Title: E-commerce satisfaction based on synthetic evaluation theory and neural networks

Authors: Jiayin Zhao; Yong Lu; Hao Ban; Ying Chen

Addresses: School of Digital Commerce, Nanjing Vocational College of Information Technology, Nanjing, 210023, China ' School of Digital Commerce, Nanjing Vocational College of Information Technology, Nanjing, 210023, China ' School of Information Science and Engineering, Southeast University, Nanjing, 210096, China ' School of Information Science and Engineering, Southeast University, Nanjing, 210096, China; Department of Psychiatry, Columbia University in the City of New York and NYSPI, New York, USA

Abstract: The rapid development of e-commerce has led to the increasing role of satisfaction in more fields. Therefore, the customers' opinion has become a necessary role for the success of related companies. E-commerce satisfaction, as the key factor affecting the performance of e-commerce enterprises, has become a research hotspot in academia. This paper proposes a synthetic evaluation model of satisfaction and logistics performance based on fuzzy synthetic model and dynamic weighted synthetic model respectively. A modified ASCI analysis method based on structured equation model is also proposed to compare with the synthetic method. Beyond this we have also evaluated consumer satisfaction based review data. And corresponding suggestions are given to the operation of e-commerce enterprises.

Keywords: e-commerce satisfaction; fuzzy synthetic model; structured equation model; neural networks.

DOI: 10.1504/IJCSE.2020.109399

International Journal of Computational Science and Engineering, 2020 Vol.22 No.4, pp.394 - 403

Received: 13 Mar 2019
Accepted: 22 Aug 2019

Published online: 26 Aug 2020 *

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