Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1056
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBanerjee, Shankhadeep
dc.contributor.authorBhattacharyya, Samadrita
dc.contributor.authorBose, Indranil
dc.date.accessioned2021-08-26T06:03:23Z-
dc.date.available2021-08-26T06:03:23Z-
dc.date.issued2017
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85012237629&doi=10.1016%2fj.dss.2017.01.006&partnerID=40&md5=6f0e3e26e559960bad50ce8d43fee3ca
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/1056-
dc.descriptionBanerjee, Shankhadeep, Indian Institute of Management Calcutta, India; Bhattacharyya, Samadrita, Indian Institute of Management Calcutta, India; Bose, Indranil, Indian Institute of Management Calcutta, India
dc.descriptionISSN/ISBN - 01679236
dc.descriptionpp.17-26
dc.descriptionDOI - 10.1016/j.dss.2017.01.006
dc.description.abstractWhy do top movie reviewers receive invitations to exclusive screenings? Even popular technology bloggers get free new gadgets for reviewing. How much do these reviewers really matter for businesses? While the impact of online reviews on sales of products and services has been well established, not much literature is available on impact of reviewers for businesses. Source credibility theory expounds how a communication's persuasiveness is affected by the perceived credibility of its source. So, perceived trustworthiness of reviewers should influence acceptance of reviews, and consequently should have an indirect impact on sales. Using local business review data from Yelp.com, this paper successfully tests the premise that reviewer trustworthiness positively moderates the impact of review-based online reputation on business patronages. Given the importance of reviewer trustworthiness, the next logical question is � how to estimate and predict it, if no direct proxy is available? We propose a theoretical model with several reviewer characteristics (positivity, involvement, experience, reputation, competence, sociability) affecting reviewer trustworthiness, and find all factors to be significant using the robust regression method. Further, using these factors, a predictive classification of reviewers into high and low level of potential trustworthiness is done using logistic regression with nearly 83% accuracy. Our findings have several implications - firstly, businesses should focus on building a good review-based online reputation; secondly, they should encourage top trustworthy reviewers to review their products and services; and thirdly, trustworthy reviewers could be identified and ranked using reviewer characteristics. � 2017 Elsevier B.V.
dc.publisherSCOPUS
dc.publisherDecision Support Systems
dc.publisherElsevier B.V.
dc.relation.ispartofseries96
dc.subjectElectronic word-of-mouth
dc.subjectOnline reviewers
dc.subjectOnline reviews
dc.subjectOnline trust
dc.subjectPredictive model
dc.subjectRegression analysis
dc.subjectReviewer characteristics
dc.subjectTrustworthiness
dc.subjectYelp
dc.titleWhose online reviews to trust? Understanding reviewer trustworthiness and its impact on business
dc.typeArticle
Appears in Collections:Management Information Systems

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.