Cui Bono? The Selective Revealing of Knowledge and Its Implications for Innovative Activity

CUI BONO? THE SELECTIVE REVEALING OFKNOWLEDGE AND ITS IMPLICATIONS

FOR INNOVATIVE ACTIVITY

OLIVER ALEXYTechnische Universität München

GERARD GEORGEAMMON J. SALTER

Imperial College London

Current theories of how organizations harness knowledge for innovative activitycannot convincingly explain emergent practices whereby firms selectively revealknowledge to their advantage. We conceive of selective revealing as a strategicmechanism to reshape the collaborative behavior of other actors in a firm’s innovationecosystem. We propose that selective revealing may provide an effective alternativeto known collaboration mechanisms, particularly under conditions of high partneruncertainty, high coordination costs, and unwilling potential collaborators. We spec-ify conditions when firms are more likely to reveal knowledge and highlight someboundary conditions for competitor reciprocity. We elaborate on strategies that allowfirms to exhibit managerial agency in selective revealing and discuss selectiverevealing’s implications for theories of organization and open innovation and formanagement practice.

He who receives an idea from me, receives in-struction himself without lessening mine; as hewho lights his taper at mine, receives light with-out darkening me (Thomas Jefferson, letter toIsaac McPherson, August 13, 1813; http://press-pubs.uchicago.edu/founders/documents/a1_8_8s12.html).

Control of valuable resources is one of themost potent sources of competitive advantageorganizations can possess (e.g., Barney, 1991;Pfeffer & Salancik, 1978; Teece, 1986). Organiza-

tions that control resources enjoy higher rates ofsurvival and exert influence over other organi-zations in need of those resources. Weaker or-ganizations, in turn, strive to get access to thoseresources or substitute for them by applyingstrategies such as partnerships, alliances, jointventures, mergers and acquisitions, board inter-locks, or political action (e.g., Bresser & Harl,1986; Hillman & Hitt, 1999; Kale & Singh, 2009;Oliver, 1990; Podolny & Page, 1998). Accordingly,organization theory predicts that firms strive tobe autonomous whenever they can and engagein collaboration whenever they must in order toaccess resources and overcome environmentaluncertainty (Cook, 1977; Galaskiewicz, 1985).

These considerations are critical to innovativeorganizations for which knowledge representsthe most essential resource (e.g., Grant, 1996;Kogut & Zander, 1992, 1996). Such organizationsmay hold two types of knowledge related to in-novation activity (von Hippel, 1988): (1) solution-related knowledge needed to develop technolo-gies and products and (2) problem-relatedknowledge about needs they will face in currentor future markets. In turn, firms in control ofproblem- or solution-related knowledge shouldbe able to generate higher rents from innova-

This article has greatly benefited from the guidance ofAdelaide King and three reviewers. Gerard George grate-fully acknowledges the Professorial Fellowship support ofthe U.K.’s Economic and Social Research Council (RES-051-27-0321). Oliver Alexy and Ammon Salter acknowledge thesupport of the U.K. Innovation Research Centre (RES/G028591/1)—which is sponsored by the Economic and SocialResearch Council; the National Endowment for Science,Technology and the Arts; the U.K. Department for Business,Innovation and Skills; and the Technology Strategy Board—and the support of the Engineering and Physical SciencesResearch Council (GR/R95371/01). We further thank AprilFranco, Keld Laursen, Patrick Llerena, Bill McEvily, LarissaRabbiosi, Dmitry Sharapov, and Anne ter Wal, as well asparticipants at the Academy of Management annual meet-ing, the CBS Conference on Absorptive Capacity, the Con-ference on Knowledge in Organizations, the DRUID Confer-ence, and the research seminar at the University of SouthernDenmark, for their valuable feedback.

� Academy of Management Review2013, Vol. 38, No. 2, 270–291.http://dx.doi.org/10.5465/amr.2011.0193

270Copyright of the Academy of Management, all rights reserved. Contents may not be copied, emailed, posted to a listserv, or otherwise transmitted without the copyrightholder’s express written permission. Users may print, download, or email articles for individual use only.

tion. Thus, they will also be encouraged to pro-tect this knowledge from other organizationsthrough a series of appropriation mechanismsto sustain their favorable competitive position(e.g., Teece, 1986; Winter, 1987). Accordingly, in-novative firms are advised to maximize incom-ing while minimizing outgoing knowledge spill-overs (Cassiman & Veugelers, 2002).

Recent empirical anomalies appear to chal-lenge this view. For example, Yang, Phelps, andSteensma (2010) found that coincidental, invol-untary spillovers of knowledge by a firm mayactually increase the possibility it will receivevaluable knowledge in the future. Other studiesgo even further, indicating the value-accretivepotential of strategies in which knowledge ispurposefully and strategically disclosed to theenvironment. Following such “selective reveal-ing” strategies (Harhoff, Henkel, & von Hippel,2003; Henkel, 2006b), firms consciously select in-ternally developed knowledge and make it ac-cessible to outside actors, often for free andwithout contractual requirements. “Open sourcesoftware” (von Hippel & von Krogh, 2003), wherecompanies disclose the source code of their soft-ware products to the general public, who arefurther allowed to freely modify and indepen-dently redistribute the software, represents aparticularly salient recent example. Notably, theuse of selective revealing in the nineteenth cen-tury has already been documented. For exam-ple, Allen (1983) discussed information sharingamong competitors in the English blast furnacesindustry after 1850. While the application of se-lective revealing strategies today remains rela-tively rare (CED, 2006), the rising prominence ofselective revealing across industries poses achallenge for theories of innovation. In particu-lar, explanations of why firms choose to enactthis behavior, how it may be value accretive,under what boundary conditions this behaviormay flourish, and how it can be embedded intofirms’ innovation strategies are scarce. Whereasrecent advances acknowledge the deterrencepotential of selective revealing (Clarkson & Toh,2010; Polidoro & Toh, 2011), there is limited re-search on selective revealing’s collaborative as-pects (Fosfuri & Rønde, 2004; Henkel, 2006a).

At the heart of our argument lies a novel ap-preciation of selective revealing as a strategicmechanism to improve a firm’s technologicaland market conditions. In particular, firms thatare part of larger innovation ecosystems—“the

collaborative arrangements through whichfirms combine their individual offerings into acoherent, customer-facing solution” (Adner,2006: 98)—are dependent on the behavior ofother actors to achieve positive returns to inno-vation (see also, for example, Adner, 2012, andPisano & Teece, 2007). By revealing some of itsown knowledge—either in the form of problemsor solutions—a focal firm can initiate collabor-ative relationships with other actors to reshapeits competitive environment and improve its ac-cess to technologies and markets. In contrast toprevailing approaches to collaboration, theseselective revealing strategies may also succeedunder adverse conditions of high partner uncer-tainty and high coordination costs and whenknown partners are unwilling to collaborate—conditions where (contractual) collaborationpreviously has been shown to be difficult to ini-tiate (e.g., Casciaro & Piskorski, 2005; Emerson,1962; Jacobs, 1974). Even if revealed knowledgeis merely absorbed and not reciprocated by ex-ternal knowledge producers in the innovationecosystem (hereafter simply “externals”), indi-rect benefits of selective revealing might out-weigh the costs for the focal firm. Specifically, ifexternals take in the revealed knowledge, be-cause of the cumulative, path-dependent natureof knowledge (Nelson & Winter, 1982), their fu-ture knowledge production and spillovers willbe of higher value to the focal firm. In short, weargue that selective revealing holds the poten-tial to reshape both the active and deliberate aswell as the passive and unknowing collabora-tive behavior of externals in the firm’s innova-tion ecosystem.

To understand when firms selectively revealtheir knowledge, we next analyze factors inter-nal and external to the firm that influence thisdecision, highlighting the particular importanceof modularity of resources, existing capabilities,and substitutive threats. Finally, we discusshow firms may embed selective revealing ininnovation strategies. When considering the re-vealing of problems and solutions in conjunc-tion with organizational goals of extending anexisting technological trajectory or creating newtrajectories (Dosi, 1982; Garud & Karnøe, 2001;Garud & Rappa, 1994), we derive four archetypesof selective revealing: issue spreading, agendashaping, product enhancing, and niche creating.

Taken together, we discuss situations inwhich the selective revealing of knowledge may

2013 271Alexy, George, and Salter

prove to be beneficial to organizations. In doingso we make several contributions to the man-agement literature. First, we add to ongoing dis-cussions of interorganizational relations (Doll-inger, 1990; Gulati, Nohria, & Zaheer, 2000;Oliver, 1990), showing how the strategic disclo-sure of knowledge allows the focal firm to notonly forge new ties to external actors and formcoalitions but to also potentially create entirelynew knowledge networks. Second, we link ourinsights to institutional theory (DiMaggio &Powell, 1983; Phillips, Lawrence, & Hardy, 2000)and resource dependence theory (Casciaro &Piskorski, 2005; Pfeffer & Salancik, 1978) by high-lighting how selective revealing implies a sub-tle form of competitor manipulation and thusrepresents an exercise of power. To explain thismechanism, we introduce the notion of inducedisomorphism—deliberate strategic action to in-duce other actors to become more similar to thefocal firm, particularly with respect to the pro-duction of knowledge. Finally, we contribute toconversations on the organization of innovativeactivity by discussing the concepts of absorptivecapacity (Cohen & Levinthal, 1990; Zahra &George, 2002) and open innovation (Chesbrough,2003; Dahlander & Gann, 2010; Laursen & Salter,2006) in light of our theorizing.

WHY? THE BENEFITS OFSELECTIVE REVEALING

Definition and Representation ofSelective Revealing

At its core, innovation is a path-dependent,cumulative activity that involves multiple actors(e.g., Nelson & Winter, 1982). Each actor privatelyinvests in R&D to expand its knowledge base soas to be able to create new or improved prod-ucts, processes, and services. At the same time,knowledge may “spill over” to competitors, inthe sense that competitors, to the disadvantageof the focal firm, gain access to private knowl-edge. In order to be receptive to spillovers, firmsbuild their absorptive capacity—an ability torecognize the value of externally produced spill-overs, to assimilate them, and to apply theminside the firm. Thus, the concept of absorptivecapacity helps explain why investment in R&D,even when its benefits cannot be fully appropri-ated by the focal firm, is sensible because itimproves the firm’s ability to learn from its en-

vironment and use this knowledge to increaseinnovative activity (e.g., Cohen & Levinthal,1990). In line with recent empirical insights byYang et al. (2010) and conceptual work by Agar-wal, Audretsch, and Sarkar (2007, 2010), innova-tive activity may be represented as a dynamicmodel in which outgoing spillovers, modifiedand enhanced by different actors along the way,may eventually return to the focal firm. Thisstylistic representation, shown in Figure 1, pro-vides an intuitive basis to explain the logic be-hind the selective revealing of knowledge.

