کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
554758 873879 2012 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
To whom should I listen? Finding reputable reviewers in opinion-sharing communities
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
To whom should I listen? Finding reputable reviewers in opinion-sharing communities
چکیده انگلیسی

Online opinion-sharing communities, which allow members to express personal opinions and preferences about specific products, provide important channels for consumers to learn about product quality and support their purchase decision process. Firms can use these reviews to understand customers' responses to their products and improve their products accordingly. Furthermore, opinion-sharing communities provide an alternative, effective marketing channel to firms by offering electronic word of mouth (eWOM). However, due to the openness and anonymity of opinion-sharing communities, their members face a challenging issue, that is, whether to believe or disbelieve information provided by other members. This study attempts to discriminate members (i.e., reviewers) with a high reputation from those with a low reputation on the basis of members' web trust network and review behaviors in an opinion-sharing community. We collected sample data pertaining to four product categories from Epinions.com to test our research model. The results indicate that four variables (trust intensity, average trust intensity of trustors, degree of review focus in the target category, and average product rating in the target category) successfully discriminate reviewers into the two groups, and product type is a significant control variable. These findings not only help firms identify reputable reviewers for marketing campaign purposes but also enable the members of an opinion-sharing community to determine who reputable reviewers are and whose reviews they should trust.


► Our model discriminates high-reputation reviewers from low-reputation reviewers.
► Factors derived from members' web trust network and review behavior were examined.
► Our proposed reputation estimation model can supplement the user-driven approach.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 53, Issue 3, June 2012, Pages 534–542
نویسندگان
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