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Exploring the potential of Blockchain-enabled Lean Automation in supply chain management: A systematic literature review, classification taxonomy and future research agenda

Jackson, Aaron, Spiegler, V.L.M., Kotiadis, Kathy (2023) Exploring the potential of Blockchain-enabled Lean Automation in supply chain management: A systematic literature review, classification taxonomy and future research agenda. Production Planning and Control, . pp. 1-20. ISSN 0953-7287. E-ISSN 1366-5871. (doi:10.1080/09537287.2022.2157746) (KAR id:98485)

Abstract

The purpose of this study is to evaluate how Blockchain Technology (BCT) can support the implementation of Lean Automation. We conducted a systematic literature review to understand how BCT is being implemented in the supply chain management (SCM) domain and to evaluate how this technology can be used to reduce inefficiencies in supply chains. Firstly, we developed a holistic taxonomy of wastes to identify most common non-value activities. Then, both inductive and deductive content analyses were performed, the latter being coded using the taxonomy. Our findings identified the most common BCT-based application themes in SCM and ways that this technology can be used to support future implementation of Blockchain-enabled Lean Automation – B-eLA. Additionally, we proposed a future research agenda. The study provides important contributions on the intersection between the BCT, lean production and Industry 4.0 within SCM context and seeks to exploit BCT’s potential to improve businesses’ efficiency and effectiveness.

Item Type: Article
DOI/Identification number: 10.1080/09537287.2022.2157746
Uncontrolled keywords: Blockchain Technology, Lean Automation, Supply Chain Management
Subjects: H Social Sciences
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Virginia Spiegler
Date Deposited: 29 Nov 2022 11:39 UTC
Last Modified: 22 Feb 2024 00:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/98485 (The current URI for this page, for reference purposes)

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