A blockchain-based approach for a multi-echelon sustainable supply chain
V. K. Manupati,
Tobias Schoenherr,
M. Ramkumar,
Stephan M. Wagner,
Sai Krishna Pabba and
R. Inder Raj Singh
International Journal of Production Research, 2020, vol. 58, issue 7, 2222-2241
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.
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (27)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2019.1683248 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:58:y:2020:i:7:p:2222-2241
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2019.1683248
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().