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A PARADOX AMONG STRATEGIC MANAGEMENT, INSTITUTIONAL,
AND RESOURCE DEPENDENCE THEORIES
DAVID L. DEEPHOUSE
Rucks Department of Management, Louisiana State University
R. CARTER HILL
Department of Economics, Louisiana State University
ERIC A. WALDEN
Department of Information Systems and Decision Sciences, University of Minnesota
Address correspondence to first author at:
E. J. Ourso College of Business Administration
Louisiana State University
Baton Rouge, LA 70803-6312
225-388-6249; 225-388-6140 (FAX)
mgdeep@lsu.edu
November 16, 1998
Under review at Academy of Management Journal. Please do not cite without authors’
permission.
We wish to thank Suzanne Carter, Peter Foreman, Bryant Hudson, Paul Jarley, Kai Lamertz,
Michael Sturman, Andrew Van de Ven, and James Westphal for their comments on prior drafts
of this manuscript. The final version benefited significantly from the suggestions of the editor
and the anonymous reviewers of this journal.
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(74 words)
A PARADOX AMONG STRATEGIC MANAGEMENT, INSTITUTIONAL,
AND RESOURCE DEPENDENCE THEORIES
ABSTRACT
Strategic management and institutional theories offer contradictory prescriptions about
how similar a firm's strategy should be to others. The former proposes differentiation increases
performance. The latter proposes conformity increases legitimacy. Moreover, institutional and
resource dependence theories propose a virtuous circle between performance and legitimacy.
This paper coalesces these propositions into a paradox and develops a model to test it. Results
support hypotheses derived from institutional theory. The paper concludes with suggestions for
future research.
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In order to prosper, strategic managers must select strategies that increase economic
performance and social legitimacy (DiMaggio & Powell, 1983; Pfeffer & Salancik, 1978).
Theory offers conflicting advice on the choice of strategies, however. Strategic management
recommends that a firm differentiate itself from its competitors to achieve superior performance
(Barney, 1991; Henderson, 1981; Porter, 1991; Wernerfelt, 1984). In contrast, new institutional
theory recommends that a firm should be isomorphic to its competitors to achieve legitimacy
(DiMaggio & Powell, 1983; Fligstein, 1991; Haveman, 1993; Meyer & Rowan, 1977). Given
that research is beginning to integrate strategic management and institutional theories (Dacin,
1997; Oliver, 1991, 1997; Powell, 1991; Roberts & Greenwood, 1997; Scott, 1994), the question
of strategic similarity is an important one for this integration (Chen & Hambrick, 1995).
Complicating this conflict is the relationship between performance and legitimacy.
Resource dependence theory suggests that legitimacy increases performance because of its effect
on the flow of resources to the firm (Pfeffer & Salancik, 1978). Institutional theory suggests that
performance increases legitimacy because it indicates how well a firm is fulfilling its roles in
society (Meyer & Rowan, 1977; Suchman, 1995). Together, these theories imply there is a
virtuous circle between performance and legitimacy.
Combining the conflicting prescriptions for how similar a firm's strategies should be to
others with the virtuous circle produces what we call the similarity paradox, depicted in Figure 1.
Hypothesis 1 states that greater strategic similarity reduces performance. Hypothesis 2 states that
greater strategic similarity increases legitimacy. Hypothesis 3 states that legitimacy increases
performance. Hypothesis 4 states that performance increases legitimacy.
-----Insert Figure 1 About Here----Empirical work has begun to examine these relationships. Three studies supported the
negative relationship between strategic similarity and performance predicted by strategic
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management (Hypothesis 1): Geletkanycz and Hambrick (1997); Gimeno and Woo (1996) and
Westphal, Gulati, and Shortell (1997). Two studies supported the positive relationship between
strategic similarity and legitimacy predicted by institutional theory (Hypothesis 2): Deephouse
(1996) and Westphal et al. (1997). Geletkanycz and Hambrick (1997) proposed and supported a
positive relationship between strategic similarity and performance, contrary to Hypothesis 1, by
combining the institutional and resource dependence arguments of Hypotheses 2 and 3. They did
not measure legitimacy, however. We are unaware of studies that formally tested either the effect
of performance on legitimacy, as predicted by institutional theory, or the effect of legitimacy on
performance, as predicted by resource dependence theory and recommended by Rao (1994: 40).
Consequently, no research examined the paradox in toto.
