主题:Beyond Keywords: Untangling Emergent Search Strategies
主讲人:Chee-Wee Tan (陈致玮),Professor, Department of Digitalization, Copenhagen Business School, Denmark![](/__local/E/18/D9/BE14666E07A039288570A6626D4_F9CB5E7C_17BE.jpg)
时间:6月26日(星期一)上午9:30
地点:学院205会议室
主持人:章骏 副教授
内容摘要:
As the digital transformation of the service sector accelerates, matchmaking platforms try to provide every available search feature (e.g., faceted filter and interactive map) to cater for consumers’ preference for feature-rich platforms. The resultant feature creep may hinder consumers’ search for desired items due to the need to scatter attention over an array of search features. This begs the question of how consumers decide which search feature to use at each step of the on-site search process without premeditation. In light of optimal foraging theory, this study advances emergent search strategies to capture consumers’ unpremeditated propensities for allocating attention among available search features when proceeding to the next search action to specify search criteria, to browse consideration set, or to examine a selected option in detail. An emergent search strategy is constituted by attention propensities that reflect a consumer’s approach to or avoidance of each search action transition. Consumers’ attention propensities can be affected by attention-steering properties of available search features. This study conducted a controlled online experiment in which the provision of search feature is manipulated. By analyzing 288 participants’ search logs through a process modeling approach, we confirm that participants change emergent search strategies when given search features shift their attention allocation propensities. We then evaluate the effectiveness of emergent search strategies for on-site search processes. Whereas one dominant effective strategy was found for consumers who are driven by specific goals, two opposing strategies — one reducing search cost and the other boosting search benefit — surfaced for the exploratory consumers.
报告人简介:
Chee-Wee Tan is a Professor at the Department of Digitalization in Copenhagen Business School (CBS), an Honorary Professor of Business Analytics and Digitalization at the Nottingham University Business School China in the University of Nottingham Ningbo China (UNNC), an Adjunct Professor at the School of Business in Monash University, a Distinguished Research Scholar at the Faculty of Business in Lingnan University (LNU), a Guest Professor at the School of Management in the University of Science and Technology of China (USTC), and a Visiting Professorial Fellow at the School of Information Systems and Technology Management in University of New South Wales (UNSW). He received his Ph.D. in Management Information Systems from the University of British Columbia. His research interests focus on design and innovation issues related to digital services. His work has been published in leading peer-reviewed journals such as MIS Quarterly (MISQ), Journal of Operations Management (JOM), Information Systems Research (ISR), Journal of Management Information Systems (JMIS), Journal of the Association for Information Systems (JAIS), European Journal of Information Systems (EJIS), and Decision Support Systems (DSS), among others. Apart from his current appointment as a Senior Editor for MISQ, Chee-Wee has served or is currently serving on the editorial boards for ACM Distributed Ledger Technologies: Research and Practice (DLT), DSS, EJIS, Industrial Management & Data Systems (IMDS), IEEE Transactions on Engineering Management (IEEE-TEM), Information & Management (I&M), Information Systems Journal (ISJ), Internet Research (IntR), Journal for the Association of Information Systems (JAIS), Journal of Computer Information Systems (JCIS), Journal of Management Analytics (JMA), and JMIS. Finally, Chee-Wee is the co-director of the joint research center between CBS and the Antai College of Economics and Management (ACEM) in Shanghai Jiao Tong University (SJTU) as well as the Vice President of Publications for the Association for Information Systems (AIS).