• Energy Research

The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

The disclosure of ESG tasks, seen as companies’ performance of sustainability, has gradually became a necessity for listed enterprises. From an ESG perspective, this paper revisits and restructures the sustainable supplier evaluation criteria. Leveraging thematic analysis, this study dissected ESG reporting guidelines across stock exchanges and explored ESG annual reports and supplier codes of conduct from the listed firms. This elucidated the evaluation criteria currently in practice. The findings indicate that existing sustainable supplier evaluations cannot fully meet ESG regulatory requirements. Drawing insights from these gaps, we reconstructed the evaluation criteria through text analysis to better align with ESG mandates. This study introduces the concept of a “Relative Word Frequency Ratio” to analyze the importance of each indicator and to further determine which to retain or delete. This research offers a robust theoretical foundation and practical guidance for enhancing supplier sustainability evaluations, and the proposed sustainable supplier evaluation criteria system could provide a decision-making reference for enterprises in the choice of ESG-qualified suppliers.

A thorough analysis of commercial banks’ product innovation performance is essential to promoting bank product innovation capabilities and sustainable development. In this paper, the product innovation performance of commercial banks is defined as the conversion efficiency of input and output factors. The credit risk of product innovation of banks is considered as an undesirable output and incorporated in the performance evaluation system. Depending on whether there is a synchronous relationship between innovation income and risks, a Fixed Correlation model (FCM) and a Variable Correlation model (VCM) are then constructed based on Data Envelopment Analysis (DEA) method for the evaluation of commercial bank product innovation performance. In addition, an output optimization model of the objective function is also constructed to estimate the target income of commercial banks’ product innovation in the FCM and VCM. Finally, the proposed model is applied to Chinese listed commercial banks for estimating the performance and target income of product innovation.