Toward SCOR 5.0: Integrating AI, IoT, and Green Metrics for Next-Generation Supply Chain Performance Management - Adieb Mursyada; Abdul Hamid; Galang Setia Budi; Nazriel Fahri Saifulloh (Logistic and Operation Management Research (LOMR), 2025)
The convergence of Artificial Intelligence (AI), the Internet of Things (IoT), and sustainability metrics is reshaping supply chain management, yet comprehensive frameworks that unify these elements remain limited. This study aims to propose a conceptual advancement, SCOR 5.0, by systematically reviewing literature from 2020 to 2025 that addresses AI, IoT, and green performance within the SCOR (Supply Chain Operations Reference) framework. Following PRISMA guidelines, 46 peer-reviewed studies were thematically analyzed and synthesized across the five SCOR process areas: Plan, Source, Make, Deliver, and Return. The findings reveal that AI improves predictive accuracy, enhances decision-making, and optimizes sourcing and manufacturing. IoT facilitates real-time tracking, agile delivery, and system-wide visibility. Green metrics, when embedded into SCOR, align performance with sustainability goals, but adoption remains inconsistent. Additionally, the study underscores the moderating role of Green Digital Learning (GDL) in supporting digital readiness and employee capacity building. While the study outlines a proposed SCOR 5.0 model integrating AI, IoT, and green KPIs, it identifies significant implementation barriers, including high costs, regulatory constraints, skill shortages, and a lack of standard metrics. The review highlights a pressing need for empirical validations, testbeds, and impact-assessment tools that can translate theoretical models into practice. This research contributes a synthesized framework and outlines actionable paths forward for both scholars and practitioners.