This paper selected the data from 2010 to 2020 to measure the carbon emissions of the logistics industry in different regions of China, decomposed the influencing factors of carbon emissions in China’s logistics industry based on the LMDI model, and, finally, conducted a decoupling analysis of carbon emissions and the development of the logistics industry. The conclusions are as follows: (1) China’s carbon emission levels vary greatly from region to region, with the highest distribution pattern in the east and the lowest in the west, while the growth rate in the east is also the highest. (2) The level of economic development has the greatest impact on carbon emissions, and it has the effect of promoting carbon emissions in three regions; logistics development effects have the characteristics of first driving and then restraining emissions in the three major regions. The effect of energy intensity has great volatility. The effect of intensity in the eastern region dropped sharply in 2015, with negative effects after that year. Development of the logistics industry has limited the inhibition of carbon emissions in the central and western regions. Although the effect of the energy structure is negative, it failed the significance test. The effects of the energy structure began to show a downward trend in three regions after 2015. (3) The decoupling analysis showed that only 3 provinces are strongly decoupled, 20 provinces are weakly decoupled, and the regional carbon emissions are quite different.

From a global perspective, carbon emissions are a global problem that needs to be solved urgently. At present, 61% of countries have committed to achieving net zero emissions. Compared with industry and construction, the transportation sector has become the focus and challenge for countries to achieve carbon neutrality due to the characteristics of strong mobility, scattered emission sources, and complex social behaviors. Therefore, the issue of carbon emissions in the transportation industry has become the focus of academic attention. This paper first calculates the carbon emission efficiency (CEE) of the regional transportation industry through the super-efficiency SBM model and then evaluates its regional differentiation characteristics through the Theil index, which has important practical significance for reducing regional carbon emissions. The results show that the national transportation CEE average value is 0.612, a relatively low level. The spatial distribution of China’s transportation CEE shows an obvious characteristic of “east highest and west lowest”. The regional differences in the transportation industry CEE are larger than those between regions. The differences in the transportation industry CEE among the eastern, central, and western regions are on the downward trend as a whole, and intra-regional differences are greater than inter-regional. The intra-regional differences cause the overall differences in transportation industry CEE; the eastern region contributed the most to the Theil index, while the central contributed the least. The biggest factor affecting the transportation industry CEE is the regional energy structure, and the smallest factor is the per capita GDP. This research has important reference significance on the target of carbon neutrality.

In agricultural production, chemical fertilizers and pesticides are being used in large quantities; the residues of these substances have some negative impact on the quality of agricultural products and soil, and they produce a large amount of carbon emissions. Green agricultural products are popular for their low carbon, quality, and safety, and they flow from the production side to consumers through a traceable supply chain. Therefore, ensuring the reliable and stable operation of the traceable supply chain for green, low-carbon agricultural products is an important issue. In view of the difficulty of obtaining information in previous coordination mechanisms in multi-person cooperative games, this article proposes an optimal pricing decision and constructs a profit-distribution model based on an improved Raiffa value to make the profit-distribution mechanism more conducive to the stability and sustainable development of the supply chain, and empirical analysis was carried out. The empirical analysis shows the following: (1) The centralized decision-making selling price of green and low-carbon agricultural products based on the quantitative cost–benefit analysis and demand function can realize the optimal profit of the supply chain. (2) Using the improved Raiffa value, considering the investment cost and risk to allocate the optimal profit of centralized decision-making, optimizes the profit distribution of supply chain members and overcomes the problem of the difficulty in acquiring information in multi-player cooperative games. (3) For investment costs and risks, the corresponding profit-distribution adjustment value weight vector can be obtained using the AHP; for risks that are difficult to quantify, the fuzzy comprehensive evaluation method and the risk-factor-based method can be used to determine the risk coefficient of each member of the supply chain. The optimized profit-distribution mechanism of supply chain members is more reasonable than decentralized decision-making, which has a significant reference for promoting the sustainable development of a traceable supply chain of green and low-carbon agricultural products.

