Leveraging procurement-related knowledge through a fuzzy-based DSS: a refinement of purchasing portfolio models

Purpose: This paper aims to model a decision support system (DSS) that could overcome the oversimplified, subjective, compensatory decision logic of extant purchasing portfolio models (PPMs) by leveraging the firms’ procurement-related knowledge base. Design/methodology/approach: The DSS was developed through a fuzzy-based approach, whose design and application were framed within a case study in a multinational company. Findings: The application of the fuzzy-based DSS to a product class suggests investing in the relationship with two specific suppliers and to loosen the relationship with a third one. Research limitations/implications: Exploiting the fuzzy set theory and fostering the elicitation of procurement-related knowledge from the decision-makers, the DSS effectively tackles the concerns about the existing PPMs by including strategic-oriented priorities and contextual constraints in the evaluation. Practical implications: The recommendations in output from the DSS are feasible, more analytical and easy to interpret, enabling knowledge sharing, group decision processes and better decision-making. Originality/value: To the best of the authors’ knowledge, this manuscript is the first attempt to effectively integrate traditional PPMs with contextual, strategy-related factors to refine the purchasing directions and make them objective.