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Managerial Fads and Fashions: The Diffusion and Rejection of InnovationsAuthor(s): Eric Abrahamson

Reviewed work(s):Source: The Academy of Management Review, Vol. 16, No. 3 (Jul., 1991), pp. 586-612Published by: Academy of ManagementStable URL: http://www.jstor.org/stable/258919 .

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Why have these questions received so much attention? Kimberly (1981)argued that answering them appeared highly practical during the post-World War II era of U.S. economic dominance. In this rich environment,high rates of innovation propelled continuing economic growth. Not sur-prisingly, proinnovation biases developed which suggested that innova-tions benefited adopters, as did their diffusion. Research yielding knowl-edge about how to speed diffusion rates, how to overcome laggards' resis-tance to adopting, or how to intervene in diffusion networks appearedeminently practical in helping to spread these beneficial innovations. Kim-berly (1981: 85) predicted, however, that "as the hopes and myths of thepost-Korean War era confront the doubts and concerns of the 1980's and1990's the social context is likely to change substantially, and this change islikely to be reflected in the literature on innovation. A more skeptical viewof innovation is likely to emerge."This article argues that this skeptical view has emerged, that it requiresresearchers' serious attention, and that this attention requires expandingthe focus of the innovation-diffusion literature. More specifically, the firstpart of the article reviews popular and scientific claims that fads or fashionsare processes that have repeatedly diffused technically inefficient innova-tions among U.S. organizations and caused technically efficient innovationsto be rejected. These claims deserve serious attention. If they are incorrect,they represent incipient anti-innovation biases that could cause organiza-tions to view most innovations as fads and to not adopt these innovations,even if they were technically efficient. If they are correct, fads or fashionswill frequently prompt the diffusion of inefficient innovations and the rejec-tion of efficient ones. Either way, researchers could spend less time onquestions such as What affects diffusion rates? and more time on the centralquestions raised in this article: When and by what process are technicallyinefficient innovations diffused or efficient innovations rejected? Answeringthese questions would provide practical knowledge for managers, who dueto intensifying international competition and reduced organizational slack,are concerned not only with diffusion rates, but also with whether the mosttechnically efficient innovations diffuse and are retained.The second section of the article argues that a perspective, which as-sumes that rational adopters make independent and technically efficientchoices, dominates the innovation-diffusion literature (Rogers, 1962, 1983).This "efficient-choice" perspective perpetuates proinnovation biases be-cause it provides limited help in addressing the questions of when and bywhat processes technically inefficient innovations are diffused or efficientinnovations rejected. To overcome this limitation, the article advances atypology that focuses attention not only on the efficient-choice perspective,but also on three less dominant perspectives that can be used to developpropositions concerning these questions. The third section discusses wheneach of these four perspectives might apply and how to exploit theoreticaltensions or paradoxes opposing these perspectives, in order to generate


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more encompassing innovation-diffusion theories (Poole & Van de Ven,1989; Van de Ven & Poole, 1988).HOW MIGHTFADS OR FASHIONSHARMORGANIZATIONS?

The innovation-diffusion literature has examined the spread of numer-ous types of innovations. This section and the next focus on the literatureregarding the diffusion of innovative administrative technologies, becausethis literature is useful in addressing the two central questions raised here(Daft & Becker, 1978; Kimberly, 1981).1The final section explains, however,that propositions derived from this literature also apply to the diffusion ofnonadministrative innovations.

Writers have used the labels "fad"or "fashion" to describe the diffusionof administrative technologies such as strategic-planning units (Porter,1989), job enrichment (Hackman, 1975), T-groups and matrix structures(Business Week, 1986), quality circles (Lawler &Mohrman, 1985), decentral-ization (Mintzberg, 1979) and joint ventures (Kogut, 1988). They offer twotypes of accounts that describe how fads and fashions harm organizations.The first claims that fads or fashions facilitate the diffusion of technicallyinefficient administrative technologies. Some of these accounts claim thatfads or fashions diffuse technologies that have little utility for any organi-zation. Mitroff and Mohrman (1987: 69), for instance, stated that with grow-ing international competition

U.S. business easily fell prey to every new management fadpromisinga painless solution, especially when itwas presentedin a neat, bright package. Butall simple formulas are eventu-ally bound to fail. By definition, simple formulas cannot copewith complexity,and complexityis what today's world is about.Other accounts of this type argue that fads or fashions fulfill symbolicfunctions such as signaling innovativeness, but do little to boost organiza-

tions' economic performances (Abrahamson, 1986; Fombrun, 1987). Mintz-berg, for instance, stated that "the swings between centralization and de-centralization at the top of large American corporations have resembled the

' Tushman and Anderson (1986: 440) defined technologies as "those tools, devices andknowledge that mediate between inputs and outputs." Here "administrative technologies" aredefined as prescriptions for designing organizational structures and cultures. Some of theseprescriptions, such as those for designing and running matrix forms, affect the overall structureof organizations; others, such as those pertaining to strategic-planning units, affect only certainorganizational subunits. When organizations implement these technologies they mediate be-tween organizational inputs and outputs. This transformation process is enhanced by firm-specific tacit knowledge and skills about how to implement prescriptions (Polanyi, 1967; Teece,1977). Consequently, administrative technology A is defined as being more "technicallyefficient" than technology B, if with equal levels of tacit knowledge and skills on how to use Aand B, technology A transforms equal inputs into greater outputs than does technology B.


