Asif Razzaq’s research while affiliated with Lebanese American University and other places

Purpose This research aims to explore how circular economy practices (CEPs) address environmental challenges in manufacturing while providing a competitive edge for sustainable growth. It examines the role of green knowledge sharing, green creative climate and enhanced artificial intelligence information quality in fostering the successful adoption of CEP, offering strategies to improve collaboration and innovation in green practices. Design/methodology/approach This research employed a quantitative method by using a survey to gather data from 332 respondents representing Chinese manufacturing SMEs. We applied partial least square structural equation modeling for hypothesis testing, offering robust insights into the relationships among the variables and their implications for the manufacturing sector. Findings The results show that green knowledge sharing and green creative climate are favorably connected to CEP. Meanwhile, green creative climate is a key mediator between green knowledge sharing and CEP. In comparison, artificial intelligence information quality positively moderates among targeted relationships. The importance-performance map analysis highlighted the superior importance (28.70) of green knowledge sharing and the exceptional performance (67.638) of green creative climate toward CEP. Research limitations/implications The findings can aid in improving academic and professional understanding of managing and evaluating CEP at the project and firm levels in the manufacturing sector. Therefore, policymakers and managers may implement CEP by emphasizing green knowledge sharing, green creative climate, and artificial intelligence information quality. Originality/value This research contributes to the limited prevailing literature by enhancing the understanding of green knowledge sharing, green creative climate, artificial intelligence information quality and CEP. It sheds light on the potential role of green knowledge sharing and green creative climate, as they are performing the role of catalysts for enhancing information quality and fostering CEP in organizations.

Amid growing concerns about global environmental sustainability, the focus on understanding the interplay between environmental policies, investments in sustainable practices, and renewable energy sources has intensified. This study delves into the relationship between environmental policy stringency, green investment, and the utilization of renewable energy, specifically examining their impact on the load capacity factor (LCF) within G11 countries utilized from 2000 to 2021. Manifestly, LCF integrates both demand‐ and supply‐side aspects of environmental quality. It also utilizes a comprehensive indicator of environmental policy stringency, evaluating its impact alongside green investment. Employing the Cross Sectional‐Augmented Autoregressive Distributed Lag (CS‐ARDL) model and the Common Correlated Effect Mean Group (CCEMG) approach, this research demonstrates that environmental policy stringency, green investment, and renewable energy consumption positively and significantly influence the LCF, consequently fostering improvements in environmental sustainability in both short‐ and long‐term scenarios. It is worth mentioning that environmental policy stringency has the strongest effects on LCF followed by renewable energy. The findings strongly indicate that reinforcing environmental policies, promoting green investment, and embracing renewable energy usage can collectively yield a substantial reduction in environmental pressure for G11 countries.

Due to the worsening issues related to resources and the environment, industrial green transformation (IGT) has emerged as an unavoidable solution in the present stage. Likewise, renewable energy technology innovation (RETI) is indispensable in driving the industrial development path towards green transformation. Initially, this study measures the current status of RETI and IGT and then applies fixed effects models and dynamic panel threshold models to analyze the underlying mechanism between RETI and IGT utilizing China’s regional data from 2006 to 2019. The results support a significant positive association between RETI and IGT. It also shows that China’s IGT is low with significant rough development characteristics, while RETI yields progressive trends. Besides, RETI significantly contributes to IGT in eastern and central areas of China, while western areas of China produce insignificant effects. Manifestly, RETI possesses a nonlinear effect on IGT, which implies that the positive effect of RETI on IGT gradually strengthens when R&D investment intensity and industrial development level crosses a specific threshold value. Similar results are endorsed using alternative instruments, proxies, and estimators, offering reliable outcomes and recommendations.

Low-carbon transformation of the economy is the inevitable orientation of socialism with Chinese characteristics to high-quality development in the new era, while the Chinese decentralized development model determines that the competition of local governments in China is an important factor influencing the green technological innovation on low-carbon transformation of the economy. How to achieve coordinated economic growth and ecological environment has become a prob-lem for local governments. Data from a Chinese provincial panel covering the years 2007–2019 is used to investigate the effects of heterogeneous local government competition (Comp), namely, economic, ecological and service competitions on economic low-carbon transition, and moderating effects of heterogeneous government competition and green technology innovation (GTECH) on the low-carbon economic transition (LCT). The results reveal that there are substantial disparities in the consequences of heterogeneous government competition on low-carbon economic transition (LCT). Among them, economic competition significantly dampens economic low-carbon transition (LCT), and ecological competition and service competition significantly boost economic low-carbon transi-tion (LCT). After performing robustness checks, these results continue to be strongly convincing. The study of moderating effects shows that economic competition can dampen the positive influence of green technology innovation (GTECH) to the economic low-carbon transition (LCT). However, ecological competition and service competition facilitate the promoting effect of green technology innovation on economic low-carbon transition (LCT).

The actions and policies enacted by today's youth hold profound implications for future generations, underscoring their pivotal role in advocating for climate issues. Younger cohorts exhibit heightened concern regarding climate change and are highly visible on social media platforms. Hence, this study aims to delineate the portrayal of climate-related news and disasters on TikTok. The research draws upon fifty TikTok accounts focused on climate-related content. Employing social network analysis, PageRank, and Superedge Rank methodologies, this investigation evaluates how TikTok users-called TikTokers-address climate change and its impact on social media. The assessment scrutinizes climate-related news, disasters, and the resultant networks to gauge the influence wielded by social influencers in disseminating messages. Results reveal that among the four key entities -internet influencers, government, scientists, and producers-internet influencers exert the most substantial influence on climate change news dissemination on TikTok, while the government plays an influential role in climate disasters. Like other social media platforms, TikTok is a valuable arena for gauging public sentiment on critical health concerns like global warming. Nonetheless, ensuring the reliability and depth of messages shared on TikTok necessitates the presence of credible experts who can deliver comprehensive and scientifically sound information within the platform's time constraints.

The Sustainable Development Goals, championed by the United Nations, have elevated the importance of renewable energy development (RED) within China's energy landscape. As China strives to align its energy goals with these global objectives, it becomes imperative to delve into the intricate spatial dynamics of renewable energy. This study employs a modified gravity model and harness the power of social network analysis to scrutinize the landscape of RED in 30 Chinese provinces from 2012 to 2021. The findings reveal a captivating narrative of transformation. Over the years, we have witnessed shifts in the general trajectory of RED across China and nuanced variations within each province. The spatial network underpins RED's growth as a multifaceted tapestry, showing stability and adaptability. It paints a vivid picture of interconnected provinces with telltale signs of spatial spillover effects. Amid this intricate web emerges a core–edge pattern, signifying the ascent of core regions while the peripheries undergo a contraction. Nevertheless, beneath the surface, the demographics of network components play a significant role, contributing to the rich tapestry of RED variations across provinces. This spatial network thrives on the disparities in industrial policy, economic development, system adjacency, transportation infrastructure, and the diverse political systems across the Chinese provinces. In light of these compelling findings, our call to action is clear. Policymakers would reinforce their commitment to RED, encouraging regional collaboration and harmonizing policies to accelerate China's journey towards sustainable energy goals.