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Datsyuk P, Dinçer H, Yüksel S, Mikhaylov A, Pinter G. Comparative analysis of hydro energy determinants for European Economies using Golden Cut-oriented Quantum Spherical fuzzy modelling and causality analysis. Heliyon 2024; 10:e26506. [PMID: 38463869 PMCID: PMC10920175 DOI: 10.1016/j.heliyon.2024.e26506] [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: 05/05/2023] [Revised: 02/04/2024] [Accepted: 02/14/2024] [Indexed: 03/12/2024] Open
Abstract
This article presents a comparative analysis of the determinants of hydropower for European economies using Golden Cut oriented Quantum Spherical fuzzy modelling and causality analysis in 24 European countries over the period 2001-2020. The indicators chosen for the analysis are inflation, population, GDP per capita, CO2 and hydropower consumption. The analysis shows that the selected groups of countries are characterised by an inverse relationship between GDP per capita and hydropower consumption, suggesting a bi-directional causal relationship, which also confirms the novelty of this paper. Furthermore, another analysis is carried out using the fuzzy decision-making methodology. In this framework, the directions of influence of the five selected indicators are constructed: GDP per capita (criterion 1, D = 88.656, E = 88.083), hydropower consumption (criterion 2, D = 89.471, E = 88.677), population (criterion 3, D = 87.705, E = 89.228), CO2 emissions (criterion 4, D = 88.578, E = 89.186) and inflation (criterion 5, D = 88.943, E = 88.180). The Quantum Spherical fuzzy methodology is used for this purpose. The values of D and E are measures of the sum of the rows and columns of the overall relationship matrix. Hydropower consumption is the main criterion. It is understood that two different analyses give similar results, namely the bidirectional causal relationship between criteria 1 and 2.
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Affiliation(s)
- Polina Datsyuk
- Financial Faculty, Financial University Under the Government of the Russian Federation, Moscow, 125993, Russian Federation
| | - Hasan Dinçer
- The School of Business, İstanbul Medipol University, İstanbul, Turkey
- Clinic of Economics, Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str. 6, Baku, AZ1141, Azerbaijan
| | - Serhat Yüksel
- The School of Business, İstanbul Medipol University, İstanbul, Turkey
- Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon
- Clinic of Economics, Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str. 6, Baku, AZ1141, Azerbaijan
| | - Alexey Mikhaylov
- Financial Markets and Financial Engineering Department, Financial University under the Government of the Russian Federation, Moscow, Russian Federation
| | - Gabor Pinter
- Faculty of Engineering, Soós Ernő, Research and Development Center, Renewable Energy Research Group, University of Pannonia, Veszprém, 8200, Hungary
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Mahmood T, Rehman UU, Emam W, Ali Z, Wang H. Partitioned dual Maclaurin symmetric mean operators based on picture fuzzy sets and their applications in multi-attribute decision-making problems. Sci Rep 2023; 13:20834. [PMID: 38012182 PMCID: PMC10682484 DOI: 10.1038/s41598-023-44344-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 10/06/2023] [Indexed: 11/29/2023] Open
Abstract
The partitioned Dual Maclaurin symmetric mean (PDMSM) operator has the supremacy that can justify the interrelationship of distinct characteristics and there are a lot of exploration consequences for it. However, it has not been employed to manage "multi-attribute decision-making" (MADM) problems represented by picture fuzzy numbers. The basic inspiration of this identification is to develop the novel theory of picture fuzzy PDMSM operator, and weighted picture fuzzy PDMSM operator and to identify their important results (Idempotency, Monotonicity, and Boundedness). Further, to identify the best decision, every expert realized that they needed the best way to find the beneficial optimal using the proper decision-making procedure, for this, we diagnosed the MADM tool in the consideration of deliberated approaches based on PF information. Finally, to drive the characteristics of the invented work, several examples are utilized to test the manifest of the comparative analysis with various more existing theories, which is a fascinating and meaningful technique to deeply explain the features and exhibited of the proposed approaches.
