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Entrepreneurial Drive in the Top Management Team: Effects on Strategic Choice and Firm Performance

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Based on upper echelons theory and the logic embodied in the entrepreneurship, strategic choice, and resource-based view literatures, a theoretical model was developed showing the relationships between top management teams’ (TMT) entrepreneurial drive, TMT strategic choices, and superior industry performance, from which testable hypotheses were formed. The authors used a strategic management simulation model to gather the requisite data to perform their empirical testing. The results strongly support the hypotheses that TMT entrepreneurial drive is positively associated with superior industry performance and that the entrepreneurial orientation of the TMT’s strategic choices is positively associated with superior industry performance.This study also found evidence that the relationship between TMT entrepreneurial drive and superior industry performance is moderated by TMT’s strategic choices. These results have important implications in terms of how TMT’s entrepreneurial drive and their strategy choices can affect firm performance in today’s hypercompetitive environment.
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Matthew S. Wood and Michael D. Michalisin
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Entrepreneurial Drive in the Top
Management Team: Effects on Strategic
Choice and Firm Performance
Matthew S. Wood
1
and Michael D. Michalisin
2
Abstract
Based on upper echelons theory and the logic embodied in the entrepreneurship, strategic choice, and resource-based
view literatures, a theoretical model was developed showing the relationships between top management teams’ (TMT)
entrepreneurial drive, TMT strategic choices, and superior industry performance, from which testable hypotheses were
formed. The authors used a strategic management simulation model to gather the requisite data to perform their empirical
testing. The results strongly support the hypotheses that TMT entrepreneurial drive is positively associated with superior
industry performance and that the entrepreneurial orientation of the TMT’s strategic choices is positively associated with
superior industry performance. This study also found evidence that the relationship between TMT entrepreneurial drive and
superior industry performance is moderated by TMT’s strategic choices. These results have important implications in terms
of how TMT’s entrepreneurial drive and their strategy choices can affect firm performance in today’s hypercompetitive
environment.
Keywords
entrepreneurship, strategic choice, performance, upper echelons theory, management team
Introduction
The entrepreneurial capability to develop and/or refine new
products and services is essential to firms’ survival and
prosperity in today’s fast-cycle markets. As a result, entre-
preneurship has become a growing research stream within
the field of strategic management, as evidenced by the
increasing number of special issues and forums on entrepre-
neurship in existing management journals as well as the
increasing number of journals specializing in entrepre-
neurship. Of considerable interest in this literature is the
relationship between the firm’s entrepreneurial orientation,
strategy, and resultant performance outcomes (e.g., Wiklund,
1998; Wiklund & Shepherd, 2003).
Some theorists suggest that the degree of entrepreneurial
behavior inherent in firm strategy varies along a continuum
from conservative to entrepreneurial, as labeled by Miller
and Friesen (1982), or from administrative focus (trustee) to
entrepreneurial focused (promoter) as posited by Stevenson
and Jarillo (1990). Empirical research also indicates that
organizational outcomes vary depending on the entrepre-
neurial nature of the firm’s strategy. For example, research
has shown that the firm’s with more entrepreneurial-oriented
strategies have higher levels of growth than firms with less
entrepreneurial-oriented strategies (e.g., Covin, 1991; Miller
& Friesen, 1982), suggesting that firms pursuing a growth
initiative would be better managed by individuals possessing
a relatively high level of drive toward entrepreneurial
behavior often referred to asentrepreneurial drive”
(Armstrong & Hird, 2009; J. C. Carland, Carland, & Stewart,
1996; W. H. Stewart, Carland, Carland, Watson, & Sweo,
2003). The latter point emphasizes “individuals” because
entrepreneurial drive has traditionally been thought of as an
individual-level characteristic associated with specific per-
sonality characteristics (J. W. Carland, Carland, & Ensley,
2001). J. W. Carland et al. have described entrepreneurial
drive as the outcome of a nexus of personality factors,
including the need for achievement, the propensity for risk
taking, the preference for innovation, and a high need for
cognition; wherein, differential levels of these personality
factors combine to affect an individual’s entrepreneurial
drive.
1
University of North Carolina–Wilmington, Wilmington, NC, USA
2
Southern Illinois University at Carbondale, Carbondale, IL, USA
Corresponding Author:
Matthew S. Wood, Department of Management, Cameron School of
Business, University of North Carolina–Wilmington, Wilmington, NC
28403-5969, USA
Email: woodms@uncw.edu
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Wood and Michalisin 223
Although there is substantial research on the role of
individual level characteristics and the recognition of oppor-
tunities and the process of new venture creation (e.g.,
Brockhaus & Horwitz, 1986; Katz & Gartner, 1988; Shane,
2003) and research on the influence of team characteristics
on the creation of new ventures (e.g., G. Chandler, Honig,
& Wiklund, 2005; Fiet & Busenitz, 1997; Gartner, Shaver,
Gatewood, & Katz, 1994), less attention has been paid to
how the individual characteristics of multiple team mem-
bers combine to affect the firms strategic orientation and
firm performance in more established firms. This research
seeks to fill this gap by considering entrepreneurial drive
as an individual characteristic that becomes a collective
orientation for the top management team. We then explore
the idea that the collective entrepreneurial drive of the top
management team affects their strategic choices and ulti-
mately impacts the firm’s financial performance relative to
competitors.
If entrepreneurial drive is an individual-level trait inher-
ent in TMT members, affecting their strategic choices and
resultant firm outcomes, then entrepreneurial drive argu-
ably falls within the logical framework of the upper echelons
theory (UET). UETs main prescription is that characteristics
of the firm’s top management team (e.g., tenure, functional
background, and education) are a key driver in the formula-
tion of the firm’s competitive strategy (Hambrick & Mason,
1984) that affects organizational outcomes. Hambrick and
Mason (1984), founders of UET, contend that the collective
characteristics of the top management team (TMT) are better
predictors of organizational outcomes than those of any
single TMT executive because the leadership and strategic
decision making of a complex organization is a shared activ-
ity, based on the collective experiences, capabilities, and
cognitions of the entire TMT (Hambrick, 2007). That is why
UET proponents propound that the collective characteristics
of executives are a viable valid proxy for the cognitive
framework of the TMT. Indeed, TMT functional experience,
industry and firm tenures, and educational background have
all been associated with predictions of strategic decisions,
lending support to UET’s main prescription (Boeker, 1997;
D’Aveni, 1990; Eisenhardt & Schoonhoven, 1990). Thus, if
the cognitive framework of the TMT is a key driver of stra-
tegic decision making and resulting firm outcomes, then the
collective entrepreneurial drive of the TMT is likely an
important predictor within the UET framework.
Because strategic decision making is grounded in the
strategic choice literature, TMT entrepreneurial drive
(TMTED) has implications to this literature stream as well.
Specifically, we contend that TMT’s collective propensity
to engage in entrepreneurial behavior can result in strategic
choices ranging from highly conservative to highly entre-
preneurial (Eisenhardt & Schoonhoven, 1990; Finkelstein
& Hambrick, 1996; Miles & Snow, 1978). Thus, the greater
the TMT’s entrepreneurial drive, the greater the likelihood
that they will make strategic choices that are more entrepre-
neurial in nature (J. W. Carland et al., 2001). The logic
behind the strategic fit literature suggests that the greater
the fit between the TMT’s entrepreneurial propensity and
the entrepreneurial nature of their strategic choices would
result in higher relative firm performance
1
than when stra-
tegic fit between the TMT’s entrepreneurial propensity and
the entrepreneurial nature of their strategic choices is lack-
ing (e.g., Chakravarthy, 1986; Donaldson, 1987; Sorge,
1991; Venkatraman & Prescott, 1990).
Based on the literatures discussed above, and the previ-
ously identified research gap, the current research seeks to
addresses the following research question: What is the rela-
tionship between TMT entrepreneurial drive, strategic
decision making, and relative firm performance? To address
a research question encompassing multiple relationships
between multiple constructs, we decomposed it into a series
of research subquestions: Does TMT entrepreneurial drive
have a direct association with superior industry returns?
Does TMT’s choice of a more entrepreneurial strategy
result in higher levels of performance? Is the relationship
between the TMT’s entrepreneurial drive and superior
industry returns mediated by the firm’s choice of strategy?
Or is the relationship between the TMT’s entrepreneurial
drive and superior industry returns moderated by the firm’s
choice of strategy, such that high levels of TMT entrepre-
neurial drive will result in higher levels of performance
when more entrepreneurial strategies are implemented?
