Abstract
This paper is aimed to propose a new framework and methodology to incorporate service quality and inertia effect into stated preference model. We use structure equation model and stated preference method to conduct with psychological and quantitative attributes. The logistics regression is used to generalize inertia effect and to explore casual influences of important factors on inertia effect. The empirical data is focus on the choice behavior of intercity bus transport. The computer questionnaire is based on the each traveler’s experiences in RP choice to design the corresponding SP scenario in avoiding to the response bias. The results of logistics regression show that there are significant casual influences between inertia index and number of alternative, traveling frequency, and personal income. The estimating results of MNL model prove that the specification of generalizing inertia index has the better model fitness than the traditional 0-1 inertia index.
