Work

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

Year: 2019

Type: article

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.

Source: Sustainability

DOI: 10.3390/su11133570

Authors: Wei Hong, Changyuan Zheng, Linhai Wu, Xujin Pu

Institution: Jiangnan University

Language: English

Topic: Customer Service Quality and Loyalty

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,722

Funders: National Natural Science Foundation of China, National Office for Philosophy and Social Sciences, Fundamental Research Funds for the Central Universities