Following Henkel (2006b), we define selectiverevealing as the voluntary, purposeful, and irre-vocable disclosure of specifically selected re-sources, usually knowledge based, which thefirm could have otherwise kept proprietary, sothat they become available to a large share oreven all of the general public, including compet-itors. Despite its contradiction with establishedliterature emphasizing the protection of knowl-edge produced in-house, work in this stream hasshown that selective revealing may positivelyaffect a firm’s innovation and business perfor-mance (Stam, 2009; West, 2003) by allowing foroutsourcing-like cost cutting (Lakhani & vonHippel, 2003), increasing the diffusion of prod-ucts leading to beneficial externalities (Varian

FIGURE 1Innovation As an Iterative, Multiagent System

Involving Spillovers

Note: The small circle represents the spillover that isbeing “passed on.” The shading of both the large and smallcircles symbolizes the varying structure of the respectiveknowledge.

272 AprilAcademy of Management Review

& Shapiro, 1999), and changing the competitivebehavior of others. Focusing on this latter point,Clarkson and Toh (2010) and Pacheco-de-Almeida and Zemsky (2012) separately showedthat disclosing internal technology resourcesmay deter rivals from investing in similar ones.Polidoro and Theeke (2012) found that firms pub-lish research results to influence their marketpositioning, particularly in the face of similarefforts by rivals and under substitutive threats.Finally, Farrell and Gallini (1988) showed thateven technology monopolists may gain from se-lectively revealing their knowledge to rivalswhen consumers face high adoption cost andare afraid of lock-in.

Thus far, however, the literature has not fullyacknowledged the use of selective revealing asa strategic tool and has fallen short of compre-hensively explaining the purposeful design anduse of strategies embodying selective revealing.For example, while Yang et al. (2010) found thatinvoluntary knowledge disclosure by firms maybe beneficial over time, they fell short of concep-tualizing spillovers as purposeful, assumingthat they occur by chance and suggesting thattheir “results should not be interpreted as a pre-scription for encouraging spillovers” (2010: 386).Relatedly, Polidoro and Toh (2011) found thatfirms choose not to fend off imitators when thethreat of substitution is high, particularly in theearly stages of development of a technology andwhen the underlying knowledge is new—raising the question of whether active revealingcould allow a further leveraging of these bene-fits (see also Agarwal et al., 2007, 2010).

Building on these important insights, we pro-pose that selective revealing can best be under-stood as a strategy aimed at shaping the collab-orative behavior of others in the context ofinnovative activity. Specifically, the two mostcrucial resources needed for innovative successare (1) knowledge embodied in technology, pro-cesses, and routines underlying the firms’ prod-ucts and services and (2) access to the respectiveproduct markets (Grant, 1996; Gulati & Singh,1998; Kogut & Zander, 1992). In turn, a firm can beexpected to initiate collaborative relationshipswith other parties if it lacks technological know-how to complete its competitive offering or toincrease its potential profits from its productsand services by establishing or improving mar-ket access and position. Accordingly, a focal firmwill primarily reveal knowledge selectively in

the hope that it will lead others to modify theirbehavior in such a way that the focal firm im-proves its access to the technologies or marketsrequired for innovative success. Notably, such aresponse should not be considered improbable.Externals may decide to reciprocate for a va-riety of reasons, such as the pure enjoyment ofproblem solving (Lakhani & Wolf, 2005), statusincentives (Jeppesen & Lakhani, 2010), reciprocity(Bonaccorsi & Rossi, 2006), and, of course, down-stream financial profit (Henkel, 2006b)—irre-spective of whether the reciprocated knowledgeis irrelevant (Allen, 1983) or relevant (Henkel,2006a; Spencer, 2003) to competition.

At the same time, selective revealing dictatesthat the firm make available some of its re-sources. Thus, the resources owned at a point intime determine what the firm can offer to enticeothers to collaborate. Following von Hippel’sdistinction (1988), we suggest that the resourcesthe organization should be most inclined toshare are problem-related (or need-related) andsolution-related knowledge. In the case of prob-lem revealing, the company purposefully dis-closes to its environment current or anticipatedfuture technological problems for which it seeksothers’ support. For example, firms such as HPand Intel regularly reveal knowledge aboutproblems they are facing internally and futureresearch trajectories they intend to explore inopen calls for research (Alexy, Criscuolo, &Salter, 2009; MacCormack & Herman, 2004). Ar-guments presented under the labels of crowd-sourcing and broadcast search advocating theinclusion of large numbers of externals in thesolution of technical problems by disclosingthese publicly or through intermediaries wouldalso be encompassed by this definition (e.g.,Afuah & Tucci, 2012; Jeppesen & Lakhani, 2010).

In contrast, solution revealing occurs whenthe focal firm voluntarily and strategically dis-closes to its environment knowledge on how tosolve a certain problem, as embodied, for exam-ple, in a patent, publication, product, or productcomponent addressing a certain need or provid-ing a certain function, to encourage imitationand diffusion. For example, an upstream firmmay be willing to share some of the results of itsR&D to increase downstream demand for re-lated products (e.g., Harhoff, 1996). Similarly,firms might be willing to contribute upstreamknowledge and intellectual property to jointknowledge production efforts in order to attract


more parties to join in quasi-collusive collabo-ration efforts to ensure the firms’ downstreamcompetitiveness (Alexy & Reitzig, in press). IBMmade publicly available 500 valuable patents tothe open source community in 2005. Followed byseveral other firms, including Nokia and NEC,this decision was motivated not by altruism butby a desire to sustain and support collectiveefforts to create and appropriate value fromopen source software.

Next we look at how selective revealing maybe used to entice externals to display activecollaborative behavior in situations where othercollaboration mechanisms known from the liter-ature rarely apply, thus increasing externals’propensity to grant access to other resourcesthat the firm needs. Subsequently, we examinehow selective revealing may reshape externals’generation of knowledge and spillovers so thatboth are of greater value to the focal firm, evenif externals merely use the revealed knowledgebut do not collaborate. Put differently, we ex-plain how selective revealing may cause exter-nals to collaborate (1) intentionally and directlyas well as (2) unknowingly and indirectly withthe focal firm. Uncovering these indirect bene-fits is relevant because it helps us understandthat selective revealing provides benefits evenif externals do purposefully change their collab-orative behavior toward the revealing firm.

Direct Benefits: Selective Revealing As a NovelPathway to Collaboration

A large body of literature exists in whichscholars argue that firms will try to establishrelationships with others when they lack criticalresources or are faced with environmental un-certainty (e.g., Casciaro & Piskorski, 2005; Hill-man, Withers, & Collins, 2009; Pfeffer & Salancik,1978). In the context of innovation, scholars haveemphasized an increasing disposition to strate-gically engage in collaborative relationships toovercome such issues (e.g., Arora, Fosfuri, &Gambardella, 2001; Chesbrough, 2003; Phelps,Heidl, & Wadhwa, in press; Powell, Koput, &Smith-Doerr, 1996). In a nutshell, these scholarsargue that organizations do not prefer to collab-orate but sometimes simply have to—either be-cause technologies and markets crucial to inno-vative success are (perceived to be) controlledby others, or because of specialization in certainelements of the value chain, as is common, for

example, in innovation ecosystems (Adner, 2006;Cook, 1977). Accordingly, firms attempt to stra-tegically design relationships with other actorsto secure access to crucial resources and to es-tablish (relatively) predictable environments(e.g., Bresser & Harl, 1986; Gulati et al., 2000;Oliver, 1990).

Conditions limiting the use of traditionalmodes of collaboration. A variety of formats forcollaboration that organizations may choosehave been proposed in different bodies of liter-ature, with selective revealing hitherto missingas an option (see, for example, Casciaro & Pis-korski, 2005; Hillman et al., 2009; Parmigiani &Rivera-Santos, 2011; Phelps et al., in press). Prev-alent arrangements—alliances, consortia, jointventures, or acquisitions—usually all occur un-der the shadow of a contract (so as to minimizeunwanted spillovers or moral hazard). At thesame time, it is clear that firms cannot alwayssuccessfully use these mechanisms (Ahuja,2000). We identify three conditions under whichtraditional collaboration mechanisms fail, andwe identify how these may be overcome by ap-plying strategies involving selective revealing.Notably, our intent is not to suggest that selec-tive revealing is a normatively superior ap-proach but, rather, to present it as a novel optionwhen firms must collaborate but, according toextant theorizing, can hardly do so.

First, firms will often need to go beyond cur-rently accessible partners to get access to thetechnologies and markets they need for innova-tive success. However, in a context of high part-nering uncertainty, firms may simply be un-aware of who the right partner is, or they mayface prohibitively high search costs identifyingthat partner (Gulati, 1998; Gulati & Gargiulo,1999; Jacobs, 1974). Notably, this problem may bebidirectional—externals that would be willingto collaborate may simply not be aware of thefocal firm’s issue.

Second, even if firms know the right partners,traditional methods of cooperating suggestedby the literature may simply be too costly toestablish or coordinate (e.g., Dollinger, 1990;Gulati & Singh, 1998; Henkel & Baldwin, 2011).While the logic of how this may apply to acqui-sitions or joint ventures is intuitive, a brief elab-oration is required for alliances. Importantly,coordination costs associated with their forma-tion and management can reasonably be as-sumed to increase nonlinearly. Thus, if firms


require multiple partners to bring a technologyto the market successfully—for example, if theyneed to form a coalition to legitimize a certaintechnology (Dodgson, Gann, & Salter, 2007;Garud & Rappa, 1994)—it is likely that the costsassociated with the creation of a plethora ofbilateral alliances will substantially decreasethe value of this option. Also, the fuzzy bound-aries of knowledge and the paradox of disclo-sure pose difficult challenges when assemblingpartnerships (Arrow, 1962).

While consortia may present a way to miti-gate some of these concerns, they have beenshown to be much less effective when potentialcollaborators are competitors in product mar-kets (Branstetter & Sakakibara, 2002), leading tothe third issue: even under the condition that thefirm is aware of a limited and accessible set ofcollaboration partners, these potential partnersmay be unwilling to collaborate. Most notably,in a situation where an external party controlsaccess to the technology and/or market desiredand the focal firm has little or no bargainingpower, incentives to collaborate for the sup-posed partner are limited, suggesting that a col-laborative tie is unlikely to form (Casciaro &Piskorski, 2005). Regarding collaboration bycompetitors of similar resource endowment inconsortia, Branstetter and Sakakibara (2002)summarized a debate in the industrial organi-zation literature stating that efficiency gainsfrom such endeavors may well be eaten up insubsequent market competition.

These conditions should be particularly prom-inent in innovation-related contexts, where tech-nological uncertainty and incomplete appropri-ability increase the salience of high partneruncertainty, high coordination costs, and poten-tial partners’ unwillingness to collaborate. Fi-nally, these three conditions might also be in-terlinked. For example, a focal firm mightalready be collaborating with another firm andhope to extend this relationship to access a tech-nology or market to foster another innovation.However, for competitive reasons the partnerfirm might be unwilling to comply (the thirdcondition), forcing the focal firm into a novelsearch for alternative partners (the first condi-tion) and subsequent contracting (the secondcondition).

We suggest that selective revealing may bean appropriate strategic move that may allow

firms to partially overcome these impedimentsto attain access to technologies and markets.

