Scenario modelling and forecasting of spatial transformation in the Russian catering market

Abstract

The COVID-19 pandemic and spatial peculiarities exacerbate the imbalance in the development of the catering market in Russia. The paper reveals the problems of spatial transformation of the market in Russian regions. Analysis of the theoretical foundations of the research showed that the existing methodological approaches neglect the spatial aspect of this transformation. Methodologically, the study relies on theoretical provisions of regional and spatial economics, including Perroux's growth pole theory, Christaller's central place theory, and Friedmann's core-periphery model. Using the methods of spatial autocorrelation analysis, regression modelling and ARIMA-forecasting, the authors develop a system-based approach to modelling and forecasting the processes of spatial transformation of the public catering market. The research specifies the main methods for forecasting the development indicators of the market, as well as their advantages and disadvantages;it also substantiates the need to apply spatial autocorrelation analysis for assessing the distinguishing features of the market transformation and proposes a methodology for its implementation. The authors established a downward trend in the catering market differentiation and an upward trend in the number of regions similar in terms of their development. Regression analysis helped identify the major factors affecting the catering market's turnover, such as GRP and average per capita income of the population. ARIMA-modelling of these factors' dynamics allowed designing forecast scenarios for the development of the Russian catering market until 2022. Based on the research results, the study outlines the development prospects of the Russian catering market in the context of a worsening epidemiological situation.