Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach
In recent years,Internet-based banking services have become the focus of competition in Iran’s banking system. In this respect, Internet banking users’ identification and segmentation leads to better understanding of users’ needs and expectations and planning to meet them. This in turn will result i...
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| Format: | Article |
| Language: | English |
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University of Tehran
2014-09-01
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| Series: | Journal of Information Technology Management |
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| Online Access: | https://jitm.ut.ac.ir/article_51836_866f25a9ec52f4268322777535f21a4d.pdf |
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| author | Shahriar Azizi Vahid Hossein Abadi Mohammad Balaghi Inanlou |
| author_facet | Shahriar Azizi Vahid Hossein Abadi Mohammad Balaghi Inanlou |
| author_sort | Shahriar Azizi |
| collection | DOAJ |
| description | In recent years,Internet-based banking services have become the focus of competition in Iran’s banking system. In this respect, Internet banking users’ identification and segmentation leads to better understanding of users’ needs and expectations and planning to meet them. This in turn will result in improving the image of the bank and obtaining competitive advantage. In this research, seven banks of Pasargad, Mellat, Parsian, Saman, Eghtesad-e-novin, Tejarat and Melli are selected as rival brands. According to scrutiny, the expectations of internet banking users were identified in the form of 17 indicators. Using closed questionnaires, necessary data was collected from 274 users of Internet banking services in selected banks. At the first stage, based on exploratory factor analysis, five factors were identified which include: ease of use, variety of e-banking services, security, speed of providing services and reliability. In the second stage, by applying k-means procedure, optimum number of clusters was detected equal to 6. Then the expectations of each cluster were evaluated. The result showed that the average of expectations and frequency of demographic variables between clusters are different. So the extracted clusters have good quality. |
| format | Article |
| id | doaj-art-a9b8aed37bfc49368ee75e5c5297dd75 |
| institution | OA Journals |
| issn | 2008-5893 2423-5059 |
| language | English |
| publishDate | 2014-09-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | Journal of Information Technology Management |
| spelling | doaj-art-a9b8aed37bfc49368ee75e5c5297dd752025-08-20T02:20:40ZengUniversity of TehranJournal of Information Technology Management2008-58932423-50592014-09-016341943410.22059/jitm.2014.5183651836Segmentation of Internet Banking Users Based on Expectations: A Data Mining ApproachShahriar Azizi0Vahid Hossein Abadi1Mohammad Balaghi Inanlou2استادیار گروه مدیریت بازرگانی ، دانشکدۀ مدیریت، دانشگاه شهید بهشتی، تهران، ایراندانشجوی دکتری مدیریت بازرگانی، دانشکدۀ مدیریت، دانشگاه شهید بهشتی، تهران، ایرانکارشناسارشد مدیریت بازرگانی، دانشکدۀ مدیریت، دانشگاه شهید بهشتی، تهران، ایرانIn recent years,Internet-based banking services have become the focus of competition in Iran’s banking system. In this respect, Internet banking users’ identification and segmentation leads to better understanding of users’ needs and expectations and planning to meet them. This in turn will result in improving the image of the bank and obtaining competitive advantage. In this research, seven banks of Pasargad, Mellat, Parsian, Saman, Eghtesad-e-novin, Tejarat and Melli are selected as rival brands. According to scrutiny, the expectations of internet banking users were identified in the form of 17 indicators. Using closed questionnaires, necessary data was collected from 274 users of Internet banking services in selected banks. At the first stage, based on exploratory factor analysis, five factors were identified which include: ease of use, variety of e-banking services, security, speed of providing services and reliability. In the second stage, by applying k-means procedure, optimum number of clusters was detected equal to 6. Then the expectations of each cluster were evaluated. The result showed that the average of expectations and frequency of demographic variables between clusters are different. So the extracted clusters have good quality.https://jitm.ut.ac.ir/article_51836_866f25a9ec52f4268322777535f21a4d.pdfClustering AnalysisExpectationsInternet BankingSegmentation |
| spellingShingle | Shahriar Azizi Vahid Hossein Abadi Mohammad Balaghi Inanlou Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach Journal of Information Technology Management Clustering Analysis Expectations Internet Banking Segmentation |
| title | Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach |
| title_full | Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach |
| title_fullStr | Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach |
| title_full_unstemmed | Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach |
| title_short | Segmentation of Internet Banking Users Based on Expectations: A Data Mining Approach |
| title_sort | segmentation of internet banking users based on expectations a data mining approach |
| topic | Clustering Analysis Expectations Internet Banking Segmentation |
| url | https://jitm.ut.ac.ir/article_51836_866f25a9ec52f4268322777535f21a4d.pdf |
| work_keys_str_mv | AT shahriarazizi segmentationofinternetbankingusersbasedonexpectationsadataminingapproach AT vahidhosseinabadi segmentationofinternetbankingusersbasedonexpectationsadataminingapproach AT mohammadbalaghiinanlou segmentationofinternetbankingusersbasedonexpectationsadataminingapproach |