Corporate Social Responsibility Based on Radial Basis Function Neural Network Evaluation Model of Low‐Carbon Circular Economy Coupled Development

Abstract

Under the background that the development of low-carbon circular economy is the objective requirement for the in-depth implementation of scientific development and the inevitable choice for promoting the sustainable development of economy and society, it is not only the requirement of corporate social responsibility but also the path to realize corporate social responsibility. Enterprises should become the representative and model of social responsibility practice in the development of low-carbon circular economy, in order to promote the fulfilment and development of corporate social responsibility in the whole society. Therefore, it is of great theoretical and practical significance to study the realization of corporate social responsibility in the context of low-carbon circular economy. This paper introduces the connotation of low-carbon circular economy and corporate social responsibility, analyses the reality and theoretical basis of realizing corporate social responsibility in low-carbon circular economy, analyses the interactive relationship between the development of low-carbon circular economy and the realization of corporate social responsibility, and puts forward the construction of enterprise low-carbon operation mechanism. This paper uses the research of corporate social responsibility based on radial basis function neural network to build a low-carbon circular economy. The evaluation model of environment economy coupling development is verified by an example, which provides useful guidance for the evaluation and development of corporate social responsibility.

Low-Carbon Awareness Information Technology of Enterprise Executives Based on Big Data and Multimodal Information Fusion

“…rough them, complex multimodal information is obtained and fused through the cognitive mechanism of the brain, combined with the prior domain knowledge base, to form perception, judgment, and reasoning and decisionmaking for the target. Intelligent agents can also rely on multisensor and intelligent information fusion models to achieve the same purpose [18,19].…”

Enterprise Operating State Evaluation Based on Association Rule Algorithm and Data Set

“…Du discussed the connotation of enterprise operating efficiency from multiple perspectives, and then discussed the source and relationship of enterprise operating efficiency. They believed that enterprise operating efficiency reflects the realization degree of enterprise operating goals, and is the comprehensive embodiment of internal efficiency and external efficiency [ 3 ]; In view of the lack of clear distinction between efficiency and benefit in existing studies, Wang et al clarified the connotation of business efficiency and standardized terms from the theoretical and academic level, providing reference for the standardization of relevant studies [ 4 ]; Gong et al, in view of the fact that the comprehensive management efficiency of enterprises is low, after determining the basic connotation of enterprise management efficiency, combining the international advanced theory and practice, from the perspective of enterprise resource utilization and capacity improvement, combined with the concept of continuous improvement and KPI management, this paper analyzes the business process of enterprises and summarizes the KPI efficiency evaluation methods based on resources and capabilities of enterprises [ 5 ]. Second, in different enterprises operating efficiency evaluation methods, Balabanis and Stathopoulou reviewed the research status of efficiency evaluation of knowledge-based enterprises.…”

Empirical Study on the Impact of Urbanization and Carbon Emissions under the Dual-Carbon Framework Based on Coupling and Coordination

“…The study considers that there is a certain time lag in carbon emissions, and its effect is less sensitive to time changes [41]. Therefore, the regression analysis is carried out with the help of the GMM model, as shown in Formula (9).…”

“…Zhou et al used the VAR model and pulse analysis to analyze the relevance between urban land construction and carbon emissions. The results showed that construction land had a greater impact on carbon emissions in the early stages of development, but with the improvement of infrastructure, other negative effects gradually decreased and entered a stable state [9]. Gong et al analyzed the coupling development of a low-carbon economy and enterprises with the help of a neural network and found that enterprises should actively undertake social responsibilities, reduce the use of fossil fuels, and contribute their own strengths to the low-carbon circular economy [10].…”