Models for Creating Price Politics of a Company Entering the Market for Speech Analytics Technologies

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.

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Publication Details

Journal
Finance Theory and Practice
Published
2025-05-09
DOI
https://doi.org/10.26794/2587-5671-2025-29-2-59-70
Citations
4
Primary Topic
Security, Politics, and Digital Transformation
Type
article
Field-Weighted Citation Impact
34.09
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article

Models for Creating Price Politics of a Company Entering the Market for Speech Analytics Technologies

Tatyana Y. Salutina, M. F. Gumerov, Galina P. Platunina, A. R. Kaberova
4 citations
Finance Theory and Practice
Security, Politics, and Digital Transformation
34.09
article

Models for Creating Price Politics of a Company Entering the Market for Speech Analytics Technologies

Tatyana Y. Salutina, M. F. Gumerov, Galina P. Platunina, A. R. Kaberova
article en
4 citations

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.

Finance Theory and PracticeVol. 29(2)
Central Economics and Mathematics Institute (RU), Moscow Technical University of Communication and Informatics (RU), Mathematical Institute of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 1%
Security, Politics, and Digital Transformation
34.09
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