DefinePK

Abstract

This paper explores the advancement of economic impact models to enhance data-driven decision-making in strategic procurement practices. Traditional models, while foundational, often fail to address the complexities of modern supply chains and the dynamic nature of today’s economic environments. This study highlights the historical evolution of economic impact modeling, examines current trends in data analytics integration, and identifies gaps in existing approaches. Proposed advancements include leveraging real-time data, predictive analytics, and artificial intelligence to improve model accuracy, scalability, and relevance. The discussion underscores the importance of addressing challenges such as data quality, integration, and regulatory compliance to fully unlock the potential of economic impact models. The implications for practitioners and policymakers are significant, emphasizing the role of advanced modeling techniques in fostering transparency, resilience, and sustainability in procurement. Recommendations for future research include standardized methodologies, technological innovations, and collaborative implementation strategies, ensuring the models remain robust and adaptable in dynamic economic landscapes.
Keywords:  Economic Impact Modeling, Strategic Procurement, Data-Driven Decision-Making, Predictive Analytics, Artificial Intelligence in Procurement, Sustainable Supply Chains.