Evaluating Customer Trust in E-Commerce with a Combined Approach to Structural Equations and Artificial Neural Networks

Purpose: Due to the increasing familiarity of people with the Internet andconsidering the many benefits of online shopping, the fields of its use havegrown rapidly. At such a stage, in case of mistrust among customers, this newphenomenon will fail in the first steps of progress. Organizing and supervisingonline stores is one of the essential indicators of e-commerce development, sothat the electronic receipt and payment system for providing goods must bedone in a safe and correct environment.Methodology: In this paper, various descriptive and inferential methods as wellas neural network method for data analysis and PLS intelligent software are usedto establish causal relationships of independent variables with dependentvariables and MATLAB software is used to measure and predict dependentvariables.Findings: The proposed model showed the priority and importance of keyparameters and indicators affecting online trust.Originality/Value: The most important purpose of this study is to examinethe dimensions and components of trust in the context of online shopping.Structural equations as well as neural networks have been used for this analysis.

Evaluating Customer Trust in E-Commerce with a Combined Approach to Structural Equations and Artificial Neural Networks Keywords:

E-Trust , ECommerce , Structural Modeling , Artificial Neural Networks