Abstract:

Digital transformation has driven a profound evolution in purchasing and procurement processes, particularly in supplier selection and order allocation activities. These processes, historically operational and reliant on expert judgment, are increasingly becoming highly sophisticated analytical practices supported by data-driven Artificial Intelligence (AI) models. This article proposes a curricular framework to integrate these methodologies into the Purchasing and Procurement course within the Master’s program in Organizational and Logistics Engineering. The proposal aims to equip students with advanced analytical competencies, enabling them to understand and apply predictive models, classifiers, segmentation techniques, data-based risk analysis, and intelligent scoring methodologies. Furthermore, the paper presents a pedagogical analysis that justifies the need for this integration, an updated state-of-the-art review, practical activity proposals, and a teaching roadmap to facilitate its implementation.

Keywords:

Data-driven, Supplier Selection, Order Allocation, Artificial Intelligence, Purchasing, Procurement.