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Alliances as collaborativeregimes

An institutional based explanation of interfirmcollaboration

Henry AdoborDepartment of Management, School of Business, Quinnipiac University,

Hamden, Connecticut, USA

Abstract

Purpose The management and strategy literature continues to show that many companies now

rely on alliances for their long-term success. This paper seeks to explain why some industries have anover-representation of inter-firm strategic alliances, relative to others.

Design/methodology/approach A theory of group behavior is used to show that aninter-organizational phenomenon, notably the interaction of convergent expectations, includingshared patterns of behavior, beliefs and mindsets, are partially responsible for the disproportionate useof alliances in some industries relative to others. The theory of group behavior presented draws mainlyon conceptual ideas from regime and new institutional theory.

Findings The framework suggests that the presence of industry-embedded factors, includingshared mindsets, creates the conditions that transform the strategic interests and behavior ofindividual firms into a macro phenomenon that diffuses across an industry. Industry developed sharedmindsets in turn provide the conditions for trust to endure, cooperation instead of opportunism toprevail, and lower transaction costs, all critical elements for alliance formation.

Practical implications The research presented here shows that industry-level factors may be an

important factor for determining the incidence and perhaps the performance of value-creatingalliances.

Originality/value This paper extends our understanding of strategic alliances as a source of afirms competitiveness and fulfills a need for a greater understanding of the over-representation ofstrategic alliances in some industries, relative to others.

Keywords Strategic alliances, Group behaviour, Organizational theory, Economic sectors

Paper type Conceptual paper

1. Introduction and backgroundWhy do some industries have an over-representation of inter-firm strategic alliances,relative to others? For example, it is known that alliances have become the definingcharacteristic in the biotechnology industry in North America and the global airline

industry with each industry having a more than disproportionate share of alliances(Delerue and Simon, 2009; Ernst & Young, 1995; Go and Williams, 1993). At thesame time, the global tourism industry has been criticized for the paucity ofinter-organizational linkages (Selin, 1993).

Answering this question is important for at least two main reasons. First, because ifalliances have become a critical factor for competitive success (Lavie, 2009; Irelandet al., 2002; Dunning, 1995; Gerlach, 1992), then it is of interest to look at the dynamicsthat foster cooperation. Indeed, the late management guru, Peter Drucker, predicted

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more than a decade ago that alliance management capabilities and their use for valuecreation will become the next strategic frontier. More recently, Lavie (2009) hassuggested that many companies rely on alliances for long-term success. Second, andrelated, despite the generally positive expectation of partnering, research and past

experience has shown that sometimes widely shared industry mindsets and strategicpostures may have a long-term negative impact on collectives of firms. Widely sharedstrategic postures have been linked to strategic inflexibility, myopia, and collectivefailure (Bresser and Harl, 1988; Abraham and Fombrun, 1994). For example, Swissair,noted for having multiple alliances with some of the industries biggest players,collapsed. Suen (2002) suggests that Swissair Groups bankruptcy was a directconsequence of the implementation of its alliance strategy.

Strategic alliances involve non-trivial, bilateral cooperation between autonomousfirms (Das and Teng, 2001; Williamson, 1991). As distinct organizational forms,alliances can range from fully integrated, shared equity joint ventures to arms-lengthrelations in which collaboration may be nothing more than loose working relationships(Yoshino and Rangan, 1995). Alliances between firms in the same industry are calledhorizontal alliances while alliances between firms in various segments of the value chainare vertical alliances. This paper focuses on horizontal alliances. Compared to verticalalliances or cross-industry alliances, research on configuration of alliances within anindustry is sparse (Burgers et al., 1993). This is in spite of the realization that horizontalstrategic alliances are more difficult to manage than vertical alliances (Bengtsson andSoren, 2000; Perry et al., 2004).

Some existing research has linked industry structures to the incidence of alliances.For example, it has been shown that the size of an industry positively relates tothe intensity of inter-firm alliances (Burgers et al., 1993). The nature of industryenvironment, defined in terms of resource scarcity or abundance, is also said toinfluence the use of cooperative strategies (Dollinger, 1990). The degree of demand

and competitive uncertainty that faces an industry has also been related to the rate ofalliance formation in an industry (Eisenhardt and Schoonhoven, 1990). It has alsobeen suggested that the cost structure and the costs of new product development in anindustry all have an effect on the rate of alliance formation in an industry (Varadarajanand Cunningham, 1995).

While insightful, these explanations alone may not adequately allow us to explorethe prime dynamics that underlie all aspects of inter-firm behavior. To some extent,these and similar explanations are based on individual firm rationality andself-interested behavior. Taken alone, models based on individual rationality andself-interested behavior may be inadequate to explain what may be a group-levelbehavioral phenomenon. The fact is most industries face the same challenges such ashigh cost of new product development and uncertainty, yet alliances may not be found

in equal numbers across all industries. As Schelling (1960) showed, models focusing onindividual rationality and self-interest behavior are inadequate to account for theconvergence of expectations. Thus, despite the important work done so far, some gapsremain in our understanding and calls have been made for a greater understanding ofindustry structures and their link to the use of cooperative strategies (Varadarajan andCunningham, 1995). Osborn and Hagedoorn (1997) call for a greater explorationof institutional aspects of strategic alliance use. Singh (1997) speculates thatindustry-embedded conditions may affect decisions about alliances and cooperation.

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This paper attempts to fill some of the existing gap by linking industry mindsets toalliance formation.

This paper argues that an inter-organizational phenomena notably the interactionof convergent expectations and patterns of behavior, practice, shared beliefs,

and mindsets are partly responsible for the incidence of alliances. The presenceof these institutional advantages confer four critical benefits on firms: they reduce thetransaction cost associated with partnering, foster cooperation, trust, and ensure thatties will be formed. Thus, industries that have well-developed convergent expectationsof behavior and practice will see more alliances relative to other industries. Priorresearch has documented that a lack of trust or its fragility (Gulati, 1995), lack, ordifficulties of cooperation (Buckley and Casson, 1988), difficulties of forming ties (Uzzi,1996) and high transaction costs (Hill, 1995) are all obstacles to alliance formation andperformance.

