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Disruptions to transport systems often significantly change travel behaviour. This is especially true when the disruption lasts over an extended period and is accompanied by the massive-scale dysfunction of transit operations. In addition, although attitude is critical for predicting travel behaviour, there is little documentation of changes in attitudes towards transit modes and the factors influencing such changes during a transit system disruption. Furthermore, few studies have investigated how social movements can exert a pronounced disrupting effect on a transit system. To fill these research gaps and provide policy recommendations for a more responsive contingency plan in response to future transit system disruptions, our study aims to investigate this issue based on the case of Hong Kong during the 2019 social movement. We collected a questionnaire survey representing the period from late June to early July 2020, a few months after the end of the protests. Using structural equation models, we have examined how people's attitudes towards different transit modes changed during the social movement. Our findings highlight that people's perception of the city's urban rail system – the Mass Transit Railway, which the government has a significant stake in and control over – worsened significantly during the transit disruption, but the effects were less pronounced for bus and mini-bus. In addition, attitudes towards the social movement were found to vary significantly across social groups, a finding linked to people's attitudes towards different transit modes. Importantly, our study reveals that people's views of social movements can significantly determine how they evaluate impacted and alternative transport modes during transit disruptions. These newly revealed attitudinal dimensions should be fully considered in predicting behavioural change and adjusting transit services under similar conditions. • Examined the attitudinal dimensions during transit disruption caused by social movement. • During the disruption, people' attitudes towards transit modes changed markedly. • Attitudes towards the social movement influenced people's attitudes of transit modes. • Political views should be considered when arranging transit service during social movement. [ABSTRACT FROM AUTHOR]

In a rapidly evolving and highly competitive transportation market, increasing customer satisfaction and ridership retention are essential for transit agencies. Understanding how different market segments perceive transit services can help service providers to identify potential priority areas and develop specialised strategies to address their varying travel concerns. However, traditional studies have predominantly investigated the variations across socioeconomic cohorts or travel characteristics but ignored the complex effect of spatial, temporal, and user heterogeneity. Recently social media data has attracted growing interest from academia as an alternative way to compensate public attitude surveys with a high volume of semantic, spatial, and temporal information. This study collected 177,807 microblogs from Sina Weibo to understand how customer satisfaction varies among different market segments characterised by social, temporal, and spatial heterogeneity. Methodologically, this study applies sentiment analysis as a real-time measurement of customers' satisfaction towards transit services, covering safety, crowdedness, reliability, personnel behaviour, and comfort. A beta regression model is then applied to identify the most important explanatory factors and the extent to which explanatory factors affect customers' satisfaction, respectively. The result indicates that age, gender, travel mode, time, and space significantly contribute to customers' satisfaction with the transit system. Their varying impacts on different service attributes are also identified in this study. This study also reveals the highly polarised nature of online sentiment, explaining gendered attitudes. Our research framework could be used as a benchmark for other service industries to conduct similar market segment analysis and integrate it into the policy decision process. • We examine social media data from Weibo to understand customer satisfaction. • We use sentiment analysis to estimate customer satisfaction. • We use beta regression model to identify key influential factors of satisfaction. • We find that age, gender, travel mode, time and geography are key factors. • The identified factors have varying impacts on different service categories. [ABSTRACT FROM AUTHOR]

In this paper, we aim to examine people's EV purchase intention in Hong Kong, an Asian compact city, and how the influential factors are different from the Western context, for which a low-density Nordic context, Denmark, was chosen. To achieve this, we conducted a survey in Hong Kong to understand the effects of several key factors, including subjective norms, personal norms, and perceptions and knowledge about EVs. Structural equation modelling was employed and multi-group analysis was conducted. Our findings show that EV purchase intentions in Hong Kong are highly value-driven with the assimilation to social expectations directly and strongly encouraging individuals' EV acceptance, which is different from the European case where the adoption desire is built upon the assessment of usage difficulty. In addition, range anxiety poses a direct deterrence to EV adoption even in the compact city. Availability of charging opportunities, be it the public ones or home-based ones, plays a critical role in an individual's decision of EV adoption in the high-density city. Our study reveals a strong disparity in the pathways towards EV adoption between the Asian and the Nordic contexts, thereby illustrating the necessity to differentiate e-mobility promotion policies in compact cities from low-density cities. • We analyse the influential factors of EV purchase intention in Hong Kong & Denmark. • Attitude, moral obligation and perceived ease of use affect EV adoption. • EV purchase intentions are highly value-driven in Hong Kong. • Range anxiety poses a deterrence to EV adoption even in the compact city (HK). • Availability of charging facilities is key to EV adoption. [ABSTRACT FROM AUTHOR]

