A supplier selection model for hospitals using a combination of artificial neural network and fuzzy VIKOR. (1st October 2020)

• Record Type: Journal Article
• Authors: Bahadori, Mohammadkarim; Hosseini, Seyed Morteza; Teymourzadeh, Ehsan; Ravangard, Ramin; Raadabadi, Mehdi; Alimohammadzadeh, Khalil
• Is Part Of: International journal of healthcare management. Volume 13:Number 4(2020)
• Page Start: 286
• Page End: 294
• Publication Date: 2020-10-01
• Subjects: Supply chain -- neural network -- fuzzy VIKOR -- hospital -- model -- Multi Criteria Decision Making (MCDM) -- Iran; Health services administration -- Periodicals; Medical care -- Marketing -- Periodicals; 362.1068
• DOI: 10.1080/20479700.2017.1404730
• Languages: English
• ISSNs: 2047-9700

Abstract

ABSTRACT: The supply chain management of medical equipment and consumer goods is full of uncertainties and unexpected issues and one of the major challenges of hospitals is the suppliers' evaluation and selection. study aimed to provide a model for selecting the best supplier in a hospital using a combination of artificial neural network and fuzzy VIKOR. This was a descriptive study conducted in a military hospital in three phases in 2016. The results showed that the most effective factor in supplier selection was 'quality' (weight = 0.165). After that, the highest weights were, respectively, related to 'price', 'timely delivery', 'packaging and transporting quality', 'the supplier's background' and 'payment terms'. According to the results of the present study, the most important factor influencing the supplier selection was 'quality'. Given the direct impact of medical equipment and consumer goods on patients' recovery and nurses and physicians' proper functioning and performance, it can be recommended that the hospital managers and the staff of purchasing unit should develop the quality assessment protocol of equipment and supplies and it should be evaluated periodically by nurses, physicians and patients.