Unravelling experiences of transit captivity with time-geography: The case of commuters in Jakarta Metropolitan area

• The time-geography approach revealed user segmentation shaped by constraints beyond typical socio-demographic factors. • Three distinct clusters emerged with different levels of transit captivity . • Capability and coupling constraints play a significant role in defining transit captivity. • Semi-captive is an intermediate group and is statistically distinct from captive and choice. • Constraint-based clusters deliver actionable insights for policymakers to address the specific needs of vulnerable users. Captive transit users are likely to be more vulnerable to public transport service disruptions than choice users. However, what precisely is a captive user? Sociodemographic characteristics have up till now been mainly used to make assumptions on who are captive and who are choice users. However, transit users with similar sociodemographic characteristics may have distinct life situations and spatiotemporal constraints. This study contributes to understanding public transport captivity by examining perceived captivity concerning experienced and measured spatiotemporal constraints, following time-geography theory. Based on a 2022 survey in the Greater Jakarta Metropolitan Area, two-way clustering based on perceived constraints was used to capture transit user segments. Ordinal regression analysis was then performed to examine the role of constraint perception segment membership in comparison to measurable sociodemographic factors and spatial instrumental capability constraints in explaining perceived transit captivity. Results revealed that perceived capability and coupling constraints are significant factors in defining transit user segments. Three clusters were identified: flexible commuters, commuters with responsibilities, and non-driving constrained commuters. The findings show that non-driving constrained commuters and commuters with responsibilities (to a lesser extent) are more captive than flexible commuters. Segmenting users based on an individual time-geography approach helps to accurately identify captive and choice users and the in-between groups. Results provide insights for policymakers about the most vulnerable groups. It helps to develop tailor-made strategies targeting different transit user segments with differing constraints to promote transit usage and reduce transport poverty.