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      How buyers perceive the credibility of advisors in online marketplace: review balance, review amount and misattribution

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      How buyers perceive the credibility of advisors in online marketplace review balance, review amount and misattribution.pdf (304.5Kb)
      Date
      2015-02-12
      Author
      Vassileva, Julita
      Wu, Kewen
      Noorian, Zeinab
      Adaji, Ifeoma
      Publisher
      Springer Berlin Heidelberg
      Type
      Article
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      Abstract
      In an online marketplace, buyers rely heavily on reviews posted by previous buyers (referred to as advisors). The advisor’s credibility determines the persuasiveness of reviews. Much work has addressed the evaluation of advisors’ credibility based on their static profile information, but little attention has been paid to the effect of the information about the history of advisors’ reviews. We conducted three sub-studies to evaluate how the advisors’ review balance (proportion of positive reviews) affects the buyer’s judgement of advisor’s credibility (e.g., trustworthiness, expertise). The result of study 1 shows that advisors with mixed positive and negative reviews are perceived to be more trustworthy, and those with extremely positive or negative review balance are perceived to be less trustworthy. Moreover, the perceived expertise of the advisor increases as the review balance turns from positive to negative; yet buyers perceive advisors with extremely negative review balance as low in expertise. Study 2 finds that buyers might be more inclined to misattribute low trustworthiness to low expertise when they are processing high number of reviews. Finally, study 3 explains the misattribution phenomenon and suggests that perceived expertise has close relationship with affective trust. Both theoretical and practical implications are discussed.
      Citation
      1
      URI
      http://hdl.handle.net/10388/7752
      DOI
      10.1186/s40493-015-0013-5
      Subject
      Misattribution
      Online marketplace
      Source credibility
      Review balance
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      • Computer Science
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