A multiple factor analysis and hierarchical clustering of global logistics governance and development

This study integrates the Logistics Performance Index (LPI), Worldwide Governance Indicators (WGI), and Human Development Index (HDI) through Multiple Factor Analysis (MFA) and hierarchical clustering to create a comprehensive perspective on global development. By clustering countries based on these indicators, the analysis reveals distinct profiles highlighting variations in logistics performance, governance quality, and socio-economic development, yielding insights essential for addressing global development challenges. Three primary clusters emerged, representing countries with socio-economic vulnerabilities, emerging economies with moderate governance, and highly developed nations with advanced infrastructure. Key results demonstrate that Cluster 1 countries require substantial support in governance and infrastructure, while Cluster 2 nations benefit from institutional and logistical investment. Cluster 3 exemplifies governance and socio-economic standards benchmarks, offering sustainable development models. MFA and hierarchical clustering have proven effective in categorising countries with complex data, allowing policymakers to tailor development strategies. The study underscores the need for ongoing research to capture shifts in country profiles and assess intervention impacts over time.