首页

当前位置: 首页 > 品牌活动 > 学术报告 > 正文 学术报告

“商学大讲堂”系列学术讲座(第221讲)---学术名家讲坛(44)

来源:tyc86太阳集团   韩晓东     发布时间: 2023-10-16    点击量:

讲座题目:When Karma Strikes Back: A Model of Seller Manipulation of Consumer Reviews in An Online Marketplace

主讲嘉宾:吴如海

间:20231018日(星期三)下午14301630

点:tyc86太阳集团119会议室


欢迎感兴趣的师生参加聆听!


tyc86太阳集团

20231016

主讲嘉宾简介

Dr. Ruhai Wu is a tenured marketing professor at the DeGroote School of Business, McMaster University. He earned his Bachelor's and Master's degrees in Finance from Tsinghua University and a Master's and a Ph.D. in Economics from the University of Texas at Austin. Dr. Wu is an established authority in the spheres of Industrial and Retail Marketing strategies. His multifaceted research encompasses a broad spectrum of disciplines, including Pricing Theory, Supply Chain/Channel Relationship Management, Advertising and Communication Strategy, and emerging E-Commerce business models. In his research, Dr. Wu employs game-theoretical and advanced empirical models to examine firms' and consumers' strategic behaviours. His research has been frequently published in top-tier journals in Marketing, Information Systems, and Operation Management, and he has received over ten competitive research grants from prestigious granting agencies, including the Social Sciences and Humanities Research Council of Canada and the Natural Sciences and Engineering Research Council of Canada. His recent research projects include pricing and management strategies of E-commerce platforms, information asymmetry in supply chains, dynamic pricing in competitive markets, communication in joint consumption, and live streaming E-commerce.

讲座主要内容

Online word of mouth (WOM) helps consumers learn about sellers' products/services quality and influences market competition. Some sellers, taking advantage of the anonymity of contributing consumers, fake consumer WOM to boost their products/services ratings. This research uses a game-theoretical model to examine sellers' dynamic pricing and their review manipulation decisions in an online marketplace. We explore the critical drivers of review manipulation and how fake reviews shape the market outcome. Specifically, the model shows a self-inhibition mechanism of review manipulation, which prevents high-quality sellers and softly discourages low-quality sellers from faking reviews. Fake WOM reduces vertical seller differentiation and intensifies price competition. Moreover, negativity bias in genuine customer reviews enhances self-inhibition, especially for low-quality sellers. Consequently, sellers with extreme (very high or very low) quality do not fake reviews when consumers are more likely to write reviews for unsatisfying products/services.