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Affiliation(s)
- Tahir Mahmood
- Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad, Pakistan.
| | - Ubaid Ur Rehman
- Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad, Pakistan
| | - Walid Emam
- Department of Statistics and Operations Research, Faculty of Science, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia
| | - Zeeshan Ali
- Department of Mathematics and Statistics, Riphah International University Islamabad, Islamabad, Pakistan
| | - Haolun Wang
- School of Economics and Management, Nanchang Hangkong University, Nanchang, 330063, China
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Uddin A, Ali Y, Sabir M, Petrillo A, De Felice F. Circular economy and its implementation in cement industry: A case point in Pakistan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 898:165605. [PMID: 37474051 DOI: 10.1016/j.scitotenv.2023.165605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 07/11/2023] [Accepted: 07/15/2023] [Indexed: 07/22/2023]
Abstract
The cement industry contributes substantially to world emissions. Sustainable and circular practices are adopted globally to mitigate such emissions. Developing countries like Pakistan lack adaptation to circular and sustainable practices. The study proposes an alternative mix of coal and crop residues that can be used for cement production. The study aims to find the best mixtures of coal with crop residue for combustion purposes in cement industries. The Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA) are implemented for the environmental and economic viability of the proposed material mixtures. Moreover, the study seeks to explore risks associated with the implementation of circular practices in the cement industry of a developing country. The study adopts Modified Safety Improvement Risk Assessment (SIRA) for assessing the risks. The results suggest that the partial replacement of coal with bagasse is the most viable mixture with lower environmental emissions and is economically feasible among other alternate mixtures. In terms of risk assessment, there is a lack of governmental support for adopting circular economy (CE) practices and profit uncertainties of these CE practices.
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Affiliation(s)
- Azfar Uddin
- MS in Engineering Management, School of Management Sciences, Ghulam Ishaq Khan Institute of Engineering Sciences & Technology, Topi, Swabi, KPK, Pakistan.
| | - Yousaf Ali
- School of Management Sciences, Ghulam Ishaq Khan Institute of Engineering Sciences & Technology, Topi, Swabi, KPK, Pakistan.
| | - Muhammad Sabir
- NUST Business School, National University of Science and Technology, Islamabad, Pakistan
| | - Antonella Petrillo
- Department of Engineering, University of Naples "Parthenope", Italy, Isola C4, Centro Direzionale Napoli, 80143 Napoli (NA), Italy.
| | - Fabio De Felice
- Department of Engineering, University of Naples "Parthenope", Italy, Isola C4, Centro Direzionale Napoli, 80143 Napoli (NA), Italy.
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Kaya SK. A novel two-phase group decision-making model for circular supplier selection under picture fuzzy environment. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:34135-34157. [PMID: 36508096 DOI: 10.1007/s11356-022-24486-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 11/26/2022] [Indexed: 06/18/2023]
Abstract
Circular supply chain management (CSCM), which incorporates circular thinking into supply chain management, promotes supply chain sustainability by offering a novel and compelling viewpoint. In the CSCM, supplier selection is crucial in establishing a competitive edge among businesses by decreasing environmental degradation and related supply chain expenses. This paper aims to propose a novel two-phase group decision-making approach, which combines the picture fuzzy Analytical Hierarchical Process (PF-AHP) and grey Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS-G) model to select railway material suppliers within the scope of circular economy perspective. In group decision-making, a picture fuzzy number-based approach aggregates individual decision makers'(DMs) opinions and provides a lower level of computing complexity and a higher level of performance. The PF-AHP has been used to produce the weights of the criteria, and the MARCOS-G technique has been used to rank the suppliers and choose the most appropriate one. The results and verification of the novel method are carried out throughout a comprehensive sensitivity analysis. For this purpose, 50 scenarios with changes in the weight values of criteria were developed. In the validation analysis, a comparison with other grey COPRAS, TOPSIS, ARAS and WASPAS methods were performed. Due to the ranking results obtained from Spearman's correlation analyses, the MARCOS-G is almost consistent and it can be seen that the A4 remains the top supplier in all 50 scenarios.
