A Mixed-Methods Approach to Disclose the Influence of Twofold Information Usefulness on Sales

System Sciences(2015)

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摘要
In the current study, we examine the relative effects of the two types of consumer reviews (i.e., Positive and negative eWOM) on consumers' purchase decisions, and the moderating roles of the two types of information usefulness (i.e., Explicit usefulness and implicit usefulness). Analyzing a large-scale panel data collected from an online shopping site, we found that consumers' purchase decisions are indeed influenced by both positive and negative reviews. In addition, a SVM classifier is built to identify the implicit useful reviews. Our results show that information usefulness, including explicit and implicit useful information, has an important moderating role in consumers' purchase decisions. This study contributes to the existing literature by explaining how information usefulness (i.e., Explicit and implicit usefulness) moderates the influence of consumer review on consumers' purchase decisions, and providing a classifier for consumer reviews through sentiment analysis in online social shopping sites. The results offer important and interesting insights to IS research and practice.
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关键词
consumer behaviour,pattern classification,retail data processing,social networking (online),support vector machines,is research,svm classifier,consumer purchase decisions,consumer reviews,implicit useful reviews,large-scale panel data,mixed-methods approach,negative reviews,online shopping site,online social shopping sites,positive reviews,sentiment analysis,twofold information usefulness,consumer purchase decision,explicit usefulness,implicit usefulness,information usefulness,mixed-methods,negative electronic word of mouth,positive electronic word of mouth,social commerce,semantics,data models,information systems,mixed methods
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