Analyzing the Relationship between Consumer Satisfaction and Fresh E-Commerce Logistics Service Using Text Mining Techniques

Wei Hong, Changyuan Zheng, Linhai Wu and Xujin Pu
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Wei Hong: Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi 214122, China
Changyuan Zheng: School of Business, Jiangnan University, Wuxi 214122, China
Linhai Wu: Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi 214122, China
Xujin Pu: Food Safety Research Base of Jiangsu Province, Jiangnan University, Wuxi 214122, China

Sustainability, 2019, vol. 11, issue 13, 1-16

Abstract: The rapid development of the Internet and the transformation of consumption patterns have prompted consumers to purchase fresh products online. For fresh e-commerce enterprises, logistics is an important aspect of customer satisfaction. Therefore, this study focused on online review information and used a convolutional neural network text mining model for its analysis. Logistics service elements concerned with customer satisfaction are convenience, communication, integrity, responsiveness, and reliability. Thereafter, comment information was converted to digital information using sentiment analysis. Finally, a correlation analysis was carried out to compare the significance of various influencing factors. The results confirm that convenience, communication, reliability, and responsiveness had a significant impact on customer satisfaction, whereas integrity had none. Fresh e-commerce logistic services need to improve for the development of the companies.

Keywords: fresh e-commerce; logistics service; customer satisfaction; convolutional neural network; sentiment analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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