The paper proceeds as follows. Section 1 introduces the concept of regimes (Young,1982; Krasner, 1986) to explain how the convergence of expectations and behavior mayemerge in an industry. Section 2 examines how the features of industries give rise to

convergent expectations. Section 3 discusses how convergent expectations influencefour key outcomes: the transaction costs associated with partnering, trust building,cooperation, and social structure. These factors ensure that alliances in such industrieswould tend to be more successful than in industries that do not share such norms.Section 4 concludes the paper. Figure 1 shows a summary of the main arguments inschematic form. Contextual and situational factors increase convergence expectations(). In turn, convergence expectations increase institutional trust, non-relationalcooperation, cultural and structural embeddedness, while reducing (2) transactioncosts. Collectively, these conditions ensure that alliances are formed in the industry.

The research uses a theory of group behavior to link industry structure to allianceincidence. It combines aspects of institutional theory (Scott, 1995; DiMaggio and

Figure 1.A framework forunderstanding therelationship betweenembedded industryconditions and allianceformation

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Situational factors

Industry recipes

Trade associations

Perception of

common threats

Migration

of executives

Contextual Factors

Spatial clustering

Age in life cycle

Convergent expectations

Shared mindsets

Guides to behavior

Social control

Institutional

Trust

Cooperative

infrastructure

Transaction

costs

Outcomes

Alliance

formation

Cultural and

structural

embeddedness

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Powell, 1983) including the concept of inter-organizational macrocultures (Abrahamand Fombrun, 1994), the notion of industry recipes (Spender, 1989), and regime theoryfrom the international relations literature (Krasner, 1986) as a baseline model to explainthe incidence of horizontal inter-firm alliances. The main argument contained in this

paper is that the convergence of expectations arises when firms develop similarmindsets and expectations, including similar recipes (Spender, 1989), which maythemselves be aided by such factors as common perceptions, migrations of keyindividuals across firms in the industry, and various forms of isomorphism. In turn,the presence of convergent expectations aid the development of trust and cooperationin alliances between firms in the industry, as well as reduce the transactioncosts associated with such relationships. These conditions make it more likelythat firms from these industries have a greater than average chance of having asuccessful alliance.

2. Convergent expectations as regimes

Regime theory has its roots in political theory and international relations. FollowingYoung (1982, p. 277), we define regimes as social institutions governing the actions ofthose interested in specifiable activities. Although some theorists argue that regimespresume explicit agreement between independent actors (Krasner, 1986), regimes maybe more or less formally articulated, and they may not be accompanied by explicitorganizational arrangements. Regime theory has been used to study issues such assecurity between nations (Nye, 1987) environmental problems, and issues of multi-statecooperation (Young, 1982). The use of regime theory in this paper has a similar mission,to elucidate inter-firm cooperation.

Whether explicitly articulated or not, a key distinguishing feature of regimes isthe conjunction of convergent expectations and patterns of behavior or practice. Young(1982) observes that the conjunction of relatively enduring expectations produces

conventionalized behavior. These behaviors are based on recognizable socialconventions that become guides to action. More importantly, perhaps, is the idea thatactors accept and treat such guides to action as operative without making detailedcalculations on a case-by-case basis. This may be so because social norms generateestablished and self-reinforcing patterns of behavior. Of course, individualactors are freeto conform to such social conventions or not to conform. However, the more widespreadthe conventions, the greater their legitimacy and the more likely that actors will adoptand conform to such social conventions. Expectations converge when relativelyenduring expectations and assumptions emerge within a group of institutional actors. Inour particular case, the industry is the level of analysis. These collective assumptionsand expectations influence behavior of individual social actors indirectly because theyare accepted without question.

Regime theory shares some similarities with the theory of social conventions (Lewis,1969) and the new institutionalism (Powell and DiMaggio, 1991). Both theories suggestthat the behavior of social actors may be determined by shared assumptions andexpectations. The implicit assumption is that the institutional values that shapeindividual actor behaviors are enduring. Again the new institutional theory, like regimetheory, accepts that individual actors create and produce the institutional order and eachindividual is free to accept or reject conformance to the social conventions. Theinstitutional actors can, similarly, change the institutional structures.

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According to institutional theorists, institutional context consists of relativelystable rules, social norms, and cognitive structures (Scott, 1995). Scott identifiesthree dimensions on an institutional context: normative, regulatory, and cognitive.Normative institutions define which behaviors and values are expected of individuals

or firms and are seen in the shared values or norms regarding the appropriate ways toact. Normative institutions can be both national and industry based. Regulatoryinstitutions consist of laws, regulations, and government policies that promote andrestrict behavior. Finally, cognitive institutions reflect how certain knowledge setsbecome institutionalized and become part of a shared social understanding. In general,institutions provide the rules of the game (North, 1990), and institutional frameworksprovide informal constraints in the form of socially sanctioned norms of behaviorwhich may become embedded in shared norms (Bucar et al., 2003).

Young (1982) identifies three main forms of regimes: spontaneous, negotiated, andimposed. First are spontaneous regimes. The term spontaneous regimes are traced toHayek. He defines spontaneous orders as the product of the action of many men but

not the result of human design (Hayek, 1973; cited in Young (1982)). As Young notes,spontaneous orders do not often require explicit consent on the part of subjects orprospective subjects. Descriptions of economic collaboration in such geographicallybound enclaves such as Silicon Valley (Saxenian, 1994), Emilia-Romagna province ofModena, North-Central Italy (Brusco, 1982) and Baden-Wurttemburg, a center of textilemanufacturing in Germany (Piore and Sabel, 1984) seem to exhibit some features ofspontaneous orders. In all these cases, the close proximity and clustering of firms seemto have provided one impetus for the widespread use of inter-firm collaboration.

