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Firm culture and performance:
intensity’s effects and limits
Patrick J. Murphy
DePaul University, Chicago, Illinois, USA
Robert A. Cooke
University of Illinois at Chicago, Chicago, Illinois, USA, and
Yvette Lopez
DePaul University, Chicago, Illinois, USA
Abstract
Purpose – The aim of this paper is to clarify distinct aspects of firm culture, delineate its effects on
performance outcomes, and to examine culture intensity on theoretic grounds with attention to its
effects and limits.
Design/methodology/approach – The study analyzes a data set of 2,657 individual cases that are
empirically aggregated into 302 organizational units. Its operationalization of culture intensity derives
from distinct culture theory. Hypothesized relations are examined via structural equation modeling
and hierarchical regression analysis.
Findings – Structural equation modeling results show culture relates positively to cooperation,
coordination, and performance. Hierarchical regression analysis results show intensity influences
cooperation and coordination directly and does not moderate culture’s relations with those outcomes.
Research limitations/implications – The large scale empirical study of a broad diversity of firms
has advantages over smaller and more targeted studies of lesser generalizability.
Practical implications – Firms with cultures of higher intensity can enhance performance
indirectly by driving cooperation and coordination directly.
Social implications – Culture entails shared values and touches the human side of a firm. Managers
can promote a firm’s culture to enhance cooperation and coordination outcomes within that firm
which, in turn, influence firm performance.
Originality/value – This study distinguishes culture from climate on conceptual grounds. Climate
strength, an analog of culture intensity, is known to moderate climate’s relations with outcomes. By
contrast, this study shows that culture intensity has a main effect on outcomes, in line with culture’s
distinct theoretic bases.
Keywords Performance management, Organizational culture
Paper type Research paper
Introduction
Firm culture is regarded quite widely as an important factor of firm performance. It is a
concept that touches many internal parts of an organization just as it interfaces with
the environment outside an organization. A firm’s culture helps managers interpret
and initiate firm activities when there are few other cues to guide behavior, even as it
informs and shapes a firm’s reputation in a market environment. Because of its strong
relevance to organizational action, firm culture continues to appear as a functional
variable in business studies. It also leads to some of the most interesting and important
questions in the domain of business studies (Asif, 2011; Denison, 1996; Ravasi and
Schultz, 2006).
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0025-1747.htm
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Management Decision
Vol. 51 No. 3, 2013
pp. 661-679
qEmerald Group Publishing Limited
0025-1747
DOI 10.1108/00251741311309715
Culture is often discussed when describing firms, but it is a notoriously hard
construct to define sui generis. In fact, theories of culture have conceptual foundations
far outside the domain of the domain of business studies. They derive from the long
tradition of anthropological research on shared values and beliefs in communities and
how those elements relate directly to internal organizational workings (Conklin, 1968;
Redfield, 1952). Research in those traditions entails a diversity of methods such as
extended fieldwork residencies and immersion in daily life in order to explain the
intricacies of the shared values and assumptions that define culture (Douglas, 1976;
Mehri, 2005). Although such shared values and assumptions also exist in today’s firms,
the qualitative data of traditional culture research can be empirically questionable in
business studies, where there is a greater emphasis on quantitative scores and the
proper navigation of different empirical levels of analysis (Tett and Burnett, 2003). As
such, researchers of firm culture regularly call for appropriate methodological
approaches and careful empirical data composition (Gregory et al., 2009; Perrin, 2004;
Schein, 1990; Weick, 2006).
Business studies based on culture theory often entail the challenge of how to benefit
from culture’s non-organizational anthropological heritage when operationalizing it as
a construct in the context of organizational factors (Brown, 1995; Glick, 1988; Wilkins
and Ouchi, 1983; Zheng et al., 2010). Unlike studying culture in well-defined
communities, organizational scholars study its assumptions and beliefs alongside
strategies, structures, control systems, technologies, and business models. These latter
elements introduce complexities that influence culture scores as they shift in response
to the external environment (Lawrence and Lorsch, 1967). The compounded relations
and interfaces account for why applying culture theory in business studies can and
does open conceptual gaps based on misusage of terms (e.g. culture versus climate),
measurement techniques that miss the essence of the construct, and insufficient
emphasis on the organizational level of the environment (Ashkanasy et al., 2000).
Culture theory must bridge such gaps to explain firm performance because shared
values and assumptions are largely outside the scope of most business research (Asif,
2011; Glisson and James, 2002; Gregory et al., 2009; Richard et al., 2009; Schneider et al.,
2002).
In this paper, we shed light on these issues via three principal research questions.
