IDEAS home Printed from https://ideas.repec.org/a/ids/ijbisy/v16y2014i3p233-246.html
   My bibliography  Save this article

Estimation of customer retention for Indian mobile telecommunication sector

Author

Listed:
  • M. Ravindar Reddy
  • Srikanth Ganesh
  • T. Rahul
  • Nandini Mann

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.

Suggested Citation

  • M. Ravindar Reddy & Srikanth Ganesh & T. Rahul & Nandini Mann, 2014. "Estimation of customer retention for Indian mobile telecommunication sector," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 16(3), pages 233-246.
    • Handle: RePEc:ids:ijbisy:v:16:y:2014:i:3:p:233-246
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=63766
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijbisy:v:16:y:2014:i:3:p:233-246. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=172 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.