The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience
Abstract
This study suggests a new approach to supply chain (SC) disruption risk management where SC behaviour is less dependent on the certainty of our knowledge about the environment and its changes. The unpredictability of the occurrence of disruption and its magnitude suggests that designing SCs with a low need for ‘certainty’ may be as important, if not more so, than predetermined disruption control strategies. In this setting, this study calls for the development of a new perspective in SC disruption management, i.e. low-certainty-need (LCN) SCs. A number of principles and concepts is derived in recent, relevant literature to structure the characteristics of the LCN framework and its management. Structural variety, process flexibility, and parametrical redundancy are identified as key LCN SC characteristics that ensure efficient disruption resistance as well as recovery resource allocation. Two efficiency capabilities of the LCN SC are shown, i.e. low need for uncertainty consideration in planning decisions and low need for recovery coordination efforts based on a combination of lean and resilient elements. The results allow the identification of an LCN SC framework, concepts and technologies for its implementation as well as missing themes and new research questions which contribute to a better understanding of SC disruption risks. Special focus is directed on the digital technology usage in the LCN framework implementation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ivanov, D., Dolgui, A., & Sokolov, B. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1488086 · Cited by 2,055
Self-citation
Cited by
Blockchain technology and its relationships to sustainable supply chain management
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1533261 · Cited by 4,118
Ivanov, D. (2020) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2020.101922 · Cited by 2,280
Self-citationDubey, R., Gunasekaran, A., Childe, S. J., Fosso Wamba, S., Roubaud, D., & Foropon, C. (2021) · International Journal of Production Research · doi:10.1080/00207543.2019.1582820 · Cited by 958
Ivanov, D. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.1890852 · Cited by 561
Self-citationReconfigurable supply chain: the X-network
Dolgui, A., Ivanov, D., & Sokolov, B. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1774679 · Cited by 501
Self-citation
Metadata
- Authors
- Ivanov, D., & Dolgui, A.
- Venue
- International Journal of Production Research
- Publisher
- Informa UK Limited
- Published
- 2018-09-14
- Volume
- 57
- Issue
- 15-16
- Pages
- 5119-5136
- ISSN
- 0020-7543 (ISSN-L)
- 1366-588X
- OpenAlex
- W2889578227
- Cited by
- 360
- References
- 1
- FWCI
- 69.55
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. https://app.cochat.ai/papers/10.1080/00207543.2018.1521025
- The paper
- Ivanov, D., & Dolgui, A. (2019). Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1521025
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.