First, if culture is a distinct construct, then how does it relate to an analogous
organizational construct such as climate? Second, what is the best empirical
composition of individual scores in culture research? Third, how does the intensity of a
culture affect its relations with firm outcomes? To engage these questions, we review
culture literature and develop and assess several hypothesized relations.
Firm culture in context
Culture helps explain firm performance despite a remarkable range of definitions for
the construct. Scholars universally agree that culture is something largely shared by
members. This characteristic makes it anthropological, historical, constructed socially,
stable, holistic, and nebulous (Hofstede, 2001; Rousseau, 1990). Culture includes shared
values inaccessible to direct observation but positively inferable from statements
(Levitin, 1973). Culture represents a pattern of evolved assumptions instilled in
members as the way to perceive organizational life (Schein, 1990). It is a collective
programming of the mind that distinguishes members of one organization from
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another based on shared values and norms in an organization (Hofstede, 2001; O’Reilly
and Chatman, 1996). Culture is also the shared beliefs and behavioral expectations of
an organizational unit (Barney, 1986; Cooke and Szumal, 1993; Denison, 1996; Glisson
and James, 2002). It is often the creation of the firm’s founders even before members
choose to adopt its values (Bass and Avolio, 1993, pp. 113-114). Though these
definitions are diverse, it is clear that culture is peculiar to a given organization and
somewhat inimitable. Its top-down values and shared assumptions are evident in
behavioral norms and common experiences of members.
What is the best way to infer shared values and assumptions in organizational
research? These elements of culture are tacit and practically invisible to members of
firms until those elements clash with conflicting elements, as they often do in a clash of
values during mergers and acquisitions (Lodorfos and Boateng, 2006; Schraeder and
Self, 2003). Along these lines, business scholars have long observed that members of
firms often have dual aspects that influence their behaviors: aspects germane to the
organization and other aspects germane to themselves (Barnard, 1938, p. 88). In this
sense, culture is a midwife of sorts to organizational behavior, that is, an element
uniquely necessary to explain a firm’s inimitable human side, such as organizational
citizenship behaviors and effective leadership (Appelbaum et al., 2004).
Dual aspects of person and context have long been seen part and parcel to culture.
As such, research tends to operationalize them via the aggregation of member-derived
scores (Kotter and Heskett, 1992). To parse organizational-based from member-based
variance in such data, studies have engaged the empirically knotty task of integrating
macro and micro-level data (Chan, 1998; House et al., 1995; Klein et al., 2001). The
integration makes empirical composition very important in culture studies (Dwyer
et al., 2003). Research on climate, an analogous construct, notes the same integration.
However, those studies emphasize attitudes and actions more than values and
assumptions (Cooper et al., 2001). As such, climate studies do not trace the elements
that are seen as definitional to culture (Asif, 2011; Glisson and James, 2002).
Yet, culture and climate overlap in organizational life. The former originates
top-down from upper echelons via artifacts and stories that ascribe meaning to shared
member experiences. The latter is instrumental to making sense of the same
phenomena, but only in terms of the effect of the organizational system on members
(Litwin and Stringer, 1968; Schneider, 1975). As such, climate is more bottom-up. In
this way, the two theoretic frames of culture and climate address the same elements
while being rooted in distinct but complementary paradigms.
The distinctiveness of culture
Culture influences sensemaking, collaboration, perspective-taking, and many
organizational actions (Weick, 1995; Zohar and Luria, 2004). It is often the best way
to explain inimitable firm actions such as innovation and adaptivity that frustrate
traditional approaches that assume a central tendencies and known distributions
(Naranjo-Valencia et al., 2011). Why is culture a deeper element of firms? One reason is
because early founder behaviors function as embedding mechanisms, and initially
form a set of cultural values (Bass and Avolio, 1993; Schein, 1990; Stinchcombe, 1965).
Indeed, in large firms undergoing change and in many entrepreneurial ventures, early
behaviors underlie the values and assumptions that emerge much later (Awasthy et al.,
2011; Sørensen, 2002).
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663
Such factors make culture a deeply rooted organizational element that can have
powerful effects. When environmental change strains operations, for instance,
culture can drive unique adaptations to sustain performance. Thus, although culture
is a stable part of can firm, it can enable adaptivity (Sørensen, 2002). Its
compounded nature helps signify what a firm values positively (and negatively).
Therefore, firm culture can promote robustness to environmental upheaval just as it
can drive discontinuous firm action amidst stable environments (Lorsch, 1986;
Polzer, 2004).