The development of e-commerce plays a very important role in changing the production and operation mode, optimizing the allocation of market resources, promoting sustainable development, and ultimately achieving the goal of e-commerce poverty alleviation. Therefore, the efficiency of e-commerce poverty alleviation has become a focus of attention for both the government and academia. The authors of this paper selected the panel data of 30 provinces and cities in China from 2010 to 2021, in order to measure the poverty alleviation efficiency of e-commerce in each province and city. We used the Moran’s I index to measure its spatial correlation to verify the existence of its spatial effect; we then used the spatial Durbin model to analyze the spatial spillover effect in the efficiency of e-commerce poverty alleviation. The conclusions are as follows: First, there is a significant positive spatial correlation of the efficiency of e-commerce poverty alleviation among different regions in China. Moran’s I index exceeds 0.5, indicating that there is a significant spatial effect in the efficiency of e-commerce poverty alleviation, and the existence of its spatial effect is unavoidable in the empirical analysis. Secondly, from the perspective of the efficiency of e-commerce poverty alleviation in various regions of the country, the overall e-commerce poverty alleviation efficiency is not high, and there are large differences among regions. The regions in which efficiency is higher include Tianjin, Beijing, and Shanghai. Regionally, the highest are in the east and the lowest are in the west. Secondly, from the decomposition of spatial spillover effects, the direct effects of each influencing factor are all positive. Only the financial development environment is less significant, and the indirect effects indicate that only four indicators have significant spatial spillover effects, of which the most significant is industrial agglomeration. The level of industrial agglomeration is not significantly related to the level of human capital, and there is a negative correlation between it and the efficiency of e-commerce poverty alleviation. The authors studied the poverty alleviation efficiency and spatial spillover effect of China’s regional e-commerce from the perspective of sustainable development, which is beneficial to China’s regional poverty alleviation results, providing practical guidance and decision-making reference for implementing differentiated coping strategies in different regions. The research complements, improves, and expands the research content in this field.

Currently, a large amount of greenhouse gas emissions has caused a series of problems such as serious environmental degradation, and China is facing enormous pressure to reduce emissions. In terms of meeting the needs of people’s lives, cold chain logistics has undergone faster development, and its carbon emissions are relatively high. In response to the government’s advocacy for green and low-carbon concepts, some technical measures taken will increase the cost of carbon emissions. Identifying measures to reduce carbon emissions using management methods is an ongoing problem that this paper intends to solve. To address the shortcomings of the traditional cost method that cannot accurately account for the cost of each calculation object and ignores the carbon emission cost, this paper constructs an activity-based cost model for cold chain logistics enterprises to more comprehensively account for the operation cost and carbon emission cost. Then, a typical enterprise YS cold chain logistics company is used as a case study for an empirical calculation and analysis. The following conclusions are drawn: (1) the results identify the main activity centers that affect the operating costs and carbon emission costs of different customers; (2) a comparison among the total cost of each project helps to identify high-quality customers; (3) clarifying the carbon emission cost of wasting resources is beneficial for further optimizing the match between production capacity and business volume. This paper provides a path reference for enterprises to efficiently implement logistics cost management and carbon emission control, which can help enterprises cope with cost reduction and efficiency enhancement in a low-carbon environment and promote the long-term development of the logistics industry and environmental protection.

As the economy develops, the level of logistics required means many activities become increasingly dependent on transportation, which leads to the deterioration of the ecological environment, aggravates air pollution, causes urban traffic jams, and has a negative influence on sustainable development. Therefore, in the context of sustainable development, how to coordinate the development of the logistics industry and regional economy has become a governmental and academic focus. The coupling coordination degree model and spatial autocorrelation analysis model were applied to empirically analyze the coupling and coordination of the logistics industry and economy in each city in YRDR and the relationship of mutual influence. The research results show that, for economically developed cities, economic development had more influence on the coupled and coordinated degree of the two, and for the less developed cities, the development of logistics drove the improvement of the coupled and coordinated degree of the two. The analysis of the Anhui Province showed that the coupling and coordination degree of its own logistics industry and economy was driven by strong radiation, and the impact on that degree of the logistics industry and economy of cities in Jiangsu, Zhejiang, and Shanghai was not significant. The development of the coupling and coordination degree of the two variables of cities in Jiangsu Province was more balanced. The divergence degree of that of the logistics industry and economy of cities in Zhejiang Province exhibited a tendency to increase, and the divergence mainly came from the endogenous development of each city. The variability was mainly due to the endogenous dynamics of each city’s development. Finally, suggestions for the coordinated and sustainable development of the logistics industry and regional economy are provided.