China’s Provincial Eco-Efficiency and Its Driving Factors—Based on Network DEA and PLS-SEM Method

Abstract

This study aims to estimate the eco-efficiencies of China at provincial levels. The eco-efficiencies of production and treatment stages are disentangled by the network data envelopment analysis (DEA) method. The key driving factors are identified by the integrative use of driving force-pressure-state-impact-response frame model (DPSIR) model and partial least squares structural equation modeling (PLS-SEM) method. This study provides several important findings. In general, the eco-efficiencies of most regions in China are inefficient and show significant regional differences. All DPSIR factors have significant and strong impacts on the eco-efficiency of the treatment stage. The eco-efficiency of the production stage evidently outweighs the eco-efficiency in economically well-developed regions. The originality of this study lies in three aspects. First, using two-stage network DEA, this study dissects the overall eco-efficiency into production efficiency and treatment efficiency. Empirical results provide insights into the root cause of the low efficiency of each province (municipality). Second, on the basis of the DPSIR model, an expanded pool of driving factors is investigated. Third, using the PLS-SEM method to analyze eco-efficiency is more reliable and effective than applying other traditional regression models.

Evolution Characters and Influencing Factors of Regional Eco-Efficiency in a Developing Country: Evidence from Mongolia

“…Further, the undesired output indicator can also be included, and the input-output indicator added is flexible in selection. There are many extended models of DEA, and the main DEA models widely used to evaluate eco-efficiency include traditional CCR and BCC models [38,39], SBM model with relaxed variables in objective function [40][41][42], DDF model of directional distance function [43,44], and Network DEA model [45][46][47][48]. This study used the Slacks-Based Measure of Efficiency (SBM) model with advantages of being dimension-free and unitvariable [49][50][51] to estimate the efficiency and eco-efficiency in Mongolia.…”

The construction efficiency study of China National Ecological Civilization Pilot Zone with network SBM model: A city-based analysis

“…Mavi et al (2019) constructed a two-stage efficiency analysis framework includes ecoefficiency and eco-innovation in OECD countries. Li et al (2020) divided economic development of China into the production stage and the processing stage. Wang and Feng (2020) applied the "productiongovernance" system evaluation framework to Chinese provincial industrial research.…”

Eco-Efficiency Analysis for the Russian Cities along the Northern Sea Route: A Data Envelopment Analysis Approach Using an Epsilon-Based Measure Model

“…Based on the SBM-DEA models, Choi et al [ 43 ] analyzed the efficiency of CO 2 emission and energy, potential CO 2 emission reduction, and marginal cost of CO 2 emission in 30 provinces of China from 2001 to 2010. Li et al used DEA to study the eco-efficiencies of China at provincial levels and the associated driving factors [ 44 ]. Lorenzo-Toja et al [ 45 ] extensively analyzed 113 wastewater treatment plants across Spain using the methodology that combines life cycle assessment (LCA) and DEA to determine the operational efficiency of each plant in order to obtain environmental benchmarks for inefficient plants.…”