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Spatial-Temporal Distribution Characteristics and Driving Mechanism of Green Total Factor Productivity in China's Logistics Industry

机译:中国物流业绿色总因素生产力的空间 - 时间分布特性及驱动机制

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摘要

The rapid development of China's logistics industry is accompanied by the deterioration of the ecological environment and excessive energy consumption. Therefore, how to effectively measure and improve the green total factor productivity (GTFP) of the logistics industry is an important guarantee for achieving the coordination of the logistics industry development and the ecological environment protection in the high-quality development stage. This study evaluated the logistics industry's GTFP of 30 provinces in China from 2004 to 2017 using the Epsilon-based measure model (EBM) and global Malmquist-Luenberger index (GML). Then, this paper applied the geographically and temporally weighted regression (GTWR) to analyze the spatiotemporal non-stationarity of influences of driving factors on GTFP. There are three main conclusions drawn in this paper. Firstly, the GTFP of the logistics industry has significant spatial and temporal differences. From a temporal perspective, the GTFP has undergone a process of alternating changes in ascent and descent. From a spatial perspective, the GTFP has an obvious "east-central-west" gradient decreasing trend. Secondly, compared with the ordinary least squares (OLS) and the geographically weighted regression (GWR), GTWR performs best in terms of goodness of fit. Thirdly, the regression results of GTWR indicate that the influences of factors have different directions and intensities on GTFP in the logistics industry at different times and regions, showing obvious characteristics of spatiotemporal non-stationarity. Finally, some practical recommendations are put forward in this paper.
机译:中国物流业的快速发展伴随着生态环境恶化和过度的能源消耗。因此,如何有效衡量和提高物流业的绿色总因素生产力(GTFP)是实现物流业发展协调和高质量发展阶段的生态环境保护的重要保障。本研究评估了从2004年到2017年在中国的30个省份GTFP的GTFP,并使用基于epsilon的措施模型(ebm)和全球Malmitmist-luenberger指数(GML)。然后,本文应用了地理上和时间加权回归(GTWR),分析了驾驶因子对GTFP的影响的时空非公平性。本文绘制了三个主要结论。首先,物流业的GTFP具有显着的空间和时间差异。从时间的角度来看,GTFP经历了Ascent和下降的交替变化的过程。从空间的角度来看,GTFP具有明显的“东中西”梯度降低趋势。其次,与普通的最小二乘(OLS)和地理加权回归(GWR)相比,GTWR在适合的良好方面表现最佳。第三,GTWR的回归结果表明,在不同时间和地区,物流行业的GTFP对因素的影响具有不同的方向和强度,表明了时尚非公平性的显而易见的特征。最后,本文提出了一些实际建议。

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