1. علی محقر، کارولوکس، فرید حسینی، آصف علی منشی،" کاربرد هوش تجاری به عنوان یک تکنولوژی اطلاعات استراتژیک در بانکداری: بازرسی و کشف تقلب"، نشریه مدیریت فناوری اطلاعات، دوره 1، شماره 1، پاییز و زمستان 1387 ، 105 تا 120.
2. علی دیواندری، " مدل سازی تغییرات استراتژیک در صنعت بانکداری" پژوهشنامه اقتصاد و بانکداری، 1380.
3. محبوبه دادفر،فاضل بهرامی،فرشته دادفر،سید جلال یونسی"بررسی اعتبار و پایایی مقیاسی برای سنجش سرسختی روان شناختی دانشجویان"، نشریه توانبخشی، دوره یازدهم،پاییز 1389، 43تا 57 .
4. محمد تقوی فرد و مصطفی ترابی ، ، “بررسی فاکتور های مؤثر در پذیرش سرویس بانکداری همراه توسط مشتریان” ، سومین کنفرانس جهانی بانکداری الکترونیک ، 1387.
5. محمد محمودی میمند، زین العابدین رحمانی، مهدی بصیرت نیا، بررسی اثر استفاده از استراتژی برون سپاری بر بهره وری صنعت بانکداری، مطالعه موردی شعب بانک اقتصاد نوین استان مازندران، فصلنامه مدیریت صنعتی دانشکده علوم انسانی دانشگاه آزاد اسلامی واحدد سنندج، سال پنجم،شماره 13، پاییز 1389.
6. Ayahiko, N, eiichirp,T,(1999).Object Oriented Approach To Combined learning of decision tree, department of control and systems engineering, Journal of Market-Focused Management. 5 ( 1), 5-23.
7. Camponovo, G. & Pigneur, Y. & Rangone, A. & Renga, F (2005), “Mobile customer relationship management: an explorative investigation of the Italian consumer market” Mobile Business, (ICMB), 42 – 48.
8.Daniel, Elizabeth and Chris Story (1999) Online Banking Strategic and Management Challenges, Long Range Planning,30, 895-898.
9. David Hand, Heikki Mannila, and Padhraic Smyth, (2010), “Principles of Data Mining”, MIT Press, Cambridge, MA.
10. Doll, W.J. and Torkzadeh, G., (1991) “The measurement of End-User Computing Satisfaction theoretical and methodological issues”, MIS Quarterly. 15 (1), 5-10.
11. Doll, W.J. and Torkzadeh, G. (1988), “The measurement of End-User ComputingSatisfaction”, Sixth International Conference on the Management of Mobile Business , Department of Business and Management, 12, 259-74.
12. Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). The KDD process for extracting useful knowledge from volumes of data, Commune. ACM 39, 27-34.
13. Hsiu-Fen Lin,(2011), “An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust”, International Journal of Information Management ,31(3), 252-260.
14. Hong Sheng & Fiona Fui-Hoon Nah & Keng Siau,(2005), “Strategic implications of mobile technology: A case study using Value-Focused Thinking”, The Journal of Strategic Information Systems, 14, 269-290.
15. J. P. Shim & Julie M. Shim (2003), “M-commerce Around the World: Mobile Services and Applications Japan, Korea, Hong Kong, Finland, and the U.S.” Decision Line.
16. Kass, G., (1980), an exploratory technique for exploring large quantities of categorical data Applied Statistics, 119–127.
17. Kamber, J. H., (2001) International journal of Data Mining and Machine Learning Concepts and Techniques, 311-328.
18. Ling j. k, chih c, ch. (2001), “mining the Customer Credit By using the neural network model with classification and regression tree approach”, Department of statistics IEEE.
19. Nicole Koenig-Lewis, Adrian Palmer, Alexander Moll, (2010) "Predicting young consumers' take up of mobile banking services", International Journal of Bank Marketing, 28 (25), 410 – 432.
20. Peter L, Yingzhen.Y,Yang, C .(2010). Pattern mining from saccadic motion data, The International Conference on Computational Science, ( ICCS).
21. Samuel Seongseop Kim, Dallen J. Timothy, Jinsoo Hwang, (2010), “Understanding Japanese tourists’ shopping preferences using the Decision Tree Analysis method”, 301-3016.
22.Saurabh Panjwani , Edward Cutrell, (2010), “Usably secure, low-cost authentication for mobile banking”, Proceedings of the Sixth Symposium on Usable Privacy and Security.
23. S. Ram, J.N. Sheth (1989), Consumer resistance to innovations: the marketing problem and its solutions, The Journal of Consumer Marketing, 5-11.
24. Tommi Laukkanen, Teuvo Kantanen, (2006) “Consumer value segments in Mobile Bill paying” Third International Conference on Information Technology: New Generations (ITNG'06) IEEE.
25. Tommi Laukkanen, SuviSinkkonen, MarkeKivijärvi, PekkaLaukkanen, (2007)" Segmenting Bank Customers by Resistance to Mobile Banking", Sixth International Conference on the Management of Mobile Business (ICMB).
26. Tiwari, R.; Buse, S.; Herstatt, C., (2006) “Customer on the Move: Strategic Implications of Mobile Banking for Banks and Financial Enterprises”, E-Commerce Technology. The 8th IEEE International Conference on and Enterprise Computing, 81 – 89.
27. Veerle D, Lieven E, & Koen De Bosschere. (2005), Using Decision Trees to Improve Program-Based and Profile-Based Static Branch Prediction, Department of Electronics and Information Systems, LNCS 3740, 336–352.
28. Wai-Ching Poon, (2008) “Users’ adoption of e-banking services: the Malaysian perspective”, Journal of Business & Industrial Marketing, 59–69.
29. Weka. (n.d.). Retrieved from www.cs.waikato.ac.nz/ml/weka.
30.Y AOMin, SHEN Bin, LI Ming-fang,( 2004), A kind of classification and regression tree algorithm for unusual customers recognition telecom trade, Journal of Artifieal Intelegence , 21, 352-369.
31. Zhang Y, Zhang P, Zhang L& Shia Y. (2010). “Knowledge extraction from multiple criteria linear programming Classification approach”, International Conference on Computational Science, ICCS.
)