To address these gaps, this paper formally develops the similarity paradox and devises a
method to test it. The similarity paradox is a social paradox, consisting of thought-provoking
contradictions about social phenomena (Poole & Van de Ven, 1989). Social paradoxes provide
opportunities for building, testing, and refining theories (Poole & Van de Ven, 1989; Sutton &
Staw, 1995). Examination of the similarity paradox is important in the integration of strategic
management and organizational theories. The similarity paradox should be most applicable to
firms in strong competitive and institutional environments where performance and legitimacy are
important, such as pharmaceutical manufacturers, hospitals, and banks (Scott & Meyer, 1991).
We structure the paper as follows. First, we formally develop hypotheses for each part of
the paradox. Second, we describe how we tested the hypotheses in a sample of commercial banks
using a simultaneous equations model. Third, we present the results. We conclude with several
implications for future research.
THE SIMILARITY PARADOX
We define strategy as the realized position of a firm in its product-market space
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(Mintzberg, 1987; Porter, 1980). Representing resource allocations resulting from management
decisions and emergent patterns of action (Chandler, 1962; Mintzberg, 1978), strategy denotes
the markets a firm serves and how it positions itself to serve them. Underlying a firm’s strategic
position are its resources (Wernerfelt, 1984). Strategy is a fundamental concept in strategic
management (Rumelt, Schendel, & Teece, 1994), and it is becoming more important in
institutional research (e.g., Fligstein, 1991; Haveman, 1993; Powell, 1991; Scott 1994, 1995).
Following Gimeno and Woo (1996), we define strategic similarity as the extent to which a firm's
resource allocations resemble those of its competitors. In this paper, strategic similarity is a firmlevel concept, although it has also been applied at the strategic group level (e.g., Cool &
Dierickx, 1993; Farjoun & Lai, 1997).
Strategic Similarity and Performance
The first hypothesis of the paradox rests on the idea that a firm with different strategies
faces less competition for resources and thus has higher performance.1 Firms compete for
resources in both product and factor markets (Chen, 1996). These resources are divided among
competitors to the extent their realized strategic positions tap the same niches (Hotelling, 1929).
A firm conforming to the strategies of others has many similar competitors for customers
and factors of production that limit its performance (Chen, 1996; Henderson, 1981). This
situation approaches perfect competition in microeconomics in which economic profit for all
competitors equals zero. Chen and Hambrick (1995) proposed these firms might be "stuck in the
middle" (Porter, 1980). Similarly, Miles, Snow, and Sharfman (1993) suggested a lack of
strategic variety in an industry increases head-to-head competition and reduces performance.
A firm that rationally differentiates into an under exploited niche faces less competition.
Porter (1991: 102) proposed: "The firm must stake out a distinct position from its rivals.
Imitation almost ensures a lack of competitive advantage and hence mediocre performance." A
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distinct position enables the firm to earn higher rents because it faces less competition and may
even establish a local monopoly (Chamberlin, 1933; Henderson, 1981). Underlying this position
are resources that are rare, inimitable, valuable, and non-substitutable (Barney, 1991; Wernerfelt,
1984). A firm attempting to establish a position in a niche that turns out to be unviable will either
fail or change to a viable niche. Over time, most firms with different strategic positions will have
higher performance because they build barriers to imitation (Barney, 1991) or stay ahead of the
competition in exploiting market niches (D’Aveni, 1994).
Hypothesis 1: Less strategic similarity increases performance.
Support for this hypothesis has been reported by Gimeno and Woo (1996), Geletkanycz and
Hambrick (1997), and Westphal et al. (1997).
Strategic Similarity and Legitimacy
The second hypothesis of the paradox is based on the argument in new institutional
theory that a firm must be isomorphic to others to maintain legitimacy (DiMaggio & Powell,
83; Meyer & Rowan, 1977). Following Suchman (1995: 574), we define legitimacy as the
generalized perception that the firm's actions are congruent with the social system's values,
cultural theories, goals, and expectations for action (cf. Meyer & Scott, 1983; Parsons, 1960). For
most for-profit firms, ambiguity and uncertainty make the choice of strategies for dealing with
the environment unclear, leading to what DiMaggio and Powell (1983) called mimetic
isomorphism. Strategic norms emerge in an iterative process among firms and external actors
(Scott, 1995). The process contains at least three components: (1) imitation in the face of
uncertainty (Cyert & March, 1963; Haveman, 1993); (2) communication through trade
associations, social networks, or the media (Davis, Diekmann, & Tinsley, 1994; Haunschild,
1993); and (3) approval by regulatory, judicial, or legislative arms of the state (Edelman, 1992).
