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What they know vs. what they do: How acquirers leverage technology acquisitions

Puranam, Phanish; Srikanth, Kannan

Published in:Strategic Management Journal

Publication date:2007

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Citation for pulished version (APA):Puranam, P., & Srikanth, K. (2007). What they know vs. what they do: How acquirers leverage technologyacquisitions. Strategic Management Journal.

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Strategic Management JournalStrat. Mgmt. J., 28: 805–825 (2007)

Published online 3 April 2007 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/smj.608

Received 4 November 2004; Final revision received 11 September 2006

WHAT THEY KNOW VS. WHAT THEY DO: HOWACQUIRERS LEVERAGE TECHNOLOGYACQUISITIONS

PHANISH PURANAM* and KANNAN SRIKANTHLondon Business School, University of London, London, U.K

Existing research suggests that in acquisitions of small technology-based firms by large estab-lished firms post-merger integration both enables and hinders acquirers’ efforts to leveragethe technology of acquired firms. This apparent paradox can be resolved once we account forthe qualitatively distinct ways in which acquirers leverage technology acquisitions. Integrationhelps acquirers use the acquired firm’s existing knowledge as an input to their own innovationprocesses (leveraging what they know), but hinders their reliance on the acquired firm as an inde-pendent source of ongoing innovation (leveraging what they do). We also show that experiencedacquirers are better able to mitigate the disruptive consequences of the loss of autonomy entailedby integration, though we find no evidence that they achieve greater coordination benefits fromintegration. Copyright 2007 John Wiley & Sons, Ltd.

INTRODUCTION

Acquisitions of small technology-based firms arean important source of technological inputs forestablished firms in high-velocity industries(Leonard-Barton, 1995; McEvily, Eisenhardt, andPrescott, 2004; Kale and Puranam, 2004). A grow-ing body of research on such ‘technology acquisi-tions’ points to an underlying paradox: post-mergerintegration both enables and hinders acquirers’efforts to leverage the technology of acquired firms(Birkinshaw, 1999; Chaudhuri and Tabrizi, 1999;Graebner, 2004; Puranam, Singh, and Zollo, 2006;Ranft and Lord, 2002). This is because organiza-tional integration mechanisms can enhance knowl-edge transfer and coordination between acquirer

Keywords: technology acquisitions; post-merger integra-tion; coordination∗ Correspondence to: Phanish Puranam, London BusinessSchool, University of London, Sainsbury 317, Sussex Place,Regent’s Park, London NW1 4SA, U.K.E-mail: [email protected]

and acquired organizations, but can also signif-icantly disrupt organizational processes in theacquired firm due to the reduction in its organiza-tional autonomy (Haspeslagh and Jemison, 1991).In an attempt to understand this paradoxical impactof integration on coordination and autonomy, somescholars have relied on detailed qualitative datato uncover the multiple consequences of post-merger integration. They have also identified inte-gration mechanisms (such as the retention of keyemployees and the creation of channels for richcommunication) and integration strategies (such asintegrating different parts of the acquired com-pany to different degrees) that promote knowl-edge flows and coordination without generatingsignificant disruptive effects through the loss ofautonomy (Graebner, 2004; Ranft and Lord, 2002;Schweizer, 2005).

In this study, we propose an alternative approachto understanding the integration paradox based ondistinguishing two distinct ways in which acquir-ers leverage technology acquisitions. We argue thatwhen acquirers use the acquired firm’s existing

Copyright 2007 John Wiley & Sons, Ltd.

806 P. Puranam and K. Srikanth

knowledge as an input to their own innovationprocesses, they are primarily leveraging what theacquired firm ‘knows.’ In contrast, when acquir-ers rely on the acquired firm as an independentsource of ongoing innovation, they are primarilyleveraging what the acquired firm ‘does.’ We arguethat post-merger integration helps acquirers lever-age what the acquired firm ‘knows’ by promotingcoordination between acquirer and target firm, buthinders their ability to leverage what the acquiredfirm ‘does’ because of the disruptive effects onthe target organization caused by a reduction inautonomy. Thus, we propose that the effect ofpost-merger integration in technology acquisitionsbecomes more transparent and less paradoxicalonce we account for the qualitatively distinct waysin which acquirers can leverage technology acqui-sitions. In doing so, we shift the emphasis fromintegration mechanisms to the impact of integra-tion strategies (broadly defined) on different kindsof post-acquisition outcomes.

We focus on two archetypes of post-acquisitionintegration: structural integration, and its converse,structural separation. These correspond to situa-tions in which the acquired firm is completelyintegrated into the acquirer and loses its dis-tinctive identity as an organizational unit, or itis preserved as a distinct organizational entitywithin the merged firm (Haspeslagh and Jemison,1991). We use patenting data to decompose theacquirer’s innovation efforts after acquisition intoleveraging what the acquired firm knows and whatthe acquired firm does (Ahuja and Katila, 2001;Almeida, 1996; Almeida, Song, and Grant, 2002;Ernst and Vitt, 2000).

We develop theoretical arguments for the impactof structural integration on the mix autonomy andcoordination that characterizes the post-acquisitionorganization, and the consequences for the result-ing mix on different kinds of technology lever-age. Consistent with our predictions, we find thatstructural integration enhances the acquirer’s abil-ity to leverage the existing knowledge base ofacquired firms. However, structural integrationdetracts from the acquirer’s ability to leverage thecapability of the acquired firm for further inven-tion. We also analyze the extent to which acqui-sition experience (Zollo and Singh, 2004) helpsacquirers avoid this stark trade-off between lever-aging knowledge and leveraging capability. Wefind that experienced acquirers are better able tomitigate the disruptive consequences of the loss of

autonomy entailed by integration, though we findno evidence that they achieve greater coordinationbenefits from integration.

The results of this study contribute to our under-standing of technology acquisitions in particularand to post-merger integration in general. How-ever, we also believe that this study has broaderimplications for understanding how firms acquireand integrate knowledge-based inputs from exter-nal sources. The distinction between knowledge(‘what they know’) and capability (‘what they do’)is well established in the strategy literature (Win-ter, 1987). Yet, this theoretically meaningful dis-tinction plays a limited role in the literature ontechnology sourcing relationships such as partner-ships, joint ventures, and acquisitions. Our analysisshows that new insights can be gained by beingprecise about exactly what is being leveraged insuch relationships. In particular, our results sug-gest that organizational arrangements necessary toleverage knowledge may be fundamentally incom-patible with those necessary to leverage capabili-ties, though greater experience may help mitigatethis trade-off to some extent.

TECHNOLOGY ACQUISITIONS: PRIORLITERATURE

Small technology-based firms are attractive toacquirers as sources of technological inputs inregimes of rapid technological change (Arora,Fosfuri, and Gambardella, 2001; Granstrand andSjolander, 1990). Acquiring such firms allowsacquirers to avoid the time-consuming, path-dependent, and uncertain processes of internallyaccumulating technological resources—the knowl-edge and intellectual property that underlie tech-nologies (Dierickx and Cool, 1989; Leonard-Barton, 1995; Steensma and Fairbank, 1999). Inaddition, acquisitions of small technology-basedfirms may also provide acquirers with an opportu-nity to acquire an organizational unit that is capa-ble of producing further innovations. The acquiredunit then functions effectively as a bundle of indi-vidual and organizational capabilities that gener-ates further innovations. Acquirers can ‘graft’ theresulting innovation streams onto their own organi-zation (Huber, 1991; Puranam, 2001), and exploitthe fruits of the acquired firms’ inventive efforts bylinking them to their own complementary assets inmanufacturing, marketing, and distribution (Doz,

Copyright 2007 John Wiley & Sons, Ltd. Strat. Mgmt. J., 28: 805–825 (2007)DOI: 10.1002/smj

What They Know vs. What They Do 807

1988; Teece, 1986; Williamson, 1975, 1985). Themanagement of technology acquisitions is, how-ever, far from simple; although they provide quickaccess to technologies and innovation streams,problems of implementation frequently beset them,and they are prone to high failure rates (Chaudhuriand Tabrizi, 1999; Hagedoorn and Duysters, 2002;Steensma and Corley, 2000).1

