contingency fit, institutional fit, and firm performance ... · approach to ﬁt may produce...

OrganizationScienceVol. 23, No. 4, July–August 2012, pp. 1040–1054ISSN 1047-7039 (print) � ISSN 1526-5455 (online) http://dx.doi.org/10.1287/orsc.1110.0687

© 2012 INFORMS

Contingency Fit, Institutional Fit, andFirm Performance: A Metafit Approach toOrganization–Environment Relationships

Henk W. VolberdaDepartment of Strategic Management and Entrepreneurship, Rotterdam School of Management, Erasmus University,

and INSCOPE: Research for Innovation, 3000 DR Rotterdam, The Netherlands, [email protected]

Niels van der WeerdtDepartment of Strategic Management and Entrepreneurship, Rotterdam School of Management, Erasmus University,

3000 DR Rotterdam, The Netherlands, [email protected]

Ernst VerwaalQueen’s University Management School, Queen’s University Belfast, BT7 1NN Belfast,

United Kingdom, [email protected]

Marten StienstraDepartment of Strategic Management and Entrepreneurship, Rotterdam School of Management, Erasmus University,

3000 DR Rotterdam, The Netherlands, [email protected]

Antonio J. VerduFinance and Economics Department, Miguel Hernandez University, 03202 Elche, Spain, [email protected]

In this paper, we attempt to reconcile contingency and institutional fit approaches concerning the organization–environmentrelationship. Whereas prior scholarly research has examined both theories and compared their impacts on organizational

fit and performance, we lay the groundwork for a metafit approach by investigating how contingency and institutionalfit interact to influence firm performance. We test our theoretical framework using a data set of 3,259 respondents from1,904 companies, examining task environmental demands and institutional demands on organizational design across a broadrange of industries and firm size classes. Our results show that contingency and institutional fit provide complementary andinterdependent explanations of firm performance. Importantly, our findings indicate that for firms under conditions of “quasifit” rather than perfect contingency fit or optimal institutional fit, improvements in contingency and/or institutional fit willresult in better performance. However, firms with high contingency fit are less vulnerable to deviation from institutional fitin the formation of firm performance, whereas firms with perfect institutional fit will slightly decrease their performancewhen they strive to achieve contingency fit.

Key words : contingency fit; institutional fit; metafit; quasi fit; organization design; task environment; environmentalturbulence; organizational effectiveness; institutional environment; external legitimacy; organizational field; firmperformance

History : Published online in Articles in Advance September 28, 2011.

IntroductionWhat criteria do successful firms use with regard toappropriate strategies and their organizational design?Do they strive to continuously adjust specific organiza-tion variables to specific elements in the task environ-ment, or do they conform to the institutional pressuresof the business environment? Scholarly research streamsin the strategic management literature have acknowl-edged that the fit of the organization with environmen-tal demands is an important precursor of high firmperformance (cf. Burton and Obel 2004, Burton et al.2008). According to contingency theory, high perfor-mance results from a fit between the organization and itsenvironmental contingencies (Donaldson 2001, Drazin

and Van de Ven 1985, Venkatraman 1989). Institutionaltheory is also primarily concerned with the organiza-tion’s relationship with the environment, but explainsfirm performance as a consequence of legitimacy andsupport that come externally (DiMaggio and Powell1983, Scott 2001, Zucker 1987), leading to the notion ofinstitutional fit (Kondra and Hinings 1998), or congru-ence of the organization’s characteristics with the insti-tutional template (Greenwood and Hinings 1996). Theimplications of these two fit approaches may lead to bothcomplementary and conflicting prescriptions for orga-nizational design (Donaldson 2008b). Integrating theseperspectives is therefore important for theory and prac-tice because neither perspective can, on its own, explain

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Volberda et al.: Contingency Fit, Institutional Fit, and Firm PerformanceOrganization Science 23(4), pp. 1040–1054, © 2012 INFORMS 1041

the success of firm behavior and the firm’s relationshipwith the environment.

According to contingency theory, managers carefullyanalyze the firm’s task environment, taking into accountthe internal characteristics of the firm, and adapt theirpractices accordingly. On the other hand, according toinstitutional theory, the environment exerts strong pres-sures for institutional fit or adoption of “conformance-enhancing templates” (Heugens and Lander 2009, p. 64).Previous scholarly research (Carroll 1993, Child et al.2003, Greening and Gray 1994, Gupta et al. 1994,Kraatz and Zajac 1996) has examined both theories andcompared their impacts on organizational change andperformance. However, these studies did not investigatewhat impact conceptual and empirical linkages betweenthe two approaches may have on firm performance. Ifsuch linkages exist and are substantial, a single-lensapproach to fit may produce incomplete theoretical pre-dictions and conclusions. In this study, we address thisunderdeveloped area of research by explicitly focusingon how contingency fit and institutional fit interact toinfluence firm performance.

Contingency theories include a variety of approachesthat focus on either the effectiveness of fit across a vari-ety of firms or the adaptation processes by which indi-vidual firms achieve fit with their task environments. Thefirst approach requires a comparison across firms thatdiffer in organizational and task environmental variables,whereas the latter requires a longitudinal study of orga-nizational adaptation processes. In this paper, we focuson the first approach; i.e., the performance implicationsof contingency fit across a variety of firms (Drazin andVan de Ven 1985, Venkatraman 1989). To investigatethe simultaneous impact of contingency fit and insti-tutional fit, we study the performance implications ofinstitutional fit across the same set of firms. Althoughinstitutional theory is used primarily to describe orga-nizational processes, this paper responds to institutionaltheorists who have mentioned the possibility of apply-ing a cross-sectional research design (see DiMaggio andPowell 1983). Furthermore, to define the notion of fitexplicitly with respect to a specific outcome over a spe-cific time period (Donaldson 2001), we studied fit inrelation to short-term organizational performance.

The rest of this paper proceeds as follows. First, wedefine the notion of fit and specify and test hypothesesregarding various notions of fit. We formulate hypothe-ses with respect to a contingency-fit-based model, whichcaptures factors related to specific requirements of thetask environment, and to an institutional-fit-based model,which captures pressures for conformity to the institu-tional environment. Furthermore, we develop hypotheseson the combined effects of these models. Since we areinterested in the short-term performance implications offit, to test our hypotheses we use a large-scale cross-sectional sample of firms across a wide range of indus-tries and firm size classes. Next, we present the results,

finding that contingency and institutional fit are com-plementary and interrelated explanations of firm perfor-mance, and show that the combination of both theoriesproduces superior insights into the relationship betweenfit and firm performance. In the final section, we discussthe implications of these findings for management andscholarly work.

Theory and HypothesesThe Notion of FitThe concept of fit has been explored widely in organi-zation and strategy literatures and covers much of thedescriptive and prescriptive research in this arena. Fit isa polyvalent concept, rooted in contingency theory andpopulation ecology (Van de Ven 1979), and subsequentlydeveloped in the fields of organization theory (Drazinand Van de Ven 1985, Van de Ven and Drazin 1985) andstrategic management (Venkatraman 1989). The con-cept of fit has been used by both organization theoristsand strategic management scholars as a key predictorof firm performance. Although fit originated in contin-gency theory, institutional theorists have also taken upthe concept (e.g., Kondra and Hinings 1998). Further-more, Donaldson (2008b) demonstrated that knowledgeof how organizations attain external legitimacy and sup-port leads to valuable prescriptions for organizationaldesign that often conflict with contingency theory. Build-ing on Donaldson’s (2008b) notion that organizationsneed to maximize both internal organizational effective-ness and external legitimacy support, our study analyzesfit implications for performance across both contingencytheory and institutional theory.

The notion of fit has been extensively defined in theliterature (Van de Ven and Drazin 1985, Venkatraman1989, Parker and Witteloostuijn 2010). In general, thereare two main operational definitions of fit in the litera-ture: interaction and congruence (Pennings 1987). How-ever, as suggested by Donaldson (2001, pp. 189–191), amultiplicative interaction fails to capture the relationshipbetween contingency fit and performance. Therefore, inthis study we use the concept of fit as congruence, whichholds that high performance occurs when organizationalresponse variables match environmental variables. Morespecifically, we link three organizational design variables(technology, structure, and culture) with both task envi-ronmental demands (i.e., contingency fit) and institu-tional demands (i.e., institutional fit) to investigate howboth types of fit separately and jointly explain organiza-tional performance.

Contingency Theory, Contingency Fit, andFirm PerformanceContingency theory is a midrange theory that involvesidentifying and matching context settings with organi-zational settings (Hambrick 1983). Since the 1960s, a

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Volberda et al.: Contingency Fit, Institutional Fit, and Firm Performance1042 Organization Science 23(4), pp. 1040–1054, © 2012 INFORMS

considerable volume of research has been conductedusing contingency theory as the principal framework,relating the task environment to organizational char-acteristics (Burns and Stalker 1961, Emery and Trist1965, Lawrence and Lorsch 1967, Woodward 1965) orto strategic management (Hambrick 1983, Hofer 1975,Porter 1980).

