Centrality Index Revealing the Central and Hidden Places in Mazowieckie Voivodeship
DOI:
https://doi.org/10.15678/krem.18713Keywords:
centrality index, central place theory, cities, Mazovia, PolandAbstract
Objective: This article aims to calculate a centrality index for Mazowieckie voivodeship using an empirical application of Christaller’s central place theory.
Research Design & Methods: We calculate the value of a centrality index for 89 cities in Mazowieckie voivodeship using data for 32 central activities (independent variables). The proposed centrality index (synthetic indicator based on a non-model method) can be used to identify cities that are important for regional development. The population-adjusted centrality index shows which cities overperform, or underperform, compared to their size; the scores are useful for the identification of the hidden centres of urban activity.
Findings: The analysis identifies three types of cities that are of interest in light of the central place theory: 16 central places (centrality index ≥ 3), 27 hidden places (population-adjusted centrality index ≥ 2), and three hidden central places (classified as both central places and hidden places). The regional supremacy of Warsaw is visible in its perfect centrality index score; other central places include Radom and Płock. On the other hand, hidden places are exemplified by Lipsko, Przysucha, and Podkowa Leśna. Wołomin, Grodzisk Mazowiecki, and Wyszków are classified as the three hidden central places of the Mazowieckie voivodeship.
Implications / Recommendations: Hidden central places can be crucial for the future growth of the region. The dominant role of Warsaw is not going to be challenged, but, with sufficient support, the hidden central places could disperse geographically some of the essential functions in a more sustainable, inclusive, and accessible way.
Contribution: The research contributes to the understanding of the regional development of Mazovia and the practical applications of the central place theory. The devised method can be used in the analysis of different regions.
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