Frontiers of Entrepreneurship Research
Volume 31 | Issue 17
CHAPTER XVII. CORPORATE
ENTREPRENEURSHIP
Article 2
6-11-2011
EMPLOYEE EFFECTUATION - WHAT
MAKES CORPORATE EMPLOYEES ACT
LIKE ENTREPRENEURS?
Alvaro Filipe da Costa
RWTH Aachen University, dacosta@win.rwth-aachen.de
Malte Brettel
RWTH Aachen University
Recommended Citation
da Costa, Alvaro Filipe and Brettel, Malte (2011) "EMPLOYEE EFFECTUATION - WHAT MAKES CORPORATE EMPLOYEES
ACT LIKE ENTREPRENEURS?," Frontiers of Entrepreneurship Research: Vol. 31: Iss. 17, Article 2.
Available at: http://digitalknowledge.babson.edu/fer/vol31/iss17/2
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da Costa and Brettel: What Makes Corporate Employees Act Like Entrepreneurs?
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Employee effectuation – what makes corporate
employees act like entrepreneurs?

Alvaro Filipe da Costa, RWTH Aachen University, Germany
Malte Brettel, RWTH Aachen University, Germany
Abstract
Entrepreneurial employees are crucial to successful CE and for developing radical innovations.
Entrepreneurial behavior means dealing with situations of uncertainty, which arise especially in
the fuzzy front-end of innovation. Effectuation is a behavioral logic to deal with uncertainty. This
study applies effectuation theory to the fuzzy-front end, and derives individual level and organizational antecedents to effectual and causal behaviors from the literature on entrepreneurial personality traits and CE organization. Using cross-sectional survey data from 56 corporate employees,
we show that a proactiveness, tenacity, and internal locus of control influence specific behaviors, as
do work discretion, time availability, and management support. This study contributes to CE and
innovation literature by deepening the understanding of the effects of traits and organization on
employee behavior, and advances effectuation theory by suggesting individual and environmental
antecedents to effectual behavior
Introduction
What we know
Recent research on CE moves the behavior and cognition of individuals into focus, and thus
understands a company’s organization as a mere stage for individuals with entrepreneurial cognitions to take action (Ireland, Covin, & Kuratko, 2009). A number of models describing corporate
entrepreneurial action have been developed (Antoncic, 2003; Hayton, 2005; Kuratko, Ireland,
Covin, & Hornsby, 2005; Monsen, Patzelt, & Saxton, 2010). Individual behavior becomes particularly important in the early phases of CE, commonly referred to as the fuzzy-front end (FFE, Smith
& Reinertsen, 1991). This phase is characterized by a high degree of uncertainty and a mostly
unstructured and unguided search for ideas (Kim & Wilemon, 2002). In this phase, committed
individuals act as boundary spanners towards the company’s external environment and as gate
keepers to the company’s decision makers (Reid & de Brentani, 2004). In fulfilling these functions,
the fuzzy front-end activities contribute significantly to the success of following product development projects (Khurana & Rosenthal, 1998)
Like their self-employed kin, these corporate entrepreneurs face similar Knightian uncertainties, e.g. the dependency on unpredictable innovation outcomes (Knight, 1921; Phan, Wright,
Ucbasaran, & Tan, 2009; Sharma & Chrisman, 1999). However, some differences set the corporate
context apart, e.g. more generous resources endowment (Shrader & Simon, 1997), a separation
between individual and organizational risk-taking (Antoncic, 2003), and the influence of the surrounding organization (Hornsby, Kuratko, & Zahra, 2002).
To deal with uncertain situations, expert entrepreneurs were found to apply a set of heuristics
termed effectuation (Sarasvathy, 2001; Sarasvathy, 2008), which were also observed in broader
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samples of entrepreneurs (Chandler, DeTienne, McKelvie, & Mumford, 2009) and in the context
of corporate R&D projects (Brettel, Mauer, Engelen, & Küpper, 2011).
