Research output: Contribution to journal › Article › peer-review
Price strategies of mobile operators in Russia in the conditions of the global economic recession. / Dengov, Victor; Tulyakova, Irina; Gregova, Elena; Sviridov, Gleb.
In: Oeconomia Copernicana, Vol. 11, No. 2, 06.2020, p. 347-370.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Price strategies of mobile operators in Russia in the conditions of the global economic recession
AU - Dengov, Victor
AU - Tulyakova, Irina
AU - Gregova, Elena
AU - Sviridov, Gleb
N1 - Publisher Copyright: © 2020 Nicolaus Copernicus University. All rights reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/6
Y1 - 2020/6
N2 - Research background: Currently, the four major mobile communications providers dominate the Russian market. The oligopolistic structure leads to negative consequences, such as a weak stimulus for the product development or technological innovation, and the lack of incentive for the callrate reduction. In their line of work, the mobile service providers use different price strategies. To comprehend what determines the current price level and what changes one should expect therein, we have to understand which factors influence the price of the mobile services. Purpose of the article: The chief goal of this work is the analysis of the influence of the crisis on the price strategies of the providers, as well as the forecasting of the changes of prices for their services. As the main hypothesis, this work presents the assumption that during the recession the price of the mobile services in the different regions of Russia will grow. Methods: The authors built regression models for the dependence of the average price of the mobile providers' services in a particular region from the selected factors. In this work, we selected the following types of the multiple regression equation as the modeling functions: linear, power-law, exponential. Adding the time factor (t) is the key element of the forecasting. Findings & Value added: After gathering the data and the subsequent calculation of the medium price baskets, we were able to build different multiple regression models. To build the forecasts for the dynamics of prices in the regions for the year 2018 we selected the best regression models. The analysis of the acquired forecasting results generally proved our hypothesis about the growth of the average prices for the mobile communications services, expected in 2018 in the majority of regions. The analysis itself, the programs created for its implementation, as well as the results obtained, can, in our opinion, be considered as some contribution to the development of the theory of price competition in oligopolistic markets. The mobile services' markets in many EU countries have a similar structure, and, with this in mind, the results of forecasting price dynamics obtained from Russian experience may be of interest to scholars dealing with similar problems in their respective countries, including the possibility of conducting comparative studies.
AB - Research background: Currently, the four major mobile communications providers dominate the Russian market. The oligopolistic structure leads to negative consequences, such as a weak stimulus for the product development or technological innovation, and the lack of incentive for the callrate reduction. In their line of work, the mobile service providers use different price strategies. To comprehend what determines the current price level and what changes one should expect therein, we have to understand which factors influence the price of the mobile services. Purpose of the article: The chief goal of this work is the analysis of the influence of the crisis on the price strategies of the providers, as well as the forecasting of the changes of prices for their services. As the main hypothesis, this work presents the assumption that during the recession the price of the mobile services in the different regions of Russia will grow. Methods: The authors built regression models for the dependence of the average price of the mobile providers' services in a particular region from the selected factors. In this work, we selected the following types of the multiple regression equation as the modeling functions: linear, power-law, exponential. Adding the time factor (t) is the key element of the forecasting. Findings & Value added: After gathering the data and the subsequent calculation of the medium price baskets, we were able to build different multiple regression models. To build the forecasts for the dynamics of prices in the regions for the year 2018 we selected the best regression models. The analysis of the acquired forecasting results generally proved our hypothesis about the growth of the average prices for the mobile communications services, expected in 2018 in the majority of regions. The analysis itself, the programs created for its implementation, as well as the results obtained, can, in our opinion, be considered as some contribution to the development of the theory of price competition in oligopolistic markets. The mobile services' markets in many EU countries have a similar structure, and, with this in mind, the results of forecasting price dynamics obtained from Russian experience may be of interest to scholars dealing with similar problems in their respective countries, including the possibility of conducting comparative studies.
KW - Price elasticity
KW - Pricing strategies
KW - Protracted recession
KW - Telecommunications market
UR - http://www.scopus.com/inward/record.url?scp=85090654505&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/8b181b10-63bc-3350-9cfe-37637574ef14/
U2 - 10.24136/oc.2020.015
DO - 10.24136/oc.2020.015
M3 - Article
VL - 11
SP - 347
EP - 370
JO - Oeconomia Copernicana
JF - Oeconomia Copernicana
SN - 2083-1277
IS - 2
ER -
ID: 60618486