Countries worldwide are focusing on energy efficiency, economic sustainability, and responsible resource management to address climate change and meet sustainable development goals (SDGs). This study investigates how factors such as artificial intelligence, renewable energy, green human capital, geopolitical risk, natural resource rent, and information and communication technology influenced CO₂ emissions in 36 countries between 2000 and 2021. The study also explores how institutional quality moderates these relationships. We employed advanced econometric techniques to address this gap, including panel-correlated standard errors (PCSE) and the Driscoll–Kraay estimations (DKSE) models. A two-step system GMM approach was also used to strengthen the robustness of our findings. The findings reveal that green human capital, renewable energy consumption, and institutional quality can significantly reduce CO₂ emissions. Conversely, artificial intelligence, geopolitical risk, natural resource rent, and information communication technology contribute to increased CO₂ emissions. Institutional quality enhances the positive impact of green human capital and renewable energy on emission reduction. However, it has the opposite effect on artificial intelligence, leading to an even greater increase in CO₂ emissions. These findings underscore the importance of green policies in achieving sustainable development goals. We recommend that policymakers prioritize investing in clean energy and green human capital while strengthening institutional quality to effectively mitigate carbon emissions and meet SDGs. They also regulate AI and ICT carbon footprints and address geopolitical risks through energy diversification and international cooperation.

This study investigates the critical roles of green innovation adoption (GIA) and green technology adoption (GTA) in advancing the digital economy (DE). It explores how creative enterprises (CE) and financial capability (FC) mediate and moderate the relationships between green innovation, technology adoption, and the digital economy. Data were collected from 400 respondents in the automotive industry in China through a structured survey questionnaire. Structural Equation Modeling (SEM) was conducted using Smart PLS 4.0 to analyze the data and test the proposed hypotheses. The findings indicate that green innovation and technology adoption significantly and positively impact the digital economy. Moreover, these factors positively influence creative enterprises, enhancing the digital economy. Creative enterprises were also found to mediate the relationship between green innovation/technology adoption and the digital economy. In addition, financial capability significantly moderated the link between creative enterprises and the digital economy. This research contributes to the literature by examining the synergistic effects of environmental sustainability, innovation adoption, and technological integration within the digital economy. It provides actionable insights into embedding sustainable practices in the evolving digital landscape while highlighting the intricate dynamics among innovation, technology adoption, and financial resources in driving economic transformation. This study contributes to the literature by exploring the synergistic effects of green innovation, technology adoption, and financial capability in driving the digital economy, focusing on creative enterprises as a mediating factor. It provides actionable insights for integrating sustainability into the digital landscape, offering a novel framework for economic transformation in the automotive industry.

The study examined the decoupling relationship between industry carbon emissions and economic growth using the most current updated data. We collected data from the industry sector of Pakistan from 1991 to 2018. This study used two techniques, Tapio’s elasticity and fluctuation index, to test the decoupling relationship and the relationship’s stability between industry carbon emissions and economic growth. First, we analyzed the decoupling relationship between industry carbon emissions and economic growth in Pakistan using Tapio’s decoupling model, decoupling the elasticity of technology, scale and structure. Second, the decoupling volatility index was used to determine the stability of the technology, scale and structure elasticity. The Tapio decoupling elasticity technique results confirmed the significant relationship between industry CO₂ emissions, economic growth and added value comes out to be a simple feature of each stage and undergoes expansive negative and strong decoupling processes. The outcomes of elastically decoupled volatility indexes suggest that three out of four indices are high, indicating unstable decoupling conditions. This study concludes that growth and volatility were the crucial characteristics of industrial carbon emissions during 1991–2018. Hence, the industry’s carbon emissions were increased from 16.67 million tons in 1991 to 55.70 million tons in 2018, an average yearly growth of 4.56%.