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Betting on the coachable entrepreneur: Signaling and social exchange in entrepreneurial pitches


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Given that stakeholders often commit more than capital to a startup, they commonly stress how important it is for entrepreneurs to be ‘‘coachable.’’ To date, however, coachability has received little attention in entrepreneurship research. We address this gap by first establishing the entrepreneurial coachability construct and validating a measurement scale. Then, drawing on social exchange and signaling theories, we develop and test a novel framework in which coachability influences a potential investor’s willingness to invest. We find that entrepreneurial coachability functions as a viable signal in a pitch setting, but this impact is conditional on the investor’s prior coaching experience.
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Betting on the Coachable Entrepreneur: Signaling and Social Exchange in Entrepreneurial
Michael P. Ciuchta*
Assistant Professor
University of Massachusetts Lowell
Lowell MA 10856
Phone: 978 934 2993
Chaim Letwin
Assistant Professor
Suffolk University
8 Ashburton Place
Boston, MA 02108
Regan Stevenson
Assistant Professor
Indiana University
Kelley School of Business
1309 E. 10th Street
Room HH3100
Bloomington, IN 47405
Sean McMahon
Assistant Professor
Love School of Business
Elon University
100 Campus Drive
Elon, NC 27244
M. Nesij Huvaj
Assistant Professor
Suffolk University
8 Ashburton Place
Boston, MA 02108
Keywords: coachability; new venture finance
Cite: Ciuchta, M. P., Letwin, C., Stevenson, R.M., McMahon, S., & Huvaj, M. N. (2018).
Betting on the Coachable Entrepreneur: Signaling and Social Exchange in Entrepreneurial
Pitches. Entrepreneurship Theory and Practice,
Betting on the coachable entrepreneur
Betting on the Coachable Entrepreneur: Signaling and Social Exchange in Entrepreneurial
Given that stakeholders often commit more than capital to a startup, they commonly
stress how important it is for entrepreneurs to be “coachable”. To date, however, coachability has
received little attention in entrepreneurship research. We address this gap by first establishing the
entrepreneurial coachability construct and validating a measurement scale. Then, drawing on
social exchange and signaling theories, we develop and test a novel framework in which
coachability influences a potential investor’s willingness to invest. We find that entrepreneurial
coachability functions as a viable signal in a pitch setting, but this impact is conditional on the
investor’s prior coaching experience.
Betting on the coachable entrepreneur
“One thing I always look for in an entrepreneur is are they coachable?”
Steve Krein, Venture Capitalist
Entrepreneurship is often characterized as collective action between entrepreneurs and
other parties such as important stakeholders and resource providers (e.g., Kotha & George, 2012;
Ruef, 2002; Schoonhoven & Romanelli, 2001). These other parties, however, must make
commitments to the entrepreneurial venture under conditions of great uncertainty. Therefore,
they often rely on signals to assess opportunities (Ahlers, Cumming, Guenther, & Schweizer,
2015; Baum & Silverman, 2004) and the entrepreneur (Chen, Yao, & Kotha, 2009; Huang &
Pearce, 2015). One potentially very important but unexplored signal is the entrepreneur’s level of
coachability. We define this new construct as the degree to which an entrepreneur seeks,
carefully considers, and integrates feedback to improve his/her venture’s performance.
Within the entrepreneurship community, coachability is seen as critical, possibly even the
most important criteria that investors look for in entrepreneurs (Campbell, 2016; Combs, 2012).
However, to-date the academic literature lacks a theoretically motivated definition of the
construct as well as a theoretical framework that situates the construct within the entrepreneurial
process. This oversight is surprising given how important the coaching function is seen in
investor-entrepreneur relationships (Baum & Silverman, 2004). In this study we address this gap
by introducing the coachability construct and empirically validating a measurement scale. More
importantly, we also develop a novel theoretical framework that establishes coachability as an
important factor in new venture funding.
In developing our model we bridge extant theory by integrating insights from signaling
(Connelly, Certo, Ireland, & Reutzel, 2011; Spence, 1973) and social exchange (Blau, 1964;
Homans, 1958) perspectives. As recently noted by Huang and Knight (2015), entrepreneurs
Betting on the coachable entrepreneur
convey informational and interpersonal signals to investors that investors weigh prior to entering
the relationship. We suggest that although more static informational signals may provide an
indication of what types of return might be expected on the investor’s financial resources,
coachability provides an indication of what type of return might be expected on both the
investor’s financial and social investments into the venture (Huang & Knight, 2015). Thus in our
framework coachability serves as an important linchpin between signaling and social exchange
Additionally, it has been noted that signals are subject to receiver interpretation
(Connelly et al., 2011) but to-date we know little about how signals’ efficacy could be
conditional on particular receiver characteristics. We address this gap by exploring how both
prior coaching and entrepreneurial experiences of the receiver (i.e. potential investor) moderates
the relationship between perceptions of coachability and willingness to invest in the venture. We
chose these conditional factors because of the critical role they play in shaping a coach’s view of
the potential costs of social exchange relationships (Allen, 2004).
Our study makes several important contributions. First, by theoretically establishing this
new construct, our study contributes to entrepreneurship theory by extending the scholarly
understanding of the critical investment criteria that investors use to evaluate venture proposals
(MacMillan, Siegel, & Narasimha, 1986; Maxwell, Jeffrey, & Levesque, 2011; Mitteness,
Baucus, & Sudek, 2012). Importantly, we demonstrate that coachability serves as a viable signal
above and beyond other criteria previously discussed in the literature. Thus, our study also
contributes to the scholarly understanding of the use of particular signals within the
entrepreneurial process. Although much attention has been given to information signals such as
human, social, and intellectual capital (Ahlers et al., 2015), research has recently noted the
Betting on the coachable entrepreneur
importance of interpersonal signals as well (Huang & Pearce, 2015). In this study we highlight
coachability’s role as another important interpersonal signal in pitch settings. Moreover, we
contribute to the growing recognition that signals are not purely objective criteria with
unambiguous meanings. Rather, to be effective, signals must also be appropriately perceived and
valued by the receiver. In this regard, we contribute to the understanding of signaling within an
entrepreneurial pitch setting by introducing important boundary conditions in this process.
Our study also contributes to our understanding of the entrepreneurial process by
emphasizing the role of social exchange. Although social exchange theory is widely invoked in
the social sciences, its utilization within the entrepreneurship literature has been limited. This is
surprising given the nature of the investor-entrepreneur relationship. Whereas signaling
perspectives emphasize the role of certain criteria as a means for investors to evaluate ventures
according to potential returns on financial resources, the social exchange perspective also
recognizes that investors scrutinize relationships according to potential returns on social
resources that they commit to a venture. In our study, we demonstrate the importance of
coachability in this process.
Following best practices (e.g., Newman, Harrison, Carpenter, & Rariden, 2016; Schwab,
1980), our study also offers a methodological contribution to the entrepreneurship literature by
introducing and validating a novel coachability scale Although coachability is considered by
many to be important for entrepreneurs, the lack of an established measurement instrument has
tempered research regarding this important construct. By developing this new construct and
scale, our study also aligns scholarly discourse with practical discourse through the validation of
previously unsubstantiated claims that coachability is a critical characteristic for entrepreneurs.
Thus, our study has important practical implications for entrepreneurs, incubator/accelerator
Betting on the coachable entrepreneur
administrators, investors, and students of entrepreneurship. Entrepreneurship curricula are replete
with opportunity identification and analysis. However, despite its importance, the role of
interpersonal dynamics within the entrepreneurial process is often downplayed. Therefore, a
better understanding of entrepreneurial coachability should be a welcome addition to the
entrepreneurship classroom as well.
Overall, the outline of the paper is as follows. First, we present a theoretical explanation
for the new coachability construct in entrepreneurship research. Then, we provide a brief
literature review of how coachability has been used in other fields. Next, we develop a
theoretical model and a set of hypotheses regarding the association between coachability and
willingness to invest, as well as contingent hypotheses related to the potential investor’s prior
coaching and entrepreneurial experience. Turning to our methods, we first present a preliminary
study in which we establish our coachability measure and assess its validity. Then, in our main
study, we further validate the scale and test our theoretical model. We conclude with a discussion
of both theoretical and practical implications of our study.
Coachability in Entrepreneurship Practice
Despite its lack of emphasis in the academic community, coachability is the object of
considerable attention and discussion within the larger entrepreneurial community as reflected in
widespread media coverage. Specifically, the media often portrays a coachable entrepreneur as
someone who is humble, open to new ideas, and willing to take criticism from trusted advisers
(ExcelerateLabs, 2012). Investors tend to emphasize the entrepreneur’s ability to listen and
process feedback (Combs, 2012). Early stage investor Catherine Mott of the BlueTree Capital
Group explains that her firm’s investments revolve around founders that “take advice, because
Betting on the coachable entrepreneur
we understand there’s lots they won’t know” (Gardella, 2010). Moreover, an entrepreneur’s
coachability is often portrayed as something that is critical for venture success (Combs, 2012;
I4Business, 2013). The belief that coachability is positively related to performance, however, is
not shared by all. Well-known entrepreneur and investor Marc Andreessen has notably said, “the
entrepreneurs who have really radical ideas are not only not coachable, but they generally react
with hostility to being coached(Suleimenov, 2014). Overall, these anecdotal insights suggest
that coachability is important to practitioners.
