@inproceedings{82faa9c017aa461aba4e5fecad51be7a,
title = "How prior users' helpfulness votes on a review influence subsequent users' trust of the review and corresponding product evaluations in e-commerce context",
abstract = "We focus on how two numeric characteristics of prior users' votes influence user's attitude towards the product/service reviewed. These characteristics are 1) vote ratio and 2) vote magnitude. The former is the ratio of prior viewers who believe that a review is helpful, and the latter is the total number of prior viewers who vote the review. We draw on social influence theory and propose vote ratio influential across positive and negative reviews but vote magnitude influential only for negative reviews. We conduct two experiments to test the research model. Our research finds that regardless of the valence of reviews, vote ratio enhances trustworthiness and guide corresponding product evaluation. By contrast, vote magnitude is significantly influential only for the negative review. These findings contribute to review helpfulness literature and extend social influence theory. Our research also provides practical implications for online voting system providers, general participatory sites, and online retailers.",
keywords = "Helpfulness voting system, Social influence, Trust, Vote magnitude, Vote ratio",
author = "Jing Li and Xin Xu and Eric Ngai",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Information Systems. All rights reserved.; 24th Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018 ; Conference date: 16-08-2018 Through 18-08-2018",
year = "2018",
month = aug,
language = "English",
isbn = "9780996683166",
series = "Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018",
publisher = "Association for Information Systems",
booktitle = "Americas Conference on Information Systems 2018",
address = "United States",
}