A GROUP DECISION-MAKING METHOD FOR RANKING PROBLEMS UNDER SUSTAINABILITY, RISKS, AND INTUITIONISTIC FUZZY ENVIRONMENT

This paper presents a group decision-making mechanism to properly manage ranking problems in an intuitionistic fuzzy environment. TOPSIS ranking multi-criteria decision-making (MCDM) methods is utilized under the intuitionistic fuzzy set theory. This solution technique examines the sets of criteria employed in decision-making problems, the preferences of a group of decision-makers, and the importance levels of decision-makers. Managers use the ranking methods as a reliable technique for making supplier evaluation decisions. Furthermore, the supply chain suffers from the shortage of materials, transportation problems, etc. In the post COVID-19 era, the need for a practical and exhaustive tool is explicit. An illustrative case on a supplier selection problem considering sustainability and risks in the post-COVID-19 era is used to demonstrate the applicability of the proposed technique by detailing the procedure step by step. A comparative analysis of the results is carried out. The results are compared with the results of the MARCOS method. The results show that the presented methodology is applicable to the other areas as well. (English) [ FROM AUTHOR] Bu makale, sezgisel bulanık bir ortamda sıralama problemlerini düzgün bir şekilde yönetmek için bir grup karar verme mekanizması sunmaktadır. Sezgisel bulanık küme teorisi kapsamında çok kriterli karar verme (ÇKKV) yöntemi olan TOPSIS kullanılmaktadır. Bu çözüm tekniğinde karar verme problemlerinde kullanılan birtakım kriterler, karar vericiler grubunun tercihleri ve karar vericilerin önem düzeyleri incelenmektedir. Yöneticiler, sıralama yöntemlerini tedarikçi değerlendirme kararlarını vermek için güvenilir bir teknik olarak kullanır. Ayrıca, COVID-19 döneminden sonra tedarik zinciri malzeme sıkıntısı, ulaşım sorunları vb. sıkıntılardan muzdariptir, pratik ve kapsamlı bir araca olan ihtiyaç açıktır. Prosedürü adım adım detaylandırarak önerilen tekniğin uygulanabilirliğini göstermek için, COVID-19 sonrası dönemde sürdürülebilirliği ve riskleri dikkate alan bir tedarikçi seçimi sorununa ilişkin örnek bir vaka kullanılmıştır. Sonuçların karşılaştırmalı analizi gerçekleştirilmiştir. Sonuçlar, MARCOS yönteminin sonuçları ile karşılaştırılmıştır. Sonuçlar, sunulan metodolojinin diğer alanlara da uygulanabilir olduğunu göstermektedir. (Turkish) [ FROM AUTHOR] Copyright of Pamukkale University Journal of Social Sciences Institute / Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi is the property of Pamukkale University, Social Sciences Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

ASSIGNING PRIORITIES FOR RAW MATERIAL OF A LARGE PET FOOD PRODUCER IN THE CONTEXT OF SUPPLY DISRUPTION

The COVID-19 pandemic has affected everyday life in societies around the world. One of the most severe consequences has been the social isolation imposed by this extremely contagious disease. In this context, many people began looking for a pet for the first time. In Brazil, for instance, the pet sector increased its financial returns in 2020. In addition, companies that produce pet foods have experienced problems with the supply of materials. Supply chain disruption is a problem faced by many different organizations during this time of crisis. This study, therefore, investigated the supply of raw materials stored in the silos and tanks of a large company. This company have operations in 80 countries across the world and produces different products, including pet food. Thirteen raw materials used to produce pet food were con-sidered. In addition, eight criteria of the company's supply process were identified and explored. Moreover, the Flexible and Interactive Tradeoff (FITradeoff) method, which is a Multiple Criteria Decision Mak-ing/Aiding (MCDM/A) method, was applied to rank the raw materials based on supply difficulty. In terms of supply criticality, the order of materials was established from less critical to most critical. These results can be used by companies to better plan the receipt of these materials to reduce the risk of supply chain-related disruptions and propose better ways to distribute activities between planners to help them in their daily management. © 2023 Brazilian Operations Research Society.

