Application of Blockchain and Smart Contracts in Autonomous Vehicle Supply Chains: An Experimental Design

M. Arunmozhi, V.G. Venkatesh, S. Arisian, Y. Shi and V. Raja Sreedharan
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V.G. Venkatesh: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School

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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. © 2022 Elsevier Ltd

Keywords: algorithm; artificial intelligence; Artificial intelligence; Autonomous vehicle; Blockchain; Digital supply chain; economic growth; experimental design; machine learning; Smart contract; supply chain management; sustainable development; Sustainable logistics; technology adoption (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

Published in Transportation Research Part E: Logistics and Transportation Review, 2022, 165, ⟨10.1016/j.tre.2022.102864⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04452839

DOI: 10.1016/j.tre.2022.102864

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