What we don’t know and why we should care
While these results suggest that effectual behavior may be found in the fuzzy front-end, it
is yet unclear what causes employees in a corporation to act effectually. Are effectual and causal
behaviors mutually exclusive or do they coexist? Which individual and organizational factors
influence the use of these heuristics? An answer to these questions could be a significant step
forward for CE research and practice, as specifically fostering certain behaviors may result in different innovation outcomes (Brettel et al., 2011), as well as for effectuation research. Furthermore,
a better understanding of organizational stimuli and employees’ behavioral preferences can lead
to an organization that is tailored to encourage particular employees, or conversely, a personnel
selection and development to fully harness the organization’s support.
Approach: Linking insights about CE organization and entrepreneurial action in a social
cognitive framework
We address these questions by drawing on Bandura’s social cognition theory (1986). Bandura
posits that behavior, personal factors, and the external environment constantly influence each
other. Ireland et al. (2009) mirror this framework by describing the interplay between an organization, individual cognition, and entrepreneurial behaviors. We operationalize entrepreneurial
behavior using Sarasvathy’s (2001) four dimensions, each of which can take an effectual and a
causal form. To measure the organization’s influence we draw on the various studies on factors
that foster CE (Brown, Davidsson, & Wiklund, 2001; Damanpour, 1991; Dess, Lumpkin, & McGee,
1999; Hornsby, Kuratko, & Zahra, 2002; Marvel, Griffin, Hebda, & Vojak, 2007). For individual
cognitive factors, we use insights from the Action Theory of Entrepreneurship, which states that
entrepreneurial action is enabled by a mindset that is self-starting, proactive, and persistent in the
face of obstacles (Frese, 2009).
We proceed as follows: We first discuss the applicability of effectuation theory in the FFE,
and develop what effectuation means in this context. Then we describe personal cognitive and
organizational influences and hypothesize their effects on effectual and causal behaviors. Next,
we describe our methodical approach to empirically test our hypotheses. Next, we present the
study results and discuss them in the light of theory. We conclude by discussing the contributions,
limitations, and future research questions of this study.
Theoretical Foundations and Hypotheses
Effectuation as entrepreneurial behavior in the fuzzy front-end
The importance of individual behavior has been highlighted for successful CE in general
(Ireland, Covin, & Kuratko, 2009), as well as for the fuzzy front-end in particular (Reid & de
Brentani, 2004). Drawing on the parallels between independent and corporate entrepreneurship,
we discuss the applicability of effectuation as one model to describe entrepreneurial behavior
(Sarasvathy, 2001)
In her seminal work, Sarasvathy (2001) outlines effectuation as a set of behaviors that entrepreneurs use in the face of Knightian uncertainty, i.e. in situations where the probabilities of the
possible consequences of one’s action are unknown. In Knight’s (1921) understanding, taking
decisions in the face of uncertainty constitutes an entrepreneur, as most people avoid “ambiguous”
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situations (e.g. Rode, Cosmides, Hell, & Tooby, 1999). Knight’s perspective is the cornerstone of a
constructionist view on entrepreneurship, in which opportunities are created by taking decisions
under uncertainty, rather than discovered in the environment (Alvarez & Barney, 2007; McMullen
& Shepherd, 2006). In a more general sense, effectuation may be an epitome of control-based
strategies that, in contrast to prediction-based strategies, rein in uncertainty by expanding one’s
influence over the environment rather than by trying to precisely position oneself in an exogenous
environment (Wiltbank, Dew, Read, & Sarasvathy, 2006)
The early stage of innovation is fraught with uncertainties, including unclear potentials of
technology, demand and competitor actions (Zhang & Doll, 2001). FFE activities have the potential
to reduce uncertainty, thereby improving the chances of effective and efficient product development (Verworn, Herstatt, & Nagahira, 2007). Individual action becomes especially important for
discontinuous or radical innovations, as individuals rather than organizational routines recognize
opportunities and channel information into the organization. (Reid & de Brentani, 2004; Rice,
Kelley, Peters, & O’Connor, 2001)
A number of helpful fuzzy front-end activities have been proposed, many of which can be
interpreted in the light of effectuation theory. Sarasvathy (2001; 2008) proposes 4 dimensions,
each of which can take an effectual, control-oriented and a causal, prediction-oriented form.