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Policy Analysis of Low-Carbon Energy Transition in Senegal Using a Multi-Criteria Decision Approach Based on Principal Component Analysis

Senegal has been investing in the development of its energy sector for decades. By using a novel multi-criteria decision analysis (MCDA) based on the principal component analysis (PCA) method, this paper develops an approach to determine the effectiveness of Senegal's policies in supporting low-carbon development. This was determined using six criteria (C1 to C6) and 17 policies selected from the review of Senegal's energy system. In order to determine the optimal weighting of the six criteria, a PCA is performed. In our approach, the best weighted factor is the normalized version of the best linear combination of the initial criteria with the maximum summarized information. Proper weighted factors are determined through the percentage of the information provided by the six criteria kept by the principal components. The percentage of information is statistically a fit of goodness of a principal component. The higher it is, the more statistically important the corresponding principal component is. Among the six principal components obtained, the first principal component (comp1) best summarizes the values of criteria C1 to C6 for each policy. It contains 81.15% of the information on energy policies presented by the six criteria and was used to rank the policies. Future research should take into account that when the number of criteria is high, the share of information explained by the first principal component could be lower (less than 50% of the total variance). In this case, the use of a single principal component would be detrimental to the analysis. For such cases, we recommend a higher dimensional visualization (using two or three components), or a new PCA should be performed on the principal components. This approach presented in our study can serve as an important benchmark for energy projects and policy evaluation.

A novel fuzzy group decision making approach for buying a house in pandemic process

After the detection of the first official case diagnosed with COVID-19 on March 2020, the new package called as "Economic Stability Shield" have been implemented in Turkey to minimize the effects of the pandemic. As in all sectors, the epidemic caused various changes in the real estate sector. The demands of citizens who stayed in homes for a long time during the epidemic period have also changed when buying a house. This study aims to investigate the importance of selection criteria for buying a house criterion in the real estate sector and to determine the most suitable house of via a Multi-Criteria Decision Making (MCDM) approach. By integrating Fuzzy Analytic Hierarchy Process (FAHP) and Multi-Attribute Ideal Real Comparative Analysis (FMAIRCA), the assessment criteria of buying house and suitable houses are evaluated. While making this evaluation, the weights of the criteria are obtained by pairwise comparisons under fuzzy environment through collected from five households living in Konya. Next, the FMAIRCA method is used to rank the candidate houses according to the views of the households. As a result of the study, it has been determined that the criteria of eligibility for credit are the most important criteria. For the case study, we perform a comparative analysis on the performance of fuzzy TOPSIS and fuzzy VIKOR in buying a house. Our comparative analysis for this case study shows that the three fuzzy MCDM methods achieve the identical rankings. (English) [ FROM AUTHOR] Ílk resmi COVID-19 vakasının Mart 2020'de tespitinden sonra pandeminin etkilerini en aza indirgemek için Türkiye'de "Ekonomik Ístikrar Kalkanı" adı verilen yeni paket hayata geçirilmiştir. Tüm sektörlerde olduğu gibi gayrimenkul sektöründe de salgın çeşitli değişikliklere sebep olmuştur. Salgın döneminde uzun süre evlerde kalan vatandaşların konut alırken talepleri de değişikliğe uğramıştır. Bu çalışma, gayrimenkul sektöründe konut satın alma kriterleri için seçim kriterlerinin önemini araştırmayı ve Çok Kriterli Karar Verme (ÇKKV) yaklaşımıyla en uygun konutu belirlemeyi amaçlamaktadır. Bu çalışmada, Bulanık Analitik Hiyerarşi Süreci (BAHS) ve Multi-Attribute Ideal Real Comparative Analysis (BMAIRCA) yöntemleri bir arada kullanılarak konut satın alma değerlendirme kriterleri ve aday konutlar değerlendirilmektedir. Bu değerlendirme yapılırken, kriterlerin ağırlıklarını belirlemek için Konya'da yaşayan beş hane halkından veri toplanarak ikili karşılaştırmalar ile bulanık ortam altında kriter ağırlıkları elde edilmiştir. Daha sonra, aday konutları ailelerin görüşlerine göre sıralamak için BMAIRCA yöntemi kullanılmıştır. Araştırma sonucunda pandemi sürecinde krediye uygunluk kriterinin en önemli kriter olduğu tespit edilmiştir. Örnek vaka çalışması için, bulanık TOPSIS ve bulanık VIKOR'un konut satın alma performansı üzerine karşılaştırma analizi gerçekleştirilmiştir. Örnek vaka çalışması için karşılaştırma analizimiz, üç bulanık yöntemin aynı sıralamalara ulaştığını göstermektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The Bank Performance Ranking in the Emerging Markets: A Case of Turkey 1

