of knowledge generated
by that field or source that is potentially useful. We then dis-
tinguished across the eleven scientific fields and the five ex-
traindustry knowledge source variables on the basis of the
ease of learning associated with each. We suggested above
that one important determinant of the ease of learning is the
degree to which outside knowledge is targeted to a firm's
needs and concerns. One can readily distinguish among both
the eleven fields and the five extraindustry knowledge
sources on that basis. The knowledge associated with the
basic sciences is typically less targeted than that associated
with the applied sciences. We also distinguished among the
extraindustry knowledge sources on the same basis. A priori,
we ranked university labs, government labs, materials sup-
pliers, and equipment suppliers as providing increasingly
more targeted knowledge to firms. We did not rank the rela-
tive effect of knowledge originating from users because, as
suggested by von Hippel (1978), users will often provide a
product idea to potential suppliers, but the informativeness of
the "solution concept" is quite variable. Therefore, the tar-
geted quality of the information is variable as well.
To represent intraindustry spillovers of R&D, we employed
measures from Levin et al.'s survey of the effectiveness of
six mechanisms used by firms to capture and protect the
competitive advantages of new processes and new products:
patents to prevent duplication, patents to secure royalty in-
come, secrecy, lead time, moving quickly down the learning
curve, and complementary sales and service efforts. We em-
ployed the maximum value of the effectiveness scores at-
tained by these mechanisms as our measure of appropriability
or spillovers, and label this variable APPROPRIABILITY; a high
level of APPROPRIABILITY reflects a low level of spillovers.
In our theory, we predicted an interaction effect by which, as
the ease of learning diminishes, or firms become less inter-
dependent, the effect of spillovers on R&D spending should
become more positive (or less negative). In the absence of
any direct measure of the ease of learning, we distinguished
categorically between those industries in which basic science
was more relevant to technical progress than the relatively
more targeted applied sciences and assumed that learning
was generally less difficult in industries that fell into the latter
category. Thus, we created a dummy variable, DUMBAS,
that equals one when the average value of the relevance
scores associated with the basic fields exceeds that asso-
ciated with the applied fields and that equals zero otherwise.
We specified the dummy variable, DUMAPP, analogously. To
capture the interdependence of firms, we employed mea-
sures of industries' competitiveness as represented by each
industry's four-firm concentration ratio (C4) and industry-level
estimates of the price elasticity of demand (PELAS).
To further control for industry demand conditions, we used
industry estimates developed by Levin (1981) of price elas-
144/ASQ, March 1990

Absorptive Capacity
ticity (PELAS) and income elasticity (INCELAS) and a demand
time-shift parameter (DGROWTH). Finally, we included an-
other control variable that may also reflect technological op-
portunity, industry maturity. We used a somewhat crude
measure of industry maturity, NEWPLANT, that measures the
percentage of an industry's property, plant, and equipment
installed within the preceding five years.
RESU LTS
Technological opportunity. Our theory suggests that when
the targeted quality of knowledge is less (i.e., learning is more
difficult), an increase in the relevance (i.e., quantity) of knowl-
edge should have a more positive effect on R&D intensity.
Therefore, the coefficient estimates of the variables mea-
suring the relevance of the four basic scientific fields should
exceed those of the variables measuring the relevance of the
seven applied scientific fields. Confirming the prediction,
Table 1 indicates that the estimated coefficients for the ap-
plied sciences are, with the exception of computer science,
lower than that for the basic sciences. The similarity of the
estimate of the effect of the relevance of computer science,
an applied science, to those of some of the basic sciences
suggests that the assumption may not be correct that only
one determinant of the ease of learning, the targeted quality
of the field, varies systematically across the fields of applied
and basic science. Another determinant of the ease of
learning postulated above is a field's pace of advance, where
faster pace should require more R&D to permit assimilation,
and the pace of advance in computer science has been rela-
tively rapid over the past two decades.
To further test the prediction that the coefficient values of the
less targeted, basic science field variables would exceed
those of the applied fields, we estimated a specification, oth-
erwise identical to the first, in which we constrained the co-
efficients of the basic sciences to be the same and the
coefficients of the applied sciences to be the same. This
shows the effect on R&D spending as the overall technolog-
ical opportunity associated with basic science and applied
science, respectively, change. The constrained coefficient es-
timates of the effect of the technological opportunity asso-
ciated with the basic and applied sciences are significantly
different (at the p < .01 level) across all estimation methods,
with the former equal to .189 and the latter equal to -.080 in
the GLS estimation. Therefore, relative to the effect of an in-
crease in the technological opportunity associated with ap-
plied science, an increase in that associated with basic
science elicits more R&D.