Coachability in Entrepreneurship Literature
Despite the popularity of coachability within the entrepreneurship community, previous
academic research has only scratched the surface of this important construct and its role in the
entrepreneurial process. There is some indication that chemistry between coach and entrepreneur
is important as well as the entrepreneur’s receptiveness to coaching and openness to change
(Audet & Couteret, 2012: 526). To date, we have a limited understanding of what, if any, role
coachability has on investors’ decision making. In the only published paper on the topic and
relying on a single-item measure, Mitteness, Sudek, and Baucus (2010) found that perceptions of
coachability were associated with angel investors’ willingness to advance to due diligence.
However, there is still much we do not know about coachability and its role in the
entrepreneurial process, including a formal construct definition and measurement scale, and
potential boundary conditions concerning its impact as a signal. Before turning to the
development of our hypotheses, we provide a brief overview of how coachability is covered in
other literatures.
Coachability in Other Literatures
Betting on the coachable entrepreneur
Athletics. Not surprisingly, coachability has roots in the literature on athletics. Although
it is presumed that coachability is an important driver in athletic performance (Smith, Schultz,
Smoll, & Ptacek, 1995), there is still little systematic research on this topic (Giacobbi Jr, 2000).
In one of the more comprehensive treatments of the topic, Giacobbi (2000) identified three key
dimensions that make up the coachability construct. “Openness to learning new skills” reflects
the athlete’s willingness to seek and develop new skills, both from the coach and other sources.
“Intensity of effort” reflects the athlete’s willingness to follow feedback from the coach. The
athlete’s “trust and respect for the coach” captures how attentive the athlete is while receiving
feedback and a general willingness to engage the coach with questions. Beyond largely
descriptive and qualitative work, there is some evidence that an athlete’s neuroticism is
negatively associated with perceptions of her/his coachability, and both agreeableness and
conscientiousness are positively associated with it (Favor, 2011; Piedmont, Hill, & Blanco,
Sales Performance. Coaching is seen as a critical role that sales managers fulfill in
developing their salesforce (Deeter-Schmelz, Goebel, & Kennedy, 2008; Hawes & Rich, 1998).
Building on work in the sports literature, salesperson coachability has been defined as “the
degree to which salespeople are open to seeking, receiving, and using external resources to
increase their sales performance in a personal selling context” (Shannahan, Bush, & Shannahan,
2013: 41). Salesperson coachability is found to both mediate the relationship between
salesperson competitiveness and salesperson performance and is a strong predictor itself of
salesperson performance (Shannahan et al., 2013).
Workplace Mentoring. Although most of the focus in mentorship research is on the
protégé, attention has also been given to the mentor (Haggard, Dougherty, Turban, & Wilbanks,
Betting on the coachable entrepreneur
2011). For example, scholars recognize that there are various costs and benefits associated with
being a mentor (Ragins & Scandura, 1999). Therefore, mentors are often selective of their
protégés. Relying on social exchange theory (Blau, 1964), Allen (2004: 470) suggests that
“mentors will favor protégés believed to bring desirable attributes and competencies to the
mentorship that will result in a mutually satisfying relationship.” Across both an experimental
and field setting, she found that both the protégé’s ability and her willingness to learn positively
impacted the mentor’s willingness to select the protégé. Moreover, in the field study she found
that protégé’s willingness to learn had a greater influence on protégé selection than did ability.
We used this as a key takeaway from the mentoring literature when developing our coachability
Literature Review Summary
Overall, these other literatures provide a useful backdrop to the development of the
entrepreneurial coachability construct. However, a key distinction between the entrepreneurial
context and these others involves the level of uncertainty. Entrepreneurs (and their
coaches/investors) operate under conditions of great uncertainty. Each opportunity presents new
uncertainties and challenges. Entrepreneurial returns serve as compensation for exercising
appropriate judgment under these conditions (Foss & Klein, 2012). In sporting endeavors,
coachable athletes are those who solicit and integrate the coach’s feedback and then execute on
the playing field. In entrepreneurship, the very rules of the game, the shape of the playing field,
and the number of players in the game are constantly changing. Investors understand that they
will generate positive returns only if the entrepreneur can successfully navigate this tumultuous
environment. Therefore, coachability in entrepreneurship is likely to be seen as just as important
if not more so than in these other more predictable contexts.
Betting on the coachable entrepreneur
We draw on signaling and social exchange theories to form the theoretical basis of our
coachability construct. We then integrate these theories to develop hypotheses associating the
entrepreneur’s coachability with the investor’s willingness to invest. We then consider prior
experiences of the social exchange partner (the coach) as an important boundary condition
regarding the impact of coachability as a viable signal.
Signaling Theory
Signals are indicators of something that is unobservable. In their review, Connelly et al.
suggest that “something” is usually quality, which they define as “the underlying unobservable
ability of the signaler to fulfill the needs or demands of an outsider observing the signal”
(Connelly et al., 2011, p. 43). Signals provide new information that may change the receiver’s
understanding of a future state (Busenitz, Fiet, & Moesel, 2005). To be effective they should be
costly to produce and go unrewarded if false (Connelly et al., 2011; Spence, 1974). In other
words, they should have high cue validity (Kirsch, Goldfarb, & Gera, 2009).
Signaling theory is frequently invoked in entrepreneurship research, particularly to
explain how entrepreneurs overcome information asymmetry to obtain outside financing (Ahlers
et al., 2015; Connelly et al., 2011; Eddleston, Ladge, Mitteness, & Balachandra, 2014). Scholars
have classified these entrepreneurial signals into several broad categories. An entrepreneur can
provide information signals that convey the underlying viability of the venture. Examples of
information signals include market and financial data (Huang & Knight, 2015), technological
competency (Hsu & Ziedonis, 2013), or indicators of human, social, and intellectual capital
(Ahlers et al., 2015; Baum & Silverman, 2004). Research has also suggested that preparedness
might serve as an effective informational signal (Chen et al., 2009).
Betting on the coachable entrepreneur
Entrepreneurs may also provide interpersonal signals that indicate the entrepreneur’s
behavioral style and ability to work with others (Huang & Knight, 2015). Examples of
interpersonal signals include entrepreneurial passion (Cardon & Kirk, 2015) and personal
commitment to the venture (Busenitz et al., 2005)1. Experienced investors often indicate these
are the more important type of signal (Huang & Pearce, 2015). Moreover, angels indicate they
make these assessments quickly, or as one angel put it, “within five minutes of meeting the
entrepreneur” (Huang & Pearce, 2015: 644). These types of signals are especially important to
capital providers during the early screening stages of new venture funding (Busenitz et al.,
We suggest that entrepreneurial coachability is an important interpersonal signal the
entrepreneur can convey. Coachability is unlike other signals in an important regard, however.
More static signals (such as market size, entrepreneur’s education, etc.) provide an indication on
what types of return can be expected on the investor’s financial resources. Coachability, in
addition to indications of financial returns, also provides an indication of what type of return
might be expected on the investor’s social resources (Huang & Knight, 2015). That is, more
coachable entrepreneurs will be perceived as those more likely to capitalize on the non-financial
resources (such as advice and connections) provided by the resource provider. But the resource
provider also recognizes that these returns can only be realized over time, and as long as the
coach continues to commit the social resources. In this regard, coachability is like a “flow”
signal, meaning that it provides an indication of underlying value that will require continual
1 An entrepreneur could also demonstrate financial commitment to the venture through his or her
own personal capital invested (Prasad, Bruton, & Vozikis, 2000), but this would be more of an
information signal.
Betting on the coachable entrepreneur
investment by the capital provider in order for that value to be realized. As such, these
relationships can be characterized as being governed by social exchange processes.
Social Exchange Theory
At its core, social exchange theory is about how potential entrants into a relationship
weigh the anticipated costs and benefits of the relationship (Blau, 1964; Homans, 1958).
Economic exchange involves short-term, discrete, financially-oriented transactions (Shore,
Tetrick, Lynch, & Barksdale, 2006). On the other hand, social exchange involves unspecified
obligations in which actors initiate exchange without knowing whether or to what extent their
counterparty will reciprocate (Molm, Takahashi, & Peterson, 2000). Relationships may evolve
over time into loyal, trusting, and mutual commitments (Cropanzano & Mitchell, 2005). On the
other hand, exchange relationships may fail to develop if initiated exchanges are not reciprocated
(Molm et al., 2000). Somewhat paradoxically, these exchange relationships are more likely to
form under conditions of greater uncertainty because these situations provide the requisite tests
of trust that foster relationship development (Kollock, 1994).
Central to these exchange processes is the development of trust between the parties and
each party’s assessment of the other party’s commitment to the relationship (Busenitz et al.,
2005; De Clercq, Dimov, & Thongpapanl, 2010). As noted by Huang and Knight (2015), these
relationships entail both instrumental and affective dimensions meaning that parties look to form
relationships that provide means to some other end (instrumental) as well as for the pleasure of
being in the relationship itself (affective). Exchange also involves both financial and social
resources (Cropanzano & Mitchell, 2005; Huang & Knight, 2015). Examples of the latter include
information, support and influence. In other words, someone may form a relationship with an
entrepreneur in order to reach some other end-goal (such as financial wealth) or for the sheer
Betting on the coachable entrepreneur
pleasure of working with the entrepreneur. The exchange may involve the counterparty
providing financial resources or social resources such as networks, information, or influence.
