NETWORK GOVERNANCE: SOCIAL MECHANISMS

AS SOLUTIONS TO EXCHANGE PROBLEMS

The network form of governance carries with it special problems of adapting, coordinating and safeguarding exchanges, relying as it does on autonomous units operating in a setting of demand uncertainty with high interdependence due to customized, complex tasks. Network governance overcomes these problems by using social mechanisms rather than authority, bureaucratic rules, standardization, or legal recourse.

FIGURE 2

How Social Mechanisms Resolve Exchange Problems
Social Mechanisms Exchange Problems

Since social mechanisms in network governance are poorly understood, we focus on identifying them and explaining how they facilitate adapting, coordinating and safeguarding exchanges (see Figure 2). These social mechanisms consist of restricting access to exchanges, imposing collective sanctions, and making use of social memory and cultural processes. In this section, we explore these social mechanisms in turn. Table 2 summarizes how these social mechanisms influence adapting, coordinating, or safeguarding exchanges, and their boundary conditions. We suggest that the social mechanisms of network governance provide comparative advantage over other governance forms for these exchange conditions. Ceteris paribus, network governance is more likely to emerge under these exchange conditions and is more likely to thrive as a viable alternative governance form when these social mechanisms are present.

TABLE 2
How Social Mechanisms Influence Exchange Behavior

Restricted Access to Exchanges in the Network

Restricted access is a strategic reduction in the number of exchange partners within a network. In network governance, restricted access occurs through status maximization and relational contracting. The status maximization strategy restricts access because partners seek to avoid partners of lower status; however, since the other parties are also avoiding parties of significantly lower status, the result of status maximization is exchange among units of similar status. Status is based on "past demonstrations of quality" or association with high status partners (Podolny, 1994: 460, 479). The status strategy is well established in film where having an "element" — star or well-known director or producer — on a film ensures funding from and distribution with a major studio (Jones & DeFillippi, 1996). Alternatively, relational contracting restricts access by working with fewer partners more often (Bolton, Malmrose, & Ouchi, 1994; Helper, 1991; Macauley, 1968). This strategy is well established in Japan, where firms work with far fewer suppliers than do American firms (McMillan 1990:39). For example, Dyer and Ouchi (1993: 54) report that U.S. auto manufacturers used twenty different suppliers for electrical wiring whereas Japanese auto manufacturers used just two.

Restricted access reduces coordination costs. Fewer partners increase interaction frequency which can augment both the actors’ motivation and ability to coordinate smoothly. First of all, fewer partners who interact more often reduces variance in expectations, skills, and goals that parties bring to exchanges, which facilitates mutual adjustment. In addition, continued interactions may substitute for internal socialization processes (Bryman, Bresnen, Beardsworth, Ford & Keil, 1987:267) and permit exchange partners to learn each other’s systems (Eccles, 1981; Faulkner & Anderson, 1987:892), develop communication protocols, and establish routines for working together (Bryman, Bresnen, Beardsworth, Ford & Keil, 1987:280), all of which enhance coordination. Thus,

Proposition 3a: Restricted access reduces coordination costs for parties with customized, complex exchanges. Ceteris paribus, restricted access enhances the likelihood of network governance emerging and thriving in rapidly changing markets for complex, customized tasks.

Restricted access also facilitates safeguarding exchanges. Fewer partners decreases the total amount of monitoring a firm must do. This allows it to do a better job of monitoring the relationships it does engage in, thus both reducing transaction costs and the danger of becoming the victim of opportunistic behavior. In addition, fewer partners who interact more often increases identification among parties and provides the conditions for the development of strong ties among those involved (Granovetter, 1973). When this occurs, the actors involved tend to see their interests and needs as aligned rather than in opposition (Granovetter, 1992; Provan & Gassenheimer, 1994) which reduces the incentives for opportunism. Finally, fewer partners who interact more often, together with joint payoffs (discussed in a later section) create the conditions for an iterated prisoner’s dilemma game (Axelrod, 1984). When the parties expect to interact repeatedly for the foreseeable future, it is rational to cooperate unless the other party defects. This decreases the potential for opportunism in exchanges. Thus,

Proposition 3b: Restricted access enhances safeguarding of customized exchanges for parties in rapidly changing markets. Ceteris paribus, restricted access enhances the likelihood of network governance emerging and thriving in rapidly changing markets for complex, customized tasks.

