Integration of Service Technologies in Real Estate Management: The Impact of Artificial Intelligence and Digital Platforms on Customer Service Perception
The relevance of the study lies in the need to adapt real estate service models to rapid digitalization and the increasing expectations of clients for personalized and technologically advanced service. The problem addressed is the imbalance between technological sophistication and the subjective perception of service quality by clients amid the widespread implementation of AI-driven and digital platforms. The purpose of the study is to identify how modern service technologies – artificial intelligence, digital platforms, and IoT solutions – affect customer experience quality in real estate organizations, and to define directions for developing hybrid models that integrate automation with human interaction. The methodological framework incorporated systematic and comparative analysis, content analysis, and expert assessment methods, as well as elements of behavioural and digital economics. The empirical base includes both Russian and international examples of AI and digital platform implementation in real estate management and brokerage services. The study identifies key parameters of contemporary customer experience – speed, transparency, personalization, and trust in digital tools. It also highlights the risks of losing the emotional dimension of service and the decline in trust toward automated systems. The findings demonstrate that while AI and digital platforms improve operational efficiency, overall client satisfaction depends significantly on maintaining a human-centered approach. The research concludes that hybrid service models combining digital tools with empathetic communication are essential for sustainable development. Recommendations include developing ethical standards for data use, ensuring algorithmic transparency, and improving digital literacy among real estate professionals.
Kalininskaya, M. A. Sergeeva, E. A. (2025), “Integration of Service Technologies in Real Estate Management: The Impact of Artificial Intelligence and Digital Platforms on Customer Service Perception”, Research Result. Business and Service Technologies, 11 (4), pp.
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Berry, L., Parasuraman, A. and Zeithaml, V. (1985), A Conceptual Model of Service Quality and Its Implications for Future Research, New York, Marketing Science Institute, 68 p.
Berry, L., Parasuraman, A. and Zeithaml, V., (1988), “SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality”, Retail, 64 (1), pp. 12-40 [Online], available at: https://scholar.google.com/citations?view_op=view_citation&hl=ru&user=7fQX_pYAAAAJ&citation_for_view=7fQX_pYAAAAJ:u5HHmVD_uO8C (Accessed 20.09.2025).
Cheterbok, P., Oleinikov, N., Mayorova, A., Gorobets, D.V., Ponomareva, E.Yu. and Sergeeva E. (2023), “Computational intelligence for the Internet of things”, E3S WEB OF CONFERENCES, International Scientific Conference Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East (AFE-2022), Т. 371 [Online], available at: https://www.elibrary.ru/item.asp?id=50395490 (Аccessed 19.09.2025).
Elnagar, S. (2024), “Using Deep Learning to Improve the Quality of Services: Applications on Real Estate Agency Websites”, Cornell University, [Online], available at: https://arxiv.org/abs/2408.06364 (Аccessed 21.09.2025) (in Russ.).
Gludkin, O. P. (2020), Servicology: theory and practice of service activity, textbook, M., KnoRus, 312 p. (in Russ).
Grebenshchikova, E. V. (2019), Digital economy: institutional and social foundations, monograph, SPb, St. Petersburg State University Publishing House, 286 p. (in Russ).
Jobin, A., Ienca, M. and Vayena, E. (2019), “Artificial Intelligence: The Global Landscape of Ethics Guidelines”, Nature Machine Intelligence, Vol. 1, 9, pp. 389-399.
Kotler, F., Bowen, D. and Makens, J. (2021), Marketing. Hospitality. Tourism, Textbook, M., Unity-Dana, 816 p. (in Russ).
Poretschkin, M. and Schmitz, A. (2023), Guideline for Trustworthy Artificial Intelligence, AI Assessment Catalog, arXiv preprint, 47 p. [Online], available at: https://arxiv.org/abs/2307.03681 (Accessed 20.09.2025)
2023), Ethics and Responsible AI Deployment, XIV preprint, 36 p. [Online], available at: https://arxiv.org/abs/2311.14705 (Accessed 20.09.2025)
Rykunova, Yu. (2023), “AI for a Realtor”, Polpred. [Online], available at: https://polpred.com/?ns=1&ns_id=4770370 (Accessed 20.09.2025) (in Russ).
Stazhkov, M. (2013), “Research "Using the Customer Satisfaction Index on the Example of Office Rental Services”, Poznan University of Economics and Business. [Online], available at: https://www.researchgate.net/publication/264232056_Use_of_Customer_Satisfaction_Index_on_the_example_of_office_rental_services (Accessed 21.09.2025) (in Russ).
Tanashkina, I. G., Tanashkin, A. S., Maksimchuk, A. S. and Poshivailo A. Yu. (2025), “Modern approaches to building interpretable real estate market models using machine learning based on mass cadastral valuation”, Pacific Quantum Center of the Far Eastern Federal University. Center for Cadastral Valuation in Primorsky Krai. [Online], available at: https://arxiv.org/abs/2506.15723 (Accessed 21.09.2025) (in Russ).