A firm conforming to strategic norms appears rational, prudent, and acceptable to its
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social system (Fligstein, 1991; Meyer & Rowan, 1977). The social system endorses the firm's
legitimacy or at least does not actively challenge it (Ashforth & Gibbs, 1990; Pfeffer & Salancik,
1978). On the other hand, a firm that deviates from the norm becomes subject to legitimacy
challenges and may be deemed unacceptable by society (Hirsch & Andrews, 1984; Meyer &
Rowan, 1977). Thus:
Hypothesis 2: Greater strategic similarity increases legitimacy.
Statistical support for this was reported by Deephouse (1996) and Westphal et al. (1997). Several
studies argued that maintaining legitimacy was important when imitating the strategies of others
(Dacin, 1997; Davis et al., 1994; Fligstein, 1991; Geletkanycz & Hambrick, 1997; Haveman,
1993). Finally, cognitive strategy researchers found that managers develop a cognitive consensus
about the appropriate strategies to use (Porac, Thomas, & Baden-Fuller, 1989; Reger & Huff,
1993). Porac et al. (1989) also reported criticism of those violating the norms.
The Virtuous Circle between Performance and Legitimacy
The last two hypotheses of the paradox consist of the virtuous circle between legitimacy
and performance. These two hypotheses have been suggested by past research but not formally
developed and tested. We first examine the effect of legitimacy on performance. From a
resource-dependence perspective, a major benefit of legitimacy is that it facilitates the flow of
resources from exchange partners to the firm (Hybels, 1995; Pfeffer & Salancik, 1978; Rao,
1994; Suchman, 1995: 574). Such resources include customer purchases, quality employees, and
supplier inputs. In general, a legitimate firm acquires better quality resources at better contract
terms than a firm that lacks social endorsements. Having higher quality resources and better
contract terms should increase a firm’s performance.
There are at least three ways that legitimacy enhances resource acquisition and improves
performance. First, some exchange partners will do business only with a firm endorsed by
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society. They wish to avoid the stigma of being associated with an illegitimate firm (Ashforth &
Gibbs, 1990). This restricts resource supply, increasing costs to a firm whose legitimacy is
challenged. Second, a legitimate firm can offer contract terms to exchange partners that are more
favorable to itself. Potential exchange partners prefer to contract with a legitimate firm because
this contract is itself an endorsement enhancing the legitimacy of the exchange partner
(Galaskiewicz, 1985; Pfeffer & Salancik, 1978: 145). Moreover, because legitimate firms are less
likely to fail (Baum & Oliver, 1991; Singh, Tucker, & House, 1986), exchange partners do not
need higher premiums in contracts to compensate for the risk of failure (Cornell & Shapiro,
1987). Third, because a legitimate firm is less likely to fail, it attracts higher quality managers
and employees who improve the quality of firm decisions (Hambrick & D’Aveni, 1992). Thus,
Hypothesis 3: Greater legitimacy increases performance.
Past research suggested informally that performance increases legitimacy (e.g., Parsons,
1960; Pfeffer & Salancik, 1978). Recent work in institutional theory provides a formal rationale
for this relationship. Since the Protestant reformation, success in the market has become an
increasingly important value in Western capitalist societies (Friedland & Alford, 1991; Weber,
1958). Firms that efficiently convert inputs into goods and services are likely to be more
acceptable to their social system (Dowling & Pfeffer, 1975; Parsons, 1960). Performance can be
viewed as a symbolic or substantive indicator of how much a firm contributes to society
(Ashforth & Gibbs, 1990; Meyer & Rowan, 1977). A firm with higher performance has more of
what Suchman (1995) called consequential legitimacy, the ability to deliver valued outcomes to
the social system. Thus, the firm should be endorsed by the social system. In contrast, a firm with
lower performance is more likely to face what Hirsch and Andrews (1984) called performance
challenges. The firm is criticized because of its failures to achieve its stated goals and to fulfill its
claimed domains in society (Ashforth & Gibbs, 1990; Levine & White, 1961). Thus:
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Hypothesis 4: Greater performance increases legitimacy.
METHOD
Sample
The paradox was tested in the entire population of commercial banks in the MinneapolisSt. Paul, Minnesota, area (Twin Cities, hereafter) from 1985 to 1992. A commercial bank is
chartered by government regulators. It differs from a bank holding company that can own several
bank and non-bank subsidiaries. Commercial banks are in strong competitive and institutional
environments (Scott & Meyer, 1991).
During the sample period, a banking market was defined as a metropolitan area or a rural
county by regulators (e.g., Federal Reserve Bulletin, 1991), financial economists (e.g., Berger,
1995; Hannan, 1991), and management researchers (e.g., Barnett, Greve, & Park, 1994). Thus,
Twin Cities banks compete with each for similar customers and similar inputs (Chen, 1996).
