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Sustainability 2015, 7(11), 14558-14573; doi:10.3390/su71114558

Predicting Public Bicycle Adoption Using the Technology Acceptance Model

1
Department of Marketing and Supply Chain Management, University of Tennessee, Knoxville, TN 37996, USA
2
Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, OH 45433-7765, USA
3
Department of Economics, Beijing Jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Academic Editor: Giuseppe Ioppolo
Received: 8 September 2015 / Revised: 23 October 2015 / Accepted: 26 October 2015 / Published: 30 October 2015
(This article belongs to the Special Issue Green Logistics)
View Full-Text   |   Download PDF [840 KB, uploaded 30 October 2015]   |  

Abstract

Bicycle sharing programs provide a sustainable mode of urban transportation. Although cities across the globe have developed these systems for their citizens and visitors, usage rates are not as high as anticipated. This research uses the technology acceptance model as the basis to understand one’s intention to adopt bicycle sharing programs. Using survey data derived from 421 participants in Beijing, China, the proposed covariance-based structural equation model consisting of perceived quality, perceived convenience, and perceived value is found to predict 50.5% of the variance in adoption intention. The findings of this research contribute to theory and practice in the burgeoning literature on public bicycle systems and sustainable urban transportation by offering a theoretical lens through which to consider system adoption, and providing information to practitioners as to what factors might contribute most to adoption. View Full-Text
Keywords: bicycle-sharing; technology acceptance; perceived quality; structural equation modeling; urban transportation; green logistics bicycle-sharing; technology acceptance; perceived quality; structural equation modeling; urban transportation; green logistics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Hazen, B.T.; Overstreet, R.E.; Wang, Y. Predicting Public Bicycle Adoption Using the Technology Acceptance Model. Sustainability 2015, 7, 14558-14573.

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