Based on the improved model of Kaya identity and LMDI decomposition method, this paper conducts decomposition analysis on the influencing factors of carbon emissions in Anhui Province from 2008 to 2020. Based on the results of LMDI decomposition method, this paper uses STIRPAT model to conduct regression analysis to study the internal driving factors of carbon emissions in Anhui Province, and provides targeted carbon emission reduction suggestions. The results show that economic development contributes the most to the positive pull of carbon emissions, and energy intensity contributes the most to the inhibition of carbon emissions. Optimizing the energy structure, improving the energy utilization rate, optimizing the industrial structure, developing the economy with high quality, and improving residents' awareness of low-carbon life can all inhibit CO2 emissions.

Under the development strategy of "new economy and management", many financial institutions focus on the deep integration of the new generation of information technology and education and teaching, and information technology teaching has been paid attention to. The new training program requires students to be able to analyze large-scale data and have strong data analysis ability on the basis of mastering a programming language. The establishment of cases in line with the integration of theoretical teaching and programming teaching can cultivate students' interest in learning statistics and improve the teaching quality of statistics. In this paper, the experimental teaching is divided into three parts: The first part is to familiarize students with basic commands.The second part is to simplify the calculation. The third part is to let students understand the basic theory of statistics, which not only helps students improve Gauss programming ability, but also helps students understand the depth and breadth of statistical knowledge.

This study combs the historical evolution of Chinese brand building and corporate social responsibility building, and combines it with the hot issues concerned by the public, proposes seven issues on the relationship between the performance of social responsibility by enterprises in the food and beverage industry to various stakeholders and the promotion of brand value, and gives analysis and explanation from five different theoretical perspectives. This study hopes to find a breakthrough and foothold to realize the growth of brand value of food and beverage enterprises, which can encourage relevant enterprises to perform their social responsibilities more actively.

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At present, the global warming problem is becoming more and more serious, and effective carbon emission reduction is urgent, and the cooperation between industries within a specific supply chain can provide a new method to reduce emissions. Whith 2017 year as the research period, 30 industrial sectors in China as the research object, using the new method proposed by Kanemoto et al. to identify high carbon emission industrial clusters. Combined with modified normalized cut function, we find out high carbon emission industrial clusters among 30 industrial sectors from the supply chain perspective with multiple clustering methods, and based on this, the relative position of each industrial sector in the industrial chain is studied through minimum spanning tree to find the key industrial chain. The results show that the clustering effect performs best at k=7, where cluster 1 accounts for 89% of the total carbon emissions of all clusters, indicating that this industrial cluster has more potential for emission reduction compared with other industrial clusters and is the focus of future emission reduction efforts, while the upstream and downstream industrial chains with the construction industry as the core are the key industrial chains of this cluster as shown by the minimum spanning tree.