Our research explores these research questions by drawing
on the upper echelons, entrepreneurship, strategic choice,
and resource-based view literatures for insights into the con-
structs and relationships among the constructs stated in the
research questions. The logic embodied in these literatures
was then used to develop an integrative theoretical model of
the relationships between TMT entrepreneurial drive, TMT
strategic choices, and relative firm performance, from which
testable hypotheses were formed. Second, following Ham-
brick’s (2007) recent suggestion that business simulations
may be a valuable tool for empirically testing upper echelon
based models, we describe how we empirically tested the
theoretical model and hypotheses using longitudinal data
from a relatively large sample of TMT’s managing mock
firms using Airline, a strategic decision-making simulation
model. We then present the empirical results, which strongly
support our hypotheses. Finally, we discuss the contributions
of our research within the context of the broader literature,
present possible avenues of future research, and discuss the
limitations of the study.
Theoretical Framework
Joseph Schumpeters (1934) original conceptualization of
the entrepreneur primarily focused on the role of the indi-
vidual as the driver of innovation. Yet, over time, there has
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224 Journal of Leadership & Organizational Studies 17(3)
been growing consensus that entrepreneurship occurs
throughout existing organizations as employees collectively
leverage their knowledge and innovativeness in helping the
firm become more efficient and effective in meeting chang-
ing customer requirements and recognizing new profitable
market opportunities (e.g., Covin, 1991; Holt, Rutherford,
& Clohessy, 2007; Lumpkin & Lichtenstein, 2005; Mises,
1949). Such entrepreneurial individuals are valuable parts
of diverse organizational systems that can be reconfigured
in a novel ways as contexts change in developing new and/
or refining existing products and processes (Miller, 1983;
Mises, 1949). Zahra, Jennings, and Kuratko (1999) asserted
that entrepreneurial activities drive new product and pro-
cess innovations, and strategic renewal at multiple levels
of the firm (corporate, divisional, and functional) in an
effort to improve overall organizational performance.
Entrepreneurial activity can lead to new venture forma-
tions within existing organizations or can significantly
transform organizations through a variety of entrepreneur-
ial initiatives (Guth & Ginsberg, 1990). Finally, Mintzberg
(1973) posits that the dominant goal of the organization
operating in the entrepreneurial mode is growth and
growth requires the entrepreneurial actions of enterpris-
ing leadership. Collectively, these perspectives point to
the advantages, for growth-minded firms, of adopting an
entrepreneurial focus at the firm level.
Entrepreneurial Top Management Teams
Several studies have shown that using executive groups as
the unit of analysis, rather than individuals, has provided
researchers with a better understanding of organizational
outcomes (e.g., Bantel & Jackson, 1989; Carpenter &
Fredrickson, 2001, Michalisin, Karau, & Tangpong,
2004) and processes (Eisenhardt & Bourgeois, 1988;
Simons, Pelled, & Smith, 1999). Similarly, entrepreneur-
ship researchers have explored the role of entrepreneurial
teams in new venture performance (e.g., Ensley, Carland,
& Carland, 2000; Gartner et al., 1994; Kamm, Shuman,
Seeger, & Nurick, 1990). J. W. Carland et al. (2001, p. 57)
point out that Gartner, Bird, and Starr (1992) admit that
“entrepreneurial firms differ in the manner by which team
level behaviors affect organizational outcomes, such as
strategy and performance, and the same may be said for the
individuals who make up the team and the roles which they
play.” Miller and Friesen (1982), Bygrave (1989a, 1989b),
and Gartner et al. (1992) all demonstrate that entrepreneur-
ial firms are radically different in their strategic posture.
More specifically, entrepreneurial firms proactively engage
their markets, are willing to take risk, and are innovative in
their solutions to market base needs (Miller, 1983). Fol-
lowing this body of literature, it is our perspective that the
source of at least part of the observed variation in strategic
decisions and performance outcomes is the differential
strength of entrepreneurial drive within the TMT (J. W.
Carland et al., 2001).
TMT research is most closely associated with Hambrick
and Mason’s (1984) seminal piece on UET. UET posits that
individual-level characteristics, such as age, tenure, and
functional background have heavy influences on the strate-
gic posture of the TMT which correlates with an identifiable
pattern of strategic decision making. Finkelstein and Ham-
brick (1996) argue that the life experiences and psychological
attributes of managers influence their view of the world
resulting in differential behavior among executives facing
similar circumstances. In support of these ideas, studies
have shown that TMT characteristics are a better predictor
of organizational outcomes than individual CEO traits alone
(e.g., Hambrick, 1994). However, it should be noted that
UET research has been criticized for its lack of emphasis on
additional characteristics, beyond basic demographics, that
may provide insight into the TMT–organizational outcome
relationship (Priem, Lyon, & Dess, 1999). Additionally,
UET research has been cited for its lack of focus on the
“black box” of intervening variables that exist between TMT
characteristics and organizational outcomes (K. Smith,
Olian, Sims, O’Bannon, & Scully, 1994). Although some
progress has been made (see Hambrick, 2007 for a commen-
tary), we are heedful of these critiques and the current study
adds to the UET literature by exploring the collective impact
of each TMT member’s propensity to engage in entrepre-
neurial behavior, referred to here as the manager’s level of
entrepreneurial drive. This study also explores the process of
strategic choice as a “black box” intervening variable. These
relationships are illustrated in Figure 1.
Entrepreneurial Drive and the TMT
Entrepreneurship researchers have long focused on indi-
vidual traits and personality characteristics as determinates
of entrepreneurial activity (e.g. Brockhaus, 1980; Gartner,
1989; Gupta & Bhawe, 2007; W. H. Stewart & Roth, 2007).
Much of this research suggests that there are stable personality
Strategic Choice
Upper Echelon
Characteristic of
Entrepreneurial Drive
(TMT Entrepreneurial Drive)
Defender Strategy
Prospector Strategy
Superior
Industry
Performance
RMNPS
RMEPS
Analyzer Strategy
Figure 1. Theoretical model
Note: RMEPS = relative mean earnings per share; RMNPS = relative
median net profit per seat; TMT = top management team.
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Wood and Michalisin 225
characteristics associated with those who act entrepreneur-
ially versus those who do not. For example, Stewart et al.
(1999) found that growth-oriented entrepreneurs were
higher in achievement motivation than were managers of
small business owners focused primarily on producing cur-
rent family income rather than growth. These researchers
also show that small business owners were not significantly
higher on achievement motivation than managers of existing
corporations. In a similar vein, J. W. Carland et al. (2001)
combined the literature on cognitive style and the literature
on entrepreneurial personality traits to conclude that the pur-
suit of entrepreneurial opportunity may be best understood
as the outcome of the individual’s level of “entrepreneurial
drive.” Entrepreneurial drive can be defined as the individu-
al’s propensity toward entrepreneurial behavior and is
thought to exist along a normally distributed continuum
(Armstrong & Hird, 2009; J. W. Carland et al., 2001). Thus,
individuals will fall somewhere along this distribution and
as the degree of entrepreneurial drive increases it is likely to
produce distinguishable differences in individual entrepre-
neurial behavior (Carland & Carland, 1992; Armstrong &
Hird, 2009).
In the context of UET, the individual level difference of
entrepreneurial drive may play a potentially influential role
in organizational outcomes (Armstrong & Hird, 2009). If
the TMT is composed of highly entrepreneurially driven
individuals, then the behavior of the organization is likely
to be very different than an organization lead by TMT
members who are less entrepreneurially driven. Moreover,
it has been shown in numerous studies that a firm’s entre-
preneurial orientation, meaning its propensity to be
innovative, be proactive, and take risks, is positively asso-
ciated with firm performance (e.g., Covin & Slevin, 1991,
Lumpkin & Dess, 2001; Wiklund, 1998). However, the
entrepreneurial orientation literature has been less explicit
as to how such an orientation may form within an organi-
zation (Rauch, Wiklund, Lumpkin, & Frese, 2009). We
suggest that one way in which this orientation may form is
via the collective entrepreneurial drive of the TMT. To be
conceptually clear, we acknowledge that the construct of
entrepreneurial drive is distinct, but closely related to the
concept of entrepreneurial orientation (Covin & Slevin,
1989). Entrepreneurial orientation and entrepreneurial drive
both speak to the propensity to engage in entrepreneurial
behavior, but entrepreneurial orientation occurs at the firm
level whereas entrepreneurial drive occurs at the individual
level. Although the relationship between these two con-
structs has not been made explicit in the literature, we
contend that entrepreneurial drive is likely an antecedent to
entrepreneurial orientation. Such theorizing is beyond the
scope of our research and we confine our study to explor-
ing the effects of entrepreneurial drive on strategic decision
making and firm performance as individuals come together
to form the TMT.
