|Title:||Two essays on reduction of fake reviews|
|Advisors:||Ngai, W. T. Eric (MM)|
|Subject:||Hong Kong Polytechnic University -- Dissertations|
Consumer behavior -- Mathematical models
|Department:||Department of Management and Marketing|
|Pages:||viii, 156 pages : color illustrations|
|Abstract:||The thesis includes two essays. In this thesis, two novel mathematical models are developed to analyze the effect of consumer behavior on the number of fake reviews. Moreover, the approaches to effectively reduce fake reviews are explored. Four areas are solved by synthetically analyzing consumer behavior. These areas are the motivation values of firms posting fake reviews, type of firms with high motivation value, characteristics of fake reviews and the efficient reduction of fake reviews by consumers, firms and online platforms. An original agent-based model depicting the dynamic influence of prior reviews on subsequent reviews is proposed to describe consumer behavior. This model is applied to quantify the motivation values of firms posting fake reviews to determine the effective approaches to reduce fake reviews. A series of computer simulation are performed to corroborate that the average star ratings of products normally converge on actual quality, and that fake reviews significantly increase the convergent value. I quantified and compared the motivation values of firms posting fake reviews under different scenarios. The results show that motivation values generally decrease with the existing number of unscrupulous products. Firms are highly motivated to post fake reviews under three situations, namely, facing fierce competition, selling low-quality products and obtaining numerous consumers. The results also reveal that the current exhibition rule for ordering online reviews unwittingly increases fake reviews. This thesis builds an original game-theoretical model, wherein two competing firms sell substitutable products in a platform, and successively observes equilibrium results in three different situations: two players (one firm and platform), three players (two firms and platform) in non-cooperative cases, and three players in cooperative cases. To the best of my knowledge, this study is the first to explore ways on how to reduce fake reviews through game-theoretical model, the first to consider the dynamic changing process of loyal consumers in game-theoretical model, and also the first to examine online reviews from a novel perspective of platforms. The results show that the cooperative case constantly benefits firms, but it would damage the platform and occasionally lead to additional fake reviews. By analyzing and comparing equilibrium results, we find that the platform with many fake reviews bears the following characteristics: (1) low sensitive degree of fake reviews on platform's reputation; (2) prefers to sell products with low unit misfit cost; and (3) improper degree of penalty. Firms prefer to issue fake positive reviews to themselves, instead of releasing fake negative reviews to their opponents.|
|Rights:||All rights reserved|
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