The conflicting demands of autonomy and coor-dination are often suggested to underlie imple-mentation difficulties in technology acquisitions(Birkinshaw, 1999; Chaudhuri and Tabrizi, 1999;Graebner, 2004; Haspeslagh and Jemison, 1991;Puranam et al., 2006; Ranft and Lord, 2002).For instance, integration mechanisms identified inthe literature on organization design such as thehomogenization of organizational processes acrossacquirer and acquired firm, the rotation of R&Dpersonnel, and joint product development activi-ties can in principle help acquirers leverage theacquired firm’s technology and innovation capabil-ity through enhanced coordination between them(Galbraith, 1974; Lawrence and Lorsch, 1967;Nadler and Tushman, 1998). However, such mech-anisms may also harm efforts to leverage technol-ogy, because they impinge on the organizationalautonomy of the acquired firm, thereby disrupt-ing existing organizational routines and lower-ing extrinsic and intrinsic motivation (Benner andTushman, 2003; Haspeslagh and Jemison, 1991).Indeed, the few existing large sample studies onthe performance effects of such integration mech-anisms in technology acquisitions report mixedresults (Chakrabarti, Hauschildt, and Suverkrup,1994; Gerpott, 1995; Ranft, 1997), consistent withthe observation that integration enhances coordi-nation at the expense of autonomy.

One approach to understanding the paradoxi-cal nature of post-merger integration in technol-ogy acquisitions has been to rely on fine-grainedqualitative data. Ranft and Lord (2002) build onseven detailed case studies of technology acquisi-tions to induce propositions about integration andperformance. Consistent with the notion of theintegration paradox, they argue that autonomy foracquired firms (in terms of formal administrative

1 A Price Waterhouse Coopers report released in 1999 estimatedthat about 80 percent of technologically motivated acquisitions inthe time period 1994–97 have failed to achieve their objectives.A study by the Hay group of Philadelphia in the same periodfound that as many as 60 percent of such acquisitions sufferfrom severe problems in the post-merger integration stage.

structure and culture) simultaneously preservestacit and socially embedded technologies and capa-bilities, but impedes acquirer’s efforts to leveragethem, because autonomy limits effective coordina-tion. However, rich unstructured communication,in the form of frequent face-to-face interactions,avoids the disruptive consequences of administra-tive and cultural integration while also enablinghigh levels of coordination. Graebner (2004) usescase data on eight technology acquisitions to focuson the role played by leaders of the acquired firmin post-merger integration. She finds that acquiredleaders can moderate the effects of integrationon performance; they may simultaneously enablegreater integration and coordination and mitigateits disruptive consequences stemming from theresulting loss of autonomy due to their superiorknowledge of and influence over the acquired orga-nization. Schweizer (2005) draws on five casestudies of acquisitions of biotechnology companiesby large pharmaceutical companies to argue for thevalue of hybrid integration strategies that integratedifferent parts of the acquired firms value chainto different degrees. He suggests that by providingautonomy to upstream R&D units while integrat-ing downstream non-R&D activities like sales andregulatory approval, acquirers can meet both short-term goals of adding to their pipeline while alsopreserving the target’s capabilities at generatinginnovation for the future.

While qualitative analysis enriches our under-standing of the working of integration mechanismsat a fine-grained level, we believe that an equallyvalid and complementary approach lies in analyz-ing technology leveraging outcomes at a more fine-grained level. To better understand exactly whatacquirers leverage in technology acquisitions, wedraw on the distinction between the knowledge thatunderlies a technology and the capability to pro-duce new technologies. The stock of technologicalknowledge in an acquired firm at the time of acqui-sition includes knowledge embodied in artifactsas well as embedded in the minds of individu-als that pertains to existing technologies (Winter,1987). In contrast, the capability to generate fur-ther innovations is primarily resident in individualand group processes that allow for the recombi-nation of existing knowledge into new knowledge(Kogut and Zander, 1992, 1996). The distinctionbetween knowledge and capability has been exten-sively discussed in both theoretical and empiricalcontributions to the strategy literature (Eisenhardt



and Martin, 2000; Teece, Pisano, and Shuen, 1997;Winter, 1987; Zollo and Winter, 2002).

Prior research on technology acquisitions hasbeen largely agnostic to the distinction betweenknowledge and capability leverage by the acquirer.For instance, Ahuja and Katila (2001) show that,on average, the impact of technologically moti-vated acquisitions on the innovative performanceof the combined firms (measured through patent-ing) is positive, but they do not distinguish betweenpatenting that arises from leveraging the existingknowledge of the acquired firm and from leverag-ing its capabilities for ongoing innovation. Ernstand Vitt (2000) explore the effects of acquisitionon innovativeness, but focus only on the numberand quality of the patents filed post-acquisitionby highly productive (pre-acquisition) inventors.In their sample, acquirers appear to have failedto fully leverage the capabilities for innovationembodied in the key inventors of the acquired firm,but their analysis does not take into account theleveraging of existing knowledge by acquirers asan alternate source of value creation.

Why does the distinction between leveragingexisting knowledge (‘what they know’) vs. capa-bilities for ongoing innovation (‘what they do’)matter in technology acquisitions? In the follow-ing section, we introduce a theoretical frameworkthat suggests that the distinction between existingknowledge and innovative capabilities is importantbecause their leverage requires distinct organiza-tional arrangements.

THEORY AND HYPOTHESES

The organizational antecedents of knowledgeand capability leverage

It is generally accepted that in technology acqui-sitions organizational autonomy minimizes disrup-tion in the target firm, thereby preserving motiva-tion and capacity for ongoing innovative activityby the target firm employees (Birkinshaw 1999;Ranft and Lord, 2002; Graebner, 2004; Schweizer,2005). The additional point we wish to highlight,however, is that the extent of coordination requiredbetween acquiring and acquired units depends onwhat the acquirer wants to leverage from the acqui-sition. When the goal is primarily to leverage theexisting knowledge of the target firm by transfer-ring it to the acquirer’s personnel, than the needfor coordination dominates the need for autonomy.

In contrast, when the primary goal is to keep theacquired employees capable of producing ongo-ing innovation, then the need to preserve auton-omy dominates the need for coordination betweenacquirer and target firm.

We represent these arguments graphically inFigure 1. Points below the diagonal represent anemphasis on autonomy over coordination, whereaspoints above the diagonal represent an emphasison coordination over autonomy. The area belowthe diagonal can therefore be thought of as the‘zone of capability leverage,’ whereas that abovethe diagonal is the ‘zone of knowledge leverage.’We note that the distinction between the zonesis a matter of emphasis—the zone of capabilityleverage also entails some degree of coordinationbetween acquirer and target organization, just asthe zone of knowledge leverage also entails somedegree of organizational autonomy. Put differently,the marginal rate of technical substitution betweencoordination and autonomy is different for capabil-ity and knowledge leverage, though both coordina-tion and autonomy may be complements in eitherkind of leverage.

Our arguments about the distinct organizationalantecedents of knowledge and capability leverageare an elaboration of a more general point firstmade by Haspeslagh and Jemison (1991). Theseauthors argued that acquisition integration strate-gies are conditional on the extent of strategic inter-dependence between acquirer and target, and theneed for organizational autonomy of the targetfirm, and suggested four generic integration strate-gies that arise from crossing these two dimensions.

Organizational Autonomyfor Acquired Unit

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Zone of EffectiveCapability Leverage

Zone of EffectiveKnowledge Leverage

Figure 1. Organizational antecedents of capability andknowledge leverage



Their argument implicitly ascribes a single objec-tive to the acquisition, which determines the levelof interdependence and autonomy. We suggest thatwithin the context of technology acquisitions theremay exist different objectives for the same acqui-sition (i.e., knowledge and capability leverage),which require distinct organizational antecedents.

