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Why are entrepreneurs more risk-loving?
On the reference dependencies of entrepreneurial decision making
Abstract
Empirical evidence on the risk propensity of entrepreneurs has produced inconclusive
results. One reason might be that most studies consider risk propensity as a stable personality
trait, thereby covering only one of the research streams on risk-taking behavior. In this
article, we consider the situational factors of risk propensity as described by prospect theory.
We show that entrepreneurs set significantly higher reference points than do non-
entrepreneurs. For a given distribution of outcomes, this behavior can explain a subsequent
willingness to take on more risks. Furthermore, we find that need for achievement has a
direct and a mediating effect on the formation of the reference point. In contrast, we do not
find a significant effect of optimism.
2
Introduction
Although a high number of new ventures fail within their first years, thousands of people
start their own business each year (Headd, 2003). An important topic in the research on
entrepreneurship is therefore why some people become entrepreneurs and which personal
characteristics differentiate entrepreneurs from managers and other groups. Despite decades
of research, scholars still have only limited understanding of the factors and decision
processes that lead an individual to become an entrepreneur (Markman, Balkin, & Baron,
2002; Shane & Venkataraman, 2000). The study of individual differences has therefore
remained a key topic of investigation in the field of entrepreneurship research (Mitchell et al.,
2007).
One important explanation for entrepreneurship is that entrepreneurs are people who are
willing to take risks, even in uncertain environments (Knight, 1921). Kihlstrom and Laffont
(1979) were the first to formalize the idea that entrepreneurs tend to be less risk-averse than
other people. Iyigun and Owen (1998) argue in a similar vein that risk-averse individuals are
less likely to become entrepreneurs in a developed economy where there is already a large
number of safe jobs. Moskowitz and Vissing-Jorgensen (2002) prove that average returns
from poorly diversified private equity are unattractive. Based on this finding they suggest that
one explanation for start-up activity is that entrepreneurs are more financially risk-tolerant
than managers or other employees.1
While theoretically appealing, these empirical findings about the risk-taking behavior of
entrepreneurs are inconclusive. For example, Cramer et al. (2002) find that risk-aversion is a
deterrent to entrepreneurship. In contrast, Xu and Ruef (2004) find that nascent entrepreneurs
are more risk-averse than non-entrepreneurs. In the psychological research, one meta-analysis
by Stewart and Roth (2001) shows that the risk propensity of entrepreneurs is indeed greater
than that of managers. In contrast, another meta-analysis by Miner and Raju (2004) including
3 different studies draws the opposite conclusion: that entrepreneurs are more risk-averse than
managers. They conclude that “it is not yet time to shut down the research engine” (p.12).2
Most of the studies on risk propensity consider risk taking as an individual trait that should
remain stable over time (Stewart & Roth, 2001). However, this approach covers only one of
the research streams on risk-taking behavior. Another important theme pertains to prospect
theory (Kahneman & Tversky, 1979) which stresses the situational factors that influence risk
attitudes. According to prospect theory, whether an outcome is perceived as a gain or as a
loss compared to a reference point has a strong influence on risk taking behavior. In general,
people exhibit risk aversion in the domain of gains, risk seeking behavior in the domain of
losses, and show significantly greater aversion to losses than an appreciation of gains.
Surprisingly, though prospect theory plays an important role in the explanation of risk taking
behavior, to our knowledge no studies of the differences in risk taking behavior between
entrepreneurs and non-entrepreneurs take this concept into account.
The purpose of the present study is to use prospect theory to offer an explanation why
some entrepreneurs are more risk loving than others. Risk taking might not always be a direct
and stable personality trait. Instead, risk attitudes might be influenced by other personality
traits that affect the assessment of the situation given reference-dependent preferences.
The determinant of risk attitudes in prospect theory is the reference point that distinguishes
gains from losses. We employ a newly developed method by Arkes et al. (2008) to compare
the reference point formation in entrepreneurs and in a control group: Subjects answered
questions in a hypothetical stock trading scenario. We asked subjects what stock price today
would generate the same utility as a previous change in a stock price. This approach allowed
us to calculate the newly formed reference point.
