Skip to main content
Erschienen in: Wireless Networks 2/2018

04.08.2016

A model for the mobile market based on customers profile to analyze the churning process

verfasst von: Mario Rogelio Flores-Méndez, Marcos Postigo-Boix, José Luis Melús-Moreno, Burkhard Stiller

Erschienen in: Wireless Networks | Ausgabe 2/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In the current telecommunications market that is reaching high saturation levels, mobile network operators (MNOs) try to position themselves among customers through aggressive marketing campaigns and offers. In this environment where customers have multiple MNOs to choose from, different factors influence customers’ decisions. In addition to this, mobile number portability contributes to a phenomenon called churning where customers migrate from one MNO to another. Churning impacts not only the network design but also the pricing methods adopted by MNOs, and hence their revenue. It is because of this that MNOs try to reduce churn through retention campaigns. The key factor for the success of these campaigns is to detect potential churners before they leave the service. The state of the art has focused on proposing methods to identify churners based on data mining techniques, however these techniques doesn’t always offer clear explanations for churn reasons. Instead, we use a technique called agent-based modeling to model customers in the mobile telecommunication market and assess the effects of customers characteristics and behaviors on such market. We propose a model that includes some relevant demographic and psychographic characteristics and the utilizations of usage profiles to describe customers. We show with simple experiments how different factors lead to churn in different ways. We believe the proposed approach is useful because MNOs can use it for explanatory, exploratory and predictive purposes.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Chau, A. (Ed.). (2010). Asia/Pacific (excluding Japan) mobile services year-end review (Vol. 1). IDC. Chau, A. (Ed.). (2010). Asia/Pacific (excluding Japan) mobile services year-end review (Vol. 1). IDC.
2.
Zurück zum Zitat Kendall, P. (2009). Wireless operator performance benchmarking Q3 2009. Strategy Analytics. Kendall, P. (2009). Wireless operator performance benchmarking Q3 2009. Strategy Analytics.
3.
Zurück zum Zitat ICT Data and Statistics Division. (2013). The world in 2013: ICT facts and figures. International Telecommunication Union. ICT Data and Statistics Division. (2013). The world in 2013: ICT facts and figures. International Telecommunication Union.
4.
Zurück zum Zitat Lonergan, D. (Ed.). (2012). Improve communication to minimize churn. Yankee Group. Lonergan, D. (Ed.). (2012). Improve communication to minimize churn. Yankee Group.
5.
Zurück zum Zitat Twomey, P., & Cadman, R. (2002). Agent-based modelling of customer behaviour in the telecoms and media markets. Info, 4(1), 56–63.CrossRef Twomey, P., & Cadman, R. (2002). Agent-based modelling of customer behaviour in the telecoms and media markets. Info, 4(1), 56–63.CrossRef
7.
Zurück zum Zitat Wong, K. K. K. (2011). Using cox regression to model customer time to churn in the wireless telecommunications industry. Journal of Targeting, Measurement and Analysis for Marketing, 19(1), 37–43.CrossRef Wong, K. K. K. (2011). Using cox regression to model customer time to churn in the wireless telecommunications industry. Journal of Targeting, Measurement and Analysis for Marketing, 19(1), 37–43.CrossRef
8.
Zurück zum Zitat Kasiran, Z., Ibrahim, Z., & Ribuan, S. M. M. (2012). Mobile phone customers churn prediction using elman and jordan recurrent neural network. In 2012 7th international conference on computing and convergence technology (ICCCT), pp. 673–678, Dec 2012. Kasiran, Z., Ibrahim, Z., & Ribuan, S. M. M. (2012). Mobile phone customers churn prediction using elman and jordan recurrent neural network. In 2012 7th international conference on computing and convergence technology (ICCCT), pp. 673–678, Dec 2012.
9.
Zurück zum Zitat Kim, N., Lee, J., Jung, K.-H., & Kim, Y. S. (2012). A new ensemble model for efficient churn prediction in mobile telecommunication. In 2012 45th Hawaii international conference on system science (HICSS), pp. 1023–1029, Jan 2012. Kim, N., Lee, J., Jung, K.-H., & Kim, Y. S. (2012). A new ensemble model for efficient churn prediction in mobile telecommunication. In 2012 45th Hawaii international conference on system science (HICSS), pp. 1023–1029, Jan 2012.
10.