Structural form, knowledge and capabilityleverage

In acquisitions, the choice between structural inte-gration and its converse, structural separation,is a fundamental choice about the form of thecombined organization (Haspeslagh and Jemison,1991). As a formal design choice concerningthe ‘grouping’ of organizational units, structuralintegration precedes decisions about the use of‘linking’ mechanisms between organizational units(such as the alignment and standardization of pro-cesses and systems, common hierarchical control,cross-unit teams, and integrating managers) bothtemporally and in importance (Galbraith, 1977;Nadler and Tushman, 1998; Thompson, 1967).Scholars who study acquisition implementationdescribe the choice between complete absorptionand preservation of autonomous organizational sta-tus as an important initial decision that shapes fur-ther fine-grained integration actions (Haspeslaghand Jemison, 1991; Pablo, 1994; Ranft and Lord,2002; Zollo and Singh, 2004).

Structural integration enhances the acquirer’sefforts to leverage the technical knowledge embed-ded in the human capital of acquired firm employ-ees. By grouping organizational units togetherwithin administrative boundaries through struc-tural integration, the coordination mechanisms ofprogramming, hierarchy, and feedback can beeffectively used to enable knowledge transfer andcoordination (Galbraith, 1977; March and Simon,1958; Thompson, 1967; Gulati, Lawrence, andPuranam, 2005). For instance, structural integra-tion will typically result in common procedures,common goals, and common authority betweenacquired and acquiring firms’ technical employ-ees, which enhances coordination and knowledgesharing between them (Haspeslagh and Jemison,1991). In addition to the impact on the formalsystems and procedures of the organization, struc-tural form also shapes the emergence of informalorganizational processes that aid knowledge trans-fer, such as the creation of common knowledge,

informal communication channels, and group iden-tity (Camerer and Knez, 1996; Kogut and Zan-der, 1996; Krackhardt, 1990; Moran and Ghoshal,1996; Grant, 1996). These effects may be strength-ened if structural integration also results in colloca-tion. Structural integration may also be conduciveto the leverage of knowledge that is embodied inphysical artifacts. Administrative integration canenable superior access to the knowledge embodiedin documents, equipment, and procedures becauseof enhanced awareness of the existence and loca-tion of these knowledge resources, as well as con-trol over their use (Haspeslagh and Jemison, 1991;Zollo, 1998). We refer collectively to these con-sequences of structural integration as the ‘coor-dination effect’—as cumulatively they serve toenhance coordination between the acquirer and tar-get firm.

Thus, structural integration, through the coordi-nation effect, is expected to create organizationalconditions that enable acquirers to successfullyleverage what the acquired firm knows: the exist-ing knowledge base of the acquired firm. This isbecause knowledge leverage relies primarily onenhanced coordination between acquirer and tar-get firms, which structural integration promotes.We therefore predict:

Hypothesis 1: Structural integration is positivelyassociated with acquirer’s success at leverag-ing the existing knowledge of acquired firms intechnology acquisitions.

In addition to the coordination effect, however,structural integration can impede the acquirer’sefforts to leverage the acquired firm’s capabili-ties for innovation because it ends the autonomousexistence of the target firm. This ‘loss of auton-omy’ effect reduces the capacity of the inventorswithin the target firm to continue doing innovativework in two different ways. First, since integrationimplies a standardization of work practices andprocedures between the target and acquirer firm,the work practices in the target firm must undergochange. Change can cause disruption, independentof any improvements brought about by a new con-figuration of organizational attributes (Amburgey,Kelley, and Barnett, 1993; Hannan and Freeman,1984). Such changes can alter organizational rou-tines within the acquired firm, and in doing socan undermine its innovative capabilities (though,



as we have noted, integration may promote coor-dination between the acquirer and target organi-zations) (Benner and Tushman, 2003; Leonard-Barton, 1992; Ranft and Lord, 2002). These effectsgo beyond the short-term disruption of produc-tivity, to describe a long-term reduction in theinnovative capability of the target firm.

Second, there is the possibility of lowered moti-vation and productivity of inventors in the targetfirm after being structurally integrated. Argumentsfrom agency theory suggest that structural integra-tion weakens the link between reward and effort.Free riding increases as formerly distinct organi-zational units are grouped together, and precludesthe use of sharper incentives (Baker, 2002). Tal-ented employees with hard-to-measure skills andefforts are often attracted to smaller organiza-tions because of their ability to offer high-poweredincentives (Zenger, 1994). Such employees arelikely to become demotivated, and could possiblyeven leave after their firm has been fully inte-grated into the acquirer, which would criticallyundermine the target firm’s innovation capacity(Ernst and Vitt, 2000). Lowered intrinsic moti-vation due to lowered task autonomy followingstructural integration can lead to similar results(Osterloh and Frey, 2000; Wageman, 1995). Theseadverse consequences for motivation can signifi-cantly and permanently damage innovation capa-bilities in acquired firms.

Thus structural integration may enhance thelinkages between the acquired and acquiring unitsthrough the coordination effect, but may preventacquirers from being able to successfully lever-age the capabilities of the acquired firm employ-ees for ongoing innovation, because of the ‘lossof autonomy’ effect (and consequent long-termdisruptions). Put differently, structural integrationmay enhance the acquirer’s ability to leverage whatthe target firm employees ‘know,’ but may impedetheir efforts to leverage what they ‘do.’

Hypothesis 2: Structural integration isnegatively associated with the acquirer’s suc-cess at leveraging the innovative capabilities ofacquired firms in technology acquisitions.

Figure 2 also provides a graphic representationof how structural integration forces a transitionfrom the zone of capability leverage to the zoneof knowledge leverage, by changing the mix ofcoordination and autonomy.

Organizational Autonomyfor Acquired Unit

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IntegrationStructuralSeparation

Figure 2. The impact of structural integration on co-ordination and autonomy

The moderating effects of acquisitionexperience

Experiential learning is a fundamental mecha-nism through which limitedly rational individu-als come to grips with complexity (Cyert andMarch, 1963). The extensive literature on thelearning curve in manufacturing processes (e.g.,Yelle, 1979; Epple, Argote, and Devdas, 1991)has documented this mechanism on shop floors.Recent research suggests its existence in corporateboardrooms as well; experience effects have beenstudied for infrequent, high-impact events suchas contracting, alliances, and acquisitions (Mayerand Argyres, 2004; Kale, Dyer, and Singh, 2001;Zollo and Singh, 2004). It would, however, be fairto say that prior empirical work on the effect ofacquisition experience on acquisition performancehas been inconclusive. Some empirical tests haveshown a positive effect of experience on perfor-mance (Fowler and Schmidt, 1989; Bruton, Oviatt,and White, 1994), while others have shown non-significant effects (Lubatkin, 1987; J.A.C. Baumand A. Ginsberg, unpublished MS, 1997; Zolloand Singh, 2004). A few studies have found a ‘U-shaped’ effect for acquisition experience on per-formance (Haleblian and Finkelstein, 1999), whichother studies have, however, failed to replicate(Hayward, 2002).

One important explanation of these inconclusivefindings is that the value of experience is con-tingent on the integration strategy—not account-ing for the latter (which is typically the case inmost prior studies) may partly explain the absence



of reliable results for experience effects. Popularaccounts of highly successful acquirers such asBanc One (Winter and Szulanski, 2001) and CiscoSystems (Reinhardt, 1999; Goldblatt, 1999) dosuggest that acquisition experience impacts focalacquisition performance at least partly throughbuilding expertise at post-acquisition management.Consistent with this view, Zollo and Reuer (2005)find that firms with greater acquisition experienceare able to derive superior performance when theymanage the focal acquisition with greater levelsof integration. We extend this line of thinking byexamining how acquisition experience may influ-ence the coordination and loss of autonomy effectsgenerated by structural integration.

In analyzing the influence of experience on theeffects of structural integration, it is useful todistinguish between the process by which struc-tural integration is achieved—the set of short-term changes that must be accomplished to createan integrated organization—from the longer-termeffects of the final integrated organizational form.Acquisition experience may undoubtedly be usefulin managing the logistics of the transition to anintegrated organizational form, as this transitioninvolves a complex set of interrelated and time-bound decisions spanning multiple organizationalsub-units (Zollo and Singh, 2004). However, theseshort-term benefits that accrue during the integra-tion period are not our focus. Both the coordinationand loss of autonomy effects we described arethe long-term consequences of a realized struc-turally integrated organizational form. To under-stand how experience influences the coordinationand loss of autonomy effects of structural integra-tion amounts to asking if (and why) these effectsdiffer across firms with different experience lev-els, even when all chose structural integration. Putdifferently, our focus is on how experiential learn-ing can help acquirers strengthen the coordinationeffect or weaken the loss of autonomy effect, ratherthan how they can transition to a structurally inte-grated form more efficiently.

