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“Transportation for A Better Life:
Smart Mobility for Now and Then”
23 August 2019, Bangkok, Thailand
Subjective norm (SN) also have a significant system has received great attention by the traveler.
positive effect on intentions. Compared to other This paper investigates intention to use bike sharing
latent factors, SN is most positively affecting to system of campus user.
intention. This mean if the reference group, such as A sample of 396 participants completed a
parents, friends, and girlfriends use bike sharing questionnaire survey that measurement a series of
and/or support the traveler to use bike sharing, the factors according to the Theory of Planned Behavior
traveler will have more intention to use bike sharing. (TPB). Structure equation models (SEM) technique
However, if their referent people not use or not is used to test causal structure of the models.
support them to use, they will reduce the intention to The results showed that campus traveler
use as well. show moderate intention to use bike sharing system.
Perceived behavior control (PBC) in this study, Intention to use are mainly affected by positive
however, has no significant effect on the intention of attitude toward bike sharing and bike sharing
using bike sharing. subjective norm. The perceived bike sharing ese,
however, has no significant effect to using intention.
Table 4 Fit Measures (Hair et al, 2006) Form this initial finding, promoting bike
sharing intention should focus on boosting positive
Index
Fitness index Ideal value attitude and subjective norm. In addition, as
value
perceived behavioral control in this study has no
Absolute fit measure effect to intention, it is interesting to further reveal
P - value 0.02 < 1.00 the influence of perceived behavioral control and
2
X /df 1.85 < 3.00 intention to behavior. This study helps to understand
RMSEA 0.05 < 0.08 the factors that affect the intention of using bike
GFI 0.97 > 0.90 sharing in non-bike culture community.
AGFI 0.94 > 0.90
RMR 0.03 < 1.00 References
SRMR 0.03 < 1.00
[1] Ajzen, I. (2006). A theory of planned behavior.
Organizational Behaviour and Human Decision
Processes, 50, 179-211.
[2] Hair, J. F. Jr. Black, W. C., Babin, B. J.
Anderson, R. E. and Tatham, R. L. 2006.
Multivariate data analysis. (6thed). New Jersey:
Prentice Hall.
[3] Rietveld P, Daniel V. Determinants of bicycle
use: Do municipal policies matter?
Transportation Research Part A Policy Practice.
2004;38(7):531–50.
[4] Hunt JD, Abraham JE. Influences on bicycle use.
Transportation (Amst). 2007;34(4):453–70.
[5] Efthymiou D, Antoniou C, Waddell P. Factors
affecting the adoption of vehicle sharing systems
by young drivers. Transport Policy [Internet].
2013;29:64–73.
[6] Kaplan S, Manca F, Alexander T, Nielsen S,
Prato CG. Intentions to use bike-sharing for
holiday cycling: An application of the Theory of
Planned Behavior. Tour Manage [Internet].
Fig. 4 Intention to use bike sharing.
2015;47:34–46.
*p < 0.05, **p < 0.01, ***p < 0.001 [7] Prieto M, Baltas G, Stan V. Car sharing adoption
intention in urban areas: What are the key
5. CONCLUSIONS sociodemographic drivers? Transport Research
Although Khon Kaen University is a non- Part A Policy Practice. [Internet]. 2017;101:218–
bike culture community, the pilot bike sharing 27.
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