Subdivided or aggregated online review systems: Which is better for online takeaway vendors?
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Subdivided or aggregated online review systems: Which is better for online takeaway vendors? Hongpeng Wang1 · Rong Du1 · Jin Li1,3 · Weiguo Fan2
© Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract This paper examines the role of a subdivided or aggregated online review system to help online takeaway vendors select the most appropriate information strategy. First, we develop two models to depict the interaction between online vendors’ information strategies and consumers’ responses. Second, we take the multidimensional product attributes with their corresponding weights into consideration and illustrate that the sensitivity to product misfits, instead of the relative importance of product attributes, dominates profit maximization. Third, we make a comparison to find the most appropriate scenario to adopt a full or partial information strategy. When a large number of consumers satisfy the delivery time performance, an aggregated review system will be a better choice. Otherwise, vendors are advised to host a subdivided review system. Finally, we universally identify a variance boundary in the rating-star review system, which not only prevents consumers from expressing their real feelings but also makes observing consumer feedback and strategic adjustments inconvenient for online vendors. Keywords Online review systems · Information strategies · Multidimensional attributes · Variance boundary
1 Introduction With the success of e-commerce in all walks of life, consumers can easily obtain related information about their targeted products through electronic word-ofmonth (eWOM) communication. Product reviews, as one of the most prevalent eWOM channels, have transformed the way that customers make purchasing
* Jin Li [email protected] 1
School of Economics and Management, Xidian University, Xi’an, Shaanxi, China
2
Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA 52242, USA
3
Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China
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decisions. People often use eWOM in online reviews to help them make judgments [47], and nearly 90% of consumers state that their consumption is affected (favorably or unfavorably) after reading these reviews. Accordingly, many online platforms have updated their product review systems to facilitate more informed purchasing decisions. For example, on May 6th, 2016, eBay.com introduced a voluntary product review system in which sellers can strategically decide whether to take part in the product review system or not. Additionally, instead of using the aggregated product review system that only provides an overall rating, such as the ones often used by online retailers (e.g., Amazon.com and BestBuy.com), the tourism industry (e.g., Airbnb.com and TripAdvisor.com) and cross-border trade websites (e.g., Gearbest.com and Banggood.com) have adopted the subdivided product review system, which allows buyers to rate products on multi-dimensional attri
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