学术讲座:Choice Urgency in Finite Recommender Services: Unraveling the Role of Choice Variability from Modeling Users' Expected Utility
2023-11-13 12:24
科研
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讲座题目:Choice Urgency in Finite Recommender Services: Unraveling the Role of Choice Variability from Modeling Users' Expected Utility

讲座时间:2023年11月16日(周四)10:00-11:30

讲座地点:明德楼1101会议室

主讲嘉宾:蔡昭副教授      宁波诺丁汉大学

主讲嘉宾简介:

蔡昭博士现任宁波诺丁汉大学商学院信息系统学副教授。他的研究领域包括数字化供应链管理、平台竞争、共享经济等方面。他的研究成果发表在MIS Quarterly、Journal of Operations Management、International Journal of Operations and Production Management等知名期刊。他还担任Industrial Management & Data Systems期刊的执行编辑(Managing Editor)以及Internet Research期刊的副编辑(Associate Editor),并在亚太信息系统会议(PACIS)和武汉国际电子商务会议(WHICEB)担任子领域主席(Track Chair),在国际信息系统会议(ICIS)、欧洲信息系统会议(ECIS)等国际会议担任子领域副编辑(Associate Editor)。

讲座主要内容:

Crowdsourced freight logistics platforms have adopted Context-Aware Finite Recommender Services (FRS) to cater to time-sensitive service demands. Presenting users with a reduced set of matched recommendations in batches, FRS is devised to induce users’ choice urgency and avoid choice delay. However, there is a dearth of research that attempts to unravel the effects of batch presentation on choice urgency. Anchored on expected utility theory, we scrutinize the role of current and historical choice variability within and across batches in generating choice urgency by first mathematically analyzing users’ decision models and then empirically validating the propositions in a massive dataset of order recommendation records from a leading crowdsourced platform. Both mathematical models and empirical results reveal that current intra-batch diversity induces choice urgency while current inter-batch growth, historical intra-batch diversity and historical inter-batch diversity discourage choice urgency. Findings from this study contribute to extant literature on recommender services by unraveling how the design of FRS impacts user choice behavior, with critical insights offered to relevant practitioners around crowdsourced freight logistics.

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 经济学院

2023年11月13日