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movement of women's hem lines" (1979: 294). Still other accounts claim thatfads or fashions facilitate the adoption of technologies that are technicallyefficient for certain organizations, but not for many of those that adopt them(Rogers, 1962, 1983). Rumelt (1974), for example, tested Chandler's (1962)claim that multidivisional structures solved the administrative problemscaused by diversification strategies. He found that diversification did notcorrelate with the adoption of a multidivisional structure after the early 1960sand concluded that structure follows not only strategy, but also fashion.A second type of account claims that fads or fashions harm organiza-tions' economic performances because they prompt rejections of adminis-trative technologies that had the potential to become technically efficient fortheir adopters. This type of account assumes that technologies become ef-fective only through gradual, careful, and sustained implementation pro-cesses that provide organizations with tacit knowledge and the skills nec-essary to implement these technologies efficiently (Polanyi, 1967; Teece,1977). However, in some of these accounts fads or fashions cause organi-zations to leap rapidly from one technology to the next, so that no technol-ogy has enough time to work (Hackman, 1975; Lawler & Mohrman, 1985). Inother accounts, managers jump rapidly from one problem to the next, sothat technologies do not solve problems because these problems go out offashion before technologies can solve them (March & Olsen, 1976; Schon,1971). OVERCOMING ROINNOVATION IASES

Reviewers of the innovation literature unanimously agree that it con-tains proinnovation biases (Downs & Mohr, 1976; Kimberly, 1981; Rogers,1962, 1983; Rogers & Schoemaker, 1971;Van de Ven, 1986; Zaltman, Dun-can, & Holbeck, 1973). Kimberly (1981) defined proinnovation biases as pre-sumptions that innovations will benefit organizations. Proinnovation biasesinfluence not only the questions that the innovation-diffusion literature em-phasizes, such as what determines diffusion rates, but also the questionsthat the literature deemphasizes. These biases, for instance, suggest anobvious answer to the question: Why do innovations diffuse or disappear?Innovations diffuse when they benefit organizations adopting them, andthey disappear when they do not. It makes little sense, therefore, to ask whatprocesses impel or counter the diffusion of innovations, when do these pro-cesses take hold, and to what extent do these processes cause the diffusionor rejection innovations. It makes even less sense to ask whether certainprocesses diffuse nonbeneficial innovations or cause the rejection of bene-ficial ones.

Recognizing how proinnovation biases limit questions addressed in thediffusion of innovation literature is important, but it does not explain how toresearch questions that do not reflect these biases. To do so, theorists musttake three steps. First, they must examine how the dominant theoreticalperspective in the innovation-diffusion literature contains assumptions thatreinforce proinnovation biases. Second, theorists must reject these assump-


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tions in order to reveal counterassumptions, which underlie less dominantperspectives that do not reinforce proinnovation biases. Third, theoristsmust develop these less dominant perspectives in order to investigate ques-tions that do not reflect proinnovation biases.The following section explains this three-step sequence. First, two ma-jor assumptions that underlie the dominant perspective in the innovation-diffusion literature are rejected in order to reveal two counterassumptionsthat support less dominant perspectives. Second, a 2 x 2 matrix, which isdepicted in Table 1, is developed. Each cell in the matrix contains a per-spective based on a different combination of the two assumptions and coun-terassumptions. Third, the less dominant perspectives in the matrix are usedto develop propositions concerning when and how technically inefficientadministrative technologies are diffused or efficient technologies are re-jected.Assumptions in the Dominant Perspective

Rogers (1983) argued that the dominant perspective in the diffusion ofinnovation literature reinforces proinnovation biases because it relies on amodel of choice in which adopters make independent, rational choicesguided by goals of technical efficiency. This efficient-choice perspectivereinforces proinnovation biases because it suggests that a rational adopternever decides to adopt a technically inefficient administrative technologythat was diffusing or to reject a technically efficient administrative technol-ogy that this organization had adopted.The efficient-choice perspective is based on two major assumptions(March, 1978): (a) organizations within a group can freely and indepen-dently choose to adopt an administrative technology and (b) organizationsare relatively certain about their goals and their assessments of how effi-cient technologies will be in attaining these goals. As a result, organiza-tional choices can be rational and can lead to the selection and retention oftechnically efficient administrative technologies. If the two assumptions thatunderlie the efficient-choice perspective reinforce proinnovation biases,then rejecting these assumptions will help researchers to find less dominantperspectives that can be developed to counter these biases.Generating Counterassumptions

How is it possible to reject the efficient-choice perspective's firstassump-tion that organizations within a group freely and independently chooseadministrative technologies? One way is to develop a counterassumptionstating that organizations outside this group, such as regulatory bodies orconsulting firms, influence the choices made by organizations within thisgroup. Perspectives that are founded on this counterassumption of outsideinfluences help in countering proinnovation biases because they can indi-cate when it is in the interest of organizations outside a group to impel thediffusion of administrative technologies that are technically inefficient fororganizations within this group (Kimberly, 1981; Rogers, 1983). These per-


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spectives also indicate when it is in these outside organizations' interest toprompt the rejection of efficient technologies.The outside-influence dimension in Table 1 distinguishes two types ofperspectives: those, such as the efficient-choice perspective, that assumethat organizations inside a group will impel the diffusion of innovations, andthose that counterassume that organizations outside such groups will impelthe diffusion of innovations.How is it possible to reject the efficient-choice perspective's second as-sumption that organizations make independent, rationally efficient choicesbecause they are guided by relatively clear organizational goals and as-sessments of administrative technologies' efficiency in attaining thesegoals? One way is to make the counterassumption that organizations have

unclear goals and high uncertainty about the technical efficiency of admin-istrative technologies (March & Olsen, 1976). Such organizations could notrationally choose technically efficient administrative technologies becausethey would not be able to assess technical efficiency. Also, these organiza-tions would not have clear goals to help them decide which type of technicalefficiency mattered in attaining organizational goals. According to perspec-tives that include this counterassumption, under conditions of uncertainty,organizations imitate other organizations-they base their decisions ofwhich administrative technology to use on the decisions of other organiza-tions (DiMaggio & Powell, 1983; Thompson, 1967).In the following section, the focus is placed on perspectives which statethat imitation impels the diffusion of innovations, because developing theseperspectives helps in countering proinnovation biases. These perspectivesindicate when organizations will imitate technically inefficient administra-

TABLE1Theoretical Perspectives Explaining the Diffusion and Rejection ofAdministrative Technologies

Imitation-Focus DimensionImitation ImitationProcesses Processes

Do Not Impel Impel thethe Diffusion Diffusionor Rejection or Rejection

Organizations Withina Group Determine Efficient-Choice Fadthe Diffusion and Perspective PerspectiveOutside- ~Rejection WithinOutside- This GroupInfluence

Dimension Organizations Outsidea Group Determine Forced-Selection Fashionthe Diffusion and Perspective PerspectiveRejection WithinThis Group