Whereas culture forms top-down, climates tend to form bottom-up from
relationships among members in response to external events (Glick, 1985; Schneider,
2000). As such, a culture may not always align with actual experiences. Indeed, it can
clash with them. That is how culture conveys a sense of “what should be done” versus
“what is done” in an organization. Culture is thus ideational in terms of its perspective
on organizational life and thereby it drives more proactive organizational behaviors.
By contrast, a climate perspective is more phenomenal in terms of its perspective on
organizational events. It is more ephemeral and reactive by nature when compared to a
pure culture perspective on organizational life.
Culture and climate theory have long been described as overlapping but mutually
incomplete and complementary (Asif, 2011; Denison, 1996). However, the relations that
this mutual incompleteness and overlap have with questions of empirical method are
not often given much attention. Figure 1 depicts this relation, in which the overlap
resides at the meso level (House et al., 1995). In organizational units, this meso level
corresponds to the groups, teams, and departments that make up an organization
(Schein, 1990; Siehl and Martin, 1990).
The meso-level of analysis is suitable for empirical culture research that identifies
member shared values and relates them to firm outcomes. Such an approach is relevant
on practical grounds too, as different organizational units (e.g. marketing or
engineering functions; product or geographic divisions) almost always have different
leaders, structures, and operations in wholly different environments that generate, in
turn, categorically different performance ramifications.
Figure 1.
Culture and climate
theoretic frames
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Summary and hypothesis development
We intended to identify a particular type of culture known as adaptive and
constructive, and link it to specific firm performance outcomes at a meso-level of
analysis. We aimed to shed light on the conceptual nature of culture by undertaking
empirical composition of scores based directly on its theoretic and conceptual
foundations. This methodological approach enabled us to directly assess the
importance of culture intensity, which is the degree to which members share a culture
or subscribe to its values (Rousseau, 1990). An analogous construct in the climate
literature is known as strength (Schneider et al., 2002). In particular, we assessed
culture intensity’s effect on performance outcomes.
Adaptive and constructive cultures are based on shared values and assumptions
pertaining to positive regard of others, performing at high levels, taking risks, and
thinking in novel ways (Cooke and Rousseau, 1988). The behavioral norms stemming
from these shared values are cooperation among members and coordination among
organizational units, departments, and functions (Thompson and Luthans, 1990).
These behavioral norms facilitate effective organizational responses to environmental
change as well as correct organizational action in the absence of environmental cues.
Adaptive and constructive cultures thus drive performance, cooperation, and
coordination (Cooke and Szumal, 2000).
An adaptive and constructive culture also promotes a setting of quality interactions
and communication, initiative, planning, and the enablement of other members and
groups to perform. In firms, these behavioral norms increase the levels of cooperation
within units and coordination between units (Glisson and James, 2002).
Constructive cultures drive firm performance by promoting settings in which
members take initiative, solve problems, and work together. Challenging goals are
common for firms with constructive culture and members also tend to understand firm
operations. As such, the assumptions and the behaviors of a constructive culture are
germane to firm performance. Our first three hypotheses are based on these established
definitional aspects of constructive culture:
H1. Constructive culture increases cooperation within organizational units in
firms.
H2. Constructive culture increases coordination between organizational units in
firms.
H3. Constructive culture improves the performance of organizational units in
firms.
Culture intensity is a meso-level variable that goes beyond individual action and
reflects the ascribed nature of a culture’s values (Glisson and James, 2002). In other
words, intensity refers to common awareness and shared assumptions that are
different from the achieved nature of the behavioral norms associated with climate
because they are ascribed (Rousseau, 2000). The ascribed nature of culture values
implies positive or negative regard for various activities. The fact that such values are
shared by members implies a direct effect on meso-level outcomes. Our final two
hypotheses reflect this expectation concerning intensity.
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665
H4. Culture intensity increases cooperation within organizational units.
H5. Culture intensity increases coordination among organizational units.
Empirical composition of data
After developing the five hypotheses and before executing our empirical study, we
formulated the best way to operationalize intensity. We noted two important aspects of
culture theory vital to undertaking empirical research. First, the difference between
shared member perceptions and firm values calls for referent-shift composition of data.
Second, unit-level behavioral norms are reliably measurable. They also reflect values
and assumptions of a culture, which are not apparent to observers but only gleaned
through prolonged experience with them.
Because of the deeper nature of values and assumptions, aggregated individual
scores in culture research should observe referent-shift logic explicitly (Hofstede, 1995;
Glisson and James, 2002; Rousseau, 1990). This type of operationalization shifts the
reference point away from members and toward ascribed values and assumptions
reflected in Figure 1. In other words, for instance, survey items in such research do not
infer the member attitudes that are relevant to climate research. Instead, they indicate
whether the dominant logic of a firm assumes that its members tend to “be
spontaneous” or “fit the mold.” It treats culture as something of an organizational
personality, as it has long been regarded (Barnard, 1938; Cooke and Szumal, 2000;
Hofstede, 2001). That is why, by contrast, climate studies tend to use survey items such
as “I feel used up” or “People in our company use opportunities quickly to attain goals”
(Ashkanasy and Nicholson, 2003; Baer and Frese, 2003).