Studying one industry in one market controls for the confounding influences of competitive
conditions, social values, and institutional forces that vary across geographic locations and
industries. We chose 1985 as the initial year because regulators changed reporting requirements
in 1984. There were 159 banks in business in the period. The unit of analysis was the bank-year.
The sample of banks was identified from the Call Reports database, which consists of balance
sheet and income statement data that regulators require banks to file.
Measures
Strategic similarity. We measure strategic similarity using strategic distance (Chen &
Hambrick, 1995; Cool & Dierickx, 1993; Fiegenbaum & Thomas, 1995; Gimeno & Woo, 1996;
Miles et al., 1993). As applied in this research, strategic distance measures the Euclidean distance
between the strategies of the individual bank and average strategies of all banks in the Twin
Cities. Average strategies represent reference points for managers in positioning decisions
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(Fiegenbaum & Thomas, 1988; Huff, 1982; Mintzberg & Waters, 1985).
The strategy variables used to measure strategic similarity in this study were bank asset
strategies (Santomero, 1984). An asset strategy is the allocation of resources to certain revenueproducing activities (cf. Chandler, 1962). It is expressed here as a proportion of total assets.
Financial economists (e.g., Swamy, Barth, Chou, & Jahera, 1996) and management researchers
(e.g., Reger, Duhaime, & Stimpert, 1992; Haveman, 1993) used asset allocation models to
measure strategy. Data from the Call Reports were used to measure eleven asset strategy
variables: commercial loans, real estate loans, loans to individuals, agriculture loans, other loans
and leases, cash, overnight money, securities, trading accounts, fixed assets, and all other assets.
The following equation was used to calculate SDit, the Euclidean strategic distance from industry
average for bank i in time t, where Pait is the proportion of the assets in strategy a for bank i in
time t, and M(Pat) is the mean proportion of strategy a for the industry in time t.
11

SDit   Pait  M Pat 
a 1

1/ 2
2
The range of SDit is non-negative, and it decreases as strategic similarity increases.
Performance. Although there are many ways to measure performance, in commercial
banking return on assets (ROA) was the most commonly used and well-regarded measure during
our sample period (e.g., Barnett et al, 1994; Berger, 1995; Gilbert, 1984; Swamy et al., 1996).
Reger et al. (1992: 195) stated: "Return on assets is the most meaningful financial indicator in the
banking industry and is the indicator most closely watched by bank analysts and the bankers
themselves." ROA measures the effectiveness of management’s utilization of its assets and
allows comparison between banks with different capital structures (Kidwell & Peterson, 1990).
ROA is especially appropriate for our sample because most banks were privately held. We
computed ROA as the ratio of net income to average assets. Total average assets was the
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denominator, consistent with bank regulatory practice, because banks undertake "window
dressing" of their balance sheets at year-end and assets change over time. For clarity in our
regression tables, we multiplied ROA (and its lagged value) by 10.
Legitimacy. Reflecting on the multidimensional nature of legitimacy, Ruef and Scott (in
press) suggested that empirical researchers limit the scope of their studies to certain components.
They examined the legitimacy of hospitals from the perspective of professional organizations.
We follow their lead and measure two types of socio-political legitimacy, regulative and
normative (Scott, 1995).
Socio-political legitimacy is usually measured from endorsements made by constituents
who have the authority to confer legitimacy (Meyer & Scott, 1983; Stinchcombe, 1968).
Constituents endorse a firm when it satisfies the norms and rules of society. They also issue
legitimacy challenges or “anti-endorsements” when a firm is not congruent with these norms and
rules (Ashforth & Gibbs, 1990; Dowling & Pfeffer, 1975; Hirsch & Andrews, 1984). Legitimacy
challenges may be more visible than endorsements. Pfeffer and Salancik (1978: 194) stated:
"Legitimacy is known more readily when it is absent than when it is present." Researchers
examined endorsements by regulatory agencies, religious organizations, finance intellectuals,
professional associations, etc. (Baum & Oliver, 1991; Davis et al., 1994; Singh et al., 1986;
Westphal et al., 1997).
Regulative legitimacy focuses on adherence to legal and regulatory rules (Scott, 1995)
that often embody deeper social values and expectations (Edelman & Suchman, 1997). An
important publicly available endorsement was the regulators’ evaluation of a bank's capital
position, which reflect its ability to safeguard customer deposits. Regulators classified banks into
three categories. Banks in lower categories were not endorsed by the regulators. Instead, they
were subject to increased levels of regulatory supervision that varied by category. Banks
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persisting in the lowest category would be closed. We measured regulative legitimacy using the
regulators’ three ordered categories (Spong, 1985, 1990). These categories were numbered 0, 1,
and 2, with 2 representing adequate capital. This variable was called regulatory endorsement.