Our predicted ranking of the coefficient magnitudes asso-
ciated with the extraindustry sources of knowledge, reflecting
increasingly targeted knowledge from these sources, is
largely confirmed. The coefficient estimate for the importance
of knowledge originating from universities exceeds that for
government labs, which, in turn, is greater than that for ma-
terials suppliers, which exceeds that for equipment suppliers.
The difference between coefficient values is statistically sig-
nificant in the case of government sources versus materials
suppliers for both the OLS and Tobit results (p < .01 ) and in
the case of materials suppliers versus equipme~nt suppliers in
145/ASQ, March 1990

Table 1
Analysis of R&D Intensity*
Regression Coefficient
OLS GLS Tobit
Variable (N = 1302) (N = 1302) (N = 1719)
Intercept - 5.184m -2.355 - 4.086m
(1.522) (1.037) (1.461)
APPROPRIABILITY x C4 .213 .342 .368w
(.128) (.103) (.130)
APPROPRIABILITY x PELAS - .192 - .200 - .176
(.106) (.091) (.103)
APPROPRIABILITY x DUMAPP .448- .248 .211
(.202) (.143) (.194)
APPROPRIABILITY x DUMBAS .302 .174 .094
(.208) (.144) (.206)
USERTECH .470w .397w .612w
(.104) (.069) (.107)
UNIVTECH .374w .318w .395s
(.131) (.091) (.147)
GOVTECH .221- .069 .137
(.106) (.079) (.107)
MATERIALTECH - .258w - .074 - .303w
(.098) (.070) (. 1 00)
EQUIPTECH - .401 - .484w - .574w
(.1 1 1) (.077) (.117)
Biology .314w .185w .276-
(.102) (.071) (.114)
Chemistry .289w .081 .191-
(.084) (.062) (.088)
Math .184 .151 .123
(.131) (.097) (.143)
Physics .373w .323w .310
(.117) (.091) (.128)
Agricultural Science -.441w -.273w -..308w
(.088) (.064) (.099)
Applied Math/Operations Research -.237 -.117 -.366-
(.148) (.102) (.152)
Computer Science .294 .116 .433w
(.124) (.090) (.122)
Geology - .363w - .240w - .365w
(.084) (.061) (.097)
Materials Science -.110 -.150 .116
(.125) (.095) (.118)
Medical Science -.179 -.133 - .133
(.093) (.070) (.103)
Metallurgy -.315w -. 195w -.393w
(.077) (.053) (.089)
NEWPLANT .057w .049w .045w
(.008) (.006) (.007)
PELAS .936 1.0820 .892
(.611) (.527) (.573)
INCELAS 1.077w .587w 1.112w
(.170) (.131) (.188)
DGROWTH .068 - .074 .004
(.090) (.053) (.105)
R2 .287
*p < .05; Up < .01.
* Reproduced from Cohen and Levinthal (1989a: 590-591, 569-596). Standard errors are in parentheses.
the GLS results (p < .01). While we had no prediction re-
garding the coefficient value for USERTECH, the consistently
high value of the coefficient estimate may reflect some ele-
ment of demand conditions. Consistent with this, we have
observed the variable USERTECH to be significantly corre-
lated with measures of the importance of product differentia-
tion (cf. Cohen and Levinthal, 1 989a).
146/ASQ, March 1990

Absorptive Capacity
Appropriability. The results largely support the prediction
that the ease of learning conditions the effect of knowledge
spillovers. The effect on R&D intensity of increasing appro-
priability (i.e., diminishing spillovers) was significantly greater
(p < .05) in those industries in which the applied sciences are
more relevant to innovation than the basic sciences. This re-
sult suggests that the positive absorption incentive asso-
ciated with spillovers is greater in industries in which the
difficulty of learning is greater. Second, there is a significant
positive effect (p < .01) of the interaction between market
concentration and the appropriability level. As market concen-
tration increases (indexing a diminution in competitiveness),
the positive effect of a given appropriability level on R&D in-
tensity increases, as predicted. Likewise, the effect of the in-
teraction of the price elasticity of demand and the level of
appropriability is negative (but only significant at p < .05 in
the GLS estimate), providing additional support for the propo-
sition that the positive effect of spillovers will increase in in-
dustries in which firms are less interdependent. The results
suggest that the learning environment affects the impact of
spillovers on R&D spending and that the importance of the
positive absorptive-capacity-building incentive relative to that
of the negative appropriability incentive is conditioned by the
degree of competitor interdependence.
