A supplier selection model for hospitals using a combination of artificial neural network and fuzzy VIKOR

Bahadori, Mohammadkarim; Hosseini, Seyed Morteza; Teymourzadeh, Ehsan; Ravangard, Ramin; Raadabadi, Mehdi; Alimohammadzadeh, Khalil

doi:10.1080/20479700.2017.1404730

Cited by 60 publications

(34 citation statements)

References 42 publications

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“…In addition, Schmidt et al [10] presented analytical hierarchy process applications in health-care research from 1981 to 2015. Furthermore, Bahadori et al [11] established a model for selecting the best supplier in a military hospital using a combination of artificial neural network and fuzzy multicriteria optimization and compromise solution (VIKOR). They stated that “quality” was the most important criterion for supplier selection in their study.…”

Section: Introductionmentioning

confidence: 99%

Integrated Multicriteria Decision-Making Methods to Solve Supplier Selection Problem: A Case Study in a Hospital

Akcan

Güldeş

2019

Journal of Healthcare Engineering

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In supply chain literature, supplier evaluation and selection problem is one of the most studied subjects because of the significant roles of suppliers in terms of the chain's sustainability and profitability. Therefore, it is important for organizations to adopt a systematic way to evaluate and select the best supplier according to their respective criteria in today's competitive environment. Multicriteria decision-making methods provide for this need of organizations because determination of an appropriate supplier selection is a multicriteria decision-making (MCDM) problem essentially. Although a lot of applications of these methods for supplier evaluation and selection can be seen in the literature, studies in the health-care sector are insufficient. Hospitals in the health-care sector also have to consider their supplier-related decisions to decrease risks and threads which affect their effectiveness. The aim of this study was to fill this gap by providing different hybrid models for selecting the best supplier for hospitals. Supplier evaluation and selection process start with recognizing the related criteria according to the studies in the literature. Analytic hierarchy process (AHP) method is deployed to weight the criteria, and suppliers are listed via technique for order preference by similarity to ideal solution (TOPSIS), elimination and choice translating reality English (ELECTRE), grey relational analysis (GRA), and simple additive weighting (SAW) methods. The main aim of this study was to present different hybrid MCDM methods and show their efficiency and consistency with each other. In this study, hybrid multicriteria decision-making models (AHP-TOPSIS, AHP-ELECTRE, AHP-GRA, and AHP-SAW) are presented and compared. The results show that the presented hybrid methods in this study are consistent with each other and give the same ranking for the selection of the best supplier. It can be considered as a useful guideline for hospitals.

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Section: Introductionmentioning

confidence: 99%

Integrated Multicriteria Decision-Making Methods to Solve Supplier Selection Problem: A Case Study in a Hospital

Akcan

Güldeş

2019

Journal of Healthcare Engineering

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“…In addition to these studies, it can also be seen that supplier selection is another important subject in which fuzzy VIKOR approach is taken into account. For instance, Awasthi and Kannan (2016), Sharaf (2019), and Bahadori et al (2017) aimed to select the best supplier by considering this methodology. On the other side, it is understood that there are limited studies in the literature with IT2 fuzzy VIKOR (Liu et al, 2018;Wu et al, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Innovation Performance for Retail Banking Industry With the Hybrid Fuzzy Decision-Making Approach

et al. 2020

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This study aims to evaluate the innovation performance of the Turkish banking industry. For this purpose, eight different financial and nonfinancial criteria are identified as a result of literature review. Moreover, five biggest Turkish deposit banks are selected as alternatives. Interval type 2 fuzzy decision-making trial and evaluation laboratory (IT2 FDEMATEL) is taken into account to weight the dimensions. On the other side, to rank the alternatives, interval type 2 fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (IT2 FVIKOR) approach is considered. The findings show that market share and return on investment are the most important factors in the innovation performance of retail banking services. This situation gives information that the when banks are more successful in the market, they can make investment to the innovation more effectively. The main reason is that these banks have enough capacity to make this kind of investments. Thus, it is recommended that Turkish banks should first make an efficiency analysis to increase their profit margin so that their capacities can be improved. For this purpose, many different factors should be taken into account by Turkish banks, such as personnel competency and technological development. Within this scope, these banks should make financial analysis of the innovation effectively by generating a qualified team. However, necessary research and development activities should be conducted to reach this objective. Hence, it can be possible to minimize ineffective innovation for the banks.

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“…20 14 20 13 4 10 10 15 4 9 2 1 5 Source: Arabzad, et al, 2014;Bahadori, et al, 2017;Bali, S., 2017;Dargi, et al, 2014;Dweiri, et al, 2016;Jain, et al, 2016;Junior & Osiro, 2014;Junior & Carpinetti, 2016;Mirmousa & Dehnavi, 2016;Rezaei, et al, 2014;Rezaei, et al, 2016;Rouyendegh & Saputro, 2014;Sivrikaya, et al, 2015;Sureeyatanapas, et al, 2018;Wan, et al, 2017;Wu, et al, 2016;Zhang, et al, 2015;and Zhong & Yao, 2017 The other consideration made in using AHP & TOPSIS methods in this study is the strengths of those methods relative to those of other alternative MCDM as summarized in Table 3. 1.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative Study Of AHP And AHP-Topsis In Analyzing Supplier Priority (A Case Study Of Diesel Fuel Supplier At PT. X)

Kurniawan

Hamali

Gunawan

2020

jmi

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The selection of diesel fuel supplier at PT. X which were held in four operational areas, namely South Sumatra, Central Kalimantan, West Kalimantan, and East & North Kalimantan. The purpose is to determine the criterias, subcriterias and their importance weights in the selection of the best diesel fuel suppliers for each operational areas of PT. X. This study will compare the use of two well-known multi-criteria decision making methods namely AHP (Analytical Hierarcy Process) and AHP-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The criterias were tested are Quality, Price, Capability, Delivery, Supplier Profile, and Service & Relationship with the results of the highest weighted criteria is Delivery, then followed by the highest weighted subcriteria is Supply Capability. Keywords— AHP, TOPSIS, Supplier Selection, Best Supplier

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A supplier selection model for hospitals using a combination of artificial neural network and fuzzy VIKOR

Cited by 60 publications

References 42 publications

Integrated Multicriteria Decision-Making Methods to Solve Supplier Selection Problem: A Case Study in a Hospital

Integrated Multicriteria Decision-Making Methods to Solve Supplier Selection Problem: A Case Study in a Hospital

Analysis of Innovation Performance for Retail Banking Industry With the Hybrid Fuzzy Decision-Making Approach

Comparative Study Of AHP And AHP-Topsis In Analyzing Supplier Priority (A Case Study Of Diesel Fuel Supplier At PT. X)

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