Abstract
The new energy vehicle (NEV) is emerging as an important alternative in the automobile industry in its potential to alleviate environmental pollution and contribute to carbon neutrality. The rapid growth of NEVs has been reflected in the scaling up of electric vehicle battery production. The dramatic increase of retired batteries, however, exposes the technological limitations in current recycling operations, which will ultimately impede the sustainable development of the NEV supply chain. Blockchain technology (BT) adoption provides a solution by contributing to the construction of an efficient recycling network. Our research investigates the influence of carbon reduction instruments on the uptake of BT. The key findings are as follows. Under a carbon tax system, (1) carbon emission reduction encourages the battery supplier to adopt BT; (2) BT adoption increases the profits of NEV supply chain stakeholders. Under carbon cap-and-trade regulations, (1) the unit outsourcing fee and the performance of the BT impact the investment decision of the manufacturer; (2) the profit of the third-party enterprise is increased by introducing the BT. Under both policies, improving the efficiency of BT helps to upgrade the traceability level and contribute to carbon neutrality in the NEV supply chain.
Data availability statement
Data sharing is not applicable to this article as no new data were created or analysed in this study.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 EIA (Energy Information Administration). 2021a. EIA projects nearly 50% increase in world energy use by 2050, led by growth in renewables. https://www.eia.gov/todayinenergy/detail.php?id=49876.
2 IEA (International Energy Agency). 2021. Electric vehicles, IEA, Paris. https://www.iea.org/reports/electric-vehicles.
3 Kelty, K. 2011. Tesla’s closed loop battery recycling program. https://www.tesla.com/blog/teslas-closed-loop-battery-recyclingprogram.
4 Diamond, J. W., and Zodrow, G. R. 2018. The effects of carbon tax policies on the US economy and the welfare of households. https://www.energypolicy.columbia.edu/research/report/effects-carbon-tax-policies-us-economy-and-welfare-households.
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Notes on contributors
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Zhangwei Feng
Zhangwei Feng is a Lecturer in the School of Business at Ningbo University. His research interest focuses on sustainable operations management and closed-loop supply chain management. He has published about 10 articles in academic journals, including International Transactions in Operational Research, Journal of Cleaner Production, Annals of Operations Research, Journal of Industrial and Management Optimization, and European Journal of Industrial Engineering. Email: [email protected]
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Na Luo
Na Luo (Rona) is an associate professor in the School of Public Administration at Dongbei University of Finance & Economics. She was working as a post-doc research fellow at the University of Auckland Business School in 2022. Her research interests include circular economy and sustainable supply chain management. She published her research in several OM journal, including Transportation Research Part E: Logistics and Transportation Review, International Journal of Logistics Management, and European Journal of Industrial Engineering. Email: [email protected]
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Timofey Shalpegin
Timofey Shalpegin is a lecturer at the University of Auckland Business School. He received PhD in Operations and Supply Chain Management at HEC Paris in 2015. His research interests include game-theoretic applications in collaborative product development and new technologies in supply chain management. He published his research in such journals as Production and Operations Management, European Journal of Operational Research, and Omega. Email: [email protected]
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Huan Cui
Cui Huan is a graduate student at School of Software & Microelectronics, Peking University. He has been engaged in supply chain management and large-scale information system management for many years. His research interests focus on new technology application and industrial data analysis. Email: [email protected]