4
We find that entrepreneurs on average set a higher reference point than non-entrepreneurs.
This behavior can have a significant impact on risk attitudes, especially when the person has
little control over the situation. With a higher reference point and a given distribution of
outcomes, more potential outcomes will represent a loss compared to the reference point.
Prospect theory predicts that people in a loss situation will show more risk seeking behavior
than people who are not in a loss situation.
Naturally, the next question is why entrepreneurs should have higher reference points.
Reference dependency has been used in many fields to explain risk attitudes that are
inconsistent with expected utility theory (see Camerer, 2000, for an overview). However,
little is known about what exactly a reference point is (Köszegi & Rabin, 2006) and about the
psychology behind the formation and evolution of reference points over time; prospect theory
does not include hypotheses (Kahneman, 1992; Lehner, 2000). At present there is no
generally accepted theory on the formation of reference points.
Often the reference point is considered to be the status quo, e.g. an existing income level or
a current endowment (Plott & Zeiler, 2005; Thaler, 1999). Lately some authors have argued
that reference points are rational expectations held in the recent past about future outcomes
(Köszegi & Rabin, 2006, 2007; Hack & Lammers, 2008). For example, Winer (1986)
predicts brand choice of different products, assuming that price expectations determine the
reference point. Heath et al. (1999) argue that goals can act as reference points and serve as
evaluative standards even though they may never be an existing state or condition. Along
these lines, Camerer et al. (1997) examine why New York City cab drivers work longer hours
on bad days, taking a target income as the reference point. Rizzo and Zeckhauser (2003) take
the same kind of reference point to explain physicians’ behavior.
Each of these factors of status quo, expectations, or goals could be differently perceived by
entrepreneurs and non-entrepreneurs, thus resulting in different reference points.3 In addition,
5 psychological research has shown that the combination of several of these factors may
determine the formation of the reference point (Blount, Thomas-Hunt, & Neale, 1996).We
are therefore not able to offer a definitive answer to the question of why entrepreneurs set
higher reference points. However, we make a first step in this direction and discuss and test
for two potential personality traits that could affect the formation of expectations and goals:
need for achievement, and optimism. We focus our discussion on expectations and goals
since they leave more room for personal differences than does the observable status quo.
In our experiment we consider a situation in which the individual has no influence on the
outcome (stock price performance). In this setting, with a higher reference point, more
outcomes will be perceived as losses relative to the reference point, resulting in subsequent
risk seeking behavior. Why should an individual set a high reference point? Goals have been
assumed to play a role in the formation of reference points. In addition, they are an important
factor in the context of achievement motivation. We therefore consider the role of the need
for achievement on the formation of a reference point.
Prior research has shown that entrepreneurs are high in need for achievement (Collins,
Hanges, & Locke, 2004). However, this concept is usually associated with situations that are
to some extent controlled by the individual. The reason that we nonetheless consider need for
achievement in our setting is that entrepreneurs have also been found to have a significantly
higher illusion of control compared to others (Simon, Houghton, & Aquino, 2000). People
who have a high need for achievement and who believe that they can control largely
uncontrollable events might therefore set themselves more difficult goals for themselves. We
find that need for achievement has a significant positive effect on the willingness to start a
venture and on the formation of the reference point.
The second personality trait that we consider is dispositional optimism. Several studies
have shown that entrepreneurs are more optimistic than non-entrepreneurs (Puri & Robinson,
6 2004). Optimism is directly related to positive expectations. It also has an indirect effect on
individual goal setting through the optimism that it is possible to meet challenging goals.
However, we find no significant effect of optimism on the formation of the reference point.
The remainder of the paper is structured as follows. In Section 2, we discuss our
hypotheses in greater detail. In Section 3, we present our experimental design. In Section 4,
we describe the empirical findings, and discuss our results. Section 5 concludes.
