Online Reviews and Recommendations

Online reviews and recommendation systems today play decisive roles in consumers’ evaluation and purchase decisions, as well as in firms’ strategic business decisions and competitive actions. First, to use online reviews strategically, online platforms and researchers need insights on how customers can be motivated to post helpful online reviews (Reviewing Behavior), on the economic effects of online reviews (Review Economics), and how review systems can be designed to obtain competitive advantages for firms and to provide reliable, useful information for consumers (Review Systems Design). Second, to further understand how recommendation systems change the competition landscape for firms and influence consumers’ awareness and view of product choices, recommendation system operators and researchers need to investigate the usage behaviors and related cognitive biases under recommendation systems (Behavior under Recommendation Systems), the economic impacts of recommendation systems (Economics of Recommendation Systems), and how to design an efficent and effective recommendation system (Recommendation Systems Design). This track invites cutting-edge and novel research that addresses various issues relating to these above-mentioned research directions or areas.

Overall, this track welcomes theoretical and/or empirical papers that improve our understanding of the behavioral, economic, strategic, and design issues associated with online reviews and recommendations systems. It encompasses studies of online reviews and recommendations at the levels of consumers, businesses or organizations, and markets. We welcome submissions from all IS research traditions and methodological approaches (e.g., analytical models, lab or field experiments, qualitative studies, design science, econometric analyses, etc.). We encourage work that crosses disciplinary and methodological boundaries, and that provides a novel understanding of online reviews and recommendations.

Track Co-Chairs;
Khim Yong GOH, Ph.D., National University of Singapore
Liangfei QIU, Ph.D., University of Florida
Steffen Zimmermann, Ph.D., Ulm University