A study of factors that contribute to online review helpfulness

被引:259
作者
Huang, Albert H. [1 ]
Chen, Kuanchin [2 ]
Yen, David C. [3 ]
Tran, Trang P. [3 ]
机构
[1] Univ Pacific, Eberhardt Sch Business, Stockton, CA 95211 USA
[2] Western Michigan Univ, Dept Business Informat Syst, Kalamazoo, MI 49008 USA
[3] SUNY Coll Oneonta, Sch Business & Econ, Oneonta, NY 13820 USA
关键词
Online reviews; Product reviews; Review helpfulness; Review sidedness; WORD-OF-MOUTH; SOURCE CREDIBILITY; CONSUMER REVIEWS; MODERATING ROLE; CUSTOMER REVIEWS; PRODUCT REVIEWS; INFORMATION; QUALITY; SALES; IMPACT;
D O I
10.1016/j.chb.2015.01.010
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Helpfulness of online reviews is a multi-faceted concept that can be driven by several types of factors. This study was designed to extend existing research on online review helpfulness by looking at not just the quantitative factors (such as word count), but also qualitative aspects of reviewers (including reviewer experience, reviewer impact, reviewer cumulative helpfulness). This integrated view uncovers some insights that were not available before. Our findings suggest that word count has a threshold in its effects on review helpfulness. Beyond this threshold, its effect diminishes significantly or becomes near non-existent. Reviewer experience and their impact were not statistically significant predictors of helpfulness, but past helpfulness records tended to predict future helpfulness ratings. Review framing was also a strong predictor of helpfulness. As a result, characteristics of reviewers and review messages have a varying degree of impact on review helpfulness. Theoretical and practical implications are discussed. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:17 / 27
页数:11
相关论文
共 73 条
[1]   Consumer response to negative publicity: The moderating role of commitment [J].
Ahluwalia, R ;
Burnkrant, RE ;
Unnava, HR .
JOURNAL OF MARKETING RESEARCH, 2000, 37 (02) :203-214
[2]  
Aizawa A., 2000, SIGIR Forum, V34, P104
[3]  
Al-Othman N.M. A., 2003, READING MATRIX, V3, P120
[4]   Assessing information quality of e-learning systems: a web mining approach [J].
Alkhattabi, Mona ;
Neagu, Daniel ;
Cullen, Andrea .
COMPUTERS IN HUMAN BEHAVIOR, 2011, 27 (02) :862-873
[5]   REGRESSION-ANALYSIS WHEN DEPENDENT VARIABLE IS TRUNCATED NORMAL [J].
AMEMIYA, T .
ECONOMETRICA, 1973, 41 (06) :997-1016
[6]   Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database [J].
Anderson, Michael ;
Magruder, Jeremy .
ECONOMIC JOURNAL, 2012, 122 (563) :957-989
[7]  
[Anonymous], 1963, MATH THEORY COMMUNIC
[8]  
[Anonymous], 2008, P INT S WIK
[9]   On the Measurability of Information Quality [J].
Arazy, Ofer ;
Kopak, Rick .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2011, 62 (01) :89-99
[10]   Helpfulness of Online Consumer Reviews: Readers' Objectives and Review Cues [J].
Baek, Hyunmi ;
Ahn, JoongHo ;
Choi, Youngseok .
INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2012, 17 (02) :99-126