WCSE

The Evaluation of Express Service Quality Based on BP Neural Network Algorithm

Abstract— The rapid development of the express delivery industry has made it an important part of the modern service industry. The quality of express delivery services has become an important indicator of the competitiveness of express delivery companies. In order to optimize consumers' experience in the service industry, based on Python crawler technology, collected comments from Baidu's word-of-mouth STO, ZTO, YTO, and Yunda Express companies, and drew a word cloud diagram of comments, combined with the SERVQUAL scale and express service business processes, and integrate the quality and process of service results, established an evaluation index system for the quality of express delivery services. Based on this evaluation system, the BP neural network algorithm was used to construct the evaluation model, and the questionnaire survey data was used for empirical analysis. The results show that: 1) The express service quality evaluation index system and evaluation model based on dynamic website review data and service quality related theories are reasonable; 2) BP neural network improves the accuracy of service quality evaluation results. Providing theoretical support for the long-term development of express delivery companies and the express industry, and promoting the high-quality and steady development of the express industry.

Index Terms— service quality, evaluation index system, Python, BP neural network.

Yina Yuan
School of modern post, Beijing University of Posts and Telecommunications
Mengke Yang
School of modern post, Beijing University of Posts and Telecommunications
Chengdong Chen
School of Economics and Management, Minjiang University
Xiaoguang Zhou
School of modern post, Beijing University of Posts and Telecommunications

[Download]

Cite: Yina Yuan, Mengke Yang, Chengdong Chen, Xiaoguang Zhou, " The Evaluation of Express Service Quality Based on BP Neural Network Algorithm, " WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications, pp. 1419-1428, Sanya, China, April 15-18, 2022.