While we have shown that the learning environment modifies
the effect of appropriability conditions, the question remains
whether spillovers may, on balance, actually encourage R&D
in some industries. To explore this possibility, we examined
the effect of spillovers in the four two-digit SIC code level in-
dustries for which our sample contains enough lines of busi-
ness to permit separate industry regressions. These include
SICs 20 (food processing), 28 (chemicals), 35 (machinery),
and 36 (electrical equipment). Due to the reduction in the de-
grees of freedom for industry-level variables, we simplified
the estimating equation to consider only the direct effect of
APPROPRIABILITY, and the science field variables were
summarized as the maximum relevance scores attained by
the basic and applied fields, respectively. In SICs 28 and 36,
the effect of the APPROPRIABILITY variable was negative
and significant at conventional levels, implying that R&D in-
tensity rises with spillovers. In the Tobit results, the sign was
also positive for SICs 28 and 36, but the coefficient esti-
mates were not quite significant at the .05 confidence level.
Thus, in SICs 28 (chemicals) and 36 (electrical equipment),
R&D intensity rose with spillovers when we controlled for
other industry-level variables conventionally thought to drive
R&D spending, including technological opportunity and de-
mand conditions. Although the analyses showing a positive
effect of spillovers in these two industry groups do not repre-
sent a direct test of our model, the results suggest, particu-
larly when considered with the interaction results, that the
positive absorption incentive associated with spillovers may
be sufficiently strong in some cases to more than offset the
negative appropriability incentive.
IMPLICATIONS FOR INNOVATIVE ACTIVITY
Drawing on our prior work (Cohen and Levinthal, 1987
1 989a), we offer some implications of absorptive capacity for
147/ASQ, March 1990

the analysis of other innovative activities, including basic re-
search, the adoption and diffusion of innovations, and deci-
sions to participate in cooperative R&D ventures, that follow
from the preceding analyses.
The observation that R&D creates a capacity to assimilate and
exploit new knowledge provides a ready explanation of why
some firms may invest in basic research even when the pre-
ponderance of findings spill out into the public domain. Spe-
cifically, firms may conduct basic research less for particular
results than to be able to provide themselves with the general
background knowledge that would permit them to exploit
rapidly useful scientific and technological knowledge through
their own innovations or to be able to respond quickly-be-
come a fast second-when competitors come up with a
major advance (see also Rosenberg, 1990). In terms of our
discussion of the cognitive and organizational aspects of ab-
sorptive capacity, we may think of basic research as broad-
ening the firm's knowledge base to create critical overlap
with new knowledge and providing it with the deeper under-
standing that is useful for exploiting new technical develop-
ments that build on rapidly advancing science and technology.
This perspective on the role of basic research offers a rather
different view of the determinants of basic research than that
which has dominated thinking in this area for the thirty years
since Nelson's (1959) seminal article. Nelson hypothesized
that more diversified firms will invest more heavily in basic
research because, assuming imperfect markets for informa-
tion, they will be better able to exploit its wide-ranging and
unpredictable results. Nelson thus saw product-market diver-
sification as one of the key determinants of basic research.6
Emphasizing the role of basic research in firm learning, our
perspective redirects attention from what happens to the
knowledge outputs from the innovation process to the nature
of the knowledge inputs themselves. Considering that ab-
sorptive capacity tends to be specific to a field or knowledge
domain means that the type of knowledge that the firm be-
lieves it may have to exploit will affect the sort of research
the firm conducts. From this vantage point, we would conjec-
ture that as a firm's technological progress becomes more
closely tied to advances in basic science (as has been the
case in pharmaceuticals), a firm will increase its basic re-
search, whatever its degree of product-market diversification.
We also suggest, with reference to all firm research, not just
basic research, that as the fields underlying technical advance
within an industry become more diverse, we may expect
firms to increase their R&D as they develop absorptive ca-
pacities in each of the relevant fields. For example, as auto-
mobile manufacturing comes to draw more heavily on newer
fields such as microelectronics and ceramics, we expect that
manufacturers will expand their basic and applied research
efforts to better evaluate and exploit new findings in these
areas.
