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Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Yu, Hongyana | Ji, Shenjiab; * | Yang, Delic
Affiliations: [a] College of Transportation and Communication, Shanghai Maritime University, Pudong, Shanghai, P.R.China | [b] College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia | [c] School of Business, Trinity University, San Antonio, TX, United States
Correspondence: [*] Shenjia Ji, College of Engineering and Computer Science, The Australian National University, 108 North Road, 2600 Canberra, ACT, Australia. E-mail: [email protected].
Abstract: Fake online reviews are so prevalent that e-commerce platforms attempt to control it from affecting the trustworthiness between buyers and sellers. The issue has also attracted sporadic scholarly endeavor to understand this new field. To address this issue, we propose a new model to examine three interrelated stakeholders of e-Commerce platforms: experienced buyers, future buyers and the online sellers in terms of purchasing behaviors and sales with three objectives. Experienced buyers influence future consumers’ behaviors and increase sales from sellers. Using data collected from the largest online e-commerce platform in China, we test relevant hypotheses. Our findings show that experienced buyers and their positive reviews increase future buyers’ purchasing and promote corporate sales. These findings contribute knowledge to the online feedback mechanism and literature on fake review studies. This study also provides a novel method to help buyers avoid fake online review from a market structure perspective.
Keywords: Online feedback mechanism, fake online reviews, e-commerce, experienced consumer reviews
DOI: 10.3233/JIFS-179933
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1601-1610, 2020
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