Overcoming partnering uncertainty. To ad-dress the problem of unawareness of partners,the disclosure of knowledge is a clear signal ofthe intent to collaborate with externals—a non-trivial precursor of actual collaboration (Kogut &Zander, 1996). By selectively revealing, the firmis reducing the preexisting information asym-metry about (1) whether or not it is looking for acollaboration partner and (2) which attributesthese partners should hold, thereby encourag-ing fitting external actors to respond to the sig-nal (see Spence, 1973). In so doing, selectiverevealing provides a solution to the basic nestedproblem of establishing common ground for col-laboration to emerge (Puranam, Singh, &Chaudhuri, 2009). Thus, selective revealing willoften represent an open invitation to externalsto collaborate (even if the firm knows exactlywho the potential collaborators might be). Thisis clear for both problem revealing (e.g., throughcrowdsourcing) and solution revealing (asshown in the earlier IBM patents example).

In addition, selective revealing may drasti-cally reduce the search cost for external actorsby allowing firms to cast a wider net in theirquest for collaboration partners. This holds notonly for the potential number of externals thatmay be reached but also for their scope. Specif-ically, the open invitation given through selec-tive revealing may be received by externals ac-tive outside the space in which the organizationtraditionally searches for collaboration part-ners, which may be particularly effective in sup-porting the focal firms’ innovative efforts (Afuah& Tucci, 2012; Jeppesen & Lakhani, 2010). Forexample, Afuah and Tucci (2012) described howproblem revealing in the form of crowdsourcingmay allow firms to drastically expand the limitsof local search. With respect to solution reveal-ing, Jeppesen and Molin (2003) articulated howsoftware firms instigated the development of ex-tensions to their products by voluntarily andstrategically disclosing parts of their products.We thus posit the following.

Proposition 1a: The higher the level ofpartnering uncertainty perceived by anorganization needing to collaborate,the more likely it will consider selectiverevealing over other mechanisms to in-duce collaborative behavior.


Overcoming coordination costs. Selective re-vealing may significantly reduce contractingcosts as potential partners can self-select to ac-cept the open offer to collaborate, which replacescostly bilateral negotiations and largely elimi-nates unsuccessful contracting. Also, selective re-vealing mandates neither formalized nor contrac-tual collaboration (Spencer, 2003). In addition, itsfixed setup costs may be discounted over a poten-tially limitless number of collaborations. The re-duction of coordination costs is a necessary con-dition to benefit from the expansion of the scope ofpartner search described above. This does notmean that no contracting exists; however, it isusually delayed until after it is clear that the col-laboration can be successful. For example, com-panies in many sectors engage in problem reveal-ing by publicly disclosing the problem on theirwebsite (Alexy, Criscuolo, & Salter, 2012). In suchscenarios companies may often not need to nego-tiate with externals since these may submit theirideas for free because of motivations other thanfinancial reimbursement (e.g., Lakhani & Wolf,2005). However, if negotiations have to take place,the revealing firm may, compared to other modesof collaboration, know better whether an externalsuggestion actually solves its problem (Lakhani,Jeppesen, Lohse, & Panetta, 2007) and may alsohave higher bargaining power because of the in-creased search scope and resulting availability ofalternate solutions.

At the same time, selective revealing positivelyimpacts the three Cs of collaborative activity—complementarity, compatibility, and commitment(Kale & Singh, 2009). Externals who self-select torespond to the selectively revealing organizationwill also signal information about themselves.First, externals should only self-select into collab-oration if they possess complementary knowledgeand use compatible processes. Because selectiverevealing creates transparency about the reveal-ing firm’s collaboration goals (i.e., the expectedcontribution of joining parties), externals shouldonly decide to partake in the exchange if thesegoals are perceived as beneficial (Emerson, 1962;Jacobs, 1974). Notably, however, even free-ridingmay generate indirect benefits for the revealingfirm.1 Second, the specific action that represents

the externals’ self-selection decision may be inter-preted as a signal of commitment. In many casesthe focal firm will be able to observe the responseof the externals. From that the focal firm may eval-uate the externals’ level of commitment by lookingat such factors as the level of resource commit-ment or its reversibility. Third, the same methodmay allow the focal firm to judge the capabilitiesof externals. Consider again the earlier HP andIntel example. Following the open call, universityresearchers will self-select into responding, gen-erating two key benefits. First, the firm will re-ceive, for free, a large number of proposals depict-ing the current level of progress of research in theproblem area and the possible range of ap-proaches to solving the problem. Second, it canhandpick and fund or hire those individualswhose suggestions it deems most economically orstrategically viable to begin the joint explorationof identifying problem solutions—that is, thosewith the highest levels of complementarity, com-patibility, and commitment.

Finally, the irrevocability of selective reveal-ing instigates trust as problems of moral hazardare minimized (Farrell & Gallini, 1988; Gulati &Sytch, 2007). In doing so, trust may eventuallybecome an enabler for more intense and higher-value information exchange between the par-ties (e.g., Gulati, 1998). Notably, this would alsosuggest that selective revealing could instigatesubsequent more in-depth relationships be-tween firms (such as joint ventures or alliances).Consider again the example where IBM dis-closed 500 patents. This not only led severalother firms to follow IBM but also paved the wayfor joint investment into the creation of a dedi-cated venture tasked to protect these firms’ se-lective revealing efforts against nonpracticingentities such as patent trolls. In summary, weposit the following.

Proposition 1b: The higher the level ofcoordination costs perceived by the or-ganization needing to collaborate, themore likely the organization will con-sider selective revealing over othermechanisms to induce collaborativebehavior.

Overcoming unwillingness to collaborate. Se-lective revealing offers two options to addressthe issue of powerful actors who are unwillingto collaborate. Generally, the most compellingmechanisms to reduce dependence on a power-

1 We extend this point in the section titled “Indirect Ben-efits: Selective Revealing As a Pathway to Reshape ExternalKnowledge,” below.


ful actor are the identification of alternatesources of supply and the formation of a coali-tion (Cook, 1977; Jacobs, 1974). Formally, how toachieve the first goal follows the argument ofhow selective revealing widens the search forpartners. As to the second goal, selective reveal-ing might represent not only an invitation tocollaborate with the focal firm but also one tocollude against another firm or even a networkof firms. Per Polidoro and Toh (2011), firms de-crease their efforts at deterring imitation whenfaced with a threat of substitution. However, thesubstitution threat not only applies to the focalfirm but to all firms following the same techno-logical trajectory (Dosi, 1982)—that is, to all po-tential imitators. Since these firms face similarincentives regarding which technology trajec-tory they want to see emerge victorious but haveidiosyncratic resource endowments for theircommercialization, selective revealing by oneactor may initiate reciprocal actions by othersfacing the same competitive issues. It is clearhow this logic applies to the IBM patents exam-ple, which has as its “targets” competitors suchas Microsoft and nonpracticing entities. Yet thisstrategy is clearly not limited to software. Forexample, as part of its Merck Gene Index, Merckdisclosed all human gene sequences into a pub-lic database. The goal of this initiative was toentice similar others to join Merck in preventingan upstream input to pharmaceutical productsbeing monopolized by actors specializing in thisspace (Pisano & Teece, 2007). We thus proposethe following.

Proposition 1c: The higher the level ofunwillingness to collaborate per-ceived by an organization needing tocollaborate, the more likely the orga-nization will consider selective re-vealing over other mechanisms to in-duce collaborative behavior.

Indirect Benefits: Selective Revealing As aPathway to Reshape External Knowledge

At the same time that selective revealing mayinfluence the intentional collaborative behaviorof externals, we further argue that it may alsohave a subtle yet important impact on how theseexternals generate knowledge that may leadthem to unintentionally exhibit collaborativebehavior. Importantly, we maintain further that

this effect should be present irrespective ofwhether or not externals reciprocate with col-laborative behavior, as long as they merely usethe knowledge that the focal firm has released.Put differently, the cost of revealing might al-ready be outweighed by indirect benefits of se-lective revealing, which always accrue if theselectively revealed knowledge is absorbed.These benefits originate from changes to howusers of the selectively revealed knowledgegenerate knowledge themselves and the volun-tary and involuntary spillovers (Winter, 1987)they produce.2 In the following section we focusour arguments on situations in which the selec-tively revealed knowledge is only used by ex-ternals who then free-ride and do not give backknowledge actively in return. If they did, then alleffects described in the following should bepresent to an even stronger degree.

Why should selective revealing have an im-pact on the knowledge, and particularly thespillovers, that organizations taking in the re-vealed knowledge produce? To be able to an-swer this question, we first need to look at whatconstitutes the value of externally held knowl-edge, namely whether it objectively addresses aneed of the firm (Cohen & Levinthal, 1990; Lane& Lubatkin, 1998)—that is, its content compati-bility—and whether it exhibits structural com-patibility with the firm’s existing body of knowl-edge—that is, an overlap in its categorization ofknowledge (e.g., according to certain scientificdisciplines) and the language used to describeit (e.g., Grant, 1996; Lane & Lubatkin, 1998). Inturn, content compatibility represents the objec-tive maximum value of externals’ knowledge(and of the spillovers they produce voluntarily orinvoluntarily), and structural compatibility pre-dicts the costs of absorption. Thus, selective re-vealing by the focal firm will produce indirectbenefits if it can influence others in such a waythat their production of knowledge and spill-overs generated in this process are of improvedstructural or content compatibility.

Effects on content compatibility. When firmsengage in problem revealing, as argued above,

2 Notably, further benefits may exist for the revealingfirm. For example, von Hippel and von Krogh (2003) maintainthat revealing in itself brings benefits such as learning,which may outweigh its total cost. Furthermore, we point tothe literature discussed above on the deterrence effect ofrevealing.


this is likely to facilitate the development ofsolutions by others. Even when externals areunwilling to freely share their solutions with thefocal firm as voluntary spillovers, their involun-tary spillovers will exhibit increased contentcompatibility, because externals will still bebasing their production of knowledge on theneeds of the focal firm. Thus, the mere use of thereleased problem-related knowledge by a suffi-ciently large number of externals, even if thesedo not actively reciprocate, may create external-ities that lead the focal firm to see its originalproblem sufficiently lessened or even solvedentirely.

This logic similarly applies to solution reveal-ing. Here the nonreciprocated use of the re-leased solution is identical to the choice of animitation strategy by externals, or free-riding.However, even free-riding may often be strictlybeneficial to the focal firm. For example, Pacheco-de-Almeida and Zemsky (2012) showed howcompetitors switching from innovation to imita-tion strategies may convey time-related advan-tages to the focal firm. And in case externalschoose to employ the revealed knowledge as aningredient in their own innovative activity, thismeans they will become more closely alignedwith the technological path of the focal firm.Thus, future spillovers by externals taking in therevealed knowledge will have higher contentcompatibility with the focal firm. As we elabo-rate below, these externals will also partake (tosome degree) in the focal firm’s technologicalpath so that they become potential supportersfor a focal firm’s attempt to create or displacetechnological standards or dominant designsand legitimize new technologies or markets.This is consistent with scholars who argue thatin the face of a substitutive threat, firms shouldchange their evaluation of strategies encourag-ing imitation (Polidoro & Theeke, 2012; Polidoro& Toh, 2011). Thus, we propose the following.