Contingency theory suggests that the appropriate orga-nizational structure and management style depend on aset of “contingency” factors (Tosi and Slocum 1984).According to contingency theory, there is no bestway of organizing; the appropriate form depends onthe nature of the firm’s task environment (Donaldson2001). Task environmental conditions are considered adirect source of variation in organizational forms. Someauthors suggest appropriate forms based on the speedof environmental change (Burns and Stalker 1961),rate of technological innovation (Woodward 1965), orlevel of uncertainty (Lawrence and Lorsch 1967). Neo-contingency theorists (Hrebiniak and Joyce 1985, Zajacet al. 2000) add a dynamic perspective of fit, in whichadaptation is a dynamic process that is both manage-rially and environmentally inspired. Donaldson (2001)proposes the notion of quasi fit as a key to high perfor-mance, because the permanent disequilibrium triggers aconstant search for strategic and structural change.

Contingency fit was examined in research by Rothand Morrison (1992) on environment–strategy coalign-ment and more recently in research by Hitt et al.(2001) on resource strategy. Priem (1994) explainedhigh performance as being a consequence of strategy–structure–environment matches that were based onexecutive judgments. Burton et al. (2002, 2003) usedcontingency fit to describe the internal consistencyof multiple contingencies (e.g., size, climate, strategy,environment, leadership preferences) and multiple struc-tural characteristics. Zajac et al. (2000) used contin-gency theory in a multicontingent environment–strategyfit defined as strategic fit. Others supported the fithypothesis using the alignment of a few variables suchas organization structure and dimensions of knowledge(Birkinshaw et al. 2002). Venkatraman and Prescott(1990) referred to contingency fit when a few charac-teristics of contextual variables are coaligned with thoseof other organizational variables (e.g., technology, struc-ture, culture, strategy).

According to Zeithaml et al. (1988) and Tosi andSlocum (1984), contingency theory building involvesthree types of variables (contingency, response, andeffectiveness variables) and congruency or a notion offit. Contingency variables relate to environmental con-text, and response variables to organizational structureor managerial actions. Effectiveness can be consideredas performance in a narrow sense (Lawrence and Lorsch1967). The essential premise of contingency theory isthat effectiveness (high performance) can be achieved in

more than one way. High performance is a consequenceof coalignment between a limited number of organiza-tional and environmental factors (Donaldson 1987, Tosiand Slocum 1984).

The fit line is central to the notion of fit as congruence,and misfit is defined as deviation from that fit line. Thefit line is considered to be a line of isoperformance (Vande Ven and Drazin 1985), meaning that for each value ofthe contingency variables, there is a value for the orga-nizational variables that constitutes fit and produces thehighest performance for that value of the contingency.All fits are equally good and better than misfits. Theidentification of a misfit involves a two-step procedure.The first step involves approximating the optimal fit linebetween a contingency and a response variable. In thesecond step, deviation from the optimal fit line is calcu-lated to represent misfit, using the following equation:

A=X − 4c ∗Z51

where A is the contingency misfit, X is the organiza-tional response variable, c is the optimal fit line coef-ficient, and Z is the contingency variable. In case ofmultiple contingencies, the separate misfits can be com-bined in an additive model to arrive at a multiple con-tingencies fit (Donaldson 2001, p. 197–198).

According to the congruence definition of contingencyfit, the impact of organizational response variables onfirm performance depends on environmental characteris-tics according to the following equation:

Y = f 4X1−31Z1 abs4X1−3 −XZ551

where Y is performance, X1−3 are organizationalresponse variables (technology, structure, culture), Z isenvironmental turbulence, and XZ is the optimal valueof X1−3 as determined by the fit line at point Z.

Following Volberda (1996, 1998), we use the degreeof environmental turbulence to represent the contingencyvariable. Environmental turbulence is operationalized asthe product of the level of dynamism within the mar-ket environment and the degree to which changes areunpredictable (see Duncan 1972, Volberda 1998). Thisdefinition captures most of the dimensions attributedin definitions of constructs analogous to environmentalturbulence, including hypercompetition (e.g., D’Aveni1994), market dynamism (Davis et al. 2009), and indus-try clockspeed (Fines 1998, Nadkarni and Narayanan2007). Technology, structure, and culture represent theresponse variables. These variables have been used tradi-tionally in contingency research (e.g., Venkatraman andPrescott 1990, Birkenshaw et al. 2002). In line withVolberda (1996, 1998), higher degrees of environmentalturbulence would require higher levels of organizationaltechnological, structural, and cultural responsiveness.

When we apply the contingency fit equation to ourselection of organizational response variables, deviation

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from the optimal fit line will negatively affect firm per-formance (Donaldson 2001). We thus hypothesize thefollowing.

Hypothesis 1. The contingency fit of the firm’s tech-nology, structure, and culture with the level of environ-mental turbulence of its task environment is positivelyassociated with firm performance.

Institutional Theory, Institutional Fit, andFirm PerformanceInstitutional theory examines the influence of the insti-tutional context on organizational behavior (e.g., Scott2001, Tolbert and Zucker 1996, Wicks 2001) and ques-tions why there is so much homogeneity of organiza-tional forms and practices in an organizational field.DiMaggio and Powell (1983) describe three isomorphicprocesses—coercive, mimetic, and normative—leadingorganizations in an organizational field to becomeincreasingly similar. Coercive isomorphism results frompolitical influence and from pressures exerted on organi-zations by other organizations upon which they dependfor resources. Mimetic isomorphism derives from uncer-tainty and ambiguity about goals. Normative isomor-phism derives from professionalization. The three typesof isomorphism may reinforce each other, and firms canexperience pressures from all three types simultaneously.

Institutional theory suggests that many aspects oforganizations are driven by the desire to achieve fit withthe institutional environment. Institutional fit has beendefined as “the degree of compliance by an organi-zation with the organizational form of structures, rou-tines, and systems prescribed by institutional norms”(Kondra and Hinings 1998, p. 750). The criterion vari-able that explains performance is legitimacy (of socialcontext), which ensures public support (DiMaggio andPowell 1983, Meyer and Rowan 1977, Zucker 1977).The effects of isomorphic conformity on substantive per-formance are subject to debate (cf. Heugens and Lan-der 2009). On the one hand, conformity may conflictwith efficiency criteria (e.g., Meyer and Rowan 1977),especially if the required resources for seeking confor-mity have a higher investment value elsewhere (Barretoand Baden-Fuller 2006), provoke tensions with inter-nal routines, or decrease a firm’s potential to differenti-ate itself from competitors (Heugens and Lander 2009).On the other hand, institutional fit increases organiza-tional legitimacy, which in turn increases performancethrough different reinforcing mechanisms such as col-lective learning (Levitt and March 1988) and accessto resources (D’Aunno et al. 1991). Collective learningoccurs as patterns of cognitive associations and causalbeliefs are institutionalized into routines, which are dif-fused by coercive, mimetic, and normative processes(DiMaggio and Powell 1983, Levitt and March 1988).Adoption of institutionalized routines increases organi-zational performance by making it more efficient to learn

from others than to learn on an individual basis. Inso-far as institutional conformity enhances the legitimacyand power of organizations (Meyer and Rowan 1977,Tolbert and Zucker 1983), it can increase their abilityto attract resources of higher quality from their environ-ment (e.g., Baum and Oliver 1991, D’Aunno et al. 1991,Deephouse 1999).

From the imperative of institutional fit, organizationstend to follow the behavior of firms that are perceived“more legitimate or successful” (DiMaggio and Powell1983). We focus on outcome-based imitation, definedas the imitation of organizational design characteristicsthat produced positive outcomes by other firms in anorganizational field (see Haunschild and Miner 1997).Not adopting the organizational design characteristicscould signal “illegitimacy” to stakeholders. High per-formers are assumed to cope effectively with the insti-tutional requirements of the environment. Other firmstend to model themselves on the high performers intheir organizational fields, resulting in a high fit withthe institutional environment. Despite the potential neg-ative performance effects of institutional conformity,Heugens and Lander (2009) found a positive relation-ship between conformity, i.e., institutional fit, and sub-stantive (accounting-based) performance when applyinga meta-analytical technique. In a study of Japanese enter-prise groups, Orru et al. (1991, p. 376) argued, “It isnot despite their institutional isomorphism that Japaneseenterprise groups are economically fit, but because ofthe incorporation of institutional elements in their orga-nizations that they are so successful.”

Following the conformity notion of institutional fit,the impact of a firm’s organizational design variableson firm performance depends on their similarity to theorganizational design variables of high performers inan organizational field, as measured by the followingequation:

Y =f 4abs4X1h−X15+abs4X2h

−X25+abs4X3h−X3551

where Y is performance, X1 is organizational technology,X1h is the institutional norm for organization technologyin an organizational field, X2 is organizational structure,X2h is the institutional norm for organization structure inan organizational field, X3 is organizational culture, andX3h is the institutional norm for organization culture inan organizational field.

Assessing institutional fit requires the determinationof the organizational design profile of high-performingfirms (in terms of technology, structure, and culture)because those firms are assumed to have reached fit withthe institutional context (Kondra and Hinings 1998).Institutional misfit, determined as the sum of the abso-lute deviations of these variables from the values asevident for high-performing firms, will have negativeeffects on firm performance.

