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Absorptive Capacity: A New Perspective on Learning and Innovation

Wesley M. Cohen; Daniel A. Levinthal

Administrative Science Quarterly, Vol. 35, No. 1, Special Issue: Technology, Organizations, andInnovation. (Mar., 1990), pp. 128-152.

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Absorptive Capacity: ANew Perspective onLearning and Innovation

Wesley M. CohenCarnegie Me llon University

Daniel A. LevinthalUniversity of Pennsylvania

O 1990 by Comell University.0001-8392/90/3501-0128/$1.OO.

W e appreciatethe comments of KathleenCarley. Robyn Dawes, Mark Fichman, TomFinholt. Sara Kiesler, Richard Nelson,Linda Pike, and three anonymous ref-erees. The representationsand conclu-sions presented herein are those of the

authors. They have not been adopted inwhole or in part by the FederalTradeCommission, its Bureau of Economics, orany other entity within the commission.The FTC's Disclosure Avoidance O fficerhas certified that the data included in this

In th is paper, w e argue that the abi l i ty of a f i rm to recog-nize the value of new, external information, assimilate it,and app ly it to comm ercia l ends is cr it ica l to i ts innovat ivecapabili t ies. We label this cap abi l i ty a f i rm's absorptivecapacity an d suggest that it is largely a funct ion of thefirm's level of pr io r related knowledge. The discussion fo-cuses f irst on the cognit ive basis fo r an individual 's ab-

sorptive capacity including, in particular, p r ior relatedkno wled ge and diversity o f background. We the n charac-terize the factors th at influence absorptive capacity at theorganizational level, h o w an organization's absorptive ca-paci ty d i f fers fro m that of i ts indiv idual members, and therole of d iversity o f expertise wi th in an organization. W eargue that the developm ent o f absorptive capacity, and, inturn, innovative performance are history- o r path-depen-dent and argue h ow lack of investment in an area of ex-pert ise ear ly o n m ay foreclose the future development o fa technical capabi li ty i n that area. We fo rmulate a m ode lof f i r m investmen t in research and development (R&D), in

wh ich R&D contr ibutes to a f i rm's absorptive capacity,and test pred ictions relating a f i rm's investmen t in R&D t othe k nowledg e under ly ing technical change wi th in an in-dustry. Discussion focuses on the implications o f absorp-tive capacity for the analysis of other related innovativeactivities, inc lud ing basic research, the ad opt ion and dif-fusion of innovations, and decisions to participate in co-op era tive R&D ventures..

INTRODUCTION

Outside sources of knowledge are often critical to the inno-vation process, whatever the organizational level at which theinnovating unit is defined. While the example of Japan illus-trates the point saliently at the national level (e.g., Westneyand Sakakibara, 1986; Mansfield, 1988; Rosenberg andSteinmueller, 1988), it is also true of entire industries, aspointed ou t by Brock (1975) in the case of computers and byPeck (1962) in the case of aluminum. A t th e organizationallevel, March and Simon (1958: 188) suggested m ost innova-tions result from borrowing rather than invention. This obser-vation is supported by extensive research on the sources ofinnovation (e.g., Mueller, 1962; Hamberg, 1963; Myers and

Marquis, 1969; Johnston and Gibbons, 1975; von Hippel,1988). Finally, the importance to innovative performance ofinformation originating from other internal units in the firm ,outside the formal innovating unit (i.e., the R&D lab), such asmarketing and manufacturing, is well understood (e.g., Mans-field, 1968).

The ability to exploit external knowledge is thus a criticalcom ponent of innova tive capabilities. W e argue that theability to evaluate and utilize outside knowledge is largely afunction of the level of prior related knowledge. A t the mo stelemental level, this prior knowledge includes basic skills or

even a shared language but may also include knowledge ofthe most recent scientific or technological developments in agiven field. Thus, prior related knowledge confers an ability torecognize the value of ne w information, assimilate it, and



Absorptive Capacity

At the level of the firm-the innovating unit that is the focushere-absorptive capacity is generated in a variety of ways.Research shows that firms that conduct their ow n R&D arebetter able t o use externally available information (e.g., Tilton,1971; Allen, 1977; Mo wery, 1983). This implies that absorp-tive capacity may be created as a byproduct of a firm's R&D

investment. Other w ork suggests that absorptive capacitymay 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 bette r able to recognize and exploit new informationrelevant to a particular product market. Production experienceprovides the firm wi th the background necessary both to rec-ognize the value of and imp lement m ethods to reorganize orautomate particular manufacturing processes. Firms also in-vest in absorptive capacity directly, as when they send per-sonnel for advanced technical training. The concept ofabsorptive capacity can best be developed through an exami-

nation of the cognitive structures tha t underlie learning.

Cognitive Structures

The premise of the notion of absorptive capacity is that theorganization needs prior related know ledge t o assimilate anduse new knowledge. S tudies in the area of cognitive and be-havioral sciences at the individual level both justify and enrichthis observation. Research on memory development suggeststhat accumulated prior knowledge increases both the abilityto p ut new knowledge into memory, what w e would refer toas the acquisition of knowledge, and the ability to recall and

use it. With respect to the acquisition of knowledge, B owerand Hilgard (1981 : 424) suggested that m emory developmentis 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 morefacile is the individual in using them in ne w settings.

Some psychologists suggest that p rior knowledge enhanceslearning because mem ory-or the storage of knowledge-isdeveloped b y associative learning in wh ich events are re-corded into m emory by establishing linkages w ith pre-existingconcepts. Thus, B ower and Hilgard (1981) suggested that the

breadth of categories into wh ich prior knowledge is orga-nized, the differen tiation of those categories, and the linkagesacross them perm it individuals to make sense of and, in turn,acquire new knowledge. In the c ontex t of learning a lan-guage, Lindsay and Norman (1977: 51 7) suggested theproblem in learning words is not a result of lack of exposureto them but that "to understand complex phrases, muchmore is needed than exposure to the wo rds: a large body ofknowledge mu st first be accumulated. After all, a wo rd issimply a label for a set of structures w ithin the mem orysystem, so the structures must exist before the word can be

considered learned." Lindsay and Norman further suggestedthat knowledge may be nom inally acquired but not we ll uti-lized subsequently because the individual did not already pos-sess the appropriate contextual know ledge necessary to



wh ich the knowledge in question m ay itself be a set oflearning skills. There m ay be a transfer of learning skillsacross bodies of knowledge th at are organized and expressedin 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). Thisprogressive improvem ent in the performance of learning

tasks is a form of knowledge transfer that has been referredto as "learning t o learn" (Ellis, 1965; Estes, 1970). Estes(1970: 16). however, suggested that the term "learning tolearn" is a misnom er in that prior experience w ith a learningtask does not necessarily improve performance because anindividual knows h ow to learn (i.e., form ne w associations)better, but that an individual may simply have accumulatedmore prior knowledge so that he or she needs to learn less toattain a given level of performance. Notwithstanding what itis about prior learning experience that may affect subsequentperformance, both explanations of the relationship betwe enearly learning and subsequent pe rformance em phasize theimportance of prior knowledge for learning.