When data are captured via referent shift logic, the scores reflect more clearly the
values of a firm (Glisson and James, 2002). This operationalization helps ensure that
the data are amenable to the examination of culture theory in a way that follows
correctly from culture theory’s foundations. As we illustrate in what follows, our
method entailed data collection and a study procedure based on referent shift logic.
Method
Sample
Our study data included sample of 2,657 members of 302 organizational units from a
variety of firms. These data were collected to allow the ongoing assessment of the
validity and reliability of published organizational culture and performance measures.
This exceptionally large sample drew from a cross-section of industries and from firms
with specific departments, groups, and other meso level organizational units.
Procedure
The data collection procedure entailed administration of surveys to all members of the
firms in all organizational units and follow up structured interviews with all members.
Missing data and scores were negligible due to the nature of the procedure;
endorsement of the procedure and local support by the firms and the units allowed us
to maximize the response rate.
Measures
The Organizational Culture Inventory (OCI: Cooke and Lafferty, 1987) includes 120
items that measure lower-order and higher-order cultural values. The measure has
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been used to forecast firm outcomes in many research studies (Cooke and Rousseau,
1988; Draper et al., 1989; Xenikou and Furnham, 1996). Participant scores based on the
40-item OCI constructive scales of humanistic, affiliative, achievement, and
self-actualization are aggregated at the meso-level for unit-level scores (House et al.
1995; Glisson and James, 2002). The items capture member endorsements of explicit
references to assumptions and values of their firm, producing a referent shift away
from the member and toward the organization (Cooke and Szumal, 1993).
The OCI items are similar to an adjective checklist and scored on a five-point
Likert-type scale ranging from 1 (not at all) to 5 (to a very great extent). The items
explicitly instruct respondents to indicate the extent to which the firm values and
expects certain behaviors, such as setting challenging yet realistic goals and taking on
new and interesting tasks.
We used another instrument to sample performance data, the Organizational
Effectiveness Inventory (OEI: Cooke, 1995) to measure individual, group, and
firm-level performance outcomes. Its 128 items assess quality, coordination,
cooperation, external adaptability, role conflict, job satisfaction, and turnover
intention. This instrument uses a variety of five-point Likert-type scales and includes
reversed-scored items to control for response biases. We utilized the OEI to delineate
meso-level firm outcomes of cooperation, coordination, and performance.
Cooperation was assessed by items targeting member interactions within units such
as “you can count on your co-workers when teamwork is needed.” Coordination across
units was measured by items such as “your workgroup can rely on other departments
to provide you with what you need – when you need it”. Performance was measured
via items such as “do you believe the quality of your organization’s products/services
meets customer expectations?” Response options for all items were situated in a
Likert-type scale that ranged from 1 (disagree) to 5 (agree).
Structured interviews
We rounded out the empirical sample via another method as a third source of data.
We undertook structured interviews to ensure fuller assessment of the targeted
variables. The structured interviews assessed the construct validity of the
self-report measures. Members reflected on the outcomes pertaining to their units.
For instance, interviewers assessed the degree to which unit members compete
versus cooperate in light of their OEI scores. Structured interview questions
pertaining to coordination called for interviewees to comment on the frequency of
incompatible requests or incongruent messages between units. Performance
questions addressed whether interviewees would choose to do business with their
unit and whether its offerings exceeded internal or external client expectations. The
structured interview scores were coded identically to the self-report scales, described
above, to allow direct comparisons.
Results
We first undertook descriptive analyses to assess data quality and fitness for
undertaking main analyses to examine our hypotheses. We found that the distribution
of unit membership was mildly skewed positive but roughly normal (skewness
index ¼0:77). We also found the median unit size to be nine members with a range of
three to 24. The average unit size was 8.8 with a standard deviation of 2.55.
Firm culture and
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From these initial examinations, we structured all of our analyses in terms of two
basic phases to carefully ensure the data did not violate analysis assumptions (Cook
and Campbell, 1979; Sirotnik, 1980). The first phase entailed descriptive statistics,
variable intercorrelations, and within and between unit analyses to warrant the
aggregation of scores. After an examination and assessment of those initial
examinations, we then moved into the second phase, in which we undertook the main
analyses of relations in order to assess our hypotheses.