We expect that, through experience, acquirerslearn how to better manage the consequences ofstructural integration. Structural integration is achange to the formal organization design result-ing in changes to reporting relationship, incentives,and operating procedures across acquiring andacquired organizations. However, the effectivenessof these changes across acquirers may differ as afunction of their prior experience with managing

acquisitions. Through experiential learning, acquir-ers may be able to develop competence at lever-aging the new formal organizational arrangementsmore effectively to enhance coordination—thesame standards and procedures may yield superiorcoordination benefits to experienced users (Kaleet al., 2001). Experienced acquirers may also beable to influence the emergent aspects of coor-dination following structural integration—such asthe creation of group norms, identity, and commonknowledge—through more sophisticated interven-tions than those used by relatively inexperiencedacquirers (Stahl and Voigt, 2004). Experience mayalso help to mitigate the disruptive consequencesof structural integration. Repeat acquirers maydevelop capabilities at minimizing the adversemotivational consequences of structural integrationthrough better communication programs, whichexplain the rationale for the changes and mini-mize ambiguity about the future fate of acquiredfirm employees. They may also develop capabili-ties at targeted retention efforts—at identifying thekey individuals whose departure or demotivationwould be most disruptive, as well as at design-ing retention packages that are likely to be mosteffective for such individuals.

In sum, we expect acquisition experience toenhance the effective implementation of structuralintegration by strengthening the coordination effectas well as weakening the disruptive consequencesof the loss of autonomy effect. Hence, we test thefollowing hypotheses:

Hypothesis 3: The relationship between struc-tural integration and knowledge leverage ispositively moderated by acquirer acquisitionexperience.

Hypothesis 4: The relationship between struc-tural integration and capability leverage ispositively moderated by acquirer acquisitionexperience.

METHODS

Sample and data

In keeping with prior literature, we define tech-nology acquisitions as the acquisition of smalltechnology-based firms by large established firmsto gain access to their technology and capa-bilities (Doz, 1988; Graebner, 2004; Granstrand



and Sjolander, 1990; Ranft and Lord, 2002). Wechose acquisitions from the information technol-ogy (computing and communications) and phar-maceutical industries for two reasons: First, thesesectors are frequently profiled in popular publi-cations as being extremely active in acquisitionsaimed at accessing the technology expertise ofsmaller companies (Reinhardt, 1999; Goldblatt,1999); second, both these industries are charac-terized by appropriability regimes that encouragesignificant patenting activity (Cohen, Nelson, andWalsh, 2000; Klevorick et al., 1995; Levin et al.,1987).

Acquiring firms were selected from SIC codes ofmanufacturing industries connected to computing,communications, and pharmaceuticals. We usedthe U.S. Small Business Administration definitionof small businesses (<500 employees) to distin-guish large acquirers from small target firms. Ourcriteria for selecting established acquirers requiredthem to have been listed continuously in COM-PUSTAT between 1988 and 1998 and to have hadmore than 500 employees at every point in timein the study. The choice of the time window wasdriven by the availability of good public informa-tion on acquisitions and ex post performance mea-sures (the data were collected in 2001). Continuedexistence during the study window operationalizedour definition of established firms. We identifiedthe technology acquisitions made by these firmsthrough SDC Platinum’s M&A database. Thesewere acquisitions of independent firms (as opposedto divestments) that had fewer than 500 employeesat the time of the acquisition, and had filed at leastone patent prior to acquisition. Similar criteria andtechniques have been used to identify technology-based entrepreneurial firms and acquisitions inthe literature (Ahuja and Katila, 2001; Ernst andVitt, 2000; Granstrand and Sjolander, 1990). Thesescreening criteria resulted in 99 acquisitions by43 acquirers. Data limitations reduced this to 97acquisitions by 43 acquirers.

Variable definitions and measures

Acquirer’s success at knowledge and capabilityleverage

One of the novel features of this study is our abil-ity to differentiate between an acquirer’s successat leveraging the existing knowledge base of theacquired firm and its capability for further inno-vation based on patent data. Hence, we describe

and theoretically justify our measures for knowl-edge and capability leverage at some length in thissection.

A patent is the grant of a property right to aninventor for an invention. The patents assignedto a firm represent the knowledge that a firm isacknowledged as having created (Jaffe, Trajten-berg, and Henderson, 1993). In this sense, thepatents filed by the acquired firm prior to acqui-sition are a measure of the knowledge stock ofthe acquired firm. The patents filed by acquirersafter the acquisition represent additional stocksof knowledge created through successful inventiveactivity after the acquisition (Ahuja and Lampert,2001; Henderson and Cockburn, 1994). In keep-ing with prior studies, we use a count of patentsfiled after the acquisition by the acquirer–acquiredfirm combination as a measure of the success-ful leveraging of technology acquisitions (Ahujaand Katila, 2001; Ernst and Vitt, 2000). However,we introduce two critical refinements by focus-ing exactly on those patents after acquisition thatinvolve either the leveraging of the acquired firm’spre-existing knowledge, its innovation capabilities,or both, and distinguishing between these cate-gories.

In order to track the successful leverage of theacquired firm’s knowledge base by acquirers, werely on patent citations. A newly patented inven-tion typically builds on the knowledge created bythe firm in the past or by other firms that havepreceded it in that line of inquiry. Several studiesusing patent and citation data argue that citationsare evidence of inter-firm and intra-firm knowl-edge transfer (Almeida et al., 2002; Rosenkopf andAlmeida, 2003; Song, Almeida, and Wu, 2003).This is because a citation implies ‘material influ-ence’ on the current patent and assumes successfultransfer of tacit knowledge, apart from the knowl-edge codified in the patent itself (Almeida andKogut, 1999; Almeida et al., 2002; Jaffe and Tra-jtenberg, 1996; Jaffe, Trajtenberg, and Fogarty,2002; Jaffe et al., 1993; Song et al., 2003). Hence,we propose that post acquisition an acquirer’spatent citing an acquired firm patent is evidence ofinventive effort that leverages the acquired firm’sexisting knowledge codified in the patent and othersecondary sources as well as the tacit componentresident in the acquired firm’s employees.

To track the leverage of innovation capabilities,we rely on patent authorship data. The authors of



a patent are referred to as the ‘inventors.’ Stud-ies of innovation frequently use patent authorshipas a measure of productivity of engineers and sci-entists (Almeida et al., 2002; Song et al., 2003;Ernst and Vitt, 2000; Nerkar, 2003). We arguethat when an inventor previously employed by theacquired firm is the author of a patent filed by theacquirer subsequent to the acquisition, the acquirerfirm has leveraged the innovative capabilities ofthe acquired firm, both as an individual and inconjunction with his or her colleagues. Through aprocess of exhaustive search and matching on sur-names, initials, technology classes and location, wecould construct measures of capability leverage bytracking patents filed by target firm inventors afterthe acquisition.

Figure 3 illustrates how we measure the successof knowledge and capability leverage. We startedby identifying the acquired firm’s active knowl-edge base prior to the acquisition—all patents (andinventors therein) that were filed in the 3 years pre-ceding acquisition. Three years appeared to be areasonable window, given the typically young ageof entrepreneurial firms, as well as the possibil-ity of inventor mobility between firms through jobchanges. We then tracked down new patents filedby the acquirer/acquired firm combination after theacquisition, and linked them back to the activeknowledge base of the acquired firm prior to acqui-sition. All such new post-acquisition patents wereplaced in one of the four cells in Figure 3.

