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Strategic Management JournalStrat. Mgmt. J., 32: 32–54 (2010)

Published online EarlyView in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smj.867

Received 9 July 2008; Final revision received 28 April 2010

ARE JOINT VENTURES POSITIVE SUM GAMES?THE RELATIVE EFFECTS OF COOPERATIVEAND NONCOOPERATIVE BEHAVIOR

M. V. SHYAM KUMAR*The Lally School of Management and Technology, Rensselaer Polytechnic Institute,Troy, New York, U.S.A.

Are joint ventures (JVs) characterized mainly by cooperative behavior or noncooperative behav-ior? In this research, we address this question by examining the interrelationship between thevalues created for two partners when they announce a JV. We argue that, on average, if coop-erative behavior and common benefits are more influential than noncooperative behavior andprivate benefits, there will be a positive association between the values created for the two part-ners. Conversely, if private benefits and noncooperative behavior are more influential, there willbe a negative association as partners derive value at the expense of each other rather than bycreating new opportunities through the JV. Using a sample of 344 JVs we find evidence of apositive association between the values created for the two partners after controlling for variousfactors. This suggests that the stock market perceives JVs to be positive sum games rather thanzero sum games, and that value creation in JVs is mainly attributable to synergies rather thanappropriation of resources. Our analysis also reveals other conditions under which cooperativebehavior and noncooperative behavior become dominant, such as the strength of the resourcesof the two partners, product market competition, and JV experience. Copyright 2010 JohnWiley & Sons, Ltd.

INTRODUCTION

Joint ventures (JVs), on average, create value forparent firms. This has been documented in a num-ber of studies examining stock price reactions toJV announcements using an event study approach(e.g., McConnell and Nantell, 1985; Woolridge andSnow, 1990; Koh and Venkatraman, 1991; Balakr-ishnan and Koza, 1993; Madhavan and Prescott,1995; Anand and Khanna, 2000; Merchant andSchendel, 2000; Kale, Dyer, and Singh, 2002).Broadly speaking, the literature has found that

Keywords: joint ventures; value creation; transaction costeconomics; resource-based view; event studies∗ Correspondence to: M. V. Shyam Kumar, The Lally School ofManagement and Technology, Rensselaer Polytechnic Institute,110 8th Street, Troy, NY 12180, U.S.A.E-mail: kumarm2@ rpi.edu

value creation is enhanced when a JV is relatedto existing businesses and when a parent firm pos-sesses experience with interfirm collaboration.

Although this literature has contributed impor-tant insights, it assumes that the value creationexperienced by parent firms in JVs is mainly theresult of synergies and common benefits. Giventheir shared governance structure, JVs are associ-ated not only with synergies and common benefitsbut also with significant private benefits. Theseprivate benefits arise as parent firms appropriateresources from each other and exploit them out-side the JV. The existence of private benefits andthe inherent tension between cooperative and non-cooperative behavior in JVs in turn raises someimportant questions about their efficiency as anorganizational form: do collaborative behavior andcommon benefits play a more significant role in

Copyright 2010 John Wiley & Sons, Ltd.

Are Joint Ventures Positive Sum Games? 33

explaining value creation in JVs when comparedto private benefits? Conversely, are noncooperativebehavior and private benefits more influential thancommon benefits? Under what conditions do eachtype of behavior and benefits become dominant inimpacting value creation?

In this study we attempt to shed light onthe above questions. While previous research hasfocused on the value created for individual par-ent firms in JVs, our focus is on the interrela-tionship between the values created for the twoparents under various conditions. The logic behindour approach is that the interrelationship betweenthe values created provides greater insight into theextent of various types of behavior when comparedto the value created for an individual parent.1 Thus,if cooperative behavior is dominant in JVs, thenboth firms are likely to gain simultaneously whena JV is announced, as new opportunities are cre-ated through the collaboration. On the other hand,if noncooperative behavior and private benefits aredominant in JVs, then one partner would gain atthe expense of the other when a JV is announced,as each firm appropriates the other’s resources andopportunities and as common benefits assume arelatively less significant role.2 Hence, by examin-ing the interrelationship between the values createdfor the two partners we gain a better understand-ing of whether JVs are mainly associated withcooperative behavior as opposed to noncooperativebehavior. Ultimately, this informs us whether JVsare positive sum games as opposed to zero sumgames, and whether they are an efficient organi-zational form for sharing resources between firmsunder various conditions.

1 To clarify further, two firms may enter into a JV and jointlyinvest in a negative net present value project. While such aninvestment may lead to negative returns for both parent firms,it may nevertheless be characterized by cooperative behaviorand may lead to a positive interrelationship between the valuescreated. Conversely, two firms may enter into a JV and mainlyengage in noncooperative behavior. In such instances, both firmsmay derive positive value from the JV. But the underlyinginterrelationship between values created may be negative sincevalue is being derived at the expense of the partner rather than bycreating new opportunities. These issues are discussed in furtherdetail below.2 In an approach parallel to ours, Berkovitch and Narayanan(1993) make a similar argument in the case of mergers andacquisitions. They note that if synergies are the main sourceof value, then acquirers and targets will gain simultaneouslywhen an acquisition is announced. On the other hand, if agencymotives are dominant, then targets are likely to gain at theexpense of acquirers.

To address our research questions, the empir-ical method we adopt is to use a simultaneousequation approach with the values created for thetwo partners at the time of the JV announcementserving as the endogenous dependent variables(Kalaignanam, Shankar, and Varadarajan, 2007).This approach provides us with the advantagesof (1) controlling for other factors while address-ing the question of whether value creation occursjointly or at the expense of the partner in a JV;(2) modeling bilateral causal relationships betweenthe values created rather than unidirectional rela-tionships, and (3) developing unbiased parameterestimates in the presence of potential endogeneity.

The paper proceeds as follows: in the nextsection we discuss our theory and hypotheses; inthe following section we describe our methods;next we outline our results along with variousrobustness checks, and in the final section we con-clude with a discussion.

THEORY AND HYPOTHESES

JVs provide firms with a means for combin-ing resources with value creating complemen-tary resources possessed by partners (Teece, 1986;Hennart, 1988). These complementary resourcesmay include technical knowledge, upstream/down-stream production knowledge, financial resources,and knowledge related to a target market suchas customer characteristics, distribution channels,knowledge of culture and institutions, and so forth.The advantages of JVs arise because often thevalue-creating complementary resources possessedby the partner tend to be imperfectly mobileand imperfectly imitable in nature (Chi, 1994).Under these circumstances, both internal develop-ment and acquisitions become relatively costly asalternatives. Internal development becomes costlybecause building the complementary knowledgetypically tends to be time consuming due topath dependencies and time compression disec-onomies. Acquisitions become costly for poten-tially two reasons. First, the desired complemen-tary knowledge may constitute only a subset ofthe partner’s operations (Hennart, 1988) and maybe comingled and inseparable from other unde-sired assets (Hennart and Reddy, 1997; Reuerand Koza, 2000). Second, if the complementaryknowledge is tacit in nature—a characteristic thatis typical of imperfectly mobile and inimitable

Copyright 2010 John Wiley & Sons, Ltd. Strat. Mgmt. J., 32: 32–54 (2010)DOI: 10.1002/smj

34 M. V. Shyam Kumar

know-how—valuation of the partner as an acqui-sition target is impeded by information asym-metry (Chi, 1994). A JV provides a solution tothese problems by allowing a firm to access requi-site complementary knowledge relatively quicklybefore external opportunities are dissipated byrivals (Kogut, 1991; Chi, 2000; Rothaermel, 2001;Kumar, 2005) and by avoiding the need to acquirethe partner in the face of valuation difficulties andinseparability (Balakrishnan and Koza, 1993).

While JVs offer these advantages when com-pared to internal development and acquisitions,they also enjoy certain superior governance fea-tures compared to market contracts (such as in-licensing, out-licensing and cross-licensing of com-plementary knowledge bases). When two firmsattempt to combine their imperfectly mobile andimperfectly imitable complementary knowledgebases, there often arises the need to make invest-ments that are cospecialized in nature. However,investments in such cospecialized assets also cre-ate the potential for holdup and ex post quasirent appropriation. When compared to market con-tracts, JVs alleviate such holdup problems byapportioning residual claimancy and residual con-trol over the joint resources through shared equityand decision rights (Chi, 1994). Further, when theknowledge bases being combined are tacit, poten-tial licensees are often unable to ascertain the truevalue of the knowledge and potential licensors areunable to assess what the costs of knowledge trans-fer are likely to be in arms-length transactions.3

Under these circumstances, once again joint own-ership and decision rights become advantageous asparties are no longer rewarded on the basis of thequantity of information transferred, but on com-pliance with managerial directives (Hennart, 1988:366) and final product market performance.

But while JVs provide these various advantages,they also entail costs that are unique to them asan organizational form due to their shared gover-nance and decision-making structure. Partly thesecosts arise from the need to coordinate activitiesacross multiple firms (Gulati and Singh, 1998).

3 As Postrel (2002) notes, situations requiring mutual understand-ing of another entity’s (a division or, in this case, another firm)knowledge base are relatively rare in the economy. When knowl-edge is tacit, however, developing such mutual understandingmay be essential for firms since otherwise they may not beable to forecast the value that can be derived from combiningtheir knowledge bases and the attendant costs. Under the cir-cumstances, ‘black boxing’ (Postrel, 2002) through arms-lengthcontracts such as licensing may not be effective.

In addition, JVs also expose firms to the threatof opportunism and appropriation of resourcesby partners. These hazards are particularly pro-nounced considering that while JVs facilitate thetransfer of relatively valuable knowledge basescompared to market contracts (Hennart, 1988;Anand and Khanna, 2000), their partial control andownership structure also expose these very knowl-edge bases to appropriation by the partner.