Second are negotiated orders. These are regimes characterized by explicit consent

on the part of individual participants. For example, the General Agreement on Tradeand Tariffs may be an example of a regime in which member nations agree to be boundby rules and regulations of a negotiated order or regime. The rise of certain forms ofinter-firm collaboration may be viewed as negotiated orders. For example, in Europe,cooperation among firms on the airbus project was greatly facilitated by memberEuropean governments (Tucker, 1991). In the USA, the passing of the NationalCooperative Research Act in 1984 led to the formation of several research consortiasuch as the semiconductor initiative, SEMATECH, and the Software EngineeringInstitute in Pittsburgh (Gibson and Smilor, 1992). Although the government providedthe incentives for firms to pull together, the collaboration was based on explicitagreement among participating firms.

Finally are imposed regimes. This occurs when norms of behavior are forced uponconsortia of actors by a dominant actor. As in spontaneous orders, individual actorsmay not explicitly give their consent, but the dominant actor(s) succeeds in getting

them to conform to the requirements of the regime through a combination of coercion,co-optation, and the manipulation of incentives. Japans Ministry of Trade andIndustry (MITI), may be a good example of a dominant actor which has fosteredcooperation among Japanese firms by manipulating incentives and building consensus(Hill, 1995; Hagen and Choe, 1998). Gerlach (1992) suggests that in the case of Japanand MITI, at least the actors or firms may have a belief, however well justified, that

their interests are being served by the sort of conscious institutional guidance MITIprovides.

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2.1 Industry structure and convergence expectationsWe conceptualize inter-firm alliances in this research as spontaneous regimes. Whatthis means is that cooperation has become a self-reinforcing norm or convention in theindustry and firms accept partnering as a legitimate strategy because it has cognitive

legitimacy. Cognitive legitimacy refers to the level of knowledge about a process in anindustry (Aldrich and Fiol, 1994).

Regime theory is less explicit on the specific mechanisms by which mostregimes come into being. However, we can speculate that the interaction of individualagents plays an important role in their emergence. In this research, we propose thatregimes, as social conventions, arise when individual firms interact with one another.Learning and behavior adaptation occurs as a result of the repeated interactions. Overtime, self-reinforcing norms that guide individual firm behavior emerge. Next, thecollective norms or rules of interaction that arise field-wide become widely known by allthe actors concerned. The convergence of expectations that facilitate the sort of industry-wide homogenization and convergence regimes imply are often industry-related. Theyinclude the dissemination of industry recipes, the migration of executives, and thepresence of strong trade associations amongst others. Other contextual factors that aidthe process of homogenization and convergence include the age of the industry and thespatial clustering of firms.

2.2 Industry recipes and convergence expectationsSocial conventions are sometimes agreed upon in advance or emerge spontaneously.They may also arise from the action of a few individuals who interact with each otheror learn a new way of doing things and adapt their behavior over time. Shoham andTennenholtz (1997) observe that there is often concurrent adaptation of behaviorbetween two interacting actors in a complex system. The same dynamics may operateat the level of the industry where individual firm behavior is learnt by another firm

who adapts its strategy accordingly. For example, partnering may be an internal recipeof a firm where the decision to form alliances may be motivated by strategic needs of afirm. Over time, partnering may become an industry recipe if other firms in theindustry begin to see it as a useful strategy. Organizational research has identifiedhow firm level behaviors produce second-image or industry behaviors.

Spenders (1989) research on industry behavior is particularly useful. Spender (1989)introduced the concept of industry recipes. He defines a recipe as a set of sharedideas. According to Spender (1989), a recipe reflects what managers think about theircompany rather than the industry, but firms in the same industry may share similarrecipes. Spender(1989, p. 194) suggests that such shared recipes may becomeinstitutionalized if they find their way into the language, dress, customs and rituals ofan industry. Once institutionalized, such shared recipes affect organizations both as

individual entities and as collectives. The extensive sharing of industry recipes maybe a factor in the formation of what Abraham and Fombrun (1994, p. 730) callinter-organizational macrocultures. They define the term as the relative idiosyncratic,organizational-related beliefs that are shared among top managers acrossorganizations. Spender (1989) identified such macro cultures in the foundry andliquid milk industry in Britain while Marcus and Goodman (1986) associated macrocultures with US airlines. The diffusion of individual level recipes into industry recipesmay occur through a number of paths.

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First, the diffusion may occur through information that circulates in specificindustry media. For example, Abraham and Fombrun (1994) point to the coordinatinginfluence of industry-specific newspapers, magazines, and newsletters. The authorssuggest that the existence of value-added networks that link firms together explains

how firms may come to share similar beliefs. The authors also suggest that a level ofhomogeneity that exists in macrocultures may affect how firms process informationabout what issues are facing them and the industry; how they evaluate thereputation of other firms, who they identify as competitors, as well as firms theyconsider as non-competitors. Tefler (2001) found that industry-wide publications andinstitutionally organized festivals were important in coordinating relations betweenthe wine industry and other related stakeholders in Ontario, Canada.

Second, the migration of senior executives, within the same industry, can be animportant factor in the homogenization and development of common values, includingan appreciation of the need for collective strategies in an industry. For example, it hasbeen proposed that firms may deliberately hire executives from their rivals as a way offacilitating inter-firm coordination (Pfeffer and Leblebici, 1973). It is proposed that thegreater the migration of executives within the industry, the greater the tendencytoward homogeneity and convergence of expectations. Institutional theorists haverecognized the role of executives in the processes of isomorphism (Stinchcombe, 1968),as well as the promotion of institutional change (Greenwood and Hinnings, 1996).

Migration, defined as the movement of executives from firm to firm, may be aparticularly effective conduit for promoting shared expectations and the developmentof collective values because of the key role executives play in the shaping oforganizational culture, strategy, and direction. DiMaggio and Powell (1983, p. 152)suggest that cross-hiring of managers facilitates this sort of industry-level isomorphism.They note that cross hiring may lead to a situation where organizations come to be runby a pool of almost interchangeable individuals who possess a similarity of orientation

and disposition that may override variations in tradition and control that mightotherwise shape organizational behavior. Executives are often the repositories of theirorganizational values and carry their shared experiences from one firm to the other.Organizational level values, including recipes, that leaders carry in their heads are thustransferred from one organization to the other. This may be one reason why theindividual experiences of executives within an industry increases their organizationsconformity to the industrys central values and behaviors (Hambrick andFinkelstein, 1987).

