Article ID: | iaor20127909 |
Volume: | 46 |
Issue: | 10 |
Start Page Number: | 1690 |
End Page Number: | 1706 |
Publication Date: | Dec 2012 |
Journal: | Transportation Research Part A |
Authors: | Cheng Yung-Hsiang, Liu Kuo-Chu |
Keywords: | statistics: inference, statistics: regression |
Bicycles and transit systems are considered to be the pinnacle of green transportation. The combined use of the two could provide a competitive alternative for an integrated, green, and seamless service, yet relatively few studies have investigated the multimodal integration problems of the entire service chain from the perspective of users. Users’ perceived inconvenience during travel can be regarded as a latent construct that describes an unobservable and immeasurable characteristic. Nevertheless, the traditional Likert method in an ordinal scale causes a misleading statistical inference. The Rasch model eliminates such bias generated by an ordinal scale through a logistic linear transformation, and it compares person parameters with item parameters, which are then subjected to a logarithmic transformation along a logit scale to clearly identify which service items’ inconvenience cannot be easily overcome by certain users. This empirical study demonstrates that perceived inconveniences differ based on the users’ sex, riding frequency, trip purpose, and environmental awareness. The differential item functioning analysis that was adopted in this study can identify the critical factors leading to the differences in perceived inconvenience. Our empirical results suggest that a male cyclist who is a commuter with a high monthly riding frequency and who is environmentally conscious has a better ability than their counterpart to overcome perceived inconveniences during travel using a bicycle‐transit service. To effectively mitigate users’ perceived inconvenience, the Rasch analytical results suggest that the improvement of the intra‐transit system factors in the short term and the improvement of external environmental factors in the long term will be successful. The information herein proves useful for transportation planners and policy makers when considering the special travel needs of certain groups to create a user‐friendly bicycle‐transit travel environment that promotes its usage.