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tive technologies and when such technologies will be diffused. Organiza-tions, moreover, may not only imitate other organizations' decisions toadopt a technology; they may also imitate decisions to reject it. These per-spectives, therefore, help overcome proinnovation biases because they in-dicate when imitation will impel widespread rejections of technically effi-cient administrative technologies.The vertical imitation-focus dimension in Table 1 distinguishes twotypes of perspectives: those that assume that imitation processes impel thediffusion and rejection of innovations and those that do not.The Efficient-Choice Perspective

Explanations guided by what this article calls the efficient-choice per-spective assume that agents, usually organizations or their top manage-ment teams, have little uncertainty about (a) their preferences or goals, bethey profit maximization, market share growth, competitive advantage, orany other strategic preference and (b) innovations' technical efficiency mea-sured as the ratio of outputs to inputs (Grandori, 1987). Therefore, givenexisting resource constraints, agents rationally choose the innovation thatwill allow them to most efficiently produce the outputs that are useful forattaining their goals.Explaining diffusion. Theories in the efficient-choice perspective canexplain when and by what processes administrative technologies are dif-fused. They suggest that environmental changes create similar perfor-mance gaps across organizations (Grandori, 1987). Performance gaps arediscrepancies between an organization's goals and the goals that this or-ganization can attain. Demand-pull explanations stress how environmentalchanges can engender new performance gaps among organizations withsimilar goal orientations, prompting them to adopt innovations closing thesegaps. Supply-push explanations focus on how changes in scientific or tech-nological knowledge present organizations with innovations that either re-veal new performance gaps or close old ones. Despite ongoing debatesover whether and which research supports demand-pull or supply-pushexplanations (Mowery & Rosenberg, 1988; Thirtle & Ruttan, 1987), theoristswho use the efficient-choice perspective concur that organizations with sim-ilar goals tend to react to performance gaps by adopting the same, efficientadministrative technology. Of course, business organizations that do notexperience these environmentally induced performance gaps or that havedifferent goals will decide not to adopt these technologies.Williamson's (1970) explanations for the diffusion of the M-form exem-plifies an efficient-choice perspective. He argued that organizationsadopted the M-form over the functional structure (U-form) because it wasmore technically efficient for large, diversified organizations attempting tomaximize profits. He stated that "the organization and operation of the largeenterprise along the lines of the M-form favors goal pursuit and least-costbehavior more nearly associated with the neo-classical profit maximizationhypothesis than does the U-form organizational alternative" (1970: 134). A


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study by Armour and Teece (1978) supports Williamson's M-form hypothesisfor two classes of large industrial firms. These arguments and researchfindings suggest thatProposition 1: Performance gaps will prompt the diffusionof innovations only among organizations that can effi-ciently close these gaps by adopting these innovations.Theorists who follow the efficient-choice perspective recognize a fewexceptions to this proposition. They assume, for example, that for-profit or-ganizations may seek to maximize their competitive advantage. Adminis-trative technologies, however, confer comparative rather than absolute ad-vantage. Therefore, the competitive advantage conferred by an organiza-tion's adoption of an administrative technology vanishes as competitorsadopt it (Starbuck & Nystrom, 1981). In the case of oligopolies, organizationsare few enough to recognize the impact of their actions on those of compet-itors (Caves, 1967). Therefore, potential adopters in oligopolies may notadopt a technically efficient administrative technology because they shouldknow that doing so will prompt competitors to imitate them and will elimi-nate their nonsustainable competitive advantage (Sherer & Ross, 1990).

Explaining rejection. Studies using the efficient-choice perspectiverarely trace both the diffusion and rejection of administrative technologies.Piecing studies together, however, provides instances of such life cycles.Chandler (1962), for example, noted that the U-form spread during the eco-nomic expansion of 1896 because it was an efficient answer to administra-tive problems created by environmentally induced growth in organizations'sizes. Rumelt (1974) noted, however, that the U-form's popularity had de-clined sharply by 1969 because it was not the answer to administrativeproblems caused by diversification strategies. It should be noted that theo-ries that maintain that life cycles deterministically impel innovations' pro-gressions through preordained stages of invention, innovation, diffusion,maturity, and rejection have received little empirical support (Gold, 1964)and have been criticized on logical grounds as well (DeBresson & Lampell,1985a, b).Chandler's and Rumelt's studies provide a nondeterministic demand-pull explanation for the rejection of an administrative technology; technol-ogies diffuse when they reduce performance gaps, and they lose popularitywhen changes eliminate or modify these gaps. A supply-push explanationstates that changes in technological or scientific knowledge may introduceinnovative substitutes that reveal new performance gaps or close old onesmore efficiently (Kimberly, 1981; Zaltman et al., 1973). As a result, thesesubstitutes prompt widespread rejections of the old technologies they re-place. These arguments suggest thatProposition 2: Organizations in a group will tend to rejectan innovation when environmental changes render itless technically efficient in closing these organizations'performance gaps.


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The Forced-Selection PerspectiveOrganizational theories that have a bearing on administrative technol-ogies have pointed to the "political environment of organizations" (Carroll,Delacroix, & Goodstein, 1988: 361) and to "institutional entrepreneurs"(DiMaggio, 1987)-powerful organizations outside a group of organizations

among which an administrative technology diffuses. These powerful orga-nizations may have an interest in forcing a technically inefficient adminis-trative technology to diffuse or an efficient technology to be rejected, despiteorganizations' resistance to adopting or rejecting this technology (Abra-hamson & Fombrun, in press).

Explaining diffusion. According to the forced-selection perspective, anumber of organizations control sufficient power to dictate which adminis-trative technologies will diffuse across organizations. Theorists have arguedthat the legitimate power of governmental bodies allows these organiza-tions to force the diffusions of innovations (Carroll et al., 1988; DiMaggio,1987; Scott, 1987). For example, Barron, Dobbin, and Jennings (1986) usedthe forced-selection perspective when they showed how government war-labor boards forced the diffusion of personnel administration technologiesduring World War II. Others have focused on the powerful influences thatnational labor unions can exert by threatening general strikes or that asso-ciations of managers can exercise through unified actions (Jacoby, 1985;Kochan & Capelli, 1984). In general, these explanations suggest thatProposition 3: Technically inefficient innovations will tendto diffuse among groups of organizations when these in-novations receive the backing of powerful organizationsoutside these groups.

