Abstract
The importance of using multipurpose smart cards in transit systems has been recently recognized by users and transit operation agencies. However, only a few studies have focused on users' perspectives when researching the use of multipurpose smart cards in transit systems. This study thus adopts the revised new product adoption model and considers the specific characteristics of transit use as a research framework to examine the effects of constructs on consumer intention to use smart cards in transit systems. The first stage of the study employs structural equation modeling (SEM). Critical attributes identified during the first-stage survey are then extracted to design the stated preference method questionnaire for the second stage. During this stage, user choice behavior is investigated and changes in the adoption rates of different payment alternatives are predicted under various scenarios. Data from two metropolitan areas are then analyzed and compared. SEM analysis results reveal that consumer use intention is significantly influenced by perceived product attribute, promotion strategy, and perceived risk. The last one is demonstrated to have an effect on perceived product attribute for consumers in terms of metropolitan difference. Initial card cost, transit fare, consumption discount, and personal information protection are further considered as critical factors that affect the possible adoption rate of smart card use in transit systems based on the analytical results obtained by the mixed logit model. The sensitivity analysis results indicate that reducing transit fare and protecting personal information significantly impact adoption rate changes of different payment alternatives. This study also offers several managerial implications and suggests future research directions.
Original language | English |
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Pages (from-to) | 363-384 |
Number of pages | 22 |
Journal | Journal of Intelligent Transportation Systems: Technology, Planning, and Operations |
Volume | 20 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2016 Jul 3 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Software
- Information Systems
- Automotive Engineering
- Aerospace Engineering
- Computer Science Applications
- Applied Mathematics