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Understanding review helpfulness as a function of reviewer reputation, review rating, and review depth

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  • Alton Y.K. Chua
  • Snehasish Banerjee

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  • Alton Y.K. Chua & Snehasish Banerjee, 2015. "Understanding review helpfulness as a function of reviewer reputation, review rating, and review depth," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 354-362, February.
    • Handle: RePEc:bla:jinfst:v:66:y:2015:i:2:p:354-362
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    File URL: http://hdl.handle.net/10.1002/asi.23180
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    Citations

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    Cited by:

    1. Hu, Xin & He, Liuyi & Liu, Junjun, 2022. "Status reinforcing: Unintended rating bias on online shopping platforms," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    2. Guha Majumder, Madhumita & Dutta Gupta, Sangita & Paul, Justin, 2022. "Perceived usefulness of online customer reviews: A review mining approach using machine learning & exploratory data analysis," Journal of Business Research, Elsevier, vol. 150(C), pages 147-164.
    3. Banerjee, Snehasish & Chua, Alton Y.K., 2020. "How alluring is the online profile of tour guides?," Annals of Tourism Research, Elsevier, vol. 81(C).
    4. Andreas J. Steur & Mischa Seiter, 2021. "Properties of feedback mechanisms on digital platforms: an exploratory study," Journal of Business Economics, Springer, vol. 91(4), pages 479-526, May.
    5. Hang Yin & Shuang Zheng & William Yeoh & Jie Ren, 2021. "How online review richness impacts sales: An attribute substitution perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(7), pages 901-917, July.
    6. Wu, Xiaoyue & Jin, Liyin & Xu, Qian, 2021. "Expertise Makes Perfect: How the Variance of a Reviewer's Historical Ratings Influences the Persuasiveness of Online Reviews," Journal of Retailing, Elsevier, vol. 97(2), pages 238-250.
    7. Xunhua Guo & Guoqing Chen & Cong Wang & Qiang Wei & Zunqiang Zhang, 2021. "Calibration of Voting-Based Helpfulness Measurement for Online Reviews: An Iterative Bayesian Probability Approach," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 246-261, January.
    8. Meek, Stephanie & Wilk, Violetta & Lambert, Claire, 2021. "A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews," Journal of Business Research, Elsevier, vol. 125(C), pages 354-367.
    9. Yani Wang & Jun Wang & Tang Yao, 2019. "What makes a helpful online review? A meta-analysis of review characteristics," Electronic Commerce Research, Springer, vol. 19(2), pages 257-284, June.
    10. Hossin Md Altab & Mu Yinping & Hosain Md Sajjad & Adasa Nkrumah Kofi Frimpong & Michelle Frempomaa Frempong & Stephen Sarfo Adu-Yeboah, 2022. "Understanding Online Consumer Textual Reviews and Rating: Review Length With Moderated Multiple Regression Analysis Approach," SAGE Open, , vol. 12(2), pages 21582440221, June.
    11. Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    12. Baidyanath Biswas & Pooja Sengupta & Boudhayan Ganguly, 2022. "Your reviews or mine? Exploring the determinants of “perceived helpfulness” of online reviews: a cross-cultural study," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1083-1102, September.
    13. Xiang, Zheng & Du, Qianzhou & Ma, Yufeng & Fan, Weiguo, 2017. "A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism," Tourism Management, Elsevier, vol. 58(C), pages 51-65.
    14. Christoph Rohde & Alexander Kupfer & Steffen Zimmermann, 2022. "Explaining reviewing effort: Existing reviews as potential driver," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1169-1185, September.
    15. Wenyi Tay & Xiuzhen Zhang & Sarvnaz Karimi, 2020. "Beyond mean rating: Probabilistic aggregation of star ratings based on helpfulness," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(7), pages 784-799, July.
    16. Kavita Rawat & Sunita Kumar, 2022. "A Meta-Analysis on the Determinants of Online Product Reviews with Moderating Effect of Product Type," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 11, November.
    17. Navid Aghakhani & Onook Oh & Dawn Gregg & Hemant Jain, 2023. "How Review Quality and Source Credibility Interacts to Affect Review Usefulness: An Expansion of the Elaboration Likelihood Model," Information Systems Frontiers, Springer, vol. 25(4), pages 1513-1531, August.
    18. Xiaomo Liu & G. Alan Wang & Weiguo Fan & Zhongju Zhang, 2020. "Finding Useful Solutions in Online Knowledge Communities: A Theory-Driven Design and Multilevel Analysis," Information Systems Research, INFORMS, vol. 31(3), pages 731-752, September.
    19. Supriyo Mandal & Abyayananda Maiti, 2022. "Network promoter score (NePS): An indicator of product sales in E-commerce retailing sector," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1327-1349, September.
    20. Yanni Ping & Chelsey Hill & Yun Zhu & Jorge Fresneda, 2023. "Antecedents and consequences of the key opinion leader status: an econometric and machine learning approach," Electronic Commerce Research, Springer, vol. 23(3), pages 1459-1484, September.
    21. Srikanth Parameswaran & Pubali Mukherjee & Rohit Valecha, 2023. "I Like My Anonymity: An Empirical Investigation of the Effect of Multidimensional Review Text and Role Anonymity on Helpfulness of Employer Reviews," Information Systems Frontiers, Springer, vol. 25(2), pages 853-870, April.
    22. Xiang, Diandian & Li, Xia & Hampson, Daniel Peter, 2023. "Service exchange activities in the sharing economy: Professional versus amateur peer providers," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    23. Yang, Luming & Xu, Min & Xing, Lin, 2022. "Exploring the core factors of online purchase decisions by building an E-Commerce network evolution model," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).

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