Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment ...factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R2 for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future.
Despite the recent growth and popularity of ride-hailing services throughout the world, there's still a lack of research on its determinants. This paper aims to examine the associations between ...ride-hailing and their spatial distribution in relation to key socioeconomic and built environment characteristics both at the trip origin and destination. To do so the study uses official data provided by Transportation Network Companies operating in the city of Chicago, with 32 million trips logged between November 1st, 2018 to June 28th, 2019. Among the built environment attributes we focus on the relationship between walkability levels and demand for ride-hailing. Study findings indicate an association between ride-hailing and income levels, car-availability and race-ethnicity. Results also suggest a positive association between walkability at either trip origin or trip destination and ride-hailing demand, together with a negative one between access to transit and ride-hail use. Findings suggest some worrisome conclusions, with ride-hailing being seldom used among the more deprived areas. Ride-hailing is predominantly being used to travel between highly accessible areas which should be accessed using more sustainable transport modes. Positive takeaways are the lack of race disparities in ride-hailing demand and the capacity of ride-hailing to interact and complement public transit provision.
•The spatial distribution of 32 million ride-hailing trips in Chicago is examined.•The association between trips and socioeconomic and environmental attributes is tested.•61% of ride-hailing trips are between highly walkable areas.•Low-income areas were associated with fewer ride-hailing trips both at origin/destination.•No race/ethnicity disparities were found.
Accessibility is generally recognised as an important element of architectural design practice. However, studies suggest that the adoption of Inclusive Design by the architectural design community is ...still quite limited. Inclusive Design embraces the principles of accessibility and its extended definition considers key sociological and behavioural aspects such as physical, sensory and cognitive needs.
This paper presents the results of an ethnographic study, conducted amongst 26 professionals from the building industry, on the adoption of Inclusive Design.
This research aims to explore the challenges and limitations that professionals experience in their daily working practice and to identify strategies to expand the use of Inclusive Design and its extended definition.
The findings emphasise how education and awareness are essential factors to encourage an inclusive mindset amongst architectural design professionals and other stakeholders. In particular, holistically mapping the user journey during the design phase and collecting and evaluating post-occupancy user feedback are complementary strategies that can foster a design process based on inclusion, diversity, equity and accessibility principles for the built environment.
•Inclusive Design is still not widely adopted in architectural design practice.•Building inclusively should embrace inclusion, diversity, equity and accessibility.•Education is key to help foster inclusion in architectural design practice.•User journey mapping can improve the Inclusive Design process.•Post-occupancy user feedback can help architects to better design for inclusion.
The Construction Industry is responsible for over 30% of the extraction of natural resources, as well as 25% of solid waste generated in the world. This happens because the construction sector mostly ...adopts a linear economic model of “take, make, dispose”, using materials to the construction of buildings and disposing them at the end of life, since they are assembled for one time use and don’t retain potential for reuse. Over the last decades, a paradigm shift has been occurring in the industry at large, with the adoption of a Circular Economy model, that aims at keeping the materials in a closed loop to retain their maximum value, therefore with a greater potential of reducing the waste generation and resources extraction for the Construction Industry. This article aims at finding the recent developments of how Circular Economy can be used inside the construction industry. To achieve this goal, a systematic literature review was conducted, including 45 articles that were divided into six areas of research: development of Circular Economy, reuse of materials, material stocks, Circular Economy in the built environment, LCA analysis and material passport. An analysis of the content of these articles was made and the knowledge gaps in this area were identified, as well as table with known Circular Economy practices for the Construction Industry was created divided by life cycle stages. Finally, a discussion of each area of research and their findings is made.
•Six different areas of research were found.•There is a lack of knowledge of standard practices of Circular Economy concepts inside the construction industry.•A list of known circular economy practices for the built environment was created.•Bigger focus should be given to economy models for Construction companies.•There is a potential to create a Community of Practice in the subject.
The socio-spatial segregation experienced by migrants has attracted considerable attention and an increasing number of studies have examined segregation in migrants’ daily activity space recently. ...However, research on activity diversity and spatial contact between local residents and migrants has been limited. This paper fills this knowledge gap by investigating the differences in the extensity, intensity, diversity and exclusivity of activity spaces among local residents, urban migrants and rural migrants based on their routine activities in suburban Shanghai, China. It finds that rural migrants have low daily mobility and are physically constrained, and there is spatial sorting of activity locations among different social groups. Neighborhood environment significantly influences activity space-based segregation: People who live in neighborhoods with higher POI density and better access to commercial establishments and public spaces have small activity spaces, while those who live in neighborhoods with mixed land use, better access to public transit, and higher street connectivity have more diverse activity participation. Neighborhoods with better public spaces and a lower land use mix promote shared activity spaces. This study uncovers the segregation suffered by migrants by examining the usage of urban space and spatial interactions among social groups, enhancing our understanding of activity space-based segregation in developing countries.