The first dimension describes the starting point of the venture. In causal thinking, a set goal
determines the means required to achieve this goal. For the FFE, this could mean actively aligning
the concepts developed to the company strategy (Zhang & Doll, 2001), and continually developing a project plan to reach this goal (Verworn, 2009). Effectually, the means available determine
potential outcomes. This is mirrored efforts to establish transparency about available knowledge
in the company (Kim & Wilemon, 2002) and in acknowledging exaptation phenomena (Dew,
Sarasvathy, & Venkataraman, 2004).
The second dimension covers the perception of risk. Causally, the focus lies on forecasting
expected returns, as commonly done in a business plan (though not found to improve performance
by Bertels, Koen, & Kleinschmidt, 2008). Effectuators, on the other hand, put an emphasis on
keeping the potential losses in an affordable range. In the FFE, this is mirrored by noted “20%rules” for employees to engage in innovative projects, e.g. at Google (Iyer & Davenport, 2008),
or in using input control mechanisms (Poskela & Martinsuo, 2009), while granting a certain
degree of autonomy and flexibility (examined for NPD projects by Tatikonda & Rosenthal, 2000).
Deliberately using loss-limited experimentation to generate insights about an environment or to
enact a new business models also reflects this dimension (Chesbrough, 2010).
The third dimension defines the attitude towards outsiders. Causally, outsiders are perceived
as potential competitors, thus focusing on competitive analyses, which are emphasized in FFE literature (Zhang & Doll, 2001). In effectuation, outsiders may well be potential partners that can
be involved in the project for mutual gain. This aspect is strongly present in FFE literature, as
cooperation with suppliers, customers and even potential competitors are encouraged (Kim &
Wilemon, 2002)
The fourth dimension delineates the mindset towards unexpected events. In causations, contingencies should be avoided. In the FFE, for this purpose process formalization (Kim & Wilemon,
2002) and rigorous planning (Verworn et al., 2007) has been proposed. Effectuators understand
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contingencies as valuable opportunities. FFE literature acknowledges the emergence and value of
surprising results and paths in the fuzzy front end (Kim & Wilemon, 2002; Rice et al., 2001);
exaptation also often has surprising characteristics (Dew, Sarasvathy, & Venkataraman, 2004).
Individual factors influencing entrepreneurial behavior
Drawing on the results of independent entrepreneurship research seems warranted when
examining individual factors influencing the choice of behaviors. Corporate entrepreneurs face
similar Knightian uncertainties, e.g. the dependency on unpredictable innovation outcomes
(Knight, 1921; Phan et al., 2009; Sharma & Chrisman, 1999). However, some differences set the
corporate context apart, e.g. more generous resources endowment (Shrader & Simon, 1997) and a
separation between individual and organizational risk-taking (Antoncic, 2003).
Entrepreneurship research has identified numerous promotive personality traits. While factors
such as generalized self-efficacy, proactive personality, innovativeness, and achievement motives
can be clearly attributed to entrepreneurship (Rauch & Frese, 2007), the question of how these
factors influence the choice of entrepreneurial behaviors demands deeper theoretical grounding.
In his Action Theory of Entrepreneurship, Frese (2009) develops three characteristics of active
(rather than reactive) entrepreneurial actions: An entrepreneur needs to be proactive, persistent in
the face of obstacles, and self-starting. How do these characteristics relate to the choice of effectual
or causal behaviors?
