Factors affecting Service Quality, Customer Satisfaction and Customer Churn in Pakistan Telecommunication Services Market

Authors:

Yasser Khan,Shahryar Shafiq,Sheeraz Ahmed,Nadeem Safwan,Mehr-e-Munir,Alamgir Khan,

DOI NO:

https://doi.org/10.26782/jmcms.2019.08.00048

Keywords:

Service quality,Customer Satisfaction,Customer Churn,Customer Loyalty,

Abstract

Telecommunication quality of service and customer satisfaction are the importantdecisive factors responsible for shifting of loyalties and increase profitability to the face the fierce competition in Pakistan telecommunication market comprised of 154 million cellular subscribers with 73.85% Teledensity. This paper intend to determine relationship among these variables and their impact on customer switching to another operator which has also become global phenomena. The analysis is conducted on primary data collected that is randomly sampled. The results clearly indicate the strong positive relations of value added services on service quality & customer satisfaction and strongly negative relationship with customer propensity to churn in Pakistan Telecom Environment. Resultantly, the customer churn can easily be controlled by providing enhance quality of voice, robust and reliable connectivity, better complaint management, customer care, and value added services with adequate features.

Refference:

I. Abbas Al-Refaie, Murad Al-Tarawneh, Nour Bata “ study of customer
churn in the telecom industry using structural equation modelling”
Journal of International Scientific Publications Economy & Business
ISSN 1314-7242, Volume 12, 2018
II. Abbas Al-Refaie “Cluster Analysis of Customer Churn in Telecom
Industry”, World Academy of Science, Engineering and Technology
International Journal of Social, Behavioral, Educational, Economic,
Business and Industrial Engineering Vol:11, No:5, 2017.
III. Adnan, Feras, Babar, Awais, sajjad “Customer churn prediction in
telecommunication industry using data certainty”, Journal of Business
Research Volume 94, January 2019, Page 290-301

IV. Alrend, Anju, Indu, Jay, Erbeth, Leslyn,”Determining the intervening
effects of exploratory data analysis and feature engineering in telecoms
customer churn modelling”,2019 4th MEC International Conference on
Big data and Smart city (ICBDSC).
V. Alrence Santiago Halibas ; Anju Cherian Matthew ; InduGovinda
Pillai ; Jay Harold Reazol ; Erbeth Gerald De “Determining the
Intervening Effects of Exploratory Data Analysis and Feature Engineering
in Telecoms Customer Churn Modelling” 2019 4th MEC International
Conference on Big Data and Smart City (ICBDSC)
VI. Amin A., Shehzad S., Khan C., Ali I., Anwar S. (2015) Churn
Prediction in Telecommunication Industry Using Rough Set Approach.
In: Camacho D., Kim SW., Trawiński B. (eds) New Trends in
Computational Collective Intelligence. Studies in Computational
Intelligence, vol 572 pp 83-95
VII. Amit C and InduUprety, “Analysis of telecom service quality factors with
analytic hierarchy process and fuzzy extent analysis: a case of public
sector unit”, Int. J. Business and Systems Research, Vol. 10, Nos. 2/3/4,
2016
VIII. Archi D , Dr. A.K. Srivastava, Impact of Service Quality on Customer
Loyalty- A Study on Telecom Sector in India”, IOSR Journal of Business
and Management (IOSR-JBM) Volume 18, Issue 2 .Ver. I (Feb. 2016), PP
45-55
IX. A.Saran Kumar, Dr. D. Chandrakala “An Optimal Churn Prediction
Model using Support Vector Machine with Adaboost” International
Journal of Scientific Research in Computer Science, Engineering and
Information Technology © 2017 IJSRCSEIT | Volume 2 | Issue 1
X. W.B. Huang, M. T. Kechadi, and B. Buckley, “Customer churn prediction
in telecommunications,” Expert Syst. Appl., vol. 39,no. 1, pp. 1414–1425,
Jan. 2012.
XI. Choi, S.-K.,Lee,M.H.,&Chung,G. H.(2001).Competition in Korean mobile
telecommunications market: Business strategy and regulatory
environment. Telecommunications Policy, 25, 125–138.
XII. Dirk Van den Poel, Bart Larivière, and “Customer Attrition Analysis for
Financial Services Using Proportional Hazard Models” issue 13(3), 45-55
(2017) [2]
XIII. Fornell, C. (1992). A national customer satisfaction barometer: The
Swedish experience. Journal of Marketing, 56, 6–21.
XIV. Greenwell, T.C., Fink, J.S., Pastore, D.L., 2002. Assessing the influence
of the physical sports facility on customer satisfaction within the context
of the service experience. Sport Manag. Rev. 5 (2), 129–148[28]
XV. Green, D. (1994), What is Quality in Higher Education?, 1st ed., The
Society for Research into Higher Education & Open University press,
Buckingham.
XVI. Jae-Hyeon, , Sang-Pil, Yung “Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry” Telecommunications Policy 30 (2006) 552–568

