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<p>This study examines the Internet of Things (IoT) impact on supply chain (SC) performance and cost minimization. Using system dynamics (SD), we analyze variables like product quality, waste, energy use, and operational costs. SD simulates variable behavior over time, capturing complex, nonlinear interactions affecting SC efficiency. The mathematical model incorporates functions estimated through SD and regression to optimize cost minimization in the SC. A significant outcome of this study is the calculation of an optimal adaptation rate, found to be 65%, at which costs reach their minimum. Findings reveal that product waste peaks around the 20-month mark and then gradually declines, while IoT implementation costs increase initially but stabilize as the adoption rate grows. To evaluate the potential impact of IoT on SC performance and sustainability, scenarios were developed, varying in IoT utilization and product quality enhancement. The results show that both higher IoT adoption and improved product quality independently lead to better system performance by reducing waste, saving costs, and increasing reliability. Furthermore, comparative analysis between conventional and IoT-based SCs reveals that the IoT-enabled SC significantly lowers product waste and energy costs across multiple periods. These findings confirm the role of IoT in driving both economic and environmental sustainability. Sensitivity analysis also highlights that strategic investments in quality improvement and production capacity not only enhance profitability but also strengthen long-term resilience and resource efficiency. Overall, IoT adoption emerges as a key enabler for sustainable and cost-effective SC operations.</p>

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Optimizing Supply Chain Sustainability through IoT Adoption: A System Dynamics and Mathematical Modeling Approach

  • 期刊论文

  • 发表日期：

    2025年11月3日

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  • Azam Modares,
  • Nasser Motahari Farimani,
  • Kimia Abdari

摘要

This study examines the Internet of Things (IoT) impact on supply chain (SC) performance and cost minimization. Using system dynamics (SD), we analyze variables like product quality, waste, energy use, and operational costs. SD simulates variable behavior over time, capturing complex, nonlinear interactions affecting SC efficiency. The mathematical model incorporates functions estimated through SD and regression to optimize cost minimization in the SC. A significant outcome of this study is the calculation of an optimal adaptation rate, found to be 65%, at which costs reach their minimum. Findings reveal that product waste peaks around the 20-month mark and then gradually declines, while IoT implementation costs increase initially but stabilize as the adoption rate grows. To evaluate the potential impact of IoT on SC performance and sustainability, scenarios were developed, varying in IoT utilization and product quality enhancement. The results show that both higher IoT adoption and improved product quality independently lead to better system performance by reducing waste, saving costs, and increasing reliability. Furthermore, comparative analysis between conventional and IoT-based SCs reveals that the IoT-enabled SC significantly lowers product waste and energy costs across multiple periods. These findings confirm the role of IoT in driving both economic and environmental sustainability. Sensitivity analysis also highlights that strategic investments in quality improvement and production capacity not only enhance profitability but also strengthen long-term resilience and resource efficiency. Overall, IoT adoption emerges as a key enabler for sustainable and cost-effective SC operations.