Explaining rejection. Researchers who use forced-selection theoriesassume that powerful organizations may or may not have conflicting pref-erences concerning whether they want organizations to use a particularadministrative technology (Benson, 1975; Covaleski & Dirsmith, 1988;Rowan, 1982). When powerful organizations' interests and preferences arehomogenous in favoring a technology, they will act in concert to back itsdiffusion and retention. When, to the contrary, these organizations havediverse interests and preferences, some will exert political pressures en-couraging the continued use of a technology, whereas others will try to forceits rejection. If the latter have greater power, they will prompt rejections.This explanation suggests that

Proposition 4: A group of organizations will tend to rejecta technically efficient innovation when organizations,outside this group, exerting political pressures to rejectthis innovation, have greater power than those exertingpressures to retain it.Cole's (1985) study of the diffusion and rejection of participative man-agement technologies in Japan, Sweden, and the United States provides a


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rare example of research conducted according to the forced-selection per-spective that has a bearing on an administrative technology's rejection. Hefound that during the 1960s and 1970s, labor unions and national associa-tions of managers in both Japan and Sweden supported the diffusion andretention of participative management technologies. As a result, these tech-nologies diffused and were retained. He noted, however, that in the UnitedStates, the conflicting preferences of these two types of organizationscaused a drop in the popularity of participative management technologies.The Fashion Perspective

Perspectives that assume conditions of uncertainty concerning environ-mental forces, goals, and technical efficiency claim that under these con-ditions organizations will tend to imitate other organizations (DiMaggio &Powell, 1983; Thompson, 1967). According to such perspectives, organiza-tions' decisions center less around which technology they should adopt, andmore around which organization they should imitate.The fashion perspective assumes that under conditions of uncertaintyorganizations in a group imitate administrative models promoted by "fash-ion-setting organizations"-organizations, outside this group, such as con-sulting firms or business mass media, whose missions involve the creationor dissemination of such models (Hirsch, 1972). The innovation-diffusionliterature has examined such "opinion leaders," but mostly to explain vari-ations in adoption rates (Mahajan &Peterson, 1985).This research provideslittle help, therefore, in explaining when and how these organizationsprompt the diffusion or rejection of innovations.Explaining diffusion. Organizational theorists have only begun to ar-ticulate which organizations participate in setting administrative fashionsand why organizations imitate models of administrative technologies thatfashion setters promote. Blumer (1969) recognized that administrative mod-els did not become fashionable by direct popular demand. He argued in-stead that fashion setters played active roles in selecting a few administra-tive models from many and in developing organizations' awareness andtastes for these models in order to render them fashionable and to prompttheir diffusion. Hirsch (1972) extended this line of inquiry by showing thatnetworks of specialized organizations set fashions for books, phonographrecords, and motion pictures.Though Hirsch (1972) examined fashion-setting networks, he did notexplore how such networks set fashions in administrative realms. Variousorganizational theorists, however, have claimed that consultants, businessschools, and business mass media populate these administrative fashion-setting networks (DiMaggio & Powell, 1983; Kimberly, 1981; Mintzberg,1979). Abrahamson (1986) suggested that business schools and consultingfirms, because of their expertise, may dominate in the selection of fashion-able administrative models. Business mass-media organizations, like For-tune, and publishers of popular business books, like In Search of Excel-


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lence, may dominate in the dissemination of these fashions because of thelarge audiences these organizations can reach.Organizational theorists have examined why organizations imitate theadministrative models promoted by organizations that belong to fashion-setting networks (Czarniawska-Joerges, 1988; DiMaggio & Powell, 1983;

Ginsberg & Abrahamson, in press). They have argued that fashion setters,unlike governmental organizations or labor unions, do not have the coer-cive power necessary to force organizations to imitate them. Instead, fash-ion setters' power to influence fashions stems from their capacity to inspireorganizations to trust their choices of technologies and to imitate them. Thefashion perspective suggests thatProposition 5: Technically inefficient innovations will tend

to diffuse among organizations when organizations infashion-setting networks promote them.It must be noted that administrative fashion-setting organizations maymarket only the most technically efficient administrative technologies and,therefore, might only influence the diffusion of efficient technologies andrejection of inefficient ones. Alternatively, fashion-setting organizationsmay select only administrative technologies they believe they can marketprofitably, regardless of how technically efficient the technologies would befor organizations. Fashion-setting organizations may, therefore, impel thediffusion of inefficient technologies or the rejection of efficient ones.Explaining rejection. Organizational theorists have only provided briefdescriptions of when and by what processes administrative fashion-settingnetworks trigger rejections of administrative technologies (Abrahamson,1986; Fombrun, 1987). Mintzberg (1979) claimed, for instance, that just asshorter and longer skirts recurrently replace each other, so do fashions forcentralization and decentralization in organizations. Such descriptions im-ply that new administrative technologies drive out old ones because theyare mutually exclusive. This implication suggests thatProposition 6: Organizations will tend to reject old tech-

nically efficient innovations when fashion-setting net-works introduce mutually exclusive replacements.The popularity of fashionable technologies may also decline becausethey are only "symbolically efficient" or "emotionally efficient." TechnologyA is more symbolically or emotionally efficient than technology B if its usefulfills more nontechnical functions such as instilling hope, signaling inno-vativeness, or relieving boredom. As innovative administrative technolo-gies age, however, they may lose their power to signal innovativeness.Over time, administrative technologies also may not fulfill the hopes theygenerated when organizations adopted them. Finally, the use of innovativetechnologies invariably becomes routine, and boredom may resurface.When the symbolic or emotional effectiveness of fashionable administrativetechnologies has largely decayed, organizations may tend to reject them.Such arguments suggest thatProposition 7: Over time, organizations will tend to reject


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technically efficient innovations promoted by fashion-setting networks.The Fad Perspective

Both the fad and fashion perspectives assume that the diffusion of in-novations occurs under conditions of uncertainty because organizations im-itate other organizations' adoption decisions. The fashion perspective as-sumes that organizations in a group imitate other organizations, such asmanagement consulting firms, that reside outside that group. The fad per-spective differs, however, because it assumes that the diffusion of innova-tions occurs when organizations within a group imitate other organizationswithin that group.