The effect of prior learning experience on subsequentlearning tasks can be observed in a variety of tasks. For in-stance, Ellis (1965: 4) suggested that "students who havethoroughly mas tered the principles of algebra find it easier tograsp advanced wo rk in mathem atics such as calculus." Fur-ther illustration is p rovided by Anderson, Farrell, and Sauers(1984), w ho compared students learning LlSP as a first pro-gramming language with students learning LlSP after havinglearned Pascal. The Pascal students learned LlSP m uch mo reeffectively, in part because they bette r appreciated the se-mantics of various programming concepts.

The literature also suggests that problem-solving skills de-velop sim ilarly. In this case, problem-solving me thod s andheuristics typically constitute the prior knowledge thatperm its individuals to acquire related problem-solving capabil-ities. In their work on the development of com puter program-ming skills, Pirolli and Anderson (1985) found that almost allstudents developed new programs by analogy-to-exampleprograms and that their success was determined by ho w we llthey understood w hy these examples worked .

W e argue that p roblem solving and learning capabilities are sosimilar that the re is little reason to differentiate the ir m odes ofdevelopment, although exactly what is learned may differ:learning capabilities involve the development of the capacityto assimilate existing knowledge, while problem-solving skillsrepresent a capacity to create ne w knowledge. Supportingthe po int that there is little difference betwee n the tw o,Bradshaw, Langley, and Simon (1983) and Sim on (1985) sug-ges ted that the sort of necessary preconditions for successfullearning that w e have identified do not differ fro m the pre-conditions required for prob lem solving and, in turn, for thecreative process. Moreover, they argued that the processesthemselves 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 havenever been cons idered before. Likew ise, Ellis (1965: 35) sug-



Absorptive Capacity

phenom enon of "insight" that typically refers to the rapid so-lution of a problem. Thus, the psychology literature suggeststhat creative capacity and wh at w e call absorptive capacityare quite similar.

To develop an effective absorptive capacity, whether it be forgeneral knowled ge or problem-solving or learning skills, it is

insufficient merely to expose an individual briefly to the rele-vant prior knowledge. Intensity of ef fort is critical. W ith regardto storing knowledge in m emory, Lindsay and Norman (1977:355) noted that the more deeply the material is processed-the more ef fort used, the more processing makes use of as-sociations betwe en the item s to be learned and knowledgealready in the memory-the bette r will be the later retrievalof the item. Similarly, learning-set theory (Harlow, 1949, 1959)implies that important aspects of learning how to solveproblems are built up over many practice trials on relatedproblems. Indeed, Harlow (1959) suggested that if practice

w ith a particular type of problem is discontinued before it isreliably learned, then little transfer will occur to the nextseries of problems. The refore, he concluded that cons iderabletime and effort should be spent on early problems beforemoving on to more complex problems.

Two related ideas are implicit in the notion that the ability toassimilate information is a function of the richness of the pre-existing knowledge structure: learning is cumulative, andlearning performance is greatest when the object of learningis related to wh at is already known. As a result, learning ismo re difficult in novel domains, and, m ore generally, an indi-

vidual's expertise-what he or she knows we ll-will changeonly incrementally. The above discussion also suggests thatdiversity of knowled ge plays an impo rtant role. In a setting inwh ich there is uncertainty about the knowledge domainsfrom wh ich potentially useful information m ay emerge, a di-verse background provides a more robust basis for learningbecause it increases the prospect that incoming informationwi ll relate to wha t is already know n. In addition to strength-ening assimilative powers, knowledge diversity also facilitatesthe innovative process by enabling the individual to makenovel associations and linkages.

From Indiv idual to Organizat ional Absorpt ive Capacity

An organization's absorptive capacity will depend on the ab-sorptive capacities of its individual me mbers. To this extent,the development of an organization's absorptive capacity willbuild on prior investment in the development of its constit-uent, individual absorptive capacities, and, like individuals' ab-sorptive capacities, organizational absorptive capacity w illtend to develop cumulatively. A firm's absorptive capacity isnot, however, simply the sum of the absorptive capacities ofits employees, and it is therefore useful to consider wh ataspects o f absorptive capac ity are distinctly organizational.

Absorptive capacity refers not only to the acquisition or as-similation of inform ation by an organization but also to the or-ganization's ability to exploit i t. Therefore, an organization'sabsorptive capacity does not simply depend on the organiza-



entry. Thus, to understand the sources of a firm's absorptivecapacity, w e focus on the structure of com munication be-tween the external environment and the organization, as wellas am ong the subunits of the organization, and also on thecharacter and distribution of expertise with in the organization.

Communication systems may rely on specialized actors totransfer information from the environment or m ay involve less

structured patterns. The problem of designing comm unicationstructures cannot be disentangled from the distribution of ex-pertise in the organization. The firm's absorptive capacity de-pends on the individuals w ho stand at the interface of eitherthe firm and the external environment or at the interface be-twe en subunits within the firm. That interface function maybe diffused across individuals or be quite centralized. Whenthe expertise of m os t individuals within th e organizationdiffers considerably from that of external actors wh o can pro-vide useful information, som e m embers of th e group arelikely to assume relatively centralized "gatekeeping" or

"boundary-spanning" roles (Allen, 1977; Tushman, 1977). Fortechnical inform ation that is difficult for internal staff to as-similate, a gatekeeper both monitors the environment andtranslates the technical information into a form understand-able to the research group. In contrast, if externa l informationis closely related to ongoing activity, then external informationis readily assimilated and gatekeepers or boundary-spannersare not so necessary for translating information. Even in thissetting, however, gatekeepers may emerge to the extent thatsuch role specialization relieves others from having to mo nitorthe environment.

A difficulty may emerge under conditions of rapid and uncer-tain technical change, however, when this interface functionis centralized. W hen information flows are som ewha t randomand it is not clear where in the firm or subunit a piece of out-side knowledge is best applied, a centralized gatekeeper maynot provide an effective link to the environment. U nder suchcircumstances, it is be st for the organization to expose a fairlybroad range of prospective "receptors" to the environment.Such an organization wo uld exhibit the organic structure ofBurns and Stalker (1961 6), wh ich is m ore adaptable "wh enproblems and requirements for action arise which cannot be

broken dow n and distributed among specialist roles within aclearly defined hierarchy."

