Impact of air quality on online restaurant review comprehensiveness
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Impact of air quality on online restaurant review comprehensiveness Jiaming Fang1 · Lixue Hu1 · Xiangqian Liu1 · Victor R. Prybutok2 Accepted: 26 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Comprehensiveness is one of the most important textual content features of online review and exhibits significant impacts on consumer’s buying decisions. This paper explores the effect of air quality on review comprehensiveness by using a large-scale daily restaurant review dataset. By applying panel data and text mining method, we report an emotion-based underlying mechanism for the link between ambient air pollution levels and review comprehensiveness. Specifically, we show that air pollution levels significantly decrease review comprehensiveness, and emotion arousal mediates the relationship. Besides, our analyses reveal that the effect of the changing natural environment on reviews is asymmetrical, such that the negative relationship between air pollution levels and emotional arousal is stronger among novice reviewers. This research extends our current understanding of air pollution’s psychological and behavioral effects on review writers and suggests the importance of integrating air quality information into online review management strategies. Keywords Online reviews · Review diagnosticity · Emotional arousal · Air quality · Review comprehensiveness
* Jiaming Fang [email protected] Lixue Hu [email protected] Xiangqian Liu [email protected] Victor R. Prybutok [email protected] 1
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, Sichuan, P.R. China
2
College of Business, University of North Texas, Denton, TX 76201, USA
13
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J. Fang et al.
1 Introduction Online retailers nowadays have increasingly recognized the importance of usergenerated online reviews for converting website traffic into sales, and many retailers are closely monitoring online reviews to manage their online reputation and improve customer experience [1, 2]. Yet most online retailers and marketers acknowledge that not all reviews are equally effective in convincing consumers to purchase, and consumers are more likely to be influenced by the high quality reviews that are diagnostic to purchase decision. According to information processing literature, information diagnosticity influences consumers’ information adoption [3]. In customer review settings, review diagnosticity reflects the ability of a review to help consumers understand and evaluate the quality and performance of products [4, 5]. Review diagnosticity in the existing studies is often theorized as the degree of information helpfulness. A number of studies have examined the potential factors affecting review helpfulness, such as reviewer characteristics and profile image [6–8], review extremity [9], review valence and depth [10, 11], product type [12], readability and subjectivity [13, 14], sentiment and emotions [2, 6, 15, 16]. The recent research has also iden
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