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Hypothesis 2. The institutional fit of the firm’s tech-nology, structure, and culture with those of high-performing firms in its organizational field is positivelyassociated with firm performance.

Complementary Linkages Between Contingency Fitand Institutional FitAlthough contingency theory and institutional theory usedifferent conceptualizations of fit, both perspectives areopen systems theories (Ashby 1956, Scott 2003, VonBertalanffy 1951). In open systems theory, the basicprinciple that explains performance is synergy derivedfrom the sum of interconnected elements (Siggelkow2001). Synergy in contingency theory refers to the inter-connection of the organization with specific environmen-tal demands, whereas synergy in institutional fit refersto the interconnection of the organization with the uni-form institutional demands of the industry environment.Contingency and institutional fit approaches are bothcoalignment approaches that focus on different types ofsynergy between the organization and its environment.Therefore, a combination of these approaches might bet-ter explain firm performance than either approach inisolation.

There have been several discussions in the literature ofthe complementarities of contingency and institutionaltheory. Gupta et al. (1994), drawing on both contin-gency and institutional theory, demonstrated that the twoperspectives can be combined to study the effect ofinstitutional forces on work unit performance. From asociological view, Carroll (1993) used the adaptation-selection perspective to explain firms’ successes andsuggested complementarities between contingency andinstitutional theories for the understanding of the homo-geneity or heterogeneity of firms in different industries.Other studies have combined both theories to explainthe organizational change and performance in transi-tion economies, considering the institutional constraintsfrom the firms’ former political systems. Child et al.(2003) analyzed a large sample of firms in Hong Kongwho were managing operations in China. They usedalternative perspectives (e.g., natural selection, strategicadaptation, and contingency) to explain business per-formance and reported empirical evidence that each ofthe following factors significantly influence firm perfor-mance: business and institutional environment, strategicmanagerial action, and the fit between firm organizationand environmental contingencies. They also discussedthe complementarities of the perspectives: “Althoughthe business and institutional environments do have asignificant influence on the performance of the cross-border affiliates in a transition economy, performancecan be improved through strategic managerial action”(Child et al. 2003, p. 253). Finally, Clark and Soulsby(1995) argued that contingency and institutional theo-ries complement each other to improve understanding of

organizational change among former enterprises in theCzech Republic. They argued that new managerial con-duct coexists with the inertia of old practices that limitorganizational change.

These contributions support the notion that both fitapproaches are complementary. Therefore, we posit thattaking into account both the synergies of the organi-zation with specific task environmental demands andits synergies with uniform institutional demands of theorganizational field should better explain firm perfor-mance than taking either approach in isolation. Thisgives rise to our third hypothesis.

Hypothesis 3. The simultaneous coalignment of thefirm’s technology, structure, and culture with its specifictask environment and uniform institutional demands ofits organizational field is positively associated with firmperformance.

Interdependence Between Contingency Fit andInstitutional FitContingency and institutional approaches refer to dif-ferent types of synergy of the organization with theenvironment. From an institutional perspective, isomor-phic processes at industry level lead to the adoptionof a “conformance-enhancing template” (Heugens andLander 2009, p. 64). The theory treats organizationsas sets of interdependent members with common pat-terns of cognition and beliefs (Argyris and Schon 1978,DiMaggio 1991, Weick 1979). Contingency theory, how-ever, refers to the specific task environment and treatsorganizations as goal-oriented activity systems that learnto coalign with the demands of a specific environmentby repeating successful behaviors and discarding unsuc-cessful ones (Cyert and March 1963, Levinthal 1991,March 1981). The two approaches assume differentrequirements for fit that are complementary to someextent but also may place paradoxical demands on theorganization (Donaldson 2008b). Indications of a poten-tial trade-off between contingency and institutional fitare reported by Lee and Miller (1996), who found thatboth contingency prescriptions and conformity to insti-tutional pressures could explain high firm performancein the same industry. Firms using traditional technolo-gies could benefit from government interventions, andthose firms that employ emergent technologies couldbenefit from heeding contingency prescriptions. Theconclusions suggest that firms can substitute or trade-offdifferent strategies (internal organizational effectivenessversus external legitimacy and support) to achieve suc-cess. However, this does not imply that the impact ofthese strategies is fully independent.

In a review of the literature, we find some evidenceto suggest that contingency fit and institutional fit areinterdependent. Greening and Gray (1994) analyzed thevariability of organizational structures in responding to

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the environment by comparing institutional theory andresource dependence theory. The authors proposed a con-tingency model that integrates the institutional pressureson firm structures with the managerial discretion withinthe constraints of other organizations that control criti-cal resources for them. Other studies advocate some con-tingency properties in institutional theory. Boiral (2003),analyzing the ISO 9000 standard implementation, discov-ered that institutional pressures that cause organizationsto become isomorphic as they adopt identical models arereinterpreted and modified within organizations, based onmanagers’ personal opinions and attitudes. Washingtonand Ventresca (2004) found that the institutional envi-ronment can actually support changes in organizationalstrategy and does not merely constrain or pressurize orga-nizations to conform as understood inside the “iron cage”(DiMaggio and Powell 1983). The authors present analternative view of institutional isomorphism in whichinstitutional process mechanisms can facilitate organiza-tional change. These contributions, which demonstratethe interrelationship between contingency fit and institu-tional fit, support the notion that it is beneficial to studyinterdependencies between both fit approaches in orderto explain firm performance.

Deviation from a socially accepted common set ofevaluation routines may be accepted if organizationalpractices produce positive outcomes (Haunschild andMiner 1997). Practices or organizational structures thatdeviate from institutional norms but produce positiveorganizational outcomes are more likely to be acceptedand receive external support (Griliches 1957). Underuncertain conditions, institutional norms may be usedpartly as a substitute for information or for the capa-bility to recognize effective organizational practices. Forexternal parties, institutional norms such as ISO normsare the “second-best” indicators of organizational effec-tiveness. However, their value may be considerably lesswhen other evidence of organizational effectiveness isavailable. For example, a bank or shareholders may beinclined to provide capital to a company that conformsto industry norms and routines. Given the imperfec-tions of capital markets, this is an important sourceof information on the reliability and professionalism oforganizational practices. However, a company that hasdemonstrated high organizational effectiveness may alsobe recognized as acceptable and receive external sup-port from shareholders and banks, even if the companydeviates substantially from industry norms and practices.The value of the second-best information provided byinstitutional conformism is reduced when the firm hasproven its effectiveness through high performance. Thus,the relevance of the impact of institutional requirementson firm performance may be reduced substantially underhigh levels of contingency fit.

Hypothesis 4. Contingency fit moderates the relationbetween institutional fit and firm performance such that

there will be a weaker, negative relationship betweeninstitutional misfit and firm performance when contin-gency fit is high.

Data and MethodSampleFit research encompasses both the relationship betweenfit and performance and the adaptation process towardorganizational fit. In our research, we focus on the per-formance implications of fit. Therefore, we need a largecross-sectional sample with substantial variation in orga-nizational and environmental variables. We use a uniquelarge-scale cross-sectional sample of firms across a widerange of industries and firm size classes to test ourhypotheses. The sample contains survey and archivaldata on 3,259 responses from a panel of 1,904 organiza-tions across 13 different industries. The distribution offirms across industries and firm size classes is presentedin Table 1. All firms are active in the Netherlands andhave at least 10 employees. Survey data for the databasewere collected mainly around the year 2002 using astructured questionnaire. All respondents held manage-ment positions in these firms. For 149 organizations, wehave multi-informant data (ranging from 2 to 95 respon-dents per firm), which allowed us to examine interraterreliability and interrater agreement. Using this subset,we calculated an interrater agreement score, rwg , for eachstudy variable (James et al. 1993). The median interrateragreement ranged from 0.68 to 0.80, which exceeds thelevel of 0.60 required to justify the use of an aggregatedperceptual measure (Glick 1985). In addition, examina-tion of within-group reliability coefficients revealed astrong level of interrater reliability (Jones et al. 1983),with � values ranging from 0.75 to 0.93.

Survey measures are more appropriate for explainingmanagerial behavior than archival measures (Bourgeois1980). However, a disadvantage of survey informationis that the source (the respondent) explains variancebetween variables, which may partly explain the study’sresults. To examine whether such common method biasmay augment relationships, we first performed Har-man’s one-factor test on the self-reported items of thelatent constructs included in our study. The hypothesisof one general factor underlying the relationships wasrejected (p < 0001). In addition, we found multiple fac-tors, and the first factor did not account for the majorityof the variance. However, this test has several limitations(Podsakoff et al. 2003), so we conducted three additionaltests. First, we found a model fit of the measurementmodel greater than 0.90, which suggests no problemswith common method bias (Bagozzi et al. 1991). Sec-ond, the smallest observed correlation among the modelvariables can function as a proxy for common methodbias (Lindell and Brandt 2000). The smallest correla-tion between the model variables is 0.06, which does

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Table 1 Industry and Firm Size Distribution ofSample

Industry Percentage

Agriculture, forestry, fishing, 3and hunting

Mining 5Manufacturing 17Utilities 3Construction 6Accommodation and food services 1Transportation, retail, and 11

warehousingFinancial services 10Professional services and leasing 28Government and social security 6Education 3Health care and social assistance 5Arts, entertainment, recreation, 2

and other services

Number of employees

10–20 721–50 1351–250 34251–1,000 18>11000 28

Total n = 31259

not suggest the presence of common method bias. Third,we performed a partial correlation method (Podsakoffand Organ 1986), adding the highest factor between anunrelated set of items and each predictor variable tothe model. These factors did not produce a significantchange in variance explained, again suggesting no sub-stantial common method bias. In sum, we conclude thatthe evidence from a variety of methods supports theassumption that common method bias does not accountfor the study’s results.