Hypotheses
Reference point formation
According to prospect theory (Kahneman & Tversky, 1979), situational factors can have an
important impact on risk attitudes. In general, people exhibit risk aversion if they consider
themselves in the domain of gains and risk seeking behavior in the domain of losses.
However, the perception of gains and losses is not based on the person’s overall wealth but
on the relation of the outcome compared to the individual reference point. Therefore, for a
given distribution of outcomes, people with a higher reference point will find themselves
more often in the domain of losses (see Figure 1).
<Please insert Figure 1: Different reference points and impact on gain/loss region >
At some point in time t=1 one person has a lower reference point R1 compared to another
person with reference point Re1. In t=2 an outcome will occur with outcomes distributed
between Ol2 and Oh
2. Then there exist some actual outcomes O2 that are perceived by the first
individual as a gain and by the second individual as a loss. With prospect theory preferences
the second individual would demonstrate more risk seeking behavior than the first.
7
Risk attitudes could be quite different if both individuals were able to spend effort in order
to influence the outcome. According to prospect theory, people are more averse to losses than
appreciative of gains. Therefore, the second individual in our example would have a
motivation to spend more effort in order to reach a higher outcome and to not find herself in a
loss situation. This behavior has been observed in experimental settings (Heath, Larrick, &
Wu, 1999). Therefore, in our experimental design we examine reference point formation for
an event that the individual cannot control (stock price movement).
Many theoretical models assume that entrepreneurs are more risk seeking than non-
entrepreneurs (see, for example, Kihlstrom and Laffont, 1979; Iyigun and Owen, 1998).
However, the empirical findings have been mixed (Miner & Raju, 2004; Stewart & Roth,
2001). One reason for the different findings might be the different experimental designs, in
which the reference point plays or does not play a role. We assume that entrepreneurs will set
a higher reference point that would subsequently result in more risk seeking behavior. This
leads to the following hypothesis:
H1: People who set a higher reference point are more likely to envision forming a venture.
Need for Achievement
Goals have been found to be one important factor in the formation of reference points
(Camerer, Babcock, Loewenstein, & Thaler, 1997; Heath et al., 1999). Differences in goal
setting behavior could therefore explain differences in risk propensity due to prospect theory
preferences. As goals play an important role in achievement motivation, one might conclude
that reference point adaptation and achievement motivation are to some extent related.
In order to assess achievement motivation, we consider the multidimensional concept of
need for achievement. It refers to an individual’s wish to take responsibility for finding
8 solutions to problems, master complex tasks and set ambitious goals (McClelland, 1961).
People who have a strong need for achievement set challenging but achievable goals for
themselves, assume personal responsibility for the accomplishment of those goals, and are
highly persistent in the pursuit of these goals.
It has been shown that performance and career satisfaction are higher when there is a good
fit between work characteristics and personality (Holland, 1985). It was further argued that
entrepreneurial positions have more of those characteristics that people with a high need for
achievement prefer. Thus it seems likely that these people would be attracted to
entrepreneurial jobs (McClelland, 1961). Empirical evidence has generally supported this
hypothesis.4 Most studies document a significant positive correlation between high
achievement motivation and the decision to become self-employed (Johnson, 1990). A
current meta-analysis, comprising 41 studies linking entrepreneurship and achievement
motivation, found that achievement motivation was significantly correlated with choice of an
entrepreneurial career (Collins, Hanges, & Locke, 2004).
H2a: People who are high in need for achievement are more likely to envision forming a
venture.
Need for achievement has been usually associated with situations that are under the control
of the individual. In contrast, our study is concerned with reference point formation when the
individual has no influence on the outcome (see reasoning above). Therefore, we cannot
directly assume that people who are high in need for achievement will set a high reference
point.