Proactiveness is defined by Frese by having a long-term focus and anticipating future problems
and opportunities. This bearing allows proactive persons to identify and seize opportunities and
thus effect change in the environment (Crant, 1996). The long-term focus leads us to expect an
inclination to work towards goals as guidelines for action:
H1a: The higher personal proactiveness, the higher the goals orientation
The second aspect of proactiveness, anticipation of future opportunities, implicates being
prepared and open to seize opportunities as they develop, rather than avoid them:
H1b: The higher personal proactiveness, the higher the appreciation of unexpected events
H1c: The higher personal proactiveness, the lower the avoidance of unexpected events
Persistence in the face of obstacles, according to Frese is required to overcome the inevitable
problems and adversities any entrepreneurial venture faces. It fosters clear goals, a clearly communicated vision, and self-efficacy for entrepreneurs (Baum & Locke, 2004). Frese name two effects
of persistence: Firstly, the agent needs tenacity to prevent being dissuades from his goals and plans,
which allows him or her to follow a course of action, but may also result in stubbornness. Secondly,
barriers external to one-self need to be overcome, for which tenacious efforts are needed. The
first effect leads us to hypothesize strong goal orientation and a reluctance to change plans when
contingencies occur:
H2a: The higher personal persistence, the higher the goals orientation
H2b: The higher personal persistence, the lower appreciation of unexpected events
H2c: The higher personal persistence, the higher the avoidance of unexpected events
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The second effect of persistence leads us expect a strong orientation towards the external
market environment – a persistent person may be very conscious of the competition any may
respond by either strengthening partnerships or competitive positioning:
H2d: The higher personal persistence, the higher the partnership orientation
H2e: The higher personal persistence, the stronger the competitive analysis
Self-Starting, according to Frese, describes taking action without external trigger. This corresponds to Rotter’s (1966) internal locus of control, which essentially describes the belief to be
in control of one’s fate, and thus self-motivation initiative. Being in control of a situation implies
reluctance to let external influences alter the course of one’s actions:
H3a: The stronger the internal locus of control, the lower appreciation of unexpected events
H3b: The stronger the internal locus of control, the higher the avoidance of unexpected events
Organizational factors influencing individual behavior
CE literature has extensively examined the question, which organizational factors foster
CE activity (e.g. Brown, Davidsson, & Wiklund, 2001; Damanpour, 1991; Hornsby, Kuratko, &
Zahra, 2002). Hornsby et al. have summarized the state of research with regards to middle managers and developed a five main factors model: Work Discretion, Time Availability, Management
Support, Rewards / Reinforcements, and Organizational Boundaries. In a later refinement however,
Organizational Boundaries was discarded (Hornsby, Holt, & Kuratko, 2008).
Work discretion refers to a job design that allows employees to take their own decisions about
how they fulfill their jobs. Not being tied to specific procedures should make it easier for employees to utilize their personal knowledge and networks as means in developing an innovation idea:
H4: The higher the work discretion, the higher the means-orientation
Time availability describes whether employees find the time to work on entrepreneurial projects besides their regular activities. When compared to a situation of high workload, available
time may lead to more goal-oriented work, as there is time to fulfill all planned steps rather than
a trimmed selection.
H5a: The higher the time availability, the higher the means-orientation
H5b: The higher the time availability, the higher the goals-orientation
Management support summarizes a climate in which calculated risks are supported by the
management with championing and resources. For an employee this means being able to incur a
certain risk of loss without negative consequences, and developing innovations from the unaffiliated resources provided by management:
H6a: The higher the management support, the higher the affordable loss-orientation
H6b: The higher the management support, the higher the means-orientation
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Management support may also involve encouragement for changing directions if unexpected
events, such as new insights or market opportunities emerge:
H6c: The higher the management support, the higher the appreciation of unexpected events
Rewards and Reinforcements mirrors the importance of incentive systems and recognition for
employees. As this factor requires a certain degree of employee accountability in terms of target
achievement and gains earned from developed innovations:
H7a: The stronger the rewards and reinforcements, the higher goals-orientation
H7b: The stronger the rewards and reinforcements, the stronger the focus on expected returns
Methods
Sample
We conducted this study together with a multi-national, highly diversified corporation that
strongly emphasizes innovation and entrepreneurship in its organization and culture. A sample
of our partner’s German employees from various functions was surveyed. The survey addressed
employees of all levels from the R&D, technical service, marketing, and sales function, some of
which have already submitted an innovation idea in the past for corporate decision. From a total
of approx. 1100 employees, 72 responded, yielding a response rate of 6.5%. From these, only complete datasets were considered for analysis, reducing the number entered to 52-56. The analysis
sample shows an approx. 50% split between frontline workers and managers, and an approx. 50%
split between R&D and other functions.
Dependent Variables
The dependent variables in this study are measures of effectual and causal behaviors. We
decided to use a slightly adapted version of the operationalization by Brettel, Mauer, Engelen,
& Küpper (2011) rather than the one suggested by Chandler, DeTienne, McKelvie, & Mumford
(2009) for three reasons: Firstly the former scale reflects the 4 principles / dimensions outlined by
Sarasvathy (2001; 2008), thereby making hypothesis generation and testing more straightforward.