Because TMTs are responsible for formulating and
implementing the firms strategies (e.g., Hambrick & Mason,
1984) and thus have the power to control the direction and
performance of the firm, they are the most important influ-
ential team in the firm (K. Smith et al., 1994; Wernerfelt,
1989). Logic embodied in the resource-based view of the
firm (RBV) indicates that key intangible TMT resources can
be strategic assets to the firm (e.g., Carpenter, Sanders, &
Gregersen, 2001). Indeed, RBV research has shown that
various intangible resources associated with the TMT, such
as TMT member attraction (Michalisin, Karau, & Conrad,
2006) and TMT cohesion (Michalisin et al., 2004; Michel &
Hambrick, 1992; K. Smith et al., 1994) have been positively
associated with firm performance. We contend that TMT
entrepreneurial drive (TMTED)—defined as the collective
effect of the individual TMT members’ entrepreneurial
drive—also has the potential to operate as a strategic asset
and thus be a source of superior industry returns. Entrepre-
neurial drive is a gestalt characteristic (J. W. Carland et al.,
2001) that must be integrated and balanced with the level of
entrepreneurial drive present amongst other TMT members,
this balancing represents a convergence process that results
in a TMTED that is unique.
According to the RBV, strategic assets are resources that
are simultaneously valuable, rare, difficult and costly to
imitate, and nonsubstitutable (Amit & Schoemaker, 1993;
Barney, 1986, 1991; Peteraf, 1993). Resources are valuable
when they allow the firm to take advantage of opportunities
in the environment and/or thwart competitive threats. By
definition, TMTED is likely the motivational force compel-
ling TMTs to transform their ex ante insights about product
and market opportunities into actions aimed at gaining and
sustaining a competitive advantage. TMTED can promote
radical changes in technologies that undermine competitive
threats and provide the basis for first mover advantages.
TMTED is also rare and difficult and costly to imitate for
several reasons. First, a TMT members entrepreneurial
drive consists of a nexus of personality factors, including
the need for achievement, the propensity for risk taking, the
preference for innovation, and a high need for cognition.
The unique combination of these personality attributes
across members of the TMT makes TMTED a rare intangi-
ble resource to the firm. Moreover, these attributes coupled
with other unique attributes such as age, education, and
functional background of the TMT members makes TMTED
a potentially socially complex resource that is rare and
inimitable (Finkelstein & Hambrick, 1996). Second, TMTED
can develop and change over time and is affected by unique
historical conditions, making it rare and difficult to imitate
(Barney, 1991). Third, TMTED is an invisible resource,
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226 Journal of Leadership & Organizational Studies 17(3)
making it hard for competitors to replicate (Godfrey & Hill.
1995). Fourth, even if competitors are cognizant of a firm’s
TMTED, its impact on firm performance is often causally
ambiguous (Reed & DeFillippi, 1990). Fifth, attempting to
perfectly replicate another firm’s TMTED would require
hiring their entire TMT. Even if all TMT members agreed to
join the competitor, it may be very costly, and the TMTED
can be impaired by the new organizational context, includ-
ing a different corporate climate.
TMTED also appears to be imperfectly substitutable.
One may argue that greater emphasis on autonomous
strategic behavior, leveraging the innovativeness of firm
employees in developing new products and services
(Burgelman, 1983), can substitute for a lack of TMTED.
Yet successful corporate entrepreneurship based on auton-
omous strategic behavior requires senior managers to act
as product champions in clearing organizational obstacles,
so that the TMT will approve the requisite resources needed
to bring the new innovation to fruition (Certo, Moss, &
Short, 2009). Unfortunately, a TMT lacking entrepreneur-
ial drive may be less inclined to approve such funding than
a TMT with high entrepreneurial drive. Moreover, indi-
vidual TMT members with low entrepreneurial drive may
be less likely to champion important radical innovations
than TMT members with high entrepreneurial drive. Put dif-
ferently, although corporate entrepreneurship can be
effectuated through both induced strategic behavior, a top-
down process of promoting corporate entrepreneurship, and
autonomous strategic behavior, a bottom-up process of
promoting corporate entrepreneurship (Burgelman, 1983;
Ambos & Schegelmilch, 2007; Shepherd, McMullen, &
Jennings, 2007), autonomous strategic behavior is not a
perfect substitute for TMTED because the strategy and
structure crafted by a TMT low in entrepreneurial drive
will likely inhibit autonomous strategic behavior. In sum,
TMTED appears to possess all of the attributes of a strate-
gic asset, and thus, according to RBV, should be positively
associated with superior industry returns. This suggests the
following hypothesis:
Hypothesis 1: TMTED will be positively associated
with superior industry returns.
Strategic Choice
The strategic choice literature has a rich heritage and has
resulted in the development of many insightful perspectives.
Several streams of strategic choice research have converged
around the idea that strategy making varies along a contin-
uum, from conservative to entrepreneurial in orientation
(Miles & Snow, 1978; Miller & Friesen, 1982; Dess, Lumpkin,
& Covin, 1997; Mintzberg, 1973). In similar vein, the entre-
preneurial orientation literature suggests that firms may vary
substantially in the degree of risk taking, proactive behavior,
and innovativeness and that variation may be manifested in
the firm’s choice of strategy, often referred to as the firms
competitive aggressiveness (Dess & Lumpkin, 2005;
K. Smith, Ferrier, & Grimm, 2001). Firms with an aggres-
sive competitive orientation are willing to go head to head
with competitors via pricing battles or by leveraging the
innovative capabilities of the firm. In this way, an aggres-
sive competitive orientation may allow firm’s to “select a
strategy that ensures their advantage by capitalizing on new
technologies or serving new markets” (Dess & Lumpkin,
2005, p. 154).
The competitive orientation of the firm becomes important
because it is an influential determinate of firm performance
(K. Smith et al., 2001). For example, Covin (1991) found
that entrepreneurial strategies are correlated with higher
levels of firm growth. Brown, Davidson, and Wiklund
(2001) assert that firms with higher scores on entrepre-
neurial management dimensions are likely to exhibit more
entrepreneurial behavior in terms of resource recombina-
tions and entry into new market segments. Covin, Green,
and Slevin (2006) found that more entrepreneurial oriented
firms were more likely to experience greater sales growth
than less entrepreneurial focused firms. However, the key
mechanism by which entrepreneurial and competitive ori-
entation influence performance is through the firms choice
of strategy (Covin et al., 2006; Olsen, Parayitam, & Twigg,
2006; Roper, 1998; Hoskisson, Johnson, & Moesel, 1994).
Thus in our model, the TMT’s choice of strategy is antici-
pated to be a key variable affecting the relationship between
the TMTED and superior industry returns.
One of the more widely acknowledged typologies of stra-
tegic choice is the Miles and Snow (1978) typology. This
typology proposes that organizations develop lasting pat-
terns of strategic behavior that actively seek to coalign the
organization with its environment (Shortell & Zajac, 1990).
The organizational process of achieving alignment with the
environment results in three strategic domains: entrepre-
neurial, which relates to how the firm orients itself to the
market place; administrative, which focuses on how the firm
coordinates and implements its strategies; and technical,
which refers to the technology and processes the organiza-
tion employs to produce its goods and services. Each of
these strategic domains can be addressed in different ways,
resulting in Miles and Snow’s (1978) identification of three
distinct types of strategic postures: prospector, analyzer, and
defender.
2
The defender firm focuses on stability by attempting to
seal-off of a portion of the market. As such, defenders pro-
duce a limited set of products or services that are focused on
a narrow market segment and vigorously defend it from
competitive threats. Defenders are also prone to ignoring
developments outside their niche markets, choosing instead
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Wood and Michalisin 227
to grow by focusing on a single highly efficient core tech-
nology. The TMT of a defender organization is likely to
engage in little environmental opportunity scanning, instead
choosing to focus on internal issues of cost efficiency and
formal control mechanisms.