There is, however, one reason why we might find some impact of need for achievement:
entrepreneurs have been found to have a significantly higher illusion of control than non-
entrepreneurs (Keh, Foo, & Lim, 2002; Simon, Houghton, & Aquino, 2000). Illusion of
9 control is a bias that occurs when individuals overestimate the extent to which their skill can
increase performance in situations where chance actually plays a large part (Langer, 1975).
People who are high in need for achievement and who believe that they can control largely
uncontrollable events are therefore likely to set themselves more demanding goals for these
events. Accordingly, we hypothesize the following:
H2b: People who are high in need for achievement will set a higher reference point.
Optimism
Expectations, goals, or both may play an important role in the formation of a reference
point. One personality trait that could influence the attitude towards both of these factors is
dispositional optimism: a bias to, across time and situation, hold positive expectations
(Wrosch & Scheier, 2003). People who are dispositionally optimistic believe that, in general,
they will meet their life goals (Chang, 2001). Therefore, optimism can have a direct effect on
expectations. It can also have an indirect effect on the goal setting of the individual through
the optimism to meet challenging goals.
Studies have shown that entrepreneurs are characterized by high optimism (Cooper, Woo,
& Dunkelberg, 1988) and are even more optimistic than other people (Puri & Robinson,
2004). Some researchers have gone further and considered entrepreneurs to be overly
optimistic: this overoptimism limits the search for information (Kaish & Gilad, 1991) and
generates rosy forecasts of the future (Kahneman & Lovallo, 1993). However, some studies
have found no significant relationship between optimism and the decision to start a venture
(Simon, Houghton, & Aquino, 2000).
H3a: People who are highly optimistic are more likely to envision forming a venture.
H3b: People who are highly optimistic will set a higher reference point.
10
Mediating effects
The previous hypotheses argue that higher achievement motivation and higher optimism
will result in higher reference points; as a result, people who set higher reference points have
higher entrepreneurial intentions. In other words, reference point adaptation mediates the
relationship between achievement motivation, optimism and entrepreneurial intention. We
therefore hypothesize that
H2c: The relationship between need for achievement and entrepreneurial intention is
partly mediated by reference point adaptation.
H3c: The relationship between optimism and entrepreneurial intention is partly mediated
by reference point adaptation.
Method
Subjects
A total of 64 business undergraduates at a large German university, the Technische
Universität Dortmund, answered our questionnaire in a classroom setting. All students
voluntarily filled out the questionnaire. The mean age of the participants was 22. Forty-five
percent of the participants were women.
This study examines the decision processes of individuals who envision forming a venture.
Another approach could have been to study people who have already done so. As suggested
by several researchers, there could be key differences in the way entrepreneurs and those
willing to become entrepreneurs process information (e.g. Baron 1998). Especially the
mediating effects of illusion of control on risk propensity proved to be different (Keh, Foo, &
11 Lim, 2002; Simon, Houghton, & Aquino, 2000). This could be due to the fact that
entrepreneurs have already experienced the (un-)controllability of market risks and therefore
have fewer illusions of control. In order to avoid possible interfering influences we examined
students who had not yet established their own venture (Krueger & Brazeal, 1994; Shaver &
Scott, 1991).
Operationalization of variables
A questionnaire was constructed to measure the two independent factors (achievement
motivation and optimism), the mediating variable (reference point adaptation), the dependent
variable (entrepreneurial intention), and two control variables (general risk propensity,
gender). Participants were asked to fill out a paper-based questionnaire which took
approximately 15 minutes to complete. In the following we briefly describe each of the
variables in the order in which they were mentioned in the questionnaire:
Reference point adaptation: To estimate reference point adaptations we presented the
following scenario taken from Arkes et al. (2008) and translated into German: “Two months
ago, you bought a stock for 30€ per share. One month ago, you were delighted to learn the
stock was trading higher – at 36€ per share. This month, you decide to check the stock’s price
again. At what price would the stock need to trade today to make you just as happy with the
stock’s price this month as you were when you learned the stock had risen from 30€ to 36€
last month?” After reading the scenario, participants were asked to indicate the stock price
generating the same utility as the previous price increase.