Theorists have advanced explanations in the fad perspective that focuson the communication of knowledge, social interactions, or economic inter-ests. Certain explanations focusing on communication claim that an orga-nization imitates other organizations' choices of an innovation when it ob-tains from these adopters knowledge that reduces ambiguity about the in-novation (Rogers, 1962, 1983). Other models focusing on social interactionsargue that an organization imitates other organizations in order to appearlegitimate by conforming to emergent norms that sanction these innovations(Carroll & Hannan, 1989;DiMaggio & Powell, 1983; Meyer & Rowan, 1977;Zucker, 1977). Finally, explanations that emphasize economic interests as-sert that an organization imitates competitors' choices of innovations in or-der to avoid the risk that these competitors could gain a competitive advan-tage by using this innovation (Abrahamson &Rosenkopf, 1990;Arthur, 1988;Katz & Shapiro, 1985; Mansfield, 1961).Writers have also advanced explanations that stress the individualcharacteristics, numbers, or interactions of organizations in order to explainwhich organizations imitate which others. Explanations stressing individualcharacteristics state that organizations that are low on certain characteris-tics will imitate the adoption decisions of organizations that are high onthese characteristics, or vice versa. Certain explanations, for example, statethat organizations imitate the adoption decisions of organizations that havereputations higher than their own (DiMaggio & Powell, 1983; Fombrun &Shanley, 1990; Mohr, 1969). In a rare study of this phenomenon, Walker(1969) showed that when U.S. states with high reputations adopted regula-tions, this triggered the diffusion of these regulations across states withlower reputations. Explanations that stress numbers assert that organiza-tions may experience "bandwagon pressures"-pressures to adopt an in-novation that increase according to the number of other organizations thathave already adopted it (Abrahamson & Bartner, 1990; Katz & Shapiro,1985;Mansfield, 1961). Explanations that emphasize interactions claim thatorganizations imitate other organizations that are proximate either geo-graphically (Brown, 1981) or in their communication networks (Burt, 1987;Galaskiewicz & Wasserman, 1989).This literature generally examines how imitation processes impel the


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diffusion of innovations in order to examine variations in diffusion rates orsequencings. It rarely considers which factors and processes might countersuch diffusion. This is unfortunate because examining simultaneously thepressures impelling and countering the diffusion of innovations makes itpossible to develop threshold models that pinpoint when administrativetechnologies will diffuse or will be rejected. These models specify the pointor threshold beyond which impelling pressures, by overwhelming counter-ing pressures, can begin to diffuse a technology. They also specify thethreshold beyond which pressures that had triggered the diffusion of aninnovation are overwhelmed by countering pressures, and the diffusionstops or gives way to rejection.Explaining diffusion. The epidemiological literature (Bailey, 1975) sug-gests that two types of mechanisms can counter "contagious diffusion"-diffusion that occurs when organizations that imitated other organizationsare imitated in turn. One mechanism immunizes organizations to varyingdegrees from imitating others, thereby either blocking contagious imitationor limiting its scope. The information, conformity, and competition explana-tions described previously recognize different immunizers, and they areexamined first. The second type of mechanism removes from the pool ofadopters certain organizations that imitated others, so that these organiza-tions cannot be imitated by other organizations.

Explanations for contagious diffusion that focus on the communicationof knowledge recognize at least two immunizers: heterophily and discon-nectedness. Rogers (1983: 18) defined heterophily as "the degree to whichpairs of individuals who interact are different in certain attributes." Innova-tion-diffusion research indicates that heterophyllous organizations are lessreceptive to each other's communication and therefore more immune toimitating each other (Rogers, 1983). Disconnectedness is the degree towhich an organization is not linked to others in a communication network.Disconnected organizations should learn less from adopters and should bemore immune to imitating the adopters' decisions.

Explanations stressing social interactions point to institutional normswhich dictate that organizations conform to past innovations in order toappear legitimate (Meyer & Rowan, 1977). Organizations may feel boundby these norms to differing degrees and, therefore, may have greater orlesser immunity to imitating other organizations' adoptions of innovations(Granovetter, 1978).Explanations emphasizing economic interests suggest that under con-ditions of uncertainty, an organization will calculate the expected returnsfrom adopting an innovation. An organization may be relatively immune toimitating another organization's adoption of an innovation if it expects neg-ative returns from the innovation (Abrahamson & Rosenkopf, 1990).A few models consider how the demography of immunities in a groupof organizations affects the diffusion of innovations. Granovetter (1978), forinstance, advanced a model which assumes that pressures to imitate others'adoption decisions increase according to the number of adopters, but that


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people have varying thresholds beyond which they will give in to thesepressures. His model generates recursive processes in which individualswith lower thresholds give in to smaller conformity pressures, raising thenumber of adopters and the strength of conformity pressure and promptingindividuals with higher thresholds to imitate.

Granovetter's model can be easily translated from an individual to anorganizational unit of analysis. Consider five organizations with immunitiesof 0, 1, 2, 3, and 4. The immunity number of an organization indicates thatit will remain immune to imitating other organizations until that number oforganizations have adopted. Therefore, the immunity 0 organizationadopts, bringing the number of adopters to 1 and triggering the immunity 1organization's decision to imitate. Because the number of adopters thenequals 2, the immunity 2 organization imitates, triggering the immunity 3organization's imitation. This recursive process drives the bandwagon untilall five organizations have adopted. This model can incorporate a reputa-tional effect, such that higher reputation organizations have a greater im-pact in triggering imitation, if higher reputation organizations' adoptionscount for more than one.

It is important to note that different demographics of immunities pro-duce dissimilar diffusion patterns. If, for instance, the immunity 2 organiza-tion had immunity 3 in the above example, then the diffusion would haveended after two adoptions. This research suggests thatProposition 8: The propensity of organizations in a groupto imitate each other's decisions to adopt a technicallyinefficient innovation will vary with the nature of pres-sures impelling imitation and the demography of immu-

nities in that group to succumbing to this pressure.Explaining rejection. In extreme cases, adoptions of highly technicallyinefficient administrative technologies could put an organization at a great

competitive disadvantage and could lead to its removal from a group ofadopters by bankruptcy (Hannan & Freeman, 1977). More generally, how-ever, organizations may reject an administrative technology because byusing it, they learn that it is inefficient (Van de Ven & Polley, 1990) orbecause its faddish appeal dissipates (Abrahamson, 1986).

