Carbon emissions management efficiency evaluation based on indicator information integration and DEA-Malmquist index

Abstract

The completeness of indicator information is a critical issue that requires further investigation in the evaluation of carbon emissions management efficiency. However, this problem has not received adequate attention in existing studies, and there is a dearth of analysis using the total factor productivity method, which has proven effective in evaluating efficiency in various domains. Consequently, this study proposes a model for evaluating carbon emissions management efficiency that integrates indicator information and employs the data envelopment analysis (DEA)-Malmquist index. The integration of indicator information is accomplished through the evidential reasoning (ER) approach, which includes the calculation of indicator weights. The DEA-Malmquist index is utilized to assess the efficiency of carbon emissions management and analyze its total factor productivity based on the integrated indicator information. To demonstrate the efficacy of the proposed model, a case study of 17 corporates in China from 2019 to 2021 is provided to illustrate the analysis of three scopes efficiency distribution, efficiency change and improvement strategy of carbon emissions management. Results discussion show that the proposed model can be used to provide a reference for the improvement effectiveness of carbon emissions management.