Proposition 2a: The more the focal firmseeks to influence the content compat-ibility of externals’ knowledge, themore likely it will consider engagingin selective revealing.

Effects on structural compatibility. The use ofselectively revealed knowledge should furtheraffect the structural compatibility of futureknowledge production by these externals. Inshort, when taking in the revealed knowledge,

the external has to bear the cost of translation.Externals that want to work on a disclosed prob-lem will need to assimilate this problem tomatch their own language and structure forknowledge (Kotha, George, & Srikanth, in press).Should they intend to solve it, they will furtherhave to produce an output that is structurallycompatible with the problem originally re-vealed (Jeppesen & Lakhani, 2010), for whichthey would need to adjust their knowledge pro-duction processes (Grant, 1996; van den Bosch,Volberda, & de Boer, 1999). In turn, this maypermanently increase the structural compatibil-ity of their knowledge production with the focalfirm (Cohen & Levinthal, 1990; George, Kotha,& Zheng, 2008; Grant, 1996; Gulati & Gar-giulo, 1999).

The argument for solution revealing is analo-gous: the revealed knowledge taken in becomesan input to the external’s own R&D and is as-similated and adapted. However, in this absorp-tion process, it is likely that the knowledge willretain some of its original language and struc-ture. Through its own absorption process, theexternal firm will familiarize itself with the orig-inal structure and language of the voluntaryspillover and keep some of it as its own (e.g.,Dyer & Singh, 1998; Lane & Lubatkin, 1998), par-ticularly when reusing the external knowledgewith little to no modification (Fleming, 2001;Kogut & Zander, 1992) or when external knowl-edge is generally preferred to internal knowl-edge (Menon & Pfeffer, 2003). Eventually, asshown by Yang et al. (2010), this increased struc-tural compatibility will lead to a rise in the focalfirm’s ability to profit from incoming spillovers.We thus posit the following.

Proposition 2b: The more the focal firmseeks to influence the structural com-patibility of externals’ knowledge, themore likely it will consider engagingin selective revealing.

Effects on technological trajectories. Techno-logical trajectories (e.g., Abernathy & Utterback,1978; Dosi, 1982) play a central role in innovationecosystems (e.g., Adner, 2012). They are best un-derstood as a socially constructed frame of ref-erence that informs organizations of what atechnology can and cannot do, how it should bephysically embodied, and how it can be evalu-ated by all players in the field (e.g., Garud &Rappa, 1994; Powell et al., 1996). Early on, a tech-


nological trajectory is solely sustained by thebeliefs of those exploring it, and huge uncertain-ties exist on all dimensions. Multiple trajecto-ries will be competing to address the same mar-ket need until the emergence of a sociallyaccepted evaluation system that selects a dom-inant design. Conversely, once a technologicalpath is established, relative certainty existsover technology and markets (Dosi, 1982; Garud& Rappa, 1994). Yet because of the cumulativenature of knowledge, organizations will findthemselves locked into a certain path (Garud &Rappa, 1994; Nelson & Winter, 1982). Accord-ingly, when the innovative activity of organiza-tions aims at extending existing paths, wewould expect that the need for collaborative be-havior will mainly originate from problems oftechnological specialization or the wish to ex-pand into different market segments. Con-versely, organizations intending to create newpaths will need to shape their technological andmarket environment to eliminate as many unfa-vorable possible future trajectories as possible.

The greater the number of externals who com-mit to a certain trajectory—and its content,structure, and language—in a given knowledgedomain, the more beneficial it is for other actorsto also convert to this trajectory and facilitateefficient cooperation (Grant, 1996; Kogut &Zander, 1992), necessitated by increased inter-connectedness and mutual dependence (Gulati& Sytch, 2007; Kotha et al., in press). In this con-text, selective revealing may allow the firm toinduce externals to align their technological tra-jectories and knowledge production processesso that they become analogous to the focal firm,with higher structural and content compatibil-ity. Providing valuable knowledge will increaseimitation, which should precipitate both greaterconvergence toward the focal firm’s technologi-cal trajectory and the generation of comple-ments and second-generation innovation builton and around the revealed knowledge (e.g.,Harhoff et al., 2003). In addition, because selec-tive revealing may decrease the fear of lock-inby a monopolistic supplier (Farrell & Gallini,1988), higher levels of use of the revealed knowl-edge, also among consumers, is more likely. Forexample, Google’s decision to make its mobileoperating system, Android, open source has cre-ated confidence among consumers and mobileoperators that this platform will be built on by

other firms, helping to increase its chances ofadoption.

Taken together, these two mechanisms sug-gest a high likelihood of network externalities,which may ultimately result in the establish-ment (or reinforcement) of favorable normsabout the focus, structure, and language ofknowledge production (Spencer, 2003)—as, forexample, articulated in the dominant design—potentially even if no firm is actively colludingwith the selectively revealing actor. While someexternals may be skeptical of such strategic ef-forts (Dollinger, 1990; Oliver, 1988, 1990)—yetmay still decide to use the selectively revealedknowledge and possibly even reciprocate—atthe same time others will unknowingly becomemore isomorphic to the firm in their knowledgegeneration.

In turn, this induced isomorphic behavior andthe resulting higher structural and content com-patibility should render future collaborationwith the focal firm an increasingly attractiveoption for externals. For example, as a responseto problem revealing, firms that have a relatedtechnology may decide to adapt it to match thesignal, thus interpreting it as information abouta potential market. Similarly, complementershaving to choose between competing platformsshould strongly prefer an open one since it de-creases uncertainty regarding the outcome ofcontracting and future access. Finally, firmsstruggling with high technological uncertaintyshould be more likely to model their explorativeefforts on the problems of others (see DiMaggio& Powell, 1983) and, thus, also use free interme-diate solutions to then extend these as needed.Notably, in all of these cases, uncertainty reduc-tion will be higher if the external permanentlyaligns itself with the revealing firm, which islikely to continue to supply further uncertainty-reducing knowledge. Permanent alignment maybe the outcome of subsequent interactions, evenin the absence of trust, which is only developedsubsequently (Van de Ven & Walker, 1984). Fur-thermore, each transaction increases mutualdependence on each other and, thus, increasesthe likelihood and value of future collaboration(Gulati & Sytch, 2007).

Accordingly, firms that strive to extend an ex-isting path may benefit from induced isomor-phism by increasing the value of their extantresources or prolonging their longevity. Firmsworking to create new paths may find that by


inducing isomorphic behavior among externals,they may foster the emergence of a more favor-able trajectory. We thus propose the following.

Proposition 2c: The more the focal firmseeks to influence the evolution of tech-nology trajectories, the more likely itwill consider engaging in selectiverevealing.

WHEN? BOUNDARY CONDITIONS OFSELECTIVE REVEALING

Of course, we are not trying to argue thatselective revealing is universally beneficial toall firms in any given competitive situation.Rather, managers will need to make boundedlyrational evaluations of whether anticipatedbenefits outweigh potential costs (Henkel, 2004).Even if the above-mentioned benefits render se-lective revealing a strategic alternative worthconsidering, this needs to be separated from thedecision of whether an organization should ac-tually reveal. Such a decision needs to factor inthe costs that the firm must bear to initiate se-lective revealing and the risks of unwanted out-comes. Here three forms of risk seem to be par-ticularly crucial. First, the organization mayaccidentally disclose knowledge beyond what itwanted to or should have released, potentiallyculminating in loss of control over current andfuture product development (Chesbrough &Teece, 1996). Second, it might struggle to man-age the increased complexity of its innovativeactivities that now transcend the boundary ofthe firm in a way that runs counter to the tradi-tional emphasis on the protection of intellectualproperty generated in-house (Alexy et al., 2009).Third, the organization may fail to attract exter-nals to even use the revealed knowledge. Theserisks may, of course, be mitigated. Specifically,organizations can decide which resources to re-veal, after taking into account their competitiveposition, capabilities, and internal processes toensure that they may reap possible benefits ofselective revealing. Moreover, factors external tothe organization need to be taken into account.

Internal Drivers of the SelectiveRevealing Decision

Whether or not to reveal a specific resource isa question of trade-offs. While an organization

must not reveal valueless resources (since thesewould most likely neither be used nor recipro-cated by externals), it will try to abstain fromdisclosing resources that are of high competi-tive relevance (e.g., Polidoro & Toh, 2011). Forexample, firms will hesitate to disclose tacit orcomplex knowledge since it can be kept secreteasily, thus promising high returns from exclud-ability and inimitability (Rivkin, 2000; Teece,1986; Winter, 1987). However, should a firm de-cide to release such high-value resources none-theless, this may substantially increase the like-lihood that those resources will be picked up byother parties, which may ultimately overcom-pensate for the initial cost of giving up exclusiv-ity. Accordingly, such trade-offs will need to beevaluated for each selective revealing decision,limiting the scope for generalization.

Looking at an organization’s resource basemore broadly, modularity should increase thelikelihood the organization will decide to en-gage in selective revealing (Henkel & Baldwin,2011). If the firm’s resource base is modular, thefirm can release some parts of it without havingto disclose others it wants to keep proprietary.Still, the released knowledge will have contentand structural compatibility with what the firmkeeps in-house so that both direct and indirectbenefits of selective revealing are attainable.For example, an organization that has its knowl-edge base modularized along the layers of in-dustry architecture (Jacobides, 2006) may be ableto reveal knowledge only on one layer of theindustry architecture and at the same time re-tain relatively secure revenue streams originat-ing from activities on other layers (West, 2003).Furthermore, such modularity may increase thelikelihood that externals exist that are inter-ested in the knowledge the firm reveals yetare not direct competitors in the product market.In turn, this should increase the likelihood thatthese externals use and reciprocate the re-vealed knowledge to engage in collaborativeresearch (Branstetter & Sakakibara, 2002) oreven collusion (Alexy & Reitzig, in press; Doll-inger, 1990). Accordingly, we propose thefollowing.

Proposition 3a: The degree of modu-larity of the organization’s resourcebase will increase its propensity to en-gage in selective revealing.


Furthermore, we expect an organization to en-gage in selective revealing if it perceives that itis fit to benefit from it. Here the assessment of fitincludes an evaluation of all steps of the selec-tive revealing process. First, is the organizationgood at disclosing knowledge—can it presentthe knowledge in a format so that others cansuccessfully use and possibly build on it? Spe-cifically, the organization will need to decontex-tualize its problems and solutions enough sothat they are accessible to externals, yet not toomuch so as to ensure that subsequent relatedknowledge generated by externals will be valu-able to the firm. Recent research shows this isindeed a nontrivial process (Baer, Dirks, & Nick-erson, in press; von Krogh, Wallin, & Sieg, 2012).Second, the firm will need to be ready to reapexternal knowledge. At the very least, sufficientabsorptive capacity is a prerequisite to be ableto gain from the contributions of others to theselective revealing effort, but specific internalorganizational practices may be required (Foss,Laursen, & Pedersen, 2011). On a larger scale,the organization may have to adjust its pro-cesses for value creation and capture—tied to-gether to form its business model—should itlook to profit from its selective revealing en-deavor (e.g., Chesbrough, 2006; Chesbrough &Appleyard, 2007). In addition, particularly if theorganization seeks to induce long-term relation-ships with externals, it will need to ensure thatits internal routines and culture are up to thetask (e.g., Alexy et al., 2009). Organizations thathave not internalized these respective capabili-ties will more likely shy away from selectiverevealing since they would otherwise need tobear the considerable burden of establishingthem. Accordingly, we posit the following.

