Suburban rail systems play a crucial role in connecting satellite towns to central cities; however, many lines suffer from low ridership, posing challenges to their long-term sustainability. Previous studies have mainly concentrated on urban rail networks and analyses at the individual station level, frequently neglecting the spatio-temporal variations in suburban rail travel and the integration between origin and destination stations. This study proposes an integrated multiplicative spatio-temporal station-to-station model, which captures the interactions of the built environment around origin–destination stations and enables the estimation of spatial and temporal variability in suburban rail ridership. An empirical analysis is conducted using smart card data from the suburban and urban rail networks in Nanjing, China. The findings reveal built environment variables have a significant spatio-temporal heterogeneity in their impacts on suburban rail ridership. Commercial areas around origin stations and transportation-hub areas around destination stations show the strongest positive associations with suburban station boardings and alightings, respectively, followed by residential and workplace areas. Residential areas on the inner suburbs’ Yangtze River west bank, workplaces on the east bank, and hospitals in the outer suburbs most strongly influence suburban rail ridership. Additionally, commercial areas significantly enhance suburban rail ridership throughout almost the entire daytime.
Limited road accessibility remains a major constraint to socioeconomic development in remote and low-income regions. While substantial investments have been made in transport infrastructure to address this challenge, we still know little about how the economic effects of road investments evolve across space and over time. Limited data on infrastructure interventions and local economic outcomes often hinder rigorous impact evaluations. This study addresses these challenges by combining recent advances in causal inference and geospatial analysis. Using Kenya as a case study, we construct a panel spanning 2002–2022 using time-series road network data to estimate travel time to the nearest urban centers and how it changed over time. We link these measures to high-resolution proxies of economic activity, including gridded gross domestic product (GDP) and nighttime lights (NTL), and estimate causal effects using a heterogeneity-robust difference-in-differences framework. Results suggest that reductions in travel time are associated with positive changes in local economic activity that accumulate over time. However, impacts are spatially uneven, with stronger responses in agriculturally productive and non-marginalized regions and more limited effects in historically marginalized areas. Comparing accessibility measures derived from the full road network and from paved roads alone indicates no statistically significant difference in estimated GDP effects. Overall, the study advances transport geography by demonstrating how dynamic changes in accessibility shape spatially uneven development outcomes.
The loss of mobility among older adults can create significant barriers to grocery shopping, especially when combined with driving cessation and limited access to nearby food stores. While Online Grocery Shopping (OGS) may be a potential alternative to individuals living in food-poor environments, its adoption among older adults is modest.This study explores the relationship between indicators of access to food stores and intention for OGS in this population. We expect that greater perceived distances to primary food stores, lower accessibility to a variety of food stores, and residence in non-urban areas will each be positively associated with planning to use OGS.A survey collected during the winter of 2021 through an organization of older adults (n = 811) is used to assess the factors shaping intention for OGS. Two logistic regressions and Pearson chi-squared tests help examine the contribution of access to groceries on OGS intention, while controlling for socio-demographic characteristics and psychosocial determinants of OGS.The number and completeness of food store options within a ten-minute walk and the walking distance to respondents' primary food store are not significantly associated with planning to use OGS. Save for respondents in urban areas that are more likely to plan to use OGS, associations are concentrated on perceptions with respect to technologies, styles of shopping, and mobility issues. Recruitment via email ensures a baseline level of digital literacy; lower literacy in the population would potentially make older adults even less likely to trade poor access with OGS intention.Widespread availability of cars may make perceived walking distance less relevant to the attraction power of food stores. However, we find no sign that intention to use OGS may counter poor access to stores. If replication in other populations leads to similar results, this would undermine policy narratives that frame OGS as a viable solution to food access constraints for older adults aging in place.
Urban Living Labs (ULLs) have gained prominence as approaches to fostering sustainable urban mobility through experimentation, co-creation, and stakeholder participation. This editorial critically examines their potential and limitations in advancing inclusive, accessible, and sustainable mobility transitions, drawing on contributions to a special issue of the Journal of Transport Geography. Four interconnected themes emerge: the conditions for meaningful co-creation, the relationship between experimentation and transformative change, the geographical situatedness and transferability of ULLs, and the methodological and reflexive challenges of Living Lab research. The contributions demonstrate that participation does not necessarily translate into decision-making power, while short-term experiments often struggle to generate lasting institutional, behavioural, or systemic change. They further demonstrate that ULLs are shaped by local contexts and by the institutional and funding arrangements within which they operate, potentially reproducing existing power relations and technocratic priorities. We argue for a more critical and reflexive approach to ULLs, emphasizing equitable knowledge production, meaningful stakeholder influence, context-sensitive learning, and more nuanced evaluation of transformative impacts. Ultimately, realizing the transformative potential of ULLs requires moving beyond experimentation as an end in itself towards sustained processes of democratic engagement and structural change in urban mobility governance.
Although international trade has become increasingly seamless, developing countries continue to face significant delays in export shipment processing due to inadequate inland transport infrastructure and unreliable logistics systems. Border delays and uncertainty in travel time to ports severely constrain freight mobility and export performance. Despite recent infrastructure investments and institutional reforms, exporters in Southern Africa still encounter frequent road disruptions, long waits at border crossings, and persistent inefficiencies in logistics operations. Using micro-level data on export shipments from ten Southern African countries to the United States, we analyze how inland border delays and uncertainty are associated with routing patterns to ports. A mixed-logit discrete choice model applied to disaggregated shipment data shows that the likelihood of choosing a port-corridor decreases with the increase in travel-time variability and border delays, indicating restricted exporters' access to global markets. Ports connected by corridors with high travel-time uncertainty are systematically less likely to be selected, even when they take longer time from the shipment origin to the port. The results underscore the importance of reducing inland transport delays and uncertainty to enhance freight reliability, strengthen trade competitiveness, expand port hinterlands, and support export diversification in the region.