Bu çalışmada, Türkiye'de işlem hacmi en yüksek 13 ticari bankanın pandemi öncesi (2019) ve dönemi (2020) finansal performansları çok kriterli karar (Entropi, ARAS, MOORA ve MOOSRA) teknikleriyle belirlenerek BrandFinance marka deǧerlemesi sıralaması ile karşılaştırmıştır. ARAS yöntemi ile ulaşılan finansal performans sıralama sonuçları BrandFinance marka deǧerleme sıralaması ile benzeri çıkmıştır. Ayrıca kamu bankası olan Ziraat Bankası'nın pandemi öncesi;pandemi döneminde de Ziraat Bankası ile diǧer kamu bankası olan Halkbank'ın da yüksek performans göstererek ilk 5 banka içinde yer aldıǧı tespit edilmiştir. Çalışmanın orijinalliǧi, finansal performans sıralaması sonuçları ile BrandFinace marka deǧerleme sıralama sonuçlarının karşılaştırıldıǧı ilk çalışmadır.Alternate :In this study, the pre-pandemic (2019) and pandemic period (2020) financial performances of 13 commercial banks with the highest transaction volume in Turkey were compared using multicriteria decision (Entropy, ARAS, MOORA, and MOOSRA) techniques. The financial performance ranking results obtained by the ARAS method are similar to the BrandFinance brand valuation ranking. In addition, before the pandemic Ziraat Bank, which was a public bank;during the pandemic period, along with Ziraat Bank, Halkbank, which is the other public bank, were found to be among the top 5 banks showing high performance.

Application of fuzzy multicriteria decision-making model in selecting pandemic hospital site

One of the most important challenges for decision-makers and investors is location selection, which may be assessed using multicriteria decision-making (MCDM) methodologies. Problems with picking a location include deciding between alternative locations, analyzing alternatives, and identifying the best location for a hospital. Because they analyze options with multiple perspectives in terms of numerous competing criteria, MCDM approaches are useful instruments for solving decision-making challenges. The fuzzy set theory (FST), which represents uncertainty in human beliefs, may be effectively used with MCDM approaches to produce more sensitive, tangible, and accurate findings in this context. A hybrid fuzzy multi-criteria decision model (FMCDM) is proposed to find the optimal location based on a combination of factors. In the first stage, the Fuzzy Analytical Hierarchy Process (FAHP) is used to estimate the relative criteria classification through the evaluation process. In the second stage, the fuzzy technique of order preference using similarities to the perfect solution (FTOPSIS) is applied to rank the possible alternative sites. The findings from this study indicate that integrate FAHP and FTOPSIS is the most often used FMCDM approach in Aleppo for selecting the best location for a new hospital.

A model for green-resilient supplier selection: fuzzy best-worst multi-criteria decision-making method and its applications.

Supplier selection is regarded as the primary goal of supply chain management (SCM) because it affects its performance, productivity, pleasure, flexibility, and system speed in lockdown. A new method is proposed based on a multi-stage fuzzy sustainable supplier index (FSSI). Experts can use the triple bottom line (TBL) criteria to select the best supplier. In addition, the worst method is proposed based on trapezoidal membership and fuzzy membership functions, which can cover uncertainties and ambiguous environments. Because it collects the related criteria and sub-criteria and uses a direct fuzzy methodology, this research has impacted the SCM literature because it helps solve previous expert methods' computational difficulties. In addition, an ordered mean integration representation method has been implemented to prioritize the selection of the best supplier (SS) based on the sustainability performance of the best supplier, which improves the selection accuracy compared to the previous ranking method. This study can be used as a benchmark to determine which supplier is the best in sustainability. To provide the superiority and broad applicability of the proposed model, a practical case study was completed. On the other hand, the COVID-19 pandemic harms productivity, company performance, and selecting the best suppliers based on sustainability performance. The lockdown situation caused by the COVID-19 pandemic hurts company performance and management.