Secondly, the former scale more clearly separates behavioral logics from outcomes (e.g., the experimentation construct in Chandler et al. contains experimental actions as well as outcome attributes). Thirdly, being designed for corporate R&D projects, only minor adaptations to the items
were necessary. As Brettel et al. suggested we measured effectuation and causation items independently from each other (rather than bipolarly like in their study). This allows us to examine both
effectual and causal behaviors in parallel without presuming that they are mutually exclusive. The
correlations shown in table 1 support this independence. All measures show high reliabilities with
Cronbach’s α greater 0.7 (Means-driven 0.73, Goals-driven 0.81, Affordable loss 0.77, Expected
Returns 0.87, Partnership 0.71, Competitive Analysis 0.92, Acknowledge Unexpected 0.73, Avoid
Unexpected 0.74)
Independent Variables
All measures for individual factors were taken from extant literature. Proactiveness (α=0.83)
was measured using an instrument proposed by Bateman & Crant (1993) and subsequently used
in various studies from the entrepreneurship and career choice literature (Crant, 1996; Seibert,
Kraimer, & Crant, 2001). For measuring persistence, the tenacity construct employed by Baum &
Locke (2004) was used (α=0.78). As described above, we operationalized self-starting by drawing
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on the locus of control construct. We used the “internal”-dimension (α=0.7) from the multidimensional conceptualization by Levenson (1973), which was also used by Chen et al. (1998
As organizational factor measures, the revised Corporate Entrepreneurship Assessment
Instrument (CEAI) was used (Hornsby et al., 2008; Hornsby, Kuratko, & Zahra, 2002), with slight
adaptations to the fuzzy front-end. Management Support, Work Discretion and Rewards and
Reinforcements exhibit satisfactory reliabilities with Cronbach’s alphas of 0.79, 0.81, and 0.77
respectively. Time Availability’s reliability is slightly lower at 0.69.
Control Variables
We used the respondent’s function as a control variable, as procedures and customary working
style could well differ between functions. Hierarchy level was also controlled to give consideration
to the greater scope for entrepreneurial activities for managers. We also included gender to control
for potential differences between men and women. Tenure and education were also controlled for,
as both might have an effect on a person’s network or specialist knowledge, which both provide
valuable means to effectuate with.
Results
The Pearson correlations of our variables are shown in table 1. No correlations exceed the
recommended cutoff of 0.6, and estimating the variance inflation factor (VIF) does not yield values above the recommended value of 10 (Hair, Black, Babin, Anderson, & Tatham, 2006), so we
conclude that no critical multicollinearity can be found in the data. Further descriptive data cannot be published at this time, as clearance from our partner company is still pending.
For testing our hypotheses, we employ a series of OLS regressions, using effectuation and
causation behaviors as dependent variables. Table 2 reports the regression outcomes. We find our
regression models to yield satisfactory R^2 values, given that no specific situational variables are
included. Looking at the adjusted R^2, however, shows unsatisfactory results for the Expected
Returns Model, which makes us doubt the explanatory power of this model.
For proactiveness, we can confirm H1b (positive effect on Acknowledge Unexpected) while
hypotheses H1a (positive effect on goals-driven) and H1c (neg. effect on Overcome Unexpected)
are rejected. For persistence, H2b (neg. effect on Ack. Unexpected) and H2e (pos. effect on Comp.
Analysis) are confirmed. H2a (pos. effect on Goals-driven) and H2c (pos. effect on Overcome
Unexpected) are rejected. For internal locus of Control, we confirm H3a (neg. effect on Acknowledge
Unexpected) and H3b (pos. effect on Overcome Unexpected). Furthermore, we find a strongly
significant negative effect on Competitive Analysis.
