To achieve the energy transition and carbon neutrality targets, governments have implemented multiple policies to incentivize electricity suppliers to invest in renewable energy. Considering different government policies, we construct a renewable energy supply chain consisting of electricity suppliers and electricity retailers. We then explore the impact of four policies on electricity suppliers’ renewable energy investments, environmental impacts, and social welfare. We validated the results based on data from Wuxi, Jiangsu Province, China. The results show that government subsidy policies are more effective in promoting electricity suppliers to invest in renewable energy as consumer preferences increase, while no-government policies are the least effective. We also show that electricity suppliers are most profitable under the government subsidy policy and least profitable under the carbon cap-and-trade policy. Besides, our results indicate that social welfare is the worst under the carbon cap-and-trade policy. With the increase in carbon intensity and renewable energy quota, social welfare is the highest under the subsidy policy. However, the social welfare under the renewable energy portfolio standard is optimal when the renewable energy quota is low.

LEED (Leadership in Energy and Environmental Design) is a certification program for quantitatively assessing the qualifications of homes, non-residential buildings, or neighborhoods in terms of sustainability. LEED is supported by the U.S. Green Building Council (USGBC), a nonprofit membership-based organization. Worldwide, thousands of projects received one of the four levels of LEED certification. One of the five rating systems (or specialties) covered by LEED is the Building Design and Construction (BD + C), representing non-residential buildings. This rating system is further divided into eight adaptations. The adaptation (New Construction and Major Renovation) or NC applies to newly constructed projects as well as those going through a major renovation. The NC adaptation has six major credit categories, in addition to three minor ones. The nine credit categories together have a total of 110 attainable points. The Energy and Atmosphere (EA) credit category is the dominant one in the NC adaptation, with 33 attainable points under it. This important credit category addresses the topics of commissioning, energy consumption records, energy efficiency, use of refrigerants, utilization of onsite or offsite renewable energy, and real-time electric load management. This study aims to highlight some differences in the EA credit category for LEED BD + C:NC rating system as it evolved from version 4 (LEED v4, 2013) to version 4.1 (LEED v4.1, 2019). For example, the updated version 4.1 includes a metric for greenhouse gas reduction. Also, the updated version 4.1 no longer permits hydrochlorofluorocarbon (HFC) refrigerants in new heating, ventilating, air-conditioning, and refrigeration systems (HVAC & R). In addition, the updated version 4.1 classifies renewable energy into three tiers, differentiating between onsite, new-asset offsite, and old-asset offsite types.

This article using thematic and content analysis investigated the contribution of innovation in achieving sustainable economic development. The objective of the bibliometric research was to assess the literature on this subject it identified research trends, ideas, and authors who contributed to this area so that future research and policy directions could be suggested. The data was derived from the Scopus database and was extracted between January 2020 and February 2024 by applying inclusion and exclusion criteria. The Scopus database search yielded 66 articles, published between 2020 and February 2024. Scopus analytics and Microsoft Excel were used for descriptive analysis and VOS Viewer software was used for network visualization of keywords. The descriptive analysis showed the trajectory of research, the prolific authors, their publication outlets, authors affiliation, and county of origin of the documents. The prolific visualization showed five clusters: red, green, blue, purple, and yellow. The main clusters are economic development, alternative energy, sustainable development, and innovation. This research showed where consideration should be given to drive sustainability and sustainable economic development. This research outcome will assist government agencies, corporations, and non-profit organizations in planning appropriate action and policies to support innovative and renewable energy initiatives so that participation in those fields could enhance the opportunity to achieve sustainable economic development.

The paper analyzes the corporate carbon emissions and GDP contributions of the top ten companies by turnover for 2020–2023 in Germany, South Korea, China and the United Kingdom. Focusing on Scope 1, 2, and 3, the study explores the contribution of these companies to carbon intensity across different sectors and economies. The analysis shows that there are significant gaps in carbon efficiency, with the UK’s and Germany’s firms emitting the lowest emissions per unit of GDP contribution, followed by China and South Korea. Additionally, the study further examines the impact of Economic Policy Uncertainty on both firm carbon intensity and economic productivity. While EPU is positively associated with GDP contributions, its impact on emissions is nuanced. Firms apparently respond to policy uncertainty by increasing energy efficiency in direct (Scope 1) and energy-related (Scope 2) emissions but find it more difficult to manage supply chain emissions (Scope 3) in that case. The results point out the critical role of comprehensive ESG reporting frameworks in enhancing transparency and addressing Scope 3 emissions, which remain the largest and most volatile component of corporate carbon footprints. The paper then emphasizes the importance of standardized ESG reporting and bespoke policy intervention for promoting sustainability, especially in carbon-intensive industries. This research contributes to the understanding of how industrial and policy frameworks affect carbon efficiency and economic growth in different national contexts.

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

From the perspective of the corporate life cycle, this study investigates the transmission mechanism of ‘technological innovation-financing constraints-carbon emission reduction’ in energy companies using panel data and mediating models, focusing on listed energy companies from 2014 to 2020. It explores the stage characteristics of this mechanism during different life cycle phases and conducts heterogeneity tests across industries and regions. The results reveal that technological innovation positively influences carbon emission reduction in energy enterprises, demonstrating significant life cycle stage characteristics, specifically more pronounced in mature companies than in growing or declining companies. Financing constraints play a mediating role between technological innovation and carbon reduction, but this is only effective during the growth and maturity stages. Further research shows that the impact of technological innovation on carbon emission reduction and the mediating role of financing constraints exhibit heterogeneity across different stages of the life cycle, industries, and regions. The conclusions of this paper provide references for energy companies in planning rational emission reduction strategies and for government departments in policy-making.