EconPapers    
Economics at your fingertips  
 

Estimation of customer retention for Indian mobile telecommunication sector

M. Ravindar Reddy, Srikanth Ganesh, T. Rahul and Nandini Mann

International Journal of Business Information Systems, 2014, vol. 16, issue 3, 233-246

Abstract: The objectives of this study are to find the factors that influence the customer loyalty and switching barriers and based on these factors predict the retention level of individual customer using artificial neural network. A well-structured questionnaire was designed and distributed to a random sample of mobile phone users. The questionnaire contains factors affecting customer retention, measured on a five-point Likert-scale. The data were analysed using factor analysis to identify the factors affecting customer loyalty and switching barriers. A paired sample T-test was carried out to determine the relationship between customer retention and customer loyalty and also to determine relationship between customer retention and switching barriers. Functional link artificial neural network (FLANN) and Legendre neural networks (LeNNs) were used to predict retention level of a customer. From the analysis, it was concluded that the switching barriers are as important as customer loyalty for retaining customers, and the FLANN model gives better customer retention prediction than the LeNN model.

Keywords: customer loyalty; switching barriers; customer retention; functional link ANNs; artificial neural networks; FLANNs; Legendre neural networks; LeNNs; mobile telecommunications; mobile phones; cell phones; India; mobile communications. (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=63766 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:16:y:2014:i:3:p:233-246

Access Statistics for this article

More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijbisy:v:16:y:2014:i:3:p:233-246