Asset Details
Do you wish to reserve the book?
Temporal Analysis of Nonmandatory Trip Frequency Using an Adaptive Multivariate Ordered Probit Model: Empirical Investigation in Shanghai, China
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Temporal Analysis of Nonmandatory Trip Frequency Using an Adaptive Multivariate Ordered Probit Model: Empirical Investigation in Shanghai, China
Do you wish to request the book?
Temporal Analysis of Nonmandatory Trip Frequency Using an Adaptive Multivariate Ordered Probit Model: Empirical Investigation in Shanghai, China
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Temporal Analysis of Nonmandatory Trip Frequency Using an Adaptive Multivariate Ordered Probit Model: Empirical Investigation in Shanghai, China
2026
Overview
This study investigates the temporal evolution of nonmandatory trip frequencies in Shanghai over a decade using a temporally adaptive multivariate ordered probit (MOP) model. Two large‐scale travel surveys are pooled, and temporal changes are captured through year dummy interaction terms, year‐specific threshold shifts, and a year‐specific correlation structure. Parameters are estimated using full‐information maximum likelihood estimation with an analytic approximation of multivariate normal cumulative distribution. The findings reveal substantial decade‐long transformations in discretionary mobility. Gender differences narrowed or reversed across several activities; the impact of aging was apparent; occupational constraints persisted; the influence of central‐area residence intensified, reflecting uneven spatial development; and weekend effects weakened, indicating increasingly blurred boundaries between weekday and weekend activity patterns. Correlation patterns across activities also shifted, suggesting changes in trip chaining and time allocation. By developing a unified, temporally adaptive MOP framework capable of jointly capturing structural stability and temporal change, this study provides new empirical evidence on how nonmandatory trip adapts to rapid sociodemographic, economic, and spatial transformations. It offers rare evidence from a major megacity of developing country where activity‐based modeling applications remain limited. These insights support the design of context‐sensitive transportation and land‐use policies.
