5. Does ‘ego’ make the entrepreneur?
5.2 Entrepreneurial overconfidence
5.3.2 Experimental design, samples and procedure
The experiment was conducted with 84 participants, 28 entrepreneurs and 56 entrepreneurs. Six sessions were run with 14 participants each. Entrepreneurs and non-entrepreneurs participated in separate sessions. All sessions were run at the experimental laboratory of a German university.
The entrepreneurs were recruited via online announcements. All of them were founders and managers of companies. Industries ranged from services, retailing, technology, and manufacturing. The average age of the entrepreneurs was 42 years (SD = 12.62). 53.6 percent of them were male and 46.4 percent were female. All entrepreneurs had been running their business for more than three years at the time they participated in the experiment. The non-entrepreneurs were students from different fields like in Camerer and Lovallo (1999) and Moore et al. (2007). Their average age was 26 years (SD = 0.64). They were recruited via class announcements and email invitations. The non-entrepreneurs sample consisted of 33.9 percent male and 66.1 percent female students. In order to account for differences in opportunity costs and wealth the show-up fee and the payoffs in the experiment were scaled up by a factor of three for the entrepreneurs.
Upon arrival participants were paid a show-up fee of 12 Euro (36 Euro for the entrepreneurs) and told to pocket it. Participants were then seated at separated computer desks. Communication between the participants was not allowed and participants did not know with whom they were playing. Instructions were displayed on the computer monitors and guided participants through the experiment. Additional hard copies of the instructions were distributed. Comprehension questions at the beginning assured that participants fully understood the instructions. The experiment consisted of three parts:
In part one, all participants completed a general knowledge quiz with 14 binary choice questions knowing that their payoffs from the subsequent task would depend on how
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well they performed in this quiz. The questions were pre-tested to avoid performance differences between men and women and to adjust difficulty. Having completed the quiz, participants did not receive feedback about their performance. Instead, they continued with part two without knowing how many questions they actually answered correctly16. For part two, they were matched in groups of seven playing the following market entry game: participants were asked to decide simultaneously whether or not to enter an experimental market with a limited capacity c (representing the market demand). In this market, success depended on the participant’s performance in the quiz as compared to the other six people in her group. Only the c best ranked entrants could make a profit. All further entrants would make a loss. The rank of a participant was determined by the number of correct answers in the quiz as compared to the other people in her group. The entrant with the highest number of correct answers had rank 1, the entrant with the second highest number of correct answers had rank 2. Ranks were unknown to the participants. Feedback about the ranks was only given at the very end of the experiment. All participants decided simultaneously and without being able to observe the others entering or not entering the market. The capacity (demand) of the market c was uncertain: it could vary between 1 and 5, whereby the distribution of c was not given to the participants in order to account for exogenous demand uncertainty as considered by Wu and Knott (2006). If a participant decided to enter and he was among the c best ranked entrants, he made a monetary profit of K. If he decided to enter but he was not among the c best ranked entrants, he made a monetary loss of L. The possible profit K was 22.50 Euro for the entrepreneurs and 7.50 Euro for the non-entrepreneurs. The possible loss L was 30 Euro for the entrepreneurs and 10 Euro for the non-entrepreneurs. The respective payoffs are displayed in Table 20.
16 In Camerer and Lovallo (1999) the trivia questions were presented only after the market entry
experiment. However, previous research has shown, that people prefer to bet on things that are yet not realized (e.g., Rothbart and Snyder 1970).This is explained by peoples’ illusion of control. In order to eliminate potential effects of illusion of control, in the present study participants were confronted with the trivia task before the market entry game – still without giving them any information about the number of questions they answered correctly.
137 TABLE 20.PAYOFFS AS A FUNCTION OF ENTRANT RANK AND MARKET CAPACITY C
ENTRANT RANK
C 1 2 3 4 5 6 7
1 22.5€ [7.5€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€]
2 22.5€ [7.5€] 22.5€ [7.5€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€]
3 22.5€ [7.5€] 22.5€ [7.5€] 22.5€ [7.5€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€]
4 22.5€ [7.5€] 22.5€ [7.5€] 22.5€ [7.5€] 22.5€ [7.5€] - 30€ [-10€] - 30€ [-10€] - 30€ [-10€]
5 22.5€ [7.5€] 22.5€ [7.5€] 22.5€ [7.5€] 22.5€ [7.5€] 22.5€ [7.5€] - 30€ [-10€] - 30€ [-10€]
Participants played five rounds of this simultaneous market entry game. After they completed this, they played another five rounds in which they received information on the ability level of their competitors. In each round, participants were randomly re-matched so that they played against a different group of six opponents in each round.