Coachability and Willingness to Invest
Given the nature of these exchanges between an entrepreneur and an investor, signals
play an important role in the early onset of these relationships. The entrepreneur’s level of
coachability should serve as a key signal regarding how the entrepreneur will approach these
social exchanges going forward. As mentioned previously, there is some limited empirical
evidence that coachability matters to angel investors (Mitteness et al., 2010). Studies have also
demonstrated the important coaching role that venture capitalists play in developing the ventures
that they have invested in (Baum & Silverman, 2004; Bertoni, Colombo, & Grilli, 2011). In this
role, venture capitalists provide mentoring and guidance that can positively impact the venture’s
performance (Hellman, 2000). Finally, in the mentorship literature there is also evidence that
protégé’s willingness to learn works as a signal to mentors regarding protégé selection (Allen,
Based on our theoretical arguments and the prior empirical results, we suggest that
coachability will act as a viable signal to potential investors – signaling an entrepreneur’s ability
to capitalize on both financial and social resources provided by the investor. Therefore,
we hypothesize the following:
Hypothesis 1: Perceived coachability is positively associated with willingness to
We next examine the moderating role of the coach’s level of previous coaching
experience on his or her willingness to invest in the venture. We argue that prior coaching
experience will positively moderate the influence of coachability on willingness to invest for
several reasons. As we argued previously an entrepreneur’s coachability can serve as an effective
Betting on the coachable entrepreneur
signal to the investor, increasing his or her willingness to invest in the venture. However, the
efficacy of signals is also contingent upon the receiver’s ability to detect them and the value
placed on them (Connelly et al., 2011). Coaches with higher levels of prior coaching experience
will be more attune during the pitching process to the observable behaviors that suggest
coachable entrepreneurs. Additionally, more experienced coaches are more likely to value
coachable entrepreneurs. Having undertaken coaching in the past, and having experienced the
challenges of advising entrepreneurs who are not coachable, or the positive experience from a
`working` coach-entrepreneur relationship, experienced coaches would appreciate the
importance of being coachable for an entrepreneur. Prior coaching experience will enable
coaches to make more informed decisions regarding the resources that they choose to commit to
a venture.
Some empirical evidence in the mentoring literature is consistent with our general causal
argument. Studies have examined the relationship between prior mentoring experience and
willingness to mentor in the future. Wang et al. (2009) found that more time spent with protégés
was negatively associated with willingness to mentor in the future. Although Ghislieri et al.
(2009) found a positive relationship between prior experience as a mentor and willingness to
mentor in the future, they also found that prior mentor experience increased the likelihood that
mentors would also see drawbacks to mentoring. Taken together, these empirical results suggest
that prior mentoring experience may make mentors more aware of both the potential positive and
negative outcomes associated with mentoring. With this heightened awareness, mentors may be
especially sensitive to signals – such as coachability – that would give early indicators of the
potential costs or rewards involved in a future relationship. Thus, based on our theoretical
arguments and these empirical results, increased coaching experience should make coaches
Betting on the coachable entrepreneur
especially sensitive to the financial and social returns they might achieve in any given investor-
entrepreneur relationship. Therefore, signals that can guide them in this regard should prove
especially effective. Based on these factors, we hypothesize:
Hypothesis 2: Prior coaching experience positively moderates the relationship
between perceived coachability and willingness to invest.
Next, we hypothesize about the moderating role of prior entrepreneurial experience.
Whereas individuals with prior coaching experience may rely on signals of coachability as an
indicator of the potential costs or rewards involved in a future relationship, individuals with prior
entrepreneurial experience may focus primarily on certain costs of the relationship. As such we
suggest that prior entrepreneurial experience leads investors to negatively value coachability. In
doing so we rely on several reasons. First, entrepreneurs tend to have high levels of confidence in
their own abilities, often to the point of overconfidence, which causes them to actually
overestimate their own abilities (Busenitz & Barney, 1997; Camerer & Lovallo, 1999;
Koellinger, Minniti, & Schade, 2007). This overconfidence is likely to diminish the value they
put on coaches. Second, entrepreneurs are also likely to attribute their own decision making style
to one that is largely based on intuition (Blume & Covin, 2011). Each of these factors –
overconfidence in their own ability and a belief that their entrepreneurial judgement was driven
by intuition – will tend to devalue a more coachable entrepreneur. That is, entrepreneurs that are
more coachable may be perceived as lacking the necessary abilities and judgment to successfully
launch and grow a new venture. Experienced entrepreneurs will be less willing to invest their
financial and social capital in a venture they see as less likely to succeed. Therefore, prior
entrepreneurial experience may actually lead them to place a lower value on coachability. Thus,
we hypothesize:
Betting on the coachable entrepreneur
Hypothesis 3: Prior entrepreneurial experience negatively moderates the
relationship between perceived coachability and willingness to invest.
Because there are no existing validated multi-item measures of entrepreneurial
coachability, it was necessary to develop and validate such a measure prior to testing our
hypotheses. To this end, the preliminary study described below uses data from several samples to
(a) generate the items for the scale; (b) evaluate the factor structure of the new measure; and (c)
present preliminary evidence of their convergent and discriminant validity. The Main Study
seeks to further confirm the psychometric properties of the new measure and to formally test our
To develop a reliable and content-valid measure of entrepreneurial coachability, we
followed recommended steps in developing a psychometrically sound measure (DeVellis, 2003;
Hair, Black, Babin, & Anderson, 2010; Hinkin, 1998). In this preliminary analysis we identify
potential items for our proposed measure and assess the items’ content validity. First, we develop
a valid construct definition (Schwab, 1980).
Construct Definition
To define our construct, we drew upon prior definitions of coachability, particularly that
of Mitteness et al. (2010), Giacobbi (2000), and Shannahan et al. (2013). Specifically, we looked
for consistencies and differences across these various definitions. Some broad similarities
include such themes as “openness to learning”, “intensity of effort” and “trust for the coach”. At
the same time, entrepreneurial coachability is distinct from its use in other domains. In particular,
entrepreneurial coachability is more than an ability to understand a playbook or follow specific
Betting on the coachable entrepreneur
directions. Entrepreneurs must exercise judgment under conditions of high uncertainty in order
to improve their venture’s performance.
To ensure face validity of our new construct, we approached a Service Corps of Retired
Executives (SCORE) organization based in the southeastern U.S. In partnership with the U.S.
Small Business Administration, SCORE is a nonprofit association with the goal of assisting and
promoting entrepreneurship and small business management through the provision of education
and mentoring services. Our contact agreed to put us in touch with their most experienced
coaches. We created a survey instrument (see below) that asked for the SCORE coaches’
opinions on the coachability construct. Our SCORE contact distributed our survey to 17 coaches
and 12 responded completely. The average age of these respondents was 65 and each one had
considerable leadership experience, both as executives of large organizations and startups.
Based on our review of the relevant literature and our fieldwork with the SCORE
coaches, we derived the following definition for entrepreneurial coachability: the degree to
which an entrepreneur seeks, carefully considers, and integrates feedback to improve his/her
venture’s performance. This definition captures the key elements of the construct. Willingness to
learn is evidenced in the entrepreneur seeking and integrating feedback. Intensity of effort is also
evidenced by seeking feedback (i.e., not just passively waiting for instruction). Respect is
evidenced through seeking feedback, but also by carefully considering that feedback. Finally, a
theme that emerged from our fieldwork was that, ultimately, the entrepreneur has to demonstrate
that he/he is committed to improving the performance of the venture.
Item Generation
In creating our coachability instrument we followed the general guidelines summarized
by Hinkin (1995) and adopted in practice by various researchers (Cardon, Gregoire, Stevens, &
Betting on the coachable entrepreneur
Patel, 2013; Carr, Cole, Ring, & Blettner, 2011). We began by compiling a list of 25 potential
indicators that represent behaviors associated with the coachability construct. We obtained these
indicators from measures in the mentoring (Noe, 1988), athletic coaching (Giacobbi Jr, 2000)
and marketing (Shannahan et al., 2013) literatures. We tailored the wording to be appropriate for
our context of entrepreneurship.
We presented these 25 items to the SCORE counselors and asked them to indicate how
well each item distinguished more coachable entrepreneurs from less coachable entrepreneurs
(please see the online appendix for details). We also provided the counselors the opportunity to
introduce any additional items that they felt were indicative of more coachable entrepreneurs.
From this process, we identified 14 items that generated the greatest consensus among the
counselors. We also incorporated an item “understands the challenges of the venture” that
counselors identified as being integral among coachable entrepreneurs.
Content Validity Assessment
To identify potential entrepreneurs that might vary in their level of coachability, we
selected sixty-nine clips from the U.S. television show Shark Tank (Maxwell et al., 2011;
Pollack, Rutherford, & Nagy, 2012). In this show, entrepreneurs pitch their ventures to potential
investors (who are known as the “Sharks”). We selected clips in which only a single entrepreneur
pitched the venture to eliminate any confusion or ambiguity associated with trying to evaluate
coachability among an entrepreneurial team.
