Environmental, social and governance (ESG) goes beyond its function as a business to maximize profits for the shareholders to work for societal purposes. Meanwhile, the green credit policy in China is still in its infancy, and the impact of green loans on the efficiency of commercial banks is significantly different. In this context, this paper details the company’s performance in crucial aspects such as low-carbon operations, eco-friendly financial innovation, a sustainable economic system, data security and the development of organizational capabilities to provide a sustainable development paradigm for supply chain finance technology peers. Based on ESG portfolio, we found that adding ESG holdings to a company affects its compliance with delivery or environmental rules, and anode and cathode of ESG combined Dual Carbon (DC) are presented in terms of emission levels. Our further research indicates the implementation of Green Credit Guideline has a positive impact on ESG performance of both green and polluting firms in comparison with others. The result was fully supported by different methods and models including PSM-DID (Propensity Score Matching-Differences-in-Differences), QDID (Quantiles Differences-in-Differences), and Kernel approaches, which can provide more implications and references for policy makers. Investors, politicians, and other essential stakeholders perceive ESG as a strategy to protect enterprises from future risks.

First principles simulation studies using the density functional theory have been performed on (9, 0) Zigzag Singlewalled Carbon Nanotube (SWCNT) to investigate its electronic, optical and thermodynamic properties using CASTEP (Cambridge Sequential Total Energy Package) and DFTB (Density Functional based Tight Binding) modules of the Material Studio Software version 7.0. Various functionals and sub-functionals available in the CASTEP Module (using Pulay Density Mixing treatment of electrons) and various eigen-solvers and smearing schemes available in the DFTB module (using smart algorithm) have been tried out to chalk out the electronic structure. The analytically deduced values of the band gap obtained were compared with the experimentally determined value reported in the literature. By comparison, combination of Anderson smearing scheme and standard diaogonalizer produced best results in DFTB module while in the CASTEP module, GGA (General Gradient approximation) functional with RPBE (Revised-perdew-Burke-Ernzerh) as Sub-functional was found to be the most consistent. These optimized parameters were then used to determine various electronic, optical and thermodynamic properties of (9, 0) Singlewalled Nanotube. (9, 0) Singlewalled Nanotube, which is extensively being used for sensing NH₃, CH₄ & NO₂, has been picked up in particular as it is reported to exhibit a finite energy band gap in contrast to its expected metallic nature. The study is of utmost significance as it not only probes and validates the simulation route for predicting suitable properties of nanomaterials but also throws light on the comparative efficacy of the different approximation and rationalization quantum mechanical techniques used in simulation studies.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

The objective of the study was to analyze green marketing in the promotion of environmentally responsible and sustainable practices in the development of resilient infrastructure in Peru. The methodology used was qualitative and interpretative, the documentary design based on the systematic review of scientific literature. The PRISMA model was applied for the selection of units of analysis, resulting in 36 articles out of an initial total of 950. Content analysis was used to examine the documents, following a detailed procedure that included the use of Grounded Theory to categorize and analyze the data. The results highlighted the importance of integrating green marketing and sustainable practices into resilient infrastructure planning and development. Key strategies were identified that include promoting environmental responsibility, adopting sustainable technologies in construction, and implementing policies that foster urban resilience and sustainability. The findings highlight the adoption of a comprehensive approach that combines green marketing with resilient infrastructure planning and development to address environmental challenges and promote sustainable development in Peru.