Exploring hidden factors behind online food shopping from Amazon reviews: A topic mining approach. (May 2018)

• Record Type: Journal Article
• Authors: Heng, Yan; Gao, Zhifeng; Jiang, Yuan; Chen, Xuqi
• Is Part Of: Journal of retailing and consumer services. Volume 42(2018)
• Page Start: 161
• Page End: 168
• Publication Date: 2018-05
• Subjects: Online coffee shopping -- Customer reviews -- Topic modeling; Retail trade -- Periodicals; Service industries -- Periodicals; Customer services -- Periodicals; Commerce de détail -- Périodiques; Service à la clientèle -- Périodiques; Customer services; Retail trade; Periodicals; 658.87
• DOI: 10.1016/j.jretconser.2018.02.006
• Languages: English
• ISSNs: 0969-6989

Abstract

Abstract: Despite the popularity of online food and grocery shopping, little research has been conducted to understand the factors that influence consumers' online food purchases. Using a topic modeling approach, our results show four interpretable factors have significant impacts on the helpfulness of customer reviews: Amazon Service, Physical Feature, Flavor Feature, and Subjective Expression. Readers of customer reviews perceive objective reviews as more helpful than subjective reviews. In addition, customer review helpfulness has a concave relationship with the length of the reviews. Our results provide important business implications on how to encourage more helpful reviews to assist potential shoppers in making better purchase decisions.