This procedure allows us to calculate the magnitude of the reference point adaptation under
the assumptions that the purchase price serves as the initial reference point (P0=R0) and that
the value function remains stable over time. The reasoning is the following: the previous
12 price change is assessed based on the initial reference point R0 resulting in utility UR0(P1) in
t=1. We ask subjects what stock price P* in t=2 will generate the same utility. For example,
without a shift in the reference point, subjects will still state P1. We are interested in the new
reference point R* with UR*(P*)=UR0(P1). Under the assumption that the shape of the value
function remains unchanged, the following equation holds:
P* - R* = P1 – R0 => ∆R = R* - R0 = P* - P1 (1)
Given this equality we are able to derive the reference point adaptation (∆R).
Entrepreneurial intention: Following Lüthje and Franke (2003), we asked participants
about their intention to start their own business within the next five years. A 4-point Likert
scale was used, ranging from “very improbable” to “very probable.”
Achievement motivation: To capture respondents’ achievement motivation we use the
Cesarec-Marke Personality Scheme (CMPS). The literature extensively discussed the distinct
differences between projective and self-reported measures of achievement motivation. While
McClelland (1972) stated that projective measures (like the TAT) are the only accurate way
to assess achievement motivation, because achievement motivation is a subconscious trait,
Spangler (1992) reported psychometric deficiencies of the TAT. Collins et al. (2004) found
that both projective and self-report measures are equally valid when predicting
entrepreneurial behaviour. For practical reasons we used a self-report measure (CMPS).
There are 165 questions on the CMPS, of which 15 concern achievement motivation. We
asked participants to answer all 15 and five filler questions. All questions were translated into
German. For each question participants had a forced choice between “yes” or “no.” The
number of “yes” answers results in an achievement score with a value of 15 for individuals
with the highest achievement motivation. The scale was reliable with α = .68.
13
Optimism: After a review of the literature, we chose the German version of the Life
Orientation Test (LOT) (Scheier & Carver, 1985) to deduce participants’ optimism. The LOT
consists of eight 5-point Likert-type items plus four filler items ranging from “strongly
disagree” to “strongly agree.” The test provides a single summary score, with high scores
indicating a more optimistic orientation and low scores indicating more pessimistic
orientation. The alpha reliability for testing optimism using this scale was 0.79.
Control Variables: As mentioned, risk taking is a behavior influenced by, among other
things, by trait, cognitive perceptions, and situational factors (Sitkin & Pablo, 1992).
Different perceptions of risk are not part of our study and to incorporate the situational factor
we measure the reference point adaptation. Therefore, we focus on risk propensity in terms of
a general personality trait as a control in this study. We measure risk propensity by asking
about the general willingness to take risk on a 10-point Likert-scale. This general measure
was shown to predict all risk taking behaviors, especially those relevant for entrepreneurial
decisions like financial risk taking and career risk taking (Dohmen et al., 2005).
Demographic information was also collected in the questionnaire. Due to low variance in
age, race and education variables of the sample, only gender as a potential influencing factor
was included in the analysis (Xu & Ruef, 2004).
Results and Discussion
Descriptive statistics for the dependent variable show that six subjects state a very high
probability of starting their own business within the next five years. Seven subjects stated that
they quite probably intend to start their own business, 25 say that this is quite improbable
while 26 subjects judge the chance as very improbable (mean = 3.11, standard deviation =
14 0.945). Means, standard deviations (SD), and correlations for all variables are shown in Table
1.
<Please insert Table 1: Means, standard deviations, and correlations among variables >
The correlation matrix indicates that, beside a significant correlation between reference
point adaptation and need for achievement, no correlation exists between the independent
variables. We therefore conclude that problems of collinearity between the variables do not
exist.
