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Today, regarding the rapid growth of Information and Communications Technology (ICT), e-commerce, and the subsequent expansion of electronic banking, the banking market structure is also expected to dramatically be changed. This paper aims to explore the main effect of electronic banking on the structure of the Iranian banking industry by investigating the banking market concentration degree. To accomplish this aim, an intelligent hybrid model is developed based on multilayer perceptron neural network and fuzzy regression of the effects of banking on the relative electronic share of banks. In the developed method, the neural network parameters such as weights and errors have been considered as the fuzzy parameters to model it under uncertainty. Ultimately, the descriptive statistics are utilized to evaluate how the difference in relative size of banks concerning e-banking has changed, in addition to exploring the main effect of e-banking on the bank’s contribution described as a neural network-fuzzy regression model. Moreover, it shows how the concentration degree in the Iranian banking sector has been reduced. The implemented analysis of the reasons for this decrease reveals that the share of banks has decreased due to an increase in the share of the small banks. Furthermore, model estimation confirms that there exists a positive relationship between banks’ share and the use of electronic banking. Besides, the small banks have strongly been shown to utilize the e-banking so that it would lead to an increase in their share and a decrease in the concentration degree. As such, it can be concluded that e-banking has reduced the concentration degree in Iran. The descriptive statistics are employed to prove it.

Since real-world data is often inaccurate and working with fuzzy data and Z-numbers arevery important and necessary, in the real world we need to rank and compare data. Inthis paper, we introduce a new method for ranking Z-numbers. This ranking algorithm isbased on centroid point.We evaluate distance between centroid point, and based on this distance, we rank theZ-numbers.We use this method in two practical examples. First in ranking the return on assets ofTehran stock exchange, and second, in ranking of factors affecting the productivity oftourism security.The advantage of this method over conventional fuzzy methods is considering uncertainty,and allocating credit in the opinion of experts to estimate fuzzy parameters.