تحلیل الگوی رفتاری مشتریان شعب به روش خوشه بندی و دسته بندی با استفاده از روش RFM (مطالعه موردی-رستوران زنجیره ای)

 

References

Bach, M.P., Jankovic, S., Dominic, K., & Sarlija, N. (2013). business client segmentation using self - organizing map. South East European journal of Economics and Business, 8(2), 32-41.

Berry, M., & Linoff, G. (2004). Data Mining Techniques For Marketing, Sales and Customer Relationship Management Second Edition. Wiley Publishing, Inc., Indianapolis, Indiana.

Burnett, A. (2001). Handbook of Key Customer Relationship Management: The Definitive Guide to Winning, Managing and Developing Key Account business. Pearson Education.

Burnett. A. (2001). Handbook of Key Customer Relationship Management: The Definitive Guide to Winning, Managing and Developing Key Account business Pearson Education.

Chadors, A. J. & V.E.D. (2014). customer segmentation model based on value generation for marketing strategy foundation. Estudios Gerenciales, 30, 25-30.

Cheng, C. H., & Chen, Y. S. (2009). classifying the segmentation of customer value via RFM theory. Expert systems with applications,36(3), 4176-4184.

Dursun & Caber, M (2016) Using data mining techniques for profiling profitable hotel customers: An application of RFM analysis.Tourism Management Perspectives, 18, 153-160

Hand. D., Mannila, H., & Smyth, P. (2001). principles of Data mining. The MIT press.

Huang. S-C., Chang, E-C. & Wu, H-H. (2009). A case study of applying data mining techniques in an outfitters customer value analysis. Expert Systems with Applications, 36, 5909-5915.

Liang, Y-H. (2010). Integration of data mining technologies to analyze customer value for the automotive maintenance industry. Expert Systems with Applications, 37, 7489-7496.

Liao, S-H., Chen, Y-N. & Tseng, Y-Y. (2009). mining demand chain knowledge of life insurance market for new product development. Expert systems with application, 36(5), 9422-9437

Ngai, E. W. T., Xiu, L., & Chau, D.C.K. (2009). Application of data mining techniques in customer relationship management: A literature review and classification. expert systems with applications, 36, 2592-2602.

Nioosha jafari momtaz, somaye alizade, mahyar sharifi vaghefi, (2013).  A new model for assessment fast food customer behavior, emerald insight, 313, 601-613.

Olson, D. L., & Chae, B. K. (2012). Direct marketing decision support through predictive customer response modeling. Decision Support Systems, 54(1), 443-451.

Rygielski, C., Wang. J-C. & Yen, D. (2002). Data mining technologies for customer relationship management. Technology in society, 24, 438-502.

References [In Persian]

Ahangari, S. S., Momeni, M., & Jafarnejad, A. (2013). Bank Shahr customers' segmentation by SOM neural networks. The First International Conference on Management and Accounting Techniques, Tehran.[In Persian]

Sadoughinia, E., Hasanzadeh, A., Elahi, Sh., & Sahraei, Sh. (2020). An Expert System for Evaluating Customers’ Loyalty in Distribution Industry. Quartly Journal of BI Management Studies, 8(30), 55-78.[In Persian]

Forouzandeh, S. (1396). Predicting the turnover of Bank Mellat's real customers using collective methods based on bagging and boosting. (Master Thesis), Kharazmi University. [In Persian]

Qasemzadeh, S. N. (1395). Segmenting Internet network mobile customers and examining their behavioral changes. (Master Thesis), Kharazmi University. [In Persian]

Kadkhodai, E. (1394). Discover knowledge of successive RFM patterns for customer segmentation. (Master Thesis), Kharazmi University. [In Persian]

Mohammadi, Sh., and Alizadeh, S. (2014). Problems Analysis of Ayandeh Bank branches across the country using data mining method. Information Technology Management, 6 (2), 350-333. [In Persian]

Motameni, Alireza; Moradi, Hadi and Hemmati, Amin. (1391). Identify and rank the factors affecting the loyalty of retailers to distribution companies. Supply Chain Management Quarterly, 14 (35), 75-62. . [In Persian]

‌

 

 

 

‌ ‌استناد به این مقاله: رحیمی، فاطمه، سبط، محمد وحید، غنبر تهرانی، نسیم. (1400). تحلیل الگوی رفتاری مشتریان شعب به روش خوشه‌بندی و دسته‌بندی با استفاده از روش RFM، مطالعات مدیریت کسب وکار هوشمند، 9(36)، 209-242.                                          DOI: 10.22054/IMS.2021.50853.1697

 Journal of Business Intelligence Management Studies is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License..

