What Makes a Helpful Review? A “Meta-analysis” Based on Elaboration Likelihood Model

Abstract

Abstract: Online review helpfulness has increasingly become a hot topic in recent years. However, existing researches fail to reach consistent conclusions on the direction and strength of the factors affecting review helpfulness. Combining empirical studies on the helpfulness of online reviews at home and abroad, our work builds a framework based on elaboration likelihood model and utilizes Meta-analysis to reanalyze 540 effect values of 138 independent studies. Our work explores the quantitative relationship between review helpfulness and its influencing factors from both review (central route) and reviewer (peripheral route) characteristics, and further explores the reasons for the heterogeneity through Meta-regression and finds some interesting insights. This study has great significance for academic research and e-commerce practice.

Key words: online review helpfulness, Meta-analysis, elaboration likelihood model, review characteristics, reviewer characteristics

Wang Yani, Wang Jun, Yao Tang, Wang Taiming. What Makes a Helpful Review? A “Meta-analysis” Based on Elaboration Likelihood Model[J]. Management Review, 2021, 33(5): 246-256.

References

[1] 中国互联网络信息中心. 2015年中国网络购物市场研究报告[EB/OL]. http:/www. Cnnic. net. cn/, 2016-06-22
[2] Mudambi S., Schuff D. What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com[J]. MIS Quarterly, 2010,34(1):185-200
[3] Chua A. Y. K., Banerjee S. Helpfulness of User-generated Reviews as a Function of Review Sentiment, Product Type and Information Quality[J]. Computers in Human Behavior, 2016,54(C):547-554
[4] 张艳辉,李宗伟. 在线评论有用性的影响因素研究:基于产品类型的调节效应[J]. 管理评论, 2016,28(10):123-132
[5] Siering M., Muntermann J., Rajagopalan B. Explaining and Predicting Online Review Helpfulness:The Role of Content and Reviewer-related Signals[J]. Decision Support Systems, 2018,108(4):1-12
[6] 殷国鹏. 消费者认为怎样的在线评论更有用?——社会性因素的影响效应[J]. 管理世界, 2012,(12):115-124
[7] Liu Z., Park S. What Makes a Useful Online Review? Implication for Travel Product Websites[J]. Tourism Management, 2015,47(47):140-151
[8] 邬溪羽,郭斌,周莎莎,等. 在线评论如何影响消费者:基于社会影响视角的整合框架[J]. 西安电子科技大学学报(社会科学版), 2015,25(1):1-18
[9] 韩雁雁,张宁,房文敏. 基于Meta分析的在线评论有用性影响因素模型研究[J]. 信息系统学报, 2015, (15):1-13
[10] Lee S., Choeh J. Y. Predicting the Helpfulness of Online Reviews Using Multilayer Perceptron Neural Networks[J]. Expert Systems with Applications, 2014,41(6):3041-3046
[11] Huang A. H., Chen K., Yen D. C., et al. A Study of Factors That Contribute to Online Review Helpfulness[J]. Computers in Human Behavior, 2015,48(C):17-27
[12] 彭丽徽,李贺,张艳丰,等. 基于品牌声誉感知差异的在线评论有用性影响因素实证研究[J]. 情报科学, 2017,35(9):159-164
[13] Singh J., Irani S., Rana N. Predicting the "Helpfulness" of Online Consumer Reviews[J]. Journal of Business Research, 2017,70:346-355
[14] Petty R. E., Cacioppo J. T. The Elaboration Likelihood Model of Persuasion[J]. Advances in Experimental Social Psychology, 1986,19(1):123-205
[15] Sussman S., Siegal W. Informational Influence in Organizations:An Integrated Approach to Knowledge Adoption[J]. Information Systems Research, 2003,14(1):47-65
[16] 张艳辉,李宗伟,赵诣成. 基于淘宝网评论数据的信息质量对在线评论有用性的影响[J]. 管理学报, 2017,14(1):77-85
[17] 曾伟. 基于ELM的在线评论有用性研究——商品类型的调节影响[J]. 现代情报, 2014,34(12):148-153
[18] 武鹏飞,闫强. 在线评论对社交网络中电子口碑采纳的影响研究[J]. 北京邮电大学学报(社会科学版), 2015,17(1):52-61
[19] Baek H., Ahn J., Choi Y. Helpfulness of Online Consumer Reviews:Readers' Objectives and Review Cues[J]. International Journal of Electronic Commerce, 2012,17(2):99-126
[20] 郝媛媛,叶强,李一军. 基于影评数据的在线评论有用性影响因素研究[J]. 管理科学学报, 2010, 13(8):78-88
[21] Racherla P., Friske W. Perceived Usefulness of Online Consumer Reviews:An Exploratory Investigation Across Three Services Categories[J]. Electronic Commerce Research and Applications, 2012,11(6):548-559
[22] Kuan K., Hui K. What Makes a Review Voted? An Empirical Investigation of Review Voting in Online Review Systems[J]. Journal of the Association for Information Systems, 2015,16(1):48-71
[23] 李恒. 在线评论特征的维度综述[J]. 企业技术开发, 2015,34(3):119-120
[24] Ghose A., Ipeirotis P. G. Estimating the Helpfulness and Economic Impact of Product Reviews:Mining Text and Reviewer Characteristics[J]. IEEE Transactions on Knowledge and Data Engineering, 2011,23(10):1498-1512
