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

Abstract

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.

Citation

Aloini, D., Dulmin, R., Mininno, V. and Zerbino, P. (2019), "Leveraging procurement-related knowledge through a fuzzy-based DSS: a refinement of purchasing portfolio models", Journal of Knowledge Management, Vol. 23 No. 6, pp. 1077-1104. https://doi.org/10.1108/JKM-10-2018-0614