For Work Discretion, we detect a negative effect on Means-driven, although we hypothesized a
positive effect (H4). For Time Availability, we can confirm H5b (pos. effect on Goals-driven), but
reject H5a (pos. effect on Means-driven). For Management Support, we confirm H6b (pos. effect
on Means-driven), and H6c (pos. effect on Acknowledge Unexpected). While we hypothesized
a positive effect on Affordable Loss (H6a), we actually found a significant negative effect. For
Rewards and Reinforcements, we have to reject both hypotheses H7a (pos. effect on Goals-driven)
and H7b (pos. effect on Expected Returns).
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Discussion
The results of this study indicate that there is a connection between individual personality
traits and organizational factors on employees’ choice of behavior. With the exception of Expected
Returns, the proposed antecedents provide satisfactory explanatory power, considering that no
situational influences (e.g. the innovativeness or uncertainty of the idea worked on) have been
included. While we find no single antecedent that fosters both effectual and causal behaviors in the
same dimension, we do find numerous effects where only effectual or causal behavior is affected.
As the effectual and causal constructs in each dimension are not strongly negatively correlated
(with the exception of Acknowledge vs. Overcome Unexpected), we conclude that both behaviors
are not mutually exclusive.
Some results of this study are surprising and call for explanations: Firstly, the finding that
employees with a strongly internal locus of control place lower emphasis on competitive analysis is intriguing, as it may indicate that these employees perceive their innovation ideas “outside
competition”, either because they perceive a high innovativeness or because they see their ideas
success not influenced by competitive positioning. The latter interpretation would suggest a
co-creation approach (Read, Dew, Sarasvathy, Song, & Wiltbank, 2009); the associated expected
positive effect on partnerships is not confirmed, however. Secondly, contrary to our hypothesis,
we found a negative effect of Work Discretion on Means-orientation. This may be interpreted
as tendency to work towards self-set goals rather than to orient oneself at means; the positive
effect on Goals-orientation implicated by this explanation is missing, however. Thirdly, against our
expectation, we found a negative effect of Management Support on Affordable loss. This suggests
that our hypothesis derivation may have failed to consider the transformation of risk between
organizational and individual level: When an employee’s superiors take responsibility for an idea
by providing resources, the risk of losing this investment moves from the employee to the underwriting manager, thus making affordable loss orientation less important for said employee.
Contribution
This study contributes in four ways. Firstly, we transfer the effectuation theory to the fuzzy frontend, thereby providing a novel way to examine individual behavior that has moved into the focus of
both CE research and FFE literature (Ireland, Covin, & Kuratko, 2009; Reid & de Brentani, 2004).
Secondly, we propose and test personal and organizational antecedents to these behaviors,
thereby answering questions about these antecedents from the innovation literature (e.g. Prather,
2000). The effectuation literature also has begun to controversially discuss the relationship between
effectuation and traits (Goel & Karri, 2006; Saras Sarasvathy & Dew, 2008), without yet giving clear
answers to Mitchell et al.’s (2007) question: “What cognitive differences and environments lead to
heuristic-based logic and which lead to effectuation-based logic in identifying opportunity?”. With
this study, we hope to take a step towards answering this question.
Fourthly, we contribute to effectuation literature by empirically demonstrating the independence of effectuation and causation behaviors. The theoretical derivation and delineation of
effectuation suggest a strong dichotomy between effectual and causal approaches, in reality both
behaviors probably are not mutually exclusive (Read et al., 2009).
Lastly, we offer practitioners important hints on how to foster effectual and causal behaviors,
given that the former may be more effective in producing highly innovative outcomes (Brettel et
al., 2011). Furthermore, if certain ways of organizing affect behavior, and certain personality types
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are inclined towards certain behaviors, matching organization and employee personalities may
amplify desired behaviors, or if done wrongly, negate the effects of organizational design.
Limitations
This study has several limitations. Firstly, the sample may not to corporate employees as all
respondents belong to the same corporation that, its internal diversity notwithstanding, probably shares cultural and organizational elements that do not apply to other companies. This calls
for replication studies in other corporations to identify similarities and differences. Secondly, the
absolute number of responses is limited, resulting in low significance levels, which could also be
mitigated by replication. The data used is entirely self-reported by a single informant, which may
cause bias. Triangulating responses with coworkers’ or superiors’ reports may solve this problem.