We speculate that the relationship between the degree of access restriction and the contribution to adaptive fit of a network follows an inverted U shape where too little restriction reduces performance because it impedes coordination of complex tasks, while too much restriction reduces performance because it provides inadequate incentives for quality and innovation. Closed systems can develop a "Not-Invented-Here" syndrome that leads to participants "wallowing in their collective ignorance" and impedes innovation within the system. This notion has been used to describe the failure of US auto manufacturers who collectively ignored Japanese innovations and improvements (Abrahmson & Fombrun, 1994). In addition, the choice of exchange partners is important since restricting exchange to only poor performers is unlikely to prove very successful.

Mathematical simulations of system performance in the context of information exchange (Huberman & Hogg, 1995) support both of these conclusions: very low restriction of exchange partners was optimal only when the number of actors in the system was very small and all of similar quality; very high exchange restriction was optimal only when the size of the system was large and at the same time the variance in quality of actors was high (in other words, if some potential partners are very poor performers, it is better to stick with a closed set of the better performers). In all other cases, an intermediate level of restriction was optimal.

Macroculture

Macroculture is a system of widely shared assumptions and values comprising industry, occupational, or professional knowledge that guide actions and create typical behavior patterns among independent entities (adapted from Abrahmson & Fombrun, 1991, 1994; Gordon, 1991; Phillips, 1994: 384). This knowledge-base is derived from fundamental assumptions about customers, competitors, suppliers, and society (Gordon, 1991). Macroculture is something which is shared by all participants of an interfirm setting (profession, industry, or occupation) — not just top managers (Abrahmson & Fombrun, 1994). Macroculture specifies roles, role relationships and conventions — accepted approaches and solutions to problems — to be employed by participants (Becker, 1982); thus, macroculture coordinates interdependent activities among independent entities so that complex tasks may be completed.

Macroculture evolves out of the "webs of direct and indirect relationships" (Abrahmson & Fombrun, 1991: 181), as well as institutional sources and the larger national culture within which it exists. The more structurally embedded (e.g., more connected and frequent interactions) industry participants, the more widely shared are their values, assumptions, and role understandings (Abrahmson & Fombrun, 1991; Reddy & Rao, 1990). Interfirm movement of participants diffuses norms, values and expectations among those within the industry (DiMaggio & Powell, 1983; Pfeffer & Leblebici, 1973). In Silicon Valley, industry norms and understandings emerged form and are reinforced by frequent strategic alliances, subcontracting and job hopping of individuals among firms which "blur the boundaries between independent firms" (Saxenian, 1990: 100).

In addition, macrocultures are diffused and sustained through three institutional means. First, socialization received in professions and crafts shapes decisional premises among disperse participants that creates strongly shared macrocultures (Kaufman, 1960; Light, 1979; Van Maanen & Barley, 1984). Socialization is often provided by third parties through formal schooling such as in law, and medicine, or through apprenticeship programs such as guild and trade associations. For example, the Directors Guild provides a limited number of highly coveted apprenticeship slots with the major studios for training directors. Second, trade journals or industry newsletters disseminate information throughout the industry (Abrahamson & Fombrun, 1994). Film industry participants refer to their primary trade journal, Daily Variety, as the "Bible" of the industry (Kent, 1991). In Silicon Valley, the San Jose Mercury News serves this function (Saxenian, 1994). Third, industry events such as trade shows, film festivals and conferences diffuse norms and values by providing role models, setting standards and exchanging information among participants (Jones, 1996). This suggests that macrocultures evolve out of long-term repeated interactions, but that they are sustained by an institutional infrastructure.

Macroculture is critical to understanding network governance because its complex products and services require shared social processes and structures for effective exchange among autonomous partners. Macroculture enhances coordination among autonomous parties in three ways: (1) by creating "convergence of expectations" through socialization so members do not work at "cross-purposes" (Williamson, 1991:278), (2) by allowing for idiosyncratic language to summarize complex routines and information (Williamson, 1975:99-104, 1985:155), and (3) by specifying "broad tacitly understood rules...for appropriate actions under unspecified contingencies" (Camerer & Vepsalainen, 1988:115). Macroculture facilitates efficient exchange among parties because the ground rules among differing parties do not have to be recreated for each interaction (Faulkner, 1987:92-93). The high failure rate of recently formed alliances reveals how important established social processes and structures are to sustaining interfirm interactions (Gulati, Khanna & Nohria, 1994). Research in international joint ventures also show high failure rates due to the difficulty of managing cultural differences among parties (Contractor & Lorange, 1988). All of this suggests that macroculture reduces coordination costs by increasing the ease of exchanging customized goods or services among autonomous parties. Thus,

Proposition 4: The presence of a macroculture reduces coordination costs for customized, complex exchanges. Ceteris paribus, macroculture enhances the likelihood of network governance emerging and thriving in rapidly changing markets for complex, customized tasks.