• We propose an innovative methodology for optimal deployment of public EV chargers. • A generalised ordered probit model is used to estimate EV purchase intention. • We derive parameters of the LA model based on survey, public data and interview. • Existing charging network should be substantially expanded, especially in suburbs. • Adding chargers at existing stations is more economical than building new stations. The optimal deployment of public charging infrastructure is critical to the popularisation of electric vehicles (EVs) in high-density cities. Existing studies on public EV charging facilities have rarely integrated government policy and spatial constraints into their optimisation algorithms. To address this research gap, we proposed a contextualised EV charger optimisation model that incorporates carefully derived supply-and-demand constraints and tested it in the case of Hong Kong. From the supply side, we studied the latest planning guidelines and conducted a spatial analysis of potential charging sites. From the demand side, we conducted a questionnaire survey with local residents, estimated their EV purchase intention using a generalised ordered probit model, and then projected the usage demand for public chargers. These supply-and-demand constraints were subsequently incorporated into a location-allocation model to minimise both charging demand shortfall and travel time to charging facilities. We also conducted sensitivity analyses with varying budget, charging demand and facility service radius. Based on our results, we made several key recommendations regarding the spatial planning of public EV charging facilities in our high-density context: (1) the existing charging network should be substantially expanded to meet the projected demand; (2) the charging network should be expanded beyond the central business district and the urban core into other urban neighbourhoods and suburbs; and (3) installing more chargers at existing charging stations is more economical than building new stations. Our research provides an important reference for the spatial planning and deployment strategies for public EV charging infrastructure in high-density cities. [ABSTRACT FROM AUTHOR]

• COVID had larger impact on the mobility of non-commute trip than commute trip. • COVID had larger impact in core area of the Greater Bay Area than peripheral area. • COVID had larger impact on mobility of disadvantaged groups than advantaged groups. • Law enforcement had a significant impact on travel mobility in the core cities. • Our findings imply social inequity in travel mobility and transport resources. The COVID-19 outbreak has significantly impacted people's mobility in terms of travel, which is directly related to regional economic vitality and individuals' well-being. This study conducted research on the COVID-19 epidemic's impact on travel mobility in China's Greater Bay Area, utilizing mobile phone big data. The overall influence of COVID-19 was measured by investigating the impact between different income and migration groups in three core cities: Shenzhen, Guangzhou, and Foshan. Individuals' weekly travel frequency and activity space area between December 2019 and May 2020 were calculated, and the average values between the different cities and various social groups were compared. The results showed that travel mobility declined during the epidemic's peak, followed by a recovery based on the overall trend. The start and end of strict law enforcement had a significant impact on the initial decline and subsequent recovery of travel mobility in the core cities. COVID-19 had a larger impact on core cities than peripheral areas, and on non-commute travel frequency, compared to commute travel frequency. Compared to advantaged groups, socially disadvantaged groups experienced a steeper decline in travel mobility during the epidemic's peak, but a more significant recovery afterwards. These findings indicate that discretionary activities have not yet recovered and remain below the pre-epidemic level, and that disadvantaged social groups had limited access to superior precautionary measures for avoiding infection. Based on the findings, we provide several policy suggestions regarding the recovery of travel mobility. [ABSTRACT FROM AUTHOR]

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]

• Built environment effects on bike-sharing as a feeder mode of metro is examined. • Low agreement exists between objective and perceived measures of built environment. • Perceived built environment directly affects the usage of dockless bike-sharing. • Perception mediates the effects of metro accessibility, bus and bike availability. • Effects of built environment are moderated by gender, age, income, and location. The rapid growth of dockless bike-sharing (DBS) systems has attracted increased academic attention in the solutions to first- and last-mile problems. However, only a few studies have examined how the synergy between DBS and metro transit is affected by objective and perceived measures of built environment collectively. This study intends to fill this research gap by focusing on the effects of objective and perceived measures of built environment on DBS–metro integrated use for commuting trips. Results reveal that low agreement between the two measures of built environment and that the perceived measure is more likely to be directly associated with DBS–metro integration than the objective measure. Different built environment attributes may affect DBS–metro integration by unique paths. Moreover, individual characteristics (i.e., gender, age, and income) and location factor moderate the association between the built environment and DBS–metro integration. Particularly, built environment attributes related to transportation service are easier to be moderated than land use and cycling condition attributes. We conclude that the understanding of and interventions for the built environment as objectively measured are necessary but not sufficient for DBS–metro integration. Promoting the perception of the built environment among different population groups is also important for interventions. [ABSTRACT FROM AUTHOR]

