An Economic Analysis of Consumer Learning for Online Entertainment Shopping

Entertainment shopping supported by pay-to-bid auction is an emerging online business model in recent years. Consumers expect both entertainment value and monetary return from their participation in entertainment shopping. We propose a dynamic structural model to study consumers’ online shopping behavior. We analyze the learning process of consumers from two perspectives based on the Bayesian updating framework: (1) consumers update their beliefs about the entertainment value through their repeated personal participation experiences, and (2) consumers infer the expected monetary payoffs on the website by observing the publically available auction ending price information. We estimate the model using a large dataset from an entertainment shopping website. The results show that consumers generally show risk-seeking preferences. They significantly overestimate the entertainment value but underestimate the level of competition at the beginning of their participation, which helps to explain the observed decreasing participation rate over time. Through counterfactual policy simulations, we discuss the website design implications and recommend strategies to create a sustainable business model.

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