Descriptive analyses
Table I presents frequency counts and percentages for the demographic variables. The
demographic items on the self-report measures suffered moderate missing data in 477
cases (18 percent of the sample).
Frequency Percentage
Gender Male 1,235 46.5
Female 1,013 38.1
No response 409 15.4
Age Under 20 17 0.6
20-29 521 19.6
30-39 802 30.2
40-49 635 23.9
50-59 291 11.0
60 or over 39 1.5
No response 352 13.2
Ethnicity Asian 73 2.7
African American 252 9.5
Hispanic 132 5.0
White 1,710 64.4
Other 39 1.5
No response 451 17.0
Education High School 201 7.6
Some College 471 17.7
Associates Degree 229 8.6
Bachelors Degree 708 26.6
Some Graduate Work 318 12.0
Masters Degree 332 12.5
Doctoral Degree 44 1.7
Other 17 0.6
No response 337 12.7
Annual salary $10,000 or less 83 3.1
$10,001 to $18,000 140 5.3
$18,001 to $25,000 326 12.3
$25,001 to $35,000 437 16.4
$35,001 to $45,000 384 14.5
$45,001 to $60,000 235 8.8
$60,001 to $75,000 109 4.1
$75,001 or more 108 4.1
No response 835 31.4
Note: n¼2,657
Table I.
Member-level frequencies
for demographic
variables
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Table II shows member-level correlations between the structured interview scores and
the outcome variables (cooperation, coordination, and unit performance). A negligible
percentage of data were missing from the structured interviews due to procedural
reasons. As shown in Table II, the outcome variables shared the strongest relations
with corresponding structured interview dimensions, thus offering validity evidence
for cooperation, coordination, and performance scores.
We executed the r
wg
procedure to assess agreement among members to warrant
aggregation to unit level scores ( James et al., 1993). The r
wg
values for culture, cooperation,
and coordination for all units ranged from 0.72 to 0.97, with an average between 0.81 and
0.88. We also examined between-unit differences using the intra-class correlation
coefficient (ICC). The ICC (type 1) estimates the proportion of total between-group variance
based on random intercepts. Estimates are generally 0.20 or lower (Bliese, 2000).
In our sample, the ICC estimates for between-unit differences in conjunction with the
r
wg
estimates for within-unit similarities indicated meaningful score composition as
unit-level membership explained significant total variance. Table III shows the ranges
and averages of these r
wg
coefficients and the ICC estimates.
Table IV presents unit-level descriptive statistics, intercorrelations, and scale
reliabilities. These results are highly consistent with past research (Cooke and Szumal,
r
wg
ICC (95% confidence)
Min Max Mean Lower Upper Coefficient
Constructive culture 0.730 0.910 0.830 0.211 0.275 0.241
Cooperation 0.750 0.970 0.880 0.056 0.165 0.107
Coordination 0.720 0.940 0.810 0.147 0.231 0.186
Note: n¼302
Table III.
Within-group consistency
and between-group
analysis for
Mean SD 1 2 3 4 5
1 Constructive culture 3.56 0.32 0.92
2 Culture intensity 0.57 0.18 20.41 n/a
3 Cooperation 3.50 0.23 0.19 20.19 0.84
4 Coordination 3.08 0.51 0.50 20.30 0.24 0.80
5 Unit performance 4.14 0.47 0.50 20.27 0.39 0.59 0.90
Notes: All correlations significant at p,0:01; reliabilities appear italicised along the diagonal;
n¼302
Table IV.
Unit-level descriptives,
intercorrelations, and
scale reliabilities
Structured interviews
Cooperation (n¼2,298) Coordination (n¼2,350) Unit performance (n¼2,301)
Cooperation 0.197 *20.072 0.143 *
Coordination 0.302 ** 0.135
Unit performance 0.243 **
Notes: *Significant at p,0:05; ** significant at p,0:01
Table II.
Quantitative measure and
structured interview
correlations
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2000; Glisson and James, 2002). Finally, we modeled the statistical operationalization of
intensity after the operationalization of strength in climate research, which uses the
inverse of the standard deviations of scores within units (Schneider et al., 2002).
Main analyses
Figure 2 presents structural and measurement models used to assess H1,H2, and H3
with standardized parameter estimates (
b
) and factor loadings for multiple indicators.
We used structural equation modeling (SEM) to assess relations between unit-level
culture, cooperation, coordination, and performance. The unit-level distributions were
mean-centered and approximated multivariate normality. We also estimated
non-causal relations between cooperation, coordination, and performance.