Following scale development protocol (Hinkin, 1998), we then selected a naïve sample of
judges to evaluate these pitches. We recruited 168 undergraduate business students in a large
southeastern U.S. research university. We randomly assigned each of these students to one of the
69 videos. Following the clip, students were presented with each of the 15 coachability items and
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asked, on a 5-point scale, how strongly they agreed or disagreed with each statement. We first
conducted an exploratory factor analysis on the 15 items. The first factor accounted for 90% of
the variance in the items. Additionally, both scree and parallel analysis supported the retention of
a single factor. Therefore, there was no need to examine a rotated factor structure (Furr, 2011).
Given the results of the EFA, there was no indication that we necessarily needed to drop
items. However, looking at loadings and inter-item correlations, we decided that a more
parsimonious (i.e., fewer item) scale would be preferred. Therefore, we analyzed each of these
potential items according to several key metrics, including their factor loading, the communality,
the Kaiser-Meyer-Olkin (kmo) measure of sampling adequacy, and their item-scale correlations.
We also purposely wanted to ensure that we captured items that reflected each of the sub-
processes in our construct: seeking feedback; carefully considering feedback; and integrating
feedback to improve the venture’s performance. Based on this analysis, we chose 9 items that
spanned the construct definition and had more than adequate scale metrics. To assess whether the
dropped items were indicators of a separate dimension, in unreported analysis we compared the
fit statistics of a one-factor solution (i.e., one that includes all 15 items) against that of a two-
factor solution consisting of maintained and dropped indicators. The fit statistics (RMSEA, CFI,
TLI, and SRMR) are virtually identical. Therefore, we do not believe the dropped indicators
assess another dimension.
Instrument Validation
We next collected data from a different sample to further validate our measure.
Participants for the study were working adults recruited by students of a large southeastern
research university. Undergraduate business students were given extra credit if they recruited
working non-students located in the United States to complete the survey. As in the item
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generation part of the study, participants were randomly assigned to watch one of the 69 videos
and answer related questions. In total, 1,025 participants started the survey, 817 partially
completed it, and 774 fully completed it. The participants’ average age was 39.6 and they had an
average of 8.3 years of work experience.
Participants were asked to watch the video, then to rate various factors of the
entrepreneur pitching the venture. They used our 9-item scale to assess coachability. Participants
also provided their perceptions of the entrepreneurs’ passion and preparedness by completing the
6-item passion and 5-item preparedness measures developed by Chen et al. (2009). Table 1
presents the results of an exploratory factor analysis of the items in our coachability scale and the
passion and preparedness scales. As shown in the table, each indicator loads on the appropriate
factor, thus providing initial support for convergent and discriminant validity.
We use the main study to conduct further scale validation as well as to formally test our
Sample and Procedures
To build the sample for the Main Study we exclusively targeted individuals who had
experience working with entrepreneurs in a capacity that involves coaching (e.g. investor,
advisor, or mentor). We identified these individuals through their membership in particular
groups that are known for working with entrepreneurs. First, we approached two SCORE
chapters in the northeast of the U.S. (these were different SCORE chapters from the one used in
our preliminary study). Second, we recruited participants from the list of presenters at the 2015
VentureWell annual conference. VentureWell is a non-profit organization based in the U.S. that
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fosters and promotes technology commercialization on university campuses through its
membership of nearly 200 colleges and universities. Finally, to increase our confidence in the
generalizability of our data, we approached one of the largest angel networks in Turkey, whose
members have extensive experience in interacting with entrepreneurs in their capacity as
individual angel investors, venture capital fund managers, and managers of incubators,
accelerators, and technology parks. Before pooling the U.S. and non-U.S. based samples, we
conducted t-tests on their responses to the coachability and investment variables. The tests failed
to reject the null hypothesis that the means were different (p > .05). After pooling, our final
sample consisted of 48 participants. We tested for the presence of non-response bias by
comparing survey responses of early and later responders, assuming that later responders more
closely resemble non-responders (Armstrong & Overton, 1977). This analysis resulted in no
statistically different means (p > .05) of their respective measures on coachability and
willingness to invest.
All participants had prior experience interacting with entrepreneurs. Approximately 75%
had previously founded a business and 73% had previously invested in a startup, and 81%
characterized their coaching experience as moderate or extensive. Their average age was 48, they
had 18 years on average of supervisory experience and 73% were male.
We followed the same general procedure that we used in the preliminary study, except
that each participant viewed two of the Shark Tank videos, and therefore statistical analysis
consisted of 96 total observations. Following the presentation of each video pitch, participants
were asked a series of questions that captured their evaluations of coachability, personality
variables, and willingness to invest, as well as other relevant controls.
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Willingness to Invest. For our outcome measure, we modified Baron and colleagues’
(2006) measure regarding whether an entrepreneurial idea was worthy of financial investment.
Specifically, on a 5-point scale anchored by 1 = definitely no to 5 = definitely yes, we asked
participants, “Would you personally invest in this entrepreneur’s new venture?” and “Would you
personally recommend to other persons that they make an investment in this venture?”.
Coachability. After each video, participants rated the coachability of the entrepreneur
pitching the venture, using our 9-item scale.
Coaching Experience. All participants in this study had prior coaching experience.
Therefore, this measure captured whether this experience was minimal, moderate, or extensive
(1, 2, or 3 respectively).
Founder Experience. We created a dichotomous variable to capture participant’s prior
experience as a founder (1 = prior founder of a startup; 0 otherwise).
Big 5 Personality Variables. We used the ten-item personality inventory (TIPI),
developed by Gosling and colleagues (Gosling, Rentfrow, & Swann, 2003) and has been used in
other scale development work (Luthans, Avolio, Avey, & Norman, 2007). On a 5-point scale
from “strongly disagree” to “strongly agree”, participants were asked how well each of the 10
personality items (two items per trait) described the entrepreneur pitching the venture.
Passion and Preparedness. We used the same measures that we used in the preliminary
Competence. We included one item that asked the participants to rate the competence of
the entrepreneur pitching in the video (Todorov, Mandisodza, Goren, & Hall, 2005).
Other Controls. We controlled for the participants’ startup investment experience (1 =
invested in a startup; 0 otherwise), as well as their gender, age, education, and supervisory
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experience. To assess the underlying quality of the idea being pitched, we created an idea quality
control variable through the following steps. We edited the 69 video clips to the point just after
the entrepreneur gave the initial pitch. For those unfamiliar with the show, typically the
entrepreneur will provide an opening pitch of around one minute. This is followed by a question
and answer period, which may also involve negotiations over terms of the transaction (valuation,
equity percentage, etc.). To isolate only the underlying quality of the idea being pitched, we cut
each video just after the opening pitch so that participants did not see initial reactions and
comments of the judges, nor the question-and-answer or investment negotiation process, if any.
Prior to launching our main study with the experienced coaches, we distributed a survey
containing the 69 truncated video pitches to 92 undergraduate business students from a
university in the southeast of the United States. The 92 participants were provided an electronic
survey with 9 or 10 randomly generated Shark Tank videos from a pool of the 69 videos. Of
those 92, 83 fully completed the survey, and 6 partially completed the survey. In total, each of
the 69 videos was viewed and rated by an average of 11.6 participants. For our measure of idea
quality we adopted the measure used by Baron et al. (2006) to create a 3-item scale by asking the
students how practical the idea is, how clever it is, and what the overall quality of the idea is.
These same students also rated the entrepreneur’s attractiveness using a single-item measure
previously used by Cable and Judge (1997) that asked, “How attractive is the entrepreneur in the
video?”. Finally, the students were asked to provide an estimate of the entrepreneur’s age (Little,
Burt, & Perrett, 2006).
Preliminary Analyses
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Before testing our hypotheses, we conducted analyses to further validate our construct.
We designed our coachability measure to reflect a first-order latent factor. Therefore, we
conducted confirmatory factor analysis to validate this structure. The results of this analysis are
presented in Table 2. However, we also recognize that our conceptualization of coachability
comprises potential sub-processes such as seeking feedback, considering feedback, and
integrating feedback. Therefore, we used CFA to evaluate alternative factor structures. Because
theoretically derived three factor structures would require only two items on the third factor,
which exceeds the minimum of three items recommended by Hair and colleagues (2010), we
focused on one- and two-factor solutions. Results are presented in Table 2.
We compared model fit statistics against established cut-off points (Hooper, Coughlan, &
Mullen, 2008). Specifically, indications of good model fit include a root mean squared error
(RMSEA) < .07, standardized root mean squared residual (SRMR) < .05, Tucker-Lewis index
(TLI) > .95, and comparative fit index (CFI) > .95. As noted by Hu and Bentler (1999), when
sample sizes are small (as in this study) TLI and RMSEA are less preferable measures.