XVII. Jayawardhana, P., Perera, D., Kumara, A. and Paranawithana, A
“Kanthaka: Big Data Caller Detail Record (CDR) Analyzer for Near Real
Time Telecom Promotions.” In 2013 4th International Conference on
Intelligent Systems, Modelling and Simulation, pp. 534-538.IEEE, (2013).
XVIII. J. Hadden, A. Tiwari, R. Roy, and D. Ruta, “Computer assisted customer
churn management: State-of-the-art and futuretrends,” Comput. Oper.
Res., vol. 34, no. 10, pp. 2902–2917, Oct. 2007.
XIX. Jay KandampullyTingting (Christina) Zhang Anil Bilgihan ,
(2015),”Customer loyalty: a review and future directions with a special
focus on the hospitality industry”, International Journal of Contemporary
Hospitality Management, Vol. 27 Iss 3 pp. 379 – 414
XX. Kim, Hee-Su., & Kwon, N. (2003). The advantage of network size in
acquiring new subscribers. Information Economics and Policy, 15(1), 17–
33
XXI. Kiran Dahiya, Surbhi Bhatia” Customer churn analysis in telecom
industry” 2015, 4th International Conference on Reliability, Infocom
Technologies and Optimization (ICRITO) (Trends and Future Directions.
XXII. Kotler, P., & Keller, K. L. (2009). Marketing management (13th ed.). New
Jersey: Pearson Prentice Hall.
XXIII. Mahafuz M, Md.Fazl, Nusrat C, Priodorshine S, “Customer satisfaction,
switching intentions, perceived switching costs, and perceived alternative
attractiveness in Bangladesh mobile telecommunications market”, South
Asian Journal of Business Studies 2017, Vol. 6 Issue: 2
XXIV. Manish, Awadhesh, AP Rathore,”Prediction Model for Telecom Postpaid
Customer Churn using Six-Sigma Methodology”, International Journal of
Manufacturing Technology and Management , Volume 31, Issue 5, 2017
XXV. Muhammad Azeem , Muhammad Usman “A fuzzy based churn prediction
and retention model for prepaid customers in telecom industry”
International Journal of Computational Intelligence Systems, Vol. 11
(2018) 66–78
XXVI. Oliver, R. L. (1997). Satisfaction: A behavioral perspective on the
consumer. Boston: Irwin McGraw-Hill
XXVII. PiasonViriri , Maxwell Phiri, “Determinants of Customer Satisfaction in
Zimbabwe Telecommunication Industry” , J Communication, 8(1): 101-
104 (2017)
XXVIII.Ritter, T., &Gemünden, H.G., (2003). “Network competence: Its impact on
innovation success and its antecedents”. Journal of Business Research,
56(9), 745-755.
XXIX. Roberts,J.H, ”Developing new rules for new markets”, Journal of the
Academy of Marketing Science, issue 28(1), 31–44 (2000).
XXX. Sebastiaan,Eugen, Bart, vanden,“Profit driven decision trees for churn
prediction” European Journal of Operational Research,2018
XXXI. Shreya M, Shubham G, Shubhangi J, Vidushi M, Artika S “Survey on
Prediction of Customer Churn Analysis in a Telecommunications Industry”, International Journal for Research in Engineering Application & Management (IJREAM)Vol-02, Issue 07, Oct 2016
XXXII. Spath, 2009, Introduction to Healthcare Quality Management,1st Edition.
Health Administration Press, Chicago, Illinois.
XXXIII.TVafeidadis, K.I. Diamantaras, Sarigiannidis, Chatzisavvas“ A
comparison of machine learning techniques for customer churn
prediction”, Simulation Modelling Practice and Theory Volume55,
June 2015 Pages1-9
XXXIV.Wenjie B, Meili C, Guo Li” A Big Data Clustering Algorithm for Mitigating
the Risk of Customer Churn” IEEE TRANSACTIONS ON INDUSTRIAL
INFORMATICS, VOL. 12, NO. 3, JUNE 2016
XXXV. Yiging H, Fangzhou Z, Mingxuan Y, KeYanhua Li, Bing N, Jia Z” Telco
Churn Prediction with Big Data”proceedings of the 2015 ACM Sigmod
International conference on management of data page 607-618, 2015
XXXVI. Zeithaml, Valerie A. &Bitner, Mary J. (2000) Services Marketing:
Integrating customer focus across the firm, 2nd ed., Irwin/ McGraw-Hill,
Boston, M.A

 

 

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