The prospector firm emphasizes innovation and flexibil-
ity in a continual attempt to be on the leading edge of new
product and service offerings. The prospector’s success
stems from its capability to identify and exploit new market
opportunities. These firms invest heavily in the capacity to
survey a wide variety of environmental conditions and
market trends. These firms are usually quite systematic in
their ongoing expansion into new products and markets,
while continually adjusting current market positions. The
goal of the prospector firm is to remain flexible and adapt-
able in order to quickly seize perceived market opportunities.
The TMT of a prospector firm is likely to focus on market-
ing, research and development, and environmental scanning
activities, whereas planning is broad and results driven. The
primary risk to the prospector firm is overextending their
resources in ways that undermine firm performance.
Miles and Snow (1978) assert that defender and prospec-
tor firms exist on two ends of a continuum of adjustment
strategies. Between these two extremes is the analyzer firm.
A true analyzer attempts to balance the minimization of risk
with maximization of opportunity seeking by maintaining
an efficient core set of products and customers, while simul-
taneously seeking out new market opportunities. This
balance is most often accomplished via imitation of new
products or markets that have been demonstrated successful
by prospector firms. In this way, the analyzer can grow
through a combination of new market development and
continued persistence in existing markets. The TMT of an
analyzer firm is likely to be focused on solving issues
related to the dual technical core paradox of simultaneously
achieving flexibility and efficiency. The balance required
for a successful analyzer strategy is inherently difficult to
achieve, and analyzers risk becoming inefficient and inef-
fective, resulting in poor performance.
The above typology provides a conceptual basis for dif-
ferentiating firms based on their patterns of strategic choice
over time. The choice of strategy is likely to be a key factor
in the returns experienced by the firm. For example,
McGrath (2001) informs us that tried and true strategies are
likely to lead to higher mean performance with less varia-
tion, while aggressive strategies may result in more
variation but higher overall profitability over extended time
periods. As such, we expect there to be a direct positive
relationship between the firm’s choice of strategy and firm
performance as reflected in the second hypothesis.
Hypothesis 2: The TMT’s choice of strategy will
be positively associated with superior industry
returns, such that selecting a more entrepreneurial
strategy (prospector) will result in higher levels of
industry returns than less entrepreneurial strate-
gies (analyzer or defender).
Moderating Role of Strategy
The first two hypotheses identify the relationships between
the TMTED and superior industry returns, and TMT’s choice
of strategy and superior industry returns, respectively. The
next logical question is whether there is an interactive effect
between the TMTED and the choice of strategy. As such,
we theoretically explore the idea that TMT’s choice of
strategy potentially mediates or moderates the relation-
ship between TMTED and superior industry returns. The
determination of the nature of moderating and mediating
relationships should be theory driven (Frazier, Tix, &
Barron, 2004). Yet, as detailed below, the theories used in
developing our conceptual model do not provide defini-
tive guidance as to whether strategic choice is likely to
mediate or moderate the relationship between TMTED and
superior industry returns. Thus, we use existing theory to
explore the possibility that the TMT’s choice of strategy
may moderate or mediate the TMTED and superior indus-
try returns relationship.
The idea that strategic choice may act as a moderating
variable comes from the logic imbedded in the RBV. The
RBV informs us that a resource is valuable if it allows the
firm to exploit opportunities in the market (Barney, 1991).
Yet, the ability of a resource to exploit market opportunities
can be undermined if the resource is not applied to the com-
petitive context it is best suited for. Put another way, the
resource may not fit the application context well and is
thereby underutilized (Black & Boal, 1994). Consistent
with the strategic fit literature, this occurs when a TMT
chooses a strategy that does not fit its resources (e.g., Black
& Boal, 1994; Venkatraman & Camillus, 1984; Venkatra-
man & Prescott, 1990). Based on this logic, the relationship
between a firm’s resources and its financial performance
will thus be moderated by the TMT’s choice of strategy.
Stated in terms of the current research, TMT’s entrepre-
neurial drive and superior industry returns will be moderated
by the firm’s choice of strategy, such that high levels of
TMTED will result in higher levels of performance when
more entrepreneurial prospector type strategies are utilized.
This suggests our next hypothesis.
Hypothesis 3a: The positive relationship between the
TMT’s entrepreneurial drive and superior industry
returns will be moderated by the firm’s choice of
strategy, such that high levels of TMTED will re-
sult in higher levels of industry returns when more
entrepreneurial prospector type strategies are used.
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228 Journal of Leadership & Organizational Studies 17(3)
Mediating Role of Strategy
In contrast to the prescriptions of the RBV, UET suggests
that strategic choice is likely to act as a mediating variable
in the relationship between TMTED and superior industry
returns. Ensley, Pearson, and Pearce (2003) argued that the
relationship between various upper echelon characteristics
and firm performance is likely to be influenced by a host of
situational variables. Integrating this notion with Hambrick
and Mason’s (1984) core UET logic suggests that the rela-
tionship between TMT characteristics and firm performance
is likely to be a mediated relationship (Olsen et al., 2006).
More specifically, UET suggests that the firm’s choice of
strategy is likely to be an intervening variable that changes
the form, rather than the strength, of the TMTED—firm
performance relationship. Simply put, UET tenets suggest
that strategy may be the mechanism by which UET charac-
teristics influence firm performance.
Building on the RBV and UET prescriptions discussed
above, we argued that TMTED may flow through strategic
choice on its way to affecting superior industry returns or it
may change the strength of the relationship between
TMTED and superior industry returns. As such, it becomes
important to explore the appropriateness of testing for both
moderating and mediating relationships within the same
model. Barron and Kenny (1986) inform that a given vari-
able may function as a mediator or a moderator, depending
on the theory being tested and suggest that it is appropriate
to explore mediating and moderating relationships within
the same model. Thus, to fully address the research ques-
tion posed earlier, we assert that it is appropriate and
necessary to test the possibility that TMTED and superior
industry returns will be mediated by the firm’s choice of
strategy, such that the relationship between TMTED and
performance will be weakened by the choice of strategy.
This relationship is captured in our final hypothesis:
Hypothesis 3b: The positive relationship between the
TMT’s entrepreneurial drive and superior industry
returns will be mediated by the firm’s choice of
strategy, such that the direct relationship between
TMT entrepreneurial drive and superior industry
returns will be weaker in the presence of the stra-
tegic choice variable.
Method
Participants
Participants were 325 undergraduate management students
(209 men, 116 women; mean age 22.92 years) enrolled in
nine sections of the capstone Strategic Management and
Policy course for graduating seniors at a doctoral/research
extensive university. We created diverse teams in each
section by categorizing individuals in terms of major,
gender, and nationality and then randomly assigned indi-
viduals to teams within each category in a stepwise fashion
so that each team included a variety of majors, included no
more than one international student, and included both men
and women. In short, this process resulted in 86 diverse
teams representing 86 independent companies. Team size
ranged from 3 to 5, with a mean of 4.06. To ensure that our
sample size provided adequate power (Cohen, 1992) to
detect a meaningful effect we conducted a post hoc power
test using G*Power software (Faul, Erdfelder, Buchner, &
Lang, 2009). This analysis found that based on our effect
size, number of predictors, sample size, and alpha level of
.05 that power was .95. This is well above the .80 threshold
commonly used as a guide for sufficent power, indicating
that our sample size was sufficient to detect meaniful effects
(Cohen, 1992).
Strategic Management Simulation
Complex management simulations have become a critical
empirical tool, and the paradigm has produced valuable
results on a number of issues central to strategic manage-
ment, organizational theory, and organizational behavior
(Chatman & Barsade, 1995; Chesney & Locke, 1991; Isa-
bella & Waddock, 1994; Lant & Mezias, 1990; Michalisin et
al., 2004; Waddock & Isabella, 1989). We chose simulation
as our research method because it allowed us to study com-
plex entrepreneurial focused organizational phenomena in a
controlled setting and in a manner that was involving to
participants and that incorporated a host of company and
industry factors commonly faced by managers. Moreover,
one of the seminal authors of UET has recently called for
empirical studies employing simulation methodology as a
way to gain new insights into phenomena involving TMTs
(Hambrick, 2007). Hambrick’s recommendation is based
on the realization that gaining access to the number of
TMT’s required for UET-based research is extremely diffi-
cult. Our use of a well-developed business simulation
methodology overcomes this problem and adds breadth to
the entrepreneurship literature, which has relied on other
methodological tools to examine firm level entrepreneurial
behavior (Rauch et al., 2009). Hence, we used Airline, A
Strategic Management Simulation (J. R. Smith & Golden,
2004). Airline is a complex, computer-assisted strategic
management simulation in which participants function as
top management teams of individual airlines that compete
against one another in the commuter airline industry. The
simulation was designed to model many key attributes of
top management decisions and resultant firm outcomes
and produce rich financial feedback to participants about
both their own firm and the industry.