Therefore, we used their two-index presentation strategy (Ferris, Brown, Berry, & Lian, 2008;
Hu & Bentler, 1999), which suggests assessing model fit with SRMR and CFI. As shown in the
table, both of these fit statistics are within acceptable ranges. Therefore, we conclude that the
coachability measurement model provides a good fit with the data. However, we also examined a
two-factor solution in which we separated our coachability construct into the two subcategories
“Seek-Integrate” and “Consider” as indicated in Table 2. We did this by placing those indicators
more closely aligned conceptually into the appropriate factor, while also maintaining at least
three indicators in each factor, the minimum number recommended by Hair and colleagues
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(2010). As shown in the table, the fit indices for the two-factor model compare favorably to those
of the one-factor model. Because theoretically coachability represents a single factor, we adopted
the composite approach by averaging across subscales. Some examples of other constructs that
have been operationalized this way include psychological capital (Luthans, Norman, Avolio, &
Avey, 2008), job satisfaction (Meyer, Paunonen, Gellatly, Goffin, & Jackson, 1989), and
negative mood (Kahler et al., 2002). For our coachability composite, all four responses for the
seek-integrate and all five responses of the consider subscales were summed and averaged to first
get a subscale composite average for each of the two subscales. The averages for each of the
subscales were then added and averaged to create an overall composite coachability measure for
each respondent’s coachability ratings. In regression results that follow later, we used this
composite coachability measure.
Using the definitions of Mullen et al. (2009), convergent validity requires that items
measuring the same construct are associated with the construct and is measured by the degree to
which items that measure the same underlying construct share common variance. Discriminant
validity concerns the degree to which the construct is distinct from other similar constructs and
nomological validity is concerned with the degree to which the construct is associated with other
causally related constructs. Results of our convergent and divergent validity analysis are
presented in Table 3. To examine convergent validity we conducted confirmatory factor analysis
to calculate the average variance explained (AVE), which is computed as the total of all squared
standardized factor loadings divided by the number of items. The AVE for the coachability
construct is .51, which exceeds the .50 minimum criterion for an indicator of good convergence
(Hair et al., 2010).
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To assess discriminant validity, we compared the AVE of coachability with other
constructs as well as the square of the correlation between coachability and the other constructs.
As explained by Hair et al. (2010) the logic behind this analysis is based on the idea that a latent
construct should explain more of the variance in its item measures than it shares with another
construct. As shown in Table 3, we specifically compare coachability against the related
constructs of passion and preparedness. Results suggest that coachability has little overlap with
these other constructs, thus our construct demonstrates good discriminant validity.
To examine nomological validity and relationships with constituent constructs (Newman
et al., 2016), we regressed coachability on the personality variables and a set of control variables.
We chose to regress coachability on the Big 5 personality variables given their importance in
entrepreneurship research (Miller, 2015; Zhao & Seibert, 2006; Zhao, Seibert, & Lumpkin,
2010) as well as evidence of their relationships with coachability in the athletics literature
(Favor, 2011; Piedmont et al., 1999). Additionally, we consider coachability to be a state-like
construct (Luthans et al., 2007), i.e. more open to development compared with trait-like
constructs such as the Big 5 but not fleeting like momentary states such as happiness.
Table 4 presents the summary statistics and correlation matrix of the variables used in the
Main Study. As shown, some of the reliabilities (coefficient alphas) were low for some of the 2-
item personality measures, which is not uncommon for these particular measures (Gosling et al.,
2003; Luthans et al., 2007). However, we only used these variables to establish nomological
validity and not for our hypothesis testing. Because each participant watched two videos, for the
regressions we used the VCE cluster option in Stata (Rogers, 1994).
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Table 5 presents the nomological validity regression. As shown in the model, openness to
experience (β = .39, p < .01) and agreeableness (β = .35, p < .01) are positively associated with
coachability and neuroticism is negatively associated with it (β = -.24, p < .01). The relationships
between agreeableness and neuroticism and coachability are consistent with those found in the
athletics literature (Favor, 2011; Piedmont et al., 1999). Interestingly, our findings do not
demonstrate a relationship with conscientiousness as has been established in the athletics
literature but do demonstrate an association with openness to experience.
Hypothesis Testing
Before presenting the results of our regression analyses, we examined the data for
potential issues arising from common methods variance. Using Harman’s single factor test, we
found the largest single factor only accounted for 47% of the variance. We examined this issue
further using the latent methods factor approach (Podsakoff, MacKenzie, Lee, & Podsakoff,
2003). For the model to converge, we constrained all paths from the method factor to be equal. A
chi-squared difference indicated the model with the latent methods factor provided better fit to
the data [! 2 (1) = 50.36, p < .001]. Therefore, we conducted the following additional analyses.
First, we examined the change in path coefficients between the two models. The average
difference in path coefficients between the model with the latent methods factor and the one
without it was only .10. Next, we performed the variance partitioning technique (Williams, Cote,
& Buckley, 1989). The average amount of variance attributed to the method factor was 11%,
well below the average of 49% attributed to the theory factors, and well below the average of
25% observed by Williams et al. (1989). Based on the results of these tests, the likelihood of
common methods bias appears minimal.
Betting on the coachable entrepreneur
Turning to theory testing, Table 6 presents the results of our hypothesis testing
regressions. In Model 1, we regress coachability on the control variables. As would be expected,
the entrepreneur’s competence and level of preparedness is associated with willingness to invest.
As in prior research (Chen et al., 2009), the level of passion does not influence the willingness to
In Model 2 we include our coachability variable. As shown, coachability explains an
additional 4% of the variance in willingness to invest and its effect is statistically significant (β =
.38, p < .05). Thus, Hypothesis 1 is supported. In Model 3, we add the interaction terms. As
shown, the coaching experience by coachability interaction is significant (β = .31, p < .05); thus
Hypothesis 2 is supported. The founder experience by coachability interaction is not significant
(β = .21, ns); thus Hypothesis 3 is not supported. To facilitate interpretation of the significant
interaction, we conducted a simple slopes analysis as presented in Figure 1. As shown, highly
experienced coaches react to the entrepreneur’s level of coachability but less experienced
coaches do not, thus providing further support for Hypothesis 2.
Implications for Research
Entrepreneurial coachability is often discussed among practitioners in the
entrepreneurship community, but to date has garnered limited attention in the academic
literature. This is surprising, given how important the coaching function is for venture success,
especially for professionally funded ventures (Baum & Silverman, 2004). In this study, we
highlight the importance of this important construct and the role it plays in the entrepreneurial
Betting on the coachable entrepreneur
process. To the best of our knowledge, this is the first study to develop a formalized
conceptualization and operationalization of entrepreneurial coachability. Over a series of studies
we followed the best practices in scale development and validation (Hinkin, 1995) to establish
the validity of our proposed 9-item coachability scale.
In establishing the nomological validity of our construct, we found that perceptions of
agreeableness were positively associated with perceptions of coachability and neuroticism was
negatively associated with it – results that are consistent with those found in the athletics
literature (Favor, 2011; Piedmont et al., 1999). However, unlike the athletics literature, our
results indicate that openness to experience may be more associated with coachability than with
conscientiousness. This finding is consistent with our notion that the entrepreneurial context with
high levels of uncertainty will require coachable entrepreneurs to go beyond conscientiously
following a scripted playbook. Importantly, our study demonstrates that perceptions of
coachability are distinct from perceptions of these Big-5 personality traits.
Overall, our study contributes to research in both social exchange and signaling theories.
Although social exchange has a long established tradition in the social sciences (Blau, 1964;
Homans, 1958), its applications in the entrepreneurial context has been somewhat limited. The
lack of research using this perspective is puzzling given the aspects of the entrepreneurial
process in which both economic and social exchange take place, particularly in investor-
entrepreneur relationships. In our study, we emphasize entrepreneurial coachability as a bridge
between these two types of exchange. That is, a relationship between an entrepreneur and an
investor clearly involves economic exchange in which the entrepreneur gives up an ownership
stake in the company in exchange for financial capital. Indeed, this is generally seen as the role
of informational signals in which each party attempts to overcome information asymmetries in
Betting on the coachable entrepreneur
this type of exchange. However, by integrating social exchange with signaling perspectives, our
study reinforces the social component of these relationships as well. That is, capital providers are
more willing to seek financial returns with entrepreneurs whose coachability positions them to
generate returns on the non-pecuniary resources the investor contributes to the relationship.
Additionally, our study provides a new understanding of how social exchange processes can
begin. Although social exchange is seen as taking place over an extended period of time, our
study indicates that potential investors appear willing to make bets on these entrepreneurs based
on very preliminary and cursory interactions. Thus, coachability serves as a key factor in the
path-dependent process in which exchange relationships either develop and flourish or die on the
pitch room floor.
In terms of signaling, our study emphasizes the role of entrepreneurial coachability as an
important signal in regard to raising capital (MacMillan et al., 1986; Maxwell et al., 2011;
Mitteness et al., 2012). During the pitch, entrepreneurs provide both information signals, which
convey the underlying quality of the venture and their own abilities (Ahlers et al., 2015; Chen et
al., 2009; Eddleston et al., 2014) and interpersonal signals, which convey insights into how
committed the entrepreneur is (Busenitz et al., 2005) as well as how well the entrepreneur works
with others (Huang & Knight, 2015). In this study, we suggest that entrepreneurial coachability
is an important interpersonal signal worth investigating. We demonstrate that this signal
influences potential investors above and beyond other signals the entrepreneur may wish to
convey, such as passion, preparedness, and competence. In their important early work,
MacMillan and colleagues suggested that one role of the business plan is to demonstrate that the
“jockey is fit to ride” (MacMillan et al., 1986: 119). This view implies that the entrepreneur
comes to the relationship with a fixed set of skills, knowledge and capabilities, which is very
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consistent with the static information signals perspective that receive so much attention in the
literature. But we know that investors do not expect to simply put the jockey on the horse and let
them loose (Baum & Silverman, 2004). Rather, they expect to take an active role in shaping the
course taken. In this regard, coachability serves as a “flow” signal in that it provides an
indication of where the horse and jockey might go, but not without the continued investment of
social resources by the investor. Thus, these more coachable entrepreneurs may be preferred for
two key reasons. For one, they may be seen as offering higher potential financial rewards. But,
perhaps more importantly, they may also be seen as offering a higher expected return on the
coach’s non-financial resources such as time, energy, and emotion that is invested in the
relationship, and by extension, to the venture.
