최정혜 교수

For Internet retailers, demand propagation varies not only through time but also over space. The authors develop a Bayesian spatiotemporal model to study two imitation effects in the evolution of demand at an Internet retailer. Building on previous literature, the authors allow imitation behavior to be reflected both in geographic proximity and in demographic similarity. As these imitation effects can be time varying, the authors specify their dynamics using a “polynomial smoother” embedded with

Offline retailers face trading area and shelf space constraints, so they offer products tailored to the needs of the majority. Consumers whose preferences are dissimilar to the majority—”preference minorities”—are underserved offline and should be more likely to shop online. The authors use sales data from Diapers.com , the leading U.S. online retailer for baby diapers, to show why geographic variation in preference minority status of target customers explains geographic variation in online sale

Companies are eager to leverage social interactions among consumers by embedding social networking tools on their websites and actively integrating marketing actions with consumers' social activities. In this article, the authors investigate the impact of online social interactions on repeat usage behavior and the effectiveness of monetary incentives by formulating a model that parses out the effects of these individual factors. Using a unique data set from a wellness program, they find that onl

Given the rise of online review communities, the management of consumer ratings has gained much attention in the recent years. In this study, we use data from Tripadvisor.com and examine the number of stars that a review receives. Specifically, we address how a star rating is determined by the components in the focal review as well as the preceding reviews of other consumers. Our qualitative and quantitative analyses provide interesting findings as follows. A star rating has a positive relations

Geographic variation in consumer use of Internet retailers is partly explained by variation in offline shopping costs. Explanations for geographic variation in the efficacy of different customer acquisition methods including traditional methods of offline word-of-mouth (WOM) and magazine advertising and information systems (IS)-enabled methods of online WOM and online search remain unexplored. We estimate a multivariate negative binomial distribution (NBD) model on zip code–level customer counts