Sequential Search and Learning from Rank Feedback: Theory and Experimental Evidence
成果类型:
Article
署名作者:
Palley, Asa B.; Kremer, Mirko
署名单位:
Duke University; Frankfurt School Finance & Management
刊物名称:
MANAGEMENT SCIENCE
ISSN/ISSBN:
0025-1909
DOI:
10.1287/mnsc.2014.1902
发表日期:
2014
页码:
2525-2542
关键词:
Sequential search
optimal stopping
behavioral decision making
Secretary problem
摘要:
T his paper studies the effect of limited information in a sequential search setting where a single selection is to be made from a set of random potential options. We consider both a full-information problem, where the decision maker observes the exact value of each option as she searches, and a partial-information problem, in which the decision maker only learns the rank of the current option relative to the options that have already been observed. We develop a model that allows for a sharp contrast between search behavior in the two information settings, both theoretically and empirically. We present the results of an experiment that tests, and supports, the key prediction of our model analysis-limited information induces longer search. Our data further suggest systematic deviations from the theoretical benchmarks in both informational settings. Importantly, subjects in our partial-information conditions are prone to stop prematurely during early stages of the search process and to suboptimally continue the search during late stages. We propose a simple model that succinctly captures the interplay of two symmetric choice and judgment biases that have asymmetric (but opposing) effects on the length of search. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1902.