Even when a gatekeeper is important, his or her individualabsorptive capacity does not constitute the absorptive ca-pacity of his or her unit within the firm. The ease or difficultyof the internal communication process and, in turn, the levelof organizational absorptive capacity are no t only a function ofthe gatekeeper's capabilities but also of the expertise ofthose individuals to w ho m the gatekeeper is transmitting theinformation. Therefore, relying on a small set of technologicalgatekeepers may not be sufficient; the group as a wh ole

mu st have som e level of relevant background knowledge, andwhen 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



Absorptive Capacity

is essential for communication. At the most basic level, therelevant knowledge that permits effective communicationboth with in and across subunits consists of shared languageand symbols (D earborn and Simon, 1958; Katz and Kahn,1966; Allen and Cohen, 1969; Tushman, 1978; Zenger andLawrence, 1989). W ith regard to the absorptive capacity of

the firm as a whole, there may, however, be a trade-off in theefficiency of internal communication against the ability of thesubunit to assimilate and exploit information originating fromother subunits or the environment. This can be seen as atrade-off between inward-looking versus outward-looking ab-sorptive capacities. While both of these components are nec-essary for effective organizational learning, excessivedominance by one or the other will be dysfunctional. If allactors in the organization share the same specialized lan-guage, they will be effective in communicating w ith one an-other, but they may no t be able to tap into diverse externalknowledge sources. In the limit, an internal language, coding

schem e, or, m ore generally, any particular body of expertisecould becom e sufficiently overlapping and specialized that itimpedes the incorporation of outside knowledge and resultsin the pathology of the not-invented-here (NIH) syndrome.This m ay explain Katz and Allen's (1982) findings that thelevel of external communication and communication withother project groups declines with project-group tenure.

This trade-off between outward- and inward-looking compo-nents of absorptive capacity focuses our attention on ho w therelationship between knowledge sharing and knowledge di-versity across individuals affects the development of organi-zational absorptive capacity. While som e overlap ofknowled ge across individuals is necessary for internal com-munication, there are benefits to diversity of knowledgestructures across individuals that parallel the benefits to di-versity of know ledge with in individuals. As Simon (1985)pointed out, diverse knowledge structures coexisting in thesame mind elicit the sort of learning and pboblem solving thatyields innovation. Assum ing a sufficient level of know ledgeoverlap to ensure effective communication, interactionsacross individuals who each possess diverse and differentknowledge structures will augment the organization's ca-

pacity for making novel linkages and associations-inno-vating-beyond wh at any one individual can achieve.Utterback (1971), summarizing research on task performanceand innovation, noted.that diversity in the work setting "stim-ulates the generation of new ideas." Thus, as with Nelsonand Winter's (1982) view of organizational capabilities, an or-ganization's absorptive capacity is not resident in any singleindividual bu t depends on the links across a mosaic of indi-vidual capabilities.

Beyond diverse know ledge structures, the sort of knowledgethat individuals should possess to enhance organizational ab-

sorptive capacity is also important. Critical knowledge doesnot simply include substantive, technical knowledge; it alsoincludes awareness of where useful complementary exper-tise resides within and outside the organization. This sort of



shown the importance for innovation of close relationshipsw ith both buyers and suppliers. To the ex tent that an organi-zation deve lops a broad and active netw ork of internal andexternal relationships, individuals' awareness of others' capa-bilities and know ledge w ill be strengthened. As a result, indi-vidual absorptive capacities are leveraged all the more, andthe organization's absorptive capacity is strengthened.

The observation that the ideal knowledge structure for an or-ganizational subunit shou ld reflect only partially overlappingknow ledge complemen ted by nonoverlapping diverse knowl-edge suggests an organizational trade-off be tween diversityand commonality of knowledge across individuals. Wh ilecommon knowledge improves communication, commonalityshould not be carried so far that diversity across individuals issubstantially diminished. Likewise, division of labor pro-mo ting gains from specialization should not be pushed so farthat communication is undermined. The difficulties posed byexcess ive specialization suggest some liabilities of pursuing

production efficiencies via learning by doing under conditionsof rapid technical change in wh ich absorptive capacity is im-portant. In learning by doing, the firm becom es more prac-ticed and hence more capable at activities in which it isalready engaged. Learning by doing does not contribute to thediversity that is critical to learning about or crea ting som ethingthat is relatively new. Moreover, the notion of "rememberingby doing" (Nelson and Winter, 1982) suggests that the focuson 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 tim e possessed and,consequently, undercut organizational absorptive capacity andinnovative 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 expertisemay be desirable to create wha t can be called cross-functionabsorptive capacities. Cross-function interfaces that a ffect or-ganizational absorptive capacity and innovative performanceinclude, for example, the relationships be twe en corporate anddivisional R&D labs or, m ore generally, the relationshipsamong the R&D, design, manufacturing, and marketing func-tions (e.g., Mansfield, 1968: 86-88). Close linkages betweendesign and manufacturing are often credited for the relativesuccess of Japanese firms in moving products rapidly fromthe design stage through development and manufacturing(Westney and Sakakibara, 1986). Clark and Fujimoto (1987)argued that overlapping product developm ent cycles facilitatecommunication and coordination across organizational sub-units. They found that the speed of product development isstrongly influenced by the links between problem-solvingcycles and that successful linking requires "direct personalcontacts 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 wh ich one unitsimply hands off the design to another unit is likely to suffergreater difficulties.



Absorptive Capacity

the firm 's absorptive capacity and that d iversity of back-grounds is usefu l. The Japanese practice of rotating theirR&D personne l through m arketing and m anufacturing opera-tions, for example, while creating know ledge overlap, alsoenhances the d iversity of background of their personnel.Ofte n involving the assignment of technical personnel to

other functions for several years, this practice also suggeststhat some intensity of experience in each of the complemen-tary knowledge domains is necessary to p ut an effective ab-sorptive capacity in place; breadth of knowledge cannot besuperficial to be effective.