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Simic V, Ebadi Torkayesh A, Ijadi Maghsoodi A. Locating a disinfection facility for hazardous healthcare waste in the COVID-19 era: a novel approach based on Fermatean fuzzy ITARA-MARCOS and random forest recursive feature elimination algorithm. ANNALS OF OPERATIONS RESEARCH 2022; 328:1-46. [PMID: 35821664 PMCID: PMC9263821 DOI: 10.1007/s10479-022-04822-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/07/2022] [Indexed: 05/09/2023]
Abstract
Hazardous healthcare waste (HCW) management system is one of the most critical urban systems affected by the COVID-19 pandemic due to the increase in waste generation rate in hospitals and medical centers dealing with infected patients as well as the degree of hazardousness of generated waste due to exposure to the virus. In this regard, waste network flow would face severe problems without taking care of hazardous waste through disinfection facilities. For this purpose, this study aims to develop an advanced decision support system based on a multi-stage model that was combined with the random forest recursive feature elimination (RF-RFE) algorithm, the indifference threshold-based attribute ratio analysis (ITARA), and measurement of alternatives and ranking according to compromise solution (MARCOS) methods into a unique framework under the Fermatean fuzzy environment. In the first stage, the innovative Fermatean fuzzy RF-RFE algorithm extracts core criteria from a finite set of initial criteria. In the second stage, the novel Fermatean fuzzy ITARA determines the semi-objective importance of the core criteria. In the third stage, the new Fermatean fuzzy MARCOS method ranks alternatives. A real-life case study in Istanbul, Turkey, illustrates the applicability of the introduced methodology. Our empirical findings indicate that "Pendik" is the best among five candidate locations for sitting a new disinfection facility for hazardous HCW in Istanbul. The sensitivity and comparative analyses confirmed that our approach is highly robust and reliable. This approach could be used to tackle other critical multi-dimensional problems related to COVID-19 and support sustainability and circular economy. Supplementary Information The online version contains supplementary material available at 10.1007/s10479-022-04822-0.
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Affiliation(s)
- Vladimir Simic
- Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11010 Belgrade, Serbia
| | - Ali Ebadi Torkayesh
- School of Business and Economics, RWTH Aachen University, 52072 Aachen, Germany
| | - Abtin Ijadi Maghsoodi
- Department of Information Systems and Operations Management, Faculty of Business and Economics, Business School, University of Auckland, Auckland, 1010 New Zealand
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Analysis of Efficiency and Productivity of Commercial Banks in Turkey Pre- and during COVID-19 with an Integrated MCDM Approach. MATHEMATICS 2022. [DOI: 10.3390/math10132300] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Above all, this study is original in that it reveals the efficiency and productivity of banks exposed to the current pandemic situation. The aim of this study is to evaluate bank efficiency and productivity of commercial banks operating in Turkey pre- and during COVID-19 by using a novel integrated multi-criteria decision-making (MCDM) approach. We divided the banks into three groups in order to evaluate the differences in terms of their efficiency and productivity: state banks, foreign banks and private domestic banks. This paper fills a gap in the literature by using a novel integrated MCDM approach including SWARA II as a subjective weighting method, MEREC as an objective weighting method, and MARCOS as a ranking method to evaluate bank efficiency and productivity. The results reveal that banks with foreign investors achieved higher productivity than other bank groups and the productivity of state banks decreased especially during the COVID-19 period. It should also be noted that state banks are restricted to certain political objectives.
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A Cluster-based Stratified Hybrid Decision Support Model under Uncertainty: Sustainable Healthcare Landfill Location Selection. APPL INTELL 2022; 52:13614-13633. [PMID: 35280110 PMCID: PMC8898660 DOI: 10.1007/s10489-022-03335-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2022] [Indexed: 12/23/2022]
Abstract
Nowadays, healthcare waste management has become one of the significant environmental, health, and social problems. Due to population and urbanization growth and an increase in healthcare waste disposals according to the growing number of diseases and pandemics like COVID-19, disposal of healthcare waste has become a critical issue. Authorities in big cities require reliable decision support systems to empower them to make strategic decisions to provide safe disposal methods with a prospective vision. Since inappropriate healthcare waste management systems would definitely bring up dangerous environmental, social, health, and economic issues for every city. Therefore, this paper attempts to address the landfill location selection problem for healthcare waste using a novel decision support system. Novel decision support model integrates K-means algorithms with Stratified Best-Worst Method (SBWM) and a novel hybrid MARCOS-CoCoSo under grey interval numbers. The proposed decision support system considers waste generate rate in medical centers, future unforeseen but potential events, and uncertainty in experts’ opinion to optimally locate required landfills for safe and economical disposal of dangerous healthcare waste. To investigate the feasibility and applicability of the proposed methodology, a real case study is performed for Mazandaran province in Iran. Our proposed methodology could efficiently deal with 79 medical centers within 4 clusters addressing 9 criteria to prioritize candidate locations. Moreover, the sensitivity analysis of weight coefficients is carried out to evaluate the results. Finally, the efficiency of the methodology is compared with several well-known methods and its high efficiency is demonstrated. Results recommend adherence to local rules and regulations, and future expansion potential as the top two criteria with importance values of 0.173 and 0.164, respectively. Later, best location alternatives are determined for each cluster of medical centers.
