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Churn analysis for an Iranian mobile operator

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  • Keramati, Abbas
  • Ardabili, Seyed M.S.

Abstract

To survive in the challenging environment of a global market, organizations must recognize and analyze customer attitudes. To be competitive, organizations must recognize and forecast customer preferences and behaviors to maximize customer retention before their rivals do so. This research identifies factors that affect customer churn, the single most valuable of an organization's assets. One year's data from call log files relating to 3150 customers were selected randomly from an Iranian mobile operator call-center database. Binomial Logistic Regression was the method of analysis used in this research. The results of this research indicate that a customer's dissatisfaction, their amount of service usage and certain demographic characteristics have the most influence on their decision to remain or churn. The results also imply that customer status (active or inactive status) mediates the relationship between churn and the cause of churn. The Iranian government's current plan to privatize the telecommunications industry without deregulation leads to a non-square competition environment. Deregulation in favor of delegating more authorities of customer care is necessary in order to develop a square private competition environment in the Iranian mobile telecommunications industry.

Suggested Citation

  • Keramati, Abbas & Ardabili, Seyed M.S., 2011. "Churn analysis for an Iranian mobile operator," Telecommunications Policy, Elsevier, vol. 35(4), pages 344-356, May.
    • Handle: RePEc:eee:telpol:v:35:y:2011:i:4:p:344-356
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    Cited by:

    1. Uner, M.Mithat & Guven, Faruk & Cavusgil, S.Tamer, 2020. "Churn and loyalty behavior of Turkish digital natives: Empirical insights and managerial implications," Telecommunications Policy, Elsevier, vol. 44(4).
    2. Gerpott, Torsten J. & Meinert, Phil, 2018. "Termination notice of mobile network operator customers after a tariff switch: An empirical study of postpaid subscribers in Germany," Telecommunications Policy, Elsevier, vol. 42(3), pages 212-226.
    3. Guven, Faruk, 2018. "Churn and loyalty behaviour of Turkish digital natives," 29th European Regional ITS Conference, Trento 2018 184943, International Telecommunications Society (ITS).
    4. Sang-Gun Lee & Chang-Gyu Yang & Sin-Bok Lee & Jae-Beom Lee, 2015. "A study on the antecedents and consequences of satisfaction and dissatisfaction in web portal usage," Service Business, Springer;Pan-Pacific Business Association, vol. 9(3), pages 567-586, September.
    5. Toni Lupo & Seyyed Ali Delbari, 2018. "A knowledge-based exploratory framework to study quality of Italian mobile telecommunication services," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(1), pages 129-144, May.
    6. Gerpott, Torsten J. & Ahmadi, Nima & Weimar, Daniel, 2015. "Who is (not) convinced to withdraw a contract termination announcement? – A discriminant analysis of mobile communications customers in Germany," Telecommunications Policy, Elsevier, vol. 39(1), pages 38-52.
    7. Srinuan, Pratompong & Srinuan, Chalita & Bohlin, Erik, 2014. "An empirical analysis of multiple services and choices of consumer in the Swedish telecommunications market," Telecommunications Policy, Elsevier, vol. 38(5), pages 449-459.
    8. Capponi, Giovanna & Corrocher, Nicoletta & Zirulia, Lorenzo, 2021. "Personalized pricing for customer retention: Theory and evidence from mobile communication," Telecommunications Policy, Elsevier, vol. 45(1).
    9. Hemlata Jain & Ajay Khunteta & Sumit Srivastava, 2021. "Telecom churn prediction and used techniques, datasets and performance measures: a review," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(4), pages 613-630, April.
    10. Abbas Keramati & Hajar Ghaneei & Seyed Mohammad Mirmohammadi, 2016. "Developing a prediction model for customer churn from electronic banking services using data mining," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-13, December.
    11. Ilisa Fajriyati & Adi Zakaria Afiff & Gita Gayatri & Sri Rahayu Hijrah Hati, 2022. "Attributes Influencing Overall Tourist Satisfaction and Its Consequences for Muslim-Majority Destination," SAGE Open, , vol. 12(1), pages 21582440211, January.
    12. Morteza Nagahi & Niamat Ullah Ibne Hossain & Raed Jaradat & Vidanelage Dayarathna & Chuck Keating & Simon Goerger & Michael Hamilton, 2022. "Classification of individual managers' systems thinking skills based on different organizational ownership structures," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(2), pages 258-273, March.
    13. Karjaluoto, Heikki & Jayawardhena, Chanaka & Leppäniemi, Matti & Pihlström, Minna, 2012. "How value and trust influence loyalty in wireless telecommunications industry," Telecommunications Policy, Elsevier, vol. 36(8), pages 636-649.
    14. Soomro, Yasir & Al-Sehli, Ahmed Nafe, 2020. "Determinants of Customer Churn: An Empirical Study Of Cellular Subscribers From Saudi Arabia," MPRA Paper 101398, University Library of Munich, Germany.
    15. García-Mariñoso, Begoña & Suárez, David, 2019. "Switching mobile operators: Evidence about consumers’ behavior from a longitudinal survey," Telecommunications Policy, Elsevier, vol. 43(5), pages 426-433.
    16. Thangeda, Rahul & Kumar, Niraj & Majhi, Ritanjali, 2024. "A neural network-based predictive decision model for customer retention in the telecommunication sector," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    17. Benítez-Peña, Sandra & Blanquero, Rafael & Carrizosa, Emilio & Ramírez-Cobo, Pepa, 2024. "Cost-sensitive probabilistic predictions for support vector machines," European Journal of Operational Research, Elsevier, vol. 314(1), pages 268-279.

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