We test the direct effect of reference point adaptation on entrepreneurial intention posited
in Hypothesis 1 using an ordered logistic regression (Model 1). Regression showed a highly
significant positive relationship, supporting Hypothesis 1. The stronger the reference point
adaptation the higher is one’s entrepreneurial intention. The same held for Hypothesis 2a,
stating that a higher need for achievement will result in a stronger intention to start one’s own
venture (Model 2a). Ordered logistic regression corroborates the hypothesized relationship on
a significant level, too. Only for Hypothesis 3a one cannot find significant support (Model
3a). In our sample optimism does not influence one’s entrepreneurial intention.
Our results on optimism are in line with findings by Simon et al. (2000) but contradicting,
for example, those of Puri and Robinson (2004). This might be attributable to different
methods of measuring optimism. While Simon et al.’s work (2000), like ours, captured
optimism using a multi-item scale, Puri and Robinson (2004) measure optimism by
comparing individuals’ self-reported life expectancy to that implied by actuarial tables.
Measuring optimism based on a single and potentially emotional question could produce
different results.
15 <Please insert Table 2: Results of ordered logistic regression on “entrepreneurial
intention“>
Even after controlling for risk propensity and gender, both reference point adaptation and
need for achievement significantly explain some of the variance of entrepreneurial intention
(Model 5). Interestingly none of the control variables were significant, indicating that in our
sample, trait induced risk propensity does not affect one’s intention to start a venture.
This is in line with several findings in the literature (Miner & Raju, 2004). However while
trait induced risk propensity does not play a role, situational induced risk propensity, due to
different reference point adaptations might be could still affect actual risk taking behavior.
An indication of the possible impact of reference dependency on entrepreneurs’ risk
propensity is the following: Stewart and Roth (2001) found larger differences in risk
propensity between entrepreneurs and non-entrepreneurs for those entrepreneurs whose
primary goals are venture growth versus those whose focus is on producing family income. It
is possible that entrepreneurs with growth intentions set themselves more ambitious goals,
resulting in stronger reference point adaptation and thus a higher (situation induced) risk
propensity. We conclude that in order to arrive at a better understanding of the influence of
risk propensity on entrepreneurial intention one must take situational antecedents influencing
reference point adaptation into account.
To verify Hypotheses 2c and 3c, that is, proving the mediation effect of reference point
adaptation, four conditions had to be met (Baron & Kenny, 1986). First, the independent
variables (need for achievement, optimism) had to affect the mediator (reference point
adaptation); second, the independent variables had to affect the dependent variable
(entrepreneurial intention); third, the mediator had to affect the dependent variable; and
16 fourth, the effect of the independent variables in a multiple regression of independent and
mediator variables on the dependent variable had to be less than in the simple regression.
Models 2b and 3b (see Table 3) report the results of the first condition: the relationship
between the independent variables and the mediator. We conducted an ordinary least square
regression confirming the positive relationship between need for achievement and reference
point adaptation on a significance level of only 10% (Hypothesis 2b).
We were thus only able to confirm Hypothesis 2b on a weak significance level. One reason
could be that need for achievement is usually associated with situations that are under the
control of the individual, which is not the case in our setting. We might find stronger support
if we had controlled for illusion of control. Apart from the illusion of control, other factors
might influence the relationship between need for achievement and reference point
adaptation, like overconfidence. Future research should therefore include moderators like
illusion of control or overconfidence.
While need for achievement does influence reference point adaptation, we cannot confirm
a significant relationship between optimism and reference point adaptation (Hypothesis 3b).
<Please insert Table 3: Results of ordinary least square regressions on “reference point
adaptation“>
We have already documented the direct effects of the independent variables (Models 2a
and 3a) as well as the direct effect of the mediator (Model 1) on the dependent variable
(Model 1) in Table 2. Regarding need for achievement, we find a strong significant
relationship with entrepreneurial intention, thus fulfilling the second condition. Optimism,
however, was not significantly related to the intention to start a venture. Hypothesis 3c was
not corroborated. We therefore excluded optimism from the subsequent analysis. The third
17 condition, the direct effect of the mediator on the independent variable, was also met (Model
1).