The simulation is also rather unique in that the simula-
tion algorithms are based on extensive research of the
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Wood and Michalisin 229
commuter airline industry, thereby providing as high a level
of realism in the market dynamics of the simulation as pos-
sible. Each of the nine sections represented a single industry
consisting of 7 to 12 firms. Although sections varied in the
number of competing airlines, all firms within each section
had an equal chance to attain profitability because the simu-
lation adjusted the number of available markets to each
airline based on the number of firms in the industry. After an
initial 75-minute meeting in which individuals were assigned
to teams, became acquainted with their teams, and began
discussing the simulation, teams then met weekly in sepa-
rate 75-minute sessions across a 11-week period to make all
strategic and tactical decisions about their business. Each
simulation period (i.e., week) represented a calendar quarter
for the firm. Experienced graduate teaching assistants keyed
the decision form information into the computer’s simula-
tion software each week, which computed a myriad of team
and industry results and information.
At the beginning of each simulation period, each team
received printouts of their financial statements, operations
management statistics, financial statistics, market reports,
industry statistics, and so on. Each graduate assistant received
formal training on how to run the software and manage the
simulation classes to promote consistency in administering
this research. The authors also periodically attended each
section to be sure that all simulation sections were being
run the same way. A total of 10% of each student’s grade in
the course was based on his or her airline’s financial perfor-
mance relative to competitors. This was determined using a
number of financial ratios, including those used to measure
the dependent variable used in this study. Each week, every
simulation team received a report showing their overall
financial performance to date, relative to their competitors.
This promoted industry competition and created a shared
goal among teams to enhance their airline’s performance
across the course of the simulation.
Measure of Superior Industry Returns
Superior industry returns measures firm performance rela-
tive to the industry. Because the simulations are conducted
in the context of the airline industry, the selection of perfor-
mance measures was based on the features of this industry.
For example, each firm can buy or lease airplanes. This
means that common return on investment (ROI) measures,
such as return on assets (ROA), are problematic because the
cost of leased planes does not appear on the balance sheet—
making ROA difficult to compare across firms. Arguably,
the two largest resources in an airline company are its air-
planes and employees. As such, we used a common internal
airline performance measure associated with these resources
and a common external measure that reflects the superior
industry returns performance outcome variable. For the
internal measure, relative median net profit per seat
(RMNPS) was selected. For the external measure, relative
median earnings per share (RMEPS) was chosen to assess
each firm’s relative earnings per share, which is an impor-
tant indicator of stock value.
Each firm’s TMT participated in strategic decision making
for each of the 11 quarters. Each individual team’s perfor-
mance data (RMNPS and RMEPS) from each quarter was
then averaged to form a final performance index. The result
of this approach is that the multiperiod performance data
provides a more accurate measure of firm performance, as
opposed to simply taking performance data from a single
period. Another key advantage of this approach is that we
more accurate captured the impact of the TMT’s strategic
decisions, as these often take time to filter through to the
firm’s bottom line.
Measure of Entrepreneurial Drive
We adopted a previously validated scale (Cronbach’s a =
.73) from J. W. Carland et al. (2001) designed specifically to
measure the entrepreneurial drive of potential entrepreneurs.
The instrument is a forced choice questionnaire that consists
of 33 paired items intended to capture an individual’s pro-
clivity for cognitions related to preference for innovation,
risk-taking propensity, and strategic posture. Each item is
then scored according to the corresponding key developed
with the instrument. The outcome of the final scoring pro-
cess is an individual index score ranging from 0 to 33 (33
being high entrepreneurial drive). Because the instrument
was designed to capture the entrepreneurial drive of indi-
viduals not actively involved in entrepreneurship we
administered the assessment instrument to participants
before they began the simulation exercise. This ensured that
the scale was used in the manner it was intended and that the
participant’s experience from the simulation’s activities did
not bias their responses to the questionnaire items. Follow-
ing existing upper echelons research techniques (e.g., Boone
& Henriks, 2009; Hambrick & Mason, 1984; Marcel, 2009)
entrepreneurial drive was assessed as an individual charac-
teristic and then aggregated (averaged) to form a composite
team level entrepreneurial drive score. The final TMT com-
posite scores ranged from 14.66 to 27.1, with a mean of
19.25 and a standard deviation of 2.35.
Measures of Strategic Choice
The goal of the strategic choice measure was to capture the
TMT’s cumulative strategic decision making process from
the simulations. Using the Miles and Snow (1978) typol-
ogy as a guide for the strategic choice measure we identified
several existing scales (e.g., Rajagopalan, 1996). However,
because of the context-specific nature of the simulations,
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230 Journal of Leadership & Organizational Studies 17(3)
existing scales were not deemed suitable for our study. As
such, a new scale was developed using the Miles and Snow
typology as a theoretical guide. The firms level of promo-
tion, advertising, market research, and diversification were
measured to capture the firm’s choice of strategic direc-
tion. Initially, each of these dimensions was measured
using 5 items per construct, resulting in a 25-item scale.
Each item was measured via a 9-point Likert-type scale
ranging from 1 (strongly disagree) to 9 (strongly agree).
The complete 25-item measurement instrument was given
to each member of the TMT across the entire sample (n =
325). Exploratory factor analysis, using an orthogonal
varimax rotation,
3
was used to identify which survey items
were the best indicators of the firm’s strategic choice. After
removing the items that cross-loaded onto multiple factors
and removing those with eigenvalues of less than 1, we
ended up with a refined 10-item measurement scale that
was both internally consistent and reliable, with a Cron-
bach’s alpha of .81. The final measurement scale used in
the data analysis is provided in the appendix. After com-
pleting the factor analysis, each TMT members response
on the 10-item scale was then averaged across the team to
form an overall firm level index of strategic choice. Higher
index scores reflected that the firm followed an entrepre-
neurial (prospector) type strategy, moderate scores
reflected an analyzer strategy, and lower scores were indic-
ative of a defender strategy. The final strategic choice
composite scores ranged from 4.97 to 8.14, with a mean of
6.54 and a standard deviation of 0.63.
Control Variables
A number of control variables were used because they are
considered to be important influences on firm profitability
4
(Michalisin et al., 2004).
Firm size. Firm size can affect performance through
economies of scale, monopoly power, and bargaining
power (A. D. Chandler, 1990). In this study, firm size is
measured as total airplane seats (in their fleet) to capture
both the number and the size of their planes (Michalisin
et al., 2004).
Competitors. Each section of the course represented one
industry. Each industry contained between 7 and 12 airline
companies depending on the number of students in the sec-
tion. Porter (1980) argues that the number of competitors in
an industry can affect the attractiveness of the industry and
thus its profitability and can affect industry rivalry. As such,
we included a control variable that represented the number
of competitors in the industry.
TMT Size. Because the size of TMTs ranged from 3 to 5
members depending on enrollment in each section, we
included a control variable for team size.
Statistical Analysis
Our hypotheses were tested using hierarchical, mediated,
and moderated regression analysis. These statistical tools
allowed us to determine the effects of each variable sepa-
rately and the interaction effects between the independent
variables (Howell, 2007). More specifically, the regression
analyses were used to identify main and interaction effects.
In this type of analysis the interaction effects are found to
be significant only if they explain a significantly greater
portion of the variance in the dependent variable. Thus,
moderated regression analysis helps test the significance of
interaction effects by regressing the dependent variable onto
two or more main variables (one independent and one mod-
erator) and the cross product of those main variables (Sharma
et al., 1981). If the addition of the interaction term signifi-
cantly increases the power of the regression equation to
explain the variance in the dependent variable, then the con-
tingency relationship can be said to exist. Of course,
moderation is only possible if it has been shown that strate-
gic choice is not acting as a mediating variable.
Barron and Kenny (1986) provide a widely accepted
technique for testing mediation. They inform us that there
are four conditions that must be satisfied for a researcher to
claim mediation. The first requirement is that there must be
a relationship between the independent variable of TMT
entrepreneurial drive and the dependent variable of firm per-
formance. Second, there must be a significant relationship
between the mediating variable of strategic choice and the
independent variable; if this relationship does not exist then
the variable cannot mediate anything. Third, the mediating
variable must be related to the dependent variable. Finally,
the effect of the independent variable on the dependent vari-
able must be significantly weakened in the presence of the
mediating variable.
