The Korean Economic Review
Information Quality of Online Reviews in the Presence of Potentially Fake Reviews
Wonho Song (Chung-Ang University), Sangkon Park (Korea Culture & Tourism Institute) and Doojin Ryu (Sungkyunkwan University)Year 2017Vol. 33No. 1
Abstract
Online reviews are important in the evaluation of product quality. This paper seeks toassess information quality of online reviews using the TripAdvisor data for Korean hotels.We first estimate the review model developed by Dai, Jin, Lee, and Luca (2012) and showthat high-quality reviews contain most of the information for the quality of hotels. Second,we assess the degree of distortions caused by fake reviews through numerical experiments andshow that the distortions of fake reviews are serious. Third, we compare the simple averageand weighted average aggregation methods. Weighted average method is better than simpleaverage in finding the quality of hotels but it is more vulnerable to fake reviews. Fourth, wesuggest excluding low-quality reviews to deal with fake reviews and show that the benefit ofavoiding serious distortions from potentially fake reviews is greater than the cost of losinginformation from low-quality reviews.