The discussion thus far has focused on internal mechanismsthat influence the organization's absorptive capacity. A ques-tion remains as to whether absorptive capacity needs to beinternally developed or to w hat extent a firm may simply buyit via, for example, hiring ne w personnel, con tracting for con-sulting services, or even throug h corporate acquisitions. W e

suggest that the e ffectiveness of such options is somewha tlimited when the absorptive capacity in question is to be inte-grated w ith the firm's other activities. A critical component ofthe requ isite 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 bebought and quickly integra ted into the firm . This is reflected inLee and Allen's (1982) findings that considerable tim e lags areassociated w ith the integration of ne w technical staff, partic-ularly those concerned wit h process and product develop-me nt. To in tegrate certain classes of comp lex andsophisticated technological knowledge successfully into the

firm's activities, the firm requires an existing internal staff oftechnologists and scientists who are both com petent in theirfields and are familiar w ith the firm 's idiosyncratic needs, or-ganizational procedures, rou tines, com plem entary capabilities,and extramural relationships. As imp lied by the discussionabove, such diversity of knowledge structures must coexistto som e degree in the same minds. Moreover, as Nelson andWinter's (1982 ) analysis suggests, m uch of the de tailedknow ledge of organizational rou tines and ob jectives thatperm it a firm and its R&D labs to func tion is tacit. As a con-sequence, such critical compleme ntary knowledge is acquired

only through experience within the firm. Illustrating our gen-eral argument, Vyssotsky (1977), ustifying the placement ofBell Labs with in AT&T, argued: "For research and develop-me nt to yield effective results for Bell System, it has to bedone by . . . creative people wh o understand as m uch as theyposs ibly can about the technical state of the art, and aboutBell System and what System's p roblems are. The R&Dpeople mus t be free to think up ne w approaches, and theymust also be closely coupled to the prob lems and challengeswh ere innovation is needed. This combination, if one is lucky,will result in insights which help the Bell System. That's w hyw e have Bell Labs in Bell System, ins tead of having all ourR&D done by outside organizations."

Path Dependence and Absorptive Capacity

Our discussion of the character of absorptive capacity and its



A similar result emerges from models ofadaptive learning. Levitt and March (1988:322) noted that "a competency trap canoccur when favorable performance withan inferior procedure leads an organizationto accumulate more experience with it.

and exploitation of n ew know ledge. Some portion of that priorknowledge should be very closely related to the new know l-edge to facilitate assimilation, and some fraction of thatknow ledge must be fairly diverse, although still related, topermit effective, creative utilization of the new knowledge.This simp le no tion that prior know ledge underlies absorptivecapacity has important implications for the developm ent of

absorptive capacity over time and, in turn, the innovative per-formance of organizations. The basic role of prior know ledgesuggests tw o features of absorptive capacity that wil l affectinnovative perform ance in an evolving, uncertain environm ent(Cohen and Levinthal, 1989b). Accum ulating absorptive ca-pacity in one period w ill permit its more efficient accumula-tion in the next. By having already developed some absorptivecapacity in a particular area, a firm may more readily accumu-late wh at additional knowledge it needs in the subsequentperiods in order to exploit any critical external knowledge thatmay becom e available. Second, the possession of related ex-pertise w ill perm it the firm to better understand and thereforeevaluate the import of intermed iate technological advancesthat provide signals as to the eventual merit of a n ew techno-logical development. Thus, in an uncertain environment, ab-sorptive capacity affects expectation formation, pe rmitting thefirm to predict more accurately the nature and commercialpotential of technological advances. These rev ised expecta-tions, in turn, condition the incen tive to invest in absorptivecapacity subsequently. These two features of absorptive ca-pacity-cumulativeness and its effec t on expec tation forma-tion-imply that its developm ent is domain-specific and ispath- or h istory-depend ent.

The cumulativeness of absorptive capacity and its effect onexpec tation formation suggest an extrem e case of path de-pendence in which once a firm ceases inves ting in its ab-sorptive capacity in a quickly m oving field, it m ay neverassimilate and exploit new information in that field, regardlessof the value of that inform ation. There are tw o reasons for theemergence of this condition, which w e term "lockout"(Cohen and Levinthal, 1989b). First, if the firm does not de-velop its absorptive capacity in some initial period, then itsbeliefs about the technological opportunities presen t in agiven field w ill tend not to change over tim e because the firm

may not be aware of th e significance of signals that wou ldotherwise revise its expec tations. As a result, the firm doesnot inves t in absorptive capacity and, w hen ne w oppo rtunitiessubsequently emer.ge, the firm may no t appreciate them .Compounding this effect, to the extent that prior knowledgefacilitates the subsequent deve lopment of absorptive ca-pacity, the lack of early investment in absorptive capacitymakes it m ore costly to develop a given level of it in a subse-quent period. Consequently, a lo w initial investment in ab-sorptive capacity diminishes the attractiveness of investing insubsequent periods even if the firm becomes aware of tech-nological opp ~r tun i t ie s.~his possibility of firms being"locked-out" of subsequent technological developments hasrecently become a m atter of concern with respect to indus-trial po licy. For instance, Reich (1987: 64) declaims Mon-santo's exit from "float-zone" silicon manufacturing because

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Absorptive Capacity

builds on that which came before , once off the technologicalescalator it's difficult to g et back on."

Thus, the cumulative quality of absorptive capacity and its rolein conditioning the updating of expectations are forces thattend to confine firms to operating in a particular technologicaldomain. If firms do not invest in developing absorptive ca-

pac ity in a particular area of expertise early on, it may not bein their interest to develop that capacity subsequently, evenafter m ajor advances in the field . Thus, the pattern of inertiathat Nelson and Winter (1982) highlighted as a central featureof firm behavior may emerge as an implication of rational be-havior in a model in wh ich absorptive capacity is cum ulativeand contributes to expectation formation. The not-invented-here syndrome, in which firm s resist accepting innovativeideas from the environment, may also at times reflect whatw e call lockout. Such ideas may be too d istant from the firm 'sexisting know ledge base-its absorptive capacity-to be ei-

ther appreciated or accessed. In this particular setting, NIHmay be pathological behavior only in retrospect. The firmneed no t 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 alsoresult from the influence of absorptive capacity on organiza-tions' goals or aspiration levels. This argument bu ilds on thebehavioral view of organizational innovation that has beenmolded in large part by the wo rk 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, w e suggest that a firm's aspirationlevel in a technologically progressive environment is notsimply determined by past performance or the performanceof reference organizations. I t also depends on the firm's ab-sorp tive capacity. The greater the organization's expertise andassociated absorptive capacity, the more sens itive it is likelyto be to em erging technological opportunities and the morelikely its aspiration level w ill be defined in terms of the oppor-tunities present in the technical environmen t rather thanstrictly in terms of performance measures. Thus, organiza-tions w ith higher levels of absorptive capacity w ill tend to be

more proactive, exploiting opportunities present in the envi-ronment, independent of current performance. Alternatively,organizations that have a m odest absorptive capacity w ill tendto be reactive, searching for new alternatives in response tofailure on some perform ance criterion that is not defined interm s of technical change per se (e.g., profitability, marketshare, etc.).

