| Michael Zhang
香港中文大学商学院决策科学与企业经济学系教授
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【主讲】张晓泉，香港中文大学商学院决策科学与企业经济学系教授
【时间】2019年5月16日（周四）上午10:00am – 11:30am
Professor Michael Zhang is a Professor of Decision Sciences and Managerial Economics at the School of Business, Chinese University of Hong Kong. He also serves as Associate Dean of Innovation and Impact at the CUHK Business School and a research affiliate at MIT Initiative on Digital Economy and European Center for Economic Research (ZEW).
He holds a PhD in Management from MIT Sloan School of Management, an MSc in Management, a BE in Computer Science and a BA in English from Tsinghua University. Before joining the academia, he worked as an analyst for an investment bank, and as an international marketing manager for a high-tech company. He holds a US patent, and cofounded several companies in Social Networking and FinTech.
Professor Zhang’s research interests are on issues related to creation, dissemination and processing of information in business and management contexts. His works study pricing of information goods, online advertising, innovation and incentives, and use of artificial intelligence in financial markets. His research has appeared in academic journals such as American Economic Review, Management Science, Marketing Science, MIS Quarterly, Information Systems Research, Journal of Marketing, Journal of MIS, etc.
【Speaker】Michael Zhang, Professor, Department of Decision Sciences and Managerial Economics, Chinese University of Hong Kong
【Topic】Distributional Matthew Effect in Consumer Choices
【Time】Thursday, May 16, 2019, 10:00am – 11:30am
【Venue】Room 453, Weilun Building, Tsinghua SEM
【Organizer】Department of Management Science and Engineering
【Abstract】 Existing research in word-of-mouth considers various descriptive statistics of rating distributions, such as the mean, variance, skewness, kurtosis, and even entropy and the Herfindahl-Hirschman Index. But real-world consumer decisions are often derived from visual perceptions about displayed rating distributions in the form of histograms. In this study, we argue that such distribution charts may inadvertently lead to a consumer-choice bias that we call the distributional Matthew effect (DME). We propose a model of consumers’tendency to pay too much attention to salient features of distributions in visual decision making. In a series of experiments, we identify DME’s significant impact on consumer preferences. We show that with DME, consumers make choices that violate widely accepted decision rules. In our experiments, subjects are observed to prefer products with lower average ratings and higher rating variances. They violate widely accepted modelling assumptions such as branch independence and may even prefer a first-order stochastically dominated distribution as a result of DME. Our study suggests how consumer-choice models should be refined to accommodate such visual decision biases.
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