Construct MeasurementWe generated an initial list of Likert-type items based onthe definitions of the constructs and on our review of theliterature relating to these dimensions. Exploratory inter-views with management consultants and audits withinvarious firms then served as a basis for item gener-ation and content validity assessment. For technologyof the firm, i.e., the hardware (such as machines andequipment) and software (knowledge) used in transform-ing inputs into outputs (Volberda 1996), we used itemsadapted from the work of Hill (1983), Perrow (1967),and Hickson et al. (1969). For organizational struc-ture, comprising the actual distribution of responsibil-ities and authority among the organization’s personneland the process regulations of decision making, coor-dination, and execution, indicators were adapted fromBurns and Stalker (1961), Pugh et al. (1963), Lawrenceand Lorsch (1967), Mintzberg (1979), and Hrebiniak andJoyce (1985). Items related to organizational culture,

defined as the set of beliefs and assumptions held rela-tively commonly throughout the organization and takenfor granted by its members (Bate 1984), were basedon the work of Ouchi (1979), Camerer and Vepsalainen(1988), and Hofstede et al. (1990). Items reflecting theconstruct of environmental turbulence, i.e., the prod-uct of unpredictability and dynamism in the environ-ment, were adapted from Dill (1958), Duncan (1972),Lawrence and Lorsch (1967), and Thompson (1967).

Archival data on firm performance were available fora number of firms. Because survey measures of perfor-mance correlate quite highly with archival measures inorganizations (Dess and Robinson 1984), we measuredfirm performance using a scale with three survey itemsadopted from Jaworski and Kohli (1993). We comparedthe survey data of our performance scale with the avail-able accounting performance data and calculated inter-coder agreement and intercoder reliability scores. Thesurvey measure appears to correlate highly with returnon assets (Pearson correlation of 0069; p < 0001). Boththe interrater agreement score (James et al. 1993) andthe interrater reliability score (Jones et al. 1983) for thisscale are adequate, with a median rwg = 0076 and anaverage within-group � coefficient of 0.95.

Control VariablesIn our model, we include control variables for firm sizeand industry effects. Researchers have identified organi-zational size as a critical variable moderating the rela-tionship between strategy and performance (Dobrev andCarroll 2003, Hofer 1975, Smith et al. 1989). Firm sizeis measured by the number of organizational membersto be organized (Blau 1970) as reported in the firm’sfinancial reports. Furthermore, because the impact ofparticular production technologies may vary substan-tially between types of industries, we control for indus-try effects by including dummy variables for industrialfirms, trade firms, service firms, nonprofit organizations,and a miscellaneous category.

Item SelectionWe first investigated the psychometric properties of thescales using exploratory factor analysis on a subset offirms. We analyzed each dimension of the scales usingprincipal component procedures and varimax rotationto assess their unidimensionality and factor structure.Only items that satisfied the following criteria wereincluded: (1) items should have communality higherthan 0.3, (2) dominant loadings should be greater than0.5, (3) cross-loadings should be lower than 0.3, and(4) the scree plot criterion should be satisfied (Briggsand Cheek 1988).

We assessed the reliabilities of the scales by meansof the Cronbach � coefficient and the construct reliabil-ity. Reliability scores vary between 0.67 and 0.84 (seeTable 2), which exceeds the commonly used threshold

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Table 2 Items and Constructs

Factor Item correlationConstructs loadings with total score

Nonroutine technology (�= 0067, composite reliability = 0080, AVE = 0050)The layout and setup of our primary process can be changed easily. 0.63 0.67Our equipment and information systems can be used for multiple purposes. 0.77 0.76Our employees master several methods of production and operations. 0.81 0.78Our organization is up to date regarding “know-how.” 0.61 0.61

Organic structure (�= 0075, composite reliability = 0084, AVE = 00585R Our organization uses extensive and structured systems for planning and control. 0.72 0.72R In our organization, the division of work is defined in detailed descriptions of jobs and tasks. 0.83 0.81R In our organization, everything has been laid down in rules. 0.85 0.83R In our organization, there are a lot of consultation bodies. 0.63 0.67

Innovative culture (�= 0070, composite reliability = 0082, AVE = 0054)R For our organization, the following applies: “The rules of our organization can’t be broken,

even if someone believes that it is in the company’s best interest.”0.68 0.72

R Deviating opinions are not tolerated in our organization. 0.84 0.81Creativity is highly appreciated in our organization. 0.65 0.68

R The person that introduces a less successful idea in our company can forget about his or hercareer.

0.76 0.72

Market dynamism (�= 0084, composite reliability = 0088, AVE = 0056)Changes in our market are very intense. 0.73 0.72In our market, customers frequently demand completely new products and/or services. 0.74 0.73In the market we operate in, changes happen continuously. 0.81 0.80Our offering of products/services to our customers changes constantly. 0.75 0.74In our market, the amount of products and/or services to be supplied changes often and quickly. 0.73 0.74In the market we operate in, each day something changes. 0.71 0.73

Unpredictability of changes (�= 0075, composite reliability = 0081, AVE = 0047)R Of what happens in our market, nothing remains unknown to us. 0.73 0.71R Information that we need concerning our market, we are bound to get. 0.81 0.79

In our market, it is hard to make decisions based on reliable information. 0.51 0.58R We have sufficient information about our competitors. 0.68 0.69R We have sufficient insight and information about our customers. 0.67 0.66

Firm performance (�= 0083, composite reliability = 0089, AVE = 0074)Our organization is very profitable. 0.77 0.82In comparison with similar organizations, we are doing very well. 0.91 0.88Our competitors can be jealous of our performance. 0.89 0.87

Note. R, reversed item.

value of 0.60 for exploratory research (Nunnally 1967).Variables with relatively low reliability are technology(� = 0067) and culture (� = 0070). These variables arerelatively broad in conceptual scope (i.e., constructsdefined by two or more distinct elements or underly-ing dimensions). However, their reliability sufficientlyexceeds the threshold level of 0.55 recommended forsuch constructs by Van de Ven and Ferry (1980). Inaddition, composite reliabilities range between 0.80 and0.85, which is above the 0.70 commonly used thresholdvalue, and average variance extracted (AVE) measuresexceed the 0.50 value (Hair et al. 1998).

Each construct contains three to six items and wasmeasured on a seven-point Likert scale. We used confir-matory factor analysis with EQS version 6.1 to validatethe scales resulting from the exploratory factor analysis.A satisfactory fit was achieved with a root-mean-squareestimated residual (RMSEA) of 0.05 and confirmatoryfactor index (CFI) of 0.94. The CFI of 0.94 is consid-ered an indication of good fit, and the RMSEA of 0.05

indicates good model fit as it does not exceed the criti-cal value of 0.08 (Bentler and Bonett 1980). We verifiedthe discriminant validity of the scales by comparing thehighest shared variance between any of the two con-structs and the variance extracted from each of the con-structs (Hair et al. 1998). In all cases, each construct’sAVE is larger than its correlations with other constructs,supporting the discriminant validity of the measurementmodel (Fornell and Larcker 1981). In addition, none ofthe confidence intervals of the correlation coefficientsbetween any of the constructs included 1.0 (Andersonand Gerbing 1988). Given this collection of support-ing indices, we conclude that the measurement model isacceptable.

ResultsThis section presents the findings of our tests concern-ing Hypotheses 1–4. First, Table 3 presents descriptivestatistics and correlations of our variable set.