A systematic and enduring neglect of technical opportunitiesmay result from the effec t of absorptive capacity on the orga-nization's aspiration leve l when innovative activity (e.g., R&D)contributes to absorptive capacity, which is often the case intechnologically progress ive env ironm ents. The reason is thatthe firm 's aspiration level then depends on the very innova-tive activity that is triggered by a failure to me et the aspirationlevel itself. If the firm engages in little innovative activity, and



This argument that such rea ctive andproactive behavior may coexist in an in-dustry over the long run assumes thatthere is slack in the selection environmentand that technologically progressive be-havior is not essential to s u ~ iv a l. ne can,alternatively, identify a num ber of indus-tries, such as semiconductors, in whic h itappears that only firms that aggressivelyexploit technical opportunities s u ~ i v e .

W e refer readers interested in the detailsof the theoretical and subsequent empir-

implies that it will continue to devote little effort to innovation.This creates a se lf-reinforcing cycle. L ikew ise, if an organiza-tion has a high aspiration level, influenced by externally gen-erated technical opportunities, it will conduct more innovativeactivity and thereby increase its awareness of outside oppor-tunities. C onsequently, 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 therequisite technical know ledge to respond proactively to theopportunities present in the environment. These firms do n otwa it for failure on some performance dimension but aggres-sively seek out ne w opp ortunities to exploit and develop theirtechnological capabilities2

The concept of dynamically self-reinforcing behavior that maylead to the neglect of n ew technological developm ents pro-vides some insight into the difficulties firms face wh en thetechnological basis of an industry changes-what Schum-

peter (1942) called "the process of creative destruction." Forinstance, the change from electromechanical devices to elec-tronic ones in the calculator industry resulted in the exit of anumber of firm s and a radical change in the market structure(Majum dar, 1982). This is an example of wha t Tushman andAnderson (1986) termed competence-destroying echnicalchange. A firm with out a prior technological base in a partic-ular field may not be able to acquire one readily if absorptivecapacity is cumu lative. In addition, a firm may be blind to ne wdevelopments in fields in which it is not investing if its up-dating capability is low. Accordingly, our argument impliesthat firms may no t realize that they should be developing theirabsorptive capacity due to an irony associated wi th its valua-tion: the firm needs to have some absorptive capacity alreadyto value i t appropriately.

Absorptive Capacity and R&D Investment

The prior discussion does not address the question ofwhether w e can empirically evaluate the importance of ab-sorp tive capacity for innovation. There is a key insigh t thatperm its empirical tests of th e implications of absorptive ca-pacity for innovative activity. Since technical change within anindustry-typically incremental in character (Rosenberg andSteinmueller, 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 maytherefore consider a firm's R&D as satisfying tw o functions:w e assume that R&D not only generates new knowledge butalso contributes to the firm's absorptive ~a p a c it y . ~f absorp-tive capacity is important, and R&D contributes to it, thenwhatever conditions the firm 's incentives to learn (i.e., tobuild absorptive capacity) should also influence R&Dspending. W e may therefore consider the responsiveness ofR&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 impac t of the characteristicsof the learning environm ent on R&D spending.

W e cons truct a simp le static model of firm R&D intensity,



Absorptive Capacity

This second dimension is incorporated inthe model developed in Cohen and Le-vinthal(1989a). We do not incorporate thissecond dimension in the present modelbecause all the qualitative theoretical and

affects the return per unit of R&D effort. This model is devel-oped in the broader context of what applied econom ists havecome to believe to be the three classes of industry-level de-terminants of R&D intensity: demand, appropriability, andtechnological opportunity conditions (Cohen and Levin, 1 989).Demand is often characterized by the level of sales and the

price elasticity of demand. The latter indicates the degree towh ich a firm's revenue w ill increase due to a reduc tion inprice. For example, in the case of a process innovation thatreduces the cost of production and, in turn, th e produc t price,the price elasticity of demand reflects the associated changein total revenue that influences the economic return to inno-vative effort. Appropriability conditions refer to the degree towhich firms capture the profits associated w ith the ir innova-tive activity and are often considered to reflect the degree towh ich valuable knowledge spills out into the public domain.The emphasis here is on valuable knowledge, because if acompetitor's know ledge spills out but the competitor has al-

ready exp loited a first-mover advantage in the marketplace,this knowledge is no longer valuable to the firm and does no tconstitute a spillover by our definition . The level of spillovers,in turn, depends on the strength of patents with in an industry,the efficacy of secrecy, and/or first-mover advantages. Tech-nological opportunity represents ho w cos tly it is for the firmto achieve some normalized unit of technical advance in agiven industry. As typically conceived, there are tw o dimen-sions of technological opportunity (Cohen and Levin, 1989).The first, incorporated in our model, refers simply to thequantity of extraindustry technological knowledge, such as

that originating from governmen t or university labs, that e f-fectively com plements and therefore leverages the firm'sow n knowledge output. The second dimension of technolog-ical opportunity is the degree to w hich a unit of n ew knowl-edge improves the technological performance of the firm 'smanufacturing processes or products and, in turn, the firm'sprofits. For example, given the vitality of the underlyingscience and technology, an advance in knowledge prom isesto yield m uch larger product-performa nce payoffs in thesemiconductor industry than in steeL4

The basic m odel of h ow absorptive capacity affects the de-

termination of R&D expenditures is represen ted diagramati-cally in Figure 1. W e postulate that learning incentives willhave a direct effect on R&D spending. We also suggest thatwh ere the eff.ect of o ther determ inants, such as technologicalopportun ity and appropriability, depend on the firm 's or rivals'assimilation of knowledge, absorptive capacity-and there -fore learning incentives-w ill med iate those effects. Finally,w e suggest that the effec t of appropriability conditions (i.e.,spillovers) w ill be cond itioned by com petitor interdependence.In this context, we define interdependence as the extent towh ich a rival's technical advances diminish the firm's profits.

There are tw o factors that w ill affect a firm's incentives tolearn, and, there fore, i ts incentives to invest in absorptive ca-pacity via its R&D expenditures. First, there is the quantity ofknow ledge to be assimilated and exploited: the more there is,



Figure 1. Model of absorptive capacity and R&D incentives.

Technological CompetitorAppropriability

Opportunity Interdependence

R&D Spending

pret this to mean that per unit of knowledge, the cost of itsabsorption may vary depending on the characteristics of thatknowledge. As learning is more difficult, mo re prior know l-edge has to have been accumulated via R&D for effectivelearning to occur. As a result, this is a more costly learningenvironment. In such a setting, R&D is m ore impo rtant tobuilding absorptive capacity and the more R&D effo rt the firmwill need to have expended to achieve som e level of absorp-tive capacity. Thus, for a given level of a firm's ow n R&D, thelevel of absorptive capacity is diminishe d in env ironm ents inwh ich it is more difficult to learn. In addition, w e are sug-

gesting that a more difficult learning environment increasesthe marginal effect of R&D on absorptive capacity. In con-trast, in environments in which learning is less demanding, afirm's ow n R&D has little impact on its absorptive capacity. Inthe extreme case in which external know ledge can be assim-ilated withou t any specialized expertise, a firm's ow n R&Dwould have no effect on its absorptive capacity.

