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Location-based social media data can offer useful insights on the spatial and temporal dynamics of public attitudes. In this study, we aim to investigate the gendered attitudes toward transit services in China, utilizing the case of Shenzhen. We collected 44,257 Weibo microblogs, a major source of social media data in China, and applied a series of text mining and visualization techniques to examine the gender differences among our focused themes. The microblogs reveal a distinct gender gap in terms of quantity, as nearly 74% are posted by women. While women tend to be more concerned about the comfort of transit environment (e.g., temperature, crowdedness, and safety, especially at night), men tend to be more interested in transit systems' e-payment services and reporting traffic incidents. Overall, this study presents a methodological framework and empirical case study about how we can utilize certain social media mining techniques to investigate gendered, subjective travel experiences, providing researchers and practitioners with an innovative way to gather customer service feedback and build more inclusive service systems. • Women's voices are often neglected or suppressed in traditional transport planning. • We examine social media data from Weibo to understand gendered perceptions. • We use Latent Dirichlet Allocation model to extract latent "topics" from the posts. • Women differ from men regarding the perceived safety concerns and comfort levels. • Gendered perceptions toward transit services vary across space and time. [ABSTRACT FROM AUTHOR]

Developing more walkable environments plays an essential role in healthy-city planning. Planners often assess the typical walkability framework from a geographic perspective based on GIS data. This paper proposes a refined walkability framework that quantifies walkability in terms of four pedestrian needs: safety, convenience, continuity, and attractiveness. Using Shenzhen as our case study, we integrate mesoscale and microscale built-environment features from different data sources: street view images (SVIs), social media, points-of-interest data, government open data, and GIS data. Deep learning semantic segmentation approaches apply to extracting street elements from SVIs. Results show that walkability and its four aspects are spatially heterogeneous in the city. Urban areas and suburban central business districts offer greater walkability than other areas. The less walkable areas are mainly in the rest of the suburbs. This work suggests that more academic and planning efforts should focus on improving walkability in less walkable neighborhoods and promoting pedestrian-friendly cities. [ABSTRACT FROM AUTHOR]

The travel mobility gap is among the indicators that can be used to evaluate the level of social and transport inequity. To achieve a large and representative sample for this investigation of the different impacts of the built environment on travel mobility of various income and migrant groups, we have utilized big data from mobile phones for over 10 million users in Shenzhen, China. Travel mobility was measured by non-commute travel frequency and activity space. Our descriptive analysis demonstrates lower-income groups and migrant workers have lower levels of travel mobility than higher-income groups and non-migrant workers. The results produced by our linear regression models also reveal a significant travel mobility gap between different income and migration groups. That gap appears to be positively impacted by job density and bus stop distance and negatively impacted by residential density and metro station distance. Our modeling results also demonstrate that the travel mobility gap is larger in the outer suburbs than in the city center and inner suburbs. Our research findings reveal that the built environment influences the travel mobility gap, which implies that marginalized groups experience some degree of social inequality and exclusion. Based on these findings, we provide policy recommendations that aim to reduce the travel mobility gap between the marginalized and reference groups. • Travel mobility gap between the marginalized and reference groups is examined. • A mobile phone dataset covering over 10 million users in Shenzhen is analyzed. • Lower income groups and migrant workers have lower levels of travel mobility. • The gap is larger in the outer suburbs than in the city center or inner suburbs. • The built environment influences the travel mobility gap. [ABSTRACT FROM AUTHOR]

• Explore spatial patterns and determinants of on-demand food delivery (ODFD) usage. • Use auxiliary datasets and prior knowledge to downscale ODFD usage to 100-m grids. • ODFD usage largely concentrates in more urbanised areas, especially city centres. • Food accessibility and built environment are critical determinants of ODFD usage. • Several factors' impact magnitudes differ between more and less urbanised areas. On-demand food delivery (ODFD) services now produce many motorised trips in Chinese cities that raises environmental concerns. It is therefore crucial to understand where people use ODFD and what factors influence their usage. This paper explores the spatial patterns and determinants of ODFD usage in Shenzhen, China, focusing on the roles of food accessibility and the built environment. The results show that ODFD usage concentrates in more urbanised areas, especially city centres and sub-centres. Furthermore, more ODFD orders are generated in areas with lower food accessibility by walking and higher food accessibility by cycling, as well as in areas with higher population density, lower point of interest (POI) density, lower intersection density, higher street density, higher land use mix, higher percentage of land used for urban residences and commerce, and lower percentage of land used for rural residences, industries, and green space. These findings provide evidence-based implications for ODFD regulation. [ABSTRACT FROM AUTHOR]

• DBS is the second most popular feeder mode choice of metro. • We conceptualize the perceived built environment with "3A + 3S" framework. • Effects of certain perceived built environment features differ across scenarios. • Effects of perceived land use and POIs on the integrated use are less than expected. In this study, we aim to explore the role of metro users' perception toward the built environment in shaping the intermodal integration between dockless bikeshare (DBS) and the metro. We propose a "3A + 3S" framework to describe the perceived built environment related to feeder trip by DBS. By analyzing data from a questionnaire survey in Shenzhen, China, we reveal that (1) the perceptions toward the accessibility of metro stations and ease of searching/parking bikes notably increase the odds of DBS–metro integration; (2) the effects of certain perceived built environment features differ across scenarios. Perceived intersection is a barrier factor only for evening egress trips; the perceived bicycle–pedestrian crashes tend to discourage home-side integration; and the perceived bikeways promote integrated use except for the evening egress scenario; and (3) the effects of perceived land use and POIs on the DBS–metro integration are less than expected. [ABSTRACT FROM AUTHOR]

• We analyze data from a large dockless bike-sharing (DBS) operator in Shenzhen, China. • We examine the effects of the built environment on DBS–metro integrated use. • DBS–metro integration varies noticeably across space and time. • Areas with greater density of metro stations have fewer incidents of integrated use. Bike-sharing provides a convenient feeder mode for connecting to a metro and is believed to be an efficient way to solve the first- and last-mile problem. Despite the increasing attention paid on the use of bike-sharing, few studies have investigated how built environment factors affect the integrated use of dockless bike-sharing (DBS) and the metro. Using data from one of the largest DBS operators in China (Ofo), this paper employed a series of negative binomial regressions to examine the effect of the built environment on the integrated use of DBS and the metro, using Shenzhen as a case study. The findings show that mixed land use is positively related to integrated use. Residential areas have higher access-integrated rates during the morning peak hours, while industrial areas are associated with more integrated uses, connecting factories and metro stations. Furthermore, parks and public squares encourage both access- and egress-integrated use during peak times. Transportation facility features, including bus stops and dedicated bike lanes, are positively related to integrated use, while areas with dense metro distribution and main streets with many intersections are negatively related. Transfer distance also plays a crucial and negative role in integrated use. In addition, metro stations that are closer to the city center with a higher number of passengers are more likely to be integrated with bike-sharing. These findings can be used to collectively facilitate a connection between cycling and metro transit by creating a bicycle-friendly environment. [ABSTRACT FROM AUTHOR]