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Ali J. A q-rung orthopair fuzzy MARCOS method using novel score function and its application to solid waste management. APPL INTELL 2021. [DOI: 10.1007/s10489-021-02921-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Simić V, Lazarević D, Dobrodolac M. Picture fuzzy WASPAS method for selecting last-mile delivery mode: a case study of Belgrade. EUROPEAN TRANSPORT RESEARCH REVIEW 2021; 13:43. [PMID: 38624967 PMCID: PMC8323095 DOI: 10.1186/s12544-021-00501-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 07/02/2021] [Indexed: 05/21/2023]
Abstract
Background Last-mile delivery (LMD) is becoming more and more demanding due to an increasing number of users and traffic problems in cities. Besides, medical crises (like the COVID-19 outbreak) and air pollution represent additional motives for the transition from traditional to socially and environmentally sustainable LMD mode. An emerging problem for companies in the postal and logistics industry is how to determine the best LMD mode in a multi-criteria setting under uncertainty. Method For the first time, an extension of the Weighted Aggregated Sum Product ASsessment (WASPAS) method under the picture fuzzy environment is presented to solve the LMD mode selection problem. The introduced picture fuzzy set (PFS) based multi-criteria decision-making (MCDM) method can be highly beneficial to managers who are in charge of LMD since it can take into account the neutral/refusal information and efficiently deal with high levels of imprecise, vague, and uncertain information. The comparative analysis with the existing state-of-the-art PFS-based MCDM methods approved the high reliability of the proposed picture fuzzy WASPAS method. Its high robustness and consistency are also confirmed. The presented method can be used to improve LMD in urban areas worldwide. Besides, it can be applied to solve other emerging MCDM problems in an uncertain environment. Findings A real-life case study of Belgrade is presented to fully illustrate the potentials and applicability of the picture fuzzy WASPAS method. The results show that postomates are the best mode for LMD in Belgrade, followed by cargo bicycles, drones, traditional delivery, autonomous vehicles, and tube transport. Supplementary Information The online version contains supplementary material available at 10.1186/s12544-021-00501-6.
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Affiliation(s)
- Vladimir Simić
- Department of Postal and Telecommunication Traffic, Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11010 Serbia
| | - Dragan Lazarević
- Department of Postal and Telecommunication Traffic, Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11010 Serbia
| | - Momčilo Dobrodolac
- Department of Postal and Telecommunication Traffic, Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11010 Serbia
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A Novel Fuzzy SIMUS Multicriteria Decision-Making Method. An Application in Railway Passenger Transport Planning. Symmetry (Basel) 2021. [DOI: 10.3390/sym13030483] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
To increase the level of adequacy in multi-criteria decision-making in the case of uncertainty, it is essential to reduce the subjectivism and to increase the reality of obtained results. The study aims to propose a novel fuzzy multi-criteria method based on the fuzzy linear programming method and sequential interactive model for urban systems method (SIMUS), named fuzzy SIMUS. This paper is something completely different because it links the power of fuzzy with the advantage of the SIMUS method. Indeed, not using weights, it works with optimal values. Here, this procedure is presented for the first time. The methodology consists of three stages. The first stage includes forming the parameters of a multi-criteria model in the case of uncertainty. The initial matrix has three values: lower, medium, and upper. In the second stage, the fuzzy SIMUS model for each objective is formed based on fuzzy linear programming method. The third stage deals with the ranking of the alternatives. The methodology was experimented for planning railway intercity passenger transport in Bulgarian’s railway network. Nine alternative transport plans and eight criteria were studied. It was found that the objectives which influence ranking the most are the frequency of train stops (15%), direct operational costs (15%), train’s capacity (14.7%), and reliability (14.3%). A transport plan for railway passenger transport is proposed. A verification of the results was performed. It was found that the stability of the choice presented a suitable alternative.
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