Many existing studies have considered the factors influencing review helpfulness,mainly focusing on reviewer impact,review informativeness,and managerial response,based on signaling theory.However,previous studies hav...Many existing studies have considered the factors influencing review helpfulness,mainly focusing on reviewer impact,review informativeness,and managerial response,based on signaling theory.However,previous studies have simply regarded these factors as independent signals,thus ignoring their in-depth transmission and reception processes.The conclusions about the impact of reviewers on review helpfulness are also inconsistent due to the inaccurate measure-ment of variables.To fill the above gaps,we followed the signaling timeline theoretical framework used in signaling the-ory and employed a bootstrapping analysis to examine how reviewer impact,review informativeness,and hotel manageri-al responses interact to influence review helpfulness.In this study,we used a unique dataset that included official labels from one leading online travel agency.The results show that reviewer impact may affect review helpfulness sequentially through review informativeness and hotel managerial response.Furthermore,by using official labels,both reviewer expert-ise and reviewer experience significantly affect review helpfulness.Finally,we discussed the theoretical and practical im-plications of these findings.展开更多
When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provi...When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provide a highly convenient channel for consumers to generate and retrieve product reviews. In addition, consumers can also vote reviews perceived to be helpful in making their decision. However, due to diverse characteristics, consumers can have different preferences on products and reviews. Their voting behavior can be influenced by reviews and existing review votes. To explore the influence mechanism of the reviewer, the review, and the existing votes on review helpfulness, we propose three hypotheses based on the consumer perspective and perform statistical tests to verify these hypotheses with real review data from Amazon. Our empirical study indicates that review helpfulness has significant correlation and trend with reviewers, review valance, and review votes. In this paper, we also discuss the implications of our findings on consumer preference and review helpfulness.展开更多
基金supported by the Philosophy and Social Science Planning Program of Shanghai(2021BGL018).
文摘Many existing studies have considered the factors influencing review helpfulness,mainly focusing on reviewer impact,review informativeness,and managerial response,based on signaling theory.However,previous studies have simply regarded these factors as independent signals,thus ignoring their in-depth transmission and reception processes.The conclusions about the impact of reviewers on review helpfulness are also inconsistent due to the inaccurate measure-ment of variables.To fill the above gaps,we followed the signaling timeline theoretical framework used in signaling the-ory and employed a bootstrapping analysis to examine how reviewer impact,review informativeness,and hotel manageri-al responses interact to influence review helpfulness.In this study,we used a unique dataset that included official labels from one leading online travel agency.The results show that reviewer impact may affect review helpfulness sequentially through review informativeness and hotel managerial response.Furthermore,by using official labels,both reviewer expert-ise and reviewer experience significantly affect review helpfulness.Finally,we discussed the theoretical and practical im-plications of these findings.
基金financially supported by DNSLAB, China Internet Network Information Center
文摘When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provide a highly convenient channel for consumers to generate and retrieve product reviews. In addition, consumers can also vote reviews perceived to be helpful in making their decision. However, due to diverse characteristics, consumers can have different preferences on products and reviews. Their voting behavior can be influenced by reviews and existing review votes. To explore the influence mechanism of the reviewer, the review, and the existing votes on review helpfulness, we propose three hypotheses based on the consumer perspective and perform statistical tests to verify these hypotheses with real review data from Amazon. Our empirical study indicates that review helpfulness has significant correlation and trend with reviewers, review valance, and review votes. In this paper, we also discuss the implications of our findings on consumer preference and review helpfulness.
