ABSTRACT
The global COVID-19 pandemic had a complex impact on the supply chain system. Manufacturing companies always strive to be able to face corporate competition and become superior with one of them through selecting the right supplier. Suppliers have the highest risk in a company, especially during the COVID-19 pandemic era, but with the correct selection of suppliers, the company can provide strength in global competition. The purpose of this research is to be able to solve the problem of sustainable supplier selection in a garment industry in Indonesia during the COVID-19 pandemic through the integration method between AHP and MOORA. AHP as a method that has been proven in many studies, in this study is used to determine the weight of each criterion. Furthermore, MOORA as a method that has good selectivity in choosing the best alternative will be used in the selection process. 12 criteria with 5 alternatives are used to determine the best supplier. The contribution of this research is the integration of the AHP and MOORA methods and the determination of important criteria in the era of the COVID-19 Pandemic. The results show that the criteria for the area with the level impact of COVID-19 (C12) have the greatest weight and supplier 3 becomes the first ranked supplier or the best supplier. The integration method between AHP and MOORA is easy to use and can choose the right sustainable supplier during the COVID-19 pandemic. © 2023 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
The outbreak of coronavirus has posed a significant threat to all sectors of life. Therefore, the World Health Organization (WHO) has urged a concerted effort to develop an effective vaccine to limit the spread of this virus among the population. Many vaccines have been produced in several countries in accordance with specified criteria. This study evaluated these vaccines using a variety of criteria. However, conflicting criteria provided a significant obstacle during the appraisal process. This article aims to evaluate and compare the COVID-19 vaccines currently licensed for emergency use worldwide. This study applied a novel hybrid multi-criteria decision approach by integrating the entropy method and MOORA technique to select the optimum vaccine. The methodology is down into two steps: 1) calculating weights for seven criteria, and 2) calculating the rank of eight COVID-19 vaccines. The findings showed that Johnson and Johnson vaccine is the best alternative, while the Pfizer-BioNTech vaccine is the worst. The study's implications helped countries to select the best vaccines for immunizing people and preventing the virus spread among them. © 2023, International Organization on 'Technical and Physical Problems of Engineering'. All rights reserved.
ABSTRACT
PurposeDue to the introduction of new vaccines in the child immunization program and inefficient vaccine supply chain (VSC), the universal immunization program (UIP), India is struggling to provide a full schedule of vaccination to the targeted children. In this paper, the authors investigate the critical factors for improving the performance of the existing VSC system by implementing the next-generation vaccine supply chain (NGVSC) in India.Design/methodology/approachThe authors design a fuzzy multi-criteria framework using a fuzzy analytical hierarchical process (FAHP) and fuzzy multi-objective optimization on the basis of ratio analysis (FMOORA) to identify and analyze the critical barriers and enablers for the implementation of NGVSC. Further, the authors carry out a numerical simulation to validate the model.FindingsThe outcome of the analysis contends that demand forecasting is the topmost supply chain barrier and sustainable financing is the most important/critical enabler to facilitate the implementation of the NGVSC. In addition, the simulation reveals that the results of the study are reliable.Social implicationsThe findings of the study can be useful for the child immunization policymakers of India and other developing countries to design appropriate strategies for improving existing VSC performance by implementing the NGVSC.Originality/valueTo the best of the authors' knowledge, the study is the first empirical study to propose the improvement of VSC performance by designing the NGVSC.
ABSTRACT
The world's labour markets were significantly affected by the coronavirus spread and lockdowns and deaths caused by it. Policy-makers tried to mitigate the consequences of the COVID-19 pandemic on the labour market by imposing different measures and aid packages. Having in mind all activities for combating the COVID-19 pandemic's effect on the labour market in 2020 and 2021, the question arose how resilient are labour markets to the effects of the COVID- 19 pandemic compared to the year before the pandemic? Therefore, this study attempts to answer this question by creating a composite index of ten labour market indicators using the MOORA ranking method. The research sample is made up of 27 European Union (EU) countries. In the first step, countries' composite indexes were compared on a year-to-year basis (2019-2020, 2019-2021 and 2020-2021) and no significant discrepancies were observed. In the second step, differences in geographical clusters of countries were captured while comparing their composite indexes for 2020 and 2021. The study results indicate that aid packages restricted the COVID-19 pandemic's effects on the EU labour markets and strengthened their sustainability. The downturn in EU labour market indicators was retained thus making divergence between geographical clusters inherited from the previous periods. The research results indicate the importance of joint EU policies in crisis periods for encouraging the sustainability of the EU labour markets and the need to make a balance among EU labour markets under normal conditions.
