Using emerging technologies to improve the sustainability and resilience of supply chains in a fuzzy environment in the context of COVID-19
| dc.contributor.author | Ipek Kazançoǧlu | |
| dc.contributor.author | Melisa Ozbiltekin-Pala | |
| dc.contributor.author | Sachin Kumar Kumar Mangla | |
| dc.contributor.author | Ajay Kumar | |
| dc.contributor.author | Yigit Kazancoglu | |
| dc.contributor.author | Ozbiltekin-Pala, Melisa | |
| dc.contributor.author | Kumar, Ajay | |
| dc.contributor.author | Kazancoglu, Ipek | |
| dc.contributor.author | Mangla, Sachin Kumar | |
| dc.contributor.author | Kazancoglu, Yigit | |
| dc.date.accessioned | 2025-10-06T17:49:33Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | In rapidly changing business conditions it has become extremely important to ensure the sustainability of supply chains and further improve the resiliency to those events such as COVID-19 that can cause unexpected disruptions in the value supply chain. Although globalized supply chains have already been criticized for lack of control over sustainability and resilience of supply chain operations these issues have become more prevalent in the uncertain environment driven by COVID-19. The use of emerging technologies such as blockchain Industry 4.0 analytics model and artificial intelligence driven methods are aimed at increasing the sustainability and resilience of supply chains especially in an uncertain environment. In this context this research aims to identify the problematic areas encountered in building a resilient and sustainable supply chain in the pre-COVID-19 era and during COVID-19 and to offer solutions to those problematic areas tackled by an appropriate emerging technology. This research has been contextualized in the automotive industry, this industry has a complex supply chain structure and is one of the sectors most affected by COVID-19. Based on the findings the most important problematic areas encountered in SSCM pre-COVID-19 are determined as supply chain traceability demand planning and production management as well as purchasing process planning based on cause and effect groups. The most important issues to be addressed during COVID-19 are top management support purchasing process planning and supply chain traceability respectively. © 2023 Elsevier B.V. All rights reserved. | |
| dc.identifier.doi | 10.1007/s10479-022-04775-4 | |
| dc.identifier.issn | 15729338, 02545330 | |
| dc.identifier.issn | 0254-5330 | |
| dc.identifier.issn | 1572-9338 | |
| dc.identifier.scopus | 2-s2.0-85132714838 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132714838&doi=10.1007%2Fs10479-022-04775-4&partnerID=40&md5=e5477ce8504a114ad99dc6ca4b6409e0 | |
| dc.identifier.uri | https://gcris.yasar.edu.tr/handle/123456789/8480 | |
| dc.identifier.uri | https://doi.org/10.1007/s10479-022-04775-4 | |
| dc.language.iso | English | |
| dc.publisher | Springer | |
| dc.relation.ispartof | Annals of Operations Research | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.source | Annals of Operations Research | |
| dc.subject | Artificial Intelligence, Decision Support System, Emerging Technologies, Resilience, Sustainable Supply Chain | |
| dc.subject | Emerging Technologies | |
| dc.subject | Sustainable Supply Chain | |
| dc.subject | Resilience | |
| dc.subject | Artificial Intelligence | |
| dc.subject | Decision Support System | |
| dc.title | Using emerging technologies to improve the sustainability and resilience of supply chains in a fuzzy environment in the context of COVID-19 | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| gdc.author.id | Kazancoglu, Yigit/0000-0001-9199-671X | |
| gdc.author.id | KUMAR MANGLA, SACHIN/0000-0001-7166-5315 | |
| gdc.author.id | Ozbiltekin-Pala, Melisa/0000-0002-1356-3203 | |
| gdc.author.id | Kazancoglu, Ipek/0000-0001-8251-5451 | |
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| gdc.author.wosid | Kazancoglu, Ipek/LGY-6982-2024 | |
| gdc.author.wosid | KUMAR, AJAY/KIC-8060-2024 | |
| gdc.author.wosid | Ozbiltekin-Pala, Melisa/AAA-2580-2019 | |
| gdc.author.wosid | KUMAR MANGLA, SACHIN/B-7605-2017 | |
| gdc.author.wosid | Kazancoglu, Yigit/E-7705-2015 | |
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| gdc.description.departmenttemp | [Kazancoglu, Ipek] Ege Univ, Fac Econ & Adm Sci, Dept Business Adm, TR-35100 Izmir, Turkey; [Ozbiltekin-Pala, Melisa; Kazancoglu, Yigit] Yasar Univ, Dept Logist Management, TR-35100 Izmir, Turkey; [Mangla, Sachin Kumar] OP Jindal Univ, Res Ctr Digital Circular Econ Sustainable Dev Goa, Jindal Global Business Sch, Sonepat, India; [Kumar, Ajay] EMLYON Business Sch, AIM Res Ctr AI Value Creat, Ecully, France | |
| gdc.description.endpage | 240 | |
| gdc.description.issue | 1 | |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
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| gdc.oaire.keywords | Artificial intelligence | |
| gdc.oaire.keywords | Transportation, logistics and supply chain management | |
| gdc.oaire.keywords | Management decision making, including multiple objectives | |
| gdc.oaire.keywords | Environmental economics (natural resource models, harvesting, pollution, etc.) | |
| gdc.oaire.keywords | decision support system | |
| gdc.oaire.keywords | Dairy Production | |
| gdc.oaire.keywords | Inventory, storage, reservoirs | |
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| gdc.oaire.keywords | Artificial-Intelligence | |
| gdc.oaire.keywords | Dematel | |
| gdc.oaire.keywords | resilience | |
| gdc.oaire.keywords | Decision support system | |
| gdc.oaire.keywords | sustainable supply chain | |
| gdc.oaire.keywords | Original Research | |
| gdc.oaire.keywords | Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming | |
| gdc.oaire.keywords | Resilience | |
| gdc.oaire.keywords | artificial intelligence | |
| gdc.oaire.keywords | Sustainable supply chain | |
| gdc.oaire.keywords | emerging technologies | |
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| gdc.virtual.author | Kazançoğlu, Yiğit | |
| gdc.virtual.author | Özbiltekin, Melisa | |
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| person.identifier.scopus-author-id | Kazançoǧlu- Ipek (36598380300), Ozbiltekin-Pala- Melisa (57222809402), Kumar Mangla- Sachin Kumar (55735821600), Kumar- Ajay (58842772900), Kazancoglu- Yigit (15848066400) | |
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