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

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Monday, December 12th
12:00 AM

Can Platform Competition Drive Ratings Inflation? The Impact of Vertical Spillover Effects

Yulia Vorotyntseva, Saint Louis University
Aleksi Aaltonen, Temple University
Subodha Kumar, Temple University
Paul Pavlou, The University of Houston

12:00 AM

Examining the Effect of Self-selection Bias on Consumer Satisfaction: A Product Type Perspective

Yancong Xie, Queensland University of Technology

12:00 AM

How Does a Review Officer and Her Incentivized Contribution Affect the Review System?

Yuanhong Ma, Beihang University
Ran (Alan) Zhang, Texas Tech University
Zhong Yao, Beihang University

12:00 AM

How is the review helpfulness evaluated?

Tien Thuy Nguyen, University of Auckland
Arvind Tripathi, University of Auckland

12:00 AM

Influence of Assimilation Effects on Recommender Systems

Markus Lill, Ludwig-Maximilians-Universität München
Martin Spann, LMU

12:00 AM

Iterative Seed Word Generation for Interactive Topic Modelling: a Mixed Text Processing and Qualitative Content Analysis Approach

Morteza Namvar, The University of Queensland
Saeed Akhlaghpour, The University of Queensland
James Boyce, The University of Queensland
Salma Sharifi Khajedehi, The University of Queensland

12:00 AM

Online Review Censorship

Aida sanatizadeh, University of Illinois at Chicago
Gordon Burtch, Boston University
Yili Hong, University of Houston
Yuheng Hu, University of Illinois at Chicago

12:00 AM

Personalized Recommendation for Balancing Content Generation and Usage on Two-Sided Entertainment Platforms

Hao Arthur Zhang, Zhejiang University
Zhiling Guo, Singapore Management University
Mingzheng Wang, Zhejiang University

12:00 AM

Personalized Recommendation through Disentangled Representation Learning of Consumers’ Multiple Digital Footprints

Yansong Shi, Tsinghua University
Cong Wang, Peking University
Xunhua Guo, Tsinghua University
Guoqing Chen, Tsinghua University

12:00 AM

Promoting Diverse News Consumption Through User Control Mechanisms

Kian Schmalenbach, Friedrich-Alexander-Universität Erlangen-Nürnberg
Eva Gengler, Friedrich-Alexander-Universität Erlangen-Nürnberg
Sven Laumer, Friedrich-Alexander-Universität Erlangen-Nürnberg

12:00 AM

The Value of Incorporating Review Tags into an Online Review System for User Review Generation

Lun Li, Beijing Institute of Technology
Nina Huang, University of Houston
Qiuju Yin, Beijing Institute of Technology
Zhijun Yan, Beijing Institute of Technology
Robert Plant, University of Miami
Yili Hong, University of Houston

12:00 AM