More recently, Kraatz and Moore (2002, p. 124) proposed that the migrationof executives may play an important role in facilitating inter-organizational learning.The authors argue that executive migration can help organizations overcome someof the barriers to inter-organizational learning because the migration of a leader

from one organization to another creates a relatively high-capacity conduit betweenorganizations and may thus promote the transfer of reliable and fine-grainedinformation, which is often necessary for social learning. Inter-organizational learningmay be particularly important to the diffusion of field-wide convergence ofexpectations because learning is at the heart of any transfer of individual-levelbehaviors into system-wide or second image behavior.

Third, the use of common industry standards can also aid the process ofhomogenization that fosters similar mindsets and collective values. In their study of

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cooperation in the Texas-based research consortium, SEMATECH, Browning et al.(1995) found that the presence of common industry standards aided the process ofcooperation in the industry. Adoption of industry standards such as ISO qualitycertification may further help homogenization in an industry. This should be so

because firms who adopt these industry standards have to meet a certain uniformcriteria. For example, firms that apply for the Malcolm Baldridge Awards or, theCanadian equivalent, the National Awards for Excellence (both national awards forquality), all have to meet a certain criteria. The process of fulfilling the requirementsfor the awards forces some degree of homogenization of systems and operations. Evenwhere a firm does not apply for these awards, the guidelines are readily available andwell-known that any firm is free to make use of them.

Finally, the perception of common threats may encourage the development ofshared expectations. More importantly, shared perceptions of common threats maypromote the use of collective strategies. For example, Browning et al. (1995) note thatthe Texas-based semiconductor research consortia, SEMATECH, was formed partiallyas a result of the common perception of threats to the semiconductor industry from

abroad. The perception that the products or services of an industry are collectivelyevaluated by consumers or outside stakeholders may also encourage the developmentof shared expectations, as well as collective behavior. In this type of setting, it is easyfor firms to see and interpret common threats more easily. For example, the averagewine buyer (except perhaps wine connoisseurs amongst us) often talk in general termsof French wine, as opposed to talking about individual French wineries suchas Mouton Rothschild, or Chateau Pauillac. This realization may have beenpartly responsible for the presence of institutional control mechanisms such as theappelation controllee by which wines are certified to meet a certain quality standard.Institutional developments similar to the French case are underway in the wineproducing regions of the Niagara Region in Ontario, Canada. Like France, Canada hasits own appellation system, the Vintners Quality Alliance that governs the quality ofwine produced in Ontario (Tefler, 2001). The evidence suggests that wine producers seethat there are benefits for cooperation and the success of the wine business in theNiagara region is one of common survival. Thus, common perception of a collectivethreat and the industries response all aid in the emergence of some collective norm ofcooperation, even if this is not explicitly defined. Research in organizational sociologyhas also shown that industry-related links provided by trade associations andinterlocking boards can be a source for referrals and information on prospectivepartners (Burt, 1992). In summary, we note that institutional-level factors, includingthe adoption of common standards, recipes, which may all be helped by perceptionof common threats and intra-industry migration of executives can lead to thedevelopment of convergent expectations on collaboration. The discussion and research

is the basis of the following proposition:P1. Industries with common recipes are more likely to have convergent

expectations than industries without shared expectations.

2.3 Industry associations and convergence expectationsAnother important factor in the development of collective norms is a strongtrade association. Trade associations can positively impact the development ofshared mindsets and expectations. Trade associations tend to be voluntary

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self-organized groups. As organized interest groups, trade associations allow membersto share industry-specific knowledge and engage in collective strategizing. Often, tradeassociations influence the development of institutional frameworks because their job isessentially to strategize on behalf of a collective of firms. Strong trade associations may

influence convergence because they are a link between several firms.Lane and Bachmann (1997) come to some interesting conclusions in their

comparative study of British and German trade associations. They found thatcompared to German trade associations, British trade associations lacked a stronginstitutional framework and a capacity to provide general guidelines for the behaviorof their members. In Germany, to the contrary, trade associations are much strongerand provide leadership for their members. The authors observed that German tradeassociations are an efficient tool for the development of the sort of social conventionsregimes imply. Bachmann (2001, p. 356) notes that as self-organized groups, Germantrade associations represent member interest actively, are able to engage in collectivestrategies, and are in general highly conducive to generating and monitoring therules and standards of business behavior within their industries and beyond.

More importantly, Bachmann (2001) found that German trade associations actuallyexercise and apply indirect social control on member firms. It is important to note thatthis sort of social control may be a factor in producing a certain amount of system orinstitutional trust (Luhmann, 1979; Zucker, 1986).

Another example of the role of strong trade association in promoting sharedmindsets and cooperation can be found in the Niagara wine region in Ontario, Canada.The Wine Council of Ontario is responsible for developing market research (Hackett,1999). The council is also said to have provided critical leadership in setting standardsfor the Ontario wine industry and as a liaison between wineries, grape growers, andgovernment organizations. In his study of alliances between wineries in the Niagararegion, Tefler (2001) reports that the existence of a series of formal associationsgoverned by rules and regulations promote alliance formation between wineries.His analysis also reveals that individual wineries accept the leadership of the formaltrade associations and actually look up to them for direction. Such an active role offormal associations should facilitate the development of shared mindsets,homogenization, and convergence on the need for collective strategizing. In general:

P2. Industries with strong associations are more likely to have convergentexpectations than those with weak industry associations.