References

Bach, M.P., Jankovic, S., Dominic, K., & Sarlija, N. (2013). business client segmentation using self - organizing map. South East European journal of Economics and Business, 8(2), 32-41.

Berry, M., & Linoff, G. (2004). Data Mining Techniques For Marketing, Sales and Customer Relationship Management Second Edition. Wiley Publishing, Inc., Indianapolis, Indiana.

Burnett, A. (2001). Handbook of Key Customer Relationship Management: The Definitive Guide to Winning, Managing and Developing Key Account business. Pearson Education.

Burnett. A. (2001). Handbook of Key Customer Relationship Management: The Definitive Guide to Winning, Managing and Developing Key Account business Pearson Education.

Chadors, A. J. & V.E.D. (2014). customer segmentation model based on value generation for marketing strategy foundation. Estudios Gerenciales, 30, 25-30.

Cheng, C. H., & Chen, Y. S. (2009). classifying the segmentation of customer value via RFM theory. Expert systems with applications,36(3), 4176-4184.

Dursun & Caber, M (2016) Using data mining techniques for profiling profitable hotel customers: An application of RFM analysis.Tourism Management Perspectives, 18, 153-160

Hand. D., Mannila, H., & Smyth, P. (2001). principles of Data mining. The MIT press.

Huang. S-C., Chang, E-C. & Wu, H-H. (2009). A case study of applying data mining techniques in an outfitters customer value analysis. Expert Systems with Applications, 36, 5909-5915.

Liang, Y-H. (2010). Integration of data mining technologies to analyze customer value for the automotive maintenance industry. Expert Systems with Applications, 37, 7489-7496.

Liao, S-H., Chen, Y-N. & Tseng, Y-Y. (2009). mining demand chain knowledge of life insurance market for new product development. Expert systems with application, 36(5), 9422-9437

Ngai, E. W. T., Xiu, L., & Chau, D.C.K. (2009). Application of data mining techniques in customer relationship management: A literature review and classification. expert systems with applications, 36, 2592-2602.

Nioosha jafari momtaz, somaye alizade, mahyar sharifi vaghefi, (2013).  A new model for assessment fast food customer behavior, emerald insight, 313, 601-613.

Olson, D. L., & Chae, B. K. (2012). Direct marketing decision support through predictive customer response modeling. Decision Support Systems, 54(1), 443-451.

Rygielski, C., Wang. J-C. & Yen, D. (2002). Data mining technologies for customer relationship management. Technology in society, 24, 438-502.

References [In Persian]

Ahangari, S. S., Momeni, M., & Jafarnejad, A. (2013). Bank Shahr customers' segmentation by SOM neural networks. The First International Conference on Management and Accounting Techniques, Tehran.[In Persian]

Sadoughinia, E., Hasanzadeh, A., Elahi, Sh., & Sahraei, Sh. (2020). An Expert System for Evaluating Customers’ Loyalty in Distribution Industry. Quartly Journal of BI Management Studies, 8(30), 55-78.[In Persian]

Forouzandeh, S. (1396). Predicting the turnover of Bank Mellat's real customers using collective methods based on bagging and boosting. (Master Thesis), Kharazmi University. [In Persian]

Qasemzadeh, S. N. (1395). Segmenting Internet network mobile customers and examining their behavioral changes. (Master Thesis), Kharazmi University. [In Persian]

Kadkhodai, E. (1394). Discover knowledge of successive RFM patterns for customer segmentation. (Master Thesis), Kharazmi University. [In Persian]

Mohammadi, Sh., and Alizadeh, S. (2014). Problems Analysis of Ayandeh Bank branches across the country using data mining method. Information Technology Management, 6 (2), 350-333. [In Persian]

Motameni, Alireza; Moradi, Hadi and Hemmati, Amin. (1391). Identify and rank the factors affecting the loyalty of retailers to distribution companies. Supply Chain Management Quarterly, 14 (35), 75-62. . [In Persian]

‌

 

 

 

‌ ‌استناد به این مقاله: رحیمی، فاطمه، سبط، محمد وحید، غنبر تهرانی، نسیم. (1400). تحلیل الگوی رفتاری مشتریان شعب به روش خوشه‌بندی و دسته‌بندی با استفاده از روش RFM، مطالعات مدیریت کسب وکار هوشمند، 9(36)، 209-242.                                          DOI: 10.22054/IMS.2021.50853.1697

 Journal of Business Intelligence Management Studies is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License..