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Tab

le3

Des

crip

tive

Sta

tist

ics

and

Co

rrel

atio

ns

Mea

nSD

N1

23

45

67

89

1011

12

1ln

(Firm

size

)50

679

2011

03,

290

12

Indu

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ldum

my

0025

000

433

3,29

000

159∗

∗1

3Tr

ade

dum

my

0003

100

173

3,29

0−

0004

8∗∗

−00

103∗

∗1

4Se

rvic

edu

mm

y00

385

0048

73,

290

−00

038∗

−00

457∗

∗−

0014

1∗∗

15

Non

profi

tdum

my

0014

500

352

3,29

0−

0000

4−

0023

8∗∗

−00

074∗

∗−

0032

6∗∗

16

Mis

cella

neou

s00

189

0039

13,

290

−00

103∗

∗−

0027

9∗∗

−00

086∗

∗−

0038

1∗∗

−00

199∗

∗1

dum

my

7En

viro

nmen

tal

1309

6150

799

3,27

700

123∗

∗00

055∗

∗00

029

0002

9−

0007

2∗∗

−00

045∗

1tu

rbul

ence

8Te

chno

logy

4019

910

125

3,26

6−

0018

5∗∗

0000

800

030

0006

6∗∗

−00

096∗

∗−

0001

8−

0000

81

9St

ruct

ure

4028

610

298

3,28

300

297∗

∗00

047∗

∗−

0006

6∗∗

−00

035∗

0005

9∗∗

−00

033

−00

065∗

∗−

0005

2∗∗

110

Cul

ture

5039

510

097

3,28

5−

0027

7∗∗

−00

072∗

∗00

074∗

∗00

025

−00

079∗

∗00

087∗

∗−

0009

3∗∗

0025

8∗∗

−00

266∗

∗1

11Fi

rmpe

rfor

man

ce40

820

1024

03,

273

0003

200

058∗

∗00

042∗

0010

7∗∗

−00

181∗

∗−

0005

5∗∗

−00

065∗

∗00

294∗

∗00

105∗

∗00

202∗

∗1

12C

ontin

genc

ym

isfit

2803

7817

0189

3,25

800

127∗

∗00

053∗

∗00

025

0002

8−

0006

6∗∗

−00

045∗

∗00

989∗

∗−

0008

3∗∗

−00

113∗

∗−

0014

7∗∗

−00

097∗

∗1

13In

stitu

tiona

lmis

fit30

014

1041

93,

259

−00

019

−00

043∗

−00

008

−00

011

0012

6∗∗

−00

049∗

∗−

0001

4−

0034

7∗∗

−00

171∗

∗−

0035

2∗∗

−00

196∗

∗00

051∗

∗

∗Si

gnifi

cant

at0.

01;∗

∗si

gnifi

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001

(Pea

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.

To test Hypothesis 1, which deals with the per-formance effects of contingency misfit, we followedthe two-step procedure described previously. First, theapproximate fit line is established as a line in whichthe level of the organization design variable equals thatof the contingency variable (environmental turbulence).Misfit is then calculated as the deviation of a responsevariable from this particular fit line. Contingency mis-fit is the sum of the deviations of the response vari-ables technology, structure, and culture. Subsequently,we regressed the summated misfit on organizational per-formance. Model 2 in Table 4 presents the regressionresults of contingency misfit on firm performance. Con-trolling for firm size and a set of industry characteris-tics, we found significant negative performance effectsof contingency misfit (�= −00120, p < 00001). In addi-tion, contingency misfit of the three design variablesin our study explains a substantial (1.4%) and signifi-cant additional variance of organizational performance.Finally, contingency misfit remains stable in the mod-els where we add institutional misfit (Models 4 and 5).Overall, the results strongly support Hypothesis 1, evenwhen we take institutional factors regarding the designvariables of our study into account.

To test our second hypothesis on the performance con-sequences of institutional misfit, the average values ofthe organizational design variables (technology, struc-ture, and culture) were calculated for a subsample ofhigh-performing firms (Z-score for firm performance,≥ 105) for each industry category in our sample. Morespecifically, for each firm we analyzed whether it is anindustrial firm, trade firm, service firm, or a nonprofitfirm. Accordingly, we created four subsamples of high-performing firms in each of the four industry categories.For the remaining sample of firms (Z-score for firmperformance, < 105), the sum of the absolute devia-tions from the three organization design variables (tech-nology, structure, and culture) of the high performersin each industry category represents institutional misfit.Model 3 in Table 4 presents the results of the regressionanalysis of institutional misfit on firm performance. Thecoefficient of institutional misfit is significant and neg-ative (� = −00190, p < 00001). The additional varianceexplained by institutional misfit is substantial (3.3%) andhighly significant. Also, when we take the contingencymisfit into account in Models 4 and 5, the impact ofinstitutional misfit remains robust. We also tested therobustness of our model using a larger subset of high-performing firms (Z-score for firm performance, ≥ 100).This model with a broader set of high performers asthe norm shows similar results (�= −0019, p < 00001).Overall, these results strongly support Hypothesis 2 ofour theoretical framework.

Having found that contingency misfit and institutionalmisfit separately affect firm performance, we next exam-ined the simultaneous impact of these fit approaches

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Table 4 Hierarchical Regression of Controls and Theory Variables on Firm Performance

Model 1 Model 2 Model 3 Model 4 Model 5(Controls) (Fit line deviation) (Profile deviation) (Complementary model) (Interaction model)

� (SE) � (SE) � (SE) � (SE) � (SE)

Constant 40599 4000735∗∗∗ 40785 4000775∗∗∗ 40999 4000815∗∗∗ 50211 4000875∗∗∗ 50193 4000875∗∗∗

ln(Firm size) 00025 4000105 00040 4000105∗∗ 00025 4000105 00035 4000105∗∗ 00034 4000105∗∗

Industrial firms 00090 4000665∗∗∗ 00096 4000655∗∗∗ 00081 4000625∗∗∗ 00098 4000645∗∗∗ 00097 4000645∗∗∗

Trade firms 00062 4001305∗∗∗ 00067 4001305∗∗∗ 00047 4001275∗∗ 00068 4001285∗∗∗ 00067 4001275∗∗∗

Service firms 00120 4000605∗∗∗ 00126 4000605∗∗∗ 00106 4000575∗∗∗ 00133 4000595∗∗∗ 00132 4000595∗∗∗

Nonprofit firms −00118 4000755∗∗∗ −00121 4000745∗∗∗ −00102 4000715∗∗∗ −00097 4000745∗∗∗ −00097 4000745∗∗∗

Contingency misfit −00120 4000015∗∗∗ −00109 4000015∗∗∗ −00102 4000015∗∗∗

Institutional misfit −00190 4000145∗∗∗ −00151 4000155∗∗∗ −00167 4000155∗∗∗

Interaction term −00062 4000205∗∗∗

R2 00043∗∗∗ 00057∗∗∗ 00076∗∗∗ 00086∗∗∗ 00090∗∗∗

ãR2 (Model 1) 00014∗ 00033∗∗∗ 00043∗∗∗ 00047∗∗∗

ãR2 (Model 2) 00019∗∗ 00029∗∗ 00033∗∗∗

ãR2 (Model 3) 00010∗ 00014∗∗

ãR2 (Model 4) 00004∗

F 29.180 32.698 42.187 43.547 39.950N 3,243 3,243 3,099 3,243 3,243

∗p < 0005; ∗∗p < 0001; ∗∗∗p < 00001.

on firm performance. Model 4 in Table 4 shows thesimultaneous impact of contingency misfit and institu-tional misfit. In support of Hypothesis 3, the resultsshow that both fit approaches simultaneously affectfirm performance. Interestingly, contingency misfit (�=

−00109, p < 00001) and institutional misfit (�= −00151,p < 00001) both have a significant impact on firm per-formance; however, the size of the coefficient of institu-tional misfit is higher. Because the correlation betweenthe two fits is very low (0.051) and Variance InflationFactor scores are below 2, the results are not influ-enced by multicollinearity. If we estimate the differencebetween the coefficients of the misfit, then the differ-ence is statistically significant at the 5% level, suggest-ing that for our three organizational design variables,institutional misfit has a larger impact on firm perfor-mance than contingency misfit.

Finally, we examined the hypothesized negative mod-erating effect of contingency fit on the relationshipbetween institutional fit and performance (Hypothesis 4).From Model 5 in Table 4, it appears that the interac-tion term is indeed significant and negatively related toperformance (� = −00062, p < 0001), and the individ-ual misfit measures remain significant. When compar-ing Model 5 with Models 1–4, the model is superior inexplanatory power. These results support Hypothesis 4of our theoretical framework.

To illustrate the impact of our findings, the interac-tions between these two types of misfit have been plottedin Figure 1. Figure 1 shows the performance effects ofchanges in institutional misfit both for firms with lowcontingency misfit (good fit) and high contingency mis-fit (bad fit). Both slopes are negative, which implies thatdeviating from the organizational design of high per-formers reduces firm performance. However, the slope is

clearly less steep for firms aligned to their task environ-ment, i.e., firms with low contingency misfit. This resultsuggests that when firms enjoy good contingency fit, theeffects of institutional misfit weaken compared to whenfirms suffer from high contingency misfit.

To gain further insights into the interaction effectbetween institutional fit, contingency fit, and perfor-mance, we plotted the significant results obtained fromModel 5 of Table 4 in a three-dimensional (3D) graph(see Figure 2). The 3D graph perfectly illustrates thatfirms with high institutional and contingency misfit (theblue and green areas) will have low performance andcan substantially raise their performance by improv-ing institutional and/or contingency fit. Firms with highinstitutional and contingency fit are on a performance

Figure 1 Performance Effects of Institutional Fit

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0 2 4 6 8 10

Institutional profile deviation

Contingency fitContingency misfit

Firm

per

form

ance

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Figure 2 Landscape of the Effects of Interaction of Institutional Misfit and Contingency Misfit on Firm Performance

–1.0

–0.8

–0.6

–0.4

–0.2

0.0

0.2

0.4

0.6

–2.0–1.5

–1.0–0.5

0.00.5

1.01.5

2.0

–2.0–1.5

–1.0–0.5

0.00.5

1.01.5

Z (

stan

dard

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fir

m p

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X(s

tand

ardi

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it)

Y (standardized institutional misfit)

3D landscape of (standardized) misfit interactions

–1.0–0.8–0.6–0.4–0.2

0.00.20.40.6

peak (the orange area). However, those firms withperfect contingency fit and large institutional mis-fit (coordinates 4−21032105, or the left peak in thegraph) can only marginally improve their performancewhen they increase their institutional fit (movementfrom 4−21032105 to 4−2103−2105 along the Y axis).Quite counterintuitively, those firms with an extremeinstitutional fit and low contingency fit (coordinates42103−2105, or the right peak in the graph) will lowertheir extreme high performance when they increasetheir contingency fit (movement from 42103−2105 to4−2103−2105 along the X axis).

