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.
The DSS was developed through a fuzzy-based approach, whose design and application were framed within a case study in a multinational company.
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.
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.
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.
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.
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
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