Proposition 3b: Existing organiza-tional capabilities in extracting valuefrom external knowledge will in-crease its propensity to engage in se-lective revealing.

External Drivers of the SelectiveRevealing Decision

Two kinds of external considerations will mat-ter in particular to firms considering selectiverevealing: (1) the firms’ competitive environmentand (2) the perceived likelihood externals will

use or reciprocate the revealed knowledge. Be-low we take each in turn.

Competitive dynamics have the potential toaffect the urgency to selectively reveal and,thus, increase a firm’s tolerance to disclosevaluable knowledge. In particular, selective re-vealing may be a reaction to a severe threat to afirm’s competitive position. Here, as alluded tobefore, the perceived threat of substitution (Po-lidoro & Toh, 2011) should strictly positively af-fect the firm’s willingness to engage in selectiverevealing. Especially if knowledge is path de-pendent and learning is cumulative (Scotchmer,1996), an organization should be willing to de-fend its path against others while hoping to beable to fend off imitators through lead time(Clarkson & Toh, 2010). Thus, particularly whenmultiple technological trajectories proposed bydifferent organizations are competing againsteach other, selective revealing might become acompelling option since some externals may beenticed to support the focal firm (Alexy et al.,2009), possibly tipping a standard race in favorof the focal firm (Varian & Shapiro, 1999).

At the extreme end of such efforts lies what isdescribed in the literature on open source soft-ware. Here companies engaged in solution re-vealing to prevent being squeezed out of a mar-ket entirely by a (to-be) monopolist. Specifically,firms such as Netscape—which found itselfoverwhelmed by Microsoft in the “browserwars” of the 1990s—felt that they would be bet-ter off competing on open products and stan-dards rather than awaiting certain competitiveannihilation, and therefore revealed essentialparts of their product portfolios to the public.While of course a gamble, these companies ex-pected higher odds of survival from taking achance on whether selective revealing dynam-ics unfolded rather than from following tradi-tional forms of product-market competition onproprietary intellectual property (Henkel, 2004).

Proposition 4: The perceived strengthof a substitutive threat to the organi-zation’s resource base will increaseits propensity to engage in selectiverevealing.

Beyond substitute threats, a brief look at theexisting literature on collaboration shows anextensive list of elements of competition, whichshould also affect selective revealing and itscosts, urgency, or likelihood of success. These


include existing collaborative networks andtheir structure, which can be reactivated for theselective revealing effort (Gulati & Gargiulo,1999) and predict a firm’s reach (Schilling &Phelps, 2007) and its influence on other actors(Galaskiewicz, Bielefeld, & Myron, 2006; Powellet al., 1996). Further, regarding the ecosystemsurrounding the firm, the number of players andtheir level of diversity determine what knowl-edge the firm may possibly attain (e.g., Gulati &Sytch, 2007; Van de Ven & Walker, 1984). Modu-larity of these ecosystems at large (Baldwin &Clark, 2000), as expressed by layered architec-tures (Pisano & Teece, 2007) or fragmented mar-kets (Dollinger, 1990; Jacobs, 1974), may also in-crease the chance that disclosed knowledge willbe used and reciprocated. Finally, the existenceof institutions and social norms supporting col-laboration will also positively affect the perfor-mance of selective revealing strategies. Theseinclude intellectual property regimes (Teece,1986), a culture that facilitates trust building(Kale & Singh, 2009), and the general existenceof an appropriate legal framework governingand supporting knowledge production and shar-ing (Fosfuri & Rønde, 2004). Whereas each ofthese factors could potentially affect selectiverevealing, we have restricted our propositions tothose where there is a preponderance of evi-dence to build theory. Our intention is not todiminish the importance of other plausible driv-ers but to be parsimonious in our selection froma multitude of potential influences.

HOW? ARCHETYPES OF SELECTIVEREVEALING STRATEGIES

In this section we address the question of howselective revealing may be embedded in inno-

vation strategies. To do so we build on our dis-tinction of problem and solution revealing,which respectively focus on improving access totechnologies and markets. In addition, we con-sider the innovation goals of the organization inlight of the existence of technological trajecto-ries, looking at whether the firm intends to cre-ate a new path or extend a current one.

Combining these two dimensions results inthe matrix depicted in Figure 2. Below we ex-plain the resulting four archetypes of selectiverevealing and how they allow firms to accesstechnologies and markets; examples of prac-tices embedding these strategies from severalindustries are shown in Table 1. Our exampleshighlight the plurality of revealing strategies.These strategies are often conducted through avariety of organizational structures, including,for example, research consortia, open sourcesoftware, and crowdsourcing. Rather than seekto explain the specific organizational structurethat enables selective revealing, we focus on therationale behind the decision of the firm to re-veal knowledge. Thus, while we present a vari-ety of examples of selective revealing to illus-trate what it may help firms achieve, at its coreour argument is indifferent to the specific mech-anism chosen to selectively disclose knowledge.

Issue Spreading

Issue spreading, the selective revealing oftechnology-related knowledge to extend exist-ing paths, may have two effects on the firm’senvironment. Both of these build on the fact thatissue spreading directly embodies a need of thefocal firm that others may be able to satisfy in away that is mutually beneficial. First, externalactors may be encouraged to submit to the focal

FIGURE 2Selective Revealing Strategies

Mode of revealing

Problem revealing Solution revealing

Path

extension

Issue spreading

(broadcast search)

Product enhancing

(open source software) Goal Path

creation

Agenda shaping

(open research calls)

Niche creating

(academic publishing)

Note: Exemplar practices embedding selective revealing are given in parentheses.


firm their existing knowledge to address thespecific problem. Alternatively, the revealedknowledge may act as a trigger for new devel-opment activity since the focal firm is signalingdownstream demand. The crowdsourcing exam-ples given earlier in this article clearly illustratethis point. Here the focal firm directly signals toits environment current problems it is unable tosolve on its own in the hope of finding externalswith related yet sufficiently distinct knowledgeable to tackle the issue at hand.

Second, issue spreading can be interpreted asan invitation to collude on extending existingtechnology paths. Under the condition that R&Dis either too costly for one firm to bear or whenR&D is not a differentiation factor, the focal firmcan reasonably hope for other actors facing sim-ilar technological problems to accept this invi-tation, thereby enabling or supporting collectivestrategies (Bresser & Harl, 1986; Dollinger, 1990).An example of issue spreading can be seen inthe GreenTouch initiative, a new consortium ofleading IT companies that have come togetherto try to increase the environmental perfor-mance of networks. Although often competitors,GreenTouch members have sought to outlinethe architecture, specifications, and road maprequired to improve network energy efficiencyby a factor of 1,000 over 2010 standards by 2015.Issue spreading allows these firms to indicatetheir commitment to this technological path,make interdependencies publicly visible, attract

new participants and complementers, and easethe coordination of R&D investment decisions.

Agenda Shaping

Theories of power make clear that the abilityto shape discourses serves as a source of powerin collaborative relationships (e.g., Lukes, 2005;Phillips et al., 2000). By influencing what is be-ing talked about and how, actors may steer thesocial construction of technology paths in a di-rection more suitable to their needs. Extendingthis argument to our context, we suggest thatproblem revealing may allow the focal firm toshape the development agenda for new paths itintends to create so as to entice externals tocoordinate or align around the production of so-lutions fitting the focal firm’s intended trajectoryand its gaps. Thus, a firm will communicatethose issues it considers relevant for the cre-ation of its most preferred pathway and will tryto set in motion a legitimate discourse around itand connect other actors to this discourse tofacilitate collaborative behavior (Hardy, Law-rence, & Grant, 2005; Phillips et al., 2000). Suchcommunication to the environment may occur,for example, through open research calls. Evenmore basic, simply making the focus of R&Dactivity known to the public through the com-pany website may spur the development of re-lated activity and its submission to the firm fromits environment. Most famously, agenda shap-

TABLE 1Selective Revealing Strategies: Examples of Successful Implementation from the

Academic Literature

Strategy Definition Studies Study Contexts

Issue spreading Encourage others to participate in sharedproblem solving and/or to makecomplementary investments

Füller (2010); Jeppesen &Lakhani (2010)

Firms on InnoCentive,consumer goods, IT

Agenda shaping Highlight focal firm’s future demands soothers can privately invest in and/oractively assist firm in developingsolutions and complementary offerings

MacCormack & Herman(2004); Alexy, Criscuolo,& Salter (2009)

Defense industry, IT,pharmaceuticals,consumer goods

Productenhancing

Facilitate wide use of revealedknowledge to increase value ofcomplementary assets and likelihoodof reciprocal behavior

Allen (1983); von Hippel(1988); West (2003)

User innovation in allsectors, engineering,IT

Niche creating Build critical mass supporting firm’stechnology trajectory to attain buy-infrom crucial actors in ecosystem

Garud, Jain, &Kumaraswamy (2002);Dodgson, Gann, &Salter (2007)

Built environment, IT


ing is incorporated in the so-called DARPAmodel, which has been executed successfully bythe U.S. Department of Defense for decades andwhich has also been transferred to several Sili-con Valley companies, as clearly shown by theexamples of Intel and HP given earlier.

Product Enhancing

By engaging in product enhancing—the ex-tension of current paths through solution reveal-ing—the firm has the opportunity to improve itscompetitive position in current markets or to ad-vance into new ones, even if strong competitorsexist. Product enhancing might be particularlyappealing to firms in control of nondominanttechnology platforms. For example, IBM openedup the core of its Eclipse software developmenttool to the public, including the source code ofthe software (West, 2003). Doing so increased itsdiffusion among end users and led many com-mercial firms to abandon their efforts to developsimilar tools and, instead, to focus on adaptingEclipse to their respective needs. As many ofthese actors made their adaptations open to thepublic again at no cost, the functional scope ofEclipse and its compatibility with other plat-forms were extended substantially beyondIBM’s initial contribution. This led to a furtherboost in diffusion, rendering Eclipse the de factostandard software development tool on mostplatforms, including those controlled by IBM’sfiercest rivals, Microsoft and Sun, in which IBMpreviously had been unable to establish a foot-hold. In turn, IBM was able to create a bustlingecosystem around its platform, producing up-grades and extensions to its program, and asubstantially increased installed base to whichit could sell complementary offerings.