Removal may also occur because of counterbandwagons-pressuresfor organizations to reject an administrative technology that increase instrength according to the number or reputation of organizations that haveadopted it. If, for example, an organization adopts an administrative tech-nology in order to achieve a competitive advantage, as competitors imitateit, its competitive advantage will decrease, possibly prompting it to rejectthis technology and adopt another (Carroll & Hannan, 1989; Nystrom &Starbuck, 1981). Likewise, an organization may adopt a technology to dis-tinguish itself from organizations with lower reputations. The more organi-zations with lower reputations imitate it, however, the more it looks like alower reputation organization. In this case there will be a greater pressureto reject the technology and adopt a new one that will redistinguish the


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600 Academy of Management Review Julyorganization from others with lower reputations (Abrahamson, 1986). Eitherof these two processes could trigger a cycle of bandwagon rejections, so thatpressures to reject the innovation increase according to the number of otherorganizations that have already rejected it.Itmust be noted that organizations may also be more or less immune toimitating other organizations' decisions to reject an administrative technol-ogy. Specifying how demographic characteristics interact with imitationpressures to prompt adoptions and rejections may help to explain the extentof contagious diffusion and the point at which the number of adopters dropsbelow the number of rejecters. This research suggests thatProposition 9: The propensity of organizations to imitateeach other's decisions to reject a technically efficient in-

novation will vary with the nature of pressures impellingand countering imitation and the demography of immu-nities in that group to succumbing to these pressures.HOW TO EXPLOIT ARADOXES N THEINNOVATION-DIFFUSIONITERATURE

This article advances four perspectives for understanding when orga-nizational processes impel the diffusion or rejection of innovations amonggroups of organizations, whether or not these innovations are technicallyefficient for these organizations. The article raises the problem, however, ofresearching phenomena that are explainable through multiple perspec-tives.

This section examines two resolutions to this multiperspective problem:a "contingency resolution" and a "paradox resolution." The contingencyresolution specifies types of diffusion contexts and innovations for which oneperspective will have high explanatory power relative to others, becausethis perspective rests on assumptions that match these types. For example,theorists typify innovations according to whether organizations are certainor uncertain about their technical efficiency (Meyer &Rowan, 1977). The fadperspective should have high explanatory power with the later type of in-novation because this perspective assumes uncertainty about innovations'technical efficiency.Contingency resolutions will help researchers if and when innovationsor contexts fall into the types theorists devise to classify them. Put differently,many innovations or contexts may only resemble different hybrids of typestheorists could specify. Many innovations, for example, may tend towardmoderate levels of uncertainty, and uncertainty may varv across organiza-tions and stages of diffusion. Therefore, in most instances, researchers willnot know whether to use perspectives that assume a high or low uncertaintytype of innovation. Researchers may also find weak results whichever per-spective they do use, because each perspective rests on assumptions thatwill only partly fit the hybrid type under study.Van de Ven and Poole (1988) and Poole and Van de Ven (1989) sug-


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1991 Abrahamson 601gested a paradox resolution that might allow researchers to develop theo-ries that capture the complexity of hybrid types: exploiting paradoxes be-tween different perspectives. These authors defined paradoxes as "interest-ing tensions, oppositions, and contradictions between theories which createconceptual difficulties" (Poole & Van de Ven, 1989: 564). They provided thefollowing tools with which to exploit paradoxes in order to stimulate theo-retical developments: (a) clarify levels of analysis, (b) take time into account,and (c) introduce new terms.This section illustrates how to exploit paradoxes created by contradic-tory assumptions among the four perspectives in order to generate tailor-made theories for varied innovations or contexts. This type of paradox res-olution works because it does not assume that different perspectives simplyapply to certain innovations or contexts and not to others. It assumes insteadthat each perspective captures some aspect of every innovation and diffu-sion context. Researchers exploiting paradoxes can, therefore, combine twoor more of the perspectives to generate a variety of theories embodyingassumptions that fit the idiosyncrasies of each innovation and diffusion con-text. Thus, theories generated by this approach may help to explain thediffusion of different types of innovations: not only administrative technolo-gies, but also of nonadministrative innovations, such as production tech-nologies, strategic actions, R&D projects, and entrepreneurial ventures.This approach also may help researchers to study the diffusion of thesevarious innovations in different types of diffusion contexts, for example, inprofit, not-for-profit, industrial, service, or U.S. and non-U.S. diffusion con-texts. More generally, this approach to theorizing may introduce the flexi-bility necessary for researchers to generate theories that incorporate as-sumptions that match the innovation or context they study and, thereby,provide for stronger empirical findings.How to Exploit Paradoxes on the Outside-Influence Dimension

A theory should have greatest explanatory power when the assump-tions that underlie it match the context in which researchers test this theory.Certain perspectives assume that organizations outside a group of organi-zations will determine the diffusion of innovations within these groups.Thus, it follows thatProposition 10: Perspectives that assume that organiza-tions outside a group of organizations will determine thediffusion of innovations within that group will have high

explanatory power in contexts in which these outside or-ganizations have both an interest in directing the diffu-sion of innovations and sufficient power to do so.