DiscussionIn this paper, we set out to address a fundamental debatein the strategic management literature on the relation-ship of the organization to its business environment,with the goal of contributing to the development ofa unifying theory on the relationship between organi-zational fit and performance. Scholars from differentschools of thought have used the concept of fit to indi-cate sources of synergy between the organization andits business environment, a concept that originates fromopen systems theory. Fit has been adopted as a key ele-ment explaining organizational performance within bothcontingency and institutional theories. Within a largesample of 3,259 respondents from 1,904 firms operat-ing in 13 different industries, we found strong supportfor the notion that the combined insights of both theo-ries produce a superior explanation of firm performance

than each theory in isolation. The results of this studyimply that each of these perspectives provides a partialexplanation of the synergetic effects between organi-zational and environmental elements, and that contin-gency and institutional fit interact in the formation offirm performance. This supports the notion of metafitproposed by Donaldson (2008a), which suggests thata sound and fully comprehensive organizational designanalysis should supplement contingency analysis withinstitutional analysis. Managers may benefit from con-sidering elements of both perspectives simultaneously tochart a course of action toward improved organizationalperformance. At the same time, managers must resolveinconsistencies between these perspectives by carefullyconsidering the context of their specific firms. Whenredesigning internal organization elements to optimizesynergy, they need to scan and interpret both the con-tingencies of their specific business environment and theinstitutional requirements of their industry.

By pursuing institutional fit, managers can help thefirm gain legitimacy through isomorphic processes. Inthis way, managers create synergy between the firm andthe institutional environment. Moreover, regardless ofthe pressures from the institutional environment, man-agers can also achieve high performance by searchingfor contingency fit. If contingency fit is not in linewith institutional requirements, however, firms may needto balance internal organizational effectiveness with theneed for external legitimacy and support. Institutionalprocesses partly substitute for a lack of capabilities and

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information on organizational effectiveness (Volberdaet al. 2010). However, by developing high levels of con-tingency fit, managers also develop a basis for externallegitimacy and support. Therefore, under high contin-gency fit when organizational effectiveness is high andobservable by external parties, the impact of institutionalmisfit on performance is reduced. The relevance of insti-tutional pressures therefore particularly applies to orga-nizations that have yet to demonstrate their effectiveness.

The relevance of our metafit approach particu-larly applies under conditions of persistent “quasi fit”(Donaldson 2001), rather than where there is perfectcontingency fit or optimal institutional fit. If we acceptthe assumption of quasi fit, the strategic discretion ofmost firms is limited to the right side of Figure 1, wherethe moderating impact of contingency fit is largest. Here,organizations face trade-offs between internal organiza-tional effectiveness and external legitimacy and supportin their organizational design. Similar conditions are alsolikely to apply where firms face suddenly unfamiliartask and institutional environments, such as in cases ofradical innovation, internationalization, unrelated diver-sification, and radical regulatory reform. Although firmsmay be tempted first to increase fit with their specifictask environment, they may be better off first decreas-ing institutional misfit, which substantially reduces thenegative impact of contingency misfit on firm perfor-mance (see Figure 1). Addressing this sequencing ques-tion of choosing whether to improve contingency fit byadaptation to the specific task environment, to invest inan improved institutional fit by copying organizationaldesigns of high-performing firms, or to improve bothsimultaneously is a fundamental strategic organizationaldesign issue. Our findings show that for all these firmsunder quasi fit (firms in the blue and green areas in Fig-ure 2), improvements in either fit or the joint optimiza-tion of these fits will result in increased performance.

Nonetheless, our results also show that for firms witha perfect contingency fit or an optimal institutional fit,our metafit approach is more of a conflicting mode thana complementary mode; that is, in situations of highcontingency fit where the firm specializes in one fitby completely adapting to its specific task environmentto improve internal organizational effectiveness, invest-ments in simultaneously improving institutional fit toincrease external legitimacy and support will only resultin marginal improvements of performance (see the con-tinuous line in Figure 1 with low contingency misfit andthe left peak with coordinates 4−21032105 in Figure 2).What emerges even more clearly is that firms that areable to realize an extreme institutional fit by copying theorganizational designs of high performers in their par-ticular industry to gain legitimacy and support shouldnot simultaneously invest in improving their contingencyfit (the right peak with coordinates 42103−2105 in Fig-ure 2). Such specific adaptations to their task environ-ment will even lower their performance (see the left side

of Figure 1, in which firms with low institutional mis-fit that decrease their contingency misfit move from thedashed line to the continuous line with lower perfor-mance). It should be noted that the number of firms withhigh institutional fit is very limited in our sample andis thus an exceptional case. Nonetheless, if these highlyinstitutionalized firms want to flourish, they should prob-ably just focus on following best practices on organiza-tion design in their industry and not distract themselvesby trying to adapt to every little whim of the market.All in all, firms under quasi fit instead of perfect fit mayimprove their performance by investing in increased con-tingency fit, increased institutional fit, or both. However,firms with perfect contingency or perfect institutional fitshould go for a specialization strategy. Figure 2 showsthat a high performance peak can be achieved by a sin-gle high contingency fit, a single high institutional fit, oracceptable levels of both fits.

Of course, the results of our study are subject toseveral limitations that need to be taken into accountwhen interpreting the results. First, our sample is largebut only contains firms that are active in the Nether-lands, which could represent a potential source of biasin our results and therefore needs validation in othercontexts. Second, respondents have not been invited tofill out the survey in subsequent years. Such an analysismight shed more light on time effects in fit–performancerelationships. Finally, although our study has shownthat contingency and institutional fit are interdependent,the development process toward metafit remains largelyunexplored. The next step would be to explore theimplications for dynamic institutional isomorphic or firmadaptation processes (e.g., Williams 2008, Volberda andLewin 2003) toward metafit. Understanding the dynam-ics of firm adaptation and institutional forces towardmetafit could further advance our understanding of howdifferent coevolutionary development paths influence therelationship between institutional mechanisms, contin-gency fit, and firm performance (Lewin and Volberda1999, Volberda and Lewin 2003).

In sum, drawing on contingency and institutional the-ory, this study demonstrated that most firms under quasifit in search of high performance need to adapt tothe task environment while simultaneously taking intoaccount institutional constraints (isomorphism). Theseperspectives are complementary and interact in whatmight be called metafit (Donaldson 2008a). However,firms with a high contingency fit should pay less atten-tion to institutional constraints because achieving aninstitutional fit at the same time will only slightlyincrease their performance. For firms that have achieveda perfect institutional fit, adapting to the specifics oftheir task environment might even decrease their per-formance. Exploring these dynamic coevolutionary pro-cesses of specific firm adaptations and more genericinstitutional forces at industry level will be a fruitfulsubject for future research.

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AcknowledgmentsThe authors are grateful to the senior editor, Rich Burton, forhis valuable feedback and guidance and to the three anony-mous reviewers. They also thank Ed Zajac for his helpfulcomments on an earlier version of this paper.

ReferencesAnderson, J. C., D. W. Gerbing. 1988. Structural equation modelling

in practice: A review and recommended two step approach.Psych. Bull. 103(3) 411–423.

Argyris, C., D. A. Schon. 1978. Organizational Learning: A Theoryin Action Perspective. Addison-Wesley, Reading, MA.

Ashby, W. R. 1956. An Introduction to Cybernetics. Chapman & Hall,London.

Bagozzi, R. P., Y. Yi, L. W. Phillips. 1991. Assessing construct valid-ity in organizational research. Admin. Sci. Quart. 36(3) 421–458.

Barreto, I., C. W. F. Baden-Fuller. 2006. To conform or to perform?Mimetic behaviour, legitimacy-based groups and performanceconsequences. J. Management Stud. 43(7) 1559–1581.

Bate, P. 1984. The impact of organizational culture on approaches toorganizational problem-solving. Organ. Stud. 5(1) 43–66.

Baum, J. A. C., C. Oliver. 1991. Institutional linkages and organiza-tional mortality. Admin. Sci. Quart. 36(2) 187–218.

Bentler, P. M., D. G. Bonett. 1980. Significance tests and goodnessof fit in the analysis of covariance structures. Psych. Bull. 88(3)588–606.

Birkinshaw, J., R. Nobel, J. Ridderstråle. 2002. Knowledge as a con-tingency variable: Do the characteristics of knowledge predictorganization structure? Organ. Sci. 13(3) 274–289.

Blau, P. M. 1970. A formal theory of differentiation in organizations.Amer. Sociol. Rev. 35(2) 201–218.