2.4 Spatial clustering and convergence of expectationsThe geographic boundedness of an industry may also affect the development of normsand shared values. There is a greater possibility for firms that are clustered to developshared norms and other characteristics that sustain cooperation than those that are

dispersed for at least two reasons.First, clustering increases the frequency of social interaction, including the initiation

of personal contacts that may become the basis of ties that are crucial for allianceformation (Gulati, 1995). There is a greater chance for people to form friendshipswhen they meet frequently (Homans, 1950) and proximity to each other makes thispossible. Second, proximity and frequency of interaction may be related to the level ofreciprocity and relational assets that develops between actors in an industry.For example, while the willingness to be in someones debt helps the process of trust

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building (Ouchi, 1980), it is known that people are more willing to be indebted to otherswhere chances of frequent interaction are greater (Homans, 1950). This may be sobecause the opportunities to repay a debt are greater the more frequently peopleinteract. Indeed, Lorenz (1988) found, in his study of subcontracting in the French

industry, that firms cited geographic proximity as one factor that made it possible todevelop personal contacts that became the basis for cooperation. Powell (1996) alsofound that trust-based governance seems easy to sustain when firms are spatiallyclustered.

While important, clusteringper se may not always lead to cooperative behavior. In acomparative study of two industrial districts in the USA, Saxenian (1994)demonstrated that two similar industries, with about the same degree of clustering,evolved into two separate forms. While there was generally a sense of cooperationamong high tech firms in Silicon Valley, there was competition among similarlyclustered firms along Route 128 (Boston) in Massachusetts. The research anddiscussion is the basis for the following proposition:

P3. Industries that are spatially clustered are more likely to have convergentexpectations than industries that are not spatially clustered.

2.5 Stage in industry life cycleThe development of collective mindsets, including institutional structures, in anindustry takes time. Thus, one may find a direct relationship between the stage inwhich an industry is and the incidence of collective strategies, including strategicalliances. Both the theory of regimes and the theory of industry life cycles(Stinchcombe, 1965) suggest that industries and regimes pass through a progression ofintroduction, growth, and maturity. Looking particularly at the industry life cycleconcept may be insightful. There is reason to suggest that the rise of regimes, as areflection of the convergence of expectation around the use of collective strategies,

is likely to be directly related to the stage of industry development for at least tworeasons.

First, the early stage in an industry life cycle is often marked by uncertainty.New industries have to gain the acceptance of all sorts of stakeholders includingpotential customers (Aldrich and Fiol, 1994). Whether new industries will succeed ornot remains unanswered in the early stages of their life cycle. Under such conditions,firms in new industries may be preoccupied with their own survival and less interestedin engaging in collective behavior. Even if collective action becomes a recipe, it isunlikely that it will diffuse widely in the industry to affect individual firm behavior.Collective action in general may be more difficult to organize in the earlier stages of anindustry because there is a greater possibility of free rider problems in the early stagesof an industrys evolution (Olson, 1965).

Second, theories of industry life cycles suggest that the emergence of alliancebuilding factors such as trust between potential partners may be dependent on theage of an industry (Stinchcombe, 1965). For example, it has been suggested that howdisputes between firms in an industry are resolved may depend on the specific valuesthat an industry develops. It may be more difficult to develop trust and collectivenorms in a young industry because there is often a lack of a shared history in theearly states of industry growth (Suchman, 1995). In new industries, new vocabularymust be coined, new labels manufactured, and shared beliefs engendered in an

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industry with no history. To the contrary, more established industries may enjoyshared metaphors and worldviews (Huff, 1982). The lack of a shared history means thatperceptions of risks are likely to be very subjective in new industries (Brophy, 1982).

These liabilities of youth can affect the process of building cooperation and the

development of shared mindsets. For example, Sabel (1993) found in his study ofcollaboration among stakeholders in Pennsylvania that the re-interpretation of acollective past can be a powerful tool for building cooperation and trust amongstakeholders even where mutual suspicion runs deep. The presumption here is thatcompared to a matured stage of an industrys life cycle, firms in young industrieswill be less inclined to behave in a trustworthy manner. In summary, we note thatthe age of an industry facilitates the development of shared norms and convergentexpectations such that older and more established industries will have greater degreesof convergent expectations on collaboration than younger industries. The research anddiscussion is the basis for the following proposition:

P4. Firms in the mature stage of their industry life cycle are more likely to have

convergent expectations than those in the younger stages of their life cycle.

3. Convergent expectations and alliance formationFigure 1 shows that shared mindsets will produce relational assets that assure not onlythat alliances will be formed but also increase the probability that such alliances will besuccessful. The presence of convergent expectations in an industry should directlyaffect the outcome of inter-organizational relationships in an industry in fourmain ways:

(1) it easier for firms interested in forming alliances to take the initiative because ofthe presence of shared mindsets (cognitive embbededness) and interpersonalties (structural embeddedness);

(2) it promotes trust building;(3) it reduces the transaction cost associated with partnering; and

(4) fosters cooperation by altering the dynamics of interaction, tilting it towardgreater cooperation by making opportunism more costly.

3.1 Embeddedness and alliancesConvergent expectations promote embeddedness. Embeddedness as first used byKarl Polanyi refers to the link between social relations and economic action. Althoughmore recent treatments of the concept have been less sweeping, the core idea has beenretained (Granovetter, 1985). DiMaggio and Powell (1983, p. 15) define embeddednessbroadly as the contingent nature of economic action with respect to cognition, culture,social structure, and political institutions. Our interest here is primarily on the culturaland structural aspects of embeddedness.

First, is structural embeddedness or the contextualization of economic exchangein patterns of ongoing inter-personal relationships (Granovetter, 1985). The manner inwhich individuals are connected to each other in an industry may be particularlyimportant. Where there are dense networks of relationships, one should expect agreater use of collective strategies. Shared norms and constitutive behaviors shouldmake the process of making the links and building ties with others in the industryeasier. Such pre-existing ties and contacts can be indispensable in building a social

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structure which can become an important source of inter-firm relationships. Socialconnections and prior ties are especially useful in making the personal connections thatoften form the basis for inter-firm relationships (Gulati, 1995; Uzzi, 1996). Research hasalso shown that such social structures are important for the development of trust and

cooperation (Uzzi, 1996).Second, is cultural embededdness. Cultural embeddedness refers to the role of

shared collective understandings in the shaping of economic strategies and goals(DiMaggio and Powell, 1983). The collective norms that result from homogenizationand convergence serve an important purpose. Cultural embeddedness provides a formof social control. Individual actors are less likely to shirk their responsibilities inalliances or engage in opportunistic behavior when they know that there is a highsocial cost attached to such behavior. Institutional social control occurs becauseindividual actors may internalize self-restraining behaviors because they know whatthe costs will be, both socially and economically, for violating trust in the industry. Theresult is that alliances between firms that are culturally embedded with each other mayexperience greater stability. More specifically, we propose that:

P5. The probability of alliance formation between firms in an industry increaseswith the level of structural and cognitive embeddedness in the industry.

