Impact of air quality on online restaurant review comprehensiveness

Jiaming Fang (), Lixue Hu (), Xiangqian Liu () and Victor R. Prybutok ()
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Jiaming Fang: University of Electronic Science and Technology of China
Lixue Hu: University of Electronic Science and Technology of China
Xiangqian Liu: University of Electronic Science and Technology of China
Victor R. Prybutok: University of North Texas

Electronic Commerce Research, 2022, vol. 22, issue 4, No 2, 1035-1058

Abstract: 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 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10660-020-09445-w

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