The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0
Abstract
We theorize a notion of a digital supply chain (SC) twin – a computerized model that represents network states for any given moment in real time. We explore the conditions surrounding the design and implementation of the digital twins when managing disruption risks in SCs. The combination of model-based and data-driven approaches allows uncovering the interrelations of risk data, disruption modeling, and performance assessment. The SC shocks and adaptations amid the COVID-19 pandemic along with post-pandemic recoveries provide indisputable evidences for the urgent needs of digital twins for mapping supply networks and ensuring visibility. The results of this study contribute to the research and practice of SC risk management by enhancing predictive and reactive decisions to utilize the advantages of SC visualization, historical disruption data analysis, and real-time disruption data and ensure end-to-end visibility and business continuity in global companies.
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Cites
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Self-citationHow ‘big data’ can make big impact: findings from a systematic review and a longitudinal case study
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“…uncertainty, structural dynamics and risk analytics (Blackhurst et al. 2005; Ivanov, Sokolov, and Kaeschel 2010; Flynn, Koufteros, and Lu 2016; Ivanov et al. 2018; Choi, Wallace, and Wang 2018; Dubey, Gunasekaran, Childe, Wamba, et al. 2019; Ivanov, Dolgui, and Sokolov 2019; Panetto et al. 2019).”
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Cited by
Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., Dennehy, D., Metri, B., Buhalis, D., Cheung, C. M. K., et al. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102542 · Cited by 2,753
Ivanov, D. (2020) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2020.101922 · Cited by 2,280
Self-citationCOVID-19 pandemic related supply chain studies: A systematic review
Chowdhury, P., Paul, S. K., Kaisar, S., & Moktadir, M. A. (2021) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2021.102271 · Cited by 992
Impact of COVID-19 on logistics systems and disruptions in food supply chain
Singh, S., Kumar, R., Panchal, R., & Tiwari, M. K. (2021) · International Journal of Production Research · doi:10.1080/00207543.2020.1792000 · Cited by 904
Ivanov, D. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.1890852 · Cited by 561
Self-citation
Metadata
- Authors
- Ivanov, D., & Dolgui, A.
- Venue
- Production Planning & Control
- Publisher
- Informa UK Limited
- Published
- 2020-05-21
- Volume
- 32
- Issue
- 9
- Pages
- 775-788
- ISSN
- 0953-7287 (ISSN-L)
- 1366-5871
- OpenAlex
- W3026226282
- Cited by
- 1,790
- References
- 9
- FWCI
- 190.37
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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