3.2 Convergent expectations and institutional trustTrust is often mentioned as a lubricant in economic exchange and the virtues of trust inalliances are widely discussed (Das and Teng, 2001; Krishnan et al., 2006; Ring and vande Ven, 1992). Spekman and Carraway (2006) observe that trust is often considered asthe glue that holds collaborative relationships together. It is widely accepted that trustcan positively affect performance in an inter-firm alliance because it reduces agencyand transaction costs (Hill, 1995). However, trust is fragile and hard to find (Aulakhet al., 1997). Thus, mechanisms that facilitate trust creation and ensure its resilience

will be important assets to firms in collaborative relationships.Trust may emerge in an alliance because the actors believe there are costs

associated with violating it (Ring and van de Ven, 1992), or because the partnerscalculate their counterpart intends to perform a beneficial act (Barber, 1983) and hasthe competence to do so or has in fact demonstrated competence performance in theexchange situation (Das and Teng, 2001; Suh and Kwon, 2006). Both situations canlead to the emergence of relational trust (Rousseau et al., 1998; Dyer and Chu, 2003).Relational trust refers to trust that emerges as the partners in an alliance interact over aperiod of time and is therefore specific to particular relationships. Trust can also derivefrom the presence of factors unrelated to specific situations. One particular form oftrust, institutional or global trust (Butler, 1991; Luhmann, 1979), emerges outside of therelational context when the presence of institutional mechanisms assures a critical

mass of trust that sustains good faith behavior and risk taking. Of course, the presenceof institutional trust can also facilitate the development of relational trust (Hagen andChoe, 1998).

Convergent expectations become a form of institutional factor that promotes goodfaith behavior. A substantial amount of research and theory suggests that the presenceof shared norms between actors promote trust. This form of trust has been calleddepersonalized or globalized trust (Butler, 1991). For example, history, ethnicity, andreligion can be a source of shared norms (Zucker, 1986). Luhmann (1979, p. 73) is most

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explicit on the role of shared norms in producing trust. He notes: trust is a question ofgeneralized attitudes, with considerable indifference toward numerous details andslight shadings of experience. The idea is that the internalization of societal or systemvalues can become effective tools for social control, thereby allowing actors to sustain

trust. The availability of institutional trust should aid alliance formation within anindustry for at least three reasons.

First, the fact that key individuals in the industry share similar outlooks andare accustomed to the same rituals makes it more likely that initial trust (McKnightet al., 1998) will develop faster among members of the collective. Initial trust refers tothe goodwill that actors extend toward each other even before they have time to verifythat their counterpart intends to honor their obligations. Initial trust should be highwhen there are shared mindsets because convergence produces a certain amount ofwhat Zucker (1986) calls background expectations. Background expectations areinstitutional-level guarantees that people will behave in a trustworthy manner. Thereis, in effect, a certain amount of institution-based trust or global trust (Butler, 1991)among firms in an industry with convergent expectations. Such an expectation mayembolden actors to develop interpersonal and firm-based trust. The high initial trustthat shared expectations make possible may translate into high initial trustingintentions. When we view trust as a form of sense making (Weick, 1995), initialintentions become very important because it allows people to make sense of highlyuncertain circumstances. High initial trust may produce a virtuous circle in which highinitial expectations lead to desirable behaviors and trust building through themechanisms of a self-fulfilling prophecy (Adobor, 2005).

Second, institutional trust should make inter-firm and interpersonal trust stronger.Trust is resilient when it is not easily broken. Institutional trust assures resiliency ininter-firm trust because shared norms act as a form of social control. Shared normsmay also imply that there are several guardians of trust (Taylor, 1987) in place,

making it less likely that firms will act opportunistically, thereby violating trust.This may be so because individual actors may engage in greater self-regulationbecause of the presence of institutional controls. Indeed, research has shown thatrelational trust or trust based on relationship-specific factors is often thin because itmay only rest on compensation for negative behavioral expectations and not positiveexpectations (Noteboom, 2002).

Finally, there is reason to suggest that shared expectations produces or at leastmakes it easier for the production of studied trust (Sabel, 1993), a particular form oftrust. Studied trust is trust that emerges out of a shared sense of community.Convergent expectations on the importance of collaboration in an industry mean thatfirms believe they would have to use alliances sooner or later. This means that thechances that individual firms will act opportunistically and exploit others are reduced.

It is important to note that institutional controls can limit the development of trustin inter-firm situations especially where legal mechanisms promote inflexibilitywith respect to conflict resolution (Zucker, 1986). That notwithstanding, we note thatrelationships with resilient trust should perform better than those with fragile trust.In turn, firms that believe that it will be easier to find trust, so to speak, will be moreinclined to enter alliances. Taken together, the presence of shared norms andconvergent expectations will help create and sustain trust and encourage tie building.Shared industry norms have also been shown to contribute to trust development at

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a dyadic level (Browning et al., 1995). The research and discussion is the basis for thefollowing proposition:

P6. The probability of alliance formation between firms in an industry increases

with the level of institutional trust in the industry.

3.3 Convergence expectations and cooperative infrastructurePrevious research has identified cooperation as one key ingredient in inter-organizational collaboration. Most of the existing research has looked at cooperationin terms of relationships. The existence of certain conditions, what is termed here ascooperative infrastructure, may also promote trust. This concept is similar to Zuckers(1986) notion of background expectations on trust. Actors who have this cooperativeinfrastructure have, in effect, some comparative advantage over those who do nothave it.