Finally, Model 4 simultaneously regressed need for achievement and reference point
adaptation on entrepreneurial intention. To examine the last condition, we compared the
coefficient for need for achievement in Model 2a to the coefficient in Model 4. The
comparison displayed that the coefficient decrease in magnitude after adding reference point
adaptation, suggesting a mediated relationship. Furthermore, the coefficient for reference
point adaptation in Model 4 was still significant, supporting a partial rather than a full
mediation. Thus Hypothesis 2c was supported.
In summary, we were able to confirm both the direct and mediating effects of reference
point adaptation and the direct effect of need for achievement on entrepreneurial intention.
Results therefore support the assumption that the situational dimension of risk propensity
does play an important role in the explanation of entrepreneurial behavior.
Conclusion
Despite decades of research, the determinants of entrepreneurship are still not yet well
understood. One important aspect of entrepreneurial behavior is the willingness to take risks.
Many theoretical models have therefore assumed that entrepreneurs are less risk averse than
non-entrepreneurs. However, empirical evidence regarding risk propensity has produced
inconclusive results. One reason for these different results might be that most studies consider
risk propensity as an individual trait that should be stable over time. However, this approach
covers only one of the research streams on risk-taking behavior.
To our knowledge, this paper is the first that considers the situational factors as described
by prospect theory to explain different risk attitudes by entrepreneurs and non-entrepreneurs.
18 In particular, we examine differences in the formation of the reference point. With a higher
reference point and a given distribution of outcomes, more potential outcomes are perceived
as a loss compared to the reference point. Prospect theory predicts that people in a loss
situation will show more risk seeking behavior than people who are not in such a situation.
We indeed find that entrepreneurs set a significantly higher reference point than do other
individuals. Subsequently we examine the role of need for achievement and optimism in this
relationship. We show that need for achievement has a direct effect on reference point
formation. In contrast, we do not find a significant effect of optimism.
There are some limitations of our study. The advantage of the current method is that it
allows direct measurements of the adaptation of the reference point. However, this advantage
comes at a cost. An important limitation is our assumption of risk attitudes based on prospect
theory. We assume that people who set a high reference point in a setting where they are not
able to control the outcome will find themselves more often in a loss situation and therefore
will show more risk seeking behavior. A future study should directly test for risk propensity
in a setting where prior information has resulted in participants’ adaptation of the reference
point (e.g. choices between lotteries). This research design could also address a further
limitation of this kind of questionnaire study: subjects’ decisions have no monetary
consequences.
Another avenue for future research would be to consider differences in reference point
formation between people who envision starting a venture and people who have already done
so. Prior research has shown that there could be important differences between the two
groups, for example regarding the mediating effect of illusion of control on risk propensity
(Simon et al., 2000).
A further interesting question concerns the role of other personality traits in the formation
of reference points. In particular, tests for illusion of control and overconfidence – both traits
19 that have often been found to be significantly associated with the decision to start a business–
are promising directions for future research. All in all, this kind of study could not only add
to the research on entrepreneurship but also to the broader field of research on factors that
influence the formation of reference points over time (Köszegi & Rabin, 2007).
20
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23
Footnotes
1 Newman (2007) has published one of the few theoretical papers in economics that argues to the contrary that
risk-based explanations for entrepreneurship are inadequate. He assumes that agents are able to insure
entrepreneurial risks but that moral hazard prevents full insurance. He finds that in this setting the decision to
become an entrepreneur based on risk preferences produces implausible results.
