Customization or conformity? An institutional and network perspective on the content and consequences of TQM adoption - total quality management

Administrative Science Quarterly,  June, 1997  by James D. Westphal,  Ranjay Gulati,  Stephen M. Shortell

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Researchers in a variety of disciplines have long been interested in identifying conditions that facilitate the spread of technological and administrative innovations. Early studies in this area sought to identify economic and organizational factors that encouraged or hindered innovation adoption by individuals or organizations. Researchers examined the relationship between adoption and such variables as firm size, performance, functional differentiation, slack, and leader characteristics (e.g., Rosner, 1968; Moch and Morse, 1977; Kimberly and Evanisko, 1981). More recent empirical research has explored the role of macro-social factors in facilitating the spread of innovations, some from an institutional perspective (e.g., Baron, Dobbin, and Jennings, 1986; Mezias, 1990, Burns and Wholey, 1993). Institutional perspectives generally emphasize the role of social factors rather than economic or efficiency factors in driving organizational action, including external conformity pressures from regulatory bodies or parent organizations, social pressures from other organizations with ties to the focal organization, as well as collective, social construction processes (e.g., Meyer and Rowan, 1977; Burns and Wholey, 1993; Scott, 1995). In institutional environments these normative pressures contribute to isomorphism, or the emergence of common organizational practices over time (DiMaggio and Powell, 1983). Several recent studies have demonstrated how interorganizational and macro-social factors such as regulatory pressure, as well as more traditional intraorganizational factors like performance, influence the likelihood of adopting organizational innovations (e.g., Baron, Dobbin, and Jennings, 1986; Davis, 1991; Palmer, Jennings, and Zhou, 1993).

While researchers have made significant advances in identifying behavioral determinants of innovation adoption at both the organizational and macro-social levels, several important issues remain largely unexplored. First, researchers have typically treated innovation as a discrete phenomenon, neglecting to examine variation in the form of adoption itself or in implementation. While some innovations are inherently discrete (e.g., specific accounting practices or executive incentive plans), most can vary appreciably in form. When the particular definition or content of an innovation is open to interpretation, as in the case of such innovations as reengineering, matrix management, zero-based budgeting, or total quality management (TQM), variation in the form of adoption may be especially high, such that classifying adoption as an either-or proposition becomes somewhat arbitrary. In such cases, it may be more appropriate to explore how organizations define and implement an innovation, rather than simply to predict whether organizations adopt at all. The importance of this issue is indicated by anecdotal evidence that the success of administrative innovations depends on how they are conceived and implemented (e.g., Lawler and Mohrman, 1985).

A second, unresolved issue concerns the role of interorganizational network ties in diffusion. In attempting to explain evidence that network connectedness can facilitate the spread of discrete innovations, organizational scholars have invoked theories ranging from vicarious learning driven by efficiency imperatives (Rogers, 1983; Mansfield, 1971) to mimetic isomorphism resulting from social cohesion and conformity pressure (Coleman, Katz, and Menzel, 1966; Fligstein, 1985; Burt, 1987; Palmer, Jennings, and Zhou, 1993). There has been little attempt in the diffusion literature to determine when each of these divergent theoretical perspectives is most applicable in explaining the spread of information about an innovation across organizations. Network effects have typically been viewed as fixed and invariant; theorists have not considered how the content of information flowing through networks may change with time.

A third, general shortcoming in the literature is that empirical tests of institutional processes have neglected to examine directly both economic and social consequences of adoption (Scott, 1995). Instead, studies have typically inferred the occurrence of institutionalization from changes in the rate of adoption (e.g., Carroll and Hannan, 1989; Edelman, 1992) or from the decreased predictive power of certain organizational factors over time (e.g., Tolbert and Zucker, 1983). As Scott (1995) noted, however, such residual effects do not necessarily capture institutional factors. For instance, the efficiency or internal effectiveness concerns that drive early adoption may be replaced by a different, unmeasured set of determinants for later adopters. Moreover, increases in the rate of adoption or mimetic isomorphism may reflect social learning efficiencies rather than institutionalization (Rogers, 1983; Abrahamson and Rosenkopf, 1993). In the absence of direct measures of economic and social consequences of adopting innovations, multiple interpretations of observed trends and residual effects are possible.