Although macrocultures enhance network governance in emerging and thriving, they are difficult to establish. Because networks involve disseminating cultural beliefs and values among many autonomous exchange parties, it may take decades to establish the shared understandings, routines and conventions for complex tasks. For example, the network governance in the film industry emerged from interfirm exchanges among the major studios during the 1930s and 1940s which excluded the minor studios (Faulkner & Anderson, 1987). In Silicon Valley, the network developed from second sourcing agreements among initial semiconductor manufacturers (Saxenian, 1990). It also takes third party institutions such as guilds, professional schools or associations to institutionalize common approaches and understandings by socializing new members. In general, macrocultures are enhanced by close geographic proximity because it increases the likelihood and ease of interaction. Macrocultures tend to rise in geographically concentrated areas such as the California Wine industry (Philips, 1994), Silicon Valley (Saxenian, 1990, 1994), Hollywood (Faulkner, 1987), Prato, Italy (Piore & Sabel, 1984; Lazerson, 1995), and Japanese auto and electronic firms around Tokyo (Nishigushi, 1994) Hence, we expect to find network governance in geographically concentrated areas.

The above discussion does not take any account of the content of macroculture. Macrocultures that emphasize the dangers of commercial exchanges, seeing them as opportunities for deception and theft, or which view cooperation among firms, especially competitors, as unethical collusion may hinder the development of network governance. However, at this point little is known empirically about the relationships between macrocultural content and the development of network governance.

Collective Sanctions

Collective sanctions involve group members punishing other members who violate group norms, values, or goals. They range from gossip and rumors, ostracism (exclusion from the network for short periods or indefinitely) to sabotage. Collective sanctions are employed in network governance. In Maine lobster trapping, "interlopers" who violate fishing territories and accepted norms are sanctioned "through surreptitious destruction of their traps" (Acheson, 1985: 386). In the film industry, ostracism is used for violating accepted behaviors. The experience of those involved in making the film Heaven’s Gate is especially instructive (Bach, 1985: 309, 319-22). Contrary to previous agreements, Michael Cimino attempted to make the film artistic rather than commercial. In the process, the film went extensively over budget. After the excessive costs and box office failure became known throughout the industry, sanctions ensued. The perceived misbehavior eventually "led to at least temporary unemployment for almost everyone associated with the picture" (Balio, 1987:339).

Collective sanctions safeguard exchanges. They define and reinforce the parameters of acceptable behavior by demonstrating the consequences of violating norms and values. However, individuals often choose not to enforce social norms because of the costs involved (Olson, 1971). Collective sanctions, supported by metanorms, enforce social norms. A metanorm is a norm for punishing those who do not punish deviants (Axelrod, 1985). In network governance, one's reputation is hurt by recommending someone whose performance does not meet expected standards. For example, Howard Becker describes his experience in the music network based on a colleague’s recommendation who "interrogated" him about his abilities. The colleague told Becker that "..if you can't it's my ass. In fact, it's not just my ass, it's three or four different asses." (1982:87). In effect, this punishes those who do not adequately screen or punish poor performers. Consequently, collective sanctions reduce behavioral uncertainty by increasing the costs of opportunism, decreasing the costs of monitoring to any one party, and providing incentives to sort and monitor compatriots.

Proposition 5: The use of collective sanctions facilitate safeguarding customized exchanges for parties. Ceteris paribus, collective sanctions enhance the likelihood of network governance emerging and thriving in rapidly changing markets for complex, customized tasks.

Collective sanctions have limitations on how accurately they may be applied. For example, one is often unable to discern intentional opportunism from genuine misunderstandings, especially with complex tasks under conditions of high uncertainty. As uncertainty increases, it becomes increasingly difficult to tell when parties have met or left unmet their obligations to one another. As Bhide and Stevenson (1992: 196) note: "the aggrieved party must not only prove that a contract was breached but also the fact that there was even an agreement (a meeting of minds). There is, in fact, a great potential for genuine misunderstandings." In addition, human asset specificity makes it difficult to discern minimal versus best effort.

Reputation

Reputation involves an estimation of one’s character, skills, reliability, and other attributes important to exchanges. Reputation is important under exchange conditions of uncertainty and customization. As environmental uncertainty increases, exchange parties’ become more concerned with information about their own and others reputation (Kollock, 1994). In film, this concern for reputation is seen in the director’s search for information on crew members. Sidney Pollack explains that his strategy for picking a crew is to "research the background of a tentative crew member religiously" (Jones & DeFillippi, 1996). Customized exchanges demand that parties work through problems and develop common understandings. Reputation reduces behavioral uncertainty by providing information about the reliability and goodwill of others.

