Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 473

The DOI matches its Crossref record; 145 of the 145 references it cites were found in a registry or an index.

Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation

Fosso Wamba, Samuel, Queiroz, Maciel M., Trinchera, Laura·2020·International Journal of Production Economics

Abstract

Abstract The logistics and supply chain management (SCM) field is experimenting with the integration of blockchain, a cutting-edge, and highly disruptive technology. Yet, blockchain is still nascent, and the extant literature on this technology is scarce, especially as regards the relationship between blockchain and SCM. Additionally, existing studies have not yet addressed sufficiently the enablers of blockchain adoption and the interplay with supply chain performance. In order to reduce this gap, this study aims to examine the potential influence of blockchain on supply chain performance. We draw on the literature on technology adoption and supply chain performance, as well as on the emerging blockchain literature, to develop and test a model in two countries, namely India and the US. Accordingly, we administered a survey in order to review the opinions and views of supply chain practitioners. The results support the model and indicate that blockchain applications can improve supply chain performance. In particular, our findings suggest that knowledge sharing and trading partner pressure play an important role in blockchain adoption, and that supply chain performance is significantly influenced by supply chain transparency and blockchain transparency. Another finding was the inexistence of evidence for a moderation effect of the industry variable on the outcomes. The research conclusions have substantial managerial and theoretical implications. Our model contributes mainly to the theoretical advancement of SCM-blockchain, thus allowing scholars to adapt our validated model.

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 · 10.1016/j.ijpe.2020.107791

Cites

145 of 145 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 145 references

Cited by

See all 473

Metadata

Authors
Fosso Wamba, S., Queiroz, M. M., & Trinchera, L.
Venue
International Journal of Production Economics
Publisher
Elsevier BV
Published
2020-11
Volume
229
Pages
107791
ISSN
0925-5273 (ISSN-L)
OpenAlex
W3022170296
Cited by
473
References
145
FWCI
54.86
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: Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation. https://app.cochat.ai/papers/10.1016/j.ijpe.2020.107791
The paper
Fosso Wamba, S., Queiroz, M. M., & Trinchera, L. (2020). Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2020.107791

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.