Regional Resilience through a Multidimensional Lens: Exploring Romanian Counties

Abstract

This paper introduces an adaptable framework to facilitate comprehensive multidimensional analyses to assess regional resilience. The application of this framework is used for a case study in conceiving and synthesizing a suite of indicators tailored for Romanian counties' resilience assessment. These indicators are categorized into four distinct dimensions: "Socio-Economic Dynamics", "Urban Infrastructure and Green Areas", "Governance and Industry", and "Material and Energy Flows". Employing Principal Component Analysis (PCA), this study strategically condenses the dataset, emphasizes inter-variable relationships, and extracts valuable insights, thereby enabling an unbiased assignment of weights. The classification leverages discriminant variables to forge composite indicators for each dimension, creating an overall score and comparative counties' rankings. Additionally, combining PCA with k-means cluster-ing simplifies data interpretation through categorical grouping. The analysis results are en-riched using an interactive geographic information system (GIS) representation, vividly portraying regional disparities and commonalities across Romanian counties.