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The Analysis of Commuting Migrations within the Urban Agglomeration: Sociological Surveys and Big Data

https://doi.org/10.25205/2542-0429-2021-21-4-205-228

Abstract

The article presents the results of a study of commuting migrations of the Novosibirsk urban agglomeration residents. The research information base includes big data (on the trajectories of population movements using geoinformation systems, on the localization of activity in mobile networks, on car traffic) and data from a mass survey of Novosibirsk region residents, conducted in July 2019 (the method of collecting information is a structured telephone interview). The general trends in the development of urban agglomeration, the boundaries and structure of the agglomeration area in the first approximation have been determined, using aggregated and visualized big data. Mass survey data analysis allowed assess the commuting migration according to the following parameters: regularity, frequency, goals, duration of trips, type of transport used, and direction. The article describes the characteristics differentiation of commuting movements taking assessments of socio-economic conditions into account.

About the Authors

P. A. Dyachkova
Novosibirsk State University; National Research University “Higher School of Economics”
Russian Federation

Polina A. Dyachkova, Bachelor of Sociology; Master of Applied Mathematics and Informatics

Novosibirsk

St. Petersburg



N. L. Mosienko
Novosibirsk State University; Institute of Economics and Industrial Engineering of the Siberian Branch of the Russian Academy of Sciences
Russian Federation

Natalya L. Mosienko, Candidate of Sciences (Sociology), Senior Researcher; Associate Professor

SPIN 5641-4168, Scopus Author ID 56502117900

Novosibirsk



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Review

For citations:


Dyachkova P.A., Mosienko N.L. The Analysis of Commuting Migrations within the Urban Agglomeration: Sociological Surveys and Big Data. World of Economics and Management. 2021;21(4):205-228. (In Russ.) https://doi.org/10.25205/2542-0429-2021-21-4-205-228

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ISSN 2542-0429 (Print)
ISSN 2658-5375 (Online)