The effect of user-controllable filters on the prediction of online hotel reviews

Ya Han Hu; Kuanchin Chen; Pei Ju Lee

doi:10.1016/j.im.2016.12.009

The effect of user-controllable filters on the prediction of online hotel reviews

Ya Han Hu, Kuanchin Chen, Pei Ju Lee

資訊管理學系

研究成果: 雜誌貢獻 › 期刊論文 › 同行評審

59 引文斯高帕斯（Scopus）

摘要

Product reviews have gained much popularity in recent years. This study examines the theoretical foundation of review helpfulness and reports how the interactions among three user-controllable filters together with three groups of predictors affect review helpfulness. Reviews from TripAdvisor.com were analyzed against three analytical models. The results show that these groups of variables have a varying effect on different user-controllable filters. Review rating and number of words are key predictors of helpfulness across all three filters. The recency, frequency, and monetary (RFM) model has received a consistent support across all filters as well. Managerial implications are provided.

原文	???core.languages.en_GB???
頁（從 - 到）	728-744
頁數	17
期刊	Information and Management
卷	54
發行號	6
DOIs	https://doi.org/10.1016/j.im.2016.12.009
出版狀態	已出版 - 9月 2017

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10.1016/j.im.2016.12.009

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AB - Product reviews have gained much popularity in recent years. This study examines the theoretical foundation of review helpfulness and reports how the interactions among three user-controllable filters together with three groups of predictors affect review helpfulness. Reviews from TripAdvisor.com were analyzed against three analytical models. The results show that these groups of variables have a varying effect on different user-controllable filters. Review rating and number of words are key predictors of helpfulness across all three filters. The recency, frequency, and monetary (RFM) model has received a consistent support across all filters as well. Managerial implications are provided.

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The effect of user-controllable filters on the prediction of online hotel reviews

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