Citation

Zhang C, Schmocker JD. Transportmetrica B: Transp. Dyn. 2019; 7(1): 223-236.

Copyright

(Copyright © 2019, Hong Kong Society for Transportation Studies, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/21680566.2017.1378599

PMID

unavailable

Abstract

Long-term travel behavior is difficult to observe and explain and even more difficult to forecast. This paper proposes an approach based on stochastic state equations to describe the gradual change of behavior over time by using panel data. Transition functions determine the likely change in behavior from one time period to another. To overcome the problem of a dynamic population and explain seasonal irregularities, we introduce 'life cycle', 'potential demand' and 'willingness to use' into our models. With this we discuss time-homogeneity issues, possibilities to identify usage states and calibrate the transition function. The model is applied to panel data from Kyoto University's bicycle share system. The errors between actual and estimated values are analyzed to evaluate two model specifications. The findings help us understanding adaptation, 'recovery' and drop-out behavior. Overall, we suggest the approach and results offer insights to a wider range of applications.

Language: en

Keywords

Behavior changes; Markov chain; panel data; stochastic process; user life cycle