A novel fuzzy group decision making approach for buying a house in pandemic process

After the detection of the first official case diagnosed with COVID-19 on March 2020, the new package called as "Economic Stability Shield" have been implemented in Turkey to minimize the effects of the pandemic. As in all sectors, the epidemic caused various changes in the real estate sector. The demands of citizens who stayed in homes for a long time during the epidemic period have also changed when buying a house. This study aims to investigate the importance of selection criteria for buying a house criterion in the real estate sector and to determine the most suitable house of via a Multi-Criteria Decision Making (MCDM) approach. By integrating Fuzzy Analytic Hierarchy Process (FAHP) and Multi-Attribute Ideal Real Comparative Analysis (FMAIRCA), the assessment criteria of buying house and suitable houses are evaluated. While making this evaluation, the weights of the criteria are obtained by pairwise comparisons under fuzzy environment through collected from five households living in Konya. Next, the FMAIRCA method is used to rank the candidate houses according to the views of the households. As a result of the study, it has been determined that the criteria of eligibility for credit are the most important criteria. For the case study, we perform a comparative analysis on the performance of fuzzy TOPSIS and fuzzy VIKOR in buying a house. Our comparative analysis for this case study shows that the three fuzzy MCDM methods achieve the identical rankings. (English) [ FROM AUTHOR]

A neighborhood-level analysis of association between social vulnerability and COVID-19 in ahvaz, Iran.

Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the '20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of 'Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level.

A novel fuzzy group decision making approach for buying a house in pandemic process

After the detection of the first official case diagnosed with COVID-19 on March 2020, the new package called as "Economic Stability Shield" have been implemented in Turkey to minimize the effects of the pandemic. As in all sectors, the epidemic caused various changes in the real estate sector. The demands of citizens who stayed in homes for a long time during the epidemic period have also changed when buying a house. This study aims to investigate the importance of selection criteria for buying a house criterion in the real estate sector and to determine the most suitable house of via a Multi-Criteria Decision Making (MCDM) approach. By integrating Fuzzy Analytic Hierarchy Process (FAHP) and Multi-Attribute Ideal Real Comparative Analysis (FMAIRCA), the assessment criteria of buying house and suitable houses are evaluated. While making this evaluation, the weights of the criteria are obtained by pairwise comparisons under fuzzy environment through collected from five households living in Konya. Next, the FMAIRCA method is used to rank the candidate houses according to the views of the households. As a result of the study, it has been determined that the criteria of eligibility for credit are the most important criteria. For the case study, we perform a comparative analysis on the performance of fuzzy TOPSIS and fuzzy VIKOR in buying a house. Our comparative analysis for this case study shows that the three fuzzy MCDM methods achieve the identical rankings. (English) [ FROM AUTHOR]

Hospital Performance Evaluation in COVID-19 Pandemic by Using Hesitant Fuzzy MABAC

Healthcare service demand during the COVID-19 pandemic has significantly increased compared to the pre-pandemic period. In some cases, it is known that the hospitals are insufficient and the health system were at the point of collapse. In order to provide a better service to patients, it is very important to measure and improve current performance. In this study, intensive care unit’s performance of hospitals under the COVID-19 pandemic was evaluated by using Hesitant Fuzzy MABAC (Multi-Attributive Border Approximation Area Comparison) method. There are different criteria sets in the literature for the evaluation of hospitals. Within the scope of this study;technical competence of the COVID-19 emergency service, patient satisfaction, sufficiency of health personnel, and patient follow-up process criteria were used. Since the comparison was made from the perspective of experts, the ambiguities and hesitations in the evaluations were reflected in ambiguous and fuzzy linguistic terms. In the application section, performance measurement of three hospitals were made. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Hybrid DEMATEL-EDAS Based on Multi-Criteria Decision-Making for A Social Aid Distribution Problem

The office of social affairs has been helping poor or marginalized families through social aid in dealing with poverty. This social aid emphasizes decreasing the poverty rate and economic recovery affected by the COVID-19 pandemic. However, the selection process in the previous year evaluated many families as aid recipient candidates through a conventional process selected by an officer. It would be vulnerable to subjectivity in assessment. Therefore, we attempted to develop a hybrid Multiple Criteria Decision-Making (MCDM) methodology to apply it to this particular decision-making process. This methodology amalgamated the DEMATEL method and the EDAS method with different tasks. Firstly, the DEMATEL method decided the feasible criteria weights automatically based on the proficient decision-maker assessment in estimating a pairwise criteria comparison. Secondly, the EDAS applied the criteria weight values to determine alternatives rank order based on the value of the appraisal score. After comparing with the VIKOR method, the hybrid DEMATEL-EDAS method demonstrated the stability and capability in dealing with the different influence parameters on the final results. © 2022 IEEE.

