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Arunyanart S. Performance evaluation of facility locations using integrated DEA-based techniques. Heliyon 2024; 10:e32430. [PMID: 38961966 PMCID: PMC11219358 DOI: 10.1016/j.heliyon.2024.e32430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 05/12/2024] [Accepted: 06/04/2024] [Indexed: 07/05/2024] Open
Abstract
Facility location, particularly in the context of international investments by global enterprises, stands out as a paramount concern within the purview of top management's strategic decision-making process. The selection of a suitable location plays a pivotal role in determining the ultimate achievement of organizational objectives. The process of selecting an appropriate location requires the comprehensive analysis of a substantial volume of data, encompassing diverse tangible and intangible evaluation criteria that may exhibit inherent conflicts. This paper addresses the challenge of determining the best location for a manufacturing facility by employing alternative performance measures within the framework of the data envelopment analysis (DEA) model. In a performance evaluation process, not only positive but also negative aspects should be determined. This paper, therefore, proposes a double-frontier DEA-AR model, which is an integrated approach that incorporates the efficient frontier, anti-efficient frontier, and assurance region weight restrictions, with the aim of increasing the discrimination ability of the DEA method. An efficient frontier evaluates the information of each location from a positive viewpoint, while the worst side is evaluated by an anti-efficient frontier. The technique of weight restrictions, which allows incorporating expert opinion into the assessment, is also applied with both frontiers to restrict the regions of weights to some specific area. The prescribed approach is illustrated by a numerical example of selecting the best location among ten different countries under consideration of 22 selection criteria obtained from PEST analysis. The results show that the proposed alternative performance measures significantly improve discrimination capability, enabling the ranking of candidates based on their suitability for the optimal location.
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Affiliation(s)
- Sirawadee Arunyanart
- Supply Chain and Logistics System Research Unit, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand
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Saleh N, Gamal O, Eldosoky MAA, Shaaban AR. An integrative approach to medical laboratory equipment risk management. Sci Rep 2024; 14:4045. [PMID: 38374369 PMCID: PMC10876531 DOI: 10.1038/s41598-024-54334-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 02/12/2024] [Indexed: 02/21/2024] Open
Abstract
Medical Laboratory Equipment (MLE) is one of the most influential means for diagnosing a patient in healthcare facilities. The accuracy and dependability of clinical laboratory testing is essential for making disease diagnosis. A risk-reduction plan for managing MLE is presented in the study. The methodology was initially based on the Failure Mode and Effects Analysis (FMEA) method. Because of the drawbacks of standard FMEA implementation, a Technique for Ordering Preference by Similarity to the Ideal Solution (TOPSIS) was adopted in addition to the Simple Additive Weighting (SAW) method. Each piece of MLE under investigation was given a risk priority number (RPN), which in turn assigned its risk level. The equipment performance can be improved, and maintenance work can be prioritized using the generated RPN values. Moreover, five machine learning classifiers were employed to classify TOPSIS results for appropriate decision-making. The current study was conducted on 15 various hospitals in Egypt, utilizing a 150 MLE set of data from an actual laboratory, considering three different types of MLE. By applying the TOPSIS and SAW methods, new RPN values were obtained to rank the MLE risk. Because of its stability in ranking the MLE risk value compared to the conventional FMEA and SAW methods, the TOPSIS approach has been accepted. Thus, a prioritized list of MLEs was identified to make decisions related to appropriate incoming maintenance and scrapping strategies according to the guidance of machine learning classifiers.
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Affiliation(s)
- Neven Saleh
- Electrical Communication and Electronic Systems Engineering Department, Faculty of Engineering, October University for Modern Sciences and Arts (MSA), 6th of October City, Giza, Egypt.
- Systems and Biomedical Engineering Department, Higher Institute of Engineering, Shorouk Academy, Al Shorouk City, Cairo, Egypt.
| | - Omnia Gamal
- Biomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt
| | - Mohamed A A Eldosoky
- Biomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt
| | - Abdel Rahman Shaaban
- Systems and Biomedical Engineering Department, Higher Institute of Engineering, Shorouk Academy, Al Shorouk City, Cairo, Egypt
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Banik B, Alam S, Chakraborty A. Comparative study between GRA and MEREC technique on an agricultural-based MCGDM problem in pentagonal neutrosophic environment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY : IJEST 2023; 20:1-16. [PMID: 36817165 PMCID: PMC9928147 DOI: 10.1007/s13762-023-04768-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 12/16/2022] [Accepted: 01/06/2023] [Indexed: 06/18/2023]
Abstract
In this research article, an improved Multi-criteria group decision-making (MCGDM) strategy has been developed in pentagonal neutrosophic environment incorporating grey relational analysis and method on the removal effects of criteria (MEREC) techniques to address the relative advantages and disadvantages of these aspects in MCGDM. The aim of the study is to improve MCGDM technique which can capture the underlying uncertainties in robust way and can produce consistent results in a more rigorous way. Here, the conception of Hamming distance between two pentagonal neutrosophic number (PNN)s is introduced and the weighted arithmetic and geometric averaging operators in PNN arena are deployed to craft our computational technique more progressive and robust. An agriculture-based numerical problem is illustrated to demonstrate the ranking results of the alternatives by both of the techniques. After evaluating the problem by two aggregation operators, it is found that "plantation crop" is the best alternative under certain circumstances. Lastly, the sensitivity investigation is performed which reveals that with the appliance of arithmetic and geometric aggregation operators the best ranked alternative preserves its position by both of the ranking methods, which definitely exhibit the consistency and robustness of our executed methodology.
