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Cited by 481

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Blockchain technology adoption, architecture, and sustainable agri-food supply chains

Saurabh, Samant, Dey, Kushankur·2021·Journal of Cleaner Production

Abstract

Abstract The emerging Information and Communication Technology play a vital role in electronic agriculture. The application of such technologies as blockchain, Internet-of-Things, wireless sensor networks, cloud computing, and machine learning can improve the agri-food supply chain efficiency and quality management. However, there is little evidence on the determinants of blockchain integrated ICTs adoption for the supply chain actors and their propensity to embrace and use such technologies. To bridge this research gap in the literature, we identify a few potential drivers of blockchain technology adoption, considering the grape wine supply chain and employing a rating-based conjoint analysis. The study finds that dis-intermediation, traceability, price, trust, compliance, and coordination and control in order of their relative importance and utilities can influence the supply chain actors’ adoption-intention decision processes. The adoption factors further rationalize the design for a modular, scalable, interoperable, and cost-effective architecture for supply chain integration and sustainability.

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Crossref · 10.1016/j.jclepro.2020.124731

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Metadata

Authors
Saurabh, S., & Dey, K.
Venue
Journal of Cleaner Production
Publisher
Elsevier BV
Published
2021-02
Volume
284
Pages
124731
ISSN
0959-6526 (ISSN-L)
OpenAlex
W3093525173
Cited by
481
References
4
FWCI
58.81
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Blockchain technology adoption, architecture, and sustainable agri-food supply chains. https://app.cochat.ai/papers/10.1016/j.jclepro.2020.124731
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Saurabh, S., & Dey, K. (2021). Blockchain technology adoption, architecture, and sustainable agri-food supply chains. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2020.124731

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.