We obtained an
x
2=df ratio (125.2/71) of 1.76 to indicate that the model reflected the
sample data (Byrne, 1998; Carmines and McIver, 1981; Marsh and Hocevar, 1985). The
model explained 93 percent of the total variance while assessing hypothesized
relations. The average factor loadings of the measurement model were 0.87 for culture
and unit performance; 0.77 for cooperation, and 0.76 for coordination.
Table V reports several indices to facilitate thorough evaluation of model fit and
several indices that help detect index bias. For example, root mean square residual
estimates are sensitive to specified factor covariance structure, whereas estimates of
root mean square error of approximation are sensitive to specified factor loadings (Hu
and Bentler, 1999). In light of our examinations of all these indices, the observed model
fit was clearly acceptable based on conventional criteria (Byrne, 1998).
Table VI reports the
b
weights for relations between culture and outcomes in terms
of unstandardized parameter estimates and standard errors. All estimates were
Figure 2.
Structural and
measurement models with
standardized parameter
estimates
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significant at p,0:001 except for culture’s relation with coordination (p¼0:015). The
correlation between coordination and performance was not significant (p¼0:03)
whereas the correlation between cooperation and performance was significant
(p¼,0:001). These results provide support for H1,H2, and H3.
We executed a hierarchical regression analysis to assess the effects of culture
intensity concurrently as a main effect and a moderator. While undertaking these
analyses we observed standard criteria for tests of moderation (Baron and Kenny,
1986). At the first step, DR
2
results replicated the culture effects on outcomes obtained
in the SEM analysis. At the second step, intensity exhibited a main effect on
cooperation and coordination, thus providing support for H4 and H5.
The final step of our hierarchical regression for the interaction term did not explain
significant incremental variance (DR2.0:05). Though certainly not a hypothesized
effect, such a null finding is congruent with the theoretically-derived expectation that
intensity is not a significant moderator of relations between culture and form
outcomes. Table VII summarizes these results.
Outcome ßSE
Constructive culture Cooperation 0.482 ** 0.086
Coordination 0.285 *0.122
Performance 0.525 ** 0.096
Notes: *significant at p,0:05; ** significant at p,0:01; N¼274
Table VI.
Unstandardized
parameter estimates and
standard errors
DR
2
Incremental Fp
Cooperation M 0.146 51.37
a
,0.01
SD 0.018 6.54
b
,0.01
Interaction 0.007 2.38
c
ns
Coordination M 0.249 99.62
a
,0.01
SD 0.010 3.98
b
,0.05
Interaction 0.003 1.35
c
ns
Performance M 0.246 97.62
a
,0.01
SD 0.004 1.74
b
ns
Interaction 0.004 1.46
c
ns
Notes:
a
df ¼1, 300;
b
df ¼1, 299;
c
df ¼1, 298; N¼302
Table VII.
Hierarchical regression of
performance outcomes on
culture
Goodness of fit index 0.931
Adjusted goodness of fit index 0.912
Standardized root mean square residual 0.011
Root mean square error of approximation 0.053
Normed fit index 0.950
Non-normed fit index 0.971
Comparative fit index 0.978
Incremental fit index 0.978
Notes: n¼274; df ¼71
Table V.
Unit-level model fit
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As Table II and Figure 2 both show, the results of the structured interviews matched
the main analysis with respect to a cooperation and performance linkage. These data
provide such evidence of construct validity in our study, to be sure, but they also
provided uniquely valuable insights into the effects and limits of firm culture. For
example, respondents not only provided answers that reflected the OCI and OEI scores
for their organizational units, but they did so in ways particular to their organizational
units. Our introduction cited the vital importance of qualitative data to culture research
and we argued for it on conceptual and theoretical grounds. Here in our findings, the
structured interview results exemplify this importance empirically in ways that formal
analyses cannot. Whereas our rigorous quantitative approach delineated the essence of
constructs by parsing true score and error variances, those findings lack capacity for
capturing the particular natures of the firms being examined.
Cooperation and coordination were expressed in different ways depending on the
context and, moreover, they related to performance in unique ways, too. For example,
one case’s structured interviews expressed cooperation in the usage of shared shop
equipment when OEI cooperation was high, for instance. Respondents explained how
and why cooperation mattered to performance of their particular firm. In this case, it
was because cooperation and sharing shop equipment relates directly to the filling of
product orders on time for clients.
Similarly, in service firms in our sample, the coordination between marketing and
accounting and finance functions is important because some creative solutions
undertaken by the marketing unit (e.g. purchased materials, software programs) are
unduly expensive for one time usage. For example, in one case, a firm with low
coordination scores pursued such solutions, clearly reflecting a non-constructive
culture. In line with our quantitative findings, the action did not affect performance
because the client received the deliverable. However, the lack of coordination between
marketing unit and other units was seen as a function of the firm’s culture and,
although it did affect cooperation within the specific units, there was a clear
coordination and culture linkage to put it in context.
