Topic

Learning about Quality from Online Reviews

Speaker

Hai Che Ph.D.

Time

start from 10:00am, December 27, 2011 (Tuesday)

Venue

Room 624, Siyuan Faculty Building

Profile of the Speaker

Hai Che is Assistant Professor of Marketing at the Marshall School of Business at University of Southern California. His primary research areas include marketing research, data-driven marketing strategies, competitive pricing and advertising strategies, structural empirical models, and behavioral economics. His research has appeared in the Journal of Marketing Research, Marketing Science and Quantitative Marketing and Economics, and he has been a member of the prestigious Marketing Science Institute Young Scholar Program.　

Professor Che received his B.A. and M.A. in Economics from Fudan University, a M.A. in Economics from University of Toronto, a MSBA and a Ph.D. in Marketing from Washington University in St. Louis. Prior to joining the Marshall School of Management, Professor Che taught at Haas School of Business, University of California at Berkeley, from 2003 to 2008. 　

Introduction of the Lecutre

We develop a structural dynamic demand model that examines how consumers learn about product quality and cost from online reviews. We assume consumers learn about product quality and cost from multiple information sources contained in reviews, update their quality belief, and then make a decision to purchase and consume the product. However, we differ from previous work on consumer Bayesian learning by allowing for 1) user-specific learning of both mean and variance of product quality, 2) correlated learning with the assumption that users learn about their expected quality experience based on user and reviewer specific attributes, 3) different learning mechanisms for learning about quality and cost. We estimate our model by matching review data from a restaurant review website with consumer restaurant visit observations, and discuss the consumer behavior and managerial implications of our estimation and policy simulation results.