• Use open data to measure walkability from the perspective of pedestrian needs. • Collect ground-truth GPS data to validate walking trips extracted from mobile data. • Identify and interpret the mismatch areas between walkability and walking trips. • Uncover the spatial effects of walkability and its four dimensions on walking trips. • Provide prioritized and contextualized built-environment intervention strategies. Stimulating more citizens to walk plays an essential role in building a healthy city. This paper explores the mismatch between walkability and walking behavior, using mobile phone data, street view images, and various sources of open data. Using Shenzhen as our case study, we identified walking trips of 6 months in 2021 from cellular mobile data, taking the rule-based heuristics approach. We collected ground truth GPS data to validate the walking trip extraction method. Open data and deep learning enabled quantifying walkability from the perspective of four pedestrian needs: safety, convenience, continuity, and attractiveness. We employed geospatial techniques to identify the mismatch areas between walkability and walking behavior in the city. We also explored the spatially varying effects of walkability on walking behavior. Our results showed that the mismatch areas with high-level walking trips but low-level walkability mainly occurred in the fringe areas of the central business district (CBD) and subcenters that require prioritizing more interventions. Moreover, walkability showed strong effects on walking trips in the inner suburbs. For the four aspects of our walkability framework, safety and convenience had greater positive effects on walking trips in suburbs than in urban areas. Continuity promotes walking trips mainly in the city's western sector. The positive effect of attractiveness on walking trips clustered in the central and western parts of the city. Based on the findings, we provide prioritized and contextualized built-environment intervention strategies and policy recommendations for urban designers and transportation planners. [ABSTRACT FROM AUTHOR]

There is a rise in ageing populations worldwide, especially in cities, and policymakers are working to address this situation. In this light, it is necessary to understand the challenges faced by both the ageing population and the policymakers. Increased mobility enables individuals to perform fundamental tasks more easily and conveniently, such as going to work, accessing health services, and purchasing essential goods, besides other important activities related to recreation and socialisation. This paper examines the impact of satisfaction with transport systems on the social inclusion of older people and their wellbeing. We conducted a questionnaire survey in 18 elderly centres, one from each of the 18 districts in Hong Kong, in 2018, and used a structural equation model (SEM) with latent variables to estimate the effect of satisfaction with the most commonly used transport systems on wellbeing. Our results show that an older person's sense of community and satisfaction with their neighbourhood is strongly related to their satisfaction with transport systems. When the local transport systems are well-functioning, older people feel more socially included. Satisfaction with transport systems also has a strong effect on older people's physical and psychological wellbeing, after controlling for social inclusion. Our findings suggest that transport systems need to be adapted to become more inclusive of the older population to improve their mobility and wellbeing. • Over 270 Chinese older adults were interviewed across 18 districts in Hong Kong. • Satisfaction with transport systems is important for older people's wellbeing. • Well-functioning transport systems make older people feel more socially included. • Higher satisfaction with transport systems leads to higher physical health. • Higher satisfaction with transport systems leads to improved psychological wellness. [ABSTRACT FROM AUTHOR]

• We estimate the price premium of rail accessibility on property prices in Hong Kong. • Access to the rail network raises the property prices significantly. • A significant spatial heterogeneity is revealed across different submarkets. • Repeat sales model shows a larger effect in several new towns along the new lines. • We offer policy implications in light of the regional impact of rail infrastructure. With new rail lines, residents can enjoy higher accessibility and more activity opportunities. However, better access to public transport can potentially increase land prices in catchment areas. In this research, we aim to investigate whether this capitalisation effect goes beyond the conventional catchment area and how such an effect varies across different regions. In a departure from previous studies, we employed a gravity-based accessibility measure to capture the regional impact of rail lines using a cross-sectional analysis of 2001 and 2011 residential apartment data in Hong Kong and a difference-in-difference approach to estimate repeated sales transacted in both years. We used a three-level hierarchical estimation method that allowed the price effect to vary by submarket. The results indicated that the network accessibility of rail lines had a statistically significant capitalisation effect on property prices that varied across different submarkets. Although the three major new rail lines had a greater impact on the built environment in suburban areas, the elasticities in property price with regard to accessibility were still larger in urban areas in both 2001 and 2011. We also establish that the improvements in rail accessibility had a substantially greater effect on the changes in property price between 2001 and 2011 in several new town submarkets along the new lines. From a regional perspective, we conclude that the price effect of new transport infrastructure goes beyond the local catchment areas and call for urban policies that address housing affordability issues across different submarkets in the region and a re-examination of land value capture policies. [ABSTRACT FROM AUTHOR]