There are at least two mechanisms by whichfirms appropriate resources from their partners inJVs (Lavie, 2006). The first is through spillovers(Inkpen and Dinur, 1998; Ahuja, 2000). Giventheir shared decision-making structure, JVs maynot only facilitate the combination of complemen-tary knowledge bases but may also provide oppor-tunities for a partner to closely observe a firm’scompetencies and overcome barriers to imitationcreated due to causal ambiguity. This may resultin the transfer of resources beyond what a firm mayhave intended to share through the venture. A sec-ond form of appropriation arises when a partnerwillfully extracts resources from a firm over thecourse of the JV, beginning with the contract nego-tiation stage. This form of opportunism has also ledprevious researchers to use various metaphors todescribe JVs, such as prisoner’s dilemma (Parkhe,1993), learning race (Hamel, 1991), and Trojanhorses (Reich and Mankin, 1986). Both types ofappropriation mechanisms may necessitate signif-icant managerial effort by the firm so that it isable to capture the resources and realize associatedbenefits outside the JV.

While these various costs and benefits high-light the tension between cooperative behavior onthe one hand and noncooperative behavior on theother, to further understand the relative effects ofthese two types of behavior on value creation, fol-lowing Khanna, Gulati, and Nohria (1998), thegains derived by a firm from a JV can be parti-tioned into two components: private benefits andcommon benefits (Dyer, Singh, and Kale, 2008).As Khanna et al. note:

Private benefits are those that a firm can earnunilaterally by picking up skills from its part-ner and applying them to its own operations inareas unrelated to the alliance activities. Commonbenefits are those that accrue to each partner inan alliance from the collective application of thelearning that both firms go through as a conse-quence of being part of the alliance; these areobtained from operations in areas of the firm that



are related to the alliance (Khanna et al., 1998:195).

Thus while private benefits stem chiefly fromappropriability hazards of various forms, commonbenefits derive mainly from the creation of jointvalue through sharing of resources.

Although previous research has tended to treatprivate benefits and common benefits as beingindependent of each other, we propose that froma theoretical standpoint the two types of bene-fits are also likely to be fundamentally interre-lated and are likely to influence each other inimportant ways. JVs can be viewed as investmentdecisions with a fixed and predetermined level ofmanagerial resources allocated to them by parentfirms (Inkpen, 2000). This fixed level of man-agerial resources, which comprise the scientists,engineers, and other managerial and administrativepersonnel transferred to the JV (Inkpen, 2000), arethen subdivided between cooperative behavior andthe creation of common benefits on the one handand noncooperative behavior and the appropriationof resources on the other (Khanna et al., 1998). Tothe extent that each firm is constrained by a fixedlevel of managerial resources, an increase in theallocation of effort toward noncooperative behav-ior by one partner would reduce the resourcesavailable for cooperative behavior and commonbenefits for both partners in the JV. Thus a fixedlevel of managerial resources implies that there islikely to be a trade-off effect between cooperativebehavior and common benefits on the one handand noncooperative behavior and private benefitson the other as firms divide their resources betweenthese two activities.

The basic trade-off between common benefitsand private benefits has also been noted by otherauthors in previous research. Hamel (1991: 91)observes that many Western firms adopted defen-sive attitudes on discovering their Japanese part-ner’s intent to appropriate resources, which led tooverall lower learning and unsatisfactory perfor-mance of their ventures. Parkhe (1993) makes asimilar point when he notes that when there isa potential for high private benefits, value willbe eroded in the JV as partners set up variouscontractual safeguards that increase coordinationcosts (cf. Reuer and Arino, 2007). Larsson et al.are explicit about the trade-offs inherent betweencreating common benefits and attempts to deriveprivate benefits. Thus they note:

. . .most socio-economic interaction involves theindividual trade-off decisions of each actorregarding how much of his/her limited effortsare to be spent on collaborating and inter-nally competing, respectively. While the collec-tive focus on integrative collaboration wouldproduce a plus-sum game where all actors canwin, the focus on distributive competition actu-ally results in a minus-sum game due to thediversion of productive efforts to distributiveinfighting (Larsson et al., 1998: 288).

To formalize these points and examine the impli-cations of cooperative and noncooperative behav-ior for value creation, consider two firms, 1 and 2,entering into a JV with each other. Assume thatthe returns to cooperative behavior are positiveand are increasing at a constant rate with effortinvested. This assumption implies that ceterisparibus, devoting greater effort toward coopera-tive behavior and common benefits is not coun-terproductive unless very high levels of effort arereached. In addition, assume that the returns tononcooperative behavior are also positive and con-stantly initially increasing with effort. Howeveras the effort devoted to noncooperative behav-ior increases further, the marginal returns decreasebeyond a point. This is likely to occur, for exam-ple, as the partner begins to withhold its resourcesand builds various safeguards to prevent furtherappropriation when it detects opportunistic behav-ior (Arino and de la Torre, 1998). Under theseassumptions, the return to effort devoted to coop-erative behavior is an upward sloping straightline, while the return to effort devoted to nonco-operative behavior is a concave curve. In addi-tion to these assumptions, assume that both firmsinitially face a marginal return with respect toeffort devoted to cooperative behavior that is lowerthan the marginal return with respect to effortdevoted to noncooperative behavior. This assump-tion makes it efficient for both firms to devotesome effort to private benefits, and absent thisassumption pure cooperation and common benefitswould be the optimal outcome. These conditionstogether imply that each firm in the JV would allo-cate an effort level to noncooperative behavior andprivate benefits up to the point that the marginalreturn from this effort equals the marginal returnfrom the effort devoted to cooperative behaviorand common benefits. After this effort level hasbeen allocated to deriving private benefits, the



residual effort in each firm will be devoted tocommon benefits given the constant returns to thiseffort. These conditions also highlight that therewould be a trade-off between private benefits andcommon benefits. Given a fixed level of manage-rial resources, a unit increase in the effort devotedto noncooperative behavior would decrease theeffort available for cooperative behavior, and con-sequently private benefits would increase whilecommon benefits would decrease and vice versa.

The simple model outlined above bears somesimilarity to models that attempt to flesh out thetension between allocating resources to coordinat-ing actions across divisions, and conducting spe-cialized activities within a particular division ofa multiunit firm (e.g, Postrel, 2002; Kretschmerand Puranam, 2008). In these models, special-ization can potentially be counterproductive bymaking activities less similar across divisions,thereby increasing coordination difficulties (e.g.Kretschmer and Puranam, 2008). This creates athreshold level for integration and coordinationbelow which collaboration incentives across divi-sions can actually be detrimental to overall pro-ductivity. Similar to these models, our assump-tions suggest that the existence of private benefitscreates a threshold level of effort below whichfirms would be unwilling to divert effort towardcommon benefits. This threshold increases as themarginal returns on private benefits increase, and ifa firm does not have adequate resources to exceedthis threshold, then pure noncooperative behaviorwould be efficient and the shared incentive struc-ture of JVs would have a minimal effect.

Based on these arguments, we may write thevalue derived by the two firms from the JV asfollows:

V1 = Vc + V1p + V1d − V2d (1)

V2 = Vc + V2p − V1d + V2d (2)

In Equations 1 and 2, V1 and V2 are the totalvalues derived by each firm from the JV. In theseequations, Vc denotes the common benefits derivedby each firm. Assuming equal equity shares, thecommon benefits are also equally divided, the totalcommon benefits being 2Vc. Equations 1 and 2also decompose private benefits of each firm intodifferent components. V1p and V2p are private ben-efits that can be captured without destroying valuedirectly for the other partner in the JV, that is, they

are non-rivalrous in nature. These benefits couldarise, for example, by observing and learning rela-tively diffused practices from the partner, such asthe organization of specific production processes,inventory management, market and country spe-cific knowledge, and so forth. Equally critically,V1p and V2p may also arise as each firm takesskills and resources created in the JV and exploitsthem outside the cooperation without sharing thebenefits with the partner. Thus, these benefits mayarise as firms attempt to maximize their shares ofthe joint value created beyond what was negoti-ated ex ante through the equity shares. While V1p

and V2p may occur either through willful extractionor through spillovers, in either instance they arelikely to require significant managerial resourcesfor their realization as the partner diverts effortfrom cooperative efforts to learning and capturingthe associated gains.4

In contrast with V1p and V2p, V1d and V2d

constitute private benefits that are value destroy-ing in their impact on the other partner, that is,they are rivalrous in nature. These benefits mayarise from various sources. One potential source iswhen a partner appropriates relatively proprietaryresources, including resources that are not directlydeployed to the JV. Once again, this may occureither through spillovers or willful extraction (suchas poaching employees, stealing secrets, etc.) whileentailing significant managerial effort. In this case,while a partner may overtly claim to be interestedin creating joint value and synergies, appropriatingthe other firm’s proprietary resources may consti-tute another significant motive for entering into theventure. Another potential source of V1d and V2d iswhen a firm attempts to capture a disproportionateshare of common benefits by using its bargainingpower to negotiate a higher equity share ex ante.This would directly reduce the partner’s share ofthe common benefits, while increasing the firm’sshare of these benefits. Note that while V1d has apositive impact on V1, it has a negative impact onV2. Similarly V2d has a positive impact on V2, anda negative impact on V1. Thus V1d and V2d consti-tute a wealth transfer between the two firms. Themain point to be highlighted is that V1d and V2d

have a dual effect: not only do they directly destroyvalue for the other partner due to their rivalrous

4 We thank the anonymous reviewers for highlighting this par-ticular source of private benefit and its implications for commonbenefits.



nature but they also suppress common benefits inthe JV by diverting managerial effort away fromcooperative behavior and the creation of synergiesfor each firm. This occurs because when the twofirms devote managerial resources and effort tocapture V1d and V2d there is lesser residual effortleft in both firms to create common benefits. Incontrast with V1d and V2d, the value suppressingeffects of V1p and V2p on the other firm occur onlythrough the diversion of effort from cooperativebehavior rather than direct value reduction.

