Online ratings play an important role in many markets. However, how fast they can reveal seller types remains unclear. To study this question, we propose a new model in which a buyer learns about the seller’s type from previous ratings and her own experience and rates the seller if she learns...

Despite widespread use in online transactions, rating systems only provide summary statistics of buyers' diverse opinions at best. To investigate the consequences of this coarse form of information aggregation, we consider a dynamic lemons market in which buyers share their evaluations...

We develop and estimate a model of consumer search with spatial learning. Consumers make inferences from previously searched objects to unsearched objects that are nearby in attribute space, generating path dependence in search sequences. The estimated model rationalizes patterns in data on...

Many internet auction sites implement ascending-bid, second-price auctions. Empirically, last minute or quot;latequot; bidding is frequently observed in quot;hard-closequot; but not in quot;soft-closequot; versions of these auctions. In this paper, we introduce an independent private-value...

Consumers’ purchase decisions can be influenced by others’ opinions, i.e., word-of-mouth (WOM), and/or others’ actions, i.e., observational learning. While information technologies are creating increasing opportunities for firms to facilitate/manage these two types of social interaction,...