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A blockchain-based approach for a multi-echelon sustainable supply chain.

Authors :
Manupati, V. K.
Schoenherr, Tobias
Ramkumar, M.
Wagner, Stephan M.
Pabba, Sai Krishna
Inder Raj Singh, R.
Source :
International Journal of Production Research; Apr2020, Vol. 58 Issue 7, p2222-2241, 20p, 5 Diagrams, 9 Charts, 1 Graph
Publication Year :
2020

Abstract

Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207543
Volume :
58
Issue :
7
Database :
Complementary Index
Journal :
International Journal of Production Research
Publication Type :
Academic Journal
Accession number :
142617311
Full Text :
https://doi.org/10.1080/00207543.2019.1683248