Between the rounds, participants did not receive any feedback about the outcome of a round. Instead, the outcomes of all rounds were presented in a table at the very end of the experiment. After all rounds were completed, participants were asked to state the number of players they expected to enter in the previous market entry game (a) in the first five rounds, and (b) in the second five rounds when they received information about the skill level of their competitors. For each correct estimate they received a small additional payoff to assure it was in their own interest to truthfully report on their expectations. Afterwards, participants risk attitude was measured using the Holt and Laury (2002) measure followed by a questionnaire including basic statistical data like age and gender. After all participants completed the questionnaire, one of the ten rounds was randomly selected as basis for the final payoff. Participants received a report about their performance in the quiz, about the results of all rounds, their decisions, and a list of their payoffs from the different parts of the experiment. Finally, participants were privately paid. The experiment was programmed and conducted using the software z-Tree (Fischbacher 2007).
5.3.3 Nash equilibria
If players knew their rank and the size of the market capacity, the best c players in a group should enter. All others should stay out because they would make a loss by
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entering. As in this experiment ranks – representing relative skills – and the market capacity – representing demand – were unknown, entry decisions mirrored the participants’ beliefs about their true ranks and their belief about the realized market capacity.
Assuming, however, in accordance to Camerer and Lovallo (1999), that participants are risk-neutral and have common ignorant priors – i.e., assuming they believe to have equal chances to be among the c best-ranked players and assign equal probabilities to all possible realizations of c, the following payoff function can be derived:
Letsi 0be the strategy of player i not to enter and letsi 1denote the strategy of player i to enter the market. The payoff function of the average player is then given by:
(10) number of entrants does not exceed the market capacity, the average entrant’s profit is K
>0 (K = 22.50 Euro for the entrepreneurs and 7.50 Euro for the non-entrepreneurs). If the total number of entrants exceeds the market capacity, the payoff of the average entrant equals the industry profit divided by the number of entrants. The industry profit is the accumulated payoff (gains and losses) of all entrants, whereby c entrants make a profit of K and (m-c) entrants make a loss of L (L = 30 Euro for the entrepreneurs and 10 Euro for the non-entrepreneurs), with K = 0.75 L.
In equilibrium, players must be indifferent about entering or staying out of the market.
If mc, entering is a dominant strategy as K > 0. If m > c, the average player should be indifferent between entering and staying out when(KcL[mc]/m)0. This happens when m = Kc/L + c; i.e., when m = 1.75 c. Consequently, in pure strategy
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equilibria the number of entrants is m = 1.75 c; i.e., the highest integer of entrants below 1.75 c.
To derive the mixed strategy equilibrium, let p(s1)be the probability with which each player selects to enter and letp(s0)1 p(s1)be the probability with which each player selects to stay out of the market. Then the probability that m players enter and N-m players stay out is
(11) p(m) p(s1)m(1 p(s1))Nm
mNIn the mixed strategy equilibrium, players enter with probabilityp*solving:
(12) *( ) (1 *( )) [ ] *( ) (1 *( 1))
0 pure strategy equilibria and the corresponding mixed strategy equilibrium.TABLE 21.OVERVIEW EQUILIBRIA
Assuming that people assign equal probabilities to all possible realizations of c = [1;
5] they would expect a market capacity of 3 to be realized. In this case the mixed strategy equilibrium predicts a mean entry rate of 0.71.
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5.4 Results
5.4.1 Analysis
Random-effects logit regressions of entry have been estimated to test the following hypothesis:
HYPOTHESIS 1: Entrepreneurs enter more frequently than non-entrepreneurs.
HYPOTHESIS 2: Entrepreneurs are less affected by reference group neglect than non-entrepreneurs; i.e., they react less to information about the ability dispersion in their reference group (interaction between group and reference group information).