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Evolution of customer relationship management to data mining-based customer relationship management: a scientometric analysis

Author

Listed:
  • Minnu F. Pynadath

    (Rajagiri Business School Kakkanad
    Rajagiri College of Social Sciences (Autonomous))

  • T. M. Rofin

    (National Institute of Industrial Engineering (NITIE))

  • Sam Thomas

    (Cochin University of Science and Technology)

Abstract

Scores of researchers have paid attention to empirical and conceptual dimensions of Customer relationship management (CRM). A few studies summarise the research output of CRM focusing on a specific industry. Nevertheless, there is scant literature summarising the research output of CRM in contrast to the data mining-based CRM. This study presents a scientometric analysis that evaluates CRM research output with a special focus on data mining-based CRM. Bibliometric data were extracted for the period 2000–2020 from the Web of Science database to apply descriptive analysis and scientometric analysis to obtain the bibliometric profile of CRM research. Further, we generated the conceptual structure map using multiple correspondence analysis and clustering for CRM and data mining-based CRM research fields. Interestingly, the analysis revealed that the future trendfi of CRM research would be based on techniques associated with machine learning and artificial intelligence. The study provides extensive insight into the basic structure of the CRM and data mining-based CRM research domain and identifies future research areas.

Suggested Citation

  • Minnu F. Pynadath & T. M. Rofin & Sam Thomas, 2023. "Evolution of customer relationship management to data mining-based customer relationship management: a scientometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3241-3272, August.
    • Handle: RePEc:spr:qualqt:v:57:y:2023:i:4:d:10.1007_s11135-022-01500-y
    DOI: 10.1007/s11135-022-01500-y
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    References listed on IDEAS

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    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Mas-Tur, Alicia & Roig-Tierno, Norat & Sarin, Shikhar & Haon, Christophe & Sego, Trina & Belkhouja, Mustapha & Porter, Alan & Merigó, José M., 2021. "Co-citation, bibliographic coupling and leading authors, institutions and countries in the 50 years of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    3. Yeganeh Charband & Nima Jafari Navimipour, 2016. "Online knowledge sharing mechanisms: a systematic review of the state of the art literature and recommendations for future research," Information Systems Frontiers, Springer, vol. 18(6), pages 1131-1151, December.
    4. Narendra Singh & Pushpa Singh & Krishna Kant Singh & Akansha Singh, 2020. "Machine learning based classification and segmentation techniques for CRM: a customer analytics," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 6(2), pages 99-117.
    5. Corrado Cuccurullo & Massimo Aria & Fabrizia Sarto, 2016. "Foundations and trends in performance management. A twenty-five years bibliometric analysis in business and public administration domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 595-611, August.
    6. Chatterjee, Swagato & Goyal, Divesh & Prakash, Atul & Sharma, Jiwan, 2021. "Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application," Journal of Business Research, Elsevier, vol. 131(C), pages 815-825.
    7. Martínez, Andrés & Schmuck, Claudia & Pereverzyev, Sergiy & Pirker, Clemens & Haltmeier, Markus, 2020. "A machine learning framework for customer purchase prediction in the non-contractual setting," European Journal of Operational Research, Elsevier, vol. 281(3), pages 588-596.
    8. Ismael Rafols & Alan L. Porter & Loet Leydesdorff, 2010. "Science overlay maps: A new tool for research policy and library management," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(9), pages 1871-1887, September.
    9. Hualin Xie & Yanwei Zhang & Zhilong Wu & Tiangui Lv, 2020. "A Bibliometric Analysis on Land Degradation: Current Status, Development, and Future Directions," Land, MDPI, vol. 9(1), pages 1-37, January.
    10. Carolin Michels & Ulrich Schmoch, 2012. "The growth of science and database coverage," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 831-846, December.
    11. Lessmann, Stefan & Voß, Stefan, 2009. "A reference model for customer-centric data mining with support vector machines," European Journal of Operational Research, Elsevier, vol. 199(2), pages 520-530, December.
    12. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    13. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    14. Yuqing Fang, 2015. "Visualizing the structure and the evolving of digital medicine: a scientometrics review," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 5-21, October.
    15. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W., 2018. "A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees," European Journal of Operational Research, Elsevier, vol. 269(2), pages 760-772.
    16. Hsiao, Chun Hua & Yang, Chyan, 2011. "The intellectual development of the technology acceptance model: A co-citation analysis," International Journal of Information Management, Elsevier, vol. 31(2), pages 128-136.
    17. Peder Olesen Larsen & Markus Ins, 2010. "The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 575-603, September.
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