Normative legitimacy focuses on adherence to social norms and values (Parsons, 1960;
Scott, 1995). The general public has values that it expects banks to share and expectations for the
actions that banks undertake. Normative legitimacy is the extent to which a bank adheres to these
values and fulfills these expectations for action. We measured normative legitimacy by content
analyzing media reports. Communication and management research pointed out the media
influence and reflect societal norms and values (Dowling & Pfeffer, 1975; Gamson, Croteau,
Hoynes, & Sasson, 1992; Gans, 1979). When firm actions are illegitimate, comments and attacks
occur, and the media report such comments (Dowling & Pfeffer, 1975; Pfeffer & Salancik, 1978:
194). Although the media may be biased towards bad news, we assume this bias does not vary
across banks. Moreover, endorsements of a bank and reports of its legitimate actions appear in
the media. A firm that was not challenged in the media would be legitimate because no question
was raised about its role and role performance (Meyer & Scott, 1983). The media was used to
assess the legitimacy of President Reagan’s Task Force on Food Assistance (Coombs, 1992),
ACT UP and Earth First! (Elsbach & Sutton, 1992), the unrelated diversification strategy (Davis
et al., 1994), the population of biotechnology firms (Hybels, Ryan, & Barley, 1994), and
downsizing (Lamertz & Baum, 1998).
We measured normative legitimacy using a variable called media endorsement reported
by Deephouse (1996) who content analyzed Twin Cities' newspapers. Following Janis and
Fadner (1965), it measures the relative proportions of endorsing and challenging recording units
for a bank in a year. Its range is (-1, 1). It equals 0 when the number of challenging articles equals
the number of endorsing articles.
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Control Variables. We included several variables to improve model specification. The
first was for bank size. Most economic research suggests that larger banks should be more
profitable than smaller banks. Two reasons for this are the market power and the efficient
structure hypotheses (Berger, 1995). The former argues that large companies can set higher
prices because of their size (Gale, 1972). The latter argues that larger firms have lower costs
resulting from scale economies or superior management (Demsetz, 1973). Size also controls for
the possibility that there are strategic groups of banks based on size, as suggested by Porter
(1979) and Reger and Huff (1993). Size may also increase legitimacy. Larger firms have more
contractual and social ties with actors in the external environment which should lead to more
endorsements (Baum & Oliver, 1991; Galaskiewicz, 1985; Pfeffer & Salancik, 1978; Singh et al.,
1986;). We measured size with market share of deposits, consistent with prior bank studies (e.g.,
Berger, 1995; Smirlock, 1985). Market share was correlated in excess of 0.93 with total average
assets and number of employees, two other measures of size common in organizational research.
The asset strategies measuring strategic similarity primarily address the revenue side of
banking, not the cost side. Banks which emphasized low costs should have higher performance
(Dos Santos & Peffers, 1995). Following Dos Santos and Peffers (1995), we controlled for costs
using the total expense ratio, the ratio of total expenses to total average assets.
Age may increase legitimacy. Singh et al. (1986) stated that older firms were more likely
to develop stronger exchange relationships, to become part of a power hierarchy, and to have
their actions endorsed by powerful collective actors. Older firms are more also reliable (Hannan
& Freeman, 1984). We obtained the founding year for each bank from Polk's Bank Directory, a
semi-annual reference of banks.
Lagged dependent variables also were included as controls. These reflect the possibility
that the effects of changes in the independent variables, such as the effect of strategic similarity
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on performance, are distributed over multiple time periods (Fomby, Hill, & Johnson, 1984).
Annual dummy variables were added to each equation. We excluded the dummy variable
for the first year to avoid perfect collinearity with the intercept (Greene, 1993). Annual dummies
reflect overall trends occurring in the competitive market or the institutional environment, such
as changes in the resource environment and the structure of the industry. We attempted to control
for these directly using annual measures of market growth and concentration. Inclusion of these
annual constants created serious collinearity problems (Belsley, Kuh, & Welsch, 1980).
Statistical model and analysis techniques
The following two equations comprise our basic statistical model. The first equation tests
performance; the second, legitimacy. The legitimacy term represents regulatory endorsement and
media endorsement. All variables are from time t except the lagged dependent variables.
