Evaluation of the pharmaceutical distribution and warehousing companies through an integrated Fermatean fuzzy entropyWASPAS approach
Künye
Aytekin, A., Görçün, Ö. F., Ecer, F., Pamucar, D., & Karamaşa, Ç. (2022). Evaluation of the pharmaceutical distribution and warehousing companies through an integrated Fermatean fuzzy entropy-WASPAS approach. Kybernetes.Özet
Purpose – Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to
successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain
extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the
level of medicine stock and logistics service level. The high stock level held by health institutions indicates that
we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service
providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as
highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable,
and strong methodological frame is required to solve these decision-making problems.
Design/methodology/approach – To achieve this challenging issue, the authors develop and apply an
integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The
evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the
importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS
approach ranks the alternatives.
Findings – The feasibility of the proposed model is also supported by a case study where six companies are
evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated
vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness
and effectiveness of the proposed approach.
Practical implications – The proposed multi-attribute decision model quantitatively aids managers in
selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.
Originality/value – A new model has been developed to present a sound mathematical model for selecting
logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper’s main
contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of
providers.