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.

Sustainability and green campus initiatives are widely examined in developed countries but less attention has been paid in developing countries such as Pakistan. Therefore, this study intends to examine the links between sustainability dimensions and green campus initiatives by mediating role of teachers and students’ involvement. Green campus or sustainable campus or environment friendly campus is based on the principles of environmental sustainability, incorporating social, and economic and environmental dimensions. Questionnaire for assessment of sustainability was adopted and 529 responses were received from the faculty, management and servicing staff of the seven Mountain Universities of the Gilgit Baltistan and Azad Jammu and Kashmir in Northern Pakistan. Partial Least Square Structural Equation Modeling (PL-SEM) was used to analyse the data. The results indicated that energy conservation, water conservation, green transport, sustainable waste management have enhanced campus green initiatives. Teachers and students’ involvement partially mediate the relationship between green transport strategies, sustainable waste management and green campuses initiatives. While on another hand, teachers and students’ involvement have not mediated the links between energy conservation, water conservation and green campus initiatives. The study contributes to theory building in the area of green and environment friendly campus initiatives by enriching the understanding of the processes carrying the effect of sustainability dimensions and both teachers and students’ involvement.

Smart electric meters play a pivotal role in making energy systems decarbonized and automating the energy system. Smart electric meters denote huge business opportunities for both public and private companies. Utility players can manage the electricity demand more efficiently whereas customers can monitor and control the electricity bill through the adoption of smart electric meters. The study examines the factors affecting the adoption intention of smart electric meters in Indian households. This study draws a roadmap that how utility providers and customers can improve the smart electric meters adoption. The study has five independent variables (performance expectancy, effort expectancy, social influence, environmentalism, and hedonic motivation) and one dependent variable (adoption intention). The sample size for the study is four hundred and sixty-two respondents from Delhi and the National Capital Region (NCR). The data was analysed using structural equation modelling (SEM). The results of this study have confirmed that performance expectancy, environmentalism, and social influence have a significant impact on the intention of adopting smart electric meters. Therefore, utility providers can improve their strategies to attract more customers to adopt smart electric meters by focusing more on the performance of smart electric meters and by making them environmentally friendly. This research offers meaningful insights to both customers and utility providers to make energy systems decarbonized and control energy consumption.