Interplay Of Demand Forecasting, Resource Allocation, Supply Chain Resilience, And Technology Integration in Inventory Management Systems for Disaster Evacuation Centers
Keywords:
Digital Transformations, Humanitarian Logistics, Logistic SystemsAbstract
This research aims to analyze the interrelationships between four key variables demand forecasting, resource allocation, supply chain resilience, and technology integration and their collective impact on the effectiveness of inventory management systems in disaster evacuation centers. This study seeks to understand how these variables influence and contribute to improving the overall operational efficiency of evacuation centers during emergency responses. A quantitative research methodology was employed, using a cross-sectional survey distributed to professionals in disaster relief and logistics operations. Data collected were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SMART PLS software. This method allowed for the exploration of both direct and moderating effects between the variables, providing a comprehensive understanding of their interactions and their influence on inventory management effectiveness. The results demonstrate significant positive relationships between the four variables. Demand forecasting and resource allocation were found to have strong but not significant direct effects on the efficiency of inventory management, while supply chain resilience contributed to maintaining operational stability during disruptions. Technology integration emerged as a critical moderating factor, enhancing the impact of the other variables by improving coordination, decision-making, and real-time tracking of resources. The findings suggest that investing in advanced forecasting tools, resilient supply chain systems, and technology-driven solutions can significantly improve the preparedness and responsiveness of disaster evacuation centers. These insights offer practical recommendations for disaster logistics practitioners seeking to optimize resource management in emergency situations.
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