The Research on Joint Effect of Online Reviews and Reputation System


Student thesis: Doctoral Thesis

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Awarding Institution
Award date10 Dec 2018


Online reputation systems are critical in reducing information asymmetry in online platforms. In this thesis, we study how the introduction of buyer protection programs, such as guaranteed return, third-party escrow services and credit card protections, influences the joint effect of online reputation systems and online reviews on seller competition.

More specifically, in the first study, we empirically examine actual sales with respect to the dynamic growth of the reputation system in the presence of buyer protection mechanisms. We find that implementing buyer protection mechanisms benefits sellers. But the impact of the reputation system is higher on the sales of low-reputation sellers than on those of high-reputation sellers in the presence of such mechanisms. For the low-reputation sellers, the reputation system is indeed effective in helping good sellers to sell. However, for the high-reputation sellers, the reputation systems only help sales when there is a large product variety. More importantly, experienced buyers are more likely to purchase search goods from new sellers than experience goods.

Since consumers are more assured of buying from the low-reputation sellers with such buyer protection mechanisms in place, in the second study, we explore whether such mechanisms benefit the low-reputation sellers more than the high-reputation sellers. Do such mechanisms help the market become more evenly distributed among sellers with different reputation levels? We first develop a theoretical model to study the joint effect of online reputation systems and buyer-protection mechanisms. We examine this impact assuming consumers are either forward-looking (that is, they maximize their long-term profits) or myopic.

Surprisingly, we find that such mechanisms are effective only in a market with forward-looking sellers who maximize long-term profits. When sellers are myopic, such mechanisms benefit the low-reputation sellers only in the short term and can be detrimental in the long term when the high-reputation seller responds to the introduction of such mechanisms by adjusting their pricing strategies. As a result, consumers rely more on reputation systems, and the online market can be more unevenly distributed in the long run in the sense that high-reputation sellers occupy a larger market share. Using a dataset from one of the largest online B2C markets in China, we also empirically evaluate these theoretical predictions.

Finally, we consider whether and how two forms of online reviews, namely, text reviews as well as numerical ratings, reflect public opinion differently. We first extend Anderson’s (1998) model to consider two ways that consumers input their opinions with different costs. Based on the asymmetric U-shaped relationship between consumers’ word-of-mouth activity and customer satisfaction, we develop a hypothesis to test the relationship between the outcomes of the online review, using a dataset from an online video news sharing platform, We find that whether the two mechanisms deliver a consistent message depends on the underlying relationship between customer satisfaction and the input mechanism. If their relationship follows an asymmetric U-shaped pattern, there might exist a positive relationship between the outcomes of click-based input mechanisms and the outcomes of a text input mechanism. By choosing the low-cost click-based input mechanism to gather opinions from the public, we can quickly figure out public attitudes towards certain video news items. For news in other categories, we might not find a consistent growing trend between these two mechanisms. Therefore, we need to rely on both mechanisms to interpret public opinion regarding video news in those categories.

    Research areas

  • online rating/review, buyer protection mechanism, online reputation system, pricing strategy, high-reputation seller, low-reputation seller, word-of-mouth activity