[25] Zhou S., Guo B. The Interactive Effect of Review Rating and Text Sentiment on Review Helpfulness[A]. International Conference on Electronic Commerce and Web Technologies[C]. Springer International Publishing, 2015
[26] Korfiatis N., García B. E., Sánchez A. S. Evaluating Content Quality and Helpfulness of Online Product Reviews:The Interplay of Review Helpfulness Versus Review Content[J]. Electronic Commerce Research and Applications, 2012,11(3):205-217
[27] 闫强,孟跃. 在线评论的感知有用性影响因素——基于在线影评的实证研究[J]. 中国管理科学, 2013,21(S1):126-131
[28] 廖成林,蔡春江,李忆. 电子商务中在线评论有用性影响因素实证研究[J]. 软科学, 2013,27(5):46-50
[29] Forman C., Ghose A., Wiesenfeld B. Examining the Relationship Between Reviews and Sales:The Role of Reviewer Identity Disclosure in Electronic Markets[J]. Information Systems Research, 2008,19(3):291-313
[30] 张鑫,朱振中. 在线评论有用性影响因素研究综述[J]. 商业经济研究, 2017,(17):82-84
[31] Cao Q., Duan W., Gan Q. Exploring Determinants of Voting for the "Helpfulness" of Online User Reviews:A Text Mining Approach[J]. Decision Support Systems, 2011,50(2):511-521
[32] Pan Y., Zhang J. Q. Born Unequal:A Study of the Helpfulness of User-generated Product Reviews[J]. Journal of Retailing, 2011,87(4):598-612
[33] Salehan M., Dan J. K. Predicting the Performance of Online Consumer Reviews[J]. Decision Support Systems, 2016,81(C):30-40
[34] Jeppesen L., Frederiksen L. Why do Users Contribute to Firm-Hosted User Communities[J]. Organization Science, 2006,17(1):45-63
[35] 彭岚,周启海,邱江涛. 消费者在线评论有用性影响因素模型研究[J]. 计算机科学, 2011,38(8):205-207
[36] 郝清民,魏凤霞. 消费者感知的在线评论有用性影响因素研究[J]. 天津大学学报(社会科学版), 2014, 16(5):404-408
[37] Rosario A. B., Sotgiu F., Valck K. D., et al. The Effect of Electronic Word of Mouth on Sales:A Meta-Analytic Review of Platform, Product, and Metric Factors[J]. Journal of Marketing Research, 2016,53(3):297-318
[38] Purnawirawan N., Eisend M., Pelsmacker P. D., Dens N. A Meta-Analytic Investigation of the Role of Valence in Online Reviews[J]. Journal of Interactive Marketing, 2015,31:17-27
[39] Schweidel D., Moe W. Listening in on Social Media:A Joint Model of Sentiment and Venue Format Choice[J]. Journal of Marketing Research, 2014,51(4):387-402
[40] Koh N. S., Hu N., Clemons E. K. Do Online Reviews Reflect a Product's True Perceived Quality? An Investigation of Online Movie Reviews Across Cultures[J]. Electronic Commerce Research and Applications, 2010,9(5):374-385
[41] Farley J. U., Lehmann D. R., Sawyer A. Empirical Marketing Generalizations Using Meta-Analysis[J]. Marketing Science, 1995,14(3):36-46
[42] 范秀成,郑秋莹,姚唐. 顾客满意带来什么忠诚?[J]. 管理世界, 2009,(2):83-91
[43] Glass G. V. Integrating Findings:The Meta-Analysis of Research[J]. Review of Research in Education, 1977,5(1):351-379
[44] 郑秋莹,姚唐,范秀成,等. 基于Meta分析的"顾客满意-顾客忠诚"关系影响因素研究[J]. 管理评论, 2014,26(2):111-120
[45] 郭恺强,王洪伟,赵月. 消费者通过在线声誉系统发表评论的前因:基于TAM的实证研究[J]. 管理评论, 2014,26(9):180-190
[46] 曾欢. 旅游者对在线评论的信息采纳意愿研究[D]. 暨南大学硕士学位论文, 2013
[47] Peterson R. A., Brown S. P. On the Use of Beta Coefficients in Meta-Analysis[J]. Journal of Applied Psychology, 2005,90(1):175-181
[48] Rosenthal R. Parametric Measures of Effect Size[A]. In Cooper H., Hedges L. V.(Eds.). The Handbook of Research Synthesis[C]. New York:Russell Sage Foundation, 1994
[49] Matos C. A. D., Rossi C. A. V. Word of Mouth Communications in Marketing:A Meta-Analytic Review of the Antecedents and Moderators[J]. Journal of the Academy of Marketing Science, 2008,36(4):578-596
[50] 张骁,胡丽娜. 创业导向对企业绩效影响关系的边界条件研究——基于元分析技术的探索[J]. 管理世界, 2013,(6):99-110
[51] Hunter J. E., Schmidt F. L. Methods of Meta-analysis:Correcting Error and Bias in Research Findings[J]. Evaluation & Program Planning, 2006,29(3):236-237
[52] Hair J. F., Anderson R. E., Tatham R. L., et al. Multivariate Data Analysis (5th)[M]. Upper Saddle River, Prentice Hall:All Publications, 1998
[53] You Y., Vadakkepatt G., Joshi A. M. A Meta-analysis of Electronic Word-of-Mouth Elasticity[J]. Journal of Marketing, 2015,79(2):19-39
[54] Lau R., Liao S., Xu K. An Empirical Study of Online Consumer Review Spam:A Design Science Approach[A]. International Conference on Information Systems[C]. ICIS2010, Saint Louis, Missouri, USA, December. DBLP, 2010
[55] Feldman J. M., Lynch J. G. Self-Generated Validity and Other Effects of Measurement on Belief, Attitude, Intention and Behavior[J]. Journal of Applied Psychology, 1988,73(3):421-435
[56] Cohen J. Statistical Power Analysis for the Behavioral Science[J]. Journal of the American Statistical Association, 1988,84(363):19-74