ISSN 2409-7616

Shilovich O.B., Gulyai V.G., Markov A.I., Shapovalov D.A.


UDC 338.2:004.93’1


Shilovich O.B.1 (Krasnodar, Russian Federation) –, Gulyai V.G.1 (Krasnodar, Russian Federation) –, Markov A.I.1 (Krasnodar, Russian Federation) –, Shapovalov D.A.1 (Krasnodar, Russian Federation) –

1Kuban State Technological University

Abstract. Improving the quality of service with the help of information technology is becoming increasingly popular in various service industries. The well-being of the population is one of the most important tasks of the economy. This article discusses the service sector as one of the three components of the economy that directly affects the welfare of the population. In order to improve the quality of services provided, research was conducted to identify the most developed sectors of the service market and the dynamics of the development of the service sector both in our country and around the world. So it was revealed that the best service market is developed in European countries; in our country, there is an increase in the provision of services, while the most developed area is the construction and improvement of real estate. To improve the quality of service, it is necessary that customers be assisted in choosing a service, as well as support is provided during its implementation. The article proposes a new method of quality control by automating and intellectualizing the system for evaluating the work of managers and call centers. For this, it is proposed to create an assessment system based on artificial intelligence algorithms. In this case, it is proposed to introduce natural language processing mechanisms into the system for evaluating the work of managers, in particular, algorithms for recognizing, processing and generating text in oral and written format. This system is necessary for assessing the quality of goods by consumers, improving the quality of manufactured goods to improve the well-being of the population. The research material has theoretical and practical value for those involved in solving the issues of this problem.

Keywords: service industry, natural language processing, artificial intelligence.


  1. Kanner D.D. An effective corporate governance system at a service sector enterprise (on the example of the event management sphere). Innovations. The science. Education, 2021, no. 36, pp. 1986-1993. (In Russian). URL:
  2. Dashin A.A., Izmailov A.A., Delyaev A.Yu. Internet traffic and QOS. Student Bulletin, 2021, no. 21-8(166), pp. 42-45. (In Russian). URL:
  3. Tatuev A.A., Pochinok N.B. Service sector: Coming system challenges. Social policy and sociology, 2021, no. 1(138), pp. 22-34. (In Russian). URL:
  4. Sergeeva N.M. Variety of information technologies introduced into the education system. Baltic Humanitarian Journal, 2021, vol. 10, no. 2 (35), pp. 153-157. (In Russian). URL:
  5. Shchepakin M.B., Mikhailova V.M. Service sector as an economic category and type of economic activity. Economics Entrepreneurship and Law, 2020, vol. 10, no. 1. pp. 71-88. (In Russian). URL:
  6. Vyalykh V.V., Ryzhkov V.V. Artificial intelligence: Problems and solutions. Student and science, 2022, no. 1(20), pp. 46-49. (In Russian). URL:
  7. Chastikova V.A. Application of natural language processing methods for solving problems of detecting social engineering attacks. Krasnodar, South Publ., 2022. pp. 261-264. (In Russian).
  8. Zolushkin Yu.A. Natural language processing. Donetsk, Donetsk National Technical University Publ., 2021. pp. 71-78. (In Russian).
  9. Tursunov M.B., Gromenko O.A. Increasing the competitiveness of an organization in the field of customs services based on a client-oriented approach. International Journal of Applied Sciences and Technologies Integral, 2021, no. 4. (In Russian). URL:
  10. Mokaeva A.K., Totorkulova A.I. Artificial intelligence in business processes. Science sphere, 2021, no.  5-2, pp. 198-202. (In Russian). URL:
  11. Darovsky D.V. Artificial and natural intelligence: challenges and ethics. Bulletin of the Dubna State University. Series: Sciences of Man and Society, 2021, no. 2, pp. 21-33. (In Russian). URL:
  12. Aleshina I.V. Artificial intelligence: digital globalization and marketing / I. V. Aleshina. Marketing in Russia and abroad, 2019, no. 1, pp. 74-80. (In Russian). URL:
  13. Chastikova V.A., Gulyai V G. Methodology for detecting social engineering attacks based on natural language analysis algorithms. Caspian Journal: Management and High Technologies, 2022, no. 3(59), pp. 61-71. (In Russian). URL:
  14. Zharkov M.S. Development of a system for classifying subscribers’ calls to the call center of Orion Telecom Group. Omsk, Omsk State Technical University Publ.,  2022. pp. 152-158. (In Russian).
  15. Azarov A.A., Davydova M.A. Digital infrastructures of the network space of the leading Russian universities in the field of social sciences & management. Power, 2021, vol. 29, no. 5, pp. 31-36. (In Russian). URL:

For citation: Shilovich O.B., Gulyai V.G., Markov A.I., Shapovalov D.A. Improving the quality of service in the service sector with the help of information technologies. CITISE, 2023, no. 1, pp. 202-213. DOI: