Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 283

The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.

Developing a framework for enhancing survivability of sustainable supply chains during and post-COVID-19 pandemic

Open access
Sharma, Manu, Luthra, Sunil, Joshi, Sudhanshu, Kumar, Anil·2022·International Journal of Logistics Research and Applications

Abstract

The pandemic has created a restrictive working system including remote working, and flexible hours for the firms and employees all around the globe, thus transforming into a platform economy may reduce unemployment and enhance job opportunities. Therefore, firms are now trying to identify the ways for enhancing survivability of Sustainable Supply Chains (SSCs). This study has made an effort to develop a framework for enhancing survivability of SSCs to survive in and post-COVID-19 pandemic. This study has utilised Stepwise Weight Assessment Ratio Analysis (SWARA) method for identifying the significant factors for enhancing survivability of SSCs to be focused in pandemic situation. The study revealed that ‘Supply Chain Network Viability (SCV)’ is the main criterion for managing buyer–supplier relationship and enhancing survivability of SSCs during and post-COVID-19 situation. This study is helpful for firms, suppliers, and other stakeholders to focus on the identified factors for healthier future.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/13675567.2020.1810213

Cites

80 of 80 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 80 references

Cited by

See all 283

Metadata

Authors
Sharma, M., Luthra, S., Joshi, S., & Kumar, A.
Venue
International Journal of Logistics Research and Applications
Published
2020-08-26
Volume
25
Issue
4-5
Pages
433-453
ISSN
  • 1367-5567 (ISSN-L)
  • 1469-848X
OpenAlex
W3080574953
Cited by
283
References
80
FWCI
44.53
Type
journal article
Language
en
Open access
green

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: Developing a framework for enhancing survivability of sustainable supply chains during and post-COVID-19 pandemic. https://app.cochat.ai/papers/10.1080/13675567.2020.1810213
The paper
Sharma, M., Luthra, S., Joshi, S., & Kumar, A. (2022). Developing a framework for enhancing survivability of sustainable supply chains during and post-COVID-19 pandemic. International Journal of Logistics Research and Applications. https://doi.org/10.1080/13675567.2020.1810213

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.