Author
Listed:
- Kun Wang
(College of Civil Engineering, Anhui Jianzhu University, Hefei 230601, China
National-Local Joint Engineering Laboratory of Building Health Monitoring and Disaster Prevention Technology, Hefei 230601, China)
- Linfeng Qi
(College of Civil Engineering, Anhui Jianzhu University, Hefei 230601, China)
- Shuo Yang
(College of Civil Engineering, Anhui Jianzhu University, Hefei 230601, China
National-Local Joint Engineering Laboratory of Building Health Monitoring and Disaster Prevention Technology, Hefei 230601, China)
- Cheng Wang
(School of Architecture & Urban Planning, Anhui Jianzhu University, Hefei 230601, China)
- Rensu Zhou
(College of Civil Engineering, Anhui Jianzhu University, Hefei 230601, China)
- Jing Liu
(School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei 230601, China)
Abstract
As a key element of the sharing economy, ride-sharing plays a vital role in promoting sustainable urban mobility by optimizing vehicle utilization rates, lowering carbon emissions, and alleviating traffic congestion. Despite its cost-efficiency and sustainability benefits, ride-sharing adoption remains limited in the post-pandemic period due to behavioral changes and safety concerns. Accordingly, using survey data from 425 commuters in Hefei, concerns about COVID-19 and satisfaction with ride-sharing services were integrated into the theory of planned behavior framework. Structural equation modeling was applied to examine the relationship between ride-sharing intention and actual usage behaviors. The results indicated that ride-sharing intention was significantly positively affected by subjective norms (β = 0.428 ***), service satisfaction (β = 0.315 ***), and perceived behavioral control (β = 0.162 *), but significantly negatively affected by concerns about COVID-19 (β = −0.183 **). Concerns about COVID-19 significantly negatively affected travelers’ actual ride-sharing behaviors (β = −0.2 **). Furthermore, ride-sharing intention was identified as a significant positive predictor of travelers’ behaviors: specifically, their likelihood of accepting a ride-sharing order (β = 0.395 ***). These findings offer transport authorities evidence-based strategies for designing targeted interventions during health crises, particularly through reinforcing social norms, improving service quality, and implementing transparent health protocols to ensure both user safety and sustainability.
Suggested Citation
Kun Wang & Linfeng Qi & Shuo Yang & Cheng Wang & Rensu Zhou & Jing Liu, 2025.
"Towards Sustainable Mobility: Factors Influencing the Intention to Use Ride-Sharing in the Post-Pandemic Era,"
Sustainability, MDPI, vol. 17(18), pages 1-17, September.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:18:p:8343-:d:1751615
Download full text from publisher
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:gam:jsusta:v:17:y:2025:i:18:p:8343-:d:1751615. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.