•We analyze the activity space-based segregation emphasizing diverse locations visited in residents' daily lives.•There is significant activity space-based segregation among hukou groups.•Rural migrants have limited daily mobility and are physically constrained in activity space.•Local residents tend not to share activity spaces with migrants.•Residential neighborhood attributes significantly influence activity space-based segregation.
To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults.
Weight trajectories were estimated using electronic health records for 115,260 ...insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values.
Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures.
The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.
•This study analyzed over 886,000 dockless e-scooter trips in two US cities.•It found that downtown and university campus areas were both high e-scooter usage clusters although the temporal patterns ...varied between the two cities.•It also found that besides common positive indicators for sustainable transportation, commercial land use and open space such as parks and green space only positively correlated with e-scooter usage in one of the cities.•This study raised the importance of the local uniqueness as well as intercity commonalities among different societies in terms of new micro-mobility modes like dockless e-scooters.
In recent years, the popularization of dockless shared electric scooters (e-scooters) across many American cities has provided a great opportunity to reduce short-distance automobile trips. However, there is not enough research that examines e-scooter usage patterns and their association with the urban environment. Moreover, the question of whether this association would vary across different cities also remains unanswered. To bridge these gaps, this study investigated e-scooter ridership in Austin and Minneapolis using GIS hotspot spatial analysis and negative binomial regression models. The spatial analysis results showed that the densest e-scooter usage happened in downtown areas and university campuses in both cities. However, the temporal characteristics of the two cities’ e-scooter usage patterns turned out to be different: in Austin, afternoons, and weekends experienced greater e-scooter traffic, whereas Minneapolis showed larger evening ridership and stable daily vehicle miles traveled throughout the week. Finally, regression results showed that proximity to the city center, better access to transit, and greater land-use diversity positively correlated with higher e-scooter ridership in both cities. Compared to single-family residential areas, office and institutional land use were more likely to relate to higher ridership in both cities. Curiously, the statistically positive relationship with commercial areas and parks only existed in Austin. This study contributes to transportation literature and practice by providing empirical evidence on e-scooter trips in the U.S. cities and by highlighting the importance of local uniqueness by comparing two cities.
To investigate the association between the neighborhood built environment and trajectories of body mass index (BMI) in youth.
Data were collected in a prospective study of 1293 adolescents in ...Montreal. Built environment variables were obtained from public databases for road networks, land use, and the Canadian Census. Anthropometric data were collected when participants were ages 12.5, 15 and 17 years. We undertook hierarchical cluster analysis to identify contrasting neighborhood types based on features of the built environment (e.g., vegetation, population density, walkability). Associations between neighborhood type and trajectories of BMI z-score (BMIz) were estimated using multivariable linear mixed regression analyses, stratified by sex.
We identified three neighborhood types: Urban, Suburban, and Village. In contrast to the Urban type, the Suburban type was characterized by more vegetation, few services and low population density. Village and Suburban types were similar, but the former had greater land use diversity, population density with more parks and a denser food environment. Among girls, living in Urban types was associated with decreasing BMIz trajectories. Living in Village types was associated with increasing BMIz trajectories. No associations were observed among boys.
Neighborhoods characterized by greater opportunities for active living appear to be less obesogenic, particularly among girls.
•Three neighborhood types were identified based on features of the built environment.•Neighborhoods had varying levels of vegetation, services and walkability.•Greater walkability and variety of services led to decreasing BMI in girls.
One major limitation of prior studies regarding the associations between built environment (BE) and obesity has been the use of anthropometric indices (e.g., body mass index BMI) for assessing ...obesity status, and there has been limited evidence of associations between BE and body fat. This study aimed to explore the longitudinal association between BE and body fat in a cohort of elderly Hong Kong Chinese and examine whether the BE-body fat associations differed by BMI categories.
Between 2001 and 2003, 3944 participants aged 65-98 years were recruited and followed for a mean of 6.4 years. BE characteristics were assessed via Geographic Information System. Body fat (%) at whole body and regional areas (trunk, limbs, android, and gynoid) were assessed by dual energy X-ray absorptiometry at baseline and three follow-ups. Latent profile analysis was used to derive BE class, and linear mixed-effects models were used to investigate the associations of BE class with changes in body fat. Stratified analyses by BMI categories were also conducted.
Three BE classes were identified. Participants in Class 2 (characterized by greater open space and proportion of residential land use) had a slower increase in whole body fat (B = -0.403, 95% confidence interval CI: -0.780, -0.014) and limbs fat (-0.471, 95% CI: -0.870, -0.071) compared with participants in Class 1 (characterized by high proportion of commercial land use). There were significant interactions of BE class with BMI, and participants in Class 2 had a slower increase in whole body fat and regional fat compared with participants in Class 1 (B ranging from -0.987 limbs to -0.523 gynoid) among overweight and obese participants only.
We found that those who resided in the areas characterized by greater open space and proportion of residential land use had a slower body fat increase.
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