W e have argued that the ease of learning is in turn deter-mined by the characteristics of the underlying scientific andtechnological knowledge. Although it is difficult to specify apriori all the relevant characteristics of know ledge affecting

the ease of learning, they w ou ld include the co mplexity of theknowledge to be assimilated and the degree to which theoutside knowledge is targeted to the needs and concerns ofthe firm. W hen outside know ledge is less targeted to thefirm's particular needs and concerns, a firm's own R&D be-comes more important in permitting it to recognize the valueof the knowledge, assim ilate, and exploit it. Sources that pro-duce less targeted knowledge would include university labsinvolved in basic research, while more targeted knowledgemay be generated by contrac t research labs, or input sup-pliers. In addition, the degree to w hich a field is cumulative, orthe field's pace of advance, should also affect how c riticalR&D is to the developm ent of absorptive capacity. The m orethat findings in a field build on prior findings, the more neces-sary is an understanding of prior research to the assimilationof subsequent findings. The pace of advance of a field affects



Absorptive Capacity

the staff requ ired to keep abreast of new developments. Fi-nally, following Nelson and Winter (1982), the less explicit andcodified the relevant knowledge , the more difficult it is to as-similate.

To structure the analysis, we assumed that firms purposefullyinvest in R&D to generate profit and take into account R&D's

dual role in b oth directly generating new knowledge and con-tributing to absorptive capacity. Knowledge is assumed to beuseful to the firm in that increments to a firm's o wn knowl-edge increase the firm's profits wh ile increments to rivals'knowledge diminish them . We posit a simple model of thegeneration of a firm 's techno logical knowledge that takes intoaccount the major sources of technological knowledge uti-lized by a firm : the firm's ow n R&D knowledge that originateswith 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 asextraindustry sources such as governm ent and universitylabs, also contribute to the firm 's know ledge . A central fea-ture of the model is that the firm's absorptive capacity deter-mines the extent to wh ich this extramural knowledge isutilized, and this absorptive capacity itself depends on thefirm's ow n R&D. Because of this med iating function, absorp-tive capacity influence s the effects of appropriability andtechnological opportunity cond itions on R&D s\pending. Thus,the effects of appropriability and technological opportunity arenot indepen dent of R&D itself.

Figure 2. Model of sources of a firm's technical knowledge.

Absorptive Capacity

Own R&D TechnicalKnowledge

Spilloversof Competitors'Knowledge I/Extraindustry Knowledge 1

A key assumption in the.model is that exploitation of com -petitors' research findings is realized through the interactionof the firm's absorptive capacity with competitors' spillovers.This interaction signifies that a firm is unable to assimilateexternally available know ledge passively. Rather, to utilize theaccessible R&D output of its competitors, the firm invests inits absorptive capacity by conducting R&D. Figure 2 also illus-trates that, like its assimilation of com petitors' R&D output, afirm'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



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 aprivate 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, thisnegative appropriability incentive associated with spillovers is

counterbalanced by a positive absorptive-capacity-building n-

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, 1989a) 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'sown 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'sproduct 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 opportunityand 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



though geology was classed as a basic

Absorptive Capacity

fined as company-financed business-un it research anddevelopm ent expenditures, expressed as a percentage ofbusiness unit sales and transfers over the period 1975through 1977. The data on interindustry differences in tech-nological opportun ity and appropriability are industry (line ofbusiness) mean scores computed as an average over all re-

spondents within a given industry. The sample consists of1,719 business units rep resenting 318 firms in 151 lines ofbusiness.

The data pose tw o estimation issues. First, some 24 percentof the firms performed no R&D in at least one year. If the in-depend ent variables reflect both the probability of conduc tingR&D, as well as the amount of R&D spending, then a Tobitanalysis 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. Inthis case, the variables reflecting the ease of learning only af-

fect the amount of R&D conducted by firms engaging inR&D activity and not the p robability of engaging in R&D ac-tivity. In light of the uncertainty over the appropriate estima-tion technique, w e explored the robustness of the results byanalyzing a Tobit and an OLS (or GLS) specification. Thesecond estimation issue is the presence of heteroscedasti-city. We found the assumption of homoscedasticity to be vio-lated, w ith the logarithm of the error variance being a linearfunction of the exogenous variables and the number of re-spondents to Levin et a l . ' ~1983, 1987) survey. Unless other-wise noted, the results we report in this section reflect

robust effects that hold across three different es timationmethods, including ordinary least squares (OLS), generalizedleast squares (GLS) n which w e adjust for heteroscedasticity,and Tobit, which was used wh en w e included the observa-tions for which R&D expenditures we re zero.

W e tested our predictions in the con text of an empiricalmod el of business unit R&D intensity in which technologicalopportunity, appropriability, and demand conditions are con-sidered as the principal industry-level determinants of firms'R&D spending. While data constraints do n ot perm it observa-tion of the direct effect of the ease of learning or its deter-

minan ts on firms' R&D spending, we w ere able to exam ineho w these variables cond ition the influence on R&D of tech -nological opportun ity and appropriability conditions.

Technological opportunity was assessed wi th variables mea-suring the "relevance" or "importance" for technologicalprogress in each line of business of what are considered tobe tw o critical sources of technological opportunity-thescience base of the industry and extraindustry sources ofknowledge (Cohen and Levin, 1989). These measures aredrawn from Levin et al.'s survey, in which R&D managers in-dicated on a 7-po int Likert scale the relevance of eleven basic

and applied fields of science and the importance of externalsources of knowledge to technological progress in a line ofbusiness. The basic fields of science include biology, chem-istry, m athematics, and physics, and the applied fields of

5



sources of knowledge considered here included equipmen tsuppliers (EQUIPTECH), materials suppliers (MATERIAL-TECH), downstream users of the industry's produc ts (USER-TECH), government laboratories and agencies (GOVTECH),and unive rsities (UNIVTECH).W e interpreted the measures ofthe relevance or importance of each field or knowledgesource to index the relative quantity of know ledge generated

by that field or source that is po tentially useful. We then dis-tinguished across the eleven sc ientific fields and the five ex-traindustry knowledge source variables on the basis of theease of learning associated w ith each. W e suggested abovethat one important determinan t of the ease of learning is thedegree to which outside know ledge is targeted to a firm'sneeds and concerns. One can readily distinguish among bo ththe eleven fields and the five extraindustry knowledgesources on that basis. The know ledge associated w ith thebasic sciences is typically less targeted than that associatedw ith the applied sciences. We also distinguished among theextraindustry know ledge sources on the same basis. A priori,w e ranked university labs, governm ent labs, materials sup-pliers, and equipment suppliers as providing increasinglymore targeted know ledge to firms. We did not rank the rela-tive effect of know ledge originating from users because, assuggested by von Hippel (1978), users w ill often provide aproduct idea to potential suppliers, but the informativeness ofthe "solution concept" is quite variable. Therefore, the tar-geted quality of the information is variable as well.