Equations 1 and 2 can be rewritten to recog-nize that if the total managerial effort allocated byeach firm to the JV is fixed, then there are likelyto be potential trade-offs between various typesof private benefits and common benefits. To theextent that both value destroying and non-valuedestroying private benefits draw ‘from the samebucket’ of managerial resources, lesser resourceswould be available for deriving common benefitswhen both types of private benefits are derived.Thus, although V1p and V2p are non-rivalrous innature, in effect they become rivalrous with eachother and with Vc in a JV since the effort levelfor each firm is fixed and the resources requiredto derive V1p, V2p, and Vc are utilized from thesame pool of resources. Consequently, V1p andV2p also have a rivalrous impact on firm 2 andfirm 1’s value creation respectively despite theirnon-rivalrous nature. Accordingly we may rewritecommon benefits, Vc, as follows, taking into con-sideration that all four components V1p, V2p, V1d,and V2d would have a negative impact on it:

Vc = f(−V1p, −V2p, −V1d, −V2d, Ø) (3)

where Ø constitutes a set of parameters relatingcommon benefits to the total residual managerialeffort left in both firms after efforts have beendevoted to appropriating private benefits by eachfirm. Ø would also be a function of various fac-tors such as the potential synergies that can berealized by combining the resources of the twofirms per unit of managerial effort, and the attrac-tiveness of the JV’s focal business and industry.In Equation 3, Vc is decreasing with increases innon-rivalrous and rivalrous private benefits V1p,V2p, and V1d and V2d. In addition, ceteris paribus,Vc is increasing with increases in Ø. SubstitutingEquation 3 into Equations 2 and 1 we get:

V1 = f(−V1p, −V2p, −V1d,

− V2d, Ø) + V1p + V1d − V2d (4)

V2 = f(−V1p, −V2p, −V1d,

− V2d, Ø) + V2p − V1d + V2d (5)

Equations 4 and 5 provide the following impli-cations. If the primary source of value in JVs isthe private benefits earned by the two firms, thenin a sample of JVs, V1 and V2 would be nega-tively correlated. This is because V1 would stemmainly from V1p and V1d, which directly and indi-rectly (through common benefits) reduce V2 andvice versa. Consequently, higher values of V1 (V2)in the sample would be associated with lower val-ues of V2 (V1).5 Note that V1 and V2 may bepositive despite being negatively correlated. Thismay occur, for example, when the two firms cre-ate some common benefits in the JV (Khannaet al., 1998: 200) while mainly deriving varioustypes of private benefits (for example, firm 1 maybe appropriating non-value destroying and non-rivalrous market knowledge and applying it else-where, while firm 2 may be appropriating rivalrousproprietary technologies from firm 1). Under theseconditions, the JV primarily becomes a mechanismto appropriate resources for the two firms ratherthan a means to cooperate and create synergies(Hamel, 1991).

In contrast if common benefits are the mainsource of value in JVs, then V1 and V2 wouldbe positively correlated. This is because V1 wouldmainly arise from the effect of the parameter Ø,which simultaneously increases V2. Hence a highervalue of V1 (V2) in the sample would be associatedwith a higher value of V2 (V1). Analogous tothe above arguments, however, it is possible thatcommon benefits may be negative despite bothfirms devoting substantial effort to cooperativebehavior if, for example, potential synergies arethemselves weak and are not enough to offsetcoordination costs, and the JV’s industry is notstructurally attractive.

5 It is, of course, not necessary that both firms will derive theirvalue mainly from private benefits. There could be situationswhere one firm may be deriving most of its value from pri-vate benefits, while the other firm is chiefly deriving commonbenefits. If this were the case, we would expect that in ourempirical analyses the impact of the value of one partner onthe other would vary. For example, firm 1’s value may have anegative impact on firm 2’s value, but not vice versa. While wedo not highlight this asymmetry in our theoretical discussion andhypotheses, our empirical tests do not preclude the possibility.As we discuss subsequently, we do find some evidence of thisasymmetry in our sample.



Given these various effects, in a semi-strongefficient stock market when JVs are announced,the values derived by two partners would reflectthe market’s expectations of the future dynam-ics of the collaboration and the relative extentof cooperative and noncooperative efforts. If, onaverage, the market expects cooperative behaviorand common benefits to be dominant in JVs, andthat firms allocate their effort mainly to derivingthese benefits as opposed to private benefits, thenthe two partners are likely to experience valuecreation simultaneously when a JV is announced.Thus:

Hypothesis 1: On average, if cooperative behav-ior and common benefits outweigh the effectsof noncooperative behavior and private bene-fits, there will be a positive association betweenthe values derived by two partners when a JV isannounced.

On the other hand, if, on average, noncoopera-tive behavior and private benefits are more domi-nant in JVs than cooperative behavior and commonbenefits, then the gains of one partner would benegatively correlated with the other as each partnerattempts to exploit existing resources and opportu-nities rather than to create new opportunities andsynergies through the JV. This would lead to ele-ments of a zero sum game as opposed to a positivesum game as there is both a dissipation of jointvalue and common benefits and a partial wealthtransfer between partners. Hence:

Hypothesis 1-alt: On average, if noncooper-ative behavior and private benefits outweighthe effects of cooperative behavior and com-mon benefits, there will be a negative associa-tion between the values derived by two partnerswhen a JV is announced.

Hypotheses 1 and 1-alt test the overall effectsof cooperative behavior versus noncooperativebehavior in JVs.6 We now turn to the specific con-ditions under which these two types of behavior

6 So far we have considered the following possibilities: (1) a JVdominated by cooperative behavior leading to a positive associ-ation and positive returns for both partners; (2) a JV dominatedby cooperative behavior, but the investment opportunity is poor,leading to a positive association but negative returns for bothpartners; and (3) a JV dominated by noncooperative behavior butboth firms maintain sufficient common benefits so that they may

are likely to be more influential. Previous research(e.g., Park and Russo, 1996) has examined thedegree of competition between partners as onefactor that affects the extent of cooperative behav-ior. Below we examine two additional factors: thestrength of resources of the two firms, and theirJV experience.

One factor that may influence whether coop-erative behavior and common benefits dominatenoncooperative behavior and private benefits is thestrength of the resources that both partners bring tothe venture. The resource-based view (RBV) sug-gests that the value created in a JV would be higherwhen both partners in the dyad possess relativelyunique and valuable resources. Under these con-ditions the combination of resources is likely toyield higher rents as the two firms find new andunexplored opportunities through the JV, and asthe JV provides an efficient mechanism for com-bining their causally ambiguous knowledge bases(Chi, 1994). In contrast, when both partners inthe dyad are not equally matched in terms of thestrength of their resources, and if any one partnerpossesses relatively weak resources, the tendencyto derive private benefits is likely to be higher.This is because the differential in the quality ofresources may motivate the partner with weakerresources to divert greater effort toward appropri-ation and noncooperative behavior (Kumar, 2010).As a result the partner with stronger resourcesmay withhold its resources, thereby causing anoverall shift in focus in the JV from cooperativebehavior to noncooperative behavior. In terms ofEquations 4 and 5, we expect that when both firmsbring valuable resources to the JV, private bene-fits V1p, V2p, and V1d and V2d would all tend tobe relatively high. But at the same time, sinceboth firms possess valuable resources, the returnsfrom devoting managerial resources to cooper-ative behavior as reflected by the parameter Øare also likely to be high. Hence, the motiva-tion to pursue synergies may be stronger than thetendency for subgoal pursuit and private benefits

continue to appropriate resources, leading to a negative associ-ation but positive returns to both partners. In addition to thesepossibilities, a fourth possibility is a JV where there is a purelearning race and where partners engage in tit-for-tat behavior. Inthese JVs we expect the returns to the two partners as well as theassociation between returns to be negative as both firms attemptto appropriate as much value as possible from the partner, andthere is a pure wealth transfer between the two firms. We thankan anonymous reviewer for highlighting this possibility.



(Kretschmer and Puranam, 2008) leading to thefollowing hypothesis:

Hypothesis 2: Value creation will be positivelyassociated between two partners in a JV whenboth firms possess relatively strong resources.

Another factor that is likely to influence whethercooperative behavior and synergies are eclipsedby noncooperative behavior and private benefits isthe extent of product market competition betweenfirms in the dyad. Park and Russo (1996) suggestthat JVs between relatively direct competitors tendto be fragile and unstable for two reasons. First,the incentives to appropriate resources and gainan advantage are particularly high when two com-petitors join forces since this is likely to be thedominant strategy for both players. Consequently,any attempts to appropriate resources are likelyto be quickly reciprocated with similar behaviorpotentially devolving the JV into a learning race ortit-for-tat behavior. Second, the ability to appropri-ate resources for both partners is also high becauseeach firm is familiar with the other’s operationsand hence has a high degree of absorptive capacitywith respect to the other’s underlying knowledge(Mowery, Oxley, and Silverman, 1996; Lane andLubatkin, 1998; Tsang, 2000). Given these twofactors, the capital market’s ex ante expectationmight be that JVs between firms that are in closelyrelated product markets are likely to be character-ized mainly by noncooperative behavior and pri-vate benefits as opposed to synergies and commonbenefits. In terms of Equations 4 and 5, in JVsbetween competitors the non-value destroying pri-vate benefits V1p and V2p are likely to be significantas firms learn various nonproprietary knowledgeand processes pertaining to the industry from eachother. However, we also expect value destroyingprivate benefits V1d and V2d to be relatively high inthese JVs compared to other types of JVs as firmshave high incentives as well as high absorptivecapacity to appropriate their direct competitors’proprietary knowledge base. This type of appropri-ation would lead to a wealth transfer between thepartners that would accentuate the negative corre-lation between the values created and the effectsof noncooperative behavior. Hence:

Hypothesis 3: Value creation will be negativelyassociated between two partners in a JV when

the two firms are in closely related businessesand are relatively direct competitors.

