Models for Creating Price Politics of a Company Entering the Market for Speech Analytics Technologies
https://doi.org/10.26794/2587-5671-2025-29-2-59-70
Abstract
The article is devoted to adapting general mathematical models of the software markets for describing the market of the specific product. These are the technologies of artificial intelligence in speech analytics. The purpose of this study is to create a modeling instrumentation for pricing the technologies of speech analytics in companies which enter this market. The purpose also includes recommendations provided with the price politics. The object of the study is the Russian market of speech analytics technologies. The subject of the study are the prices of this product in companies which enter the market being explored. In this studying the authors use classical methods of economical and mathematical modeling the markets with different competitive levels (monopoly, duopoly, oligopoly, monopolistic competition). The results of the study are the foundations of prices for the companies which enter the speech analytics market. These prices are based on three kinds of economical mathematical models: regression, rating and marginal indicators. All three kinds of models lead to one recommendation. A company which enters the speech analytics market should establish the prices with Less orientation to the indictors of analytics’ quality. Because in all three models this factor has very weak influence on a result. More important factor are the additional options. Their bigger quantity allows a company to establish a price which is nearer to the same one of the market leaders.
Keywords
artificial intellect,
speech analytics technologies,
software market,
pricing,
level of monopolization
JEL: D49, E39
About the Authors
T. Yu. Salutina
Moscow Technical University of Communications and Informatics
Russian Federation
Russian Federation
Tatyana Yu. Salutina — Dr. Sci. (Econ.), Assoc. Prof., Head of Department of digital economy
Moscow
M. F. Gumerov
Central Economic and Mathematical Institute of the Russian Academy of Sciences
Russian Federation
Russian Federation
Marat F. Gumerov — Dr. Sci. (Econ.), Assoc. Prof., Leading Researcher, Laboratory of
Microeconomic Analysis and Modelling
Moscow
A. R. Kaberova
Moscow Technical University of Communications and Informatics
Russian Federation
Russian Federation
Asiya R. Kaberova — Cand. Sci. (Econ.), Assoc. Prof., Department of digital economy,
management and business technologies
Moscow
G. P. Platunina
Moscow Technical University of Communications and Informatics
Russian Federation
Russian Federation
Galina P. Platunina — Major Lecturer, Department of digital economy, management and business technologies
Moscow
References
1. Zeleneva E. S. Assessment of the characteristics, scopes and limits of the application of digital innovations in the financial sector. Finance: Theory and Practice. 2023;27(2):76-86. DOI: 10.26794/2587-5671-2023-27-2-76-86
2. Kumar A., Kumar A., Kumari S., et al. Artificial intelligence: The strategy of financial risk management. Finance: Theory and Practice. 2024;28(3):174-182. DOI: 10.26794/2587-5671-2024-28-3-174-182
3. Pokamestov I. E., Nikitin N. A. Modern artificial intelligence technologies as a tool of transformation of value chains of Russian commercial banks. Finance: Theory and Practice. 2024;28(4):122-135. DOI: 10.26794/2587-5671-2024-28-4-122-135
4. Kuzovkova T. A., Salutina T. Yu., Sharavova O. I. The impact of digital platforms on the business management information system. In: Systems of signal synchronization, generating and processing in telecommunications — SYNCHROINFO 2021. (Kaliningrad, June 30 — July 02, 2021). New York, NY: IEEE; 2021. DOI: 10.1109/SYNCHROINFO51390.2021.9488330
5. Kuzovkova T. A., Sharavova O. I., Tikhvinskiy V. O., Devyatkin E. E. Matching of 6G network capabilities to digital services requirements. In: Systems of signal synchronization, generating and processing in telecommunications — SYNCHROINFO 2022. (Arkhangelsk, June 29 — July 01, 2022). New York, NY: IEEE; 2022. DOI: 10.1109/SYNCHROINFO55067.2022.9840939
6. Ustyuzhanina E. V., Sigarev A. V., Komarova I. P., Novikova E. S. The impact of the digital revolution on the paradigm shift in the economic development. Espacios. 2017;38(62):12. URL: https://es.revistaespacios.com/a17v38n62/a17v38n62p12.pdf
7. Ustyuzhanina E., Evsukov S., Komarova I. Network economy as a new economic system. European Research Studies Journal. 2018;21(3):77-89. DOI: 10.35808/ersj/1045
8. Dementiev V. E., Evsukov S. G., Ustyuzhanina E. V. Reciprocity in emerging markets for network goods. Terra Economicus. 2019;17(4):23-40. (In Russ.). DOI: 10.23683/2073-6606-2019-17-4-23-40
9. Dementiev V. E., Evsukov S. G., Ustyuzhanina E. V. The importance of a strategic approach to pricing in markets for network goods. Zhurnal Novoi ekonomicheskoi assotsiatsii = Journal of the New Economic Association. 2020;(2):57-71. (In Russ.). DOI: 10.31737/2221-2264-2020-46-2-3
10. Dementiev V. E. The value chain facing the challenges of digitalization and the economic downturn. Voprosy ekonomiki. 2021;(3):68-83. (In Russ.). DOI: 10.32609/0042-8736-2021-3-68-83
11. Soloviev V. Mathematical modeling of the software market. Doct. econ. sci. diss. Moscow: Central Economics and Mathematics Institute of the Russian Academy of Sciences; 2010. 272 p. (In Russ.).
12. Soloviev V. Cloud IT-services efficiency under random demand. VestnikFinansovogo universiteta = Bulletin of the Financial University. 2013;(1):120-123. (In Russ.).
13. Ivanyuk V., Soloviev V. Neural network model for the multiple factor analysis of economic efficiency of an enterprise. In: Rutkowski L., Scherer R., Korytkowski M., et al., eds. Artificial intelligence and soft computing (ICAISC 2021). Cham: Springer-Verlag; 2021:278-289. (Lecture Notes in Computer Science. Vol. 12855). DOI: 10.1007/978-3-030-87897-9_26
14. Antipina O., Inozemtsev V. The dialectics of value in post-industrial society. Mirovaya ekonomika i mezhdunarodnye otnosheniya = World Economy and International Relations. 1998;(5):48-59. (In Russ.). DOI: 10.20542/0131-2227-1998-5-48-59
15. Antipina O. N. Pricing in the information economics. Doct. econ. sci. diss. Moscow: Lomonosov Moscow State University; 2009. 340 p. (In Russ.).
16. Antipina O. How much is the digit? On the nature of value in the digital economy. Obshchestvennye nauki i sovremennost’ = Social Sciences and Contemporary World. 2019;(5):5-16. (In Russ.). DOI: 10.31857/S086904990006558-5
17. Antipina O. N. Platforms as multi-sided markets of the digital age. Mirovaya ekonomika i mezhdunarodnye otnosheniya = World Economy and International Relations. 2020;64(3):12-19. (In Russ.). DOI: 10.20542/0131-2227-2020-64-3-12-19
Review
For citations:
Salutina T.Yu., Gumerov M.F., Kaberova A.R., Platunina G.P. Models for Creating Price Politics of a Company Entering the Market for Speech Analytics Technologies. Finance: Theory and Practice. 2025;29(2):59-70. https://doi.org/10.26794/2587-5671-2025-29-2-59-70
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