The patents in cell A are a measure of both suc-cessful knowledge leverage and capability lever-age, since these patents both cite a previousacquired firm patent and at least one acquired firminventor is among the authors of these patents. Thenumber of patents in cell B is used as a measureof the success of ‘pure’ knowledge leverage activ-ity. These patents cite patents that were previouslyfiled by the acquired firm, thus acknowledging thatthe innovation embodied in the focal patent utilizesthe knowledge previously created by the acquiredfirm. However, no acquired firm employee is an

author of the focal patent, implying that no signif-icant utilization of acquired firm employee’s inno-vative capabilities occurred in the focal innovation.The patents in cell C are a measure of the suc-cess of ‘pure’ capability leverage. These patentsinclude at least one acquired firm employee asan author, thus acknowledging those employees’contributions to the innovation in the focal patent.However, no acquired firm patent is cited, signi-fying that the focal patent does not build on thecodified knowledge base of the acquired firm rep-resented by its stock of patents. While cells B andC represent ‘pure’ forms of knowledge and capa-bility leverage, it also appears reasonable to countpatents in cell A in both categories—i.e., patentsin cells A and B represent the leverage of existingknowledge, while those in cells A and C representthe leverage of innovation capabilities. Our anal-ysis results in qualitatively identical results witheither measure. We deem post-acquisition patentsthat are not linked by citation or authorship tothe acquired firm’s patents prior to acquisition asirrelevant to the study (cell D). Even if a poten-tial recombination of ideas between acquirers andacquired firms took place that resulted in such apatent, it was minor enough not to warrant eitherauthorship or citation of acquired firm knowledge.

Structural integration

To record the structural integration decision foreach acquisition, we examined the CORPTECHdatabase in the year after the acquisition. CORP-TECH conducts an annual survey of technologyfirms and units within firms that maintain indepen-dent P&L accounts, or distinct status as operatingentities. The continued appearance of the acquiredfirm in the CORPTECH database published in thesecond year after the acquisition was interpreted tomean that structural integration had not been car-ried out. If the firm disappeared from CORPTECH,we interpreted this to mean that structural inte-gration had occurred so that it was no longer

Acquired firm pre-acquisition patents are cited?PATENTS FILED BY ACQUIRERAFTER ACQUISITION IN WHICH Yes

YesCapability andKnowledge Leverage (A)

Only Capabilityleverage (C)Acquired firm inventor(s) are

authors?

No

NoOnly Knowledge leverage(B)

Irrelevant (D)

Figure 3. Measuring leverage of innovation capability and existing knowledge through post-acquisition patenting



traceable as a distinct organizational entity or itmaintained separate P&L accounts. We verified thevalidity of this measurement of structural integra-tion through an examination of press releases andarticles.

Acquirer acquisition experience

While our study window began in 1988, we mea-sured acquisition experience as a count of prioracquisitions conducted by the acquirer from theearliest date for which SDC data are available(1984).

Acquired firm size and age

We obtained the number of employees in theacquired firm, and its age at the time of acqui-sition from CORPTECH and SDC Platinum. Ageand size of acquired firms may influence their inno-vation outcomes and also how they are managed(in terms of organizational autonomy) by acquirers(Ranft and Lord, 2002).

Acquired firm current knowledge base

We measured the size of the current knowledgebase of the acquired firm by the number of patentsgranted to the acquired firm in the past 3 yearsbefore the acquisition. Since these patents form thebasis on which we identify future post-acquisitioninventive activity, their number can be expected tocritically influence observed patenting outcomes.

Acquired firm pre-citations and prior-stock ofpatents

We measured the quality of the acquired firm atthe time of the acquisition in two ways. First, wemeasured the number of citations (‘pre-citations’)the acquired firm’s patents received prior to acqui-sition by all firms (including the acquirer firm).Citations received by a patent are regarded as ameasure of the quality of the patent (Trajtenberg,1990). As a second measure of acquired firm qual-ity, we measured the prior stock of knowledge(‘prior stock’) in the acquired firm by the numberof patents that were granted to the acquired firmfrom its inception until 3 years before acquisition.In conjunction with the variable measuring ‘Cur-rent knowledge base,’ these variables include acomprehensive count of all pre-acquisition patents.

Acquirer R&D intensity

Investment in R&D as a percentage of salesfor acquirers was calculated from data availablefrom COMPUSTAT. R&D investments by acquir-ers could lead to superior innovation outcomes ontheir own, and could also build absorptive capacity,enabling successful utilization of external sourcesof knowledge (Ahuja and Katila, 2001; Cohen andLevinthal, 1990).

Acquirer size

We obtained the number of employees in theacquirer at the time of acquisition from CORP-TECH and SDC Platinum. Acquirer size mayaffect retention of key inventors, since employ-ees with hard-to-measure skills tend to self-selecttoward small companies (Zenger, 1994).

Technological relatedness

We included a measure of technological related-ness between acquired firm and acquirer (Seth,1990; Singh and Montgomery, 1987). Relatednesswas assessed through the extent of overlap betweenthe technology codes assigned to acquired firmsand acquirers by SDC Platinum. The extent ofoverlap was calculated as the number of codescommon to acquirer and acquired firm dividedby the total number of technology codes of theacquired firm.

Time

Our sample consists of acquisitions that occurredin a 10-year time window between 1989 and 1998,in which an acquisition could have happened at anytime. We measure patenting after acquisition fromthe time of acquisition until 2002. Since patentsaccumulate over the years after acquisition, wecontrol for time elapsed after acquisition until theend of our observation period.

Model specification and econometric issues

Since our dependent variables are counts that takeon non-negative integer values, use of the Poissonmodel is indicated (Hausman, Hall, and Griliches,1984; Henderson and Cockburn, 1994). This modelassumes that the number of patents filed by a firmin any given year, or the number of acquired firm



inventors who appear on patents, is a random vari-able that is approximated via a Poisson process, inwhich the mean is equal to the dispersion of thedata. This implies that the probability of obtainingq counts of patents or inventors in a particular yearis given by

Pr(y = q) = λqe−λ

q!(1)

where λ is the expected value (and the variance)of the random variable q. Poisson regressionsestimate this parameter in log-linear models of theform

log(λ) = β ′x (2)

using the method of maximum likelihood. Sincethe Poisson process models counts per unit time(year), and our data contain inventions accumu-lated over several years after acquisition, in ourestimation we control for exposure time: the timeperiod over which patenting is observed.

Our data display overdispersion (the variance isgreater than the mean), thus violating the Poissondistribution assumption. However, Poisson regres-sions have the appealing property that whether ornot the distributional assumptions are met, the esti-mates of β will be consistent and asymptoticallynormal (Wooldridge, 2000: Ch. 17). Therefore wereport heteroskedastic-consistent robust standarderrors for coefficients estimated through Poissonmodels, as these provide consistent estimates forthe standard errors even under misspecification ofthe distribution (Cameron and Trivedi, 1998; Halland Ziedonis, 2001).

In our setting, we believe that unobserved stablefeatures of acquirers are an important aspect to betaken into account. Differences in terms of post-acquisition inventive activity could potentially beattributed to stable acquirer features such as supe-rior routines and incentive mechanisms, manage-ment methods, and better acquired firm selectioncapabilities. With multiple acquisitions observedfor each acquirer, it is possible to control for suchstable acquirer features. With multiple acquisitionsper acquirer, Equation 2 becomes modified to

log(λit ) = β ′xit + αi (3)

where the α term captures acquirer level het-erogeneity. Our data reject the hypothesis that

the α are all zero. We can therefore estimateEquation 3 either via random or conditional fixedeffects (Hausman et al., 1984). In our data, theHausman test rejects the null hypothesis of ran-dom effects for some of the models; we report themore conservative conditional fixed-effects results,and compare these results to the random-effectsmodel in the robustness analyses (Wooldridge,2001).

RESULTS

Descriptive statistics

The descriptive statistics for our data are displayedin Table 1. There is considerable variance on thekey acquirer characteristics of size, acquisitionexperience and R&D intensity, and target charac-teristics such as age, size, quality, and previouspatenting behavior. Post acquisition, about 40 per-cent of the target firms were structurally integrated.In about 44 percent of the acquisitions no patentingactivity from either knowledge or capability lever-age was observed at the end of the observationperiod.

Examining the correlations displayed in Table 2,we note that there is only a small (ρ = 0.27)correlation between the measures of the success ofknowledge leverage and capability leverage. Thissuggests that these measures are indeed capturingdifferent conceptual entities. We also note thatcorrelations between independent variables do notsuggest any obvious concerns about collinearity.