Another factor that may influence the behaviorof firms within a JV is their prior experience withinterfirm collaboration (Anand and Khanna, 2000;Merchant and Schendel, 2000). Experience withJVs may have an impact along various dimen-sions. First, it may help a firm strike the rightbalance between divulging knowledge on the onehand and protecting it from appropriation on theother through the development of isolating mech-anisms (Simonin, 1999; Kale, Singh, and Perl-mutter, 2000). Second, it may also help a firmformulate better JV contracts ex ante. This mayenable it to anticipate various environmental con-tingencies where its resources can be appropriated,and to preemptively formulate contracts that atten-uate incentives for appropriation (Kumar, 2010).

While these mechanisms may promote cooper-ative behavior, we suggest that experience withJVs also allows firms to gain an appreciation ofthe delicate balance that exists between value cre-ation on the one hand and value appropriation onthe other in interfirm collaboration. Firms withexperience in operating JVs are more likely to rec-ognize the importance of devoting efforts towardcommon benefits and cooperative behavior in sus-taining a mutually beneficial relationship from theoutset. These firms are also likely to understand theimportance of factors such as creating the right ini-tial conditions and making appropriate adjustmentsover time to realize the goals of the JV (Arinoand de la Torre, 1998). In contrast, firms with lessexperience in operating JVs may not have sucha well-developed understanding of the value cre-ation logic of JVs and may have a tendency toadopt competitive postures in the relationship. Interms of Equations 4 and 5, we expect that whenJV experience is high among both firms it wouldlead to lesser effort being devoted to V1p, V2p, andV1d and V2d, and greater effort being devoted tocooperative behavior and deriving common ben-efits. Based on these arguments we suggest thefollowing hypothesis:

Hypothesis 4: Value creation will be positivelyassociated between two partners in a JV whenboth firms possess JV experience.



METHODS

Sample and event study methods

To test Hypotheses 1–4, the first step was to con-duct an event study analysis of a suitable sampleof JV announcements to measure value creation.Our data source in identifying the sample wasthe Securities Data Corporation (SDC) database onmergers, acquisitions, and alliances. The databasehas been used extensively in previous JV research(e.g., Anand and Khanna 2000; Gulati and Wang,2003; Sampson, 2005). Using this database, weretrieved information on JVs beginning with thefirst year, which was 1985, up to the year 2003.At this stage we restricted ourselves to two part-ner JVs where the JV was a distinct and separateentity from the parent firms, and where both part-ners were based in the United States. This wasdone so that stock price data could be retrievedfrom the Center for Research in Stock Prices(CRSP) database. For these two partner JVs wethen retrieved information pertaining to the dateof the announcement, partner names, equity sharesheld, and the primary Standard Industrial Classifi-cation (SIC) code assigned to the JV.

Next, we obtained stock price data for both part-ners on and around the announcement date fromCRSP. In addition, we also obtained various sec-ondary data items pertaining to Tobin’s q and firmsize (discussed further below) from Compustat.After combining all data items we were left with688 firms belonging to 344 JVs in the sample.

The event study was conducted by estimating themarket model over the period −250 to −50 withthe announcement date acting as day 0. We usedthe software EVENTUS with the CRSP equallyweighted index serving as the market return. Pre-diction errors were then calculated for the window[−1,0] for each partner. After calculating the pre-diction errors we obtained the value created foreach partner by multiplying the market value atthe year-end preceding the formation of the JV bythe prediction error.7 The average prediction errorover the [−1,0] period for the 688 firms in oursample was 0.75 percent and the average value

7 We also used market value at day −5 as opposed to theyear-end preceding the year of the announcement of the JV tocalculate value creation. Our results remained unchanged. Belowwe report results using the previous year-end market value sincethis is consistent with the measurement of our other independentvariables, such as firm size.

created was USD 33 MN. These figures are con-sistent with previous research (e.g., McConnell andNantell, 1985), which indicates that our sample andevent study results were valid and reliable. Follow-ing Kalaignanam et al. (2007) we used the valuescreated for the two partners over the [−1,0] periodin each JV as the endogenous dependent variablesin our study.8

Empirical approach

In this research, our objective was to understandthe relative effects of cooperative and noncooper-ative behavior in JVs. However, since the com-ponents Ø, V1p, V2p, V1d, and V2d in Equations 4and 5 cannot be observed directly, our argumentis that we can infer the relative effects of coop-erative and noncooperative behavior as anticipatedby the stock market by looking at how the val-ues of the two firms are inter related. FollowingEquations 4 and 5, if we consider two firms, 1 and2, entering into a JV, we can test our hypothe-ses by examining how the value created for firm 1(V1) is correlated with the value created for firm2 (V2) and vice versa. We therefore specified thefollowing two empirical equations:

V1 = g (V2, control variables,

identifying variables) (6)

V2 = h (V1, control variables,

identifying variables) (7)

where g and h are assumed to be linear func-tions. After specifying equations of the form 6 and7 we then estimated them simultaneously to testour hypotheses. A simultaneous equation approachallows for the possibility that the values derived bythe two partners mutually influence each other andare endogenously determined (given that each part-ner’s payoffs depend not only on its own manage-rial effort, but also the allocation of the partner’s

8 In addition to the dollar values, we also conducted robustnesstests with percentage abnormal returns as the endogenous depen-dent variables. While the simultaneous equation models did notproduce a good fit with these variables, in no instance were theresults contradictory to the results we present with dollar values.In general, regressions with abnormal returns do not producea good fit because these errors are residuals from a previousregression (the market model; Servaes, 1991). In our case, thisproblem was compounded because we were examining the inter-relationship between two prediction errors in our regressions.



managerial effort toward private and common ben-efits), rather than assuming that there is a causalrelationship in any particular direction, such as,for example, assuming only V1 impacts V2 andnot vice versa. Second, it enables controlling forother variables when examining the interrelation-ship between V1 and V2. Finally, by using appro-priate methods such as three-stage least squares(3SLS) to estimate these equations we also avoidthe potential biases in parameter estimates thatmay be introduced by ordinary least squares (OLS)given the non-recursive nature of these equationsand the correlations of the endogenous variableswith the error terms.

Having decided on a simultaneous equationapproach to test our hypotheses, the next impor-tant issue we needed to address was how do wedivide partners into groups so that we can specifyEquations 6 and 7 and examine the interrelation-ship between the values derived by the two firms?From a theoretical standpoint, what is the appro-priate criterion or characteristic that can be used toassign partners into separate groups for purposesof understanding the relative effects of cooperativeand noncooperative behavior?9 Unlike acquisitionswhere there is a natural distinction between thetwo firms in a dyad (acquirers and targets), JVsare indistinguishable dyads (Kenny et al., 2006)where there is no criterion as such by which firmscan be distinguished.10 Thus, based on theoreticalconsiderations an appropriate variable needs to beidentified by which partners can then be dividedinto groups for purposes of testing Equations 6 and7 (Kenny et al., 2006).

In our analysis we used Tobin’s q to distin-guish between the two partners in each JV dyad.Tobin’s q is a measure of the value of the intan-gible resources possessed by a firm (Villalonga,2004). The higher the Tobin’s q, the higher thevalue of intangible resources. Based on Tobin’s q,we assigned firms in the 344 JVs into two groups:

9 Put differently, the question we needed to address was: whattypes of firms do we put into Group 1 and what type dowe put into Group 2? Do we assign firms randomly or isthere a theoretically meaningful criterion that we need to applywhen assigning firms into each of the two groups across the344 JVs? This is critical because ultimately it would impactthe relationship observed between the values once we estimateEquations 6 and 7.10 To clarify further, an example of a distinguishable dyad is ahusband and wife or a boss and employee. Correspondingly, anindistinguishable dyad is a gay couple or two coworkers (Kenny,Kashy, and Cook, 2006: 6).

firms with higher Tobin’s q than the partner inthe dyad (the HI group) and firms with lowerTobin’s q than the partner in the dyad (the LOgroup). Once having grouped firms using this cri-terion, we then examined the association betweenthe values derived by the HI and LO group byestimating the system of simultaneous equationsrepresented by 6 and 7. Tobin’s q was used asthe criterion to distinguish between the partnerssince it fundamentally reflects the value of theresources of the two firms, and hence captures thedirection in which resources are likely to be appro-priated in a JV. Thus it enables testing whetherfirms with less valuable resources are appropriatingvalue at the expense of their partners, or whethervalue creation is occurring simultaneously for bothfirms in JVs. In contrast, using an alternative cri-terion such as firm size to distinguish betweenpartners may be not be as suitable for testing theinterrelationship since differences in size may notalways capture the direction in which appropria-tion is likely to take place. Larger firms can havestronger resources and a higher Tobin’s q thantheir smaller partners, as was the case with 127out of 344 cases in our sample, and grouping part-ners based on size may confound the relationshipbetween V1 and V2 (since in some cases Group 1firms would have a higher Tobin’s q than Group 2firms and vice versa). For this reason, we decidedto use Tobin’s q as our criterion. We did, how-ever, conduct robustness checks by distinguishingbetween partners based on size. In addition we alsoconducted a robustness check by assigning firmsrandomly into Groups 1 and 2. As discussed inthe next section, the results with respect to ouroverall hypothesis (Hypothesis 1 and Hypothesis1-alt) about the relative effects of cooperative andnoncooperative behavior remained unchanged withthese different group assignments.