ROAit   0   1Strategic Distance it +  2 Legitimacy
it
  3 Market Share it 
M
 4 Total Expense Ratio it   5 ROAi ,t 1    m  4 Year Dummy
m2
Legitimacy
it
m
 e1t
(1)
  0   1Strategic Distance it +  2 ROAit   3 Market Share it 
 4 Age it   5 Legitimacy
M
i ,t 1    m  4 Year Dummy
m2
m
 e2t
(2)
Taken as individual equations, a least squares estimator would be appropriate for the
ROA equation, a probit estimator would be appropriate for the ordinal regulatory endorsement
legitimacy variable, and a tobit estimator would be appropriate for the censored media
endorsement legitimacy variable (Greene, 1993; Judge, Hill, Griffiths, Lüktepohl, & Lee, 1985).
However, the mutual relationship between legitimacy and performance creates simultaneity bias
which makes these estimators biased and inconsistent (Greene, 1993; Judge et al., 1985;
Kennedy, 1985). The usual solution for simultaneity bias is to replace ROA and the legitimacy
measures on the right hand side of the equations with instrumental variables, but the typical twostage least squares procedures in most statistical packages are inappropriate because the
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legitimacy measures are not continuous.
To address this, we applied the two-step estimator introduced by Heckman (1978) and
Amemiya (1978, 1979) for non-continuous variables. Identification is a precondition for
estimating a simultaneous equations model. The two equations are identified by the rank
condition (Judge et al., 1985; Greene, 1993). In small samples, the asymptotic covariance
matrices derived by Amemiya (1979) and Hill and Waters (1995) for censored and ordinal
dependent variables usually understate the true standard errors (Freedman & Peters, 1984). This
increases the chance of Type I error. To mitigate this, we employed empirically derived standard
errors based on a bootstrap procedure (Jeong & Maddala, 1993). We implemented our estimation
procedure using IML, the matrix programming procedure in SAS (SAS Institute, 1990).
After collecting our media data, we discovered that not all the banks received media
coverage each year. Because media endorsement is measured only for banks covered by the
media, there may be sample selection bias (Heckman, 1979). Estimates for the sample may not
apply to all the banks in the period, thus raising generalizability concerns. To correct for this, we
applied the two-step procedure presented by Heckman (1979). The first step estimated a probit
model predicting whether a bank received media coverage. We used these estimates to create a
variable called the "inverse Mills ratio" that corrects for sample selection bias when included in
both equations of the model. We also modified the statistical model slightly. To reduce
collinearity in the ROA equation, we eliminated the theoretically unimportant dummy variable
for 1989 (Belsley, Kuh, & Welsch, 1980). In the legitimacy equation, we eliminated the lagged
dependent variable because its inclusion would cut the sample size from 265 to 155.
RESULTS
We examined our data in the two periods associated with our measures of regulative and
normative legitimacy. After collecting and classifying the regulatory data, we discovered that all
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banks were in the highest regulatory category during 1989-1992, so we analyzed this variable
only in 1986-1988. Table 1 presents the means, standard deviations, and correlations among the
variables during the period 1986-1988 when regulatory endorsement was the legitimacy measure.
The sample size was 400. Table 2 presents these statistics from 1988-1992, when media
endorsement was the legitimacy measure. The sample size was 265.
-----Insert Tables 1 and 2 About Here----Table 3 presents the results of the two-step estimates. Hypothesis 1, based on strategic
management theory, predicted that less strategic similarity increases performance. In columns 1
and 3, the coefficients for strategic distance were not statistically significant, providing no
support for Hypothesis 1. The collusion hypothesis of oligopoly theory was not supported either,
given that the coefficients were greater than zero. Hypothesis 2, based on institutional theory,
predicted that greater strategic similarity increases legitimacy. In columns 2 and 4, the
coefficients for strategic distance were negative and significant at the p<.05 and p<.01 level,
respectively, supporting hypothesis 2. Hypothesis 3, based on resource dependence theory,
predicted that legitimacy increases performance. Neither the coefficient for regulatory
endorsement in column 1 nor the coefficient for media endorsement in column 3 was statistically
significant, providing no support to hypothesis 3. Hypothesis 4, based on institutional theory,
predicted that performance increases legitimacy. The coefficient for ROA was positive and
significant at the p<.05 level in column 2. It was not significant in column 4. Thus, there is
mixed support for Hypothesis 4.
-----Insert Table 3 About Here----Turning to the control variables, market share did not have a significant effect on any of
the dependent variables. The total expense ratio had a significantly negative effect on ROA in
both columns 1 and 3, as expected. Age did not have a positive effect on regulatory endorsement,
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but it had a significantly negative effect on media endorsement. The lagged dependent variables
were positive and significant, as expected. The inverse Mills ratio was positive and significant at
the p<.001 level in column 4, implying that controlling for selectivity was very important when
estimating media endorsement.
