Ecological efficiency evaluation and driving factor analysis of the coupling coordination of the logistics industry and manufacturing industry.

The coupling coordination of the logistics industry and manufacturing industry is conducive to the sustainable development of logistics and manufacturing and the stability of sustainable supply chain. The logistics and manufacturing industries are not only the basic industries that support social development, but also the industries with high carbon emissions. This paper constructs the measurement system of coupling coordinating ecological efficiency of two industries based on carbon emission constraints and finds out the driving factors affecting ecological efficiency, which is of great significance to the low-carbon coordinated development of the two industries in the future. Firstly, this paper classifies the carbon emissions from the logistics industry and manufacturing industry as undesirable outputs and evaluates the ecological efficiency of the logistics industry (LEE) and manufacturing industry (MEE) in the three urban agglomerations from 2006 to 2019 by using the unexpected slacks-based measure (SBM) model. Secondly, the coupling coordination method is used to analyze the coupling coordination scheduling of industrial ecological efficiency (MLCC). Finally, the spatial econometric model is used to analyze the driving factors of the MLCC. The results show that during the study period, the coupling coordination of the three urban agglomerations continued to grow, the Pearl River Delta coupling coordination is the highest, the Yangtze River Delta coupling coordination grew the fastest, and the Beijing-Tianjin-Hebei coupling coordination grew slightly slower. The development during the 13th Five-Year Plan period is obviously faster than that during the 11th and 12th Five-Year Plan. The empirical analysis results of spatial econometrics show that the driving factors have an impact on the coupling coordination degree of the three urban agglomerations, but the significance of each factor is different. The driving factors have significant spatial heterogeneity. The three urban agglomerations should formulate low-carbon industry development policies in line with local development according to the actual situation of each region and local conditions.