Our study also contributes to a broader understanding of signaling theory by highlighting
that a signal’s impact is conditional on certain characteristics of the receiver (Connelly et al.,
2011). Specifically, our results are consistent with our theory that potential investors with more
prior coaching experience are more likely to notice and value the coachable entrepreneur. We did
not find support for our hypothesis that potential investors with prior entrepreneurial experience
would place a lower value on the coachable entrepreneur. We suspect that the relationship
between prior entrepreneurial experience and perceptions of coachability is more nuanced than
we depicted. For example, on the one hand, prior experience may lead to the perception that
coachable entrepreneurs are less capable, as we suggested. Alternatively, prior entrepreneurial
experience may work through mechanisms similar to those of prior coaching experience in
which it fosters a greater awareness of and positive view towards the coachable entrepreneur.
Clearly, more research should be directed towards understanding this complex relationship.
Limitations and Suggestions for Future Research
Betting on the coachable entrepreneur
Like all studies, ours has certain limitations. First, in establishing the nomological
validity of the new construct we examined the association between perceptions of personality
traits and coachability. Although perceptions of personality traits are highly correlated with self-
reported personality traits (McCrae & Costa, 1987) future researchers may want to examine the
relationships between personality traits (as measured at the entrepreneur level) and coachability
assessments (as measured at the coach level), as well as other antecedents of coachability.
Second, we focused on potential investors’ willingness to invest rather than on actual funding
outcomes. Given the importance of coachability to venture investors, assessing the impact of
coachability across discrete funding settings (e.g., crowdfunding, venture capital settings) could
extend both the entrepreneurship and social exchange literatures. Moreover, examining the link
between coachability and venture performance using a longitudinal design could provide
valuable insight with regard to the long-term value of coachability. Additionally, the influence of
coachability may be conditional on contextual factors or individual differences of the
entrepreneur or stakeholder beyond what we studied. For example, future research could be
directed towards examining if the impact of coachability on funding outcomes varies across
investment stages (Petty & Gruber, 2011). Lastly, throughout the paper we suggest that
coachability can serve as a viable signal. In doing so, we explicitly assume that it is not
something an entrepreneur can fake through “cheap talk” (Farrell & Rabin, 1996). Certainly,
further research should be directed towards examining this critical assumption.
Implications for Practice
Our finding that coachability has predictive power on funding outcomes, above and
beyond competence, passion, and preparedness has important implications for entrepreneurs
pitching to a professional investor. That is, much of entrepreneurship education provides students
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with skills and capabilities to improve their overall competence in this domain as well as to be
better prepared in a pitch setting. These skills are important, but may also imply that the overall
process is highly generic, mechanistic, or objective. Our research highlights the subjective,
interpersonal, and perceptual nature of this process. Therefore, in addition to teaching students
that they should be passionate and prepared when pitching their venture, we should also teach
them the importance of being coachable. Moreover, we demonstrate that this is particularly
important when they are pitching to experienced coaches.
Entrepreneurial ventures are inherently risky. Investors and other stakeholders face the
daunting task of trying to scrutinize the merits of a potential opportunity. In addition to financial
capital or other resources, stakeholders are frequently expected to contribute their time and
knowledge to the ventures they support. Thus, in making these investments, they are seeking
returns on both their financial and social resources. Our research suggests that coachable
entrepreneurs are perceived as being better positioned to generate both of these returns.
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Table 1: Preliminary Study Exploratory Factor Analysis
Factor 1
Factor 2
Factor 3
Trusts the investors' expertise.
Genuinely considers feedback.
Wants to learn.
Exhibits a genuine respect for the investors
Appears attentive when receiving feedback.
Proactively seeks help and advice.
Is genuinely committed to improving the venture.
Understands the challenges of the venture.
Does not get upset or angry when given corrective feedback.
The entrepreneur had energetic body movements.
The entrepreneur had rich body language.
The entrepreneur showed animated facial expression.
The entrepreneur used a lot of gestures.
The entrepreneur’s face lit up while talking.
The entrepreneur talked with varied tone and pitch.
The presentation content had substance.
The presentation was thoughtful and in-depth.
The presentation was coherent and logical.
The entrepreneur articulated the relationship between the
business plan and the broader context.
The entrepreneur cited facts to support key arguments.
Note: Blanks represent abs(loading)<.3)
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Table 2: Main Study Factor Structure Comparison
Factor / Item
Seek - Integrate
Wants to learn.
Proactively seeks help and advice.
Is genuinely committed to improving the venture.
Understands the challenges of the venture.
Trusts the investors' expertise.
Genuinely considers feedback.
Exhibits a genuine respect for the investors
Appears attentive when receiving feedback.
Does not get upset or angry when given corrective feedback.
Fit Indices
! 2
df, degree of freedom; RMSEA, root mean squared error of approximation;
CFI, comparative fit index; TLI, Tucker-Lewis index;
SRMR, standardized root mean squared residual
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Table 3: Construct Convergent and Divergent Validity
Note: Diagonals are AVE; numbers below diagonal are correlations
and numbers above diagonal are squared correlations
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Table 4: Main Study Summary Statistics and Correlations
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Table 5: Coachability Regression Analysis
DV: Entrepreneurial Coachability
Coach gender
Coach age
Coach supervisor experience
Coach education
Coach startup experience
Coach founder experience
Coaching experience
Entrepreneur extraversion
Entrepreneur open to experience
Entrepreneur agreeableness
Entrepreneur neuroticism
Entrepreneur conscientiousness
R 2
Adj. R 2
* p < .05; ** p < .01; *** p < .001.
Regression coefficients; Robust standard errors in parentheses.
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Table 6: Willingness to Invest Regression Analysis
Model 1
Model 2
Model 3
Coach gender
Coach age
Coach supervisor experience
Coach education
Coach startup experience
Coach founder experience
Coaching experience
Entrepreneur competence
Entrepreneur age
Entrepreneur attractiveness
Idea Quality
Entrepreneur passion
Entrepreneur preparedness
Entrepreneur coachability
Coaching experience X Coachability
Founder experience X Coachability
R 2
Adj. R 2
* p < .05; ** p < .01; *** p < .001.
Regression coefficients; Robust standard errors in parentheses.
Interaction terms centered in Model 3.
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Figure 1: Coaching experience X Coachability Interaction
Low Coachability High Coachability
Willingness to Invest
Low Coaching
High Coaching
... For investors, as signal receivers, the effectiveness of signals is moderated by environments, such as the industry of the new venture (Hsu, 2007) or the regulations in the new venture's country of origin (Bell et al., 2012). Furthermore, different investors interpret the same signals differently; patents are interpreted differently by backers in reward crowdfunding versus investors in equity crowdfunding (Scheaf et al., 2018), and signals about coachability evoke different interpretations by experienced versus unexperienced business angels (e.g., Ciuchta et al., 2018). ...
... We advance the conversation about both signal receiver characteristics and the signaling environment, which both are under-researched concepts in signaling theory (Connelly et al., 2011). Entrepreneurship research on receivers of venture quality signals tends to focus on investors and how investors interpret signals, such as in relation to their specific knowledge, understanding, and attention (Ciuchta et al., 2018;Scheaf et al., 2018;Steigenberger & Wilhelm, 2018). We introduce ECFPs as (previously neglected) signal receivers that do not invest themselves but act as mediators. ...
... Yet a variety of additional signals also might be relevant for ECFPs. For example, entrepreneurial passion and other soft skills by entrepreneurs (e.g., Ciuchta et al., 2018), presentation quality (Scheaf et al., 2018), or language signals conveyed on the pitch decks (Anglin et al., 2018) are relevant for other entrepreneurial finance players. Continued research might expand the sets of quality signals and consider potential interaction effects among them. ...
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Among the new ventures actively seeking funds through equity crowdfunding, only a lucky few seemingly survive the rigorous selection process imposed by equity crowdfunding platforms (ECFPs). With a conjoint experiment involving decision-makers from 50 platforms in 22 countries , this study provides first quantitative evidence regarding how ECFPs actually use quality signals to select new ventures to start fundraising campaigns. The ECFPs interpret signals differently , depending on whether they impose a co-investment requirement or generate revenues from new ventures' long-term performance. The effectiveness of the signals also is contingent on the applicant's industry background and the signals' accessibility in the country where the ECFP operates.