Thirdly, this study only includes rather static antecedents, as neither personality traits nor the
perceived organization change frequently. Including contingency variables, such as uncertainty or
innovativeness, in subsequent studies should drastically increase the predictive power of the model.
Fourthly, the strongly negative correlation between Acknowledge and Overcome Unexpected may
be an artifact of the measuring model, the formulations of which strongly emphasize the dichotomy of both. Reviewing the measuring model may clarify this concern.
Future Research
Beyond these suggestions, future research should build on our study and deepen the understanding of antecedents to each of the four dimensions. By building deeper theoretical foundations
for each, more nuanced effects may come to light. For instance, is locus of control only a direct
influence on behavior, or does it also interact with Proactiveness? Work Discretion may also be a
moderating factor to allow behavioral choice driven e.g. by Management Support. Interactions
between individual and organizational level also seem likely, e.g. a lower reliance on Management
Support for employees with a strongly internal locus of control. Beyond these topics, social cognitive theory suggests an effect of individual factors on the environment, either through actually
changing it or by perceiving it in a biased way. This calls for a multi-level analysis, analyzing how
employees of the same organizational unit perceive their environment and whether this perception is individually biased. Another question raised is the influence of teams and interactions in
the teams on the behavior of the group.
Conclusion
Our findings offer a novel perspective on important questions: What does effectual behavior
mean for corporate employees and what causes it? We bring together insights from the innovation
and CE literature as well as from entrepreneurship research, and build a model inspired by the
social cognitive theory. We find evidence supporting our theoretical deductions, but also encounter unexpected results that may spur research in this intriguing field.
CONTACT: Alvaro Filipe da Costa; dacosta@win.rwth-aachen.de.
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Table 1
M
SM
e.ia (1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
Means-driven
1.00
4.27
1.13
1.80
7.00
Goals-driven
-0.22
4.56
1.17
2.00
6.67 1.00
Affordable Loss
0.20
3.21
1.19
1.00
5.75 0.12
1.00
Expected Returns
0.08
5.50
1.13
2.00
7.00 0.20
-0.02
1.00
Partnership
-0.24
4.22
1.25
1.75
6.50 0.30
0.26
0.26
1.00
Comp. Analysis
0.28
4.14
1.48
1.00
7.00 0.06
0.10
0.46
0.17
1.00
Ack. Unexpected
0.22
4.73
0.94
2.33
7.00 0.07
-0.07
0.47
0.08
0.35
1.00
Overc. unexpected
-0.05
4.09
1.00
1.83
6.17 0.30
0.22
-0.06
0.18
0.10
-0.59
1.00
Proactiveness
-0.01
5.29
0.75
3.00
6.80 0.19
-0.04
0.27
0.23
0.26
0.33
-0.05
1.00
Tenacity
0.06
4.56
0.99
2.00
6.80 0.16
0.03
0.20
0.14
0.35
0.08
0.10
0.69
1.00
internal Locus of Control
-0.02
5.47
0.98
2.00
7.00 0.14
0.07
0.21
0.04
-0.09
-0.05
0.17
0.32
0.18
1.00
Work Discretion
-0.06
5.12
0.93
2.43
7.00 0.16
0.08
0.30
0.08
0.03
0.40
-0.13
0.35
0.04
0.17
1.00
Time Availability
-0.03
3.65
1.00
1.40
6.33 0.18
0.01
-0.00
-0.16
0.11
0.17
-0.16
0.04
-0.14
0.11
0.10
1.00
Management Support
0.30
4.89
1.09
1.80
7.00 0.12
-0.16
0.38
-0.18
0.20
0.39
-0.20
0.28
0.21
0.04
0.41
0.24
1.00
Rewards & Reinf.