To the contrary,Proposition 11: Perspectives that assume that organiza-tions within a group will determine the diffusion of inno-vations within that group will have high explanatorypower in contexts in which organizations outside that


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group either have no interest in directing the diffusion ofinnovations or insufficient power to do so.This article does not attempt to specify all the diffusion contexts andinnovations under which Propositions 10 and 11 might hold. It provides

instead an example of such a specification in order to indicate when thistype of contingency resolution may be insufficient and a paradox resolutionmay become necessary. Proposition 10 suggests that forced-selection per-spectives might have the greatest explanatory power during wars or de-pressions, because in such cases many societal sectors expect governmen-tal organizations' interventions and they receive political backing to forceonto organizations innovations that are necessary to resolve these crises(Lindblom, 1977). This may explain why forced-selection perspectives ex-plain the diffusion of innovations occurring during these crises (Barron,Dobbin, & Jennings, 1986; Carroll, Delacroix, & Goodstein, 1988). To thecontrary, in noncrisis contexts, governmental organizations may exert littleinfluence over business organizations. Other perspectives may havegreater explanatory power at such times, because they assume that orga-nizations are not influenced by governmental organizations when theyadopt or imitate innovations.A typology of diffusion contexts in which organizations outside a groupeither exert absolute influence over all organizations in that group or noinfluence over any organization will help researchers if and when contextstend to match these types. Ifcontexts do not match these types, researcherswill have to use a paradox resolution in order to develop perspectives thatexplain the diffusion of innovations occurring in these hybrid types. Orga-nizations outside a group may, for example, continuously exert some but notabsolute influence over all organizations in a group. National labor unionsno longer exert the widespread influences they did after the labor crisesleading to the passage of the Wagner Act. They may, however, influenceorganizations that either have or risk having strong union chapters (Free-man & Medoff, 1989). Likewise, management consulting firms may not in-fluence administrative fashions used by all organizations. They may do so,however, with organizations that can afford their services. What type ofperspective will explain the diffusion of innovations occurring in these hy-brid diffusion contexts where outside organizations exert some, but not ab-solute control?

Exploiting paradoxes between perspectives based on contradictory as-sumptions suggests answers to such questions. For example, understand-ing the diffusion of innovations in contexts where organizations outside agroup do not exert absolute control over diffusion in that group may requireexploiting paradoxes between perspectives that rest on contradictory as-sumptions, such as (a) outside organizations control the diffusion of innova-tions and (b) organizations freely select innovations that diffuse. Such res-olutions generate theories based on assumptions that match contexts that donot fall neatly into a single type.One such resolution overcomes tensions between efficient-choice and


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1991 Abrahamson 603

forced-selection perspectives. It does so by introducing a new term thatdistinguishes what was defined above as "technical efficiency" from "polit-ical efficiency"-Innovation A is defined as more politically efficient thanInnovation B if organizations using A tend to incur relatively fewer costs,such as legal proceedings or lost government contracts, imposed by outsideorganizations, such as regulators or the military. This resolution makes itpossible to consider simultaneously both the political costs for an organiza-tion in a group of organizations that are not conforming to external organi-zations' pressures and the technical costs for this organization of adoptingan innovation that is technically inefficient for it. This resolution implies thatif organizations behave as profit-maximizing decision systems, they shouldconsider both political and technical efficiency of innovations in selectingthe least-cost alternative. This explanation suggests thatProposition 12: Technically inefficient innovations backed

by organizations outside a group of organizations shoulddiffuse only among organizations, within that group, forwhich the political costs of not conforming to pressuresexerted by outside organizations exceed the technicalcosts of adopting technically inefficient innovations.

Conversely,Proposition 13: Widespread rejections of technically effi-cient innovations opposed by organizations outside agroup of organizations will occur only among organiza-tions, within that group, for which the political costs of notconforming to pressures exerted by outside organizationsexceed the technical gains from retaining these techni-cally efficient innovations.

Another resolution exploits tension between fad and fashion perspectives.This resolution specifies a temporal ordering in which fads trigger fashionsor vice versa. The incipient faddish diffusion of innovations may, for in-stance, signal to fashion-setting organizations the emergence of marketniches for these innovations. Fashion-setting organizations may decide thatit is in their economic interest to promote these innovations, thereby rein-forcing the faddish diffusion. This reasoning suggests thatProposition 14: The faddish diffusion of technically inef-ficient innovations will prompt fashion-setting networks toback this diffusion.Alternatively, when fashion-setting networks promote innovations,these networks may enhance innovations' power to confer a higher repu-tation to organizations that adopt them. As a result, organizations mayadopt these innovations in order to heighten their reputations, and organi-zations with lower reputations may imitate them. This reasoning suggeststhat Proposition 15: When fashion-setting networks back thediffusion of technically inefficient innovations, they willtend to promote their faddish diffusion.


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It should be noted that the aim in advancing Propositions 12 through 14was not to generate all resolutions to the paradoxes between theories in thefour perspectives. Indeed, these perspectives suggest a large number ofparadoxes and propositions. Rather, it was to provide examples of howexploiting paradoxes between these theories could generate other theoriesthat might fit the idiosyncrasies of varied innovations and diffusion contexts.How to Exploit Paradoxes on the Imitation-Focus Dimension

Theories on the imitation-focus dimension should have the greatest ex-planatory power when the assumptions that underlie these theories matchthe context in which the researchers test them. Perspectives that emphasizeimitation processes assume that organizations are uncertain about environ-mental impacts, goals, or technical efficiency. This explanation suggeststhat Proposition 16: Perspectives that assume that imitationprocesses impel the diffusion of innovation will havehighest explanatory power when innovation or diffusion

contexts create uncertainty about environmental influ-ences, organizational goals, or technical efficiency.To the contrary,Proposition 17: Perspectives that assume that imitationprocesses do not impel the diffusion of innovations willhave highest explanatory power when innovation or dif-fusion contexts do not create uncertainty about environ-mental influences, organizational goals, or technical ef-ficiency.

Organizational theorists assert that whereas administrative technolo-gies produce unclear outputs, production technologies do not. As a result,organizations experience high uncertainty about the technical efficiency ofthe former and low uncertainty about the latter (Meyer & Rowan, 1977).Others assert that greater uncertainty over organizational goals exists innot-for-profit, as opposed to for-profit diffusion contexts, because economicgoals do not dominate in the former (Rogers, 1962, 1983). Therefore, accord-ing to Proposition 16, fad and fashion perspectives should have the greatestpower when explaining the diffusion of administrative technologies in not-for-profit sectors. According to Proposition 17, the other two perspectiveswould have the greatest power in explaining the diffusion and rejection ofproduction technologies in for-profit sectors.This attempt to specify when each type of perspective will have greaterexplanatory power is only useful in situations where innovations or contextsfall neatly into either of these high or low uncertainty types. These situationsmay occur infrequently, however. Moderate uncertainty, for instance, prob-ably characterizes judgments concerning the technical efficiency of manyadministrative and production technologies, strategic moves, and entrepre-neurial ventures (Nystrom & Starbuck, 1984). Organizations may also expe-rience varying levels of uncertainty or changes in uncertainty during the