Niche Creating

Niche creating is the use of solution revealingto shape and establish novel knowledge pathsby collaborating with relevant others to assem-ble a critical mass that allows for the creation ofnew institutional rules and resources (Phillips etal., 2000). Specifically, niche creating assists thefirm in trying to convince other industry stake-holders that its preferred technology trajectoryis both viable and legitimate and should bepreferred over alternative solutions, if these ex-ist (Garud & Rappa, 1994). By encouraging others

to use the revealed knowledge, the firm may beable to influence its environment to converge (orat least shift) toward the focal firm’s preferredtrajectory (Garud, Jain, & Kumaraswamy, 2002).As these externals’ future paths become morealigned to that of the focal firm, niche creatingwill increasingly allow the firm to impact howother industry stakeholders think about the evo-lution of the technology, guiding them towardthe firm’s preferred path and encouraging themto participate in the social construction processnecessary for its eventual legitimation. In doingso, niche creating ultimately may enable thefirm to shape relevant discourses and createentirely new markets that are closely alignedwith its interests and resources (Garud et al.,2002; Phillips et al., 2000).

As a poignant example of niche creating,Dodgson et al. (2007) described the case of theengineering consultancy Arup, which had de-veloped a novel technological solution to useelevators in case of fire emergencies. However,since established norms were strictly contradic-tory to this technological advancement, Arupneeded to convince industry stakeholders of theviability of this technology. Arup revealed itssolution knowledge to its competitors and otherexternals to increase the number of actors inter-ested in establishing this market, including theregulators of new building designs. Ultimately,this strategy allowed Arup to create and legiti-mate “fire engineering,” a new niche in the builtenvironment in which Arup became recognizedas the primary authority, since everyone was inconcordance with Arup’s technology trajectory.Finally, since Arup was strategic about whichpieces of knowledge it revealed, it continued tocommand a technological lead over other indus-try players.

DISCUSSION AND IMPLICATIONS

We have proposed a model of selective re-vealing as a deliberate, strategic action to im-prove conditions for innovation (Figure 3). Wesuggested that selective revealing is a novelmechanism that can shape the collaborative be-havior of external actors. First, selective reveal-ing may initiate active collaboration even underconditions of high partner uncertainty and highsearch costs and when known partners are un-willing to collaborate. Second, it may cause pas-sive and possibly unknowing collaboration by


externals, even when these are merely free-riding on the selectively revealed knowledge, bymaking future involuntary knowledge spilloversmore valuable to the focal firm, and it may in-duce the external to become isomorphic. We fur-ther outlined internal and external factors thatshould positively impact the firm’s propensity toengage in selective revealing and pointed outthe role of modularity, existing capabilities, andsubstitutive threats in this context. Finally, wespecified four forms of selective revealing de-pending on whether the firm aims to improve itsaccess to technologies (through problem reveal-ing) or markets (through solution revealing) andwhether it aims to extend existing paths or cre-ate new ones: issue spreading, agenda shaping,product enhancing, and niche creating.

Selective Revealing and Collaboration

Our work provides three insights for manage-ment theory. First, we highlight the nature ofselective revealing as a previously undocu-mented, theoretically relevant mechanism toinitiate collaborative behavior. We extend thepossibility for strategic action in reshaping en-vironmental dependencies to situations wherethe strategy and organization theory literaturewould consider the actor largely unable to es-tablish access to critical resources through col-laboration: high partner uncertainty, high coor-dination costs, and unusable knowncollaboration options (e.g., Bresser & Harl, 1986;

Cook, 1977; Dollinger, 1990; Jacobs, 1974). Weshow how even under these conditions actorscan positively influence environmental contin-gencies through selective revealing to create analternative source of supply, rally allies, andmitigate uncertainty.

Our argument points to a dynamic element ofnetwork creation spurred by selective revealing.There is scarce current related theory explain-ing the emergence of collaborative mechanismssuch as strategic alliances beyond the argu-ment of multiplex relations—that is, currentlyexisting relationships on another dimensionthat will be leveraged to form the desired alli-ance (e.g., Ahuja, Polidoro, & Mitchell, 2009;Gulati & Gargiulo, 1999; Hallen, 2008). While ex-isting relationships will still matter in ourmodel, they are clearly not necessary for collab-oration to emerge from selective revealing.Thus, we would argue that selective revealingrepresents a novel mechanism explaining theemergence of knowledge networks and collec-tive strategies, in which, in contrast to muchextant literature (e.g., Kilduff & Brass, 2010),there is a clear role played by managerialagency. This argument further expands on Hill-man et al.’s (2009) question of whether organiza-tions progress through a sequence of strategiesaimed at lowering their dependence on theirenvironment; we would predict that, in innova-tive activity, selective revealing may often pre-cede more resource-intensive forms of collabor-ative engagement.

FIGURE 3A Process Model of Selective Revealing

Note: Element shaded in gray represents relationships that are discussed in the article but for which we refrain frompresenting propositions.


An important issue that remains to be ad-dressed is what forms of networks will emergefrom selective revealing and how these net-works may be governed beneficially. For exam-ple, Eclipse has long been governed by a foun-dation in which IBM is one among manymembers. This would suggest that selective re-vealing aimed at establishing a collective strat-egy against dominant competitors may requirethe revealing firm to give up its position at theformal center of the network. We strongly en-courage empirical research in order to betterunderstand these points.

Selective Revealing and Power

Second, our model further allows us to rein-vigorate the link between knowledge exchangeand isomorphism to provide a stronger integra-tion of theories explaining collaborative innova-tive behavior with institutional and resource de-pendence. In this context, as the relationshipbetween the revealing party and the user of itsknowledge is established, this link automati-cally and concomitantly forces the using partyto engage in behavior similar and, thus, benefi-cial to the focal firm. In short, the focal firm isemploying selective revealing to subtly exercisepower over others to purposefully initiate iso-morphic behavior.

This induced isomorphism shares similaritieswith other forms (DiMaggio & Powell, 1983), par-ticularly coercive isomorphism, which resultsfrom pressure or persuasion from environmentalsources. Yet the use and reciprocation of selec-tively revealed knowledge by external actorsis not a coerced decision, since the voluntarydisclosure of knowledge merely represents anopen offer to an indiscriminate number of exter-nals, which all are free to reject. Nonetheless, itsacceptance mandates at least some isomorphicbehavior. Induced isomorphism also shares as-pects of mimetic isomorphism; we have ex-plained how some externals will react posi-tively to the focal firm’s knowledge disclosuresbecause these disclosures will reduce uncer-tainty. Finally, the ultimate goal of induced iso-morphism is to create normative pressures byestablishing dominant standards and designs.Once enough firms have converged on the focalfirm’s trajectory, normative isomorphism maylead the focal firm to emerge as the centralorganization in a larger knowledge network or

ecosystem, and it may stimulate bandwagon ef-fects that strongly and primarily benefit the fo-cal firm.

From the vantage point of resource depen-dence theory, our argument implies that an ac-tion born out of a dependence on access to re-sources held by others may in fact be recast tobecome a source of control. This logic is partic-ularly appealing when looking at the potentialof selective revealing to act as a less expensivemechanism for generating an alternate sourceof supply and for instigating collective action inthe face of power imbalance and low mutualdependence. In this situation the high-power ac-tor is likely to be able to withhold the desiredresource (Casciaro & Piskorski, 2005) if the low-power actor cannot establish a relationship witha third party constraining the high-power actor(Gargiulo, 1993). We would argue that selectiverevealing invokes different power dynamics: be-cause of its wider reach and lower coordinationcost, the low-power actor should find it easier tocreate alternative sources of supply or support-ive coalitions than with other collaborationmechanisms. Also, a swift and comprehensivecompetitive response by the high-power actor toa newly open competitor, especially if opennessis exhibited in the core product market of thehigh-power actor, is difficult to imagine—for ex-ample, because of varying levels of organiza-tional fit with selective revealing strategies. Weare unaware of studies on this subject andwould thus strongly encourage empirical workto uncover the competitive dynamics underlyingthese processes.

Selective Revealing and Innovation

Third, we contribute to a rich body of innova-tion literature by providing a theoretical argu-ment extending selective revealing beyond itsknown use as a deterrence mechanism (Clark-son & Toh, 2010; Polidoro & Toh, 2011) to its useas a facilitator of collaboration—one that is par-ticularly helpful in, but not limited to, adverseconditions. In addition, our discussion of the in-direct benefits of selective revealing has madeclear that it can instigate a process in whichincoming spillovers become more valuablewithout the firm’s changing anything about itsknowledge production process.

In doing so, our arguments extend a recentcontribution (Yang et al., 2010) to the literature


on absorptive capacity (Cohen & Levinthal, 1990;Todorova & Durisin, 2007; Zahra & George, 2002)indicating that outgoing spillovers might be-come beneficial to a firm over time. We contrib-ute to this discussion by conceptualizing selec-tive revealing as a conscious strategy aimed atshaping the knowledge others produce. Outputsof the focal firm’s knowledge production processare purposefully disclosed so that they may bepicked up by actors in the firm’s environment. Inturn, externals using these outputs will purpose-fully or unknowingly transform their knowledgeproduction, making its outputs more valuable tothe focal firm. Importantly, since the anticipatedbenefits of selective revealing lie in the futureand depend on the activities of others, the valueof such strategies can only be appreciated byincluding such intertemporal dynamics, whichare currently not present in the absorptive ca-pacity literature.

Finally, innovation scholars may benefit fromour classification of selective revealing strate-gies based on what resources companies revealand what innovation goals they seek to fulfill.For example, it may be used to inform ongoingdebates on open innovation and the increasingimportance of innovation conducted by noncor-porate actors (Baldwin & von Hippel, 2011; Ches-brough, 2003; Dahlander & Gann, 2010). We arehopeful that scholars active in these debateswill enrich our conceptual framework with em-pirical data so as to also clarify the boundaryconditions of our argument. For example, muchstill needs to be learned about the relative ef-fectiveness of problem and solution revealing,as well as the factors that lead externals toreciprocate in the firm’s interest.

Future Directions

Selective revealing is gaining recognition asa strategic tool in hypercompetitive industriesthat may confound established managementtheories predicting firm behavior and innova-tion outcomes. By perceiving selective revealingas a mechanism to reshape the collaborativebehavior of others, we open new avenues toenrich strategy and organization theory and itsattendant implications for innovation and per-formance. Substantial empirical effort is neededto operationalize the drivers, contingencies, andoutcomes of selective revealing discussed in

this article in order to guide emergent practice,as well as to provide valuable extensions.

Additionally, our model raises questionsabout the right degree of influence firms maywant to exert, since too similar an environmentmay not present a firm with sufficiently originalknowledge spillovers. Thus, research could tryto interrelate (changes in) the position of therevealing firm in the network, the network struc-ture, and the emergent homogeneity of knowl-edge with firm performance as revealing dy-namics unfold. We could also imagine ascenario where selective revealing leads to value-destructive dynamics following the logic of pat-ent races. In a similar vein, one might imaginefirms using selective revealing as a bluff. Spe-cifically, a firm may disclose knowledge it con-siders a dead end, hoping that externals commitsubstantial resources to find that out for them-selves and giving the focal firm the opportunityto achieve lead time in an area it considerscrucial. Further systematic evidence is likely toenrich our knowledge of the false signals andcompetitive gaming even within selective re-vealing strategies.

