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1027上海管理论坛第475期(孙建坤博士,英国帝国理工学院)

创建时间:  2021-10-24  沈洁   浏览次数:


题目:Choice Overload with Search Cost and Anticipated Regret: Theoretical Framework and Field Evidence(在搜索成本与预期遗憾下的选择过载效应:理论框架与现实证据)

演讲人:孙建坤,英国帝国理工学院商学院助理教授

主持人:陈楠,十大正规网投官网平台(中国)有限公司讲师

时间:20211027日(周三),上午10:00

地点:公司校本部东区十大正规网投官网平台420

主办单位:十大正规网投官网平台(中国)有限公司、十大正规网投官网平台(中国)有限公司青年教师联谊会


演讲人简介:

孙建坤,英国帝国理工学院商学院助理教授,美国西北大学凯洛格商学院运营管理专业博士,清华大学工业工程专业学士。

主要研究方向为数字平台运营的实证研究与理论分析,特别是数字化与智能化对组织运营与消费者行为的影响。 Management ScienceManufacturing & Service Operations Management等运营管理领域国际顶级期刊发表论文。曾获国际运筹学与管理科学学会(INFORMS)制造与服务运作管理领域(M&SOM Society)博士生论文竞赛第二名。


演讲内容简介:

As consumers are offered an ever-increasing number of options for almost every purchase decision in online retail, understanding the impact of assortment size on consumer choice decisions, especially on both search and purchase behavior, is critical. Our research speaks to this question by combining empirical analyses with theoretical modeling. First, via a large-scale field experiment involving 1.6 million consumers on Alibaba's online retail platforms, we causally examine how consumers’ click and purchase behavior changes as the number of products in a choice set increases. We document that consumers’ likelihood of clicking or purchasing at least one product increases at first but then decreases as the number of offered products rises. To explain this inverted-U-shaped relationship, we develop a “consider-then-choose-with-regret” (CTCR) choice model that incorporates consumers’ search cost and anticipated regret. Numerical experiments suggest that our CTCR model leads to smaller optimal assortments containing products of higher expected utilities and lower prices on average than the classical multinomial logit choice model. Altogether, this work presents real-world experimental evidence for choice overload on both search and purchase behavior, advances the field's understanding of how assortment sizes alter consumer choices, and provides a theoretical foundation for incorporating the choice overload effect in operational decisions.



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