• Greenspaces promoted active mobility and mental well-being in the Philippines. • Greenspaces relieved stress among the elderly and unemployed during COVID-19. • Living near nature or community parks reduced COVID-19 stress. • People living near linear parks walked or biked more during COVID-19. • Perceived neighborhood safety can help individuals manage stress induced by the pandemic. This study investigated the impact of greenspace proximity on stress levels and active travel behavior in post-lockdown Pasig City, Philippines. 307 residents took part in an online survey, sharing insights on mobility changes, park usage, and their perception of park and neighborhood. Pasig City's greenspaces were classified as Nature parks, Linear parks, Town squares, and Community parks, based on their characteristics and usage. Proximity to these parks was measured via Network analysis in ArcGIS, and data underwent ordered regression analysis with interaction effects for different population groups. Results indicated that proximity to Nature and Community parks correlated with manageable stress levels, while residing near Linear parks was marginally associated with increased walking and cycling. Elderly and unemployed residents near parks experienced greater stress relief and physical activity. The study emphasized residents' recognition of parks' role in promoting relaxation and serenity, highlighting a shift in active travel behavior. Additionally, it underscored the potential health benefits of urban greenspaces, emphasizing the need to consider citizens' subjective experiences when designing and maintaining them. Overall, the study suggests that greenspaces can play a crucial role in fostering well-being and active lifestyles, particularly during stressful and uncertain times. [ABSTRACT FROM AUTHOR]

Highlights • Two recent surveys about perception of transport systems were conducted in Guangzhou and Brisbane. • We examine the impact of car ownership on attitudes towards public transport. • We measure car ownership and attitudes through latent variables and construct an SEM model. • Car ownership is found to significantly affect people's attitudes towards public transport in Guangzhou. • Environmental concerns is found to be a significant factor in the case of Brisbane. Abstract Car ownership has often been linked to a strong commitment to car use and a tendency to undervalue alternative transport modes, thereby potentially biasing people away from using more environmentally friendly transport modes such as public transport. Although a considerable body of research has shed light on the attitudinal dimensions of car ownership and usage, few have investigated the potential influence of car ownership on attitudes towards alternative transport modes from an international comparative perspective. Across cities with distinct mobility cultures and economic backgrounds, car ownership may have differentiated influences on how people view various transport modes, yet little research exists in this area. This study aims to bridge this knowledge gap by investigating the relationship between car ownership and attitudes towards public transport in two vastly different metropolises, Guangzhou, China and Brisbane, Australia, while taking account of environmental concerns, past behaviour and socio-demographic characteristics. Drawing on two survey data sets, we derived measurements that directly compare the perceived difference between bus transit and cars, and constructed latent attitudinal variables based on loose-matching and strict-matching criteria to enable a more robust test of hypotheses. Using structural equation modelling (SEM), our analysis shows that car ownership appeared to contribute significantly to the perceived disparity between public transport services and car use in Guangzhou, but less so in Brisbane. Furthermore, environmental concerns were found to have a stronger influence on transport-mode attitudes in Brisbane. Recommendations are developed to inform local policies to promote more sustainable urban transportation. [ABSTRACT FROM AUTHOR]

• Longitudinal evidence is provided of life events alter travel behavior. • The number of household cars was inversely related to men's train use. • Changing jobs increase household car ownership for both couples. • Childbirth decreases both male and female partners' cycling frequency. Despite increasing interest in how travel behavior changes over time, few studies have investigated how life events alter travel behavior, especially from a household perspective. This study examined the extent to which life events influenced changes in travel mode frequencies at the household level. We applied structural equation modeling based on the Netherlands Mobility Panel data for 2014 and 2016. For both partners, acquiring a household car significantly increased car use, and disposing of household cars decreased car use frequency. The number of household cars was inversely related to men's train use. Childbirth in the household decreased both partners' cycling frequency. Men's job changes increased train use. These findings emphasize that life events can influence changes in travel behavior within household partners. [ABSTRACT FROM AUTHOR]

