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      Exploring factors of the sustainable supply chain in the post-COVID-19 pandemic: SWARA approach

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          Abstract

          The present research aimed to provide a mechanism for enhancing sustainable supply chain survivability (SSCS) during and after the COVID-19 outbreak. Logistical and manufacturing operations have been restricted due to the severe lockdown, which significantly impacts the demand and supply of various items. COVID-19 has a massive effect on a multitude of units of various sectors. This research emphasized the important elements that must be considered to adapt the sustainable supply chain (SSC) practices. As a result, businesses are now attempting to improve the system for SSC. The stepwise weight assessment ratio analysis (SWARA) approach is used in this research to classify dynamic aspects for improving SSC survival in an epidemic condition. The results reveal that the viability of the supply chain network is the essential criteria for managing the relationships of suppliers and buyers and maximizing SSCS during and after COVID-19. This research will help businesses, manufacturers, and other stakeholders to concentrate on the described factors to achieve a brighter environment.

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          Most cited references116

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          From a literature review to a conceptual framework for sustainable supply chain management

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            Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case

            Highlights • Epidemic outbreaks are a special case of supply chain (SC) risks. • We articulate the specific features of epidemic outbreaks in SCs. • We demonstrate a simulation model for epidemic outbreak analysis. • We use an example of coronavirus COVID-19 outbreak.
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              Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

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                Author and article information

                Contributors
                khizarhayat@nuaa.edu.cn
                Journal
                Environ Sci Pollut Res Int
                Environ Sci Pollut Res Int
                Environmental Science and Pollution Research International
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0944-1344
                1614-7499
                16 October 2021
                : 1-19
                Affiliations
                [1 ]GRID grid.64938.30, ISNI 0000 0000 9558 9911, College of Economics and Management, , Nanjing University of Aeronautics and Astronautics, ; Nanjing, 211106 Jiangsu People’s Republic of China
                [2 ]Department of Economics, Government Graduate College Kot Sultan, Kot Sultan 31650, Layyah, Punjab Pakistan
                [3 ]GRID grid.411501.0, ISNI 0000 0001 0228 333X, Department of Business Administration, , Bahauddin Zakariya University, ; Multan, Pakistan
                Author notes

                Responsible Editor: Eyup Dogan

                Author information
                http://orcid.org/0000-0001-8962-3084
                Article
                16908
                10.1007/s11356-021-16908-6
                8520465
                2fe55f75-cb3a-4e23-9ad0-b09b6ece869a
                © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 29 May 2021
                : 2 October 2021
                Categories
                Post COVID Green Supply Chain Opportunities and Challenges

                General environmental science
                sustainable supply chains,survivability,post-covid-19,viability,digital data-driven supply chains,buyer-supplier relationship

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