DISCUSSION AND CONCLUSION
The relationships among firm-level similarity, performance, and legitimacy have attracted
increased research attention recently (e.g., Chen & Hambrick, 1995; Deephouse, 1996;
Geletkanycz & Hambrick, 1997; Gimeno & Woo, 1996; Westphal et al., 1997). This paper
coalesced strategic management, institutional, and resource dependence theories to create the
similarity paradox. The paradox highlights the challenges managers face in strong competitive
and institutional environments. It also advances our understanding of theory (Poole & Van de
Ven, 1989; Sutton & Staw, 1995). We tested the paradox in a population of commercial banks
using a simultaneous equations model. Although the paradox as a whole was not supported, our
results lent support to the predictions of institutional theory. Our study has several implications
for future research on the paradox and its components.
The first hypothesis stated that less strategic similarity increases performance, based on
strategic management theory (e.g., Porter, 1991). We did not find statistical support for this. Past
results in different industries have been mixed (Geletkanycz & Hambrick, 1997; Gimeno & Woo,
1996; Westphal et al., 1997). One explanation may be the level of uncertainty in the banking
industry. Geletkanycz and Hambrick (1997) found the relationship was positive in the more
certain branded foods industry and negative in the more uncertain computer industry. At some
level of uncertainty, the relationship between conformity and performance switches from positive
to negative. It is plausible that the level of uncertainty in the banking industry is between the
levels in computers and branded foods such that the relationship between similarity and ROA is
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near zero. A second explanation for these results is that we examined similarity across all
competitors in the market, consistent with strategy (e.g., Geletkanycz & Hambrick, 1997) and
financial economics research (e.g., Berger, 1995). Future research could examine if competition
is more localized around strategic groups (e.g., Cool & Dierickx, 1993) or firm-specific niches
like geography (e.g., Gimeno & Woo, 1996).
Our second hypothesis stated that greater strategic similarity increases legitimacy, based
on new institutional theory (e.g., DiMaggio & Powell, 1983; Meyer & Rowan, 1977). We found
strong support for this. Because our estimation controlled for the virtuous circle between
performance and legitimacy, we provide more conclusive evidence for the positive effect of
conformity on legitimacy shown in past research (e.g., Deephouse, 1996; Westphal et al., 1997).
Taken together, the results for hypotheses 1 and 2 suggest the set of firms important for
determining performance in the competitive environment can differ from the set important for
determining legitimacy in the institutional environment. Having two different groups complicates
the strategic choices made by managers and could be an important topic for future research.
Past research implied there may be a virtuous circle between performance and legitimacy,
but neither relationship has been formally tested in past research . Hypothesis 3 stated legitimacy
should increase performance, based on resource dependence theory (Pfeffer & Salancik, 1978).
Although least squares estimates (available on request) show that regulative legitimacy had a
positive effect on ROA, our final analysis did not support this hypothesis. Thus, controlling for
simultaneity bias is important when testing performance and legitimacy. A theoretical
explanation for our results is that other institutions may diminish the benefits of legitimacy. In
banking, government deposit insurance and the regulators’ practice of merging troubled banks
may have curtailed the need for potential exchange partners to rely on the regulatory and media
endorsements in their decisions.
Page 19
Hypothesis 4 stated that performance should increase legitimacy, based on institutional
theory (e.g., Friedland & Alford, 1991; Suchman, 1995). We found different results for the two
types of legitimacy. Performance had a positive effect on regulatory legitimacy. A central
concern of regulators is the safety and soundness of banks (Spong, 1990), and, as our results
demonstrated, performance helps alleviate this concern. The results for normative legitimacy did
not support hypothesis 4, however. One explanation is the Twin Cities community did not value
higher profits as much as other characteristics, such as the companies’ charitable giving that
Galaskiewicz (1997) has studied extensively. Similarly, in Canada, high bank profits led to “bank
bashing” (Partridge, 1996: B1). Taken together, the results for Hypotheses 3 and 4 suggest that
future research could examine differences in the relationship between performance and different
types of legitimacy (e.g., Ruef & Scott, in press; Scott, 1995; Suchman, 1995).
This paper also makes a methodological contribution to legitimacy research. Legitimacy
is often conceptualized non-continuously (Galaskiewicz, 1985; Meyer & Scott, 1983; Pfeffer &
Salancik, 1978: 194) and measured using endorsements (Baum & Oliver, 1991; Singh et al.,
1986). Although this complicates testing the virtuous circle between performance and legitimacy,
we resolved it by developing a simultaneous equations technique.