SUPPLY CHAIN MANAGEMENT DURING THE COVID 19 PANDEMIC PERIOD EVALUATION OF STRUCTURAL PROBLEMS: AN APPLICATION ON GÍRESUN HAZELNUT FIRMS

Supply chains are important components in terms of effective production, service management, as well as the ability of businesses to fulfill their objectives and to compete. Especially the effective, economical and efficient operation of this structure provides cost advantage and increases customer satisfaction. However, some structural problems arise in terms of fulfilling the supply chain at the desired level, and these problems affect businesses negatively. In this study, it has been aimed to rate the supply chain management structural problems in the hazelnut firms in Giresun during the Covid 19 pandemic. Spherical fuzzy analytical hierarchy method, one of the Multi Criteria Decision Making methods, has been used in solving supply chain structural problems.

A Hybrid Supplier Evaluation Model for Personal Protective Equipment Procurement to Healthcare Employees

Healthcare workers face the risk and the danger of contracting several infectious diseases. In order to prevent from the risk of being infected by blood, contact, respiratory droplets, etc., healthcare workers need to use Personal Protective Equipment (PPE). Because of the increasing demand for quality PPE after COVID-19 pandemic, it is important for healthcare institutions to determine the best supplier. Evaluation of suppliers is a complex decision, which contains a number of alternative suppliers and conflicting criteria. The conflicts between supplier evaluation factors require institutions to make a compromise choice among alternative suppliers. Therefore, the main aim of this study is to develop an analytic supplier evaluation model for PPE procurement to healthcare institutions. To that end, a hybrid multi-criteria decision making (MCDM) model based on Analytic Hierarchy Process (AHP) and VIse KriterijumsaOptimiz acija I Kompromisno Resenje (VIKOR) is proposed. A case study for surgical mask procurement to a hospital is presented to demonstrate the applicability of the proposed model. The application results show that the proposed model is a useful decision support tool for PPE procurements to policy-makers of healthcare institutions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Sugeno Integral Based Pandemic Risk Assessment

Complex situations such as pandemics generally lead to consider different sources of information in the analysis. We propose a general framework for coronavirus risk assessment based on multi-criteria decision aiding (MCDA) where input variables are indicators expressed on the basis of qualitative-ordinal scales. The proposed approach, based on Sugeno Utility Functionals, makes the problem setting easy to interpret and allows us to reflect the policy-makers’ opinions on the importance of each indicator or subset of indicators. Interestingly, our approach is related to if-then rule-based systems adopted by some Governments for pandemic risk assessment and restriction policy planning. © 2022, Springer Nature Switzerland AG.

Evaluating Interventions in Response to COVID-19 Outbreak by Multiple-Criteria Decision-Making Models

The COVID-19 outbreak has currently led to serious social and economic consequences. In poor and developing countries, there are more challenges and barriers to tackling the pandemic. The study’s aim is to propose a hybrid approach to multiple-criteria decision-making (MCDM) models for determining the most efficient intervention strategies. The methodology is a combination between the Best-Worst Model (BWM) and Group Best-Worst Model (GBWM) to estimate the efficiency score of intervention. Based on the background of knowledge, five groups of stakeholders including Academicians, Entrepreneurs, Commons Residents, Social Workers, Health Workers are considered decision-makers (DMs). A set of nine potential strategies was evaluated and prioritized by all DMs. The findings have shown that different groups of stakeholders prioritized differently the importance of criteria due to their interests. In the context of Vietnam, however, the Availability of Health Systems is prioritized as the most important intervention. The results and proposed model of this paper contributed to MCDM literature as well as a good reference to apply practically in many different countries.