Boiral, O. 2003. ISO 9000: Outside the iron cage. Organ. Sci. 14(6)720–737.

Bourgeois, L. J., III. 1980. Performance and consensus. StrategicManagement J. 1(3) 227–248.

Briggs, S. R., J. M. Cheek. 1988. On the nature of self-monitoring:Problems with assessment, problems with validity. J. PersonalitySoc. Psych. 54(4) 663–678.

Burns, T., G. M. Stalker. 1961. The Management of Innovation. Tavi-stock, London.

Burton, R. M., B. Obel. 2004. Strategic Organizational Diagnosisand Design: The Dynamics of Fit. Kluwer Academic Publishers,Dordrecht, The Netherlands.

Burton, R. M., J. Lauridsen, B. Obel. 2002. Return on assets loss fromsituational and contingency misfits. Management Sci. 48(11)1461–1485.

Burton, R. M., J. Lauridsen, B. Obel. 2003. Erratum: Return on assetsloss from situational and contingency misfits. Management Sci.49(8) 1119.

Burton, R. M., B. H. Erikson, D. D. Håkonsson, T. Knudsen,C. C. Snow, eds. 2008. Designing Organizations: 21st CenturyApproaches. Springer, New York.

Camerer, C., A. Vepsalainen. 1988. The economic efficiency of cor-porate culture. Strategic Management J. 9(S1) 115–126.

Carroll, G. R. 1993. A sociological view on why firms differ. StrategicManagement J. 14(4) 237–249.

Child, J., L. Chung, H. Davies. 2003. The performance of cross-border units in China: A test of natural selection, strategic choiceand contingency theories. J. Internat. Bus. Stud. 34(3) 242–254.

Clark, E., A. Soulsby. 1995. Transforming former state enterprises inthe Czech Republic. Organ. Stud. 16(2) 215–242.

Cyert, R. M., J. G. March. 1963. A Behavioral Theory of the Firm,2nd ed. Prentice Hall, Englewood Cliffs, NJ.

D’Aunno, T., R. I. Sutton, R. H. Price. 1991. Isomorphism and exter-nal support in conflicting institutional environments: A studyof drug abuse treatment units. Acad. Management J. 34(3)636–661.

D’Aveni, R. A. 1994. Hypercompetition: Managing the Dynamics ofStrategic Maneuvering. Free Press, New York.

Davis, J. P., K. M. Eisenhardt, C. B. Bingham. 2009. Optimal struc-ture, market dynamism, and the strategy of simple rules. Admin.Sci. Quart 54(3) 413–452.

Deephouse, D. L. 1999. To be different, or to be the same? It’s a ques-tion (and theory) of strategic balance. Strategic Management J.20(2) 147–166.

Dess, G. G., R. B. Robinson Jr. 1984. Measuring organizational per-formance in the absence of objective measures: The case ofthe privately-held firm and conglomerate business unit. StrategicManagement J. 5(3) 265–273.

Dill, W. R. 1958. Environments as an influence on managerial auton-omy. Admin. Sci. Quart. 2(4) 409–443.

DiMaggio, P. J. 1991. Constructing an organizational field as a pro-fessional project: U.S. art museums, 1920–1940. W. W. Powell,P. J. DiMaggio, eds. The New Institutionalism in OrganizationalAnalysis. University of Chicago Press, Chicago, 267–292.

DiMaggio, P. J., W. W. Powell. 1983. The iron cage revisited: Insti-tutional isomorphism and collective rationality in organizationalfields. Amer. Sociol. Rev. 48(2) 147–160.

Dobrev, S. D., G. R. Carroll. 2003. Size (and competition) amongorganizations: Modeling scale-based selection among automo-bile producers in four major countries, 1885–1981. StrategicManagement J. 24(6) 541–558.

Donaldson, L. 1987. Strategy and structural adjustment to regain fitand performance: In defense of contingency theory. J. Manage-ment Stud. 24(1) 1–24.

Donaldson, L. 2001. The Contingency Theory of Organizations. Sage,Thousand Oaks, CA.

Donaldson, L. 2008a. Resolving the conflict between contingency andinstitutional theories of organizational design. R. M. Burton,B. H. Erikson, D. D. Håkonsson, T. Knudsen, C. C. Snow, eds.Designing Organizations: 21st Century Approaches. Springer,New York, 21–40.

Donaldson, L. 2008b. The conflict between contingency and institu-tional theories of organizational design. R. M. Burton, B. H.Erikson, D. D. Håkonsson, T. Knudsen, C. C. Snow, eds.Designing Organizations: 21st Century Approaches. Springer,New York, 3–20.

Drazin, R., A. H. Van de Ven. 1985. Alternative forms of fit in con-tingency theory. Admin. Sci. Quart. 30(4) 514–539.

Duncan, R. B. 1972. Characteristics of organizational environmentsand perceived environmental uncertainties. Admin. Sci. Quart.17(3) 313–327.

Emery, F. E., E. Trist. 1965. The causal texture of organizationalenvironments. Human Relations 18(1) 21–31.

Fines, C. H. 1998. Clockspeed: Winning Industry Control in the Ageof Temporary Advantage. Perseus, Reading, MA.

Fornell, C., D. F. Larcker. 1981. Evaluating structural equation modelswith unobservable variables and measurement error. J. Market-ing Res. 18(1) 39–50.

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Glick, W. H. 1985. Conceptualizing and measuring organizationaland psychological climate: Pitfalls in multilevel research. Acad.Management Rev. 10(3) 601–616.

Greening, D. W., B. Gray. 1994. Testing a model of organizationalresponse to social and political issues. Acad. Management J.37(3) 467–498.

Greenwood, R., C. R. Hinings. 1996. Understanding radical organi-zational change: Bringing together the old and the new institu-tionalism. Acad. Management Rev. 21(4) 1022–1054.

Griliches, Z. 1957. Hybrid corn: An exploration in the economics oftechnological change. Econometrica 25(4) 501–522.

Gupta, P. P., M. W. Dirsmith, T. J. Fogarty. 1994. Coordination andcontrol in a government agency—Contingency and institutionaltheory perspectives on GAO audits. Admin. Sci. Quart. 39(2)264–284.

Hair, J. F., Jr., R. E. Anderson, R. L. Tatham, W. C. Black. 1998.Multivariate Data Analysis, 5th ed. Prentice Hall, EnglewoodCliffs, NJ.

Hambrick, D. C. 1983. Some tests of the effectiveness and functionalattributes of Miles and Snow’s strategic types. Acad. Manage-ment J. 26(1) 5–26.

Haunschild, P. R., A. S. Miner. 1997. Modes of interorganizationalimitation: The effects of outcome salience and uncertainty.Admin. Sci. Quart. 42(3) 472–500.

Heugens, P. M. A. R., M. W. Lander. 2009. Structure! Agency! (andother quarrels): A meta-analysis of institutional theories of orga-nization. Acad. Management J. 52(1) 61–85.

Hickson, D. J., D. S. Pugh, D. C. Pheysey. 1969. Operations technol-ogy and organization structure: An empirical reappraisal. Admin.Sci. Quart. 14(3) 378–397.

Hill, T. 1983. Production/Operations Management: Text and Cases.Prentice Hall, New York.

Hitt, M. A., L. Bierman, K. Shimizu, R. Kochhar. 2001. Direct andmoderating effects of human capital on strategy and perfor-mance in professional service firms: A resource-based perspec-tive. Acad. Management J. 44(1) 13–28.

Hofer, C. W. 1975. Toward a contingency theory of business strategy.Acad. Management J. 18(4) 784–810.

Hofstede, G., B. Neuijen, D. D. Ohayv, G. Sanders. 1990. Measur-ing organizational cultures: A qualitative and quantitative studyacross twenty cases. Admin. Sci. Quart. 35(2) 286–316.

Hrebiniak, L. G., W. F. Joyce. 1985. Organizational adaptation: Strate-gic choice and environmental determinism. Admin. Sci. Quart.30(3) 336–349.

James, L. R., R. G. Demaree, G. Wolf. 1993. rwg : An assessmentof within-group interrater agreement. J. Appl. Psych. 78(2)306–309.

Jaworski, B. J., A. K. Kohli. 1993. Market orientation: Antecedentsand consequences. J. Marketing 57(3) 53–70.

Jones, A. P., L. A. Johnson, M. C. Butler, D. S. Main. 1983.Apples and oranges: An empirical comparison of commonlyused indices of interrater agreement. Acad. Management J. 26(3)507–519.

Kondra, A. Z., C. R. Hinings. 1998. Organizational diversity andchange in institutional theory. Organ. Stud. 19(5) 743–767.

Kraatz, M. S., E. J. Zajac. 1996. Exploring the limits of the newinstitutionalism: The causes and consequences of illegitimateorganizational change. Amer. Sociol. Rev. 61(5) 812–836.

Lawrence, P. R., J. W. Lorsch. 1967. Organization and Environment.Division of Research, Harvard Business School, Boston.

Lee, J., D. Miller. 1996. Strategy, environment and performancein two technological contexts: Contingency theory in Korea.Organ. Stud. 17(5) 729–750.