Tobin’s q was measured as the sum of marketvalue of equity, short- and long-term debt, pre-ferred stock at liquidating value, and book valueof convertible debt normalized by book value oftotal assets (Perfect and Wiles, 1994).

Identifying and control variables

In estimating the above simultaneous equations,another important issue was that we needed toinclude independent variables in 6 that did notappear in 7 and vice versa for identification pur-poses. Recent research suggests that the value



derived by a firm from a JV depends not only on itsown characteristics but also on the partner’s char-acteristics (e.g., Stuart, 2000; Gulati and Wang,2003; Lavie, 2007). Thus, in deciding our spec-ifications of Equations 6 and 7 it was necessaryto consider what firm characteristics to include ineach of the two equations as well as what partnercharacteristics to include and exclude in a par-ticular equation. Following previous research, weexpected that a focal firm’s value derived from aJV would depend not only upon its own resourcesbut also upon the resources that the partner bringsto the JV. Partnering with a firm with strongresources may create more value for a focal firmthrough, for example, signaling effects (Lerner andMerges, 1998) and spillover effects such as repu-tation spillovers (Kumar, 2010). Hence, it is nec-essary to control for these effects since they maypotentially impact the interrelationship between thevalues created for the two firms independent ofcooperative and noncooperative behavior. To con-trol for these effects, we included the Tobin’s q ofthe partner in Equations 6 and 7. In addition, wealso included the industry adjusted Tobin’s q of afocal firm as a control in the two equations. Thereason we used a firm’s industry adjusted Tobin’sq was to avoid spurious correlations between rawTobin’s q and the dependent variable (value cre-ation) since both variables are based on the firm’smarket value. The industry adjusted Tobin’s q mea-sure was calculated as the Tobin’s q of the focalfirm minus the average Tobin’s q of all firmsreporting the same SIC code as their principalactivity as the focal firm in Compustat. Indus-try adjusted q was added as a control because,ceteris paribus, firms with more valuable intangi-ble resources may experience lower returns froma JV given the appropriability hazards that thesefirms are likely to face. Conversely, these firmsmay also experience higher returns due to thepotential synergies they may generate in the JV.

In addition to a firm’s industry adjusted q andpartner q, we also included firm size and partnersize as controls in each equation. Size was includedas a control since, ceteris paribus, larger firmsmay exercise their market power, thereby creatinggreater value for themselves as well as the partnerin the JV. This may create a positive correlationbetween the values derived by the two partners.Hence, firm size was added along with partnersize in Equations 6 and 7 to control for this effect.In addition, we also added controls for a focal

firm’s prior experience with JVs and the related-ness of the JV with each parent. Independent ofthe dynamics of cooperative and noncooperativebehavior, ceteris paribus, firms with greater expe-rience in JVs are likely to realize greater valuefrom their cooperation (Anand and Khanna, 2000).Similarly, related JVs may create greater valuethan unrelated JVs (Koh and Venkatraman, 1991).JV experience was measured as a count of allprior JVs undertaken by a firm listed in the SDCdatabase. A similar measure has also been usedby Anand and Khanna (2000) and Zollo, Reuer,and Singh (2002). JV relatedness was calculatedas a distance measure (Balakrishnan and Koza,1993) given by the absolute value of the differ-ence in SIC code of the core business of the parent(obtained from Compustat) and the SIC code of theJV (obtained from the SDC database).

Model specification and hypotheses tests

We specified the following two simultaneousequations to test our hypotheses:

LOVALUE = a0 + a1 HIVALUE + a2 LOQADJ

+ a3 HIQ + a4 LOSIZE + a5 HISIZE + a6

LOEXPERIENCE + a7 LODISTANCE + ε (8)

HIVALUE = b0 + b1 LOVALUE + b2 LOQ

+ b3 HIQADJ + b4 LOSIZE

+ b5 HISIZE + b6 HIEXPERIENCE

+ b7 HIDISTANCE + ε (9)

Where:LOVALUE = Value derived by the low Tobin’s

q firm (i.e., Tobin’s q < partner’s Tobin’s q)over the [−1,0] period obtained by multiplyingabnormal returns with market value

HIVALUE = Value derived by the high Tobin’sq firm (i.e., Tobin’s q>partner’s Tobin’s q) overthe [−1,0] period obtained by multiplying abnor-mal returns with market value

LOQ= Tobin’s q of the firm whose Q islower in the dyad (LOQ<HIQ); Correspondingly,LOQADJ= industry adjusted Tobin’s q (LOQ−industry average Q)

HIQ= Tobin’s q of the firm whose Q is higher inthe dyad (HIQ>LOQ); Correspondingly,HIQADJ= industry adjusted Tobin’s q (HIQ−industry average Q)



LOSIZE= size of the firm with lower Tobin’s qHISIZE= size of the firm with higher Tobin’s qLOEXPERIENCE= experience of the firm with

lower Tobin’s qHIEXPERIENCE= experience of the firm with

higher Tobin’s qLODISTANCE= relatedness of the JV with

respect to the low Tobin’s q firmHIDISTANCE= relatedness of the JV with

respect to the high Tobin’s q firmε = error termsIn the above two simultaneous equations,

LOVALUE and HIVALUE are the endogenousdependent variables. Thus the coefficients of inter-est in our hypotheses tests are the coefficientsa1 and b1. As discussed earlier, Equations 8 and9 each contain identifying variables that do notappear in the other equation (all variables apartfrom the two Ssize variables). Thus both equationsare overidentified.

Hypothesis 1 suggests that if cooperative behav-ior and common benefits are more influentialthan noncooperative behavior and private bene-fits in JVs, then, on average, the values derivedby two partners will be positively associated. Sup-port for Hypothesis 1 implies that the coefficientof HIVALUE a1 will be >0 in Equation 8 andthe coefficient of LOVALUE b1 will be >0 inEquation 9. In contrast Hypothesis 1-alt suggeststhat if noncooperative behavior and private ben-efits are more influential and stronger, then therewill be a negative association between the valuesof the two partners. Support for Hypothesis 1-altimplies a1 <0 and b1 <0.

Hypothesis 2 suggests that the value derivedby the two partners will be positively interrelatedwhen both firms bring relatively strong resourcesto the JV. To test this hypothesis, we identified thesubset of JVs in the sample where both the lowTobin’s q firm and the high Tobin’s q firm had qvalues above the median. The median Tobin’s qof the LO group was 0.92 and the median Tobin’sq of the HI group was 1.53. The rationale wasthat in this subsample both firms are likely to pos-sess relatively strong resources when comparedto the rest of the JVs. Hypothesis 2 implies thatin this subsample a1 >0 and b1 >0. Hypothe-sis 3 suggests that when the relatedness of part-ners is high and they are direct competitors, therewould be a tendency for noncooperative behav-ior to eclipse cooperative behavior. To test thishypothesis, we calculated the absolute value of the

difference between the SIC codes of the core busi-ness of the two partners. The logic was that thecloser the SIC codes and the distance between thetwo partners, the more likely they will be directcompetitors. Thus in the subsample where the dif-ference was below the median of the 344 JVs, weexpected a1 <0 and b1 <0.

Finally Hypothesis 4 suggests that when bothfirms in the dyad have JV experience, coopera-tive behavior will tend to dominate noncoopera-tive behavior. This is because experienced firmsare likely to possess a better understanding of thevalue creation logic of JVs and the delicate balancethat exists between cooperative and noncoopera-tive behavior. To test the hypothesis, we examinedthe subsample where both the low Tobin’s q firmand the high Tobin’s q firm had above median JVexperience. Our expectation was that in this sub-sample a1 >0 and b1 >0.

We used 3SLS to estimate Equations 8 and9. The reason we preferred 3SLS over alterna-tives such as two-stage least squares (2SLS) wasbecause the endogenous dependent variables in thetwo equations pertain to the value associated withannouncing the same JV. Hence, there were likelyto be correlations between the error terms acrossthe two equations. 3SLS takes this aspect intoaccount when estimating parameters. In addition3SLS also produces more efficient estimates com-pared to 2SLS.

RESULTS

Event study results

As an initial test of our hypotheses, we began byexamining the average values created for the LOand HI groups over the [−1,0] period and the totalvalue created in the JV over [−1,0] period basedon our event study analysis. Earlier, we had arguedthat to assess the effects of cooperative behaviorand noncooperative behavior in JVs it is necessaryto look at the interrelationship between the valuescreated for the two partners rather than the averagevalues created. This is because private benefits canalso potentially result in positive gains to both part-ners. Conversely, both partners can earn negativereturns despite best cooperative intentions if syn-ergies are weak and the JV is a poor investment.These limitations notwithstanding, the average val-ues created in various subsamples can be used to



Table 1. Value creation for high Q and low Q Partners

Panel A: Value creation over [−1,0] (USD Mn)

Sample Value createdfor LOgroup

Value createdfor HIgroup

Total valuecreated in

the JV

Full sample 22.89 43.39 66.28LOQ>median, HIQ>median 120.74∗ −9.69 111.05Partners direct competitors −8.12 −98.81 −106.93Both partners with JV experience 117.51+ 49.97 167.48

Panel B: Number of positives/negatives

Sample Number of dyads insample/ sample size(expected signs of

value creation)

Number of cases insample/sample size(expected sign of

value creation)

Full sample 105/344∗ 189/344+

(+/+) (+)LOQ>median, HIQ>median 46/130∗∗ 74/130

(+/+) (+)Partners direct competitors 46/173 86/173

(−,−) (−)Both partners with JV experience 33/100+ 53/100

(+,+) (+)

+ indicates p<0.10, two-tailed∗ indicates p<0.05, two-tailed∗∗ indicates p<0.01, two-tailed∗∗∗ indicates p<0.001, two-tailed

gain initial insight into our data and our hypothe-ses. Table 1, Panel A presents the results. Usingthis data, we conducted t tests to examine whetherthe average values created were significantly abovezero or below zero for the two partners and the JVas a whole. The significance of these t tests is alsoindicated in Table 1.

