A fuzzy multi-criteria decision analysis approach for risk evaluation in healthcare logistics outsourcing: Case of Morocco. (August 2020)

• Record Type: Journal Article
• Authors: Mokrini, Asmae El; Aouam, Tarik
• Is Part Of: Health services management research. Volume 33:Number 3(2020)
• Page Start: 143
• Page End: 155
• Publication Date: 2020-08
• Subjects: fuzzy multi-criteria decision analysis -- healthcare logistics -- outsourcing -- public–private partnerships -- risk evaluation; Public health administration -- Research -- Periodicals; Public health administration -- Study and teaching (Higher) -- Periodicals; Health services administration -- Research -- Periodicals; Health services administration -- Study and teaching (Higher) -- Periodicals; 362.1072
• DOI: 10.1177/0951484820901668
• Languages: English
• ISSNs: 0951-4848

Abstract

Public–private partnerships in emerging countries are gradually considered a tool for growth development. One particular public–private partnership is that of outsourcing logistics in the healthcare sector. These partnerships provide several benefits for both private and public sectors but are generally associated with numerous risks that must be evaluated and subsequently managed. The aim in this paper is to develop a risk evaluation approach to rank risks when decision makers' judgment is taken into consideration and where traditional risk evaluation techniques become less applicable. The proposed approach makes use of fuzzy multi-criteria decision analysis methods since they are efficient techniques to rank alternatives based on selected evaluation criteria and can accommodate human judgment and preferences. The approach treats predetermined risks like alternatives, and evaluation criteria are represented by areas of impact of the risks. To validate the approach, we applied it to a real case of logistics outsourcing to private service providers in a Moroccan public pharmaceutical supply chain. The ranking results obtained show that the two methods lead to some differences in ranking but are highly correlated. The obtained results support healthcare policy makers in setting priorities to effectively deploy preventive and mitigation efforts.