Analysis of technological innovation on provincial green development levels of logistics industry in China.

The transition from traditional logistics to green and low-carbon logistics is crucial and inevitable due to the pressure of climate change and sustainable development in China. Meanwhile, technological innovation is perceived as an important factor affecting the development of the logistics industry. To explore the impacts of technological innovation and other factors and to propose proper policies based on the results, this study utilizes a generalized estimating equations (GEE) regression model to analyze panel data of 30 provinces during 2001–2019. Firstly, the entropy weight method is applied to calculate the green logistics development level based on an index system considering green factors. Secondly, a GEE model which considers the correlation among different observations is used to investigate the impacts of crucial factors on the green logistics development level. Moreover, regional heterogeneity is also analyzed in this paper by comparing the regression results of the Eastern region, Central region, and Western region. Based on the above analysis, several conclusions are drawn: (1) In terms of the average green logistics development levels, the Eastern region ranks 1st, the Central region ranks 2nd, and the Western region ranks 3rd. (2) GEE regression model is proved effective in our sample. (3) For the full sample, technological innovation, trade openness, and logistics infrastructure positively affect the green logistics development level; while, government regulation and energy intensity negatively influence the green logistics development level. (4) Regional heterogeneity is confirmed in our sample. Related policy recommendations are proposed based on our regional regression results. Take the Eastern region as an example, the local governments in the Eastern region should upgrade the manufacturing industry, reduce government financial investment in the transportation sector, and enhance environmental control expenditure in the transportation sector. [ABSTRACT FROM AUTHOR]