Hypothesis testing

The fixed-effects Poisson regression estimates forthe effect of structural integration on differentinnovation activities are presented in Table 3. Inthis table, the controls were entered first (Model 1a,b), followed by structural integration (Model 2a, b)and the interaction term with experience (Model3a, b). In this table, the measure of knowledgeleverage includes all patents in which a target firminventor appears as an author (cells A and B inFigure 3), while capability leverage includes allpatents that cite the target firm’s pre-acquisitionpatents (cells A and C in Figure 3).

In Hypothesis 1 we predicted a positive rela-tionship between structural integration and theacquirer’s success at leveraging existing knowl-edge from the acquired firm. From Model 2a in



Table 1. Descriptive statistics

Variables Measurement Obs. Mean S.D. Min. Max.

Structural integration Dummy coded 1 if structurally integrated 97 0.37 0.48 0 1Acquirer size Log of acquirer sales 97 6.41 2.51 2.01 10.67Acquirer R&D intensity

(%)Acquirer R&D budget as a fraction of

acquirer sales97 11.03 5.19 0 33.3

Acquirer acquisitionexperience

Number of firms the acquirer had boughtprior to focal acquisition

97 6.88 6.17 0 26

Acquirer employees Number of employees in acquirer at time ofacquisition

97 37,252 40,573 748 156,373

Technology relatedness Normalized measure of the number of sharedtechnology codes

97 0.31 0.41 0 1

Acquired firm age Number of years from founding untilacquisition

97 11.67 11.12 0 88

Acquired firm size Number of target employees at time ofacquisition

97 132.2 110.7 3 500

Acquired firmpre-citations

Number of citations received by targetpatents prior to acquisition

97 9.5 19.4 0 103

Acquired firm priorstock of patents

Number of patents filed by target until3 years prior to acquisition

97 9.8 21.9 0 182

Acquired firm currentinnovativeness

Number of patents filed by target in the3 years prior to acquisition

97 4.9 6.5 1 47

Capability leverage Patents filed by acquirer or target afteracquisition in which at least one targetinventor is an author

97 2.9 5.3 0 34

Knowledge leverage Patents filed by acquirer or target afteracquisition in which at least one targetpatent is cited

97 3.1 6.4 0 38

Table 3 we note that the coefficient for struc-tural integration is positive and significant (p <

0.10). Hence, we find support for Hypothesis 1. InHypothesis 2 we predicted a negative relationshipbetween structural integration and the acquirer’ssuccess at leveraging the innovation capabilities ofthe acquired firm. From Model 2b in Table 3 wefind a negative and significant (p < 0.05) coeffi-cient for structural integration, supporting Hypoth-esis 2.

In Hypothesis 3 we predicted that acquisitionexperience would positively moderate the effect ofstructural integration on knowledge leverage. FromModel 3a in Table 3 we see that the coefficientfor the interaction term is negative but not signifi-cant. We also conducted a joint test of significancefor structural integration and the interaction termto assess whether collinearity between these termswas suppressing a significant effect. However, wefound no evidence for this as the coefficients arenot jointly significant (χ 2(2) = 3.48, p = 0.17).Hence, Hypothesis 3 is not supported. In Hypoth-esis 4 we predicted that acquisition experiencewill positively moderate the effect of structuralintegration on capability leverage. From Model

3b in Table 3 we see that the interaction termhas the expected positive sign and is significant(p < 0.10). Hence, we find support for Hypothe-sis 4.

The results on the control variables empha-size the conclusion that knowledge and capabil-ity leverage have distinct antecedents. Knowledgeleverage is enhanced by the quality of the acquiredfirm at the time of acquisition, as measured bythe stock of accumulated patents granted prior to3 years before acquisition. Capability leverage, onthe other hand, is enhanced not by the stock ofaccumulated knowledge but by the extent to whichthe target firm is active in patenting prior to theacquisition. Capability leverage is also diminishedby increasing target size, which is consistent withprior work on scale diseconomies in R&D (Zenger,1994).

Robustness checks

A number of robustness checks lend confidenceabout the basic validity of our results. A basicpremise in our argument is that the coordinationand autonomy effects are temporally stable. Thus,



Tabl

e2.

Cor

rela

tion

tabl

e

12

34

56

78

910

1113

14

1St

ruct

ural

inte

grat

ion

1.00

2A

cqui

rer

size

0.05

1.00

3A

cqui

rer

R&

Din

tens

ity−0

.11

0.01

1.00

4A

cqui

rer

empl

oyee

s−0

.07

0.20

∗∗−0

.16

1.00

5A

cqui

rer

acqu

isiti

onex

peri

ence

0.15

0.22

∗∗0.

28∗∗

∗0.

101.

006

Tech

nolo

gyre

late

dnes

s−0

.01

−0.0

50.

080.

120.

151.

007

Acq

uire

dfir

mag

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03−0

.18∗

−0.1

30.

05−0

.13

−0.1

11.

008

Acq

uire

dfir

msi

ze0.

020.

00−0

.12

−0.0

1−0

.13

0.12

0.26

∗∗∗

1.00

9A

cqui

red

firm

pre-

cita

tions

0.14

0.02

0.35

∗∗∗

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00.

20∗∗

0.27

−0.0

80.

131.

0010

Acq

uire

dfir

mcu

rren

tin

nova

tiven

ess

−0.1

1−0

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0.27

∗∗∗

0.06

0.00

0.15

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0.16

0.45

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1.00

11A

cqui

red

firm

prio

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ock

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080.

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70.

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0.15

0.03

0.40

∗∗∗

1.00

12C

apab

ility

leve

rage

−0.1

9∗−0

.23∗∗

0.31

∗∗∗

0.02

0.00

0.06

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.13

0.02

0.34

∗∗∗

0.22

∗∗1.

0013

Kno

wle

dge

leve

rage

−0.0

70.

090.

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0.24

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10−0

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10.

30∗∗

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060.

040.

27∗∗

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00

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<0.

01;

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05;

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<0.

1



Table 3. Impact of structural integration on knowledge leverage: Poisson fixed-effects models with robust standarderrors

Knowledge leverage Capability leverage

Model1a

Model2a

Model3a

Model1b

Model2b

Model3b

Acquirer acquisition experience −0.05 −0.08 −0.02 −0.01 −0.001 −0.05(0.11) (0.11) (0.14) (0.05) (0.04) (0.06)

Structural integration 0.57∗ 1.37∗ −0.53∗∗ −2.29∗∗

(0.35) (0.81) (0.22) (1.08)Acquisition experience × Structural −0.07 0.13∗

integration (0.06) (0.07)Acquirer size −0.11 −0.14 −0.26 0.02 0.04 0.02

(0.46) (0.42) (0.44) (0.29) (0.30) (0.29)Acquirer R&D intensity 0.01 0.02 0.01 0.08 0.05 0.04

(0.1) (0.11) (0.11) (0.08) (0.07) (0.07)Acquirer number of employees −8.4 e-6 1.6 e-5 −2.5 e-5 4.2 e-6 8.5 e-6 1.4 e-5

(3.8 e-5) (3.5 e-5) (3.8 e-5) (2.3 e-5) (2.4 e-5) (2.4 e-5)Technological overlap 0.24 0.27 0.39 0.44 0.45 0.49

(0.48) (0.53) (0.55) (0.5) (0.49) (0.62)Acquired firm age −0.08∗ −0.07∗∗ −0.09∗∗ −0.01 −0.006 −0.008

(0.04) (0.03) (0.04) (0.02) (0.02) (0.02)Acquired firm number of employees −0.001 −0.002 −0.002 −0.003 −0.004∗ −0.005

(0.003) (0.003) (0.003) (0.002) (0.002) (0.003)Acquired firm pre-citations 0.02∗∗∗ 0.02∗∗∗ 0.02∗∗ −0.002 −4.2 e-4 0.007

(0.004) (0.005) (0.007) (0.007) (0.005) (0.008)Acquired firm current innovativeness 0.08 0.09 0.10 0.07∗∗∗ 0.06∗∗∗ 0.04∗

(0.08) (0.08) (0.07) (0.02) (0.02) (0.02)Acquired firm prior stock of patents 0.03 0.03 0.03 −0.001 −0.002 −5.5e-4

