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This study investigates the role of ambiguity in market entry decisions, drawing on existing literature and experimental design. Ambiguity, defined as uncertainty created by missing information, leads to behaviors such as ambiguity aversion and seeking. We designed a Market Entry Game to analyze decision-making among potential entrants under varying levels of market capacity uncertainty. Key findings reveal that ambiguity causes higher entry rates compared to risky markets and demonstrates the phenomenon of over-entry. These results highlight the significance of ambiguity seeking in understanding market dynamics and business failures.
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Ambiguous information and market entry Jordi Brandts and Lan Yao (IAE&UAB, Barcelona) July 30, 2007
Motivation • Defining ambiguity: • “ambiguity is uncertainty about probability, created by missing information that is relevant and could be known.” Frisch and Baron(1988) • Many researchers have found evidence of ambiguity aversion. • Ellsberg paradox; Sarin and Weber (1993); • One recent study finds ambiguity seeking. • Chen, Katuscak and Ozdenoren (2006) • There are several ways in which information can be missing. We study ambiguity as unknown probability about market capacity.
Motivation • Why study ambiguity in market entry problem? • We are interested in ambiguity in strategic environments; • Empirical evidence of over entry and high rate of business failure is hard to explain; • Market capacity uncertainty is more an ambiguous situation than a risky one.
Experimental Design • One Market Entry Game • 5 potential entrants; π = 6 payoff if stay out; π = 6 + 2 (c – n ) payoff if enter; • c: market capacity, n: actual entrants. • 50 periods; • The vector of realizations of c same for risk and ambiguity.
Experimental Design • Procedure: • all the subjects make decisions at the same time; • in risk or ambiguity situation, c is not informed neither at the beginning nor in the end of the period; • the only information feedback they received is their own payoff.
MSNE 2.6 Experimental Result • 5 rounds smoothed line of average number of entrants for 50 periods
Experimental Result • We extend our design to three cases with two markets; • One market with certain capacity, the other with risky capacity; • One market with certain capacity, the other with ambiguous capacity; • One market with risky capacity, the other with ambiguous capacity; • And also study random vs. fixed matching. • Most previous work uses fixed matching, but both random and fixed make economic sense.
Experimental ResultsAggregate results • Observation1: in both one market and two markets cases, entrant number in ambiguous market is higher than that in risky market. • Observation 2: over entry happened in all markets. However entrant number in certain market is always less than that in risky or ambiguous market when they are present at the same time. • Observation 3: entrant number is higher in fixed matching than in the random matching.
Summary • We find clear evidence of ambiguity seeking; • Two explanations of excess entry; • Overconfidence about relative ability, Camerer and Lovallo (1999); • Self-assessed competence, overconfidence plays no roles, Grieco and Hogarth (2006); • Our results suggest a new factor---ambiguity seeking--- may be behind observed over entry into markets.