The t tests suggest that in the overall sample, thevalue created for the LO group ($ 22.89 Mn) andHI group ($ 43.39 Mn) were both insignificantlydifferent from zero, while the total value created ($66.28 Mn) was marginally significant and greaterthan 0 (p=0.13). Table 1, Panel A also showsthat in the subsample where both firms had strongresources, only the LO group experienced signifi-cant value creation while the HI group’s value andthe total value created were insignificant. In thesubsample where both partners were direct com-petitors, value creation was negatively signed andinsignificant for both firms. Finally, in the subsam-ple where both firms had JV experience, the LOgroup experienced significant positive value cre-ation, while the value created for the HI group and

the total value created were insignificant. Overallthese results only weakly support our hypothesesand the argument that, on average, JVs are charac-terized by cooperative behavior as opposed to non-cooperative behavior. However, as noted above,the average value created does not always reflectthe relative effects of the two types of behaviorand a test of our hypotheses calls for estimatingEquations 8 and 9 and examining the coefficientsa1 and b1 in various subsamples, rather than exam-ining average value creation.

Another way to address the issue of coopera-tive versus noncooperative behavior is to examinethe proportion of JVs where both partners experi-enced positive returns versus negative returns andthe proportion of JVs where the total value cre-ated was positive versus negative, rather than theaverage value created (Kumar, 2007). While thisis a nonparametric approach that is based on thedistribution of the signs of the values rather thanthe averages, its advantages are that it is less sen-sitive to the impact of random disturbances thatmay affect value creation, such as for example



the signaling effects of the JV (which may haveimpacted the values observed in Panel A). Table 1,Panel B presents the results. To assess signifi-cance, we conducted binomial tests comparing theobserved proportion in various subsamples withthe expected proportion under the null hypothe-sis that value creation occurs randomly in JVs.The expected proportion is 0.25 (0.5 × 0.5) underthe null hypothesis that both partners experiencepositive/negative returns (since there is 0.5 proba-bility that any one partner would experience pos-itive/negative returns under random occurrence).Correspondingly, the expected proportion is 0.5that total value creation in the JV will be posi-tive/negative in a sample of firms if value creationoccurs randomly. As shown in Panel B, when weexamine the signs of the value created for bothpartners, there is support for the notion that the twopartners experience positive returns simultaneouslyin JVs. The number of cases where both partnersgained positive value was 105 out of 344, a propor-tion of 0.31, which was significantly greater thanthe expected proportion of 0.25. The number ofcases where total value created was positive was189 out of 344, which was significantly greaterthan 0.5. Table 1, Panel B also shows that bothpartners experience positive returns when they pos-sess strong resources, and when they have JVexperience. However, these results are not corrobo-rated by the number of positives/negatives for totalvalue created. In addition, the results are also notconsistent with our expectations in the subsamplewhere both partners were direct competitors. Over-all, these results are more supportive of the notionthat JVs are dominated by cooperative behaviorand are positive sum games. But once again, theydo not tell us whether the positive gains for the twopartners are the result of private benefits or com-mon benefits. We now turn to more systematic testsof our hypotheses by estimating the simultaneousequations represented by 8 and 9.

Regression results

Table 2 presents the correlations between our vari-ous dependent and independent variables inEquations 8 and 9. By and large, the correla-tions were within the acceptable range with theexception of the HIQ and the HIQADJ variableswhere the correlation was 0.92. The high corre-lation suggested that the two variables did not Tabl

e2.

Sum

mar

yst

atis

tics

and

corr

elat

ions

Mea

nL

OV

AL

UE

HIV

AL

UE

LO

QH

IQL

OQ

AD

JH

IQA

DJ

LO

SIZ

EH

ISIZ

EL

OE

XP

HIE

XP

LO

DIS

TH

IDIS

T

LO

VA

LU

E22

.890

1H

IVA

LU

E43

.400

0.22

91

LO

Q1.

122

0.03

3−0

.010

1H

IQ2.

380

0.28

90.

262

0.48

1L

OQ

AD

J−0

.860

−0.1

95−0

.046

0.09

−0.0

541

HIQ

AD

J0.

620.

356

0.27

10.

380.

922

0.11

1L

OSI

ZE

1357

9.72

−0.0

020.

226

−0.1

50.

070

−0.1

60.

014

1H

ISIZ

E70

99.4

30.

025

−0.0

39−0

.11

−0.0

970.

00−0

.067

0.17

61

LO

EX

P3.

330.

130

0.12

7−0

.03

0.11

2−0

.33

0.06

10.

527

0.04

1H

IEX

P2.

550.

023

0.04

00.

000.

124

−0.1

00.

116

0.10

70.

330.

146

1L

OD

IST

1325

−0.0

150.

065

0.04

0.06

70.

030.

027

0.15

6−0

.04

0.07

9−0

.031

1H

IDIS

T13

80−0

.068

0.04

10.

180.

119

−0.0

40.

100

−0.0

320.

08−0

.032

0.11

10.

256

1



Table 3. 3SLS estimates

I: Full model estimates (n=344) II: Partners with strong resources (n=130)

Coeff S.E P>|z| Coeff S.E P>|z|LOVALUE equationHIVALUE 1.015∗∗∗ 0.28 0.000 0.47∗∗∗ 0.13 0.000HIQ −17.16 38.53 0.65 72.026∗∗∗ 19.52 0.000LOQADJ −5.42 17.87 0.76 −65.76∗∗ 21.19 0.002LOQ SIZE −0.012∗∗ 0.004 0.002 0.006 0.004 0.167HIQSIZE 0.008+ 0.004 0.06 0.007 0.006 0.22LOQEXP 2.18 4.76 0.65 −0.88 10.45 0.93LOQDISTANCE −0.002 0.01 0.83 −0.02 0.028 0.46CONSTANT 115.01 130.4 0.37 −271.766∗ 137.56 0.05P Value .000 .000HIVALUE equationLOVALUE 1.08∗∗∗ 0.19 0.000 1.04∗∗∗ 0.27 0.000LOQ 30.54 65.21 0.64 −16.71 95.11 0.86HIQIND 8.72 45.92 0.84 −308.45∗ 146.56 0.04LOQSIZE 0.012∗∗∗ 0.003 0.000 −0.002 0.01 0.802HIQSIZE −0.008+ 0.005 0.084 −0.009 0.01 0.46HIQEXP −0.74 6.68 0.91 −29.16 31.66 0.36HIQDISTANCE −0.005 0.02 0.77 0.001 0.042 0.99CONSTANT −124.42 145.37 0.39 757.78 388.11 0.05P Value .000 .000

+ indicates p<0.10, two-tailed ∗ indicates p<0.05, two-tailed∗∗ indicates p<0.01, two-tailed ∗∗∗ indicates p<0.001, two-tailed

contain unique information and were weak instru-ments. To address this concern, we substitutedthe industry adjusted q variable with the indus-try average q (HIQIND). The correlation betweenHIQ and HIQIND was lower at 0.69 but was highenough that we could still use HIQIND as a proxyfor the high Tobin’s q firm’s resources. Whileour results remain substantively similar, in theremainder of our analysis we present results withindustry average q (HIQIND) in place of industryadjusted q (HIQADJ) in Equation 9. Table 2 alsoshows the bivariate correlation between the valuesderived by the two partners over the [−1,0] period(LOVALUE and HIVALUE). As shown, the cor-relation was significant and positive at 0.22, whichprovides preliminary support for Hypothesis 1 andthe argument that, on average, cooperative behav-ior dominates noncooperative behavior in JVs.

As a next step in our analysis, we tested forendogeneity of the two structural equations, 8 and9, using the Durbin-Wu-Hausman test. If this testis rejected, then it implies OLS can be used toestimate the two equations and that the parameterswould not be biased. The test was implementedusing Stata’s ivendog command. The test showedstrong evidence of endogeneity in both equations

(p<0.001). From a theoretical standpoint the impli-cation of this result is that rather than beingindependent, the values created for the two part-ners when a JV is announced are simultaneouslyand endogenously determined and mutually influ-ence each other. Next, since our equations con-tained more than one identifying variable and wereoveridentified, we examined whether our instru-ments were valid and were correctly excludedfrom each equation by conducting the Sargan’s test(Davidson and McKinnon, 1993). This test weaklyaccepted the null hypotheses that our instrumentswere valid and were correctly excluded in bothequations (p=0.052 and p=0.045).11

Table 3, Column I presents the results afterestimating Equations 9 and 10 using 3SLS. Hy-pothesis 1 implies that there will be a positiverelationship between HIVALUE and LOVALUE.Hypothesis 1-alt, in contrast, implies there willbe a negative relationship between HIVALUE andLOVALUE. As shown in Table 3, the coefficients

11 The higher the p value, the greater the confidence in the nullhypothesis that the instruments were correctly excluded. Whilethe test results were weak, from a theoretical standpoint ourchoice of variables to include and exclude seemed reasonableand, hence, we present our results using these specifications.




