Evaluating market-based interventions for heavy-duty zero-emission truck adoption under consumer heterogeneity
File(s)
Published version
Author(s)
Tan, Zhenyu
Oluleye, Gbemi
Type
Journal Article
Abstract
This research aims to assess the effects of different market-based interventions on accelerating the adoption of heavy-duty zero-emission trucks (ZETs). A novel agent-based model is developed and applied to simulate heterogeneous consumer choices across three heavy-duty truck segments, namely 49t tractor-trailers, 31t dump trucks, and 18t straight trucks, while accounting for perceived risks. The analysis also considers three powertrain options: internal combustion engine trucks, battery electric trucks, and hydrogen fuel cell trucks. The assessment covers 56 policy scenarios, including hydrogen subsidies, purchase subsidies, electricity subsidies, operational subsidies, diesel taxes, and various combinations of these interventions. The results indicate that while subsidies are effective in promoting ZET adoption, they are costly; however, diesel taxation can help finance these measures. Therefore, policy combinations appear to be more effective. The analysis further shows that the effectiveness of interventions may diminish over time and that better alignment between specific policy instruments and truck types may improve policy efficiency. The simulation also reveals competition between different ZET technologies, which may lead to policy inefficiencies. This research contributes to the literature by demonstrating the impacts of market-based interventions on adoption behaviour beyond total cost of ownership calculations.
Date Issued
2026-08-01
Date Acceptance
2026-06-09
Citation
Engineering Science and Technology, an International Journal, 2026, 80
ISSN
2215-0986
Publisher
Elsevier
Journal / Book Title
Engineering Science and Technology, an International Journal
Volume
80
Copyright Statement
© 2026 The Author(s). Published by Elsevier B.V. on behalf of Karabuk University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
10.1016/j.jestch.2026.102442
Publication Status
Published
Article Number
102442
Date Publish Online
2026-06-15