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The Impact Research Of Online Reviews’ Sentiment Polarity Presentation On Consumer Purchase Decision

Posted on:2016-12-21Degree:MasterType:Thesis
Country:ChinaCandidate:L WangFull Text:PDF
GTID:2309330467992043Subject:Industrial Economics
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With the rapid development of e-commerce, online reviews have become an important source of information for consumers to evaluate the quality of the products. To facilitate consumer viewing of online reviews, many e-commerce sites try to subdivide online reviews, making online review presentation a constantly changing resource. According to online reviews’ sentiment polarity, namely, the positive or negative sentiment tendency of online reviews, the presentation of online reviews is divided into two categories:one type is the mixed presentation of online reviews’ sentiment polarity (hereinafter referred to as mixed presentation), under which all of online reviews are successively presented in chronological order without classification, and the other type is the classified presentation of online reviews’ sentiment polarity (hereinafter referred to as classified presentation), under which positive, medium and negative reviews are presented, respectively in chronological order. As China’s two largest B2C enterprise, the market share of Tmall.com and Jingdong.com accounts for72%of the overall sales in the B2C market. However, the online reviews’presentation between the two websites is quite different, which of Tmall.com is mixed presentation while which of Jingdong.com includes both mixed presentation and classified presentation. According to previous studies, information presentation affects a consumer’s cognitive behavior and consumers have the characteristic of loss aversion. Therefore, compared with mixed presentation, classified presentation is likely to lead to a consumer’s higher awareness of negative reviews by highlighting the negative reviews, which will affect the purchase decision process.The existing research of online reviews’ sentiment polarity mainly focuses on the study of the leading factors, the result factors and the moderating factors of online reviews’ sentiment polarity, and according to the different effect of the different sentiment polarity on the consumer purchase decision, the scholars conducted superficial research on the management of the online reviews’emotional polarity. However, The existing research pays less attention to the impact of online reviews presentation on consumers’decision-making, especially lacks discussion on the interaction effect between involvement and online reviews presentation, which leads to the management measures research on online reviews emotional polarity presentation still at the blank stage.Because online-shopping is risky, there is a strong need to develop better presentation of online reviews, which may reduce the perceived risk and create more pleasurable shopping experiences. To test the impact of online reviews’sentiment polarity presentation, this paper adopts a scenario experiment to study consumers’ decision-making process under the two scenarios of mixed presentation and classified presentation of online reviews collected from Jingdong.com in China: focusing on the comparative analysis of the differences of the consumers’ perceived risk, purchase intention and purchase delay, and further studying the interaction effect of involvement and online reviews’ sentiment polarity presentation. The results show compared with mixed presentation, classified presentation can reduce purchase intention and increase purchase delay due to the existence of loss aversion and availability heuristic. Further, the paper also confirms there is a significant interaction effect between involvement and online reviews’ sentiment polarity presentation. Based on the results, the paper advances related suggestions on the management activities of online reviews’ presentation from the perspective of network marketing.
Keywords/Search Tags:online reviews, sentiment polarity, informationpresentation, involvement, decision confusion
PDF Full Text Request
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