Application of blockchain and smart contracts in autonomous vehicle supply chains:An experimental design

Abstract

With the rise of digital sustainable business models in the Autonomous Vehicles (AV) industry, the traditional automakers are undergoing a major restructuring in their key performance areas and associated supply chains processes. Focusing on an innovative AV design (AD) concept, this paper investigates how Artificial Intelligence (AI) and Blockchain-based Smart Contracts can enhance sustainable supply chain operations. A novel design element, Margin Indicator (MI), is developed to obtain reliable predictive analytics results from the mainstream machine learning algorithms. The proposed approach supports a robust control of costs and energy, while maintaining a high level of transparency in managing decentralized AV supply chain processes, monetary impacts, and environmental sustainability. Testing the developed concept through a preliminary case study, we observed a reduction in energy wastage and hidden financial transactions by 12.48% and 11.58%, respectively. Supported by the rapid advancement in the blockchain and AI technologies, the developed framework is expected to improve product traceability, transaction transparency, and sustainable economic growth for the AV supply chains.

Publication DOI: https://doi.org/10.1016/j.tre.2022.102864
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences
Additional Information: Copyright © 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Artificial intelligence,Autonomous vehicle,Blockchain,Digital supply chain,Smart contract,Sustainable logistics,Business and International Management,Civil and Structural Engineering,Transportation
Publication ISSN: 1366-5545
Last Modified: 30 Apr 2024 07:33
Date Deposited: 22 Mar 2023 09:49
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 2459?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2022-09
Published Online Date: 2022-08-23
Accepted Date: 2022-08-05
Authors: Arunmozhi, Manimuthu (ORCID Profile 0000-0003-4909-4880)
Venkatesh, V. G.
Arisian, Sobhan
Shi, Yangyan
Raja Sreedharan, V.

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