These kinds of rich results and observations require some interpretation by
researchers, which we provide in the next section. Yet, as objective results, these
qualitative data and findings gave us a stronger and clearer perspective on construct
validity. They made theoretically expected relations apparent to us in ways that would
be impossible to appreciate if our research was solely quantitative.
Discussion
Our findings supplement the understanding of firm culture in several ways that build
on existing research and theory. Our results show that constructive culture raises
levels of member cooperation within organizational units, levels of coordination
between those units, and unit-level performance. In particular, the SEM results
replicate past research on those relations using a large and heterogeneous sample of
firms. Our study also contributes some extensions to past work. The hierarchical
regression results, for instance, clarify the role of intensity in a way that is distinct to
culture theory, as intensity yielded a main effect on cooperation and coordination. By
contrast, climate strength, an analog of culture intensity, has been found to moderate
such relations in climate studies (e.g. Schneider et al., 2002).
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Our study contributes to distinct definitions of firm culture (Glisson and James,
2002). For example, cultural assumptions can be very subtle if members are not queried
about them in an appropriate way (Mehri, 2005). Variance attributable to culture can
therefore be attenuated if survey measures do not carefully compose those data
(Saffold, 1988). Our study builds on these peculiar aspects of culture research in the
hope that future research will continue to distinguish firm culture as a construct with
appropriate empirical methods and not generate confusion by confounding it with
analogous constructs such as climate (Ashkanasy, 2003).
Our research shows that ideational aspects are vital to culture and share a
complementary relation with the phenomenal aspects of climate, as shown in Figure 1.
This complementarity, long cited in culture and climate studies, generates theoretically
derived ramifications for empirical research. The effects of a culture’s values on
behavior are less immediate than the effects of climate-driven reactions to external
events. Culture conveys essential ideals that are nascent only via sustained shared
experiences. These day-to-day experiences of members are “low-fidelity” reflections of
a firm’s culture, and remain low in immediacy without specific references to the values
and assumptions. Those specific references to culture often come from the firm’s
leadership or members with significant firm experience. By contrast, specific
references to a climate can come from almost any member in a firm. This theoretic
contrast matters to operationalizing and integrating empirical data. That is, as we
illustrated in this study, culture research should explicitly incorporate a referent shift
at the item-level.
The meso-level of an organization has dual acquaintance with ideational values and
shared member experiences. Our study utilized this level of analysis on purpose, in
order to best capture a referent-shift. Where the dominant unit of analysis the
individual or the macro-level organization itself, referent shift operationalization would
have masked important differences across units that matter to today’s firms.
As an aside, it is worth acknowledging here that shared culture perceptions have
long been referred to as “intensity” (Rousseau, 1990). That term is more appropriate
and distinct to culture theory. “Strength” is a common statistical term anyway, as it is
so commonly used to refer to other phenomena, such as the strength of an effect or a
relationship, which can create confusion. Moreover, intensity appears to indicate
something substantially different than strength. To wit, our findings provide evidence
that it is a functional variable with main effects on firm outcomes.
As we examined intensity’s linkages with culture, cooperation, coordination, and
performance, we found that it relates directly to cooperation and coordination, but not
performance. We did not find intensity to moderate any relations between culture and
outcomes. We posit on theoretic and empirical grounds that culture intensity influences
firm outcomes directly, not interactively. This finding clarifies the effects and limits of
culture intensity as it helps distinguish it from climate strength.
Our findings regarding culture intensity shed light on firm relations with the
external environment. That is, external conditions can and do influence internal
operations and firm performance. However, when a firm culture is intensely held by an
organization’s members, the culture itself can begin to substitute for the external
environment from the perspective of members. Of course, the quality of the interface
between firm culture and external culture is important to this dynamic. Our
observations when presenting our results, concerning the value of qualitative data in
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673
culture research, are vital to this consideration. Firm culture is deeply rooted and
inimitable; it is particular to a given firm based on that firm’s unique structures,
strategies, and other organizational elements. To delineate its interface with the
external environment, we argue strongly for culture research to always include
qualitative data as a useful means to round out any findings based on quantitative
data. Indeed, every firm may be unique, but so are every firm’s competitors, customers,
and the myriad other factors that compose a given firm’s environment and situation.
Finally, our study also offers some practical implications for managers in
organizations. Of course, managers and leaders already use healthy cultures to
promote cooperation and coordination. However, we show that shared perceptions of
culture directly affect cooperation and coordination. Managers and leaders may find it
useful to frequently refer to their firm’s culture. It is not only management decisions
that can reflect and promote a firm’s values, but also the maximization of awareness
and the cultivation of shared perceptions through communication between leaders and
members.