Cooperation has been defined as coordination affected through mutual

forbearance (Buckley and Casson, 1988, p. 32). A person who forbears, refrainsfrom opportunistic behavior. Although cooperation is important for performance inalliances, getting actors to cooperate in alliances, or any mixed-motive situation forthat matter, may not be easy. Transaction cost theorists are most explicit on thehazards of opportunism in economic exchange (Williamson, 1985), and there is someuniversal recognition that opportunism certainly exists in inter-firm alliances. In fact,some evidence suggests that firms are vulnerable to opportunistic behavior of theirpartners. For example, Tucker (1991) notes that collaborative projects involving highlyappropriable technologies have often been conducted in ways that suggest firms areconcerned about opportunism on the part of their counterparts. As Buckley and Casson(1988, p. 34) indicate, there is an inalienable de facto right of all parties involved in aventure to pursue their own interests at the expense of the others. This same theme is

echoed by experimental research in game theory where the paradigm example of theprisoners dilemma is used to illustrate the difficulties of cooperation, in even insituations, where cooperation, not self-interested behavior, will yield the maximumbenefits (Axelrod, 1984).

Research in game theory has demonstrated that actors can use ex ante strategies toinduce cooperation. Axelrod (1984) demonstrated that patterns of payoffs, shadow ofthe future, and behavioral transparency can be manipulated to promote cooperation.First, game-theoretic reasoning suggests that there can be no cooperation unless bothfirms see that there are benefits, or payoffs, from mutual cooperation. Parkhe (1993)demonstrated that the pattern of payoff most conducive to mutual cooperation is one inwhich the parties suffer the greatest lost when there is a complete break up of thestrategic alliance.

Second, future payoffs are also very important to cooperation. Anticipation of futurepayoffs creates a shadow on the present and the shadow of the future links presentcooperation to future benefits. A long shadow of the future is conducive to cooperation.The time horizon of the relationship or how long the partners will stay togetherlengthens the shadow of the future. A long time horizon will positively affect cooperationbecause it serves as a disincentive to discount future payoffs. Finally, behavioraltransparency promotes cooperation. Frequent communication, including a clearunderstanding of the signaling behavior partners send to each other will also prolong

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the shadow of the future (Axelrod, 1984). Shared mindsets facilitate communication,including the understanding of signals.

Although partners can use ex ante strategies to enhance cooperation, the presenceof convergent expectations will achieve the same results for at least two reasons.

First, convergent expectations alter the payoff structure in the alliance by makingdefection more costly. The presence of shared mindsets and values reduce the gainsfrom opportunistic behavior, thereby reducing the incentives for opportunism.Shared mindsets mean that opportunism is less likely to be acted on since the costsof opportunism are much higher because of the power of both social control andself-monitoring.

Second, the presence of shared mindsets presupposes that firms in the industryhave accepted certain norms and values, including the norms of cooperation. Thesenorms and values are then invoked as informal constraints against opportunisticbehavior. There is some suggestion that people, as members of a collective, will tend tofollow known rules out of respect for those rules as long as they know that other peoplewill respect those rules (Zucker, 1986; Coleman, 1993). Sometimes, institutionalbehavior is often adopted simply because people accept their existence as a social factwhich other actors must obey (Zucker, 1986). Thus, while partners in an alliance maybe tempted to be opportunistic (defect in game theoretic terms), the presence ofconvergent expectations of behavior and practice mean that they will be less inclined todo so. The interesting thing here is that the alteration of the payoff structure betweenalliance partners is accomplished by the institutional or sectoral level constraints,rather than the deliberate actions of individual actors as suggested in transactioncost economics (Williamson, 1985). The recognition that a violation of partnerexpectations amounts to a violation of a collective norm reduces the probability ofopportunistic behavior and enhances the chances for partner cooperation.

Convergent expectations also promote cooperation because they indirectly create

structural conditions that lengthen the shadow of the future. Game theorists haveidentified behavioral transparency as an important factor in cooperation. Parkhe (1993,p. 305) notes that poor behavior transparency limits actors ability to recognizecooperation and defection by others, separates beliefs from reality, and serves to severthe critical links between current actions and future consequences. Shared mindsetsmean that actors are able to interpret the signals their counterparts send accuratelyand misperceptions between the partners can be minimized. This is important becausethe power of signals fade with time ( Jervis, 1976). Finally, interaction is less conflictualwhen partners in an alliance share some common institutional norms. These conditionsensure that firms in an industry with shared expectations will have a greater incentivefor cooperation and partnership formation.

Collectively, these collaborative assets enhance the prospects for better relational

governance in intra-industry alliances and may help reduce relational risksassociated with alliances. Alliances generate relational risks due to the dual controlof the relationship and the uncertainty about the partners behavior and the possibilityof change in future goals (Parkhe, 1993; Das and Teng, 2001). Das and Teng (2001)suggest that trust reduces the perceived risk of opportunistic behavior because it leadsto positive expectations about alliance partners. Shared mindsets similarly reducerelational risk by both making it more costly for defections and for acting as a bufferagainst opportunism. In some sense, what these conditions promote is a form of

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cooperative infrastructure which in turn makes it more likely that alliance partnerswill have a productive relationship with the possibilities of instability reduced.The research and discussion is the basis for the following proposition:

P7. The probability of alliance formation between firms in an industry increaseswith the level of cooperative infrastructure in the industry.

3.4 Shared expectations transaction costsThere are substantial costs associated with partnering. The importance and relevanceof transaction costs in alliances has made transaction cost theory (TCE) perhaps themost common theoretical framework for the study of strategic alliances (Anderson andSedatole, 2003). At its core, TCE holds that it is the characteristics of transactions inalliances that raise risk. The theory assumes that managers adopt a particulargovernance arrangement to minimize risk. Asset specificity, uncertainty associatedwith the transaction and the frequency of these transactions all affect transaction costs(see, Williamson, 1991 for a more complete explanation of TCE).

Hill (1995) defines transaction costs in terms of all these sources:. the costs of identifying a partner who is less likely to shirk or avoid its

responsibility;

. negotiating costs, including the costs of providing incentives to a counterpart toreduce the temptation to avoid responsibility;

. monitoring costs; and

. enforcement costs.

