Uncorrected Author Proof Human Systems Management xx (20xx) x–xx DOI 10.3233/HSM-200868 IOS Press 1 Too obvious to ignore: Influence of popular reviews on consumer online purchasing decisions 1 2 3 Xin Su a and Mingzi Niu b,∗ 4 a School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China 5 b Department of Economics, Rice University, Houston, TX, USA 6 Received 3 January 2020 7 8 Accepted 7 June 2020 9 Abstract. 10 BACKGROUND: Online reviews, as an important way for consumers to understand product information, have an important impact on consumers’ online shopping decisions. A lot of useful explorations have been made on the role of online reviews in existing empirical research, but the interaction between online reviews and its subdivided dimensions have not been explored. 11 12 13 OBJECTIVE: Based on the two-step flow theory, this article aims to explore the impact of online review valence, review volume, and their interactions on online sales, focusing on the question of what are the factors that influence customer purchase decisions and what is the moderating effect of popular reviews on review valence. 14 15 16 METHODS: Empirical analysis was done by tracking the product information and online sales data of mobile phone products and laptops in search goods category on the Amazon.cn website. 17 18 RESULTS/CONCLUSION: The research results found that: (1) in terms of review valence, the average score significantly promotes online sales, and negative word-of-mouth significantly decreases online sales; (2) as for review volume, the number of total reviews and popular reviews have significantly promote online sales; (3) regarding the interactions between the review valence and review volume, popular reviews significantly enhance the impact of review valence on online sales, playing a complementary effect for review valence. 19 20 21 22 23 Keywords: Online review, opinion leader, popular comment, online sales, search goods 24 Xin Su is an assistant professor in 25 School of Economics and Manage- 26 ment, Beijing University of Posts 27 and Telecommunications. She got her 28 PhD in School of Business, Ren- 29 min University of China. Her research 30 focuses on customer behaviour analy- 31 sis and big data driven management 32 innovation. Her work has appeared 33 in Journal of Cleaner Production, 34 Chaos, Solitons and Fractals, Journal 35 of Intellectual Capital, Applied Eco- 36 nomics et al. She can be contacted at: 37 E-mail: xin.su@bupt.edu.cn. 38 ∗ Corresponding author: Mingzi Niu, Department of Eco- nomics, Rice University, Kraft Hall 443, Houston, TX, 77005, USA. E-mail: mingzi.niu@rice.edu. Mingzi Niu is a PhD candidate in 39 Department of Economics, Rice Uni- 40 versity. She got her bachelor degree in 41 School of Economics, Peking Univer- 42 sity and master degree in Department 43 of Economics, Duke University. Her 44 research focuses on applied micro the- 45 ory. She can be contacted at: E-mail: 46 mingzi.niu@rice.edu. 47 48 1. Introduction 49 With the expansion of online shopping customer 50 groups and the obvious differences among users, 51 0167-2533/20/$35.00 © 2020 – IOS Press and the authors. All rights reserved