ABSTRACT
SMPN 174 Jakarta is a junior high school in East Jakarta that has 719 students and 22 classrooms, including being one of the schools with government programs in the form of assistance such as Smart Jakarta Card, Smart Indonesia Program, and School Operational Assistance. To meet educational needs and distribute to students who are entitled to assistance. Currently, the selection process for student beneficiaries at SMPN 174 Jakarta is still done manually, so there is a risk of making decisions that are not on target and require a longer time. Therefore, a decision support system was made to select students who receive assistance. The development of the decision support system used in this research is the Multi-Objective Optimization Method on the Basic of Ratio (MOORA). The tests include black-box testing and comparison testing of calculation results with manual calculations. The Decision Support System for Selection of Student Recipients for the Impact of COVID-19 has been successfully created, and the results of selecting recipients of this assistance are obtained based on the calculation of the highest optimization value. The verifier has approved them with a percentage of 66.7% strongly agreeing and 33.3% agreeing. © 2022 IEEE.
ABSTRACT
In line with the losses brought about by the recent pandemic of the new coronavirus, the oil market, as well as other segments, has been facing economic difficulties to recover. Seeking to bring a practical and efficient strategy to the corporate environment, in this area, this study demonstrates a new multi-criteria method based on multi-objectives, capable of calculating the importance of each criterion, to encourage more assertive and objective decision-making to evaluate different situations in the oil industry, such as the application of resources, investments and other strategies. As a case study, a group of AHTS (Anchor Handling Tug Supply) vessels was used to supply offshore platforms and application of the CRITIC-MOORA-3N method, which allows a logical analysis of the relevant criteria and presents an objective solution, as result for the scenario that applies. © 2022 The Authors. Published by Elsevier B.V.
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In the methodology part of this study, we introduced a combined “AHP(blocks) and Entropy” approach for improving of Multi-Criteria Decision Making (MCDM) for Cloud Services (CS) selection. On this basis, we optimize the combination of professional experts’ opinion and objectivity of entropy criteria weighting. In this second part, we test our findings on an existing universal dataset with Quality of Service (QoS) and Quality of Experience (QoE) criteria and adapting for the needs of individual users and small education organisations under conditions of COVID-19 pandemics. © 2022, Springer Nature Switzerland AG.
ABSTRACT
The COVID-19 pandemic was difficult for everyone and even more so for hospitals and medical personnel. The infections caused by this disease were many in a very short time, due to this, hospitals resorted to using engineering tools for effective and efficient management of patients with severe symptoms of COVID-19. Considering the above, it is possible to apply a multi-criteria decision method to prioritize the objectives that must be met to achieve the best medical care for patients with severe symptoms. The results obtained is that the criterion that should be approached first is the use of digital communication platforms such as WeChat, Whatsapp, Telegram, because these platforms offer instant communication through text, images, documents, videos or audios and which does not require physical presence between the isolation room and the outside, compared to those obtained at Huazhong University, this method would define the order of priority in which these objectives should be achieved. Finally, the results obtained depict that it is possible to prioritize the management of workloads in the care of patients with COVID disease.
ABSTRACT
BACKGROUND AND OBJECTIVE: The COVID-19 pandemic results in an intense flow of patients to hospitals especially to the intensive care units (ICUs) to be treated. The ICUs will therefore be confronted with a massive influx of patients (e.g. Spain and Italy). However, if the number of patients is higher than the resources available in ICUs, rationing decisions such as determining and evaluating the criteria for ICU admission becomes essential. In this case, the decision of which patients will be admitted to the ICUs may put significant pressure on healthcare personnel. The goal of this paper is to determine the criteria to be used in the decision of admission of COVID-19 patients to the ICUs. METHODS: A three-step methodology is applied. In the first step, the evaluation criteria are determined, and then the criteria are prioritized using a fuzzy analytical hierarchy process (AHP) in an uncertain and multiple-criteria environment choice. Finally, COVID-19 patients are ranked using the Multi-Objective Optimization Method by Ratio Analysis to find out which patient is more urgent. RESULTS: According to experts' evaluation of ICU admission criteria, "increment of >2 in SOFA score" seems the most dominant factor among others. The proposed methodology is tested on 10 anonymous COVID-19 positive patients being treated in a public hospital and the ICU admission results are discussed. CONCLUSIONS: Obtained priorities and ranking is in line with the hospitals' behavior that potentially depicts the usefulness and validity of the proposed approach.