Results
The first step in the data analysis process was to explore a
graphical representation of the data. These graphical repre-
sentations were first used to identify any potential outliers in
our data set. Because the total number of teams in our sample
is relatively small, the impact of including, or excluding,
outlier data in the regression models is likely to be severe.
Close inspection of the scatterplots revealed a few values
that could be considered extreme which we then identified
as potential outliers. Because the removal of data points is a
subjective endeavor and because data removal can have seri-
ous implications for the study’s validity, many empiricist
and statisticians argue that the researcher must provide a
substantive justification for the removal of data points (e.g.,
Hair, Black, Babin, Anderson, & Tatham, 2006). Hair et al.
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Wood and Michalisin 231
assert that if the researcher feels that the data represent a
viable, albeit small, segment of the population, the data
should be retained. In this case, there was no indication that
the more extreme data points were the result of any proce-
dural error, in terms of data collection or entry, and the data
points appeared to be somewhat extreme but still viable to
the researchers. Finally, we statistically explored for the pos-
sibility of outliers by conducting a Cook’s distance test
(Cook & Weisberg, 1982). Cook’s distance uses residual
values to measure the influence of specific cases on the
model and it has been suggested that values greater than one
may be a cause for concern (Cook & Weisberg, 1982; Field,
2005). For our sample, Cook’s distance ranged from .00 to
.13 with a mean of .02 indicating that the presence of outli-
ers was not a major concern. As such, the full sample of 86
teams was included in the statistical analysis. Descriptive
statistics and variable correlations based on the sample of 86
teams are presented in Table 1.
The next step in the data analysis process was to ensure
that the assumptions for the use of regression techniques
had been adequately satisfied. As such, graphical represen-
tations of the data were used to ensure that our data were
normally distributed and that the relationships between the
variables were in fact linear. We also plotted the standard-
ized residuals to ensure that the homogeneity of variance
assumption had been satisfied. Taken collectively, we felt
confident that the regression assumptions had been ade-
quately satisfied and our data was appropriate for use in
hypotheses testing.
Our first hypothesis argued for a positive relationship
between entrepreneurial drive and firm performance. This
hypothesis was tested using hierarchical regression analysis
with the control variables of firm size, number of competi-
tors, and TMT size entered simultaneously in Model 1.
Model 2 includes the stepwise addition of the independent
variable of TMT drive. The two previously identified mea-
sures of performance, RMNPS and RMEPS were the
dependent variables considered in each model. The regres-
sion coefficient, R
2
, and relevant test statistics are reported
in Table 2. The regression models reveal, as predicted, that
there was a significant change in the R
2
value between the
control (Model 1) and predictor model (Model 2). For
RMNPS, the control variables are explaining 9.8% of the
variance, but when we add the TMTED predictor the
explained variance jumps to 18.7%. The 8.9% change in R
2
is statistically significant, F(1, 81) = 8.85, p < .01. For the
Table 1. Descriptive Statistics and Correlation
Variable M SD 1 2 3 4 5 6
1. RMEPS 0.14 10.55
2. RMNPS 51.58 1802.92 .96**
3. TMT entrepreneurial drive 19.25 2.35 .27* .30**
4. Strategic choice 6.54 0.63 .26* .24* .07
5. Firm size 75.79 20.56 -.24 -.31** -.05 .06
6. No. competitors 10.30 2.33 .02 .01 -.23* -.12 .03
7. TMT size 4.07 0.43 -.01 .00 .28** -.01 .01 -.44**
Note: RMEPS = relative mean earnings per share; RMNPS = relative median net profit per seat; TMT = top management team. N = 86.
*p < .05. **p < .01 (two-tailed).
Table 2. Multiple Regression Results (Standardized Coefficients)
Model 1 b
1
Model 2 b
1
Model 3 b
1
Model 4 b
1
RMNPS RMEPS RMNPS RMEPS RMNPS RMEPS RMNPS RMEPS
Firm size -.31** -.24* -.29** -.23* -.33 -.26*
Team size .01 .01 -.06 -.06 -.03 .03
Competitors .02 .03 .06 .07 .06 .07
TMT entrepreneurial drive .314** .286** .322 .288
Strategic choice .268** .283** .308 .313
TMT drive × Strategic choice -.207* -.165
R
2
.098 .058 .187 .131 .168 .136 .287 .226
Change in R
2
.089 .074 .070 .078 .039 .025
Change in F 8.848 6.876 6.841 7.345 4.299 2.509
Significant F change (p =) .004** .010** .010** .008** .041* .117
Note: RMEPS = relative mean earnings per share; RMNPS = relative median net profit per seat; TMT = top management team.
*p < .05. **p < .01.
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232 Journal of Leadership & Organizational Studies 17(3)
performance variable RMEPS, the control variables are
explaining 5.8% of the variance. When we add the TMTED
predictor variable the explained variance climbs to 13.1%.
The change in R
2
of 7.3% is statistically significant, F(1,
81) = 6.87, p < .01. As such, the results for both the internal
and external measures of performance support Hypothesis 1,
indicating that the TMT characteristic of entrepreneurial
drive is an important predictor of firm performance, with
higher levels of entrepreneurial drive leading to increased
firm performance.
Hypothesis 2 asserts that the firm’s choice of strategy
will affect its performance, such that a more entrepreneurial
strategy will lead to superior industry returns. This hypoth-
esis was tested using hierarchical regression analysis with
the same control model (Model 1) and the stepwise addition
of the strategic choice variable in Model 3. The two previ-
ously identified measures of performance (RMNPS and
RMEPS) were the dependent variables considered in each
model. Consistent with predictions, the regression models
show a significant change in the R
2
value between the con-
trol (Model 1) and the predictor model (Model 3). For
RMNPS the change in R
2
change between models is 7.0%.
This change in explained variance is statistically significant,
F(1, 81) = 6.84, p < .01, supporting Hypothesis 2 for this
measure of performance. For RMEPS, the change in R
2
between Model 1 and Model 3 is 7.8%. This change in
explained variance is also statistically significant, F(1, 81) =
7.34, p < .01 The combined results of the two measures of
performance provide support for Hypothesis 2, indicating
that within this sample, firms that chose a more entrepre-
neurial strategy enjoyed higher levels of performance
relative to the rest of the industry.
Hypothesis 3a posited that the relationship between
the TMTs entrepreneurial drive and firm performance
would be moderated by the firm’s choice of strategy,
such that higher levels of TMTED will result in higher
levels of performance when more entrepreneurial strate-
gies are employed. The test of this hypothesis was
conducted using moderated regression analysis. This
method tests the significance of interaction effects by
regressing the dependent variable onto two or more main
variables (one independent and one moderator) and the
cross-product of those main variables (Sharma et al.,
1981). If the addition of the interaction term significantly
increases the power of the regression equation to explain
the variance in the dependent variable, then the contin-
gency relationship can be said to exist. However,
statisticians have noted that regression analysis using two
independent variables in the same model often suffer
from multicolinearity issues (Howell, 2007). The recom-
mendation for resolving this issue is mean centering of
the variables. As such, we centered each variable and the
interaction variable before proceeding with the moder-
ated regression analysis.
The results of the moderated regression analysis pro-
vide partial support for the moderating effect of the firm’s
choice of strategy (Table 2, Model 4). For RMNPS,
results indicated that the addition of the interaction term
increased explained variance in R
2
by 3.9% and this
change in R
2
was statistically significant F(1, 79) = 4.29,
p < .05. These results are consistent with the prediction in
Hypothesis 3a and indicate that the firm’s choice of strategy
acts as a moderator in the TMTED–RMNPS relationship.
The results for the RMEPS performance variable are
somewhat different from the findings for our internal per-
formance metric. Here the moderated regression analysis
revealed that the addition of the interaction term increased
explained variance by 2.5%, but this change was not sta-
tistically significant, F(1, 79) = 2.51, p > .05. Hence, the
moderation effect of strategic choice is observable, but for
this sample, it plays a more limited role in the TMTED–
RMEPS relationship than in the TMTED–RMNPS
relationship. Collectively, these results provide partial
support for Hypothesis 3a.
