Journal article
IoT-Blockchain: Harnessing the Power of Internet of Thing and Blockchain for Smart Supply Chain
Sensors, Vol.21(18), pp.1-25
2021
PMID: 34577261
Abstract
This study aims to build smart supply chains for the first time using the internet of things (IoT) and blockchain. Classification and clarification of causal relationships can provide a useful framework for researchers and professionals who seek to implement an intelligent supply chain using IoT tools in a blockchain platform, and it also demonstrates the intensity of communications indicating such relationships. The research methodology is mixed method, comprised of qualitative and quantitative methods. The qualitative method includes the Delphi method used for selecting indigenous components and features proper for the pattern. The quantitative method is the Dematel method used for assessing the relationships between the available concepts in the pattern and accessing the network structure between components. Interpretative Structural Modeling is also employed to classify the network structure obtained from the Dematel technique. The findings of the study identify indicators of IoT and blockchain as causes based on Dematel, application of tools, components interconnectedness, optimal decision making, automatedness, integration, innovation and learning, which are indicators of smart supply chain, are the effects in this study.
Details
- Title
- IoT-Blockchain: Harnessing the Power of Internet of Thing and Blockchain for Smart Supply Chain
- Authors
- Neda Azizi - Torrens University AustraliaHeliyeh Malekzadeh - Iran University of Science and TechnologyPeyman Akhavan - Iran University of Science and TechnologyOmid Haass - RMIT UniversityShahrzad Saremi - Torrens University AustraliaSeyedali Mirjalili (Corresponding Author) - Torrens University Australia
- Publication details
- Sensors, Vol.21(18), pp.1-25
- Publisher
- MDPI AG
- Date published
- 2021
- DOI
- 10.3390/s21186048
- ISSN
- 1424-8220
- PMID
- 34577261
- Copyright note
- © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- Not applicable.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991136503902621
- Output Type
- Journal article
Metrics
2 File views/ downloads
33 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Chemistry, Analytical
- Engineering, Electrical & Electronic
- Instruments & Instrumentation