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To limit global warming to 1.5 °C, it is imperative to accelerate the global energy transition. This transition is crucial for solving the climate issue and building a more sustainable future. Therefore, within the loaded capacity curve (LCC) theory framework, this study investigates the effects of digital adaptation, energy transition, export diversification, and income inequality on the load capacity factor (LCF). This study also attempts to investigate the integration effects of digital adaptation and energy transition, and digital adaptation and export diversification, on LCF. Furthermore, we explored how income inequality influences the LCF in economies. For this study, 112 countries were selected based on the data availability. Panel data from 2010 to 2021 were analyzed using the STATA software 13 application utilizing a two-step system generalized method of moments (GMM) approach. First, interestingly, our finding shows that digital adaptation and income significantly affect the LCF. An increase in income increases the LCF among the middle-income group of countries. Therefore, LCC is confirmed in this research. Surprisingly, energy transition, export diversification, and foreign direct investment negatively impact the LCF in the base model. Second, the impact of integrating digital adaptation and energy transition has a positive effect on LCF. Third, a negative correlation was observed between the interaction of export diversification and digital adaptation with the LCF. Fourth, a positive correlation was observed between the interaction of renewable energy and digital adaptation with the LCF. Finally, this study explores the impact of the energy transition, export diversification, and income inequality on the LCF with reference to the Organization of Petroleum Exporting Countries (OPEC). The result shows a negative effect between export diversification and LCF among OPECs at a 10% significance level. To improve the quality of our planet, policymakers must understand the forces causing climate change. By adopting a comprehensive perspective, the study aims to understand how these interrelated factors collaboratively influence the LCF thoroughly. Additionally, this research seeks to provide valuable insights related to energy transition, digital adaptation, and export diversification to policymakers, researchers, and stakeholders regarding possible avenues for cultivating a more joyful and sustainable global community. [ABSTRACT FROM AUTHOR]

Due to increasing energy consumption, there has been a significant expansion in worldwide trade, leading to the emergence of severe environmental issues. This situation is further compounded by the non-negotiable requirement to simultaneously mitigate environmental degradation and achieve economic progress. To ensure a healthier future, it is imperative to identify and address the factors that contribute to environmental contamination. The purpose of this study is to examine how Malaysia's carbon dioxide (CO2) emissions are affected by energy consumption, economic growth, and the economic complexity index (ECI). Time series data from 1997 to 2020 are used in this study, along with the autoregressive distributed lag model. The environmental Kuznets curve theory holds true in Malaysia, according to the study's findings, and energy use has a negative impact on CO2 emissions. There is also evidence suggesting that a higher ECI is linked with increased levels of CO2 emissions over a prolonged period. Malaysia's main export, electrical and electronic goods, generates substantial CO2 emissions during the manufacturing process. The outcomes of this research have important ramifications for environmental strategies concerning the mitigation of CO2 emissions. The electrical and electronics industries can implement energy-efficient technologies and practices in manufacturing processes. This would include upgrading to more efficient machinery, optimizing production schedules, and reducing idle times. It is also crucial to work with governments and industry bodies to advocate for policies that support sustainable manufacturing practices. [ABSTRACT FROM AUTHOR]

This paper looks at the changing impact of renewable energy and green innovation on the carbon footprint of eight MENA nations between 2000 and 2020. We investigate this by using the panel Q-ARDL model for the first time, and we find that, with various impacts across different quantiles, a rise in green innovation and renewable energy greatly boosts environmental sustainability in the short run. In the long run, this effect becomes increasingly more noticeable. According to our analysis, the chosen MENA countries quickly embraced energy storage, solar hydrogen, and other technology pathways to diversify their energy mix, which was a turning point in the fight against climate change. Although these factors have been separately examined in different studies, our research merges them into a single non-parametric model. This research is significant as it provides empirical evidence on the efficiency of green innovation and renewable energy policies, and it will guide policymakers and energy stakeholders in developing strategies to achieve sustainable development goals. [ABSTRACT FROM AUTHOR]