The findings on the role of absorptive capacity and the ways
in which it may be developed also have implications for the
analysis of the adoption and diffusion of innovations. Our per-
spective implies that the ease of learning, and thus tech-
nology adoption, is affected by the degree to which an
innovation is related to the pre-existing knowledge base of
148/ASQ, March 1990
6
Markets for information often fail because
they inherently represent a situation of in-
formation asymmetry in which the less in-
formed party cannot properly value the
information he or she wishes to purchase,
and the more informed party, acting self-
interestedly, attempts to exploit that in-
ability (Williamson, 1975).

Absorptive Capacity
prospective users. For example, personal computers diffused
more rapidly at the outset among consumers and firms who
had prior experience on mainframes or minicomputers. Like-
wise, software engineering practices seem to be adopted
more readily by programmers with previous Pascal rather
than Fortran experience because the structure of Pascal more
closely reflects some of the underlying principles of software
engineering (Smith et al., 1989). Our argument also suggests
that an innovation that is fully incorporated in capital equip-
ment will diffuse more rapidly than more disembodied inno-
vations that require some complementary expertise on the
part of potential users. This is one of the anticipated benefits
of making computers more "user friendly."
The importance of absorptive capacity also helps explain
some recent findings regarding firms' cooperative research
ventures. First, Link (1987) has observed that cooperative re-
search ventures are actually found more typically in industries
that employ more mature technologies rather than in indus-
tries in which technology is moving ahead quickly-as seems
to be suggested by the popular press. Second, it has been
observed that cooperative ventures that have been initiated to
pursue basic research, as well as more applied research ob-
jectives, have been subject over the years to increasing pres-
sure to focus on more short-term research objectives
(Mowery and Rosenberg, 1989). The simple notion that it is
important o consider the costs of assimilating and exploiting
knowledge from such ventures provides at least a partial ex-
planation for these phenomena. Many cooperative ventures
are initiated in areas in which the cost to access the output of
the venture is low, or they often gravitate toward such areas
over time. Conversely, those who are attempting to en-
courage cooperative research ventures in quickly advancing
fields should recognize that the direct participation in the ven-
ture should represent only a portion of the resources that it
will take to benefit from the venture. Participating firms also
must be prepared to invest internally in the absorptive ca-
pacity that will permit effective exploitation of the venture's
knowledge output.
CONCLUSION
Our empirical analysis of R&D investment suggested that
firms are in fact sensitive to the characteristics of the learning
environment in which they operate. Thus, absorptive capacity
appears to be part of a firm's decision calculus in allocating
resources for innovative activity. Despite these findings, be-
cause absorptive capacity is intangible and its benefits are in-
direct, one can have little confidence that the appropriate
level, to say nothing of the optimal level, of investment in ab-
sorptive capacity is reached. Thus, while we have proposed a
model to explain R&D investment, in which R&D both gen-
erates innovation and facilitates learning, the development of
this model may ultimately be as valuable for the prescriptive
analysis of organizational policies as its application may be as
a positive model of firm behavior.
An important question from a prescriptive perspective is
When is a firm most likely to underinvest in absorptive ca-
pacity to its own long-run detriment? Absorptive capacity is
more likely to be developed and maintained as a byproduct of
149/ASQ, March 1990

routine activity when the knowledge domain that the firm
wishes to exploit is closely related to its current knowledge
base. When, however, a firm wishes to acquire and use
knowledge that is unrelated to its ongoing activity, then the
firm must dedicate effort exclusively to creating absorptive
capacity (i.e., absorptive capacity is not a byproduct). In this
case, absorptive capacity may not even occur to the firm as
an investment alternative. Even if it does, due to the intan-
gible nature of absorptive capacity, a firm may be reluctant to
sacrifice current output as well as gains from specialization to
permit its technical personnel to acquire the requisite breadth
of knowledge that would permit absorption of knowledge
from new domains. Thus, while the current discussion ad-
dresses key features of organizational structure that deter-
mine a firm's absorptive capacity and provides evidence that
investment is responsive to the need to develop this capa-
bility, more research is necessary to understand the decision
processes that determine organizations' investments in ab-
sorptive capacity.
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