Comparing shared autonomous vehicle adoption in Beijing and Busan: The role of rideshare perception

Understanding shared autonomous vehicle (SAV) adoption requires attention to psychological dispositions and contextual influences. This study investigates how perceptions related to ridesharing, particularly the willingness to rideshare (WTRS), shape SAV adoption intentions in two contrasting urban contexts: Beijing, China and Busan, South Korea. Employing a hybrid choice modeling framework, we incorporated latent psychological constructs including technology savviness, trust in fellow passengers, perceived economic benefits, environmental consciousness, and privacy concerns, along with socio-demographic variables. The results confirm that the WTRS is a significant predictor of SAV adoption in both cities. However, a posterior analysis of the latent variable distributions reveals that Busan respondents, despite exhibiting lower technology savviness, weaker trust in fellow passengers, lower environmental consciousness, and stronger privacy concerns than their Beijing counterparts, express greater interest in adopting SAVs. This divergence suggests that psychological readiness alone does not fully account for behavioral intentions. It may reflect practical considerations, such as limited mobility or higher transportation costs in the region, which can heighten interest in shared mobility services despite lower psychological readiness. Therefore, a nuanced understanding of both attitudinal and contextual drivers is essential for promoting equitable and context-sensitive SAV deployment.

Authors

Institutions

Publication Details

Journal
Journal of Transport Geography
Published
2026-04-02
DOI
https://doi.org/10.1016/j.jtrangeo.2026.104647
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparing shared autonomous vehicle adoption in Beijing and Busan: The role of rideshare perception

Haotian Zhong, Jinuk Hwang, Fei Wang, Jinhyeok Jang et al.
Journal of Transport Geography
Transportation and Mobility Innovations
article

Comparing shared autonomous vehicle adoption in Beijing and Busan: The role of rideshare perception

Haotian Zhong, Jinuk Hwang, Fei Wang, Jinhyeok Jang, Gahyeong Yu, Sunxuhan Wang
article en

Abstract

Understanding shared autonomous vehicle (SAV) adoption requires attention to psychological dispositions and contextual influences. This study investigates how perceptions related to ridesharing, particularly the willingness to rideshare (WTRS), shape SAV adoption intentions in two contrasting urban contexts: Beijing, China and Busan, South Korea. Employing a hybrid choice modeling framework, we incorporated latent psychological constructs including technology savviness, trust in fellow passengers, perceived economic benefits, environmental consciousness, and privacy concerns, along with socio-demographic variables. The results confirm that the WTRS is a significant predictor of SAV adoption in both cities. However, a posterior analysis of the latent variable distributions reveals that Busan respondents, despite exhibiting lower technology savviness, weaker trust in fellow passengers, lower environmental consciousness, and stronger privacy concerns than their Beijing counterparts, express greater interest in adopting SAVs. This divergence suggests that psychological readiness alone does not fully account for behavioral intentions. It may reflect practical considerations, such as limited mobility or higher transportation costs in the region, which can heighten interest in shared mobility services despite lower psychological readiness. Therefore, a nuanced understanding of both attitudinal and contextual drivers is essential for promoting equitable and context-sensitive SAV deployment.

Journal of Transport GeographyVol. 133
Urban Land Institute (US), Pusan National University (KR), Renmin University of China (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Ministry of Education, Ministry of Land, Infrastructure and Transport
Sustainable cities and communities
Openalex Percentile: Top 12%
Transportation and Mobility Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.