Author
Listed:
- Nguyen-Phuoc, Duy Quy
- Truong, Thi Minh
- Ho-Mai, Thao Nhi
- Luu, Tuan Trong
- Li, Zhi-Chun
Abstract
In low- and middle-income countries, the extensive use of internal combustion engine motorcycles contributes to environmental degradation and urban challenges. Electric motorcycles (EMs) present a viable solution, yet their adoption remains limited. While previous research has primarily focused on technological knowledge, less attention has been given to the influence of consumer awareness regarding government subsidies and EMs’ technological advancements on adoption behavior. This study addresses this gap by extending the Value-Attitude-Behavior (VAB) model to include two underexplored constructs: (1) knowledge and awareness of government subsidy policies and initiatives, and (2) knowledge and awareness of AI-driven benefits for EMs. The study also investigates the moderating role of consumers’ technology interest and engagement within the VAB framework. Using data collected in Vietnam and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM), the results obtained demonstrate that the added knowledge and awareness-related constructs, alongside perceived value, significantly influence the intention to adopt EMs. Additionally, consumers’ technology interest and engagement are found to moderate these relationships. These findings highlight the importance of targeted policies and strategies that address knowledge gaps and leverage consumer engagement to accelerate EM adoption, promoting a sustainable transformation in the transportation sector.
Suggested Citation
Nguyen-Phuoc, Duy Quy & Truong, Thi Minh & Ho-Mai, Thao Nhi & Luu, Tuan Trong & Li, Zhi-Chun, 2026.
"How do the awareness of AI benefits and government subsidies affect green transport adoption: the moderating role of technology interest and engagement,"
Transportation Research Part A: Policy and Practice, Elsevier, vol. 204(C).
Handle:
RePEc:eee:transa:v:204:y:2026:i:c:s0965856425004793
DOI: 10.1016/j.tra.2025.104846
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:204:y:2026:i:c:s0965856425004793. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.