Dergiler / Sakarya University Journal of Science / 2022 / Cilt: 26 Sayı: 3

The Attitudes of the Telecommunication Customers in the COVID-19 Outbreak: The Effect of the Feature Selection Approach in Churn Analysis

Sayfa
530–544
Yayın Tarihi
2022-06-30
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This paper contributes to the practitioners by presenting the most important customer features in telecom customer churn, and a new approach in performance evaluation have been proposed specific to the telecommunication market with the industry experts’ guidance as a theoretical contribution.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Today's rising cutting-edge technology requirements and competitive environment in telecommunication industry has gained a remarkable importance due to the COVID-19 pandemics in terms of high need of information sharing and remote communication necessity.
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Temel Bulgular & Veri:Telecommunication companies conduct significant analyses by highlighting that the customer data is the most valuable information.
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Sonuç & Katkı:This paper contributes to the practitioners by presenting the most important customer features in telecom customer churn, and a new approach in performance evaluation have been proposed specific to the telecommunication market with the industry experts’ guidance as a theoretical contribution.
🔬Tür:Araştırma Makalesi
📍Kapsam:2019 Verileri
⚙️Değişkenler:telecommunication · customer churn · churn analysis

Abstract

Today's rising cutting-edge technology requirements and competitive environment in telecommunication industry has gained a remarkable importance due to the COVID-19 pandemics in terms of high need of information sharing and remote communication necessity. Telecommunication companies conduct significant analyses by highlighting that the customer data is the most valuable information. Besides, they obtain results emphasizing that acquiring new customers is costlier than retaining the existing ones. Therefore, the companies are willing to determine the important customer features in order to understand why they shift to the other telecommunication service providers. Hence, this study aims to conduct a churn analysis by feature selection approach with large volumes of telecommunication customer data in order to present what kind of customer behaviors and qualifications exist. Since there is a huge amount of data in this field, data mining is a vital requirement. The performance outputs were observed, and the features carrying these outputs to the highest value were identified. The data collection and analysis were carried out in mid-2019, and the same data collection and analysis were carried out again at the beginning of 2021, and these before and after results were compared. In addition, a comparison was made with the results obtained by the other churn analysis studies. This paper contributes to the practitioners by presenting the most important customer features in telecom customer churn, and a new approach in performance evaluation have been proposed specific to the telecommunication market with the industry experts’ guidance as a theoretical contribution.

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Bu Makaleye Atıf Yap

DONAT, H., USTA, S. K. (2022). The Attitudes of the Telecommunication Customers in the COVID-19 Outbreak: The Effect of the Feature Selection Approach in Churn Analysis. Sakarya University Journal of Science, Cilt: 26 Sayı: 3, 530–544. https://ajindex.com/articles/941706

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Kaynakça (13)

  1. P.J. Nesse, S.W. Svaet, D. Strasunskas, and A.A. Gaivoronski, “Assessment and optimisation of business opportunities for telecom operators in the cloud value network”, Transactions on emerging telecommunications technologies, vol.24, no.5, pp. 503-516, 2013
  2. T.-H. Chou, J.-L. Seng, “Telecommunication e-services orchestration enabling business process management”, Transactions on emerging telecommunications technologies, vol.23, no.7, pp. 646-659, 2012
  3. Y. Atlı, N. Yücel, “Hibrit iletişim teknolojileri”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol.21, no.3, pp. 785-797, 2016
  4. Deloitte. “Covid-19 sonrası tedarik zincirlerinde kazananlar ve kaybedenler.” https://www2.deloitte.com/tr/tr/pages/consumer-business/articles/Covid-19-sonrasi-tedarik-zinciri.html 2021
  5. PwC. “COVID-19 salgınının telekom sektörü üzerinde olası etkileri”. https://www.pwc.com.tr/covid-19-telekom-sektoru 2020
  6. S. Tabassum, M.A. Azad, and J. Gama, “Profiling high leverage points for detecting anomalous users in telecom data networks”, Annals of Telecommunications, vol.75, no.9-10, pp. 573-581, 2020
  7. U. T. Şimşek Gürsoy, “Customer churn analysis in telecommunication sector”. Istanbul University Journal of the School of Business Administration, vol.39, no.1, pp.35–49, 2010
  8. García, D. L., Nebot, À., & Vellido, A. Intelligent data analysis approaches to churn as a business problem: a survey. Knowledge and Information Systems, 2017, 51(3), 719–774
  9. A. K. Ahmad, A. Jafar, & K. Aljoumaa, “Customer churn prediction in telecom using machine learning in big data platform”. Journal of Big Data, pp. 6-28, 2019
  10. M. Al-Mashraie, S.H. Chung, H.W. Jeon, “Customer switching behavior analysis in the telecommunication industry via push-pull-mooring framework: A machine learning approach”, Computers and Industrial Engineering, vol.144, 106476, 2020
  11. N. Alboukaey, A. Joukhadar, N. Ghneim, “Dynamic behavior based churn prediction in mobile telecom”, Expert Systems with Applications, 162, 2020
  12. M. Ahmed, H. Afzal, I. Siddiqi, M.F. Amjad, K. Khurshid, “Exploring nested ensemble learners using overproduction and choose approach for churn prediction in telecom industry”, Neural Computing and Applications, vol. 32, no.8, pp. 3237-3251, 2020
  13. M. Hemalatha, S. Mahalakshmi, “Customer churns prediction in telecom using adaptive logitboost learning approach”, International Journal of Scientific and Technology Research, vol.9 no.