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Affiliation(s)
- B. Banik
- Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, 711103 India
| | - S. Alam
- Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, 711103 India
| | - A. Chakraborty
- Department of Engineering Science, Academy of Technology, Adisaptagram, West Bengal 712502 India
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Shang C, Saeidi P, Goh CF. Evaluation of circular supply chains barriers in the era of Industry 4.0 transition using an extended decision-making approach. JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT 2022. [DOI: 10.1108/jeim-09-2021-0396] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
PurposeThe poor leadership style is a key obstacle to the effective implementation of Industry 4.0 technologies. To successfully apply the Industry 4.0 technologies, which can enhance the sustainability of firms, senior management needs to be inspiring and transformational. On the other hand, numerous factors can hinder the Industry 4.0 transition and “Circular Supply Chain (CSC)” transformation. Therefore, the main purpose of this study is to evaluate the related barriers of CSCs in the era of Industry 4.0 transition.Design/methodology/approachThe current study developed an innovative decision-making approach with the help of the “Combined Compromise Solution (CoCoSo)” method and “Criteria Importance Through Intercriteria Correlation (CRITIC)” method on the “q-Rung Orthopair Fuzzy Sets (q-ROFSs).” CRITIC in this combined method was used to predict the importance or weighting degrees of the CSCs barriers in the age of Industry 4.0 transition.FindingsThe results of this study found that the absence of knowledge about the Industry 4.0 technologies and circular approaches was the first barrier followed by the problems associated with data security in relationship management in circular flows, the deficiency of knowledge regarding the data management among stakeholders and the lack of awareness about the potential benefits of autonomous systems in labor-oriented “End-of-Life (EOL)” activities for CSCs in the era of Industry 4.0 transition.Research limitations/implicationsA limitation may be that despite the generalizability of the proposed framework, the results may differ when it is implemented in different sectors. By emphasizing the obstacles to sustainable operations of supply chains (SCs) in the context of circular economy (CE) and Industry 4.0, researchers working in the same domain may be encouraged to find ways to remove such obstacles in different settings. As suggested in this study, the priority of various barriers helps researchers suggest effective strategies for the sustainable development of companies within the current dynamic business atmosphere.Practical implicationsThe findings of this paper can aid industry practitioners in fixing their attention on the digitization or automation of their systems in the context of sustainability or resource circularity. Note that within the current context of CE, one of the crucial issues is how to conserve the existing resources; the answer to this question can save the environment.Originality/valueThe current paper proposed a new multi-criteria decision-making method using q-ROFSs to analyze, rank and evaluate the CSC barriers in the age of Industry 4.0 transition. To this end, a new decision-making approach with the help of CRITIC and CoCoSo methods on q-ROFSs called q-ROF-CRITIC-CoCoSo was introduced to evaluate the CSCs barriers in the era of Industry 4.0 transition.
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Boyacı AÇ, Şişman A. Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:1985-1997. [PMID: 34357491 PMCID: PMC8342988 DOI: 10.1007/s11356-021-15703-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 07/24/2021] [Indexed: 05/25/2023]
Abstract
COVID-19 poses many challenges for hospitals around the world. Each country attempts to solve the problems in its hospitals using different methods. In Turkey, two pandemic hospitals were built in İstanbul, the most crowded province. In addition, some hospitals were designated as pandemic hospitals. This study focuses on the methods used for site selection for a pandemic hospital in Atakum, a district of Samsun City, Turkey. As a solution to the problem, initially, spatial analysis was performed using GIS to produce maps based on seven criteria obtained from the insight of an expert team. Analytic hierarchy process (AHP) augmented by interval-valued Pythagorean fuzzy numbers (PFNs) was then used to determine weights for the criteria. Distance to transportation network was the most important criterion influencing the selection process and the least significant one was the distance to fire stations. Based on the criteria weights, and five rules specified by the expert team, 13 suitable locations for a pandemic hospital were determined using GIS. The technique for order preference by similarity to ideal solution (TOPSIS) method was used to determine the final ranking of 13 alternative locations (A1-A13). A10 was identified as the most appropriate site and A11 as the least appropriate site for a pandemic hospital. Finally, sensitivity analysis was performed to investigate how changes in weight values of the criteria affect the ranking of the alternatives.