Reputation safeguards exchanges because it relays the detection of and serves to deter deceptive behavior which enhance cooperation (Parkhe, 1993). As an experienced production manager in film explained that, "...Everyone knows everyone. If you don’t know them, you normally know about them. If you don’t know, you can find out." (Jones & DeFillippi, 1996). A film commissioner confirmed this: "We're a big industry but a small industry because we talk to one another" (Jones, 1996: 65). Reputations have economic consequences for participants in network governance. In the film industry, for example, those "with successful performances and track records move ahead in their careers, those with moderate reputations do not, those with poor reputations experience employment difficulties" (Faulkner & Anderson, 1987:881). "A director does not want to have a reputation for being wasteful because that is harmful to a career," explains director Sidney Pollack. In fact, reputations for mutual adjustment are critical for deciding who gets to repeat exchanges. As Paul Maslansky, a line producer, explains "After all, other productions will follow this one" (Jones & DeFillippi, 1996). Consequently, reputation, supported by structural embeddedness, allows specialized exchanges to occur under a wider range of governance mechanisms (Williamson, 1991:290-91).

Proposition 6: Reputations enhance safeguarding customized exchanges. Ceteris paribus, the more important reputations are, the greater likelihood of network governance emerging and thriving in rapidly changing markets for complex, customized tasks.

Reputations have limitations in their use. Information about reputation may

be inaccurate or misinterpreted. When diffused across long chains of links, information may become distorted, as information is filtered by participants. In addition, over-reliance on reputation may reduce new and innovative information as actors limit their range of partners to a small, increasingly in-bred group. Over time, this may increase homophile, effectively shutting out players that are very different (Blau, 1977). For example, Joan Micklin Silver describes how she was denied an opportunity to do a 46 minute television film by a male producer because she had only done 30 minute films so far. She remembered thinking "the opportunities are going to be extremely rare for me as a woman who wanted to direct" (quoted in Squire, 1983: 39). Others in the film industry complain that the system is an "old boys network" that excludes minorities and women.

Interaction Effects of Social Mechanisms

The interaction of these social mechanisms in network governance may promote cooperative behavior at the same time that they thwart problems characterized as social dilemmas (Schroeder, 1995). "[Social] dilemmas are defined by two simple properties: (a) each individual receives a higher payoff for a socially defecting choice … than for a socially cooperative choice, no matter what the other individuals in society do, but (b) all individuals are better off if all cooperate than if all defect" (Dawes, 1980: 169). Restricted access, structural embeddedness, and collective sanctions align well with Putnam’s (1993: 166) review of the conditions that favor cooperation in the face of collective or social dilemmas: "the number of players be limited, that information about each player’s past behavior be abundant, and that players not discount the future too heavily" along with "graduated sanctions against violators." Social mechanisms of network governance enhance cooperative behavior needed for customized, complex tasks under conditions of uncertainty. Restricted access limits the number of players, structural embeddedness facilitates abundant flows of information about participant’s actions, and collective sanctions and reputation both discourage participants from yielding to incentives for short-term opportunistic behavior.

Proposition 7a: Multiple social mechanisms of restricted access, macroculture, collective sanctions, and reputation interact to decrease coordination costs of and enhance safeguarding customized exchanges. As more of these social mechanisms are used, the likelihood of network governance emerging and thriving is enhanced for overseeing complex, customized tasks in rapidly changing markets.

A key issue in assessing the effectiveness of these social mechanisms for adapting, coordinating, and safeguarding exchanges is their congruence. Congruent mechanisms reinforce one another to promote cooperation. For example, reputation and collective sanctions safeguard semi-specialized or specialized exchanges in network governance by dispersing information about behavior and increasing the costs of malfeasance. However, the content of some social mechanisms may undermine others and create incoherence in the system. For example, macroculture content may inhibit and collective sanctions may penalize information sharing of honest information and undermine coordination even when there is an appropriate social structure for dispersing information about reputations. We suggest that the interplay of social mechanisms and their influence on coordinating and safeguarding exchanges is an area ripe for empirical study.

Proposition 7b: The congruent content of social mechanisms influences the coordination costs and safeguarding of complex, customized exchanges. The more congruent the content of multiple social mechanisms for collaboration and sharing information, the greater the likelihood of network governance emerging and thriving in rapidly changing markets for complex, customized tasks.