Examining attitudes toward bicycle-share program use: A dual-process theory approach.
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| Title: | Examining attitudes toward bicycle-share program use: A dual-process theory approach. |
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| Authors: | Chen, Li-Hsin1 (AUTHOR) Lihsinc@g.clemson.edu, Chancellor, H. Charles1 (AUTHOR) hchance@clemson.edu |
| Source: | Transportation Research: Part F. Apr2019, Vol. 62, p769-781. 13p. |
| Subjects: | Implicit attitudes, Cycling, Global warming, Human research subjects, Theory, Bridge testing |
| Abstract: | • Participants implicitly hold more positive attitudes toward cycling than cyclists. • Participants explicitly hold more positive attitudes toward cyclists than cycling. • Positive attitude towards cyclists is the most critical driver of leisure BSP use. • No relationship is found between implicit attitudes and leisure BSP use. The transportation sector, the largest contributor to global warming, is responsible for around 75% of the tourism industry's total CO 2 emissions. Accordingly, encouragement of eco-friendly travel behavior has come to the fore as a key tourism-industry responsibility. One promising alternative transportation option, bicycle-share programs (BSPs), have developed rapidly over the past two decades, but studies of non-commuter BSP use have been limited. Moreover, the small body of BSP research that does exist has mostly applied social-cognitive models to explore individuals' rational decision-making processes, while largely ignoring the influences of emotional and intuitive factors. This study utilized Single Target Implicit Association Tests to bridge this gap by examining the influences of individuals' dual attitudes toward leisure use of BSPs. The results suggest that the research participants generally have favorable implicit attitudes toward both leisure-time cycling and leisure cyclists. Overall, this study points to a potentially fruitful new direction for future work. [ABSTRACT FROM AUTHOR] |
| Copyright of Transportation Research: Part F is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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