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Affiliation(s)
- Aslı Çalış Boyacı
- Department of Industrial Engineering, Ondokuz Mayıs University, 55139, Samsun, Turkey.
| | - Aziz Şişman
- Department of Geomatics Engineering, Ondokuz Mayıs University, 55139, Samsun, Turkey
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Mishra AR, Rani P, Pandey K. Fermatean fuzzy CRITIC-EDAS approach for the selection of sustainable third-party reverse logistics providers using improved generalized score function. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2022; 13:295-311. [PMID: 33584868 PMCID: PMC7871958 DOI: 10.1007/s12652-021-02902-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 01/09/2021] [Indexed: 05/17/2023]
Abstract
In today's world, the demand for sustainable third-party reverse logistics providers (S3PRLPs) becomes an increasingly considerable issue for industries seeking improved customer service, cost reduction and sustainability perspectives. However, the assessment and selection of right S3PRLP is a complex uncertain decision-making problem due to involvement of numerous conflicting attributes, imprecise human mind and lack of information. Recently, Fermatean fuzzy set (FFS) has been recognized as one of the suitable tools to tackle the uncertain and inaccurate information. In this paper, we introduce a hybrid methodology based on CRITIC and EDAS methods with Fermatean fuzzy sets (FFSs) to solve the S3PRLP selection problem in which the attributes and decision makers' weights are completely unknown. In this framework, CRITIC approach is applied to calculate the attribute weight and EDAS method is used to evaluate the priority order of S3PRLP options. To do this, a new improved generalized score function (IGSF) is developed with its elegant properties. Also, a formula is discussed to calculate the decision makers' weights based on the developed IGSF. Next, developed framework is applied to assess a case study of S3PRLP selection problem with Fermatean fuzzy information, which elucidates the usefulness and practicality of the proposed method. Finally, comparative study is implemented to show the strength of introduced framework with extant approaches. The outcomes of the work confirm that the introduced approach is more feasible and well-consistent with the other extant approaches.
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Affiliation(s)
| | - Pratibha Rani
- Department of Mathematics, NIT, Warangal, Telangana India
| | - Kiran Pandey
- Department of Mathematics, Bioinformatics and Computer Application, MANIT, Bhopal, MP India
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TUŞ A, AYTAÇ ADALI E. Green Supplier Selection Based on the Combination of Fuzzy SWARA (SWARA-F) and Fuzzy MARCOS (MARCOS-F) Methods. GAZI UNIVERSITY JOURNAL OF SCIENCE 2021. [DOI: 10.35378/gujs.978997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Jafari M, Seyedjavadi M, Zaboli R. Assessment of performance in teaching hospitals: Using multicriteria decision-making techniques. JOURNAL OF EDUCATION AND HEALTH PROMOTION 2020; 9:214. [PMID: 33062747 PMCID: PMC7530430 DOI: 10.4103/jehp.jehp_89_20] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 04/05/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND It is essential to evaluate the performance of hospitals in the health system. Hospitals need a performance evaluation system to develop and compete in order to measure the efficiency and effectiveness of their programs, processes, and human resources. This study aimed to evaluate the performance of teaching hospitals using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and hierarchical analysis. MATERIALS AND METHODS This was a cross-sectional and descriptive study conducted in 2019 in all teaching hospitals affiliated to Shahid Beheshti University of Medical Sciences. The required data were collected using a standard checklist. The collected data were analyzed using the analytic hierarchy process (AHP) and TOPSIS. In the first phase, annual indicators of hospital evaluation were collected. Following the AHP, key performance indicators (KPIs) were selected and prioritized in hospitals. RESULTS The questionnaires were provided to 15 experts to weigh KPIs, and the most important indicators were selected. The results of hierarchical analysis showed that three main indicators in evaluating the performance of hospitals were bed turnover rate, emergency clients, and length of stay. CONCLUSIONS One of the problems in evaluating hospitals is the use of key indicators that alone measure the quantity or quality of their performance. Multicriteria decision-making can be used to determine key indicators first, and then by combining these indicators into a multicriteria decision-making model, a better assessment of the role and performance of hospitals can be provided.
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Affiliation(s)
- Mehdi Jafari
- Department of Health Services Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
- Health Managers Development Institute, Ministry of Health and Medical Education, Tehran, Iran
| | - Maryam Seyedjavadi
- Department of Health Services Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Rouhollah Zaboli
- Department of Health Administration, School of Health, Baqiyatallah University of Medical Sciences, Tehran, Iran
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