(0.03) (0.02) (0.02) (0.01) (0.01) (0.01)Time Exposure Exposure Exposure Exposure Exposure ExposureN 97 97 97 97 97 97LL −109.9 −106.3 −103.8 −124.03 −120 −113.8Wald χ 2 115.0∗∗∗ 111.1∗∗∗ 117.2∗∗∗ 74.0∗∗∗ 77.7∗∗∗ 80∗∗∗

∗∗∗ p < 0.01; ∗∗ p < 0.05; ∗ p < 0.1

we assume that structural integration moves theconfiguration of organizational attributes towardsan emphasis on coordination over autonomy(Figure 2), but assume away the possibility thatover time the disruption effects may get weakeror the coordination effects could get stronger. Ifthis assumption is invalid, we could well findthat over time the effects we found may weakenor disappear. To assess how stable the effectsof structural integration are over time, we re-estimated the main-effects models for the impact ofstructural integration in Table 3 with an interactionterm between structural integration and the timeperiod over which we observed patenting activityfor each firm. If over time the loss of autonomyor coordination effects weakened/strengthenedsignificantly, then we would expect significantinteraction terms. We find that the interactionterm between time and structural integration is not

significant for capability leverage, but positive andsignificant for knowledge leverage.

Thus we conclude that there is no evidencethat the disruption effects arising from the loss ofautonomy following structural integration weakensignificantly over time. This is quite consistentwith our view of the loss of autonomy effect asa long-term effect due to the demotivation of keyinventors and the disruption of productive routinesthat tie them to each other, rather than a shortperiod of lowered productivity after the acquisi-tion. In contrast, we find that the effect of struc-tural integration on knowledge leverage strength-ens over time, suggesting that the coordinationeffect becomes even stronger over time, leadingto even greater knowledge leverage in later peri-ods than would be apparent from examining theaverage effect of structural integration over theentire time period (as we did in testing Hypothesis



1). Thus accounting for time-varying effects ofstructural integration does not alter our basicresults and conclusions.2

We reported the results for the fixed-effectsmodels as the Hausman test suggested that theywere preferable to a random-effects model in somecases; however, despite the Hausman test indicat-ing differences in the vector of covariates acrossthe fixed- and random-effects models, we foundthat the coefficients of interest to us (i.e., thosetested in Hypotheses 1–4) are in fact qualitativelyidentical in the fixed- and random-effects mod-els, and are estimated more precisely in the latter.This lends additional confidence to our conclu-sions.

We also re-estimated our models with a num-ber of alternative measures. First, we includedalternative measures for target quality includingnumber of citations obtained by the target firm’spatents from firms other than the acquirer priorto acquisition, the number of citations receivedfrom the acquirer prior to acquisition, and thedollar value per employee paid by the acquirerfor the target. We also used measures of capabil-ity and knowledge leverage that restricted patentcounts to only ‘pure’ capability and knowledgeleverage. In Figure 3 this corresponds to excludingpatents that indicated both knowledge and capa-bility leverage (cell A) in measures of knowl-edge leverage, for instance. We obtain qualita-tively similar results from these specifications.Second, we also conducted a number of checksto identify outliers and influence points, includ-ing constructing ‘bootstrapped’ standard errorsand coefficients and examining residuals in lin-ear versions of our specifications. We could notidentify any individual observations that signif-icantly altered the results. Third, by estimatingfixed effects for acquirers, we are implicitly con-trolling for industry differences between IT andpharmaceuticals. However, we also assessed theextent to which our results vary across thesetwo industries. We therefore constructed interac-tion terms with all variables in the model and adummy variable for industry. We find that thereis no impact of industry on the effect of struc-tural integration on knowledge or capability lever-age.

2 We thank an anonymous referee for suggesting this analysis.

DISCUSSION

The results of this study indicate that acquirers canleverage technology acquisitions in two qualita-tively distinct ways; they may leverage the exist-ing knowledge of the acquired firm (‘what theyknow’) and/or its capabilities for ongoing inno-vation (‘what they do’). Structural integration hasa negative impact on the acquirer’s attempts toleverage innovative capabilities, but has a positiveimpact on the leveraging of existing knowledge.Our results are consistent with the theory we pro-pose that these two leverage processes have dis-tinct organizational antecedents—the optimal mixof coordination and autonomy is distinct in the twocases, and structural integration shifts the balancein favor of coordination over autonomy. We alsofind that the acquirer’s acquisition experience alle-viates the adverse consequences of structural inte-gration on the acquirer’s efforts to leverage inno-vation capabilities, but do not find any evidencethat prior experience enhances efforts to leverageknowledge. This suggests that in terms of long-term performance consequences (rather than effi-ciency of the integration process itself) acquisitionexperience may primarily be useful in mitigatingthe loss of autonomy effect rather than strengthen-ing the coordination effect. We discuss the impli-cations of our results for research and practice, aswell as limitations and scope for further research.

Implications for research and practice

This study helps to shed new light on the inte-gration paradox in technology acquisitions. Ratherthan focusing on the conflicting effects on all lever-aging activities, we show that structural integra-tion has different effects on qualitatively differ-ent forms of leveraging activities. These findingssuggest several implications for research on tech-nology acquisitions in particular, and technologysourcing relationships in general.

First, this study suggests that organizationalarrangements necessary to leverage existing knowl-edge may be incompatible with those necessaryto leverage capabilities for ongoing innovation.Acquisition management practices that encourageinnovation outcomes from capability leverage arelikely to do so at the cost of reduced innovationfrom knowledge leverage, and vice versa. Thisargument is particularly clear in the case of struc-tural integration, which is essentially a discrete



choice about post-acquisition organizational form.While other formal coordination mechanisms suchas process overlays, compensation systems, andthe standardization of procedures are not as dis-crete as structural integration choices, the exis-tence of complementarities between elements ofan organizational form creates natural limits tothe extent to which discreteness in organizationalalternatives can be overcome (Gersick, 1991; Ghe-mawat and Costa, 1993; Milgrom and Roberts,1990; Nickerson and Zenger, 2002; Williamson,1991). A related implication is that post-acquisi-tion innovative activity is likely to be dominatedby whichever mode of technology leverage thatthe post-acquisition organizational form supports:observed inventive activity will correspond primar-ily to capability leverage or knowledge leverage,but is unlikely to be characterized by balanced lev-els of both activities. In our sample, we find someevidence in favor of this argument. We performedt-tests with the null hypothesis that the numberof patents from capability leverage and knowl-edge leverage are the same in each acquisition.The t-test shows that the number of patents corre-sponding to knowledge and capability leverage aredifferent from each other on average (p < 0.05).

Our theory and analysis reflect to some extentthe well-known trade-off between exploration andexploitation in organizational learning (March,1991). From the acquired firm’s perspective,knowledge leverage may be seen primarily as anexploitation of its current knowledge base, whereascapability leverage involves exploration of newopportunities through ongoing innovation. The dif-ferent organizational antecedents of explorationand exploitation, and the difficulties of reconcil-ing them, have been recognized in other con-texts (Benner and Tushman, 2003; Ghemawat andCosta, 1993; Siggelkow and Levinthal, 2003). Ouranalysis can be seen as linking post-merger inte-gration strategies to specific forms of exploration(capability leverage) and exploitation (knowledgeleverage). This interpretation treats the differencebetween exploration and exploitation primarily interms of the degree to which the use of existingknowledge vs. the pursuit of ongoing innovation isemphasized. However, an alternative perspectiveis also feasible, if exploration and exploitation areviewed primarily in terms of local vs. more distantsearch in the opportunity space. Both knowledgeand capability leverage can be seen as exploratorysearch from the perspective of the acquirer, as

either form of leverage may generate innovationsthat are distinct from the acquirer’s existing tech-nological trajectory (Dosi, 1982, 1988; Nelson andWinter, 1982). Conversely, either may be exploita-tive if the technology trajectories of the two firmsare related. Thus, from the acquirer perspective,knowledge and capability leverage do not neces-sarily correspond to exploitation and exploration,as either form of leverage is consistent with bothlocal and distant technological search (Rosenkopfand Almeida, 2003).

