On solving a healthcare supplier selection problem using MCDM methods in intuitionistic fuzzy environment

Presence of numerous competing suppliers along with conflicting evaluation criteria, increased participation and expectations of the stakeholders having varying interest, uncertainty in demand and supply, and lack and vagueness of information make healthcare supplier selection a challenging task which can be effectively solved with the application of multi-criteria decision making (MCDM) methods in fuzzy environment. This paper proposes a two-stage methodology for solving a supplier selection problem in the Indian healthcare scenario. Four efficient suppliers are first shortlisted from a pool of 25 candidate pharmaceutical suppliers using data envelopment analysis based on nine pivotal financial metrics. In the second stage, three MCDM techniques, in the form of weighted aggregated sum product assessment (WASPAS), combinative distance-based assessment (CODAS) and combined compromise solution (CoCoSo) are individually integrated with intuitionistic fuzzy (IF) set to identify the most apposite healthcare supplier on the basis of five qualitative criteria (cost, delivery time, service, quality and flexibility). It is interestingly noticed that all the adopted MCDM techniques behave similarly in selecting the best supplier in IF environment. A sensitivity analysis with respect to changing criteria weights is also carried out to search out the most robust IF-MCDM method.