Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment

• This paper investigates the dichotomy between theory and practice in supplier selection.
• A model based on analytic hierarchy process and fuzzy set theory is proposed and evaluated.
• The implementation and the usability of the model in a real-world scenario are tested.
• Managerial implications deriving from the implementation process are discussed.

In the contemporary global market, supplier selection represents a crucial process for enhancing firms’ competitiveness. In firms operating in low-complexity sectors, supplier selection generally leverages on few significant variables (price, delivery time, quality) and it is often left to the buyers’ experience. On the other hand, in industries characterised by remarkable product complexity, supplier selection systems gain the characteristics of a multi-stakeholder and multi-criteria problem, which needs to be theoretically formalised and realistically adapted to specific contexts.An increasing number of researches have been devoted to the development of different methodologies to cope with this problem. Nevertheless, while the number of applications is growing, there is little empirical evidence of the practical usefulness of such tools, that are mainly tested on numerical examples or computational experiments and focused on a dyadic version of the problem, overlooking the wider set of actors involved in the decision-making problem. The result is a clear dichotomy between academic theory and business practice.Therefore, the paper contributes to understand the above dichotomy by evaluating the applicability to real-world multi-stakeholder problems of the two main approaches proposed in the literature to deal with supplier selection, the analytic hierarchic process (AHP) and the fuzzy set theory (FST). Based on an industrial case study, a thorough discussion is developed, dealing with the issues arising during the implementation and practical functioning of such decision support systems, also providing provide practical guidelines and managerial implications.