... Broadly, our findings show how the initial nature of entrepreneurs' identities shapes how they engage in IFS, from why they seek feedback to how they respond to challenges and change their IFS strategies. Additionally, it is also possible that the trajectories identified here can apply to other entrepreneur groups beyond SEs, such as novice entrepreneurs experimenting with and elaborating a provisional entrepreneur identity (Demetry, 2017), or those attempting to portray an image consistent with that expected by stakeholders (Fisher et al., 2017), for instance the image of a coachable entrepreneur to obtain VC investment (Ciuchta et al., 2018). ...
... Previous research has demonstrated how entrepreneurs' IFS can be seen positively by investors (Ciuchta et al., 2018;Warnick et al., 2018). In line with these findings, our research shows that entrepreneurs seek feedback as a symbolic action (Zott and Huy, 2007), aware of the expectations of different audiences. ...
... While past research focused on how IFS may be positively perceived by audiences (Ciuchta et al., 2018;Warnick et al., 2018), the SEs in our study offered a more nuanced perspective. They highlighted the importance of also considering the potential negative meanings that audiences can draw from entrepreneurs' IFS-a sign of weakness and incompetence or "pestering" and "annoying." ...
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This study advances understanding of interpersonal feedback seeking as a relational micro-foundational process whereby social entrepreneurs proactively involve others in venturing and engage in sensemaking when this fails. Our inductive analysis of 82 interviews with 36 social entrepreneurs reveals the agency in and the plurality and precariousness of feedback seeking by identifying three distinct feedback-seeking trajectories. Feedback seeking is an identity-driven process whereby how and why social entrepreneurs seek feedback depends on their psychological closeness to the targeted social issue. Our study elucidates the relationship between identity and feedback processes and uncovers psychological distance from the social issue as a new construct in social venturing.
... Initial research suggests the willingness of an entrepreneur to accept feedback and engage with suggestions influences whether angel investors recommend moving forward after a pitch (Balachandra, Sapienza and Kim, 2014;Mitteness, Sudek and Baucus, 2010). Consistent with this, Ciuchta, Letwin, Stevenson, McMahon and Huvaj (2018) found that an entrepreneur's coachability related positively to an investor's willingness to invest. ...
... We found that coachability is positively related to the venture's actual progress. In addition, considering that the ability to attract social or financial investment is critical for founders, we focused on whether mentors would personally invest or recommend other people to invest in the venture (Ciuchta et al., 2018). We found that indeed coachability was related to a willingness to invest. ...
... The coachability of an entrepreneur is critical and possibly the most important criterion that investors look for when making investment decisions (Ciuchta et al., 2018). Consequently, our study, as well as practical advice from mentors (Inam, 2017), leads to several key suggestions for entrepreneurs to consider for improving their coachability and their mentorship experience. ...
Mentorship from other experienced individuals has become essential to entrepreneurs and their fledgling ventures, particularly in today’s accelerators. However, even with the acknowledgment that mentoring and coaching improve an entrepreneur’s likelihood of success, we know very little about the nuances of mentor-mentee relationships or the individual characteristics important to an entrepreneur’s coachability. Therefore, we examined mentors and founders across entrepreneurial support organizations to investigate the factors that influence an entrepreneur’s coachability, how coachability translates to venture outcomes, and whether or not the mentor-mentee relationship met the entrepreneur’s expectations. We found that entrepreneurs that are more coachable are ultimately more successful during their time in these programs and are more satisfied with their mentorship experience. This article provides insights for the leaders of accelerators to improve mentorship opportunities and suggestions for entrepreneurs to improve their coachability.
... Docility also acts as a mechanism for the social exchange of aid and resources through mentoring, teamwork, coaching, and deep collaboration; learning, and giving and accepting advice are its central elements (McMillan, 2016a). All of these behavioral aspects are relevant in the context of how stakeholders interact with entrepreneurs in the early stages of new venturing and, therefore, are of particular significance in business incubation (see Ciuchta et al., 2017;Scarbrough et al., 2013;Vedel and Gabarret, 2014). ...
... Her responsiveness made Incubatee-2 feel like she now had a choice in the process. Unlike a reliance on initial impressions (Ciuchta et al., 2017), the behavioral expression of docility in the form of responsiveness enables coaches to tweak procedures so that they are better suited to the needs of individual entrepreneurs. Hence, we make the following proposition: ...
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The business incubation process evolves through coach-incubatee interactions rather than merely institutional intervention. We contribute to a behavioral understanding of this process by exploring the determinants and expression of docility, a fundamental human behavior. Our findings suggest that business coaches’ perceptions of stakeholder value creation needs and their experience of incubatees’ proactive behavior are essential determinants of coaching behavior. These behavioral determinants lead coaches to place idiosyncratic expectations on and become responsive to incubatees, and this is reflected in the range of their interventions in new venture creation. From a behavioral perspective, the outcome of coaches’ interventions is a shared understanding of how to navigate the ambiguous and uncertain aspects of new venturing. Adopting a behavioral approach thus helps us to reframe business incubation—previously regarded to be a structured process—as a flexible process, more accurately capturing its role in facilitating the highly uncertain process of new venture creation.
... Combinatory resource mobilization relates to the notion of bootstrapping as it allows entrepreneurs to minimize external financial needs (Ebben and Johnson, 2006;Winborg and Landström, 2001) by striving to mobilize as many of the required non-financial resources directly instead of raising money to acquire these. While extant literature has discussed how entrepreneurs can obtain important non-financial resources such as knowledge or access to networks from formal (Ciuchta et al., 2018;Huang and Knight, 2017) and informal (Kotha and George, 2012;Murray et al., 2020) resource providers, our study sheds light on voluntary workforce as an often neglected but extremely valuable type of human resource (Welter et al., 2018) entrepreneurs can mobilize from communities to significantly reduce their financial resource requirements. Looking at the activities that lead to successful combinatory resource mobilization, we found that entrepreneurs must not only make a case for their business and create a sense of identification, but must additionally engage in activities targeted towards diversification of community involvement and towards creating a sense of ownership. ...
... Importantly, in relation to the 'how' of resourcefulness, our study hints at the potential of mobilizing human capital which can have a multiplier effect. Although human capital mobilization has been extensively discussed in the literature, such studies mainly look at how entrepreneurs can acquire missing knowledge, expertise and experience (Ciuchta et al., 2018) and literature expects that entrepreneurs must raise additional funds to pay for workforce. The few studies that have reported that entrepreneurs were able to mobilize human resources in the form of voluntary workforce, usually assume that this happens out of a necessity-and usually only in the context of social entrepreneurship (Haugh, 2007;Zahra et al., 2009). ...
In this study, we move beyond the predominant focus entrepreneurship researchers have put on the acquisition of financial capital from professional investors by exploring how, and with what effects, entrepreneurs can mobilize all required resources—financial, human, physical, and social—from local communities. Our temporal analysis of the resource mobilization processes of seven cases of community-based enterprises (CBEs) reveals four sets of activities with distinct goals and effects, which explain how entrepreneurs can meet or even exceed their resource mobilization goals by mobilizing a greater variety of resources from a broader base of resource providers. Importantly, the findings show how entrepreneurs can achieve a multiplier effect meaning that they can perpetuate the inflow of significant amounts of unsolicited resources by continuously engaging in activities targeted at creating a sense of identification and ownership, which require comparatively little extra effort and resource inputs. We synthesize our findings in a framework of community resourcefulness in new venture creation. This framework adds a new perspective of resourcefulness as “getting more from many,” and demonstrates that resourceful behavior is not necessarily about individuals' ability to respond to situational constraints but also about their ability to recognize and seize situational resource potentials. Our findings have important implications for our understanding of resourcefulness in entrepreneurship and the nascent body of literature on community-based enterprises.
... Similarly, Davis et al. (2017) examined investors' perceptions and found that the indirect effect of product creativity is contingent on the extent to which funders perceive an entrepreneur to be passionate. Moreover, Ciuchta et al. (2018) examined the effect of the entrepreneur's coachability on a potential investor's willingness to invest. Our analysis extends these prior studies by examining failures and challenges in the implementation stage after the entrepreneurs have successfully raised funds and met their funding goals. ...
... Similarly, Davis et al. (2017) examined investors' perceptions and found that the indirect effect of product creativity is contingent on the extent to which funders perceive an entrepreneur to be passionate. Moreover, Ciuchta et al. (2018) examined the effect of the entrepreneur's coachability on a potential investor's willingness to invest. Our analysis extends these prior studies by examining failures and challenges in the implementation stage after the entrepreneurs have successfully raised funds and met their funding goals. ...
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Purpose This conceptual paper focuses on a common observation in the implementation stage of reward-based crowdfunding (RBC) – entrepreneurs' failures and delays in delivery of rewards to investors, which, in turn, may be perceived as violations of reward delivery obligations. Design/methodology/approach Drawing on entrepreneurial personality theory and psychological contract theory, this paper develops propositions and identifies factors related to both entrepreneurs (overconfidence and narcissism) and factors related to investors (types of motivators and psychological contracts) that may explain the perceived violations of reward delivery obligations. Implications for theory and practice are also discussed. Findings The theoretical analysis, by wielding two independently developed literatures, has demonstrated that it is important to investigate factors that are related to both investors and entrepreneurs in understanding issues and challenges at different stages of the RBC model. The authors believe that the current analysis provides an integrated understanding and a solid foundation for researchers to further examine these issues by empirically testing these propositions. Originality/value The authors examined two previously understudied psychological factors in the context of RBC – entrepreneurial traits, mainly overconfidence and narcissism, and the type of psychological contracts formed between investors and entrepreneurs, both of which, according to McKenny et al. (2017), need greater attention from researchers studying crowdfunding.
