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Hong Kong's Mass Transit Railway (MTR) system has been widely acclaimed for its unique 'rail-plus-property' (R+P) model of operation. However, MTR projects, like other transit-oriented development (TOD) projects, have been under scrutiny as a catalyst for land-price appreciation and gentrification. In this study, we aim to examine the impact of new MTR lines on the spatial distribution of public and private housing estates across Hong Kong since the 1980s. Drawing on housing, transport and census data, we reveal that local improvement in accessibility due to the expansion of the MTR network has attracted private residential developments. This implies that low-income households might have been gradually squeezed out of such prime locations. Based on our findings, we propose recommendations on urban development under the TOD model, with a view to making Hong Kong and other transit cities more socially and spatially just. Keywords: accessibility, Hong Kong, private development, public housing, residential location, spatial justice, transit-oriented development, urban rail, Introduction It has been argued that investment in transport infrastructure has a multitude of neighbourhood impacts (Geurs et al., 2009; Won et al., 2015). Among these, the ability of transport [...]

We live in an increasingly urbanised world, with the world urban population expected to double by 2050. Cities across the world have been subject to dramatic socio-economic and environmental changes. [...]

Most Asian cities are 'incomplete democracies' (Barnes, 1998); the governments of the more developed Asian cities are dubbed as those of 'developmental' or even 'entrepreneurial' states (Weiss, 2000; Yu, 2003). [...]

•We examine non-linear effects of bike-sharing and ride-hailing on metro ridership.•Ride-hailing complements metro more at night and at stations far from job center.•Bike-sharing boosts metro use more at stations near job center during peak hours.•The complementary effects of shared mobility on metro fade away in distance.

ABSTRACTPromoting active aging has emerged as a key objective of urban planning and policymaking globally. Our study aims to provide new insights from a time-use perspective. In this paper, we use Hong Kong as a case study to investigate how people aged 60 and older allocate their time in various out-of-home activities. We analyse how personal and household characteristics affect the duration of out-of-home activities among older adults using two decennial time-use surveys. We focus on the influence of employment status and age because of policy relevance, particularly since the Hong Kong Government is considering extending the retirement age from 60 to 65. Comparison of time-use and activity participation between 2002 and 2013 suggests that employment status is positively associated with the duration of out-of-home activities and travel in both cross-sections; it also explains change over time. Findings also underscore the role of gender, age, education, type of housing, tenure of accommodation, household size, and income in determining older people’s activity–travel patterns. Our study shows that government policies to increase the share of employed people in the 60-years-and-older cohort and changes in the sociodemographic makeup of older people owing to various economic or societal forces could alter older people’s time-use and out-of-home activity patterns. Our study suggests that Hong Kong and other cities in the Asian region and beyond must aim at creating inclusive, age-friendly communities with adequate access to various activity opportunities in order to enhance quality of life in an aging society.

•We measured people’s perceived gentrification (PG) and sense of community (SOC)•We examined the relationship between rail development, PG and SOC.•Urban rail bears a positive association with perceived gentrification.•Perceived gentrification is positively linked to SOC.•Residents of neighbourhoods with prospective MTR service have lower SOC.

Improving perceptions of service quality is a promising planning strategy for increasing the attractiveness and retaining the ridership of public transport systems. The widespread use of social media presents an opportunity to investigate the performance of transport services from the customer’s perspective. This study proposes a framework for integrating quantitative and qualitative analyses to investigate the perceptions of transport services by mining data from social media. We utilise Sina Weibo data related to the Shenzhen metro system to illustrate a text mining process categorised by semantic, spatial and temporal information. On the semantic front, in addition to identifying service attributes and sentiment polarity consistent with previous literature, we find attributes specific to the Chinese context. We also identify clear temporal variations among different service attributes by visualising the number of corresponding microblogs across varying time scales such as hours, days and weekdays. The spatial variations reveal five main clusters around central business districts and transport hubs, which produce the highest density of reports about crowdedness, waiting times, reliability and frequency. However, microblogs that report on perceptions of safety and personnel behaviour present a different spatial pattern. This research offers insights into the ways in which we can use social media data to identify key service areas for immediate improvement and to monitor and manage metro systems more effectively over the long term.

•Social distancing leads to adaptive travel mobility and impacts travel experiences.•Engagement in online activity is driven by perceptions of ICT but not street crowdedness.•The modal shift from public to private transport is minimal in this transit-oriented city.•Reduced crowdedness has both direct and indirect effects on travel satisfaction.•The increased usage of rail, buses, minibuses and taxis is associated with travel satisfaction.

Travel behaviour has been studied for decades to guide transportation development and management, with the support of traditional data collected by travel surveys. Recently, with the development of information and communication technologies (ICT), we have entered an era of big data, and many sources of novel data, including mobile phone data, have emerged and been applied to travel behaviour research. Compared with traditional travel data, mobile phone data have many unique features and advantages, which attract scholars in various fields to apply them to travel behaviour research, and a certain amount of progress has been made to date. However, this is only the beginning, and mobile phone data still have great potential that needs to be exploited to further advance human mobility studies. This paper provides a review of existing travel behaviour studies that have applied mobile phone data, and presents the progress that has been achieved to date, and then discusses the potential of mobile phone data in advancing travel behaviour research and raises some challenges that need to be dealt with in this process.

To better understand trip-chaining patterns and mode choice of various urban forms, this study examines the effects of land use on travel mode choice and analyzes the concept of neighborhood design in the substitution of short car trips by other transportation modes.