Energy acts as a catalyst to boost the human development index (HDI) in a country. However, the overuse of energy leads to environmental deterioration, which is a byproduct of economic development. Due to the utilization of non-renewable energy sources for a long time, worldwide environmental conditions have become alarming. This study investigates the relationship between renewable and non-renewable energy consumption, economic growth, environmental sustainability, and the human development index (HDI) in Pakistan. The investigation incorporates population growth and technology variables to form a multivariate framework. We use a fully modified ordinary least squares (FMOLS) approach to time-series data from 1990–2017. To check the robustness of estimations, we apply the Gregory–Hansen test with a causality test under the VECM to confirm this association’s directions. Our findings confirm that non-renewable energy sources have a positive association with economic growth and CO₂ emissions. However, human development, technology, and renewable energy boost economic development and reduce environmental pollution in Pakistan. The co-integration results confirmed the long run connectivity among all variables. The causality outcomes support the bidirectional causality between renewable and non-renewable energy consumption, economic growth, and CO₂ emissions, both in the short and long run. These outcomes suggest that Pakistan should focus on energy shifts and gradually increase the share of renewables in its energy mix under the China Pakistan Economic Corridor (CPEC). Additionally, the government should increase human and technological development to enhance economic and environmental sustainability.

Market-based environmental regulations play a crucial role in promoting local carbon emissions reduction under the context of achieving “carbon peaking and carbon neutrality goals” goals. Previous studies have mainly focused on the emission reduction effects of single policy instruments, lacking systematic measurement of market-based environmental regulation. Based on panel data from Chinese prefecture-level cities during 2011–2020, this study constructs a market-based environmental regulation index using a policy text analysis method to empirically examine its impact on carbon emission intensity and the underlying mechanisms. The research findings are as follows: (1) The impact of market-based environmental regulations on carbon emission intensity shows an inverted U-shaped relationship, indicating increased carbon emissions in the short term but favorable carbon reduction in the long term. (2) Mechanism tests reveal that market-based environmental regulations primarily influence carbon emission intensity through enterprise green innovation, showing an inverted U-shaped relationship, suggesting that such regulations may suppress enterprise innovation vitality in the short term but effectively promote green innovation in the long term. (3) The carbon reduction effect of market-based environmental regulations varies significantly across regions with different official characteristics. This study provides an important theoretical basis and policy implications for improving market-based environmental regulation policy design and enhancing carbon reduction effectiveness.

Digital technologies are increasingly reshaping how top management teams (TMTs) make strategic decisions regarding green innovation. Although prior research has examined the roles of TMT characteristics and artificial intelligence (AI), it remains unclear how TMT internal structures influence green innovation through organizational attention and how AI shapes this process. In particular, CEO–TMT faultlines, reflecting divisions in experiences, roles, and authority, may affect how environmental issues are recognized and prioritized, especially in AI-enabled contexts where complex information processing can amplify internal divisions. Drawing on the attention-based view (ABV), this study examines the cognitive mechanism linking CEO–TMT faultlines to green innovation. Using a panel dataset of 35,347 firm-year observations from 2010 to 2023, we find that CEO–TMT faultlines negatively affect green innovation through reduced eco-attention. Moreover, AI technology strengthens the negative relationship between CEO–TMT faultlines and eco-attention, thereby deepening the negative indirect effect on green innovation. These findings highlight the role of organizational attention in linking TMT structures to strategic outcomes and suggest that AI adoption may reinforce, rather than mitigate, the challenges arising from internal divisions.