Decision support model for supplier selection in healthcare service delivery using analytical hierarchy process and artificial neural network

Abstract

The healthcare industry today has grown rapidly and emphasizing the efficiency and effectiveness within the healthcare delivery systems has become a major priority in the field. In order to increase the satisfaction and safety of patient, hospitals must improve their overall performance. We established from our review that a number of models have been developed for supplier selection using diverse methods. Most of the models were used to evaluate the performance of healthcare service sector but there is little emphasis on suppliers of health service facilities. And also to the best of our search, we could not find research works on models for evaluating and selecting suppliers in the healthcare unit of tertiary institution. Hence our focus in this study is to develop a decision support model for evaluating and selecting suppliers in the healthcare service of universities. The use of manual techniques for supplier selection in healthcare unit of universities in developing countries is quite tedious and inefficient particularly when several criteria are taken into consideration. These make decision making difficult and also cause the health centre to frequently stock out. Moreover deciding when to order and how much to order is not very easy and hence not meeting patients' demands adequately. This study focuses on investigating and developing a decision support model for evaluating and selecting suppliers in the healthcare service of tertiary institutions using analytical hierarchy process (AHP) and artificial neural network (ANN). Our case study is the health center of Redeemers University, Nigeria. According to the Overall Priority Vector, the priority values for the respective criteria are: Quality = 0.2192, Service = 0.2160, Delivery = 0.2102, Cost = 0.1968 and Risk = 0.1860. Our results revealed that the quality of product supply by the supplier is the most important criterion, while the risk on the supplies is the least important. To improve on the accuracy of these results, the AHP model was supplemented by a 3-layer artificial neural network, adding a learning component to the model. The result also shows that quality is the most important criterion, but with a high index of 0.6845 as opposed to 0.2192 for the AHP alone. This shows that the hybrid model is much better than the AHP alone.

Minimizing OHS Risks with Spherical Fuzzy Sets as a Verdict to Inventory Management: A Case Regarding Energy Companies

“…e number of certified suppliers for items grouped under Steel Fittings is again three possible 12) was employed to create aggregated SFS-SAW evaluation matrices. e criteria set was created in the light of the performed delineated literature review [57][58][59][60][61][62][63][64][65][66][67][68] and the eld knowledge of DMs. Dickson [69] conducted one of the rst and most comprehensive studies on supplier selection problem through a questionnaire research applied to 273 randomly selected purchasing experts and executives from the National Association of Purchasing, USA.…”

Supplier evaluation and Selection. A review

“…AHP permits some little irregularity in judgment on the grounds that human is not generally consistence. The proportion scales are obtained from the principal eigenvectors and the consistency file is obtained from the major eigenvalue Fashoto et al, 22 . Advantages of AHP include: Presenting the purchaser with a decent picture of the supplier's execution by utilizing the hierarchy of the criteria and assessing the suppliers 23 stability and flexibility because an existing model can be changed.…”

EDAS ve WASPAS yöntemleriyle tıbbi malzeme tedarikçisi belirleme

“…Fiyat, teknik yeterlilik, hizmet kalitesi, tamir hizmeti ve garanti politikası [15] Ekonomik, çevresel ve sosyal [18] Kalite, fiyat, müşteri servisi, geçmiş deneyimi, dönüş hızı ve teslim süresi [19] Kalite, teslimat, teknoloji, imaj, çevre işleri, esneklik, bilgi sistemi, fiyat ve çevresel riskler [20] Fiyat, servis, teslimat, risk ve kalite [21] Satın alma fiyatı, kalite, tepki süresi, teslimatta güvenilirlik, son kullanma tarihi [22] Fiyat, kalite, zamanında teslimat, ödeme koşulları, tedarikçinin geçmişi, paketleme ve nakliye kalitesi [23] Atık yönetim maliyeti, tedarikçi ayrıntıları, atık işleme prosedürü, atık arıtma [24] Kalite, zamanında teslimat, güven, itibar, esneklik, önceki işbirliği deneyimi, mali durum, fiyat, teslim süresi, sağlanabilecek malzeme miktarı [25] Maliyet, tedarikçi durumu, teslim süresi, kalite [26] Fiyat ve maliyetler, kalite, tedarikçi profili, teslimat, esneklik [27] Satın alma maliyeti, ürün kalitesi, finansal istikrar, teslimat performansı, bina ve tesis, personel [92] Fiyat, teslimat, servis, esneklik ve ilişki [93] Maliyet, kalite, hizmetler, teslimat, tedarikçi profili [94] Maliyet, kalite, hizmetler, diğer, tedarikçi profili, risk [95] Kalite, maliyet, mevzuata uygunluk, hizmet güvenilirliği, risk yönetimi, tedarikçi profili, yeşil satın alma [96] Tedarik kapasitesi, üretim kapasitesi, tepki süresi, üretim teknolojisi, fiyat, garanti, prosedürel uygunluk, satın alma işlemi, iletişim sistemi, kalite, tamamlanan sevkiyat belgesi, miktar, zamanında teslimat, mali durum, yer, itibar, yönetim ve organizasyon [97] Tablo 3. Kriterlerin Tedarikçileri değerlendirmek için gerekli olan nihai kriter ağırlıklar, Tablo 5'de verilen sıralamalarda aynı indisli kriterlerin aritmetik ortalaması alınarak belirlenmiştir.…”

“…Adım: Her bir seçenğin nisbi performansı, seçeneklerin kriterlere göre kuvvetlerinin çarpımı alınarak bulunur. Denklem(21) ile bu durum ifade edilmiştir.…”