Zurück zum Zitat Inoue, A., Iwashita, M., Kurosawa, T., & Nishimatsu, K. (2013). Mobile-carrier choice behavior analysis around smart phone market. In 2013 14th ACIS international conference on software engineering, artificial intelligence, networking and parallel/distributed computing (SNPD), pp. 400–405, July 2013. Inoue, A., Iwashita, M., Kurosawa, T., & Nishimatsu, K. (2013). Mobile-carrier choice behavior analysis around smart phone market. In 2013 14th ACIS international conference on software engineering, artificial intelligence, networking and parallel/distributed computing (SNPD), pp. 400–405, July 2013.
11.
Zurück zum Zitat Qureshi, S. A., Rehman, A. S., Qamar, A. M., Kamal, A., & Rehman, A. (2013). Telecommunication subscribers’ churn prediction model using machine learning. In 2013 eighth international conference on digital information management (ICDIM), pp. 131–136, Sept 2013. Qureshi, S. A., Rehman, A. S., Qamar, A. M., Kamal, A., & Rehman, A. (2013). Telecommunication subscribers’ churn prediction model using machine learning. In 2013 eighth international conference on digital information management (ICDIM), pp. 131–136, Sept 2013.
12.
Zurück zum Zitat Yabas, U., & Cankaya, H. C. (2013). Churn prediction in subscriber management for mobile and wireless communications services. In Globecom workshops (GC Wkshps), 2013 IEEE, pp. 991–995, Dec 2013. Yabas, U., & Cankaya, H. C. (2013). Churn prediction in subscriber management for mobile and wireless communications services. In Globecom workshops (GC Wkshps), 2013 IEEE, pp. 991–995, Dec 2013.
13.
Zurück zum Zitat Lu, N., Lin, H., Lu, J., & Zhang, G. (2014). A customer churn prediction model in telecom industry using boosting. IEEE Transactions on Industrial Informatics, 10(2), 1659–1665.CrossRef Lu, N., Lin, H., Lu, J., & Zhang, G. (2014). A customer churn prediction model in telecom industry using boosting. IEEE Transactions on Industrial Informatics, 10(2), 1659–1665.CrossRef
14.
Zurück zum Zitat Niyato, D., & Hossain, E. (2008). Modeling user churning behavior in wireless networks using evolutionary game theory. In Wireless communications and networking conference, 2008. WCNC 2008. IEEE, pp. 2793–2797, March 2008. Niyato, D., & Hossain, E. (2008). Modeling user churning behavior in wireless networks using evolutionary game theory. In Wireless communications and networking conference, 2008. WCNC 2008. IEEE, pp. 2793–2797, March 2008.
15.
Zurück zum Zitat Hassouna, M. & Arzoky, M. (2011). Agent based modelling and simulation: Toward a new model of customer retention in the mobile market. In Proceedings of the 2011 summer computer simulation conference, SCSC ’11, pp. 30–35, Vista, CA, 2011. Society for Modeling and Simulation International. Hassouna, M. & Arzoky, M. (2011). Agent based modelling and simulation: Toward a new model of customer retention in the mobile market. In Proceedings of the 2011 summer computer simulation conference, SCSC ’11, pp. 30–35, Vista, CA, 2011. Society for Modeling and Simulation International.
16.
Zurück zum Zitat Assimakopoulos, C. (2013). Mobile internet users profile along with subscribers model of payment and attitudinal characteristics. Procedia Technology, 8:425–434. 6th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2013). Assimakopoulos, C. (2013). Mobile internet users profile along with subscribers model of payment and attitudinal characteristics. Procedia Technology, 8:425–434. 6th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2013).
17.
Zurück zum Zitat Dharmapalan, J. (Ed.). (2013). The mobile maze: Navigating consumer usage of mobile data. Ernst & Young Global Limited. Dharmapalan, J. (Ed.). (2013). The mobile maze: Navigating consumer usage of mobile data. Ernst & Young Global Limited.
18.
Zurück zum Zitat Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information and Management, 48(1), 1–8.CrossRef Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information and Management, 48(1), 1–8.CrossRef
19.
Zurück zum Zitat Kumar, A., & Lim, H. (2008). Age differences in mobile service perceptions: Comparison of Generation Y and baby boomers. Journal of Services Marketing, 22(7), 568–577.CrossRef Kumar, A., & Lim, H. (2008). Age differences in mobile service perceptions: Comparison of Generation Y and baby boomers. Journal of Services Marketing, 22(7), 568–577.CrossRef
20.
Zurück zum Zitat Kumar, U., & Helmy, A. (2010). Extract: Mining social features from wlan traces—A gender-based case study. In Proceedings of the 13th ACM international conference on modeling, analysis, and simulation of wireless and mobile systems, MSWIM ’10, pp. 240–247, New York, NY, USA, 2010. ACM. Kumar, U., & Helmy, A. (2010). Extract: Mining social features from wlan traces—A gender-based case study. In Proceedings of the 13th ACM international conference on modeling, analysis, and simulation of wireless and mobile systems, MSWIM ’10, pp. 240–247, New York, NY, USA, 2010. ACM.
