The study provides an identification and analysis of potential enablers that facilitate transition towards net zero in the energy sector through Multi Criteria Decision-Making (MCDM) framework. The identified enablers and causal relationships between them in terms of decarbonization initiatives are studied using the DEMATEL method and combining trapezoidal fuzzy numbers (TFNs). The research design involves an overarching review of thirteen potential enablers to net zero transition within the energy sector, in order of their impact and causality. Top-ranked enablers that would have the greatest impact in achieving the energy transition were carbon pricing mechanisms, waste-to-energy conversion, decentralized energy systems and circular procurement policies. The research indicates that the enablers show causal pathways that are interconnected and can take place as both causes and effects in the decarbonization framework. Application of DEMATEL method using TFNs increases the strength of causal relationship derivation. The study adds to the literature on enabling net zero transition in energy and highlights the importance of a conceptual approach involving a combination of policy, technology and principles of the circular economy. Such lessons can guide policy makers, industry players and academics in planning and speeding up the process to sustainable energy systems and world climate targets.

This study aims to provide a framework for categorising safety behaviours of construction workers, recognising the importance of employee safety in the competitive business environment. Employee safety is crucial to overall efficiency, productivity, and well-being, and the study seeks to contribute to understanding and managing workplace safety in the construction industry. This study utilises machine learning (ML) algorithms, like logistic regression, support vector machine, and decision trees, to develop a categorisation framework for the safety behaviours of construction workers. The framework is validated using frequent safety behaviours observed in a random sample of construction professionals. The study finds that workplace safety behaviours (WSB) are primarily influenced by supervisor support, reckless habits, and safety motivation. Limiting workplace accidents, enforcing safety laws, properly documenting safety processes, and organising sessions to educate staff are identified as critical sub-factors. Advancements in technology have resulted in significant improvements across construction organisations in allied domains. Additional considerations include education, preempting the possibility of accidents in different workplace situations, and enforcing strong disciplinary measures. The framework proposed can serve as a valuable tool for organisations to tailor safety interventions. By recognising the diverse influences on safety behaviours, companies can implement targeted measures to address specific root causes of unsafe practices. The practical implications of these findings for safety management in the construction industry are noteworthy.