When knowledge is to be revealed, an essen-tial issue lies in how to structure and present theselectively revealed knowledge so as to maxi-mize direct and indirect benefits (Baer et al., inpress; von Krogh et al., 2012). This would open anavenue to connect our reasoning to the problem-based view of the firm (Nickerson & Zenger,2004). Also, there is a question of how selectiverevealing relates to the concept of disruptiveinnovation and the issue of overcoming inertialforces favoring the extension of known techno-logical trajectories (e.g., Christensen, 1997). Se-lective revealing may present an opportunity toincumbents to disrupt themselves; however, atthe same time it may enable competitors to ini-tiate and coordinate the development and diffu-sion of disruptive innovations.3 Finally, we fo-cused on knowledge as a selectively revealedresource. However, we see promise in extendingselective revealing to other nonrivalrous re-sources and in identifying conditions underwhich it could also apply when the revealedresource is rivalrous.

3 We are indebted to an anonymous reviewer for bringingthis possible extension of our work to our attention, as wellas suggesting the intriguing idea of selective revealing asa bluff.


Managerial Implications

From the perspective of managers chargedwith creating and implementing corporate andinnovation strategy, our argument is a clear callto make selective revealing a standard tool inthe competitive toolbox. Specifically, we pointout why, when, and how managers can reason-ably expect to benefit from selective revealingto solve problems, shape technologies, improvemarket positioning, or even create new niches.In addition, we provide insight to firms in whoseenvironment selective revealing takes place,and we encourage firms to study potential idio-syncratic advantages from reciprocating, even ifthey know that such action might also be bene-ficial to somebody else. Finally, our argumentcan act as a note of caution to managers incurrently dominant strategic positions for whomthe threat of being attacked through selectiverevealing may loom large. In turn, even thesefirms may find that under certain conditionsthey may stand to benefit from selectively open-ing their resources to others to preempt beingoutmaneuvered by a coalition assembled via aselective revealing strategy.

REFERENCES

Abernathy, W. J., & Utterback, J. M. 1978. Patterns of indus-trial innovation. Technology Review, 80: 41–47.

Adner, R. 2006. Match your innovation strategy to your inno-vation ecosystem. Harvard Business Review, 84(4): 98–107.

Adner, R. 2012. The wide lens. New York: Portfolio/Penguin.

Afuah, A., & Tucci, C. L. 2012. Crowdsourcing as a solution todistant search. Academy of Management Review, 37:355–375.

Agarwal, R., Audretsch, D., & Sarkar, M. B. 2007. The processof creative construction: Knowledge spillovers, entrepre-neurship, and economic growth. Strategic Entrepreneur-ship Journal, 1: 263–286.

Agarwal, R., Audretsch, D., & Sarkar, M. B. 2010. Knowledgespillovers and strategic entrepreneurship. Strategic En-trepreneurship Journal, 4: 271–283.

Ahuja, G. 2000. The duality of collaboration: Inducementsand opportunities in the formation of interfirm linkages.Strategic Management Journal, 21: 317–343.

Ahuja, G., Polidoro, F., & Mitchell, W. 2009. Structural ho-mophily or social asymmetry? The formation of alli-ances by poorly embedded firms. Strategic Manage-ment Journal, 30: 941–958.

Alexy, O., Criscuolo, P., & Ammon, S. 2012. Managing unso-licited ideas for R&D. California Management Review,54(3): 116–139.

Alexy, O., Criscuolo, P., & Salter, A. 2009. Does IP strategyhave to cripple open innovation? Sloan ManagementReview, 51(1): 71–77.

Alexy, O., & Reitzig, M. In press. Private-collective innova-tion, competition, and firms’ counterintuitive appropria-tion strategies. Research Policy.

Allen, R. C. 1983. Collective invention. Journal of EconomicBehavior & Organization, 4: 1–24.

Arora, A., Fosfuri, A., & Gambardella, A. 2001. Markets fortechnology: The economics of innovation and corporatestrategy. Cambridge, MA: MIT Press.

Arrow, K. J. 1962. Economic welfare and the allocation ofresources for inventions. In R. R. Nelson (Ed.), The rateand direction of inventive activity: 609–625. Princeton,NJ: Princeton University Press.

Baer, M., Dirks, K. T., & Nickerson, J. A. In press. Microfoun-dations of strategic problem formulation. Strategic Man-agement Journal.

Baldwin, C. Y., & Clark, K. B. 2000. Design rules: The power ofmodularity. Cambridge, MA: MIT Press.

Baldwin, C. Y., & von Hippel, E. 2011. Modeling a paradigmshift: From producer innovation to user and open collab-orative innovation. Organization Science, 22: 1399–1417.

Barney, J. 1991. Firm resources and sustained competitiveadvantage. Journal of Management, 17: 99–120.

Bonaccorsi, A., & Rossi, C. 2006. Comparing motivations ofindividual programmers and firms to take part in theopen source movement: From community to business.Knowledge, Technology, and Policy, 18(4): 40–64.

Branstetter, L. G., & Sakakibara, M. 2002. When do researchconsortia work well and why? Evidence from Japanesepanel data. American Economic Review, 92: 143–159.

Bresser, R. K., & Harl, J. E. 1986. Collective strategy: Vice orvirtue? Academy of Management Review, 11: 408–427.

Casciaro, T., & Piskorski, M. J. 2005. Power imbalance, mu-tual dependence, and constraint absorption: A closerlook at resource dependence theory. Administrative Sci-ence Quarterly, 50: 167–199.

Cassiman, B., & Veugelers, R. 2002. R&D cooperation andspillovers: Some empirical evidence from Belgium.American Economic Review, 92: 1169–1184.

CED. 2006. Open standards, open source, and open innova-tion: Harnessing the benefits of openness, Committee forEconomic Development. http://www.ced.org/docs/report/report_ecom_openstandards.pdf, accessed May 12, 2007.

Chesbrough, H. W. 2003. Open innovation: The new impera-tive for creating and profiting from technology. Boston:Harvard Business School Press.

Chesbrough, H. W. 2006. Open business models: How tothrive in the new innovation landscape. Cambridge, MA:Harvard Business School Press.

Chesbrough, H. W., & Appleyard, M. M. 2007. Open innova-tion and strategy. California Management Review, 50(1):57–74.


Chesbrough, H. W., & Teece, D. J. 1996. Organizing for inno-vation: When is virtual virtuous? Harvard Business Re-view, 74(1): 65–73.

Christensen, C. M. 1997. The innovator’s dilemma. Boston:Harvard Business School Press.

Clarkson, G., & Toh, P. K. 2010. “Keep out” signs: The role ofdeterrence in the competition for resources. StrategicManagement Journal, 31: 1202–1225.

Cohen, W. M., & Levinthal, D. A. 1990. Absorptive capacity: Anew perspective on learning and innovation. Adminis-trative Science Quarterly, 35: 128–152.

Cook, K. S. 1977. Exchange and power in networks of interor-ganizational relations. Sociological Quarterly, 18: 62–82.

Dahlander, L., & Gann, D. M. 2010. How open is innovation?Research Policy, 39: 699–709.

DiMaggio, P. J., & Powell, W. W. 1983. The iron cage revisited:Institutional isomorphism and collective rationality inorganizational fields. American Sociological Review, 48:147–160.

Dodgson, M., Gann, D. M., & Salter, A. 2007. “In case of fire,please use the elevator”: Simulation technology andorganization in fire engineering. Organization Science,18: 849–864.

Dollinger, M. J. 1990. The evolution of collective strategies infragmented industries. Academy of Management Re-view, 15: 266–285.

Dosi, G. 1982. Technological paradigms and technologicaltrajectories. Research Policy, 11: 147–182.

Dyer, J. H., & Singh, H. 1998. The relational view: Cooperativestrategy and sources of interorganizational competitiveadvantage. Academy of Management Review, 23: 660–679.

Emerson, R. M. 1962. Power-dependence relations. AmericanSociological Review, 27: 31–41.

Farrell, J., & Gallini, N. T. 1988. Second-sourcing as a com-mitment: Monopoly incentives to attract competition.Quarterly Journal of Economics, 103: 673–694.

Fleming, L. 2001. Recombinant uncertainty in technologicalsearch. Management Science, 47: 117–132.

Fosfuri, A., & Rønde, T. 2004. High-tech clusters, technologyspillovers, and trade secret laws. International Journalof Industrial Organization, 22: 45–65.

Foss, N. J., Laursen, K., & Pedersen, T. 2011. Linking customerinteraction and innovation: The mediating role of neworganizational practices. Organization Science, 22: 980–999.

Füller, J. 2010. Refining virtual co-creation from a consumerperspective. California Management Review, 52(2): 98–122.

Galaskiewicz, J. 1985. Interorganizational relations. AnnualReview of Sociology, 11: 281–304.

Galaskiewicz, J., Bielefeld, W., & Myron, D. 2006. Networksand organizational growth: A study of community basednonprofits. Administrative Science Quarterly, 51: 337–380.

Gargiulo, M. 1993. Two-step leverage: Managing constraintin organizational politics. Administrative Science Quar-terly, 38: 1–19.

Garud, R., Jain, S., & Kumaraswamy, A. 2002. Institutionalentrepreneurship in the sponsorship of common techno-logical standards: The case of Sun Microsystems andJava. Academy of Management Journal, 45: 196–214.

Garud, R., & Karnøe, P. 2001. Path dependence and creation.Mahwah, NJ: Lawrence Erlbaum Associates.

Garud, R., & Rappa, M. A. 1994. A socio-cognitive model oftechnology evolution: The case of cochlear implants.Organization Science, 5: 344–362.

George, G., Kotha, R., & Zheng, Y. 2008. Entry into insulardomains: A longitudinal study of knowledge structura-tion and innovation in biotechnology firms. Journal ofManagement Studies, 45: 1448–1474.

Grant, R. M. 1996. Prospering in dynamically-competitiveenvironments: Organizational capability as knowledgeintegration. Organization Science, 7: 375–387.

Gulati, R. 1998. Alliances and networks. Strategic Manage-ment Journal, 19: 293–317.

Gulati, R., & Gargiulo, M. 1999. Where do interorganizationalnetworks come from? American Journal of Sociology,104: 1439–1493.

Gulati, R., Nohria, N., & Zaheer, A. 2000. Strategic networks.Strategic Management Journal, 21: 203–215.

Gulati, R., & Singh, H. 1998. The architecture of cooperation:Managing coordination costs and appropriation con-cerns in strategic alliances. Administrative ScienceQuarterly, 43: 781–814.

Gulati, R., & Sytch, M. 2007. Dependence asymmetry andjoint dependence in interorganizational relationships:Effects of embeddedness on a manufacturer’s perfor-mance in procurement relationships. AdministrativeScience Quarterly, 52: 32–69.

Hallen, B. L. 2008. The causes and consequences of the initialnetwork positions of new organizations: From whom doentrepreneurs receive investments? Administrative Sci-ence Quarterly, 53: 685–718.