To further understand the true nature of the interaction
effects associated with Hypothesis 3a, high–moderate–low
values were selected (standard deviations above and below
the mean) for the level of TMTED and the strategic choice
variables. This matrix analysis provided estimated levels
of RMRPS given specific levels of the independent and
moderator variable. These values were then graphed (see
Figure 2) to illustrate the moderating effects of the choice
of strategy. This graphical representation reveals that at
low levels of TMTED a more conservative (defender type)
strategy leads to higher performance whereas more entre-
preneurial strategies lead to lower performance. At a
moderate level of TMTED the choice of strategy has a rela-
tively small effect on performance, with a more conservative
strategy leading to slightly higher levels of performance.
However, at a high level of TMTED, the choice of a more
entrepreneurial (prospector type) strategy clearly leads to
much higher levels of performance. Collectively, these
results indicate that there is an important alignment or
fit” that must take place between the TMT characteris-
tic of entrepreneurial drive and the type of strategy
pursued by the firm. Entrepreneurial–prospector type strate-
gies are most effective when used by an entrepreneurial-minded
TMT. Alternatively, the use of an entrepreneurial strategy
by a conservative-minded TMT results in poorer perfor-
mance outcomes.
Hypothesis 3b posits that the relationship between the
TMT’s entrepreneurial drive and firm performance would
be mediated by the firm’s choice of strategy. As previously
discussed, Barron and Kenny’s (1986) four-step technique
was used. We began by testing the relationship between the
TMT’s entrepreneurial drive and firm performance via
ordinary least squares regression. The relationship between
TMT entrepreneurial drive and RMEPS was significant,
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Wood and Michalisin 233
F(1, 85) = 6.39, p < .05. Similarly, the relationship between
TMTED and RMNPSM was also significant, F(1, 85) =
8.06, p < .01. Thus, the first condition for mediation was
satisfied. We then tested the relationship between TMTED
and the strategic choice variable using ordinary least
squares regression. We found that there was not a signifi-
cant relationship between these variables, F(1, 84) = 0.381,
p > .05. This means that the second condition for mediation
was not met and that strategic choice did not act as a medi-
ating variable in the entrepreneurial drive and firm
performance relationship. Therefore, Hypothesis 3b was
not supported.
In summary, the results of our study provide interesting
new insights. We found support for a significant and positive
relationship between the TMT characteristic of entrepre-
neurial drive and both internal and external performance
measures for superior industry returns. We also found a pos-
itive and significant relationship between the firm’s choice
of strategy and both performance outcomes. Finally, when
considering our internal performance measure (RMNPS),
we found evidence of moderation for the choice of strategy
on the TMTED–performance relationship; such that that an
entrepreneurial prospector type strategy is most effective
when used by TMTs that exhibit high levels of entrepreneur-
ial drive, whereas defender strategies are best used by TMTs
that rate lower in entrepreneurial drive. Consistent with the
logic contained in classical contingency theory models (e.g.,
Donaldson, 1987; Rumelt, 1974), the entrepreneurial drive–
strategy alignment appears to be a crucial determinate of
financial performance.
Discussion and Conclusion
The purpose of our research was to explore the following
research question: What is the relationship between TMTED,
strategic decision making, and relative firm performance? As
such, we have used UET (Hambrick & Mason, 1984) and
Miles and Snow’s (1978) strategy typology to develop a
theoretical model and associated hypotheses that identify
the anticipated relationships between the TMT’s level of
entrepreneurial drive, the firm’s choice of strategy, and firm
performance. We then tested our hypotheses using perfor-
mance data collected from TMTs engaged in a competitive
strategic management simulation based on the airline industry.
Previous UET research has shown that certain demo-
graphic based individual level characteristics, such as age,
tenure, and functional background have heavy influences
on the strategic posture of the TMT, which correlates with
organizational performance (e.g., Finkelstein & Hambrick,
1996). Our results are consistent with this stream of research
and reveal a strong positive relationship between the TMT’s
entrepreneurial drive and firm performance. More specifi-
cally, we found that TMTs who were higher in entrepreneurial
drive outperformed their industry competitors. In that way,
our research identifies entrepreneurial drive as a previously
overlooked upper echelon characteristic that is an important
predictor of firm performance. This is an important contri-
bution because UET research has been criticized for its
lack of emphasis on additional characteristics, beyond basic
demographics, that may provide insight into the TMT–
organizational outcome relationship (Priem et al., 1999).
–0.5
–0.25
0
0.25
0.5
0.75
1
1.25
–4 0 4
TMTED
RMNPS
Low
Neutral
High
Strat. Choice
Figure 2. Hypothesis 3b—Moderation effects: Level of strategic choice by level of TMT entrepreneurial drive on RMNPS
Note: RMNPS = relative median net profit per seat; TMTED = top management team entrepreneurial drive.
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234 Journal of Leadership & Organizational Studies 17(3)
In addition to providing new UET-based insights, our
entrepreneurial drive finding is consistent with the logic
embodied in the resource-based view of the firm, which
argues that key intangible TMT resources can be strategic
assets to the firm (e.g., Carpenter et al., 2001). Because
each TMT members entrepreneurial drive is composed of a
nexus of personality factors, including the need for achieve-
ment, the propensity for risk taking, the preference for
innovation, and a high need for cognition. The unique com-
bination of these personality attributes across members of
the TMT makes TMTED a rare intangible resource to the
firm. Here, our use of simulations provides an exception-
ally clear picture of TMTED as a valuable and intangible
resource that has the potential to lead to superior perfor-
mance. Because each of the teams were given the same
tangible resources (e.g., planes and capital) it is clear that
intangible resources are influencing firm performance. Our
results show that TMTED is clearly one of those resources.
Moving beyond the UET- and RBV-based insights, our
entrepreneurial drive finding is also important because it
speaks to the entrepreneurship literature’s widely used firm
level construct of entrepreneurial orientation (see Rauch
et al., 2009, for a review). Entrepreneurial orientation has
been linked to firm performance for some time, but how
that orientation develops and manifests itself within the
firm’s strategic decision-making process is an understudied
area (Covin et al., 2006). Our study provides initial insights
into this process by revealing that the individual charac-
teristic of entrepreneurial drive can become a collective
orientation in the TMT that affects the firm’s strategic
posture. However, the relationship between the TMT’s
entrepreneurial drive and financial performance is quali-
fied by the moderating effect of strategic choice. As such,
our results suggest that individual characteristics, such
as entrepreneurial drive, can become a collective phe-
nomenon that impacts firm performance; however, that
relationship is strengthened when the chosen strategy is
appropriate to the TMT’s entrepreneurial orientation. As
such, future research should build on our study by more
directly exploring other possible antecedents and develop-
ment processes of firm level entrepreneurial orientation.
Another key aspect of our research was to investigate the
question of whether or not the TMT’s choice of a more
entrepreneurial strategy would result in higher levels of
performance. As such, we hypothesized that the firm’s
choice of strategy would impact firm performance, such
that firms who chose a more entrepreneurial (prospector)
type strategies would be rewarded with higher performance.
Our results indicate that this is indeed the case. For our
sample, firms who chose a more aggressive strategy were,
on average, the highest performers relative to the industry.
This finding adds further support to a large body of litera-
ture (e.g., McGrath, 2001) that shows the firm’s choice of
strategy is a crucial determinate of firm performance and is
consistent with Miles and Snow’s (1978) argument that
prospector firm’s who strategies emphasize innovation
and flexibility in a continual attempt to be on the leading
edge of new product or service offerings are likely to see
more variability in returns but outperform more conserva-
tive firms over the long term. These results are also consistent
with the entrepreneurship literature that suggests, holding all
else constant, firms that are competitively aggressive and
have a strong entrepreneurial focus will outperform those
firms who are more conservative (Dess & Lumpkin, 2005).
In addition to our findings for the direct relationships
between entrepreneurial drive, strategic choice, and finan-
cial performance, another important contribution of this
study was the investigation of the moderating versus medi-
ating role of the firm’s choice of strategy. Very little UET
and TMT research considers the possibility that interven-
ing variables, such as the firm’s choice of strategy, may act
as mediating or moderating variables (see Olsen et al.,
2006, for a recent exception). Thus, we considered the idea
that the choice of strategy may act as either a mediator or
moderator and found that the firm’s choice of strategy did
not mediate the relationship between the TMT’s level of
entrepreneurial drive and firm performance. One possible
explanation for this finding is that although the TMT’S
choice of strategy is an important variable (evidenced by
our finding of a positive moderating effect), it is not the
key variable by which TMTED influences performance.