I: Closely related partners (n=172) II: Distant partners (n=172)

Coeff S.E P>|z| Coeff S.E P>|z|LOVALUE equationHIVALUE −0.21 0.15 0.17 1.09∗∗∗ 0.26 .000HIQ 36.38+ 19.8 0.07 −75.46 55.64 0.17LOQADJ 24.47 34.06 0.47 19.81 23.55 0.4LOQ SIZE −0.001 0.002 0.56 −0.017∗∗∗ 0.005 0.001HIQSIZE −0.003 0.004 0.52 −0.002 0.005 0.76LOQEXP 4.96 6.92 0.47 7.23 9.45 0.44LOQDISTANCE −0.103+ 0.06 0.07 0.004 0.08 0.83CONSTANT −43.57 53.44 0.41 335.54 198.24 0.09P Value .000 .000

HIVALUE equationLOVALUE −1.59∗∗ 0.51 0.002 1.23∗∗∗ 0.18 .000LOQ 121.32 184.72 0.51 42.2 77.61 0.58HIQIND −86.05 162.89 0.59 97.39+ 59.06 0.09LOQSIZE 0.001 0.001 0.86 0.01∗∗∗ 0.00 .000HIQSIZE −0.01+ 0.01 0.09 0.01 0.01 0.93HIQEXP −33.87 39.84 0.39 4.10 15.14 0.78HIQDISTANCE 0.04 0.14 0.77 0.02 0.02 0.45CONSTANT 49.84 226.53 0.82 −427.67 202.43 0.04P Value .000 .000


of both HIVALUE and LOVALUE are significantand positive in the two structural equations. ThusHypothesis 1 was supported. These results sug-gest that, on average, the stock market perceivescooperative behavior and common benefits to bethe main source of value creation in JVs, and thatthese effects outweigh the effects of noncoopera-tive behavior and private benefits. Thus, the marketviews JVs to be positive sum games rather thanzero sum games, and to be an efficient organiza-tional form for sharing resources between firms.Hypotheses 2 implies that there will be a positiveassociation between HIVALUE and LOVALUEwhen both firms in the JV possess strong resources.As argued earlier, when both firms possess strongresources, the mutual gains from cooperation arelikely to be high leading to a positive sum game.To test the hypothesis we conducted the 3SLSregression in the subsample where the q valueswere above median for both firms in the dyadamong the 344 JVs (n=130). As shown in ColumnII of Table 3, in this subsample LOVALUE andHIVALUE were positively associated with eachother in both equations. Thus Hypothesis 2 wassupported. As a further test of this hypothesis,

we conducted the analyses for the three sub-groups where one or both firms had q valuesbelow median. In these three subgroups, we foundinsignificant associations between LOVALUE andHIVALUE, which lends further support to Hypoth-esis 2.

Hypothesis 3 implies there will be a negativeassociation between LOVALUE and HIVALUE aspartner firms become more related in terms oftheir core businesses, and as they become rela-tively direct competitors. To test the hypothesis,we split our sample based on the median value ofthe difference in SIC codes between the principalbusinesses of the two partners. Table 4, Column Ipresents the results. The results suggest that in thesubsample where the partners were relatively closeto each other, LOVALUE had a negative impact onHIVALUE. However, while HIVALUE was neg-atively signed, the coefficient was insignificant.These results provide partial support for Hypoth-esis 3. In addition, they also imply that in oursample when partners were relatively close com-petitors to each other, the ratio of private to com-mon benefits may have been relatively greater forthe low Tobin’s q firm. This may have caused it to




I: Firms with JVexperience (n=100)

II: High Tobin’s q firms withlow JV experience (n= 186)

Coeff S.E P>|z| Coeff S.E P>|z|LOVALUE equationHIVALUE 0.51∗∗∗ 0.14 0.00 −0.56∗∗ 0.18 0.003HIQ 42.61 48.30 0.37 31.614∗ 15.02 0.04LOQADJ −29.08 24.67 0.23 −59.89∗∗∗ 18.48 0.001LOQ SIZE −0.01+ 0.00 0.06 −0.001 0.002 0.54HIQSIZE 0.01 0.01 0.12 0.001 0.004 0.86LOQEXP 8.28 8.83 0.34 −3.58 6.78 0.59LOQDISTANCE 0.02 0.03 0.48 −0.003 0.011 0.78CONSTANT −61.79 230.07 0.78 −93.01 59.9 0.12P Value .000 .000HIVALUE equationLOVALUE 1.58∗∗∗ 0.32 0.00 −0.71∗∗∗ 0.22 0.001LOQ −41.18 281.64 0.88 −48.43 33.96 0.15HIQIND −162.81 175.99 0.35 151.31∗∗∗ 30.14 0.000LOQSIZE 0.01∗ 0.01 0.03 0.001 0.002 0.53HIQSIZE −0.02 0.01 0.15 0.001 0.003 0.94HIQEXP −13.63 26.20 0.6 −6.02 42.57 0.88HIQDISTANCE −0.01 0.06 0.83 0.001 0.012 0.98CONSTANT 180.22 584.25 0.75 −195.14 75.46 0.01P Value .000 .000


appropriate value to some extent at the expense ofthe high Tobin’s q firm, whereas the reverse wasnot necessarily true. To test the hypothesis further,we also analyzed subsamples where the distancebetween the core businesses of the two partnersin terms of the SIC code was lower than themedian value in the full sample. Since the medianvalue was fairly high at 1550, we chose distancevalues of less than 1,000 (i.e., the two partnersare in the same two-digit code; n=126) and 500(n=103). The results (not reported) showed a sig-nificant negative association between LOVALUEand HIVALUE in both these subsamples indicat-ing support for Hypothesis 3. As a further testof this hypothesis, Column II in Table 4 presentsthe results pertaining to the subsample where thepartners were relatively distant and unrelated toeach other. As shown, LOVALUE and HIVALUEwere positively associated with each other in bothequations. Hence, as the degree of competitiondecreased, synergies and common benefits beganto significantly outweigh the effects of noncooper-ative behavior and private benefits leading to posi-tive gains for both partners (Park and Russo, 1996).These results were also obtained in subsamples

where the distance in SIC codes was greater than1,000 and 500 indicating consistent support forHypothesis 3.

Finally, Hypothesis 4 suggests when both firmspossess JV experience, cooperative behavior islikely to become more dominant than noncoop-erative behavior leading to a positive correlationbetween the values created. To test the hypothe-sis we identified the subsample where both firmshad above median JV experience. Table 5, ColumnI presents the results. Consistent with Hypothe-sis 4, the relationship between LOVALUE andHIVALUE was positive and significant when bothfirms had above median JV experience. To testthis hypothesis further, we also created threesubsamples where either one or both partnershad below median JV experience. This analysisrevealed that the relationship between LOVALUEand HIVALUE was insignificant when the lowTobin’s q firm had below median experience(results not presented). Interestingly when the highTobin’s q firm had below median JV experi-ence, LOVALUE and HIVALUE were negativelyassociated in both equations. These results are pre-sented in Column II of Table 5. Thus, it appears




I: Groups based on size II: Groups based on random assignment

Coeff S.E P>|z| Coeff S.E P>|z|Partner1 equationVALUE2 1.11∗∗∗ 0.30 0.000 1.06∗∗ 0.4 0.008Q2 60.20 37.21 0.11 −19.68 45.65 0.66Q1ADJ 28.24 23.71 0.23 −78.44 75.9 0.3Q1 SIZE −0.01 0.01 0.43 −0.01∗∗ 0.01 0.006Q2SIZE 0.01∗∗∗ 0.00 0.000 0.01 0.01 0.45Q1EXP 0.22 18.14 0.99 −7.09 14.93 0.64Q1DISTANCE 0.01 0.02 0.61 0.03 0.03 0.36CONSTANT −156.62 90.63 0.08 34.32 131.61 0.79P Value .000 .000Partner2 equationVALUE1 1.13∗∗∗ 0.27 0.000 0.75∗∗ 0.27 0.005Q1 −38.86 34.57 0.26 42.3+ 24.86 0.09Q2ADJ −61.72 51.10 0.23 39.68 21.4 0.06Q1SIZE 0.01 0.01 0.69 0.01∗∗∗ 0.002 0.000Q2SIZE −0.01∗∗∗ 0.00 0.001 −0.004 0.003 0.25Q2EXP −4.34 7.10 0.54 17.85 11.07 0.11Q2DISTANCE −0.01 0.02 0.72 −0.01 0.021 0.64CONSTANT 188.85 143.86 0.18 −38.42 90.69 0.67P Value .000 .000


that the experience of the firm with more valu-able resources plays an important role in creat-ing the proper collaborative atmosphere in JVs.Finally LOVALUE and HIVALUE were insignifi-cantly related when both firms had below medianJV experience (results not reported). Hence, therewas support for Hypothesis 4 and the role of expe-rience of both partners in creating a positive sumgame in JVs.

In terms of our control variables, by and largeour results indicate that the value derived by thelow q firm in the dyad was positively associatedwith the Tobin’s q of the high q firm. The reverse,however, was not true indicating the presence ofreputation spillovers and knowledge transfers fromthe high q firm to the low q firm (Kumar, 2010).Another effect we observed was that while firmsize was negatively associated with value cre-ation (McConnell and Nantell, 1985), partner sizewas positively associated. Hence there appearedto be positive value creation effects associatedwith partnering with larger firms. These resultsfurther support the argument that a firm’s valuefrom a JV doesn’t just depend upon its ownresources and characteristics but also the part-ner’s characteristics, and that partnering with larger

firms can confer benefits such as monopoly powerand can signal quality of resources (Lerner andMerges, 1998).

