Eco-efficiency assessment of regional industrial systems in China considering scale heterogeneity

This paper introduces a novel Meta-frontier slacks-based measure network data envelopment analysis (Meta-frontier SBM-NDEA) model to evaluate the eco-efficiency of China's provincial industrial systems, addressing scale heterogeneity and undesirable outputs. Scale heterogeneity refers to differences in the scale or size of decision-making units (DMUs), which can impact their production technologies and performance evaluation. The model incorporates slack variables and a multi-stage network structure, providing a robust framework for performance evaluation. Analyzing panel data from 2011 to 2020, we find an overall eco-efficiency score of 0.4034, indicating significant room for improvement. Eastern provinces excel in eco-efficiency, while Western provinces face challenges primarily due to low economic efficiency. The Central region suffers from resource and environmental inefficiencies. Notable technological gaps exist across regions, and our findings reveal that regional economic development enhances eco-efficiency, whereas R&D focus and profitability can hinder it. Importantly, this study's innovation lies in enabling comparisons of efficiency among heterogeneous DMUs while integrating ecological considerations. These insights provide practical guidance for policymakers and business leaders seeking to foster sustainable industrial development in China.