This study explores integrating Building Information Modeling (BIM) technology into risk management practices for construction projects, aiming to enhance project performance through improved risk identification, assessment, and mitigation. The research employs the Analytical Hierarchy Process (AHP) to prioritize BIM-based strategies across multiple risk management dimensions, including technical, financial, sustainability, and time management. The findings demonstrate that BIM-based financial strategies rank highest among BIM-driven risk management, followed by sustainability and time. In contrast, technical, operation, and maintenance capabilities have the lowest rank. Given the high priority of BIM financial strategies, they have been applied to conduct sensitivity analysis; the sensitivity analysis results demonstrate the dynamic nature of a BIM sub-criteria strategy in response to changes in the weight of financial considerations. As financial concerns diminish, the shift towards sustainability, health, safety, and time efficiency underscores the importance of a more balanced approach in BIM strategy prioritization. BIM-based risk management improves project outcomes by enabling real-time data-driven decision-making, enhancing stakeholder collaboration and optimizing resource use, cost control, and sustainability. This research contributes to theoretical and practical advancements in construction risk management, suggesting that BIM can be a transformative tool for optimizing project performance while addressing the complexities and uncertainties inherent in the construction industry.

This comprehensive bibliometric study investigates Sustainable Supply Chain Innovation (SSCI) research, examining its evolution, identifying key contributors, and unveiling emerging trends. Analyzing 1158 English-language SSCI articles using the robust Scopus dataset exposes noteworthy journals, authors, institutions, and global contributions. The findings suggest a consistent increase in research output since 1999, with a notable surge in the past decade. Network analysis and density-based spatial clustering identified six SSCI research clusters: Sustainability and Responsibility in Business, Navigating Innovation and Disruption, Sustainable Business Strategies, Environmental Sustainability and Innovation, Sustainable Food Systems and Environmental Impact, and Sustainable Business Dynamics. These clusters highlight the diverse nature of the evolving Sustainability and Supply Chain Management (SCM) field, contributing to a thorough understanding of the SSCI research landscape and emphasizing interconnections between sustainability and SCM themes, potentially leading to more comprehensive theoretical models. Furthermore, this understanding aids businesses in anticipating emerging trends and implementing optimal practices in SSCI. Moreover, recognizing active institutions and global contributors provides practical insights for fostering strategic collaborations.

This study investigates the impact of lean and green supply chain practices on business process performance and sustainable supply chain performance. The research utilises the resource-based view (RBV) theory to construct a conceptual model wherein lean and green supply chain practices are employed to augment business processes and sustainable performance. Concurrently, dynamic capabilities theory is applied to signify an organisation’s capacity to adapt and evolve in response to internal and external pressures from customers and competitors. The conceptual model is validated using structural equation modelling with a sample of 170 supply chain practitioners from the apparel and textile supply chain in Jordan. Results indicate that lean practices exhibit no direct impact, whereas green practices significantly influence business process performance and indirectly affect sustainable supply chain performance. Business process performance does not mediate the relationship for lean practices, but it does so for green practices. Moreover, the environmental orientation of both competitors and customers negatively moderates the impact of green practices on business processes and sustainable supply chain performance. These findings contribute to existing literature and underscore the crucial role of green supply chain practices in enhancing sustainable supply chain performance in the apparel and textile industry.

This study explores integrating Building Information Modeling (BIM) technology into risk management practices for construction projects, aiming to enhance project performance through improved risk identification, assessment, and mitigation. The research employs the Analytical Hierarchy Process (AHP) to prioritize BIM-based strategies across multiple risk management dimensions, including technical, financial, sustainability, and time management. The findings demonstrate that BIM-financial strategies rank most among BIM-driven risk management, followed by sustainability and time. In contrast, Technical, Operation, and maintenance capabilities have the lowest rank. Given the high priority of BIM financial strategies, it has been applied to conduct sensitivity analysis; the sensitivity analysis results demonstrate the dynamic nature of BIM sub-criteria strategy in response to changes in the weight of financial considerations. As financial concerns diminish, the shift towards sustainability, health, safety, and time efficiency underscores the importance of a more balanced approach in BIM strategy prioritization. BIM- risk management improves project outcomes by enabling real-time data-driven decision-making, enhancing stakeholder collaboration, and optimizing resource use, cost control, and sustainability. This research contributes to theoretical and practical advancements in construction risk management, suggesting that BIM can be a transformative tool for optimizing project performance while addressing the complexities and uncertainties inherent in the construction industry.