Previous research on the self-containment of new towns has focused on access to employment and commute travel; little research has been documented regarding access to non-work facilities and its relation to non-work active travel, overlooking an important aspect to assessing the self-containment of new towns. Drawing on multiple sources of data in Hong Kong, we measure walking accessibility to three main types of non-work facilities (markets, restaurants and parks) as major destinations for non-work travel. Through a series of statistical analysis, we investigate in detail the effects of accessibility on the probability and duration of home-based walking trips. Our findings indicate that: (1) new towns were more disadvantaged and less equitable in terms of the accessibility to non-work facilities than urban areas; and (2) accessibility increased both the likelihood and duration of new town residents' walking trips particularly for grocery-shopping and dining-out purposes. The findings indicate that enhancing accessibility to non-work facilities in new towns can be beneficial in terms of both achieving self-containment and promoting more sustainable travel behaviour. Recommendations are proposed accordingly to help create more pedestrian-friendly environment, and balanced provision of non-work facilities in and around new towns and other suburban developments. • Accessibility to non-work facilities is vital to the self-containment of new towns • Walking accessibility to three main types of non-work facilities is measured. • The relationship between accessibility and walking trips is investigated. • Accessibility is lower and less equitable in new towns than urban areas. • Higher accessibility encourages longer walking trips for new-town residents. [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]

The objective of this research is to understand intentions to buy a car and how car-ownership, together with other personal, situational and attitudinal factors, influences travel mode choice in a Chinese megacity. A survey was carried out in Guangzhou, China to examine respondents’ car ownership and travel mode perceptions and choices, as well as personal and situational characteristics. A quota sampling procedure was used to select members of three different groups: car owners; no car but planning to buy one in the next 5 years – car intenders; and no car and not planning to buy one. We find that car ownership is the most important among included predictors of travel mode choice, which also depend on other personal and situational factors, but only indirectly by attitudinal factors. However, attitudinal factors have a strong impact on the intention to buy a car, while controlling for other personal and situational factors. Our results suggest that several policies can be further improved in China for greater effectiveness in reducing the car use of car owners and car intenders. [ABSTRACT FROM AUTHOR]

Resource-based cities play a crucial role in China's economic development. However, they are faced with the challenge of urban shrinkage due to the slowdown of economic growth in China, single industrial structure and the ‘boom and bust’ industrial cycle. To reverse the expected decline of these cities in the future, the Chinese Government has implemented active policies at national, provincial and municipal levels. This paper reviews the current planning policies and practices in resource-based cities in China from the macro perspective, and analyses how the Government engages with the pressing economic problems faced by resource-based cities, in particular, focussing on economic restructuring. To further analyse the policies from Central Government and the diversification of practices in local contexts, this paper presents two case studies, a petroleum mining city (Daqing City) and a coal mining city (Pingxiang City). Through discussion and an evaluation of general and place-based policies and practices for resource-based cities, this paper aims to enhance the understanding of shrinking cities in China and shed light on the policy-making of economic development for other resource-based cities in developing countries. [ABSTRACT FROM AUTHOR]

Resource-based economies often face the challenge of resource depletion and population shrinkage. After reaching a production peak, cities confront slower economic development and the inability to attract skilled workers, often leading many resource-based cities to experience urban shrinkage. This prompts questions regarding whether residents of resource-based cities are concerned about liveability indicators beyond job opportunities and whether residents would stay if a city were more liveable. This research has employed a mixed-methods approach to examine the relationship between urban liveability and migration intention. We collected data via a questionnaire survey and in-depth interviews in seven resource-based cities in the Northeast and Northwest regions of China characterised by slow or negative population growth. Our mixed-methods approach identifies five main dimensions of factors affecting an individual's migration intention: job opportunities, employability and prospects with the mining industry; transport; public facilities; age, life cycle stage and family consideration; income and financial considerations. Our findings confirm that certain aspects of liveability significantly affect migration intention. Our subsequent analysis suggests that there is a skills gap between newly created employment opportunities and the labour force in resource-based cities. These issues call for government action to improve the liveability of resource-based cities and retain skilled workers. • A mixed-methods approach to study migration intention in resource-based cities • We identify and discuss five main categories of influential factors. • Certain aspects of liveability significantly affect migration intention. • Skill gaps may exist between newly created jobs and existing skills of labour force. • Improved intra- and inter-city transport infrastructure can retain population. [ABSTRACT FROM AUTHOR]

