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Customer Relationship Management as Tool to Enhance Competitive Effectiveness: Model Revisited

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  • Maraj Rahman Sofi
  • Iqbal Ahmad Hakim

Abstract

Maintaining collaborative relationships of a business firm with the customer is very important in the contemporary competitive business scenario, besides the service rendered by it. Against this backdrop, the study was undertaken which aims to analyse the customer relationship management (CRM) practices and dimensions in the business. The past research studies were reviewed and the CRM frameworks given by the various authors, in particular of Sin, Tse, and Yim (2005, European Journal of Marketing , 11 (12), 1264–1290), were critically examined. The research article based on the study revisited the four behavioural dimensions of CRM. A total of 225 respondents were conveniently contacted from banks and hotel establishments. In view of the challenges faced by the business organizations in the contemporary scenario, in particular in the service sector, this article identified and discusses ‘customer prospecting’ and ‘personalization’ as additional practices/dimensions that need to be incorporated to design a robust CRM framework which has been presented as revisited model. Structural equation modeling (SEM) had been used to validate the revisited model. These dimensions, though need to be ratified in the future research.

Suggested Citation

  • Maraj Rahman Sofi & Iqbal Ahmad Hakim, 2018. "Customer Relationship Management as Tool to Enhance Competitive Effectiveness: Model Revisited," FIIB Business Review, , vol. 7(3), pages 201-215, September.
    • Handle: RePEc:sae:fbbsrw:v:7:y:2018:i:3:p:201-215
    DOI: 10.1177/2319714518798410
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    References listed on IDEAS

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    3. Giridhari Mohanta, 2024. "Small Savings Scheme of the Post Office and Savings Habit of People: The Role of Financial Consultant," Business Perspectives and Research, , vol. 12(1), pages 65-82, January.
    4. Md Shamim Hossain & Mst Farjana Rahman, 2023. "Customer Sentiment Analysis and Prediction of Insurance Products’ Reviews Using Machine Learning Approaches," FIIB Business Review, , vol. 12(4), pages 386-402, December.

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