There are at least three sources of costs in partnerships. Hill (1995) demonstrated fromhis analysis of exchange in Japan that the transaction costs associated with economicexchange may be substantially reduced by the nature of national institutional

structures in a country.First, there is the cost of searching for the right partner. Partner selection issues

have been well-discussed in the strategic alliance literature. The main recommendationis to choose a partner with whom one shares some similarity. Finding the right partner,however, involves a search cost (Larson, 1992). Firms can research the background oftheir prospective allies by talking to others or by conducting their own research.Second, there are costs that arise when a partner engages in opportunism or free riding.Finally, costs arise in cooperation when a partner makes a specific investment for thealliance and the counterpart firm fails to deliver its side of the project, thereby holdingup the other firm. In general, uncertainties about the partners competence, intentions,and behavior increases transaction cost (Williamson, 1985).

The presence of convergent expectations reduces all these forms of transaction

costs. Social conventions, in general, reduce transaction costs because they coordinateexpectations and reduce uncertainty associated with exchange (Warneryd, 1994).Primarily, convergent expectations provide background expectations for interactionin exchange. Such background expectations serve as general frameworks for behavior,guaranteeing prospective partners some assurance that they can work toward asuccessful alliance. It may also be easier to identify a prospective partner because ofthe several institutional ties that exist under shared industry mindsets. Also, becauseopportunism is less likely to be acted upon, losses from shirking and opportunism will

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tend to be lower and this should increase the motivation of firms to take the risk ofentering an alliance. As alliances become industry recipes, there is a reduced need tocraft elaborate incentive structures to promote good faith behavior and reduceshirking. This is because the average firm in the industry will recognize the importance

of inter-firm relations and may use it at one point in time. The benefit of shared normsdecreases some of the uncertainty associated with transactions. For example, sharedmindsets reduce the monitoring costs as well as the maladaptation cost that arise fromcommunication and coordination failures between constracting parties and smoothsthe difficulties associated with their ability to react rapidly to changing conditions overtime in alliances (Dahlstrom and Ingram, 2003).

In sum, we note that the presence of institutional structures and mindsets wouldhelp reduce the transaction costs associated with partnerships which make it morelikely that firms will enter alliances with each other. The reverse situation is also true.Higher transaction costs mean less incentive to collaborate. Specifically:

P8. The probability of alliance formation between firms in an industry is

inversely related to the level of transaction cost of partnering in the industry.

4. Conclusion and discussionThe proliferation of alliances has somewhat altered the traditional norms of competition.Terms such as alliance capitalism and co-opetition have become common indiscussions of sources of competitive advantage. Recently, competition not only relieson internal capability and resources but also on close cooperation with externalorganizations (Claybond and Franwick, 2004). Alliances may be popular, but recentevaluations of their performance show a low success rate (Sadowski and Duysters, 2008).This indicates that despite the proliferation of studies on alliances, our appreciation oftheir complexity and value-creating potential still requires additional study. Knowingwhat promotes successful collaboration is important and looking within industries that

have an overrepresentation of alliances may give us a greater understanding of theirdynamics. Using a theory of group behavior, this paper makes the argument thatconvergent expectations may be partly responsible for the preponderance of alliances insome industries relative to others.

This paper has shown that a useful theoretical approach to explainingthe disproportionate incidence of alliances across industries is to look at industry-embedded conditions. A combination of this approach and existing economicapproaches that focus solely on self-interested behavior is capable of offering a morecomplete explanation of alliance formation and distribution across industries.This research therefore may offer a more comprehensive explanation of alliancesformation by showing how industry conditions can transform the strategic interests andbehavior of individuals firms into a macro phenomenon that diffuses across an industry.

It is important to reiterate that while shared mindsets offer a comparative advantage soto say, it may not be the only guarantee for creating and benefiting from allianceportfolios. Firms need to develop their internal and relational capabilities to moreeffectively utilize the pre-existing advantages that emanate from their institutionalenvironments.

It is clear that the very nature of competition has altered in the light of theemergence of an era of alliance capitalism (Gerlach, 1992). This and previousresearch shows that firms seeking to create value and benefit from alliances need to

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develop the internal capabilities required to successfully deal with the dualities ofcompetition and collaboration. Amongst others, key competences and skills discussedin the literature are partner selection and relationship management issue (Claybondand Franwick, 2004).

4.1 Future research directionsThis research raises some issues that require future exploration. First, the propositionalinventory generated here requires empirical verification. The variables discussed can beassessed with a survey instrument to determine managerial perceptions on the issues.Second and related, although the discussion focused exclusively on the positive aspectsof shared industry mindsets, it is important to note that there may be dysfunctionalconsequences associated with shared expectations and some earlier research has raisedthat possibility (Bresser and Harl, 1988). Previous research has demonstrated thatwidely shared mindsets can breed strategic inflexibility because firms may narrow theirsearch for prospective partners to their industry. More importantly, extensively shared

mindsets may also unnecessarily foreclose the ability of firms to recognize otheropportunities. This may be so because industries with widely shared mindsets may findit harder to trust those they consider as outsiders. For example, Yamagishi andYamagishi (1994) found that while shared values made for trust in relations betweenpeople from Japan, this same mechanism made them less likely to trust non-Japanese.Their findings imply that intense group ties often seen in collectivist cultures mayprevent trust from developing beyond the group. This same thinking may apply toorganizational fields such as industries. A greater exploration of both the positive anddysfunctional consequences of shared industry mindsets requires our researchattention.

Third, although this paper did not focus on the feedback mechanism that ishighlighted, but not discussed, in the framework (the broken lines in Figure 1), this is a

real possibility. In fact, research on network forms has shown that prior ties promotefuture relationships (Gulati, 1995) and an exploration of this issue will offer a morecomplete explanation of the feedback mechanisms that may exist in this type ofsituation. Finally, it will be of interest to see whether intra-industry alliancesnecessarily yield a more stable and satisfying relationship than cross-industryalliances. The theory developed here suggests so, but evidence is required to validatethat theoretical claim.

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Further reading

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Corresponding authorHenry Adobor can be contacted at: Henry.Adobor@quinnipiac.edu

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