Second, our findings also indicate the importantand different roles played by acquisition experi-ence in influencing the coordination and loss ofautonomy effect. Our results suggest that expe-rience had a positive moderation effect on thelink between integration and capability leverage,implying that acquirers with experience can mit-igate the disruptive consequences of the loss ofautonomy resulting from structural integration.However, we found no moderation effects forknowledge leverage. This suggests that the valueof experience in acquisitions arises primarily frommanaging the loss of autonomy effect, ratherthan enhancing the coordination effect. This alsosuggests a broader insight—experience effectsmay be most significant in acquisitions whereautonomy preservation is critical but some degreeof integration is unavoidable (Zollo and Singh,2004).

Third, this study points to the importance ofbeing precise about exactly what is being lever-aged in inter-firm technology sourcing relation-ships. Leveraging existing knowledge may involveknowledgeable individuals teaching others ‘whatthey know’—through a process of knowledgetransfer or capability replication (Szulanski, 1996).However, leveraging the innovative capabilities ofindividuals and teams may involve the utiliza-tion of their creative outputs as they continue todo ‘what they do’ rather than having them teachtheir creative skills to others. Huber (1991) andPuranam (2001) make similar observations aboutthe benefits of transferring knowledge vs. ‘graft-ing’ on knowledgeable employees. Our analysisextends these theoretical observations by show-ing how the success of these different leveragemechanisms can be measured (through citationsand authorship patterns in patenting), and alsodeveloping and testing a theoretical frameworkabout their distinct and incompatible organiza-tional antecedents. A related implication of our



results for researchers is that they must specifyinnovation performance more accurately in empir-ical work on technology acquisitions, as lumpingtogether inventive activity from capability leverageand knowledge leverage may not yield any effectsfor organizational variables like structural integra-tion. The absence of effects may in fact disguisetwo offsetting effects.

Fourth, the findings of this study also draw man-agerial attention to an important choice: managersshould form clear ideas regarding whether thepotential for future innovation from an acquisitionis likely to be derived from leveraging capabilityor knowledge. Based on this decision, managersshould plan their acquisition integration strategiesaccordingly to maximize the innovation returnsfrom acquisitions.

Limitations and scope for further research

Several limitations of this study are worth noting.Patents have both significant strengths and weak-nesses as measures of innovative outputs, whichhave been extensively discussed in prior litera-ture (Caballero and Jaffe, 2002; Jaffe et al., 2002).Clearly, our study suffers from the same weak-nesses and benefits from the same strengths asother studies that rely on patenting data. Of con-cern is the specific critique that citations are a noisymeasure of knowledge flow, since they could alsobe used to delineate the rights of the present patentfrom that of other closely related patents. Cita-tions could also be introduced by patent examiners,rather than by the inventors (Trajtenberg, 1990). Inour setting, we expect the ‘noisiness’ of citations isof less concern because both the citing patent andthe cited patent belong to the same legal entity.Hence, it is more likely that the firm would beaware of the existence of relevant prior art.

Using patent data limits our ability to draw anyconclusions about the eventual commercial suc-cess of innovations arising from acquisitions. Wehave therefore been careful to draw inferences onlyabout the success of acquirers at leveraging theexisting knowledge and capabilities of acquiredfirms, and have not discussed their success at inno-vation per se. Although patenting is an imperfectindicator of innovation in general, it does repre-sent a fairly reliable indicator of efforts at inno-vation (Hausman et al., 1984) in industries withstrong appropriability regimes (Klevorick et al.,1995; Teece, 1986). As regards the two industries

that comprise our sampling frame, there is strongconsensus in the literature that patenting is an indi-cator of innovations in the IT hardware and phar-maceutical industries (Cohen et al., 2000). Futurestudies could utilize alternate measures of inno-vation especially when generalizing to industrieswithout strong intellectual property regimes, wherepatents may not be a meaningful indicator of inno-vation.

Our analysis has also been confined to study-ing the effect of structural integration on innova-tion outcomes conditional on acquisition, ratherthan the effect of acquisition on innovation out-comes (e.g., Ahuja and Katila, 2001). In futurestudies, it may be useful to analyze the effect ofacquisition on the continued productivity of inven-tors or in the utilization of their knowledge ininnovation activity (e.g., Ernst and Vitt, 2000).Further, we have focused on only one aspect ofpost-acquisition structural form—structural inte-gration—whose discrete nature throws the trade-off between knowledge and capability leverageinto sharp relief. We have argued that additionalcoordination mechanisms like process overlaysand linking mechanisms primarily elaborate andreinforce the fundamental decision about post-acquisition organizational structure (Haspeslaghand Jemison, 1991). Nonetheless, we believe thatfurther research that explores the limits of usingprocess overlays and other formal coordinationmechanisms to compensate for the discrete natureof organizational grouping choices in acquisitionswill prove valuable in understanding the issues inthis study.

Finally, our analysis stops short of leading toconclusions about causation. While we are ableto control for unobserved features of acquirers(through fixed effects) that may induce spuri-ous correlations between structural integration andinnovation outcomes, we cannot econometricallyrule out the possibility that other unobserved fea-tures of the transaction, such as the culture, struc-ture, or technological properties of the acquiredfirm may have influenced both structural inte-gration and innovation outcomes in a mannerthat spuriously induces a correlation between thetwo.3 However, we feel confident about the basic

3 Accounting for such unobservable transaction features throughHeckman-style endogeneity corrections requires the availabilityof a good instrumental variable; we could not find a satisfactoryone in our data. In addition, this approach is computationally



validity of our results for two reasons. First, webelieve we have controlled for plausible alter-nate explanations through control variables for theacquired firm’s age, size, pre-acquisition techno-logical quality, technological activity, and sim-ilarity to acquirer. We believe these variablesshould be correlated with important features ofacquired firms that we cannot directly observe,such as culture, leadership, structure, and tech-nological properties. Second, we are comfortedthat our hypotheses are supported across differ-ent model specifications with different depen-dent variables (knowledge and capability lever-age) and with moderation effects. It seems dif-ficult to suggest a plausible alternative expla-nation that accounts coherently for all of theseeffects.

CONCLUSION

Scholars interested in the specific mechanismsthrough which firms use acquired knowledge andcapabilities have often relied on fieldwork andqualitative data (Haspeslagh and Jemison, 1991;Leonard-Barton, 1992, 1995; Ranft and Lord,2002; Schweizer, 2005). While the richness ofcase data is undisputed, they typically play a lim-ited role in testing rather than inducing theoreticalarguments. Patenting activity provides a reliableif not rich record of the knowledge flows charac-terizing inventive activity, a feature that has beenextensively used in studies on inter-firm technol-ogy transfer (Almeida and Kogut, 1999; Almeidaet al., 2002). However, studies based on patentdata have typically been agnostic to the organi-zational antecedents of observed patenting behav-ior. Our study combines the analysis of inventiveactivity and its organizational antecedents. We thuscontribute to the literature on how firms acquire,use, and generate new knowledge by refining andcomplementing existing theory derived from case-based inductive research as well as patent-basedanalysis of inter-firm knowledge transfer (Almeidaand Kogut, 1999; Leonard-Barton, 1985; Ranftand Lord, 2002; Song et al., 2003). By clari-fying the conceptual and empirical distinctionsbetween leveraging knowledge (‘what they know’)and leveraging capabilities (‘what they do’), we

very complicated for exponential models such as Poisson regres-sions (Wooldridge, 2001).

hope to have helped refine future theorizing andempirical analysis of these important phenom-ena.

ACKNOWLEDGEMENTS

We acknowledge funding from the Mack Cen-tre for Technological Innovation at the WhartonSchool, and a Research and Materials Develop-ment grant and support from the Institute of Tech-nology from the London Business School. We arealso grateful for useful suggestions over the courseof this project from Asli Arikan, Harry Barkema,Julian Birkinshaw, Sea-Jin Chang, Dave Jemison,Sendil Ethiraj, Philippe Haspeslagh,Rosemarie Ham-Ziedonis, Anita McGahan,Srikanth Parachuri, Freek Vermeulen, and Den-nis Yao.

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