Under its Vision 2030, Saudi Arabia has heavily invested in mega construction projects such as NEOM and QIDDIYA, where logistics resilience is critical due to environmental, infrastructural, and operational uncertainties. This study proposes an IoT-enabled framework for managing project disruptions via real-time sensing, environmental stress indicators, and predictive modeling. Using a dataset of 1,000 logistics events, multiple statistical and machine learning models were applied to evaluate the impact of IoT deployment on delivery delays caused by disruptions, cost variability, and environmental stress. The findings indicate that IoT integration significantly reduces delay volatility and enhances cost predictability. However, disruptions like traffic and weather partially attenuate these benefits. Environmental stress had a minor but consistent influence on logistics risk exposure. A mediation analysis revealed no significant indirect effect of IoT on delay through environmental stress, suggesting a more direct intervention pathway. A decision dashboard is also proposed to visualize delay triggers and automate risk signaling. Theoretical implications extend the Unified Theory of Acceptance and Use of Technology (UTAUT) to construction logistics, emphasizing real-time sensing as the key performance enabler. Managerial implications suggest full IoT adoption in NEOM and QIDDIYA logistics and real-time SCM dashboarding. Future research may incorporate ensemble learning and edge-based IoT to improve predictive capacity. This study demonstrates the feasibility and strategic value of IoT-based disruption control in transforming mega-infrastructure supply chains.

The complexity and vulnerability of supply chains in today's globalized economy have heightened the significance of understanding and managing disruptions. Supply chain disruptions, ranging from natural disasters to pandemics, can lead to substantial delays, increased costs, and reduced quality, thereby impacting the operational performance and stability of businesses. Considering the theoretical sophistication and substantial relevance of the field, this research seeks to conduct an extensive bibliometric analysis of supply chain disruption. The goal is to offer a thorough summary of recent advancements and ongoing progress in this specific area. Additionally, it aims to pinpoint emerging research patterns that can guide future studies. We performed a bibliometric review of the structure and global trends of disruptions among supply chains, from 1996 to 2024 using techniques such as analysis of (1) the dataset, (2) sources, (3) authors, (4) countries and institutions, (5) documents, and (6) keywords. A total of 1356 bibliographic records from Web of Science databases were analyzed to generate the study’s research data through Scientometrics networks. The paper concludes by discussing the strengths and limitations of the study and suggesting potential avenues for future research, aiming to guide and inform future studies in this critical area of supply chain management. The findings of this study will enhance understanding of the prevailing patterns in this topic, thus laying the groundwork for future research initiatives in this field.

This research paper is a systematic literature review (SLR) based on a theory-grounded analysis of supply chain resilience (SCR) concerning, in particular, resilience capabilities and resilience capability logics. In accordance with PRISMA 2020, 45 peer-reviewed journal articles found in Scopus were identified, screened and analysed. In addition to classifying the resilience capabilities, this review takes a dynamic capabilities and contingency approach to theorize the role resilience capabilities play as interacting logics through the phases of disruption (pre-disruption, during disruption, and post-disruption). The results suggest 7 central resilience capabilities (flexibility, redundancy, agility, collaboration, visibility, robustness and adaptability) that are grouped into three higher-order capability logics (buffering, adaptive and transformational). It has systematic trade-offs between efficiency and resilience, is characterized by a pre-eminent focal-firm bias, and limited longitudinal and multi-tier research are revealed in the review. This study lays these contributions on process-oriented resilience capability logic framework and sequencing of capability, shifting the capability enumeration to a capability configuration and sequencing to enhance theory development in supply chain resilience. Theoretically based coding scheme drew on the dynamic capabilities theory (sensing, seizing, reconfiguring) and contingency logic in order to discover underlying capability mechanisms.