Online WOM Spillover Effect in the U.S. Automobile Industry

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Wang, Yen-Yao
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Online Word-of-Mouth (WOM) is an important aspect of consumer-firm relationship and is a leading indicator of product performance. However, prior research focuses considerably on the static view of online WOM. This paper attempts to explicate the dynamics of the spillover effects in online WOM in the U.S. automobile industry. I employed the Bayesian approach using Markov Chain Monte Carlo (MCMC) methods for model estimation. The results suggest that there is a pressing need for extending to the dynamic view of online WOM by examining the spillover effects. \ \ Keywords \ Online WOM, spillover effects, U.S. automobile industry, Bayesian.