While Tables 3–5 present the main results ofour hypotheses tests, we also conducted variousrobustness tests of our results. We did this in twomain ways: by dividing firms into groups basedon their size instead of their Tobin’s q, and byassigning firms randomly into groups. Once hav-ing divided firms into groups based on these twocriteria, we then constructed all other independentvariables accordingly and reestimated Equations 8and 9. Table 6 Column I presents the results afterdividing partners based on their size. In Column I,Partner 1 comprises all firms that were smaller insize in the JV dyad, while Partner 2 comprises thelarger firm in the dyad. Consistent with Hypothesis1, the results showed that there was a positive asso-ciation between the values derived by larger andsmaller partners in both equations. These resultsfurther corroborate the results presented in Table 3and highlight the relatively stronger effect of coop-erative behavior and common benefits in JVs whencompared to noncooperative behavior and privatebenefits. However, although the overall associa-tions in both equations were positive, we did not



find support for our hypothesized relationships invarious subsamples when we used size to distin-guish between partners. In terms of testing theeffects of randomly assigning partners into groups,we conducted 20 such random assignments andestimated Equations 8 and 9 in each of these sam-ples. In nine out of the 20 random samples, the val-ues of the two partners were positively correlatedwith each other, indicating support for Hypothesis1. Table 6 Column II presents the results of esti-mating Equations 8 and 9 in one of these randomsamples. In the remaining 11 samples, while onepartner’s value had a positive impact on the other,the reverse relationship was insignificant.

In addition to these various steps, we conductedtwo additional analyses to ascertain the robustnessof our results. First we included dummy variablesfor the JV industry in Equations 8 and 9. Theobjective was to control for variations in the attrac-tiveness of the JV investment and its impact on thecorrelation between LOVALUE and HIVALUE. Todo this, we included industry dummies for var-ious economic sectors such as mining, construc-tion, wholesale trade, retail trade, transportationand services, other services, chemicals, electronicsand other manufacturing. Although these dummiescapture industry effects at a very aggregate level,lack of sufficient number of observations in vari-ous two-digit categories prevented us from using amore fine-grained approach. The results remainedunchanged when we used these dummy variablesas controls, and there continued to be a positivecorrelation between LOVALUE and HIVALUE inthe full sample. Next, we also conducted regres-sions using the total value created in the JV asour dependent variable. The rationale was thatif JVs are characterized by greater cooperativebehavior when both partners bring strong resources(Hypothesis 2) and have JV experience (Hypothe-sis 4), then the total value created should be pos-itively associated with the sum of the Tobin’s qof the two partners in the JV and the sum of JVexperience due to higher common benefits. Con-versely, if JVs are characterized by noncoopera-tive behavior when partners are direct competitors(Hypothesis 3), then the total value created shouldbe negatively associated with the distance betweenthe core businesses of the two partners due to lowercommon benefits. Results (not reported) indicatedthat after controlling for factors such as parent firmsize, total value creation was positively associated

with the sum of the Tobin’s q of the two part-ners, but was insignificantly related to the sumof experience and distance. These results indicatesupport for Hypothesis 2, but not for Hypotheses 3and 4. Total value creation provides an alternativeway to test our hypotheses, but it does not fullyreflect the relative effects of cooperative and non-cooperative behavior for two reasons. First, whenthe values of the two partners are summed, thewealth transfer effects represented by V1d and V2d

in Equations 4 and 5 are, in effect, canceled out,which does not take into consideration the fullimpact of noncooperative behavior in total valuecreation. Second, total value created also containsthe non-value destroying private benefits appropri-ated by the two firms. Thus, when the individualvalues of the parents are summed, these privatebenefits may offset any lower common benefits inthe JV due to noncooperative behavior, making itdifficult to discern whether higher total value cre-ation is due to higher common benefits or higherprivate benefits.12

DISCUSSION AND CONCLUSION

The results of our study indicate that in the JVsin our sample, on average, the effects of coopera-tive behavior and common benefits were strongerthan noncooperative behavior and private benefits.This was evidenced by the finding that after con-trolling for various factors, the values created forthe two partners at the time of the JV announce-ment were positively associated with each other.Over the last few decades, scholarly research hashighlighted that JVs create value for individualparent firms. However there has been compara-tively lesser evidence pertaining to whether thisvalue stems from cooperative behavior and com-mon benefits or resource appropriation and privatebenefits. Our study sheds light on this aspect byusing a simultaneous equation framework to exam-ine how the values derived by two partners areinterrelated. Thus, our study shows that, on aver-age, JVs create value simultaneously for the twoparent firms and are positive sum games ratherthan zero sum games. In doing so, it attests to

12 The total value creation variable also does not allow for adirect test of the interrelationship between the values created forthe two partners.



the efficacy of JVs as a means for accessing com-plementary resources and creating value for bothpartners rather than as a means for any one part-ner to appropriate resources and derive value at theexpense of the other.

But though our results indicate that, on average,JVs are positive sum games, we also found var-ious contingencies that influenced to what extentvalue creation occurred simultaneously for the twopartners. One important contingency we identi-fied was the strength of the resources of firmsand how equally matched the two firms werealong this dimension in the dyad. Our resultssuggest that value creation occurred simultane-ously when the two partners possessed relativelystrong resources as measured by Tobin’s q. Incontrast, value creation did not occur simultane-ously when one or both firms possessed relativelyweak resources. This result points to the funda-mental role of resources in influencing the dynam-ics of interfirm collaboration. Previous researchhas tested the impact of the resources of networkpartners on value creation (Lavie, 2007), but itdoes not examine how the distribution of resourceswithin the dyad impacts the dynamics of a focalJV. Our findings fill this gap in the literature byshowing that cooperative forces eclipse competi-tion when both firms possess valuable resources.In doing so, they also point to a critical differ-ence between acquisitions and JVs. In the case ofacquisitions (e.g., Lang, Stulz, and Walking, 1989;Servaes, 1991) it has been consistently found thatvalue creation is enhanced when firms with highTobin’s q acquire firms with low Tobin’s q. Butthe results of our study suggest that the same doesnot apply to JVs because, unlike acquisitions, JVsoffer a significant potential for resource appropri-ation and private benefits. This shifts incentivesaway from cooperative behavior to noncoopera-tive behavior when there is high differential in thevalue of resources, thereby leading to elements ofa zero sum game.

Another important contingency our study iden-tifies is the degree of relatedness and product mar-ket competition between parent firms. Previousresearch has theoretically identified product mar-ket competition as an important factor that influ-ences the degree of cooperative behavior in a JV(e.g., Hamel, 1991; Inkpen and Beamish, 1997;Khanna, 1998). Evidence in this regard has mainlycome from qualitative studies and from studies that

have examined the duration of the JV as a func-tion of various factors (Park and Russo, 1996).Our research complements these studies and showsthat the degree of product market competition hasan important impact on whether value is createdsimultaneously or at the expense of the partnerin a JV. In doing so, it points to the hazardsof partnering with direct competitors despite thepotential for value creation through various mech-anisms such as economies of scale. Relatedly, ourstudy also shows that partnering with firms thatare not direct competitors and are distant can bevalue creating for both partners. This finding alsocorroborates the argument that JVs can be moreefficient than acquisitions when they involve mod-erately unrelated parent firms since they not onlyreduce information asymmetry (Balakrishnan andKoza, 1993) and provide nonoverlapping knowl-edge bases (Sampson, 2007) but also because theyare associated with greater incentives for coopera-tive behavior.

In addition to these findings, our research alsoemphasizes the importance of experience in settingthe tone for a JV and the dynamics of interfirm col-laboration. Previous research has mainly focusedon the experience of a focal firm on the valuederived from a JV (see Hoang and Rothaermel,2005, for an exception). Our findings suggest thatJV experience of both firms in the dyad is crit-ical in promoting collaboration. Experience withinterfirm collaboration plays an important role notonly in framing JV contracts and developing mech-anisms to protect resources (Kale et al., 2000)but also in understanding the subtle value cre-ation logic of JVs. Firms that lack experience maybe tempted to allocate greater effort to immedi-ate and short-term outcomes such as appropriatingresources to the detriment of long-term cooperativeoutcomes, leading to zero sum outcomes. This wasevidenced in our research in the subsample wherehigh Tobin’s q firms lacked JV experience. In thissubsample, there was a strong negative associa-tion between the values derived by the two part-ners, which suggests that inexperience may lead togreater emphasis on noncooperative behavior.

Future research could build on our study in var-ious ways. First, future research could examinewhether these findings hold in alternative samplesand settings, especially with regard to the posi-tive association between the values derived by thetwo partners. This would be critical toward estab-lishing that, on average, cooperative behavior and



common benefits play a more influential role inJVs compared to noncooperative behavior and pri-vate benefits. Second, future research could alsoexamine a wider set of factors and contingenciesimpacting the interrelationship apart from what weexplored here. Thus, for example, it would be use-ful to examine whether the number of prior col-laborations with a particular partner influences theextent of competition versus cooperation. Similarlyit would be valuable to study whether the presenceor absence of an alliance function has an impact onthe nature of the relationship (Kale et al., 2002).Ceteris paribus, a dyad where the two firms havealliance functions may have a greater tendency toexhibit cooperative behavior and synergies versusnoncooperative behavior (Kale and Singh, 2007).Finally, it would also be useful to examine situa-tions where there are asymmetries in the relation-ship between the values derived between the twopartners (i.e., conditions where a firm’s value maybe positively associated with the partner’s value,but the partner’s value may be negatively associ-ated with the firm’s value). In our research, therewas some evidence of this effect in the subsamplewhere the two partners were direct competitors.In this subsample, the high q firm’s value hadan insignificant impact but the low q firm’s valuehad a negative impact (Table 4, Column I) whichsuggests that the ratio of private to common ben-efits may have been substantially greater for thelow Tobin’s q firm. Future research could exam-ine other such conditions that lead to asymmetriceffects.

ACKNOWLEDEGMENTS

I thank Anna Cui and Ikenna Uzuegbunam forcomments on an earlier version. The paper has alsobenefitted immensely from the comments of thetwo anonymous reviewers, and I am grateful fortheir guidance. Responsibility for any remainingerrors is mine.

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