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TRB 90th Annual Meeting (January 23-27, 2011)
Event Number:411
Event Title:Bicycle Planning and Policy
Event Date:Jan 24 2011 7:30PM- 9:30PM
Event Location:Hilton, International Center
Event Description:
Event Agenda:

Attitudinal Bicycle Commuting Market Segmentation in Nanjing, China: Structural Equation Modeling Approach (11-2389)
    
The primary purpose of this paper is to identify travelers¡¯ willingness to commute by bicycles and to investigate the effects of their attitudes on this willingness. To achieve this objective, an attitudinal market segmentation method is presented with a case study of Nanjing in China. This approach uses structural equation modeling (SEM) to simultaneously identify the travelers¡¯ cognitive and affective attitudes, perceptual evaluation on bicycling, and willingness to use bicycles. According to the result of SEM, three attitudes have highly significant effects on the willingness to use bicycle. It is found that travelers¡¯ desire for comfort is negatively related to the willingness; while both their need for fixed schedule and environmental consciousness have positive impacts. And then travelers are clustered into several distinct segments by using these three attitudes and the willingness as segmentation variables in K-Means clustering. The K-Means analysis gives six segments with varying willingness. Each segment is also a unique combination of cognitive and affective attitudes, suggesting that the same willingness can take place for different reasons and that the same attitude can lead to different willingness. The results of attitudinal market segmentation can also identify the potential ¡®mode switchers¡¯ and provide information for developing focused strategies to well serve the targeted segment and to promote more bicycle usage.

Authors
     Yang, Chen , Shanghai City Comprehensive Transportation Planning Institute, China
     Wang, Wei , Southeast University, China
     Xu, Chengcheng , Southeast University, China
     Li, Zhibin , Southeast University, China
     Shan, Xiaofeng , University of Wisconsin, Madison
     Jin, Jing , University of Texas, Austin


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