Abstract

Nowadays the telecommunications sector is becoming very complex Because of the panoply of high-speed technological services. Customers are abandoning the services offered by telecommunications operators because of their dissatisfaction with the services they offer. «Churn» or the migration of customers from one telecommunications operator to another is the main problem facing the telecommunications industries worldwide. Business managers consider the quality of service to be paramount. As a consequence, they have devised reliable criteria to assess the flow of customers within the market and check and evaluate whether customers are satisfied with the services they are offered. This, in turn, helps to establish customer loyalty and provide a healthy and sustainable trading agreement. Service quality control assessment is pivotal to identify the leverage and evaluate the internal and external competition in the industry. Although this concept is not foreign, rather it is an essential business management tool. The goal of this study is to determine the significant criteria for the cause migration of a Tunisie Telecom customer to another operator. Telecommunication is an essential lifelong component that contributes to the comfortability of our daily lives. The various means of telephone communication play a significant role in improving the effectiveness of communication industry. Every telecommunication operator is aware today that it is cheaper to retain an existing customer than to seek to recruit a new one. Indeed, we noticed that the telecommunications market is characterized by intense competition, where a change in the quality of service or a negative interaction perceived by the customer could risk losing them. As a result, the majority of operators introduce studies and action plans to retain customers and keep them as long as possible. The notion of keeping customers and building loyalty is probably one of the biggest challenges that operators around the world face in global competition. In order to achieve the goals set by telecom operators and to achieve maximum profitability, operators must effectively analyze market data and adopt a most effective targeted communications strategy for their customers.

Keywords: churn analysis, customer loyalty, mobile marketing, telecommunications, telecommunications customer

JEL Classification: L14, M31.

Cite as: Mbarek, R, Baeshen, Y. (2019). Telecommunications customer churn and loyalty intention. Marketing and Management of Innovations, 4, 110-117. https://doi.org/10.21272/mmi.2019.4-09

This work is licensed under a Creative Commons Attribution 4.0 International License

References

1. Ahn, J.H., Han, S.P., Lee, Y.S. (2006). Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry. Telecommunications Policy 30(10-11), 552-568.
2. Ashwin Wali and Sunitha R.S. (2016). Churn Analysis and Plan Recommendation for Telecom Operators, Journal for Research|,Volume 02, Issue 3.
3. Aspromourgos. Adam Smith on Labour and capital. In Berry, C. J., Paganelli, M. P., Smith, C. (Eds). (2013). The Oxford handbook of Adam Smith (pp. 267–289). Oxford: Oxford University Press.
4. Gundlach, G., Achrol, R. and Mentzer, J. (1995). The Structure of Commitment in Exchange. Journal of Marketing, 59, 78-92.
5. K.Dahiya and S.Bhatai. (2015). Customer churn analysis in telecom industry, 4th International Conference on Realibility, Infocom Tehnilogies and Optimization (ICRITO).
6. Kiesler, C. A. (1971). The psychology of commitment: experiments linking behavior to belief. New York: Academic Press.
7. Killeya, J.C, Armistead, C.G. (1984). Transfer of Concepts between Manufacture and Service’, International Journal of Operations and Production Management, Vol 3, No 3.
8. Balasubramanian, M. and Selvarani, M. (2014). Churn Prediction in Mobile Telecom Systems Using Data Mining Techniques, Department Of Computer Science, Annamalai University, Chidambaram, April.
9. Mbarek Rahmoun Dr. Mairaj Salim and Amal Kefi. (2017). Impact of perceived service quality on business customers satisfaction «an empirical study of tunisie telecom operators», International Journal of Current Research.
10. Morgan, R, M. et Hunt, S, D. (1994). The Commitment-Trust Theory of Relationship Marketing, Journal of Marketing, Vol, 58, N°, 20/38, 20-23.
11. Morman C., Zaltman G., & R. Desphande (1992). Relationships between Providers and Users of Market Research: the Dynamics of Trust within and between Organizations. Journal of Marketing Research, 29, 31 4-328.
12. Moulins, J-L. et Roux, E. (2008). Un Modele tridimensionnel des relations a la marque : de limage de marque a la fidelite et aux communications de bouche-a-oreille, Communication au Congres Marketing Trends, Venise, 17-19 janvier, 4-8-9-10.
13. Oliver, L, R. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions, Journal of Marketing Research, Vol, 17, N°, 4, 460-469.
14. Oliver, L.R. (1999). Whence Consumer Loyal, Journal of Marketing, 63, 34-35-36.
15. Rahul J. Jadhav and Usharani T. Pawar, (2011). Churn Prediction in Telecommunication Using Data Mining Technology, International Journal of Advanced Computer Science and Applications, vol. 2, no. 2.
16. Shaaban, Essam, Yehia Helmy, Ayman Khedr, and Mona Nasr (2012). A proposed churn prediction model. IJERA 2, 693-697.
17. Umayaparvathi V., Iyakutti K. (2016). A Survey on Customer Churn Prediction in Telecom Industry: Datasets, Methods and Metrics, International Research Journal of Engineering and Technology (IRJET), vol. 03, no. 04.
18. Umayaparvathi, V., Iyakutti, K. (2016). Attribute Selection and Customer Churn Prediction in Telecom Industry, Proceedings of the IEEE International Conference On Data Mining and Advanced Computing.