This would mean that although strategy is important, there
are likely a host of other variables that help facilitate the
TMT’s proclivity to engage in entrepreneurial behavior
and thus affect firm performance. As such, future research
should explore the possibility of other key intervening vari-
ables that may mediate the relationship between TMTED
and firm performance.
In contrast to our findings for the mediating role of
strategic choice, we did find evidence of strategic choice
acting as a moderator in the relationship between the
TMT’s level of entrepreneurial drive and the common air-
line industry performance measure of relative median
revenue per seat. Close examination of this contingency
relationship revealed that firms who have TMTs with a
high level of entrepreneurial drive are best served by
choosing a highly entrepreneurial strategy and firms
exhibiting low levels entrepreneurial drive perform best
when a conservative strategy is selected. In this way,
when the entrepreneurial drive–type of strategy contin-
gency relationship is well aligned the RMRPS was
significantly higher than when it was not. This finding is
consistent with the logic imbedded in the strategic fit lit-
erature which suggests that the greater the fit between the
TMT’s entrepreneurial propensity and the entrepreneurial
nature of their strategic choices the higher relative firm
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Wood and Michalisin 235
performance (e.g., Chakravarthy, 1986; Donaldson, 1987;
Sorge, 1991; Venkatraman & Prescott, 1990).
This finding is important because it begins to shed light
on the “black box of process” that has been identified as a
shortcoming of the current TMT literature (Priem et al.,
1999). By this we mean that our study more accurately por-
trays the mechanisms by which the TMT characteristic of
entrepreneurial drive actually affects performance. Our
results indicate that the degree of strategic fit (Donaldson,
1987) between entrepreneurial drive and the choice of strat-
egy appears to directly influence firm performance, such
that a TMT that is very entrepreneurial minded and selects
a prospector strategy outperforms alternate combinations of
these variables. As such, future research could add to our
findings by empirically evaluating firms on their TMT’s
entrepreneurial drive, firm level entrepreneurial orienta-
tion, their choice of strategy, and the firm’s performance in
order to further validate the our alignment hypothesis.
Given the interaction effects (moderation) between the
TMTs level of entrepreneurial drive and the choice of
strategy on the RMNPS performance measure, we were
somewhat surprised to find that this relationship was evi-
dent but much weaker for our external performance measure
of RMEPS. Although there may be several possible expla-
nations for this finding, we posit that this is likely an artifact
of the performance measure. This performance measure is
global in nature and captures a broader spectrum of influen-
tial performance factors than does the internal measure of
RMNPS. It is also possible that the TMTs were mostly
focused on profitability indices rather than returns to share-
holders. As such, the strategic decisions made over the
course of the simulation may be directed at maximizing
profitability, which could lead to a much smaller effect in
the relationships involving the RMEPS measure. Future
research could explore this possibility using simulations
based on different industries and using a broader range of
performance measures in order to more thoroughly confirm
our conjectures.
Limitations of the Study
Although this study makes a number of important contri-
butions, it also has some inherent limitations. The primary
limitation of the study is related to concerns over external
validity. Given that our sample consisted of senior-level
business students playing the role of TMTs rather than
TMTs of actual organizations, generalizability becomes an
issue. Adding to this concern is the fact that our sample was
restricted to one university, and the simulation was based on
only the airline industry. Despite these considerations, there
are several reasons why the results of this study are likely to
have external as well as internal validity. First, the simula-
tion incorporated a host of major decisions found in many
organizations and incorporated an industry environment
modeled after actual industry variables, including direct
competition. Second, TMTs made their own decisions, and
resulting firm and industry outcomes were reliant on the
interaction of the decision outcomes of multiple firms and
industry variables. Thus, each team was functioning as a
TMT in terms of managing all aspects of decisions related
to the operation of actual real-world firms. Finally, we fol-
lowed Hambrick’s (2007) recommendation to employ a
simulation-based methodology in the exploration of TMT
phenomena, which allowed us to examine a large number of
TMTs and the performance of multiple firms in multiple
markets. Nonetheless, research that examines TMTs in
actual organizations across different industries is an impor-
tant future step in testing entrepreneurial phenomena within
the corporate environment.
Another potential limitation to the study is the implicit
relationship between individual-level entrepreneurial drive
and the firm-level construct of entrepreneurial orientation.
In several places, we have highlighted the potential related-
ness between the degree of TMTED and the entrepreneurial
orientation of the firm. However, the explicit relationship
between these two constructs was beyond the scope of our
research and we did not attempt to measure entrepreneurial
orientation or correlate it with our entrepreneurial drive
measure. We view this limitation as less of a liability and
more as an opportunity for future research. Our study shows
that there is an important relationship between TMTED and
firm performance and hints at the idea that TMTED may be
a key mechanism by which entrepreneurial orientation
develops within the firm. As such, our study lays the ground-
work for future research that investigates this potentially
important relationship.
Despite its limitations, we feel that our study provides a
step forward in exploring several important relationships.
The exploration of determinates of entrepreneurial behavior
within TMTs is rather limited, and this study contributes to
the filling of that void. Previous entrepreneurship research
has shown that individual level characteristics are impor-
tant determinates of entrepreneurial behavior, but how
those characteristics interact to determine team-level entre-
preneurial behavior is not well understood. As such, this
study provides initial insights into determinates, processes,
and outcomes of team-based entrepreneurial activity within
a corporate setting.
Appendix
Final Multi-Item Scale for Measuring
Strategic Choice
Instructions: Using the scale below, please indicate the
degree to which you feel each statement most accurately
reflects your airline management team’s beliefs and
actions.
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236 Journal of Leadership & Organizational Studies 17(3)
1 2 3 4 5 6 7 8 9
Strongly Neutral or Strongly
Agree Uncertain Disagree
1. _____ Our promotion budget is typically higher
than our competitors
2. _____ There is little benefit to promotion (R)
(continued)
Appendix (continued)
3. _____ Promotion is a key to success
4. _____ Our advertising budget is typically lower
than our competitors. (R)
5. _____ There is great benefits to advertising
6. _____ We allocate substantial resources to our
advertising budget
7. _____ Market research is a valuable investment
8. _____ Our market research budget is typically
higher than our competitors
9. _____ Market research provides little value (R)
10. _____ Diversification is a key success factor
Authors’ Note
An earlier version of this article was presented at the Academy of
Management Conference, Anaheim, California, August 2008.
Acknowledgments
Special thanks to Bryan Stinchfield and the anonymous reviewers
for providing helpful comments on earlier versions of this article.
Declaration of Conflicting Interests
The author(s) declared no conflicts of interest with respect to the
authorship and/or publication of this article.
Funding
The author(s) received no financial support for the research and/or
authorship of this article.
Notes
1. Because we later use “superior industry returns” as our mea-
sure for firm performance relative to industry competitors, we
use these terms interchangeably throughout the article.
2. Because reactors are defined as lacking an identifiable strat-
egy, a priori theoretical predictions cannot be made and thus
we excluded the reactor category from our model. This exclu-
sion is consistent with prior research based on the Miles and
Snow typology (e.g., Dvir, Segev, & Shenhar, 1993; Shortell &
Zajac, 1990).
3. Following the suggestion of D. W. Stewart (1981), oblique and
orthogonal varimax rotations were initially used to simplify the
factor structure. The orthogonal technique was found to pro-
vide the clearest factor structure.
4. Firm age is a commonly included control variable. However,
because we used simulations, all the firms were the same age
and thus there was no need to include age as a control variable.
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Bios
Matthew S. Wood is an Assistant Professor of Entrepreneurship
at the University of North Carolina Wilmington. He received
his Ph.D. in Strategic Management and Entrepreneurship from
Southern Illinois University, Carbondale. His research interests
include the nature of entrepreneurial opportunities, opportunity
evaluation and exploitation, entrepreneurial cognition and
decision-making and entrepreneurial top management teams.
Michael D. Michalisin is an Associate Professor of Management
at Southern Illinois University, Carbondale. He received his Ph.D.
in Strategic Management and Macro-Organizational Theory from
Kent State University. His research, which includes strategic
entrepreneurship, corporate environmental strategies, resource-
based competitiveness, supply chain management, and top
management team dynamics, appears in various journals including
Decision Sciences, Group & Organization Management, and the
Journal of Business Research.
at Randall Library, UNC Wilmington on August 26, 2010jlo.sagepub.comDownloaded from
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