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Analyzing regional connectivity through population mobility data from cellular operators

Author

Listed:
  • Alexander V. Martynenko

    (Institute of Economics, Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia;)

  • Yuliya G. Myslyakova

    (Institute of Economics, Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia;)

  • Natalia A. Matushkina

    (Institute of Economics, Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia;)

  • Natalia N. Neklyudova

    (Institute of Economics, Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia;)

Abstract

Relevance. In the current economic climate, maintaining the integrity of regional economic space is crucial. This involves ensuring uniform socio-economic development across regions and promoting a high rate of technology transfer from the center to the periphery. Therefore, it is essential to identify sustainable points of spatial development that represent centers of power concentration and guide spatial transformation. Research objectives.The study aims to assess the connectivity of the region’s economic space by measuring population mobility. This approach will help identify the centers of social and labor communications that represent sustainable points of spatial development. The focus of the study is on the municipal districts of Sverdlovsk region, which are key elements of its economic space. Data and methods. The study employed geoinformation analysis of origin-destination matrix of population flows in Sverdlovsk region (Russian Federation), provided by Russian mobile operators. Results. The paper presents the analysis of intracity and intercity population flows based on the average daily data of mobile operators for 2022. The intensity and diversification of population flows in the region’s municipal districts, reflecting the connectivity of its economic space, were estimated using geographic information systems and the Python programming language. The study revealed that Sverdlovsk region has a bicentric system of spatial interconnections, with two distinct centers of attraction: Ekaterinburg and Nizhny Tagil, with Ekaterinburg being the dominant center. Conclusions. The proposed classification of municipal districts by the level of their inclusion into the economic space of Sverdlovsk region illustrates that only 5% are characterized by intensive and diversified inter-territorial interaction, while 34% are characterized by low indicators of intensity and diversification of mobile population flows. The spatial structure of the municipalities in Sverdlovsk region, which are located in the zone of attraction to the agglomeration centers, will be maintained and reinforced.

Suggested Citation

  • Alexander V. Martynenko & Yuliya G. Myslyakova & Natalia A. Matushkina & Natalia N. Neklyudova, 2024. "Analyzing regional connectivity through population mobility data from cellular operators," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 10(2), pages 159-173.
    • Handle: RePEc:aiy:journl:v:10:y:2024:i:2:p:159-173
    DOI: https://doi.org/10.15826/recon.2024.10.2.010
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    More about this item

    Keywords

    population mobility; economic relations of territories; inter-municipal communications; localisation of cellular network users; zones of attraction; geoinformation analysis;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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