21.
Zurück zum Zitat Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decision: Implications for a changing work force. Personnel Psychology, 53(2), 375–403.CrossRef Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decision: Implications for a changing work force. Personnel Psychology, 53(2), 375–403.CrossRef
22.
Zurück zum Zitat Pagani, M. (2004). Determinants of adoption of third generation mobile multimedia services. Journal of Interactive Marketing, 18(3), 46–59.CrossRef Pagani, M. (2004). Determinants of adoption of third generation mobile multimedia services. Journal of Interactive Marketing, 18(3), 46–59.CrossRef
23.
Zurück zum Zitat Papaioannou, E., Georgiadis, C. K., Kourouthanassis, P. E., & Giaglis, G. M. (2011). Profiling the mobile phone users and their relationship to the internet services and portals. In 2011 tenth international conference on mobile business (ICMB), pp. 313–319, June 2011. Papaioannou, E., Georgiadis, C. K., Kourouthanassis, P. E., & Giaglis, G. M. (2011). Profiling the mobile phone users and their relationship to the internet services and portals. In 2011 tenth international conference on mobile business (ICMB), pp. 313–319, June 2011.
24.
Zurück zum Zitat Peslak, A., Shannon, L.-J., & Ceccucci, W. (2011). An empirical study of cell phone and smartphone usage. Issues in Information Systems, 12(1), 407–417. Peslak, A., Shannon, L.-J., & Ceccucci, W. (2011). An empirical study of cell phone and smartphone usage. Issues in Information Systems, 12(1), 407–417.
25.
Zurück zum Zitat Quorus Consulting Group. (2012). Cell phone consumer attitudes study. Canadian Wireless Telecommunications Association, April 2012. Quorus Consulting Group. (2012). Cell phone consumer attitudes study. Canadian Wireless Telecommunications Association, April 2012.
26.
Zurück zum Zitat Rocha, E., Salvador, P., & Nogueira, A. (2012). Classification of hidden users’ profiles in wireless communications. In Kostas P., Rui A., Susana S., & Ramón A. (Eds.), Mobile networks and management (Vol. 97, pp. 3–16). Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Berlin Heidelberg: Springer. Rocha, E., Salvador, P., & Nogueira, A. (2012). Classification of hidden users’ profiles in wireless communications. In Kostas P., Rui A., Susana S., & Ramón A. (Eds.), Mobile networks and management (Vol. 97, pp. 3–16). Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Berlin Heidelberg: Springer.
27.
Zurück zum Zitat Sell, A., Mezei, J., & Walden, P. (2014). An attitude-based latent class segmentation analysis of mobile phone users. Telematics and Informatics, 31(2), 209–219.CrossRef Sell, A., Mezei, J., & Walden, P. (2014). An attitude-based latent class segmentation analysis of mobile phone users. Telematics and Informatics, 31(2), 209–219.CrossRef
28.
Zurück zum Zitat Shi, C. K., Hao, X., & Sharma, R. S.. A cross-disciplinary study of what determines the adoption of MDS. In 2010 43rd Hawaii international conference on system sciences (HICSS), pp. 1–11, Jan 2010. Shi, C. K., Hao, X., & Sharma, R. S.. A cross-disciplinary study of what determines the adoption of MDS. In 2010 43rd Hawaii international conference on system sciences (HICSS), pp. 1–11, Jan 2010.
29.
Zurück zum Zitat Dewey, J. (2007). How we think. Lightning Source Incorporated. Dewey, J. (2007). How we think. Lightning Source Incorporated.
30.
Zurück zum Zitat Anaman, M., & Lycett, M. (2010). Toward a model of customer experience: An action research study within a mobile telecommunications comodel. In 12th international conference on enterprise information systems (ICEIS 2010). Funchal, Madeira, Portugal. June 2010. Anaman, M., & Lycett, M. (2010). Toward a model of customer experience: An action research study within a mobile telecommunications comodel. In 12th international conference on enterprise information systems (ICEIS 2010). Funchal, Madeira, Portugal. June 2010.
32.
Zurück zum Zitat Bemmaor, A. C., & Glady, N. (2012). Modeling purchasing behavior with sudden “death”: A flexible customer lifetime model. Management Science, 58(5), 1012–1021.CrossRef Bemmaor, A. C., & Glady, N. (2012). Modeling purchasing behavior with sudden “death”: A flexible customer lifetime model. Management Science, 58(5), 1012–1021.CrossRef
Metadaten
Titel
A model for the mobile market based on customers profile to analyze the churning process
verfasst von
Mario Rogelio Flores-Méndez
Marcos Postigo-Boix
José Luis Melús-Moreno
Burkhard Stiller
Publikationsdatum
04.08.2016
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 2/2018
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-016-1334-8

Weitere Artikel der Ausgabe 2/2018

Wireless Networks 2/2018 Zur Ausgabe

Neuer Inhalt