Effect of Robo-Taxi User Experience on User Acceptance: Field Test Data Analysis

Cited 2 time in webofscience Cited 0 time in scopus
  • Hit : 1004
  • Download : 0
With the advancement of self-driving technology, the commercialization of robot taxi (Robo-taxi) services is expected. However, there is some skepticism as to whether such taxi services will be successfully accepted by real customers because of perceived safety-related concerns; therefore, studies focused on user experience have become more crucial. Although many studies statistically analyze user experience data obtained by surveying individuals' perceptions of Robo-taxis or indirectly through simulators, there is a lack of research that statistically analyzes data obtained directly from actual Robo-taxi service experiences. Accordingly, based on the user experience data obtained by implementing a Robo-taxi service in the downtown of Seoul and Daejeon in South Korea, this study quantitatively analyzes the effect of user experience on user acceptance through structural equation modeling and path analysis. Balanced and highly valid insights were also obtained by re-analyzing meaningful relationships obtained through statistical models based on the results of in-depth interviews. The results revealed that the experience of the traveling stage had the greatest effect on user acceptance, and the cutting-edge nature of the service and apprehension of technology were emotions that had a significant effect on user acceptance. Based on these findings, guidelines are suggested for the design and marketing of future Robo-taxi services.
Publisher
SAGE PUBLICATIONS INC
Issue Date
2022-02
Language
English
Article Type
Article
Citation

TRANSPORTATION RESEARCH RECORD, v.2676, no.2, pp.350 - 366

ISSN
0361-1981
DOI
10.1177/03611981211041595
URI
http://hdl.handle.net/10203/292406
Appears in Collection
GT-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 2 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0