To represent intraindustry spillovers of R&D, w e em ployedmeasures from Levin et al.'s survey of the effectiveness ofsix mechanisms used by firms to capture and protect the

competitive advantages of new processes and ne w products:patents to prevent duplication, patents to secure royalty in-come, secrecy, lead time, moving quickly down the learningcurve, and complementary sales and service efforts. We em -ployed the maximum value of the effectiveness scores at-tained by these mechanisms as our m easure of appropriabilityor spillovers, and label this variable APPROPRIABILITY; a highlevel of APPROPRIABILITY reflects a low level of spillovers.

In our theory, we predicted an interac tion effec t by which , asthe ease of learning diminishes, or firms become less inter-dependent, the e ffect of sp illovers on R&D spending should

become more positive (or less negative). In the absence ofany direct measure of the ease of learning, w e distingu ishedcategorically be tween those industries in which basic sciencewas more relevant to technical progress than the relativelymore targeted applied sciences and assumed that learningwas generally less difficult in industries that fell into the lattercategory. Thus, w e created a dum my variable, DUMBAS,that equals one when the average value of the relevancescores associated w ith the basic fields exceeds that asso-ciated with the applied fields and that equals zero otherw ise.W e specified the dum my variable, DUMAPP, analogously. Tocapture the interdependence of firms, w e employed mea-sures of industries' competitiveness as represented by eachindustry's four-firm concentration ratio (C4) and industry-leve lestimates of the price elasticity of demand (PELAS).



Absorptive Capacity

ticity (PELAS) and income elasticity (INCELAS) and a dem andtime-shift parameter (DGR OW TH). Finally, we included an-other control variable that may also reflect technological op-portunity, industry ma turity. W e used a somew hat crudemeasure of industry maturity, NEWPLANT, that measures thepercentage of an industry's property, plant, and equipment

installed within the preceding five years.

RESULTS

Techn ological o pp ort un ity . Our theory suggests that whenthe targeted quality of knowledge is less (i.e., learning is moredifficult), an increase in the relevance (i.e., quantity) of knowl-edge should have a m ore positive e ffect on R&D intensity.Therefore, the coefficient estimates of the variables mea-suring the relevance of the four basic scientific fields shouldexceed those of the variables measuring the relevance of theseven 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 theestimate of th e e ffect of the relevance of computer science,an applied science, to those of so me of the basic sciencessuggests that the assumption m ay not be correct that onlyone determinant of the ease of learning, the targeted qualityof the field, varies systematically across the fields of appliedand basic science. Another determinant of the ease oflearning postulated above is a field's pace of advance, wh erefaster 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 tw o decades.

To further test the prediction that the coefficient values of theless targeted, basic science field variables wo uld exceedthose of the applied fields, w e estimated a specification, oth-erwise identical to th e first, in wh ich w e constrained the co-efficients of the basic sciences to be the sam e and thecoefficients of th e applied sciences to be the same. Thisshow s the effec t on R&D spending as the overall technolog-ical opportunity associated wi th basic science and appliedscience, respec tively, change. The constrained coefficient es-timates of the effec t of the technological opportunity asso-

ciated wi th the basic and applied sciences are significantlydifferent (at the p < .O1 level) across all estimation methods,w ith the form er equal to ,189 and the latter equal to - ,080 inthe 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 wi th basicscience elicits more R&D.

Our predicted ranking of the coefficient magnitudes asso-ciated wi th the extraindustry sources of knowledge, reflectingincreasingly targeted knowledge from these sources, islargely confirmed. The coe fficient estimate for the importance

of knowledge originating from universities exceeds that forgovernment 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-



Analysis of R&D Intensity*

VariableOLS

(N = 1302)

Regression CoefficientGLS

(N = 1302)Tobi t

(N = 1719)

Intercept

APPROPRlABlLlTY x C4

APPROPRlABlLlTY x PELAS

APPROPRlABlLlTY x DUMAPP

APPROPRlABlLlTY x DUMBAS

USERTECH

UNIVTECH

GOVTECH

MATERIALTECH

EQUIPTECH

Biology

Chemistry

Math

Physics

Agricultural Science

Applied Mathloperations Research

Computer Science

Geology

Materials Science

Medical Science

Metallurgy

NEWPLANT

PELAS

INCELAS

D G R O W H

R2

,936(.611)1 077-(. 170),068

(.090),287

1.082*(.527),587-

(.I311- ,074

(.053)

,892(.573)1.112-(.I881,004

(.105)

* p < .05; p < .01.* Reproduced from Cohen and Levinthal (1989a: 590-591, 569-596). Standard errors are in parentheses.

the GLS results (p< .01). While w e had no prediction re-

garding the coefficient value for USERTECH, the cons istentlyhigh value of the coefficient estimate may reflect some ele-me nt of demand conditions. Consistent wi th this, we haveobserved the variable USERTECH to be sign ificantly corre-



Absorptive Capacity

Appropriability. The results largely support the predictionthat the ease of learning conditions the effect of know ledgespillovers. The effe ct 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 aremore 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 thedifficulty of learning is greater. Second, there is a significantpositive effect (p < .01) of the interaction betwe en marketconcentration and the appropriability level. As m arket concen-tration increases (indexing a diminution in competitiveness),the positive effect of a given appropriability level on R&D in-tensity increases, as p redicted. Likewise, the e ffect of the in-teraction of the price elasticity of demand and the level ofappropriability is negative (bu t only s ignificant at p < .05 inthe GLS estimate), providing additional support for the propo-sition that the positive effect of spillovers wi ll increase in in-

dustries in which firms are less interdependent. The resultssuggest that the learning environm ent affects the impac t ofspillovers on R&D spending and that the importance of thepositive absorptive-capacity-building ncentive relative to thatof the negative appropriability incentive is conditioned by thedegree of competitor interdependence.

