Abstract
Competitive escalation occurs frequently in managerial environments, when decisions create sunk costs and decision makers compete under time pressure. In a series of experiments using a minimal dollar auction paradigm, we test interventions to prevent competitive escalation. Without any intervention, most people, including experienced managers, escalate and lose money by bidding more than the price is worth (e.g., more than 10 € for 10 €). We test several interventions, in which we provide individuals with different types of experience: direct experience in structurally identical and in structurally similar situations, as well as direct experience in similarly competitive situations (lacking the escalation dimension). We also study indirect experience based on vicariously learning about the situation's consequences (experienced by others) and based on mental simulation by setting oneself a limit regarding where to exit the competition. In 3 experiments (N = 1,229), we find that direct experience in exactly the same or a structurally similar situation allows individuals to prevent subsequent escalation, whereas direct experience in a similar situation without escalation does not. Indirect experience based on vicarious learning successfully reduces competitive escalation, whereas a goal-setting intervention that has proven instrumental in reducing classic escalation of commitment is not effective. This pattern of variation in the effectiveness of different interventions is consistent with the theory of a hot-cold empathy gap that prevents people from anticipating how they will experience a competitive situation before entering it. As a methodological contribution, we developed a deception-free computer-player dollar-auction for online participants and a dynamic chicken game.
Original language | English |
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Pages (from-to) | 695-714 |
Number of pages | 0 |
Journal | Journal of Behavioral Decision Making |
Volume | 31 |
Issue number | 5 |
Early online date | 22 May 2018 |
DOIs | |
Publication status | Published - Dec 2018 |