[Dynamic Evolution and Transformation Path of Carbon Emissions in China's Logistics Industry under the Background of...

The low-carbon transformation of the logistics industry is an important component of achieving China's "dual carbon" goals. Analyzing the dynamic evolution of carbon emissions in China's logistics industry and exploring effective paths for green and low-carbon development under the background of digital intelligence are of great significance for the long-term development of the logistics industry. Based on the carbon emission coefficient method, we calculated the carbon emissions of the logistics industry in 30 provinces and cities in China and analyzed the dynamic evolution of the logistics industry using kernel density analysis. We also constructed a measurement index system for the level of digitalization and incorporated it into the TOE framework, based on the three levels of technology, organization, and environment, to construct the antecedents of carbon emissions in the logistics industry, using the fsQCA method for configuration analysis of carbon emission reduction pathways in the logistics industry. The results indicate that: ① The carbon emissions of China's logistics industry showed a trend of first increasing and then decreasing, with a gradual decrease in the concentration of carbon emissions in the early stage and an increase in regional differences in carbon emissions, indicating spatial polarization. The gap between regions gradually narrowed in the later stage, and the distribution became more concentrated and balanced. ② There were three driving modes for low-carbon emissions in the logistics industry: digital intelligence-open collaborative type, technology-market synergy type, and digital intelligence-environment collaborative type. Among them, digital intelligence-open collaborative type was the most common. ③ There were three driving modes for non-low-carbon emissions in the logistics industry: open deficiency type, technology-open deficiency type, and numerical intelligence deficiency type. This was mainly due to the lack of two variables, namely the level of digital intelligence and the degree of openness to the outside world. ④ The presence of multiple configurational paths indicated that the level of digital intelligence was a core condition for the low-carbon development of China's logistics industry. Empowering the low-carbon transformation of the logistics industry with digital intelligence is a way to alleviate the burden of high-quality development in the logistics industry. The research findings can provide important reference and guidance for the government and relevant departments.