10.25673/119246">
Proceedings of International Conference on Applied Innovation in IT  ·  2025/04/26  ·  Vol. 13  ·  Issue 1  ·  pp. 295–303
Impact of Artificial Intelligence on Customer Relationship Management: a Bibliometric Analysis
Aleksy Kwilinski, Nataliia Trushkina, Yuliia Remyha and Tamila Patlachuk
📄 Download PDF DOI: <a href="http://dx.doi.org/10.25673/119246">10.25673/119246</a>
Abstract
In modern conditions, the strategic task of logistics management of companies is to form an appropriate customer relationship management system that is able to quickly respond to crisis situations, risks, threats, transformation of the business environment, as well as flexibly adapt to unstable demand and constant changes in customer needs and preferences. In this regard, it is advisable to introduce qualitatively new management and customer-oriented approaches, smart technologies, customer experience management methods, digital marketing tools, and digital innovations. At the same time, in recent years, the use of artificial intelligence as the most influential digital innovation in customer relationship management has played a significant role. Therefore, the purpose of this article is to identify the relationship between artificial intelligence and customer relationship management by characterizing the evolution of key patterns of scientific publications on this problem. To achieve the goal, a relevant sample of scientific articles was formed based on identifying periods of publication activity and bibliometric analysis of keyword coincidences to identify promising areas of research in this area. The formed sample of publications for the study includes 797 documents indexed by the database Scopus for the period 2001-2024. Bibliometric analysis and visualization of its results were carried out using the VOSviewer software product. Based on visualization maps, seven clusters were identified and characterized by the content coincidence of keywords in publications and five stages of evolutionary development of the customer relationship management system using artificial intelligence. Based on the analysis of empirical data, an exponential growth in the number of publications on the selected issues was confirmed (the annual increase in the number of scientific papers on this topic is 15.3%). The results of the analysis can be used in further research to substantiate and develop a strategy for the digital transformation of the customer relationship management system.
Keywords
Artificial Intelligence Customer Relationship Management Logistics Service Customer Experience Loyalty Customer Orientation Digital Transformation Information Environment Digital Marketing Digital Technology Digital Innovation Bibliometric Analysis.
References
  1. A. Kwilinski et al., “Managing the Logistic Activities of Agricultural Enterprises under Conditions of Digital Economy”, Virtual Econ., vol. 5(2), pp. 43-70, 2022. https://doi.org/10.34021/ ve.2022.05.02(3).
  2. Y. Remyha et al., “Energy-saving technologies for sustainable development of the maritime transport logistics market”, IOP Conf. Series: Earth and Environmental Science, vol. 1126, 012037, 2023. https://doi.org/10.1088/1755-1315/1126/1/012037.
  3. A. Kwilinski et al., “Organizational and Economic Mechanism of the Customer Relationship Management under the Era of Digital Transformations”, E3S Web of Conf., vol. 456, 05002, 2023. https://doi.org/10.1051/e3sconf/ 202345605002.
  4. The Zendesk Customer Experience Trends Report 2020. Zendesk, 2020. https://www.zendesk.com/ blog/zendesk-customer-experience-trends-report-2020/.
  5. C. Scott, “Top Customer Experience Trends You Should Watch in 2025”, CMSWire, Dec. 4, 2024. https://www.cmswire.com/customer-experience/top-customer-experience-trends-you-should-watch.
  6. K. Costello, “Gartner Says the Future of Self-Service Is Customer-Led Automation”, Gartner, May 28, 2019. https://www.gartner.com/en/newsroom/press-releases/2019-05-28-gartner-says-the-future-of-self-service-is-customer-l#targetText.
  7. Global Data from IBM Shows Steady AI Adoption as Organizations Look to Address Skills Shortages, Automate Processes and Encourage Sustainable Operations. IBM Corporation, May 19, 2022. https://newsroom.ibm.com/2022-05-19-Global-Data-from-IBM-Shows-Steady-AI-Adoption-as-Organizations-Look-to-Address-Skills-Shortages,-Automate-Processes-and-Encourage-Sustainable-Operations.
  8. Market value of artificial intelligence (AI) in marketing worldwide from 2020 to 2028 (in billion U.S. dollars). Statista, Dec. 10, 2024. https://www.statista.com/statistics/1293758/ai-marketing-revenue-worldwide/.
  9. AI adoption for customer experience uses in 2024. Statista, Dec. 10, 2024. https://www.statista.com/ statistics/1490150/ai-customer-experience-adoption/.
  10. AI Statistics 2024. AIPRM. https://www.aiprm.com/ ai-statistics/.
  11. Main challenges encountered in implementing AI for customer experience uses in 2024. Statista, Sep. 3, 2024. https://www.statista.com/statistics/1490167/ai-implementation-customer-experience-challenges/.
  12. R. Abduljabbar et al., "Applications of artificial intelligence in transport: An overview”, Sustainability (Switzerland), vol. 11, iss. 12, 189, 2019. https://doi.org/10.3390/su11010189.
  13. P. B. Acharjee et al., “Artificial Intelligence (AI) in CRM (Customer Relationship Management): A Sentiment Analysis Approach”, Proc. of the 2nd IEEE International Conf. on Trends in Quantum Computing and Emerging Business Technologies (TQCEBT 2024), 10545168, 2024. https://doi.org/ 10.1109/TQCEBT59414.2024.10545168.
  14. S. Chatterjee et al., “Assessing Organizational Users’ Intentions and Behavior to AI Integrated CRM Systems: a Meta-UTAUT Approach”, Information Systems Frontiers, vol. 25, iss. 4, pp. 1299-1313, 2023. https://doi.org/10.1007/s10796-021-10181-1.
  15. S. Chatterjee and R. Chaudhuri, “Customer Relationship Management in the Digital Era of Artificial Intelligence”, In: EAI/Springer Innovations in Communication and Computing. Berlin: Springer Science and Business Media Deutschland GmbH, pp. 175-190, 2023. https://doi.org/10.1007/978-3-031-19711-6_8.
  16. Y. Fu, G. Guo, and T. S. Huang, “Age synthesis and estimation via faces: A survey”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, iss. 11, pp. 1955-1976, 2010. https://doi.org/10.1109/TPAMI.2010.36.
  17. K. Krishnareddy et al., “AI-based Fuzzy Clustering System for Improving Customer Relationship Management”, Proc. of the 6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud, I-SMAC 2022), pp. 673-677, 2022. https://doi.org/10.1109/I-SMAC55078.2022. 9987262.
  18. V. Kumar et al., “Understanding the role of artificial intelligence in personalized engagement marketing”, California Management Review, vol. 61, iss. 4, pp. 135-155, 2019. https://doi.org/10.1177/ 0008125619859317.
  19. D. Ozay et al., “Artificial Intelligence (AI)-based Customer Relationship Management (CRM): a comprehensive bibliometric and systematic literature review with outlook on future research”, Enterprise Information Systems, vol. 18, iss. 7, 2351869, 2024. https://doi.org/10.1080/17517575.2024.2351869.
  20. A. Kwilinski, “The Relationship between Sustainable Development and Digital Transformation: Bibliometric Analysis”, Virtual Econ., vol. 6(3), pp. 56-69, 2023. https://doi.org/10.34021/ve.2023. 06.03(4).
  21. V. Khaustova, M. Kyzym et al., “Digital transformation of energy infrastructure in the conditions of global changes: bibliometric analysis”, Proc. of the 12th Int. Conf. on Applied Innovations in IT. Koethen: Anhalt University of Applied Sciences, vol. 12, iss. 1, pp. 135-142, 2024. http://dx.doi.org/ 10.25673/115664.

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