Decision Making Under Impending Regime Shifts
研究了在环境即将发生制度转变时，决策者的定价决策如何受风险态度和概率判断的影响，发现当先验概率低时，定价反应模式与系统忽视假说一致，而先验概率高时则消失。
In environments with impending regime shifts, previous research studies probability judgments of decision makers (DMs) regarding a regime shift and finds evidence for the system neglect hypothesis: In unstable environments with precise signals, DMs exhibit relatively more underreaction in their probability judgments, and in stable environments with noisy signals, they exhibit relatively more overreaction. In the present paper we focus on pricing decisions and study how risk attitudes, as well as probability judgments regarding a regime shift, affect these decisions. We develop a model that integrates prospect theory with the system neglect hypothesis and compare changes in empirical pricing decisions to those of a Bayesian risk-neutral agent. We find a pattern of under- and overreaction in pricing decisions that mimics the system neglect hypothesis in probability judgments only when the DM’s prior probability of a regime shift is low; the system neglect pattern vanishes when the DM’s prior probability of a regime shift is high. We argue that in the case of low priors, changes in risk attitude in reaction to signals indicative of a regime shift amplify system neglect in probability judgments. In the case of high priors, on the other hand, changes in risk attitude dampen the effect of system neglect. We test our model predictions in experimental insurance markets and offer various extensions to check for the robustness of our findings. Finally, we discuss implications for managerial practice in organizational contexts that are characterized by continuous change. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Funding: This work was funded by Fundação para a Ciência e a Tecnologia (UIDB/00124/2020, UIDP/00124/2020 and Social Sciences DataLab - PINFRA/22209/2016), POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016). Furthermore, it was supported by the Ministerio de Ciencia e Innovación España [10.13039/501100011033, Grants ECO2014-52925-P, PID2019-111512RB-I00-HMDM, and HDL-HS-280218]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4661 .