2 Some attempts have been made to reconcile the risk-bearing characterization of entrepreneurs with the
inconsistent empirical findings. For example, some scholars suggested that risk taking behavior results not
only from risk-propensity which is the tendency to take actions that one has judged to be risky but from a
combination of risk propensity and risk perception (Weber & Milliman, 1997). Risk perception is defined as
a decisions maker’s assessment of the risk inherent in a situation (Sitkin & Pablo, 1992). Empirical research
indeed supports the hypothesis that individuals who perceive less risk are more likely to evaluate an
opportunity more favorably and are more likely to start their own venture (Simon et al. 2000; Keh et al.
2002). Another attempt to reconcile the different findings is the study by Wu and Knott (2006). They
differentiate demand uncertainty from ability uncertainty and propose that entrepreneurs are risk-averse with
respect to the first concept but overconfident and therefore “apparent risk-seeking” with respect to the
second.
3 One other important factor that has been identified in the literature to influence the reference point is social
comparisons (Frank, 1985; Ho & Levesque, 2005). Since our experiment does not induce social comparisons,
we do not consider this factor in our discussion.
4 For exceptions see Frey (1984) and Hansemark (2003).
24
Tables
Table 1: Means, standard deviations, and correlations among variables
-0.216**3.335.12Reference point adaptation (2)
Kendall‘s rank correlation coefficient, n=64,*p<0.1; **p < 0.05, ***p < 0.01
-0.0820.032-0.0690.1201.844.81Risk propensity (5)
--0.0590.002-0.0490.592.38Optimism (4)
-0.154*0.270***2.2210.17Need forAchievement (3)
-0.951.89EntrepreneurialIntention (1)
4321SDMeanVariables
-0.216**3.335.12Reference point adaptation (2)
Kendall‘s rank correlation coefficient, n=64,*p<0.1; **p < 0.05, ***p < 0.01
-0.0820.032-0.0690.1201.844.81Risk propensity (5)
--0.0590.002-0.0490.592.38Optimism (4)
-0.154*0.270***2.2210.17Need forAchievement (3)
-0.951.89EntrepreneurialIntention (1)
4321SDMeanVariables
25 Table 2: Results of ordered logistic regression on “entrepreneurial intention“
13.318
0.222
0.116 (.0524)
0.161 (0.141)
-0.008 (0.414)
0.286** (0.119)
0.153* (0.079)
Model 5
Gender
Risk Propensity
15.362***
0.197
0.292** (0.118)
0.146* (0.077)
Model 4
0.858
0.003
-0.160 (0.395)
Model 3a
1.255
0.140
0.327*** (0.116)
Model 2aModel 1Independent variables
*p<0.1; **p<0.05; ***p<0.01; () standard deviation
1.745
0.103
Test of parallel lines(Chi-Square)
Nagelkerkes R2
Optimism
Need for achievement
0.175** (0.074)Reference point adaptation
13.318
0.222
0.116 (.0524)
0.161 (0.141)
-0.008 (0.414)
0.286** (0.119)
0.153* (0.079)
Model 5
Gender
Risk Propensity
15.362***
0.197
0.292** (0.118)
0.146* (0.077)
Model 4
0.858
0.003
-0.160 (0.395)
Model 3a
1.255
0.140
0.327*** (0.116)
Model 2aModel 1Independent variables
*p<0.1; **p<0.05; ***p<0.01; () standard deviation
1.745
0.103
Test of parallel lines(Chi-Square)
Nagelkerkes R2
Optimism
Need for achievement
0.175** (0.074)Reference point adaptation
26 Table 3: Results of ordinary least square regressions on “reference point adaptation“
0.001
0.058
-0.172 (0-713)
Model 3bModel 2bIndependent variables
*p<0.1; **p<0.05; ***p<0.01; () standard deviation
0.052
3.386*
Adjusted R2
F-statistic
Optimism
0.341* (0.185)Need for achievement
0.001
0.058
-0.172 (0-713)
Model 3bModel 2bIndependent variables
*p<0.1; **p<0.05; ***p<0.01; () standard deviation
0.052
3.386*
Adjusted R2
F-statistic
Optimism
0.341* (0.185)Need for achievement