... Future researchers should consider collecting more diversified data of actors involved in each start-up. Concretely, access to more fine-grained information of founders would allow us to understand why they edit their pitches as well as how sensitive or coachable they are to the feedback provided by mentors, as this attribute has been shown to be crucial for investment decisions [44][45][46]. With these data we could better understand why mentors believe that founders accept or resist changes. ...
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Background: After a six-month training program in the Chilean public accelerator Start-Up Chile, entrepreneurs are asked to update a short pitch they wrote in the submission stage to appear in the program's online portfolio. Literature review: We reviewed relevant literature related to the pitch as well as research aiming to track changes within pitches. Research questions: 1. Which are the editing strategies used to change their pitch? 2. Do these strategies conform to specific discursive patterns? Research methodology: To answer the research questions, we designed an exploratory qualitative study to describe in depth the editing strategies used by two generations of startups, corresponding to 148 pairs of written pitches. In order to contextualize the results, we conducted two interviews with the program managers and analyzed the accelerator's official Playbook and Technical and Administrative Requirements. Results: We identified 10 editing strategies. Of those editing strategies, “Deleting technical descriptions” is by far the most common procedure. The identified patterns can be classified into two groups, those simplifying, hedging, and focusing on certain elements of the first pitch, and those adding and specifying information of the first version. Conclusions: We conclude by discussing the strengths of this methodological approach for understanding such edits and for supporting successful edits in accelerator programs, as well as the potential for better understanding entrepreneur coachability.
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Research summary We meta‐analyze the structural relationship between human capital, the ability to generate new venture ideas and the favorability of opportunity beliefs to address divergent theoretical predictions and inconsistent empirical findings. We test a two‐stage process model of entrepreneurial opportunity identification, distinguishing between the ability to generate new venture ideas and the favorability of 3rd and 1st‐person opportunity beliefs. We also distinguish between two categories of human capital: general and specific human capital. Our results suggest that general and specific human capital are positively associated with the ability to generate new venture ideas. Furthermore, only specific human capital matters in influencing the favorability of opportunity beliefs, yet the ability to generate new venture ideas is far more important than human capital for the favorability of opportunity beliefs. Managerial summary How does an individual's human capital relate to the attractiveness of opportunities identified? In this study we review the body of literature on this topic and analyze the relationships between two types of human capital – general and specific human capital, the ability to generate new venture ideas, and the attractiveness of opportunities. We find that both general human capital – primarily education and work experience – and specific human capital – industry and entrepreneurial experience – are useful for generating new venture ideas. However, only specific human capital is useful when assessing which new venture ideas can turn into attractive opportunities. We also find that the ability to generate new venture ideas is more strongly associated with the attractiveness of opportunities than either type of human capital. This article is protected by copyright. All rights reserved.
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The paper’s principal purpose is to present the original concept of the project supply chain’s entrepreneurial management. Based on the literature on the subject, one defines the entrepreneurial management concept showing the influence of entrepreneurial management on company operation. Moreover, the paper also outlines the most important concepts of the project supply chain and presents the functioning scheme. Theoretical considerations concerning contemporary theories of entrepreneurial management and project supply chain are the prelude to presenting the concept of entrepreneurial management. The presented approach can be found helpful for the effective management of the project supply chain, which has not yet been thoroughly defined. It should be mentioned that the designed model of the entrepreneurial supply chain management is an original proposal for the paradigm of project supply chains. Both in a classical and project supply chain, a significant role is given to the flow of material resources between the individual chain components. It determines that the project supply chain is mainly driven by the need for its members’ value increase. It was explained that regarding entrepreneurial competences, knowledge can be transferred to other organizations in the whole supply chain. It was also mentioned that the project supply chain’s entrepreneurial management takes into account the flexibility manifesting itself through the establishment of agile project teams, and by focusing on human relationships. It is the basis for the presented concept of the entrepreneurial management model of the project supply chain. AcknowledgmentThe project is financed within the framework of the program of the Minister of Science and Higher Education under the name “Regional Excellence Initiative” in the years 2019–2022; project number 001/RID/2018/19; the amount of financing PLN 10,684,000.00.
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We review the practice of building new psychological constructs by combining older constructs (a process we refer to as construct mixology), with a focus on the impact, methodology, and substantive knowledge implications of this practice. Our review suggests that some of the most influential micro-level constructs in the field of management are either new compound constructs or old constituent constructs that have been used in some form of mixology. Further, we review a range of methodological approaches that researchers have employed when conducting construct mixology over the last 30 years. These strategies range from disavowing the role of the constituent constructs to explicitly acknowledging and modeling the relationships between constituent constructs and their corresponding (superordinate) compound constructs. The scientific consequences of these approaches are then summarized, and include both unrecognized redundancy (reinventing the wheel, or confirming classic findings without realizing it) and heightened explanatory power (resulting from using broad compound constructs). To further illustrate the variation of methods and implications, we review several exemplars of compound constructs that have enjoyed popularity in the fields of OB and HR, including work engagement, emotional intelligence, organizational commitment, and core self-evaluations. Prescriptions for future construct mixology efforts are provided.
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We develop a theoretical model, grounded in exchange theory, about the process through which relationships between entrepreneurs and investors develop and influence the growth of new ventures. Our theory highlights the multifaceted relationships that entrepreneurs and investors share—comprising both affective and instrumental dimensions—and the bidirectional exchanges of social and financial resources that build these relationships over time. An exchange theory perspective sheds light on the emergence of different patterns of relationship development over time and how different kinds of resource exchange contribute to new venture growth, contingent on the core problems that a venture faces at a given stage of development. We discuss implications of an exchange perspective on resources and relationships in entrepreneurship for theory, research, and practice.
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Using an inductive theory-development study, a field experiment, and a longitudinal field test, we examine early-stage entrepreneurial investment decision making under conditions of extreme uncertainty. Building on existing literature on decision making and risk in organizations, intuition, and theories of entrepreneurial financing, we test the effectiveness of angel investors’ criteria for making investment decisions. We found that angel investors’ decisions have several characteristics that have not been adequately captured in existing theory: angel investors have clear objectives—risking small stakes to find extraordinarily profitable investments, fully expecting to lose their entire investment in most cases—and they rely on a combination of expertise-based intuition and formal analysis in which intuition trumps analysis, contrary to reports in other investment contexts. We also found that their reported emphasis on assessments of the entrepreneur accurately predicts extraordinarily profitable venture success four years later. We develop this theory by examining situations in which uncertainty is so extreme that it qualifies as unknowable, using the term “gut feel” to describe their dynamic emotion-cognitions in which they blend analysis and intuition in ways that do not impair intuitive processes and that effectively predict extraordinarily profitable investments.
We explore a well-known instance of fast decision making under high uncertainty, venture capital (VC) opportunity screening. We analyze a sample of 722 funding requests submitted to an American VC firm and evaluate the influence of the form of the submission and content of business planning documents on VC funding decisions. We improve on prior literature by a) using a large sample of known representativeness, b) relating request characteristics to actual VC decisions, and c) developing an inferential logic that takes account of the multiple sources of information to which VCs have access. We find that the presence of planning documents and some information contained therein are weakly associated with VC funding decisions. Based on our inferential strategy, we find that this information is learned independently of its inclusion in the business planning documents. Copyright 2009 John Wiley & Sons, Ltd.
Psychometrics and measurement are important for all aspects of psychological research and especially so in social/personality psychology. This volume provides conceptual and practical foundations in scale construction and psychometrics for producers and consumers of social and personality research. It covers basic principles, practices, and processes in scale construction, scale evaluation, scale use and interpretation of research results in the context of psychological measurement. It explains fundamental concepts and methods related to dimensionality, reliability, and validity. In addition, it provides relatively non-technical introductions to special topics and advanced psychometric perspectives such as Confirmatory Factor Analysis, Generalizability Theory, and Item Response Theory. Social/personality research is often grounded in effective measurement, but poor measurement can and does compromise the meaningfulness of psychological research. This volume is intended to raise awareness and understanding of issues that will enhance even further the generally good conduct and interpretation of research in social and personality psychology. This text will be perfect for all advanced students and researchers in social and personality psychology using psychometrics or measurement as part of their studies or research.
Entrepreneurship, long neglected by economists and management scholars, has made a dramatic comeback in the last two decades, not only among academic economists and management scholars, but also among policymakers, educators and practitioners. Likewise, the economic theory of the firm, building on Ronald Coase's (1937) seminal analysis, has become an increasingly important field in economics and management. Despite this resurgence, there is still little connection between the entrepreneurship literature and the literature on the firm, both in academia and in management practice. This book fills this gap by proposing and developing an entrepreneurial theory of the firm that focuses on the connections between entrepreneurship and management. Drawing on insights from Austrian economics, it describes entrepreneurship as judgmental decision made under uncertainty, showing how judgment is the driving force of the market economy and the key to understanding firm performance and organization.
Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.