Levinthal, D. A. 1991. Organizational adaptation and environmen-tal selection—Interrelated processes of change. Organ. Sci. 2(1)140–145.

Levitt, B., J. G. March. 1988. Organizational learning. Annual Rev.Sociol. 14 319–338.

Lewin, A. Y., H. W. Volberda. 1999. Prolegomena on coevolution:A framework for research on strategy and new organizationalforms. Organ. Sci. 10(5) 519–534.

Lindell, M. K., C. J. Brandt. 2000. Climate quality and climate con-sensus as mediators of the relationship between organizationalantecedents and outcomes. J. Appl. Psych. 85(3) 331–348.

March, J. G. 1981. Footnotes to organizational change. Admin. Sci.Quart. 26(4) 563–577.

Meyer, J. W., B. Rowan. 1977. Institutionalized organizations: Formalstructure as myth and ceremony. Amer. J. Sociol. 83(2) 340–363.

Mintzberg, H. 1979. The Structuring of Organizations. Prentice Hall,Englewood Cliffs, NJ.

Nadkarni, S., V. K. Narayanan. 2007. Strategic schemas, strategic flex-ibility, and firm performance: The moderating role of industryclockspeed. Strategic Management J. 28(3) 243–270.

Nunnally, J. 1967. Psychometric Theory. McGraw-Hill, New York.

Orru, M., N. W. Biggart, G. G. Hamilton. 1991. Organizational iso-morphism in East Asia. W. W. Powell, P. J. DiMaggio, eds. TheNew Institutionalism in Organizational Analysis. University ofChicago Press, Chicago, 361–389.

Ouchi, W. G. 1979. A conceptual framework for the design of organi-zational control mechanisms. Management Sci. 25(9) 833–848.

Parker, S. C., A. van Witteloostuijn. 2010. A general framework forestimating multidimensional contingency fit. Organ. Sci. 21(2)540–553.

Pennings, J. M. 1987. Structural contingency theory: A multivariatetest. Organ. Stud. 8(3) 223–240.

Perrow, C. 1967. A framework for the comparative analysis of orga-nizations. Amer. Sociol. Rev. 32(2) 194–208.

Podsakoff, P. M., D. W. Organ. 1986. Self-reports in organiza-tional research: Problems and prospects. J. Management 12(4)531–556.

Podsakoff, P. M., S. B. MacKenzie, J. Y. Lee, N. P. Podsakoff. 2003.Common method biases in behavioral research: A critical reviewof the literature and recommended remedies. J. Appl. Psych.88(5) 879–903.

Porter, M. E. 1980. Competitive Strategy: Techniques for AnalyzingIndustries and Competitors. Free Press, New York.

Priem, R. L. 1994. Executive judgment, organizational congruence,and firm performance. Organ. Sci. 5(3) 421–437.

Pugh, D. S., D. J. Hickson, C. R. Hinings, K. M. Macdonald,C. Turner, T. Lupton. 1963. A conceptual scheme for organiza-tional analysis. Admin. Sci. Quart. 8(3) 289–315.

Roth, K., A. J. Morrison. 1992. Business-level competitive strategy:A contingency link to internationalization. J. Management 18(3)473–487.

Scott, W. R. 2001. Institutions and Organizations. Sage, ThousandOaks, CA.

Scott, W. R. 2003. Organizations: Rational, Natural, and Open Sys-tems. Prentice Hall, Upper Saddle River, NJ.

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Siggelkow, N. 2001. Evolution toward fit. Admin. Sci. Quart. 47(1)125–159.

Smith, K. G., J. P. Guthrie, M.-J. Chen. 1989. Strategy, size and per-formance. Organ. Stud. 10(1) 63–81.

Thompson, J. D. 1967. Organizations in Action: Social Science Basesof Administrative Theory. McGraw-Hill, New York.

Tolbert, P. S., L. G. Zucker. 1983. Institutional sources of changein the formal structure of organizations: The diffusion of civilservice reform, 1880–1935. Admin. Sci. Quart. 28(1) 22–39.

Tolbert, P. S., L. G. Zucker. 1996. The institutionalization of the insti-tutional field. S. R. Clegg, C. Hardy, W. R. Nord, eds. Handbookof Organization Studies. Sage, London, 175–190.

Tosi, H. L., Jr., J. W. Slocum Jr. 1984. Contingency theory: Somesuggested directions. J. Management 10(1) 9–26.

Van de Ven, A. H. 1979. Review of Organizations and Environments.Admin. Sci. Quart. 24(2) 320–326.

Van de Ven, A. H., R. Drazin. 1985. The concept of fit in contingencytheory. B. M. Staw, L. L. Cummings, eds. Research in Organi-zational Behavior, Vol. 7. JAI Press, Greenwich, CT, 333–365.

Van de Ven, A. H., D. L. Ferry. 1980. Measuring and Assessing Orga-nizations. John Wiley & Sons, New York.

Venkatraman, N. 1989. Strategic orientation of business enterprises:The construct, dimensionality, and measurement. ManagementSci. 35(8) 942–962.

Venkatraman, N., J. E. Prescott. 1990. Environment-strategy coalign-ment: An empirical test of its performance implications. Strate-gic Management J. 11(1) 1–23.

Volberda, H. W. 1996. Toward the flexible form: How to remain vitalin hypercompetitive environments. Organ. Sci. 7(4) 359–374.

Volberda, H. W. 1998. Building the Flexible Firm: How to RemainCompetitive. Oxford University Press, New York.

Volberda, H. W., A. Y. Lewin. 2003. Co-evolutionary dynamics withinand between firms: From evolution to co-evolution. J. Manage-ment Stud. 40(8) 2111–2136.

Volberda, H. W., N. J. Foss, M. A. Lyles. 2010. Absorbing the con-cept of absorptive capacity: How to realize its potential in theorganization field. Organ. Sci. 21(4) 931–951.

Von Bertalanffy, L. 1951. General system theory: A new approach tounity of science. Human Biol. 23(4) 303–361.

Washington, M., M. J. Ventresca. 2004. How organizations change:The role of institutional support mechanisms in the incorporationof higher education visibility strategies, 1874–1995. Organ. Sci.15(1) 82–97.

Weick, K. E. 1979. The Social Psychology of Organizing, 2nd ed.Random House, New York.

Wicks, D. 2001. Institutionalized mindsets of invulnerability: Differ-entiated institutional fields and the antecedents of organizationalcrisis. Organ. Stud. 22(4) 659–692.

Williams, C. 2008. Comparing evolutionary and contingency theoryapproaches to organizational structure. R. M. Burton, B. H.Erikson, D. D. Håkonsson, T. Knudsen, C. C. Snow, eds.

Designing Organizations: 21st Century Approaches. Springer,New York, 41–56.

Woodward, J. 1965. Industrial Organization: Theory and Practice.Oxford University Press, London.

Zajac, E. J., M. S. Kraatz, R. K. F. Bresser. 2000. Modeling thedynamics of strategic fit: A normative approach to strategicchange. Strategic Management J. 21(4) 429–453.

Zeithaml, V. A., P. R. Varadarajan, C. P. Zeithaml. 1988. The contin-gency approach: Its foundations and relevance to theory buildingand research in marketing. Eur. J. Marketing 22(7) 37–64.

Zucker, L. G. 1977. The role of institutionalization in cultural persis-tence. Amer. Sociol. Rev. 42(5) 726–743.

Zucker, L. G. 1987. Institutional theories of organization. Annual Rev.Sociol. 13 443–464.

Henk W. Volberda is a professor of strategic managementand business policy and director of knowledge transfer at theRotterdam School of Management, Erasmus University. He isscientific director of the top institute INSCOPE, member ofthe board of the Netherlands Center for Social Innovation, andvice president of the European Academy of Management. Hisresearch on strategic renewal, organizational flexibility, coevo-lution, and innovation has been published in many books andin a wide range of journals.

Niels van derWeerdt is an assistant professor in the Depart-ment of Strategic Management and Entrepreneurship at theRotterdam School of Management, Erasmus University. Hisresearch focuses on the measurement and performance con-sequences of organizational flexibility and design choices. Hereceived an M.Sc. in business administration and a Ph.D. instrategic management from Erasmus University Rotterdam.

Ernst Verwaal is a professor of international businessand market strategy at the Queen’s University ManagementSchool, Belfast. His research focuses on how firms developcompetitive advantage in international markets using insti-tutional structures, governance mechanisms, cooperative net-works, and analytics-based strategic decision making. Hereceived an M.Sc. in economics and business administrationfrom the University of Amsterdam and a Ph.D. in internationalbusiness studies from Leiden University.

Marten Stienstra is an assistant professor of strategic man-agement at the Rotterdam School of Management, ErasmusUniversity. He received his Ph.D. from the same institution.His research interests include organizational design and strate-gic renewal, with particular emphasis on the role of institu-tional issues in these processes.

Antonio J. Verdu is an associate professor of strategicmanagement at Miguel Hernandez University. He received hisPh.D. from the University of Granada (Spain). He workedas a postdoc at the Rotterdam School of Management, Eras-mus University. His research interests include strategic change,organizational adaptation, and business environment, with par-ticular emphasis on the dynamics of fit.

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