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Assessing Municipal Performance in Serbia: A TOPSIS-Based Analysis of Economic Vitality and Public Safety Dynamics
This study applies the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method combined with entropy-based weighting to systematically rank Serbian municipalities regarding economic vitality, infrastructure quality, and socio-economic stability. By developing a composite municipal performance index, the research explores the extent to which stronger economic standings relate to public safety outcomes. Infrastructure factors—including road conditions, housing quality, and water supply—are assessed through correlation and t-tests to evaluate their influence on municipal economic rankings. An ordinary least squares (OLS) regression model also examines how education and health expenditures per capita contribute to broader socio-economic resilience. The findings reveal a moderately strong, though nonlinear, negative relationship between economic performance and crime rates, with road infrastructure emerging as a consistently significant driver of economic strength. Investments in education and health initially correlate with greater municipal stability but show signs of diminishing marginal impact over time. These insights contribute to understanding the complex interplay between governance, infrastructure, and safety in transitional economies, highlighting the value of integrated data-driven approaches for regional development planning.
Assessing Renewable Energy Development Potential in Polish Voivodeships: A Comparative Regional Analysis
This work evaluates the renewable energy development potential of Polish voivodeships based on the TOPSIS method and spatial autocorrelation analysis. Data were obtained from the Polish Local Data Bank, covering 22 indicators in the field of economic, social, environmental, and energy related to renewable energy initiatives. The TOPSIS method was applied to construct a synthetic indicator for each voivodeship, facilitating a hierarchical ranking based on their proximity to an ideal solution representing optimal conditions. The results indicate that the Mazowiecki voivodeship leads the list in terms of renewable energy development potential, followed by Małopolskie i Pomorskie, and that this is mainly due to good economic conditions and large investments in renewable energy projects. Spatial autocorrelation analysis yielded a Moran’s I value of –0.1137 with a Z score of 0.303 and a p value of 0.752, suggesting a weak negative spatial autocorrelation that is not statistically significant. This implies that the distribution of renewable energy potential across voivodeships is largely random and is not influenced by spatial proximity. The study concludes that non-spatial factors play a more significant role in renewable energy development potential, offering valuable insights for policymakers and stakeholders to allow them to focus on economic and social variables when promoting renewable energy initiatives in Poland.