An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

Saraji, Mahyar Kamali; Mardani, Abbas; Köppen, Mario; Mishra, Arunodaya Raj; Rani, Pratibha

doi:10.1007/s10462-021-10029-9

Cited by 52 publications

(22 citation statements)

References 49 publications

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“…Cui et al ( 2021 ) combined Pythagorean fuzzy SWARA with the combined compromise solution (CoCoSo) method in order to IoT adaption barriers for the circular economy. Recently, Saraji et al ( 2021 ) suggested an integrated decision-making framework by combining SWARA and multi-objective optimization based on ratio analysis with the full multiplicative form (MULTIMOORA) with hesitant fuzzy sets (HFSs) and applied to adapt online education during COVID-19.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach

Xin

Lang

Mishra³

2022

Oper Manag Res

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Industry 4.0 has the potential of growing industrialization and, on the other hand, disrupting the sustainability of prevailing manufacturing supply chains through inducing great challenges such as higher resource consumption that, in turn, results in global warming and climate change. As a result, researchers working in the area of sustainable supply chain 4.0 need to make deep evaluations on the challenges arising for manufacturing supply chains contemplating the improvement of their sustainability levels and having a digital transformation toward Industry 4.0. To fill this gap, the current paper designs an innovative framework on the basis of the Stepwise Weight Assessment Ratio Analysis (SWARA) technique and the Complex Proportional Assessment (COPRAS) approach to evaluate the challenges that may arise for supply chain 4.0 in the q-Rung Orthopair Fuzzy Sets (q-ROFSs) setting. The proposed method uses an extended SWARA process to determine the criteria importance degrees considering the experts’ preferences. The performance of the proposed method was assessed by conducting an empirical case study under the q-ROFSs condition. Further, a sensitivity analysis was executed to check whether the proposed method is stable enough to be relied on parameter values. Finally, the results obtained were compared to those of currently used methods to verify the obtained results’ reliability. As revealed by the comparative results, the framework proposed in this article was of higher consistency and strength compared to other prevailing approaches.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach

Xin

Lang

Mishra³

2022

Oper Manag Res

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“…Saraji et al [ 29 ] offered the MCDM problem to select suitable education techniques under hesitant fuzzy sets. Alkan and Kahraman [ 30 ] introduced IF-TOPSIS method to choose the hospital site under pandemic conditions.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Decision-Making Model with Interval-Valued Intuitionistic Fuzzy Sets for Evaluating Digital Technology Strategies in COVID-19 Pandemic Under Uncertainty

Salimian

Mousavi

2022

Arab J Sci Eng

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Coronavirus diseases 2019 (COVID-19) pandemic is an essential challenge to the health and safety of people, medical members, and treatment systems worldwide. Digital technologies (DTs) have been universally introduced to improve the treatment of patients during the pandemic. Nevertheless, only a few governments have been partly successful in executing the DT strategies. In this regard, it is critical to demonstrate a suitable strategy for the governments. This problem is built based on the experts' opinions with some conflicting criteria to evaluate various types of alternatives. Hence, this research presents a new multi-criteria decision-making (MCDM) model under uncertain conditions. For this reason, interval-valued intuitionistic fuzzy sets (IVIFSs) are employed to help decision-makers (DMs) evaluate in a broader area and cope with uncertain information. Moreover, a new extended weighting method based on weighted distance-based approximation (WDBA) and a new combined ranking approach are proposed to determine the DMs’ weights and rank the alternatives under IVIF conditions. The developed weighting method is constructed based on computing the DMs’ weights with objective criteria weights. Furthermore, a new ranking approach is proposed by obtaining two ranking indexes separately: The first and second ranking indexes are calculated according to the positive and negative ideal solutions distances and the nature of criteria weights, respectively. Afterward, the final values of rankings are computed by considering a new aggregating procedure. The results of the proposed model represent the first alternative as the best strategy. Comparisons between the IVIF-TOPSIS and IVIF-VIKOR methods are also provided to investigate the proposed model to determine the rankings of main alternatives. Sensitivity analyses are conducted to check the reliability and the robustness of the model. For this purpose, criteria weights are analyzed to compute the dependencies’ degree of the new extended weighting method. The dependencies of the ranking model are discussed on the criteria weights as well.

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“…The coronavirus disease 2019 (COVID-19) outbreak has adversely affected all social sectors worldwide, including the economy, healthcare, and education (1)(2)(3)(4)(5). Its high infectivity has necessitated measures such as social distancing, isolation, and travel restrictions, bringing almost all face-to-face activities to a standstill (1,4,6).…”

Section: Introductionmentioning

confidence: 99%

Laboratory and clinical teaching experience of nursing professors in the COVID-19 pandemic era: Now and the future

Choi

Jin

Kim

2022

Front. Public Health

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Nursing professors must constantly interact with students, maintain a high level of professional performance, and meet targets and deadlines, even during a pandemic. Considering the changing educational environment, it is essential to identify contemporary limitations and problems to provide feedback for improvement. This study aimed to explore the laboratory and clinical teaching experiences of nursing professors during the COVID-19 pandemic. Focus group interviews were conducted with professors from the nursing departments of universities in Korea. In total, 19 professors who had laboratory and clinical experience participated in this study. The collected data were analyzed using thematic analysis. The analysis identified four themes. The themes included feeling helpless in the infection management system, uncertainty about the effectiveness of alternative practice training, acceptance of changes, and preparation for future practice training. As the necessity and possibility of non-face-to-face education have been confirmed by the pandemic, it is expected that classes using technology will be actively developed in nursing practice education. The roles and attitudes of teachers and educational institutions also need to change. Nursing professors should reflect upon and evaluate challenges to prepare for post-pandemic practical education.

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An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

Cited by 52 publications

References 49 publications

RETRACTED ARTICLE: Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach

RETRACTED ARTICLE: Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach

A Multi-Criteria Decision-Making Model with Interval-Valued Intuitionistic Fuzzy Sets for Evaluating Digital Technology Strategies in COVID-19 Pandemic Under Uncertainty

Laboratory and clinical teaching experience of nursing professors in the COVID-19 pandemic era: Now and the future

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