Impact of Online Review Grouping on Consumers' System Usage Behavior: A System Restrictiveness Perspective

Impact of Online Review Grouping on Consumers' System Usage Behavior: A System Restrictiveness Perspective

Jia Li (School of Business, East China University of Science and Technology, Shanghai, China), Xinmiao Li (School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China), David C. Yen (School of Economics and Business, SUNY College at Oneonta, Oneonta, NY, USA) and Pengzhu Zhang (Antai College of Economics and Management, Shanghai Jiaotong University Shanghai, China)
Copyright: © 2016 |Pages: 22
DOI: 10.4018/JGIM.2016100103

Abstract

Information overload is one of the major challenges for online shoppers. One possible solution to this aforementioned problem is to take advantage of the interactive decision aids (IDAs). Prior studies on IDAs have mainly focused on information overload problems caused by the products (e.g., recommendation agents) and hence, have overlooked the information overload problems related to online reviews. However, online reviews are becoming more popular and turning into a major information source in consumer purchase decisions. To bridge this gap, this study investigates the effect of message grouping, an IDA approach supporting review browsing, onto the consumer's information processing and system usage intention. An experiment with a one-factor, three-level design was conducted to test the proposed research model. It is noted that grouping customer reviews into task-related categories significantly increases users' perceived usefulness, system satisfaction and intention to use the system next time. However, grouping customer reviews into task-distracting categories may significantly decrease users' perceived usefulness, system satisfaction and intention to use the system.
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1. Introduction

Online reviews have become a major information source in making consumers’ purchase decisions (Dellarocas, 2003; Godes & Mayzlin, 2004; Zhao, Yang, Narayan, & Zhao, 2013). Many consumers utilize online reviews when making their purchase decisions, and for this reason, reviews are widely considered to be more credible than advertisements and other seller-generated product information (Nielsen, 2007). Previous studies in this subject field have also noted that online reviews may have a significant influence onto the consumers’ purchase decisions (Goh, Heng, & Lin, 2013; Zhang, Zhao, Cheung, & Lee, 2014) and also retailers’ sales (Chevalier & Mayzlin, 2003; Gu, Park, & Konana, 2012; Ho-Dac, Carson, & Moore, 2013; Lee, Lee, & Shin, 2011; X. Lu, Ba, Huang, & Feng, 2013; Sun, 2012). To this end, online reviews have increasingly become an important resource that both consumers and retailers should seriously take into account.

Information overload is one of the major challenges for online shoppers and this simply because electronic commerce tends to increase the amount of information that customers must deal with before they are able to select the particular items to meet their specific needs (Schafer, Konstan, & Riedi, 1999). One solution to this information overload problem is to utilize the interactive decision aids (IDAs). According to earlier research, the source of information overload can be either products-oriented (e.g., too many candidate products to evaluate) or reviews-oriented (e.g., too many reviews to read). However, previous studies on IDAs have mainly focused on the recommendation agents; for example, tools that address the problem of product information overload by eliciting users’ preferences; to carry out a set of search and evaluation operations on behalf of users, and thus provide the adequate product recommendations (Maes, Guttman, & Moukas, 1999; Wang & Benbasat, 2009; Xiao & Benbasat, 2007). With the rapid development of electronic commerce and social media technologies, the volume of customer reviews appeared on the Internet is increasing at an unprecedented speed. Unfortunately, research on IDAs to address the problem of information overload related to reviews has been lacking in this subject field.

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