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1991 Abrahamson 605

diffusion of innovations. Understanding how innovations diffuse in thesecontexts requires resolving paradoxes between different perspectives thatassume conditions characterized by either high or low uncertainty.Extant research on the diffusion of administrative technologies providessome clues concerning how to resolve paradoxes between theories on theimitation-focus dimension. Studies have replicated an interesting finding;after administrative technologies have partially diffused, efficient-choice ex-planations no longer explained adoptions. Rumelt (1974: 77) tested Chan-dler's (1962) claim that multidivisional structures solved the administrativeproblems caused by diversification strategies. Rumelt (1974) found diversi-fication correlated with the adoption of a multidivisional structure between1949 and the early 1960s, but not after. Likewise, Tolbert and Zucker (1984)found that city size and percentage of foreign-born population correlatedwith city government's adoptions of civil service reform between 1885 and1914, but not between 1914 and 1935 (cf. Baron, Dobbin, & Jennings, 1986;Meyer, Stevenson, & Webster, 1985).As these studies suggest, after administrative technologies have par-tially diffused, efficient-choice explanations no longer explain adoptions.Therefore, fad and fashion perspectives could explain the diffusion of tech-nically inefficient technologies in these later stages. This reasoning suggestsa temporal resolution of paradoxes on the imitation dimension, such that

Proposition 18: Rational choices may trigger technicallyefficient adoptions in the early stages of diffusion,whereas faddish pressures or fashion-setting networksmay drive technically inefficient adoption in later stagesof the diffusion of innovations.Additionally,Proposition 19: Rational choices may trigger technicallyefficient rejections in the early stages of diffusion,whereas faddish pressures or fashion-setting networksmay drive technically inefficient rejection in later stages

of the diffusion of innovations.There are at least two other complementary resolutions of paradoxes onthe imitation-focus dimension. The first depends on clarifying levels of anal-ysis. Efficient-choice perspectives focus on the organizational level of anal-ysis to explain the diffusion of innovations. They assume that indepen-dently, numerous individual organizations choose to select the most tech-nically efficient innovations, and these innovations are diffused. Fadtheories focus on the group level of analysis. They explain how adoptions ina group of organizations create endogenous pressures that impel the diffu-sion of innovations across other organizations in that group. Jointly, effi-cient-choice and fad theories may explain how a multitude of unrelatedadoption decisions in the early stages of diffusion could trigger group pres-sures impelling later stages of diffusion. This resolution, therefore, wouldprovide a bridge that spans levels of analysis between literatures that have


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1991 Abrahamson 607

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tive, also assumes high uncertainty among organizations in a group. Unlikethe fad perspective, however, the fashion perspective recognizes influenceson organizations in a group exerted by organizations outside the group. Itclaims that outside fashion setters either lead the diffusion of inefficientinnovations or the rejection of efficient innovations when they introducesubstitute innovations. The third, the forced-selection perspective, assumesboth low uncertainty and outside influences by organizations. It suggeststhat it may be in the interest of powerful outside organizations, such asgovernmental regulators or labor unions, to coerce organizations inside agroup either to adopt technically inefficient innovations or to reject efficientones.The four types of explanations developed in the article might explainthe diffusion and rejection of innovations among groups of organizationsthat match closely the assumptions underlying these explanations. How-ever, groups of organizations may have characteristics that do not matchthese assumptions. For instance, uncertainty about goals and efficiencymay be moderate in a group, may vary across organizations within it, ormay change across different stages of diffusion in that group. Likewise,organizations outside a group may exert only moderate influence over dif-fusion in that group, high influence over only certain organizations within it,or changing influences during different stages of the diffusion. Under theseconditions, the efficient-choice, forced-selection, fad, or fashion perspec-tives will not be able to explain the diffusion of inefficient innovations or thewidespread rejections of efficient ones. This article indicates how research-ers can develop new theories that explain these phenomena by exploitingparadoxes among the four perspectives.

Overcoming proinnovation biases and assumptions in the innovation-diffusion literature would make it easier for organizational theorists to de-velop theories with which they could study the diffusion of technically inef-ficient innovations and the rejection of technically efficient ones. In trying toovercome proinnovation biases, however, researchers could generate anti-innovation biases. Therefore, theorists must understand how diffusion pro-cesses, such as those described in fad or fashion perspectives, while theycould harm organizations' economic performances, could also benefitcountless organizations.Fads and fashions may benefit organizations if they are symbolicallyefficient; if, for example, they project an image of innovativeness (Nystrom& Starbuck, 1984). Although these expressive functions have intrinsic value,they may also be economically beneficial. An innovation that makes anorganization appear innovative or ethical, for instance, may help it either toraise capital from other organizations or to attract customers. However,even if fads and fashions have few symbolic or political efficiencies, orga-nizational theorists still cannot conclude that fads and fashions necessarilyharm organizations. Even if quality circles did not enhance the performanceof a single U.S. organization, they may have refocused attention on thenotion of quality and worker participation. Likewise, strategic planningunits, even if they did not help organizations directly, may have focused


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1991 Abrahamson 609

attention on strategic planning (Porter, 1987). Administrative fads and fash-ions may, therefore, play vital functions in drawing the attention of manyorganizations to problems and solutions that have long remained over-looked.Finally, the popular press has been most strident in denouncing howfads and fashions prompt the diffusion and rejection of innovations, regard-less of their technical efficiencies (Business Week, 1986). Itdoes not consider,however, that organizations may have no choice but to adopt and rejectmany technically inefficient innovations while searching for a few efficientones. The cost of adopting and rejecting multiple fads or fashions in order tofind a technically efficient innovation may be much lower than the returnsfrom using this innovation. From this perspective, fads and fashions mayconstitute vital processes that animate random variations from which in-creasingly efficient innovations can evolve (Anderson & Tushman, 1991;Hannan & Freeman, 1977).

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Review, 42: 726-743.Eric Abrahamson received his Ph.D. from the Stern School of Business, New YorkUniversity. He is an assistant professor in the Graduate School of Business, ColumbiaUniversity. His current research interests include innovation diffusion, as well as in-dustry and interindustry cultures.

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