Implications and future research
Our study clarifies theoretic boundaries of firm culture and the effects and limits of
intensity as an antecedent of cooperation, coordination, and performance. Our findings
offer insights into how to utilize culture in as a strategic weapon in organizational
settings. For practicing managers, such insights clarify what focus to on during times
of uncertainty. For instance, the shared values that define firm culture can add
meaning to member activities undertaken as they perform their jobs. Managers that
routinely express those cultural values when communicating with members reinforce
the shared and clarify the meaning of member experiences. An intense firm culture can
thus account for the difference between an organizational unit that stays cohesive and
focused versus one that fractures when the external environment shifts. From a
strategic management perspective, the fact that culture intensity tends to have a direct
effect on cooperation and coordination has clear practical implications. For one, it can
help a firm weather periods of upheaval. But just as well, it can help a leader justify a
needed strategic pivot when there is not a clear environmental reason for one.
Given that culture associates mostly with unit-level outcomes, a focus on the
meso-level helps delineate linkages with other organizational elements. These
delineations can help direct managerial attention amidst uncertainty. Such
implications hold promise for elaborating the role of culture and delineating its
linkages with performance. The findings of such future research may help explain why
some kinds of structures align with certain kinds of cultures. Future research will also
delineate how culture drives performance only if combined with certain strategies. For
example, variables of structure (e.g. degree of hierarchy) or strategic purpose
(e.g. growth orientation) may yield joint effects on the relation between culture and
performance that are traceable at organizational and meso levels, but not micro or
macro levels.
Culture research ought to operationalize culture in ways that do not rely on post hoc
aggregation of scores, but instead on careful reference to firm assumptions as being
distinct from pure member perceptions in order to achieve a clear referent shift. For
instance, members could discuss culture values in a referent shift contexts before
completing a culture measure collaboratively to develop a truer unit score. Such an
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innovative approach would blend qualitative and quantitative data, thus sharpening
generalizability with heuristic depth. It would also better reflect the rigor of the
anthropological research that is basic to culture theory, which we reviewed in the
introduction. Such methods could control for level of agreement with greater fidelity
than conventional operationalizations of intensity. Reflecting the logic of Figure 1, such
research would support the development of hybrid models of firm countercultures in
which shared experiences drive emergent norms that rebound against a firm’s strategy
or structure. The studies would also enjoy the affordances of specifically noting
organizational level or positional longevity of members, as those variables account for
better appreciation of the evolutionary aspects of a firm’s culture.
As noted in the introduction to this paper, our findings suggest implications for the
importance of linkages between the external environment and the internal works and
performance of firms and the organizational units within them. Like a firm itself, a
culture is not divorced from the larger context in which it is embedded. In our study,
these linkages were most apparent via the structured interview data, which allowed
participants to describe particular actions and elements in specific terms. Such
descriptions include external elements, like customers and competitors, which make a
firm and its context distinct and unique.
Some characteristics of our sample enabled us to avoid certain methodological
issues. For instance, the noted turbulence of culture relations with unit-level outcomes
is liable to frustrate results based on small samples (Sørensen, 2002). Our study sample
was large. We undertook multivariate methods, combined with our large sample, to
mitigate random and systematic error variances. Our SEM approach utilized multiple
indicators to allow examination of the structural model while parsing out method
variance via the measurement model. However, aspects of our study warrant some
caution when interpreting our findings. A cross-sectional research design is less fitting
than a true longitudinal one that allows better detection of causality. Such studies are
appropriate for culture research, as they take larger stock of a firm’s novel values.
Multiple measurement points offer greater empirical fidelity and they also help
determine if variable interrelations are stable across time. Finally, a cross-sectional
research design is not very robust to spuriousness, which may have been a factor in the
results for the performance outcomes in our study. We sought to mitigate such sources
of error with a large heterogeneous mix of firms and organizational units in our
sample. We intend for our contribution to fuel distinct new questions and lines of
inquiry in culture research and theory.
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About the authors
Patrick J. Murphy is Associate Professor, Driehaus College of Business, DePaul University, and
Chair of the Management History Division of the Academy of Management. Patrick J. Murphy is
the corresponding author and can be contacted at: profpjm@gmail.com
Robert A. Cooke is Associate Professor Emeritus, Liautaud College of Business, University of
Illinois at Chicago. He is co-founder and CEO of Human Synergistics.
Yvette Lopez is Assistant Professor, Driehaus College of Business, DePaul University.
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