In this paper, we present a case study on planning the locations of public electric vehicle (EV) charging stations in Beijing, China. Our objectives are to incorporate the local constraints of supply and demand on public EV charging stations into facility location models and to compare the optimal locations from three different location models. On the supply side, we analyse the institutional and spatial constraints in public charging infrastructure construction to select the potential sites. On the demand side, interviews with stakeholders are conducted and the ranking-type Delphi method is used when estimating the EV demand with aggregate data from municipal statistical yearbooks and the national census. With the estimated EV demand, we compare three classic facility location models – the set covering model, the maximal covering location model, and the p -median model – and we aim to provide policy-makers with a comprehensive analysis to better understand the effectiveness of these traditional models for locating EV charging facilities. Our results show that the p -median solutions are more effective than the other two models in the sense that the charging stations are closer to the communities with higher EV demand, and, therefore, the majority of EV users have more convenient access to the charging facilities. From the experiments of comparing only the p -median and the maximal covering location models, our results suggest that (1) the p -median model outperforms the maximal covering location model in terms of satisfying the other’s objective, and (2) when the number of charging stations to be built is large, or when minor change is required, the solutions to both models are more stable as p increases. [ABSTRACT FROM AUTHOR]

Abstract: Children's independent mobility in many urban areas in the United States has been in decline. This implies that children's out-of-home travel involves the company of adults more often than before. This need requires parents to seek ways to balance work-family life. This study examines the factors that influence a parent-child joint trip to school in dual-earner households, with special consideration given to parental work arrangements and location, which act as intra-household temporal and spatial constraints. The study is carried out in the five-county Los Angeles region, drawing from household travel diaries from the 2001 Southern California Association of Governments (SCAG) Post Census Regional Household Travel Survey. The results show that parental employment, especially the mother's, is a very important factor influencing the probability of a joint trip to school. In terms of temporal constraints, longer working hours will reduce the likelihood that a child will be escorted by its parents. However, the option of flexible work hours offsets the negative effect of long working hours by offering a higher degree of scheduling flexibility. In terms of spatial constraints, the closer the mother's workplace is to the school, the more likely it is that the child will be escorted by the parents. This research provides important evidence that a child's joint trip is heavily influenced by the parents' work schedule and location. The findings shed light on how the provision of certain employment policies and programs may affect joint trips to school. [Copyright &y& Elsevier]

Abstract: Over the past twenty-five years, more workers in the United States have been given the option of flexible work schedules, which are designed to redistribute commuter traffic over the course of a day by allowing employees to vary their arrival and/or departure times. This paper examines whether and to what degree access to flexible work schedules affects the departure times of commuters in the two largest and most congested areas of California: the Los Angeles and San Francisco regions. Trip data were obtained from the 2009 US National Household Travel Survey (NHTS). The results of this study show that people who have access to flexitime preferred later departure times rather than earlier times. Workers with flexible schedules were 3.30% less likely to depart before peak hours, 4.11% less likely during peak hours, and 7.41% more likely afterwards. Based on these findings, government agencies and private firms in regions with severe traffic congestion problems may consider adopting alternative work schedules. [Copyright &y& Elsevier]

Abstract: For accurate prediction, a shopping destination choice model must rely on a realistic representation of available opportunities. Thus, spatio-temporal constraints are indispensable in specifying a realistic choice set. Failure to take into account such constraints results in misspecification of shopping alternatives, erroneous inferences, and misunderstanding of individual travel behavior. However, due to lack of data, heavy computational burden, and algorithm complexity, spatio-temporal constraints have often been ignored in shopping destination choice modeling. In our study, we use the potential path area, which is the projection of a space–time prism onto a plane, to determine an individual’s destination choice set given their spatio-temporal constraints. In this way, the destination choice set is a more realistic representation of the shopping alternatives available to the individual. We select 616 shopping trips from a travel survey conducted in five counties of the Louisville KY-IN MSA in 2000, and aggregate shopping opportunities to traffic analysis zones (TAZs) for analysis. Multinomial logit models are estimated to understand the determinants of shopping destination choice. The results are compared to those of a conventional, unconstrained destination choice model. [Copyright &y& Elsevier]

