@article { author = {Moslehi, Fateme and Haeri, Abdolrahman and Gholamian, Mohammad reza}, title = {Investigation of effective factors in expanding electronic payment in Iran using datamining techniques}, journal = {Journal of Industrial and Systems Engineering}, volume = {12}, number = {2}, pages = {61-94}, year = {2019}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {E-banking has grown dramatically with the development of ICT industry and banks offer their services to customers from different channels. Nowadays, considering the great economic benefits of electronic banking systems, the need to pay attention to the expansion of electronic banking is increasingly felt in terms of reducing costs and increasing the bank's profitability. The purpose of this study is to identify the factors that encourage customers to accept e-banking across the country using the statistics and information retrieved from the Central Bank and the data mining techniques. For this purpose, initially, the K-Means clustering algorithm was applied and the provinces of Iran is separated into 3 clusters. In addition, the transactions related to each year were clustered separately, and the formed clusters were compared with each other. In the next step, the hidden patterns of the E-payment instrument transactions were detected using the CART algorithm. According to the results obtained from decision tree rules, indices of social-economic and Information and Communication Technology development and business boom were the most effective factors in increasing the use of electronic payment methods.}, keywords = {Machine Learning,Data mining,electronic payment instruments,Classification,Clustering}, url = {https://www.jise.ir/article_82628.html}, eprint = {https://www.jise.ir/article_82628_551ce071e4a3521e5a209190c8f93cf2.pdf} }