Professors Anindya Ghose and Panos Ipeirotis of NYU Stern and Professor Beibei Li of Carnegie Mellon won the Best Theme Paper Award for their paper “Search Less, Find More? Examining Limited Consumer Search with Social Media and Product Search Engines,” at the International Conference on Information Systems (ICIS) 2012 Conference. Beibei Li received her Ph.D. from NYU Stern in 2012.
With the proliferation of social media, consumers’ cognitive costs during information-seeking can become non-trivial during an online shopping session. We propose a dynamic structural model of limited consumer search that combines an optimal stopping framework with an individual-level choice model. We estimate the parameters of the model using a dataset of approximately 1 million online search sessions resulting in bookings in 2117 U.S. hotels. The model allows us to estimate the monetary value of the search costs incurred by users of product search engines in a social media context. On average, searching an extra page on a search engine costs consumers $39.15 and examining an additional offer within the same page has a cost of $6.24, respectively. A good recommendation saves consumers, on average, $9.38, whereas a bad one costs $18.54. Our dynamic model indicates that consumers pay a lot of attention to non-price factors during an online hotel search.
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