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Demonstration of a blockchain-based framework using smart contracts for supply chain collaboration

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  • Tarun Kumar Agrawal
  • Jannis Angelis
  • Wajid Ali Khilji
  • Ravi Kalaiarasan
  • Magnus Wiktorsson

Abstract

Blockchain technologies can support traceability, transparency and trust among participants. This has primarily been explored in established supply chains and not in the growing use of business networks or ecosystems, which is a notable limitation since supply chains typically are organised with a dominant actor that ensures common information systems and standards that negate blockchain benefits. Hence, this study explores the design of a blockchain-based collaborative framework for resource sharing using smart contracts. These are particularly well-suited for supporting operations in broader networks or ecosystems beyond supply chains with established collaborations and hierarchies. Based on a systematic literature review, a demonstrator framework was developed for stakeholder interactions through a procurement and distribution unit backed with blockchain technology. The framework consists of (a) network architecture to demonstrate partner interactions; (b) rules for network working principles based on supply collaboration requirements; (c) UML diagram to define smart contract interaction sequence; and (d) algorithm for smart contract network verification and validation. Applicability of these smart contracts was verified by deployment on an Ethereum blockchain. The demonstrator framework ensures quality and data authenticity in supply networks, so it is useful for effective resource utilisation in networks where outsourcing and production surpluses are major issues.

Suggested Citation

  • Tarun Kumar Agrawal & Jannis Angelis & Wajid Ali Khilji & Ravi Kalaiarasan & Magnus Wiktorsson, 2023. "Demonstration of a blockchain-based framework using smart contracts for supply chain collaboration," International Journal of Production Research, Taylor & Francis Journals, vol. 61(5), pages 1497-1516, March.
  • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:5:p:1497-1516
    DOI: 10.1080/00207543.2022.2039413
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    Cited by:

    1. Yong Eui Kim & Sang-Min Choi & Dongwoo Lee & Yeong Geon Seo & Suwon Lee, 2023. "A Reliable Prediction Algorithm Based on Genre2Vec for Item-Side Cold-Start Problems in Recommender Systems with Smart Contracts," Mathematics, MDPI, vol. 11(13), pages 1-25, July.

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