0.12
5.21
1.07
1.67
7.00 0.23
-0.01
0.44
0.01
0.16
0.34
-0.05
0.29
0.10
0.04
0.38
0.23
0.58
(15)
1.00
Table 2
Dimension 1
Dimension 2
Dimension 3
Dimension 4
Means-driven
Goals-driven
Affordable Loss Expected Returns Partnership
Comp. Analysis Ack. Unexpected Overc. Unexpected
beta
t-value beta
t-value beta
t-value beta
t-value beta
t-value beta
t-value beta
t-value beta
t-value
Variables
Proactiveness
-0.293
-1.51
-0.156
-0.66
-0.348
-1.54
0.117
0.68
0.195
1.12
0.179
Tenacity
0.0529
0.27
0.424
1.53
0.294
1.37
0.128
0.75
-0.109
-0.58
0.508*** 3.32
int. Locus of Control
0.119
0.82
0.00177 0.01
0.252
1.53
Work Discretion
-0.282* -1.87
-0.0601 -0.31
0.00615 0.04
-0.300
-1.62
0.265
1.28
-0.00259 -0.02
-0.223
-1.53
-0.433*** -3.81
-0.312** -2.50
0.243*
1.71
0.128
-0.0280
-0.21
-0.0552
0.0235
0.17
-0.114
-0.75
-0.80
0.98
-0.49
Time Availability
0.120
0.460** 2.31
0.239
-0.0277 -0.20
-0.204
-1.48
0.329*** 2.92
-0.116
0.208
1.31
0.377** 2.45
-0.295
-1.51
-0.331* -2.01
0.217
1.40
-0.195
-1.31
-0.0102
-0.08
0.351** 2.41
-0.222
-1.49
Rewards & Reinf.
-0.0178 -0.13
0.120
0.73
0.0697
0.46
0.0734
0.56
0.0561
0.45
0.114
0.86
-0.0828 -0.67
-0.0366
-0.27
0.07
Funct.: Tech. Service
a
1.39
0.437** 2.67
-0.368** -2.15
Management Support
Control Variables
0.72
1.25
1.006** 2.70
0.0132
0.03
0.735*
1.79
0.0284
-0.832*
-1.93
0.544*
1.69
-0.264
-0.79
0.715*
1.74
Funct: Marketing
0.554
1.15
-0.826
-1.47
-0.331
-0.58
-0.0864 -0.21
0.993*
1.91
0.177
0.50
0.447
1.11
-0.194
-0.40
Funct: Sales
-0.297
-0.42
-0.756
-1.02
-1.472* -1.96
0.552
0.58
0.227
0.35
-0.561
-1.05
1.261** 2.30
-1.352** -2.19
Funct: other
1.218
1.20
-0.0180 -0.02
-0.409
-0.36
0.701
1.38
-0.685
-1.29
0.635
1.41
0.279
0.41
-0.239
-0.33
Level: Team Leader
0.593
1.56
0.343
0.68
0.264
0.63
0.120
0.30
0.970**
2.51
0.375
1.20
0.733** 2.16
-0.399
-1.05
Level: Dept. Head
0.228
0.65
0.267
0.62
0.599
1.56
0.161
0.49
1.032*** 2.96
-0.365
-1.34
-0.0238 -0.08
0.208
0.61
1.95
-0.312
-0.47
-1.281
-1.67
-0.309
-0.61
0.686
0.758*
1.80
0.856
0.0452
0.08
b
Level: Chief Dept. Head 1.141*
1.34
1.48
Gender(1 = male)
0.00568 0.01
-0.916** -2.11
-1.127** -2.51
-0.206
-0.61
-0.247
-0.65
-0.656** -2.35
0.133
0.39
-0.634*
-1.72
Education
0.301
0.119
0.52
-0.115
-0.59
0.0168
0.08
-0.345*
-1.74
-0.519*** -3.35
-0.113
-0.72
0.0406
0.23
Tenure
_cons
-0.0743
-1.488 -0.61
-1.44
0.136
-0.155
0.97
-0.13
0.1000
1.010
0.77
0.96
-0.0381
-0.31
0.262
0.26
0.0281
1.213
0.25
1.23
0.134
2.131**
-0.300***1.48
-2.76
1.297
N
52
53
53
52
52
53
56
55
R-sq
0.498
0.279
0.452
0.364
0.621
0.693
0.544
0.480
adj. R-sq
0.248
0.126
0.186
0.047
0.432
0.544
0.340
0.241
1.60
1.39
2.60
0.351*** -0.93
3.00
-0.926
* p<0.1
** p<.05
***p<.01
a
default is R&D
b
default is frontline employee
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