Hardy, C., Lawrence, T. B., & Grant, D. 2005. Discourse andcollaboration: The role of conversations and collectiveidentity. Academy of Management Review, 30: 58–77.

Harhoff, D. 1996. Strategic spillovers and incentives for re-search and development. Management Science, 42: 907–925.

Harhoff, D., Henkel, J., & von Hippel, E. 2003. Profiting fromvoluntary information spillovers: How users benefit byfreely revealing their innovations. Research Policy, 32:1753–1769.

Henkel, J. 2004. Open source software from commercialfirms—Tools, complements, and collective invention.Zeitschrift für Betriebswirtschaft-Ergänzungsheft [Jour-nal of Business Administration-Supplementary Issue],74(4): 1–23.

Henkel, J. 2006a. The jukebox mode of innovation: A model ofcommercial open source development. Paper presentedat the DRUID Summer Conference, Copenhagen.


Henkel, J. 2006b. Selective revealing in open innovation pro-cesses: The case of embedded Linux. Research Policy,35: 953–969.

Henkel, J., & Baldwin, C. Y. 2011. Modularity for value appro-priation: Drawing the boundaries of intellectual prop-erty. Finance Working Paper no. 11-054, Harvard Busi-ness School, Boston.

Hillman, A. J., & Hitt, M. A. 1999. Corporate political strategyformulation: A model of approach, participation, andstrategy decisions. Academy of Management Review,24: 825–842.

Hillman, A. J., Withers, M. C., & Collins, B. J. 2009. Resourcedependence theory: A review. Journal of Management,35: 1404–1427.

Jacobides, M. G. 2006. The architecture and design of orga-nizational capabilities. Industrial and CorporateChange, 15: 151–171.

Jacobs, D. 1974. Dependency and vulnerability: An exchangeapproach to the control of organizations. AdministrativeScience Quarterly, 19: 45–59.

Jeppesen, L. B., & Lakhani, K. R. 2010. Marginality and prob-lem-solving effectiveness in broadcast search. Organi-zation Science, 21: 1016–1033.

Jeppesen, L. B., & Molin, M. J. 2003. Consumers as co-developers: Learning and innovation outside the firm.Technology Analysis & Strategic Management, 15: 363–383.

Kale, P., & Singh, H. 2009. Managing strategic alliances:What do we know now, and where do we go from here?Academy of Management Perspectives, 23(3): 45–62.

Kilduff, M., & Brass, D. J. 2010. Organizational social networkresearch: Core ideas and key debates. Academy of Man-agement Annals, 4: 317–357.

Kogut, B., & Zander, U. 1992. Knowledge of the firm, combi-native capabilities, and the replication of technology.Organization Science, 3: 383–397.

Kogut, B., & Zander, U. 1996. What firms do? Coordination,identity, and learning. Organization Science, 7: 502–518.

Kotha, R., George, G., & Srikanth, K. In press. Bridging themutual knowledge gap: Coordination and the commer-cialization of university science. Academy of Manage-ment Journal.

Lakhani, K. R., Jeppesen, L. B., Lohse, P. A., & Panetta, J. A.2007. The value of openness in scientific problem solv-ing. http://www.hbs.edu/research/pdf/07-050.pdf, accessedMarch 20, 2007.

Lakhani, K., & von Hippel, E. 2003. How open source softwareworks: “Free” user-to-user assistance. Research Policy,32: 923–943.

Lakhani, K., & Wolf, B. 2005. Why hackers do what they do:Understanding motivation and effort in free/open sourcesoftware projects. In J. Feller, B. Fitzgerald, S. Hissam, &K. Lakhani (Eds.), Perspectives on free and open sourcesoftware: 3–21. Boston: MIT Press.

Lane, P. J., & Lubatkin, M. 1998. Relative absorptive capacityand interorganizational learning. Strategic Manage-ment Journal, 19: 461–477.

Laursen, K., & Salter, A. 2006. Open for innovation: The role ofopenness in explaining innovation performance amongU.K. manufacturing firms. Strategic Management Jour-nal, 27: 131–150.

Lukes, S. 2005. Power: A radical view (2nd ed.). Basingstoke,UK: Palgrave MacMillan.

MacCormack, A. D., & Herman, K. 2004. Intel research: Ex-ploring the future. Case No. 9-605-051. Boston: HarvardBusiness School Case Services.

Menon, T., & Pfeffer, J. 2003. Valuing internal vs. externalknowledge: Explaining the preference for outsiders.Management Science, 49: 497–513.

Nelson, R. R., & Winter, S. G. 1982. An evolutionary theory ofeconomic change. Cambridge, MA: Harvard UniversityPress.

Nickerson, J. A., & Zenger, T. R. 2004. A knowledge-basedtheory of the firm: The problem-solving perspective. Or-ganization Science, 15: 617–632.

Oliver, C. 1988. The collective strategy framework: An appli-cation to competing predictions of isomorphism. Admin-istrative Science Quarterly, 33: 543–561.

Oliver, C. 1990. Determinants of interorganizational relation-ships: Integration and future directions. Academy ofManagement Review, 15: 241–265.

Pacheco-de-Almeida, G., & Zemsky, P. B. 2012. Some like itfree: Innovators’ strategic use of disclosure to slow downcompetition. Strategic Management Journal, 33: 773–793.

Parmigiani, A., & Rivera-Santos, M. 2011. Clearing a paththrough the forest: A meta-review of interorganizationalrelationships. Journal of Management, 37: 1108–1136.

Pfeffer, J., & Salancik, G. R. 1978. The external control oforganizations: A resource dependence perspective (2003classic ed.). Stanford, CA: Stanford University Press.

Phelps, C., Heidl, R., & Wadhwa, A. In press. Knowledge,networks, and knowledge networks: A review and re-search agenda. Journal of Management.

Phillips, N., Lawrence, T. B., & Hardy, C. 2000. Inter-organizational collaboration and the dynamics of institu-tional fields. Journal of Management Studies, 37: 23–43.

Pisano, G. P., & Teece, D. J. 2007. How to capture value frominnovation: Shaping intellectual property and industryarchitecture. California Management Review, 50(1): 278–296.

Podolny, J. M., & Page, K. L. 1998. Network forms of organi-zation. Annual Review of Sociology, 24: 57–76.

Polidoro, F., & Theeke, M. 2012. Getting competition down toa science: The effects of technological competition onfirms’ scientific publications. Organization Science, 23:1135–1153.

Polidoro, F., & Toh, P. K. 2011. Letting rivals come close orwarding them off? The effects of substitution threat onimitation deterrence. Academy of Management Journal,54: 369–392.

Powell, W. W., Koput, K. W., & Smith-Doerr, L. 1996. Interor-ganizational collaboration and the locus of innovation:


Networks of learning in biotechnology. AdministrativeScience Quarterly, 41: 116–145.

Puranam, P., Singh, H., & Chaudhuri, S. 2009. Integratingacquired capabilities: When structural integration is(un)necessary. Organization Science, 20: 313–328.

Rivkin, J. W. 2000. Imitation of complex strategies. Manage-ment Science, 46: 824–844.

Schilling, M. A., & Phelps, C. C. 2007. Interfirm collaborationnetworks: The impact of large-scale network structureon firm innovation. Management Science, 53: 1113–1126.

Scotchmer, S. 1996. Protecting early innovators: Should sec-ond-generation products be patentable? RAND Journalof Economics, 27: 322–331.

Spence, M. 1973. Job market signaling. Quarterly Journal ofEconomics, 87: 355–374.

Spencer, J. W. 2003. Firms’ knowledge-sharing strategies inthe global innovation system: Empirical evidence fromthe flat panel display industry. Strategic ManagementJournal, 24: 217–233.

Stam, W. 2009. When does community participation enhancethe performance of open source software companies?Research Policy, 38: 1288–1299.

Teece, D. J. 1986. Profiting from technological innovation:Implications for integration, collaboration, licensingand public policy. Research Policy, 15: 285–305.

Todorova, G., & Durisin, B. 2007. Absorptive capacity: Valu-ing a reconceptualization. Academy of Management Re-view, 32: 774–786.

Van de Ven, A. H., & Walker, G. 1984. The dynamics ofinterorganizational coordination. Administrative Sci-ence Quarterly, 29: 598–621.

van den Bosch, F. A. J., Volberda, H. W., & de Boer, M.1999. Coevolution of firm absorptive capacity andknowledge environment: Organizational forms andcombinative capabilities. Organization Science, 10:551–568.

Varian, H. R., & Shapiro, C. 1999. Information rules: A strate-gic guide to the network economy. Boston: Harvard Busi-ness School Press.

von Hippel, E. 1988. The sources of innovation. New York:Oxford University Press.

von Hippel, E., & von Krogh, G. 2003. Open source softwareand the “private-collective” innovation model: Issues fororganization science. Organization Science, 14: 209–233.

von Krogh, G., Wallin, M. W., & Sieg, J. H. 2012. A problem inbecoming: How firms formulate sharable problems forinnovation contests. Paper presented at the ResearchPolicy Special Issue Conference “Open Innovation: NewInsights and Evidence,” London.

West, J. 2003. How open is open enough? Melding proprietaryand open source platform strategies. Research Policy,32: 1259–1285.

Winter, S. G. 1987. Knowledge and competence as strategicassets. In D. J. Teece (Ed.), The competitive challenge:Strategies for industrial innovation and renewal: 159–184. Cambridge, MA: Ballinger.

Yang, H., Phelps, C., & Steensma, H. K. 2010. Learning fromwhat others have learned from you: The effects of knowl-edge spillovers on originating firms. Academy of Man-agement Journal, 53: 371–389.

Zahra, S. A., & George, G. 2002. Absorptive capacity: A re-view, reconceptualization, and extension. Academy ofManagement Review, 27: 185–203.

Oliver Alexy ([email protected]) is professor of strategic entrepreneurship at TUMSchool of Management, Technische Universität München, where he was also awardeda Ph.D. in management. His research focuses on capability emergence, organizationaldesign, and evaluation by relevant audiences and how these factors foster the growthof start-ups and the renewal of established organization, with a particular interest inthe theoretical and managerial implications of user and open innovation.

Gerard George ([email protected]) is the deputy principal for faculty andprograms and professor of innovation and entrepreneurship at Imperial CollegeLondon, where he also serves as the director of the Rajiv Gandhi Centre. He receivedhis Ph.D. from Virginia Commonwealth University. His recent work examines strategicand organizational factors such as business models and organizational design andtheir impact on innovation and performance in technology ventures and emergingmarkets.

Ammon J. Salter ([email protected]) is professor of technology and innovationmanagement at Imperial College London. He also serves as the research director ofthe UK Innovation Research Centre. He completed his doctorate at the Science PolicyResearch Unit (SPRU) at the University of Sussex. His research explores open anddistributed models of innovation, social networks and innovation, and university-industry collaboration.


Cui Bono? The Selective Revealing of Knowledge and Its Implications for Innovative Activity

Documents

Transcript of Cui Bono? The Selective Revealing of Knowledge and Its Implications for Innovative Activity