There are some limitations to this study that could be examined in future research. We
examined only one type of performance, ROA, an appropriate measure in our sample of privately
held banks. Future research could use market return to measure performance among publicly
traded firms. A second limitation is causality. Consistent with the strategic choice view (Child,
1972), we assumed strategic choices led to differences in the similarity of competitors, which
then affect performance and legitimacy. Strong causal inference from our results would be
inappropriate. A third limitation is generalizability. We studied only one industry in one market.
Future research could examine the similarity paradox in other samples facing strong competitive
Page 20
and institutional forces.
In sum, this paper integrated strategic management, institutional, and resource
dependence theories to develop a paradox connecting three important concepts: similarity,
legitimacy, and performance. Our empirical analysis supported hypotheses based on institutional
theory. We recommend further examination of the hypotheses based on strategic management
and resource dependence theories that did not receive support here. On a broader level, this paper
contributes to the study of how firms interact with competitive and institutional forces and to the
dialogue among the theories that address this important topic.
Page 21
ENDNOTES
Some research in strategic management proposes that greater strategic similarity increases
performance, namely strategic groups and oligopoly theories. Similar firms may engage in tacit
collusion (Caves & Porter, 1977; Stigler, 1964). Whether collusion supplants competition
depends on many conditions (Cool & Dierickx, 1992), and empirical support in the banking
industry is weak (Berger, 1995). Hence, we do not state this as a competing hypothesis. We do
consider it in our research design and in our results.
1
Page 22
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Page 29
TABLE 1
Correlations for 1986-1988a
Mean
s.d
1. ROA (Return on Assets)
0.009
0.008
2. ROAt-1
0.010
0.008
.65**
3. Regulatory endorsement
1.805
0.461
.37**
.24**
4. Regulatory endorsementt-1
1.833
0.447
.27**
.30**
5. Strategic Distance
0.042
0.033
-.07
-.09
-.28**
-.24**
6. Market Share
0.007
0.034
-.14**
-.13**
-.04
-.04
.11*
7. Total Expense Ratio
0.083
0.010
-.60**
-.54**
-.28**
-.30**
.15**
53.230
32.677
.04
.05
8. Age
1
2
3
4
5
6
.50**
-.04
.02
-.08
4
5
-.07
.28**
aN=400. * p < 0.05; ** p < 0.01 (two-tailed).
TABLE 2
Correlations for 1988-1992a
Mean
s.d
1
2
1. ROA (Return on Assets)
0.008
0.008
2. ROAt-1
0.008
0.008
3. Media Endorsement
0.871
0.317
-.03
-.00
4. Strategic Distance
0.040
0.035
.04
-.00
7
3
.56**
-.11
6
-.21**
Page 30
5. Market Share
0.017
0.060
-.03
-.17**
-.18**
.17*
6. Total Expense Ratio
0.084
0.014
-.44**
-.33**
.10
.06
50.230
33.5995
-.00
-.03
-.10
-.10
7. Age
aN=265. * p < 0.05; ** p < 0.01 (two-tailed).
.01
.46**
-.07
Page 31
TABLE 3
Two-Step Estimatesa
Sample Period & Dependent Variables
1986-1988
1
1988-1992
ROA
2
Regulatory
Endorsement
ROA
Intercept
0.337***
(0.075)
0.052
(0.362)
0.151
(0.255)
2.763***
(0.170)
Strategic Distance
0.003
(0.004)
-0.184*
(0.078)
0.003
(0.008)
-0.101**
(0.038)
Regulatory endorsement
0.001
(0.010)
Independent Variables
Media Endorsement
4
Media
Endorsement
-0.002
(0.177)
ROA
3.390*
(1.709)
Market Share
-0.280
(0.234)
Total Expense Ratio
-3.328***
(0.720)
Age
ROAt-1
3
-0.051
(3.208)
-1.148
(0.746)
0.081
(0.223)
-2.026
(2.146)
-1.334+
(0.794)
-0.000
(0.003)
0.430***
(0.087)
-0.005***
(0.001)
0.502***
(0.146)
Regulatory endorsementt-1
0.968***
(0.208)
Ordinal Probit Threshold
1.339***
(0.229)
Inverse Mills Ratio
0.016
(0.015)
0.380***
(0.080)
Annual Dummy Variables Not Shown.
Sample Size
400
400
265
aStandard errors based on 500 bootstrap samples are in parentheses. Significance tests are two-tailed.
+ p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001.
265