While the exponential growth of entrepreneurial ecosystem research has dramatically increased our understanding of the role of context in entrepreneurial outcomes, our knowledge of entrepreneurial ecosystems and environmentally sustainable entrepreneurship is still fragmented. There is ambiguity on how entrepreneurial ecosystems influence sustainable entrepreneurship and what factors facilitate or constrain sustainable entrepreneurship. We attempt to take stock of the extant scholarship on entrepreneurial ecosystems and synthesize studies examining their linkages with sustainability. We systematically reviewed 77 articles identified in the World of Science and Scopus databases to discuss the main themes. The content analysis uncovered four key themes: (a) how entrepreneurial ecosystems become more sustainable, (b) the role of entrepreneurs, (c) the role of universities, and (d) the outcomes of sustainable ecosystems. The findings reveal that interactions between different actors, including customers, suppliers, institutions, governments, and universities, can result in a sustainable entrepreneurial ecosystem. The novelty of our study arises from integrating extant studies on entrepreneurial ecosystem and sustainability in a systematic and replicable manner. We observed heightened attention to the environmental challenges in ecosystem literature and entrepreneurs' expanded roles in generating ecological and social value. Future studies can further evaluate the effectiveness of entrepreneurial ecosystems to examine whether creating an entrepreneurial ecosystem has a similar value while achieving sustainable development goals across varied contexts. [ABSTRACT FROM AUTHOR]

The COVID-19 crisis seems to have disproportionately impacted women's financial resilience. In fact, women's economic involvement in the financial sector remains unequal. This study compares the impact of digital financial inclusion on women's economic empowerment before and after the COVID-19 epidemic in Saudi Arabia. Using data collected from the Global Financial Inclusion Database for 2017 and 2021 and ordered probit models, the paper examines the relationship between economic women's empowerment and digital financial inclusion. Findings indicate that using digital financial services has become more crucial since the pandemic. The results demonstrate that women now play a more significant economic role in decision-making than they did before the epidemic because they have access to a variety of digital financial services that could affect their choices and decisions. The findings are consistent with a number of previous studies, which found that financial digitization is a significant factor in women's economic empowerment. The distinctiveness of this study is that it provides a recent assessment of Saudi women's present financial circumstances and assesses current Saudi government initiatives to enhance women's economic empowerment and leadership capabilities. The research conclusions provide insights for regulators and implications for future research in promoting digital financial inclusion and ensuring Saudi women's economic empowerment. [ABSTRACT FROM AUTHOR]

Over the past few years, the Association of Southeast Asian Nations (ASEAN) has experienced great economic expansion, which has resulted in varied degrees of diversified commerce, an elevated level of government revenue, and an increase in the demand for energy. The purpose of this study is to provide a solution to this conundrum by analyzing the effects of trade diversification (TDF), government revenues (GRN), gross domestic product (GDP), and natural resource rent (NTR) on the sustainable development of the ASEAN countries between the years 1981 and 2022. In order to accurately portray the concept of environmental sustainability, the ecological footprint (EFP) is utilized to represent sustainable development. The quantile‐based econometrics technique known as the Method of the Moments Quantile Regression (MMQR) has been utilized in order to investigate the direction and amplitude of the asymmetric correlation that exists between the interaction of GRN, TDF, NTR, and EFP. According to the estimations of the MMQR, it is proposed that government revenues, which include significant financial incentives that promote the stringent execution of environmental rules, hence avoiding deleterious impacts on the environment, have negative coefficients at all quantiles (Q0.25 − Q0.90). Conversely, TDF and GDP have a positive and statistically strong significant correlation across all quantiles (Q0.25 − Q0.90), revealing that TDF reduces environmental sustainability and expands the size of the world's EFP by making energy‐intensive products more accessible. In addition, the Augmented Mean Group (AMG) and the Common Correlated Effect Mean Group (CCEMG) both provide evidence that supports the correlation study by demonstrating that there is a similar pattern of causality across variables. [ABSTRACT FROM AUTHOR]