While w e have shown that the learning environment modifiesthe effec t of appropriability conditions, the question remainswhether spillovers may, on balance, actually encourage R&Din some industries. To explore this possibility, w e examinedthe 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 includeSICS 20 (food processing), 28 (chem icals),35 (machinery),and 36 (electrical equipm ent). Due to th e reduction in the de-grees of freedom for industry-level variables, we simp lifiedthe estimating equation to consider only the direct effect ofAPPROPRIABILITY, and the science field variables weresummarized as the maximum relevance scores attained bythe basic and applied fields, respectively. In SICS 28 and 36,

the effect of the APPROPRIABILITY variable was negativeand significant at conventional levels, implying that R&D in-

tensity rises w ith spillovers. In the Tobit results, the sign wasalso positive for SICS 28 and 36, but the coefficient esti-mates were not quite significant at the .05 confidence level.Thus, in SICS 28 (chem icals) and 36 (electrical equipment),R&D intensity rose with spillovers when w e controlled forother industry-level variables conventionally thought to driveR&D spending, including technological opportunity and de-mand conditions. Although the analyses showing a positiveeffec t of spillovers in these tw o industry groups do not repre-sent a direct test of our model, the results suggest, particu-larly wh en considered w ith the interaction results, that thepositive absorption incentive associated w ith spillovers maybe sufficiently strong in some cases to m ore than offset thenegative appropriability incentive.



Markets for information often fail becausethey inherently represent a situation of in-formation asymmety in which the less in-formed party cannot properly value theinformation he or she wishes to purchase,

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, tha t followfrom the preceding analyses.

The observation that R&D creates a capacity to assimilate andexploit ne w know ledge provides a ready explanation of whysome firms may inves t 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 particularresults than to be able to provide themselves with the generalbackground knowledge that wo uld permit them to exploitrapidly use ful scientific and technological knowledge throughtheir ow n innovations or to be able to respond quickly-be-come a fast second-when competitors come up with amajor advance (see also Rosenberg, 1990). In terms of ourdiscussion of the cognitive and organizational aspects of ab-sorp tive capacity, we may think of basic research as broad-ening the firm's know ledge base to create critical overlap

with new knowledge and providing it with the deeper under-standing that is useful for exp loiting ne w technical develop-ments that build on rapidly advancing science and technology.

This perspective on the role of basic research offers a ratherdifferent view of the determinants of basic research than thatwhich has dominated thinking in this area for the thirty yearssince Nelson's (1959) seminal article. Nelson hypothesizedthat more d iversified firms wi ll invest more heavily in basicresearch because, assuming imperfect markets for informa-tion, they w ill be better able to exploit its wide-ranging andunpredictable results. Nelson thus saw product-market diver-

sification as one of th e key determinan ts of basic research.=Emphasizing the role of basic research in firm learning, ourperspec tive redirects attention from wh at happens to theknow ledge outputs from the innovation process to the natureof the knowledge inputs themselves. Considering that ab-sorptive capacity tends to be specific to a field or know ledgedomain means that the type of knowledge that the firm be-lieves it may have to exploit will a ffect the so rt of researchthe firm conducts. From this vantage point, w e would conjec-ture that as a firm 's technological progress becomes moreclosely tied to advances in basic science (as has been thecase in pharmaceuticals), a firm will increase its basic re-search, whatever its degree of produc t-market diversification.W e also suggest, w ith reference to all firm research, not justbasic research, that as the fields underlying technical advancewithin an industry become m ore diverse, we may expectfirms 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 newerfields such as m icroelectronics and ceramics, w e expect thatmanufacturers will expand their basic and applied researchefforts to better evaluate and exploit new findings in theseareas.

The findings on the role of absorptive capacity and the waysin which it may be developed also have implications for theanalysis of the adoption and diffusion of innovations. Our per-spective implies that the ease of learning, and thus tech-



Absorp tive Capacity

prospec tive users. For example, personal computers diffusedmore rapidly at the outse t among consumers and firms wh ohad prior experience on mainframes or minicomputers. Like-wise, software engineering practices seem to be adoptedmore readily by programmers with previous Pascal ratherthan Fortran experience because the s tructu re of Pascal more

closely reflects som e of the underlying principles of so ftwareengineering (Smith et al., 198 9). Our argument also suggeststhat an innovation that is fully incorporated in capital equip-ment will diffuse more rapidly than more disembodied inno-vations that require some com plementary expertise on thepart of potential users. This is one of the anticipated benefitsof making computers more "user friendly."

The im portance of absorptive capacity also helps explainsome recent findings regarding firms' cooperative researchventures. First, Link (1987) has observed that cooperative re-search ventures are actually found more typically in industries

that emp loy more mature technologies rather than in indus-tries in which techno logy is moving ahead quickly-as seemsto be suggested by the popular press. Second, it has beenobserved that cooperative ventures that have been initiated topursue 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 sim ple notion that it isimportan t to consider the costs of assimilating and exploitingknow ledge from such ventures provides at least a partial ex-planation for these phenomena. Man y cooperative venturesare initiated in areas in which the cost to access the ou tput ofthe venture is low, or they often gravitate toward such areasover time. Conversely, those wh o are attempting to en-courage cooperative research ventures in quickly advancingfields should recognize that the direct participation in the ven-ture should represen t only a portion of the resources that itwi ll take to benefit from the ven ture. Participating firms alsomust be prepared to invest internally in the absorptive ca-pacity that will permit effective exploitation of the venture'sknowledge output.

CONCLUSION

Our empirical analysis of R&D investment suggested thatfirms are in fact sens itive to the characteristics of the learningenvironm ent in which they operate. Thus, absorptive capacityappears to be part of a -firm 's decision calculus in allocatingresources for innovative activity. D espite these findings, be-cause absorptive capacity is intangible and its bene fits are in-direct, one can have little confidence that the appropriatelevel, to say nothing of the optimal level, of investment in ab-sorptive capacity is reached. Thus, while w e have proposed amodel to explain R&D investment, in which R&D both gen-erates innovation and facilitates learning, the development of

this mod el may ultimately be as valuable for the prescriptiveanalysis of organizational policies as its application may be asa positive model of firm behavior.

An importan t question from a prescriptive perspective is



routine activity when the know ledge domain that the firmwishes to exploit is closely related to its current knowledgebase. When, however, a firm wishes to acquire and useknow ledge that is unrelated to its ongoing activity, then thefirm must dedicate effort exclusively to creating absorptivecapacity (i.e., absorptive capacity is not a byprod uct). In thiscase, 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 tosacrifice current output as we ll as gains from specialization topermit its technical personnel to acquire the requisite breadthof knowledge that would permit absorption of knowledgefrom ne w domains. Thus, while the current discussion ad-dresses key features of organizational structure that deter-mine a firm's absorptive capacity and provides evidence thatinvestment is responsive to the need to develop this capa-bility, more research is necessary to understand the decisionprocesses that determ ine organizations' investments in ab-sorptive capacity.

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You have printed the following article:

Absorptive Capacity: A New Perspective on Learning and Innovation

Wesley M. Cohen; Daniel A. Levinthal

Administrative Science Quarterly, Vol. 35, No. 1, Special Issue: Technology, Organizations, andInnovation. (Mar., 1990), pp. 128-152.

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