Identifying and Prioritizing Barriers to E-Commerce Implementation Using Artificial Neural Network

One of the hallmarks of the ۲۱st century is the development of electronic commerce around the world in different ways. The importance of the implementation and development of E-commerce is so important that it has been known as one of the highest-paid jobs since ۲۰۰۶. The importance of the development of E-commerce for customers, employers and, government is not feasible, so identify and prioritize the barriers that prevent the phenomenon in the age of information and technology is necessary. It's safe to say that one of the areas that have the most effective use of E-commerce is the banking sector. Saving time, reducing mistakes, overnight services, and remote services are the benefits of using E-commerce in the banking sector. This study aims to identify and prioritize barriers to E-commerce implementation using the artificial neural network in the statistical society of West Azarbaijan Saderat Bank Branches. Since artificial neural networks are a powerful tool for predicting with the least possible errors, we have used it for this research. The research method follows, first the mean values of the independent variables were calculated and prioritized by the AHP technique on the Expert Choice program and then entered into the artificial neural network on the Matlab software. Type of the artificial neural network used in this research is the K-Means and Self-Organizing Map clustering. The findings of the research show that there are five main independent variables as follows, Communications and Information technology infrastructure, Economic, cultural and educational, Sociopolitical, and Legal.

کلیدواژه ها:

E-commerce ، Implementation Barriers ، Artificial Neural Network ، K-Means Clustering ، Self-organizing Mapping (SOM).