Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93639
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Management and Marketing | en_US |
dc.creator | Wu, Y | en_US |
dc.creator | Ngai, EWT | en_US |
dc.creator | Wu, P | en_US |
dc.creator | Wu, C | en_US |
dc.date.accessioned | 2022-07-19T08:13:58Z | - |
dc.date.available | 2022-07-19T08:13:58Z | - |
dc.identifier.issn | 0167-9236 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93639 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2020 Elsevier B.V. All rights reserved. | en_US |
dc.rights | © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. | en_US |
dc.rights | The following publication Wu, Y., Ngai, E. W., Wu, P., & Wu, C. (2020). Fake online reviews: Literature review, synthesis, and directions for future research. Decision Support Systems, 132, 113280 is available at https://doi.org/10.1016/j.dss.2020.113280. | en_US |
dc.subject | Antecedents and consequences | en_US |
dc.subject | Electronic commerce | en_US |
dc.subject | Fake review | en_US |
dc.subject | Literature review | en_US |
dc.subject | Online review | en_US |
dc.title | Fake online reviews : literature review, synthesis, and directions for future research | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 132 | en_US |
dc.identifier.doi | 10.1016/j.dss.2020.113280 | en_US |
dcterms.abstract | Fake online reviews in e-commerce significantly affect online consumers, merchants, and, as a result, market efficiency. Despite scholarly efforts to examine fake reviews, there still lacks a survey that can systematically analyze and summarize its antecedents and consequences. This study proposes an antecedent–consequence–intervention conceptual framework to develop an initial research agenda for investigating fake reviews. Based on a review of the extant literature on this issue, we identify 20 future research questions and suggest 18 propositions. Notably, research on fake reviews is often limited by lack of high-quality datasets. To alleviate this problem, we comprehensively compile and summarize the existing fake reviews-related public datasets. We conclude by presenting the theoretical and practical implications of the current research. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Decision support systems, May 2020, v. 132, 113280 | en_US |
dcterms.isPartOf | Decision support systems | en_US |
dcterms.issued | 2020-05 | - |
dc.identifier.scopus | 2-s2.0-85081257189 | - |
dc.identifier.eissn | 1873-5797 | en_US |
dc.identifier.artn | 113280 | en_US |
dc.description.validate | 202207 bchy | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | MM-0090 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Ministry of Education of China; Natural Science Foundation of Hunan Province | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 26286212 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Wu_Fake_Online_Reviews.pdf | Pre-Published version | 1.08 MB | Adobe PDF | View/Open |
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