Temporal Analysis of Nonmandatory Trip Frequency Using an Adaptive Multivariate Ordered Probit Model: Empirical Investigation in Shanghai, China

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.