• 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]

Ever since their first establishment in Britain in 1946, new towns have become commonplace globally as a means to accommodate spillover populations from urban areas. Many of the planned new towns have a goal of creating self-contained communities with sufficient local jobs. However, despite over seventy years of new town development, few studies have examined whether and to what extent an intra-urban agglomeration economy has formed within these towns. This paper adds to the literature on new towns' spatial planning and performance by investigating the local agglomeration economy in new towns through employment sub-centres, with Hong Kong as the study area. We identify employment centres from 2000 to 2015 to map changes in the spatio-economic structure. Our results reveal that only a few of these primary employment centres exhibit strong location agglomeration: the proportion of jobs in the long-established urban core remained stable, while the agglomeration economies in new towns have not gained much momentum in attracting a larger proportion of the city's total employment. The new towns' sub-centres also indicate a similar industrial composition, and seemingly fail to foster local specialisation-based economies. • Local agglomeration economies were identified in Hong Kong from 2000 to 2015. • The main employment centres in Hong Kong exhibit strong location agglomeration. • A few relatively small employment sub-centres are located in new town areas. • New towns' employment sub-centres share homogeneous characteristics. • Most new towns have not formed a substantial agglomeration economy. [ABSTRACT FROM AUTHOR]

Daily mobility of disadvantaged social groups, particularly low-income people, has gained increasing interest since the daily life of these people may encounter significant constraints that lead to certain social issues such as social exclusion and segregation. The concept and measure of activity space have been applied to measure the spatial barriers and inequalities faced by the low-income group in their daily life. However, research on how the daily mobility of different social strata has evolved over a longer period in parallel with urban development has been very limited. This study aims to address these gaps by investigating the activity space of the low-income group in comparison with other income groups in Hong Kong from 2002 to 2011, a period when several subway lines were opened. Four indicators were employed to capture the spatial extent and diversity of activity space. Propensity score matching was used to compare the activity space and mobility of the low-income group with those of the below-average and higher-income groups, while controlling for several confounding factors. The findings indicate that the activity space of the low-income people has not improved over the decade, despite some marked expansion of public transport infrastructure and urban development. In addition, a persistent gap in activity space between the low-income group and other income groups has remained stark in both urban areas and the new towns. Policy recommendations are put forward with a view to improving the daily mobility of the low-income group, with avenues for future research identified as well. • Activity space of the low-income group in Hong Kong of 2002 and 2011 is examined. • The spatial extent and diversity of activity space are measured in four indicators. • The activity space of the low-income group has not improved during the study period. • A persistent gap exists between the low-income group and other income groups. • The discrepancy along the income line exists in both urban areas and new towns. [ABSTRACT FROM AUTHOR]

• One-month dockless bikeshare trip data and metro smart card data from the same period in Beijing is used. • The random forest model and accumulated local effects plots were used to examine the nonlinear effects of factors associated with the links between dockless bikeshare and metro trips. • Findings suggest metro ridership and DBS density around service areas are the most crucial factors with certain thresholds and notable joint effects. • The results draw attention to the importance of how bikes are allocated spatially. In this study, we examine the factors associated with the integrated use of dockless bikesharing (DBS) and metros. Special attention is paid to the nonlinear effects of these factors, using machine learning; in this case, a random forest model and accumulated local effects (ALE) plots. We measure the integrated use of DBS and metros based on DBS data and metro smart card data in Beijing. Explanatory variables include metro station characteristics, road infrastructure, public transportation services, land use, and urban density, as well as meteorological variables. We find that metro ridership and DBS density around service areas are the most crucial factors for promoting cycling access/ egress near metro stations. After reaching the thresholds of 6,000 trips for metro ridership and 200 bikes/ per km2 for DBS density, notable joint effects are evident between the two variables, which are negative in egress trips but positive in access trips. Bicycle parking and bus transfer distance and their connectivity to metro stations are important for integrated use. We find that buses will be less competitive when exceeding 25 lines per station. Population density has a nonlinear effect, with a positive association below 9,000 persons/ km2 and a decreasing effect above this level. The land-use mix index was also found to be negatively associated with integrated use, and bicycle lanes are not associated with integrated use. Our results demonstrate that public transit service planning should consider the constraints of resources and public space, and we provide recommendations for governments and stakeholders to reallocate DBS and other public transit services around metro stations. [ABSTRACT FROM AUTHOR]