Search

Bike-sharing holds promise for available and healthy mobility services during COVID-19 where bike sharing users can make trips with lower health concerns due to social distancing compared to the restricted transportation modes such as public transit and ridesharing services. Leveraging the trip data of the Divvy bike-sharing system in Chicago, this study exploresspatially heterogeneous effects of built environment on bike-sharing usage under the pandemic. Results show that the average weekly ridership declined by 52.04%. To account for the spatially heterogeneous relationship between the built environment and the ridership, the geographically weighted regression (GWR) model and the semiparametric GWR (S-GWR) model are constructed. We find that the S-GWR model outperforms the GWR and the multiple linear regression models. The results of the S-GWR model indicate that education employment density, distance to subway, COVID-19 cases, and ridership before COVID-19 are global variables. The effects between ridership and the built environment factros (i.e., household density, office employment density, and the ridership) vary across space. The results of this study could provide a useful reference to transportation planners and bike-sharing operators to determine the high bike-sharing demand area under the pandemic,thus adjusting station locations, capacity, and rebalancing schemes accordingly. [ABSTRACT FROM AUTHOR]

The adoption of bus rapid transit (BRT) systems has gained worldwide popularity over the past several decades. China is no exception as it has long been aiming at promoting public transportation. Prior studies have provided extensive evidence that BRT has substantial effects on house prices with traditional econometric techniques, such as hedonic pricing models. However, few of those investigations have discussed the non-linear relationship between BRT and house prices. Using the Xiamen data, this study employs a machine learning technique, namely the gradient boosting decision tree (GBDT), to scrutinize the non-linear relationship between BRT and house prices. This study documents a positive association between accessibility to BRT stations and house prices and a negative association between proximity to the BRT corridor and house prices. Moreover, it suggests a non-linear relationship between BRT and house prices and indicates that GBDT has more substantial predictive power than hedonic pricing models. [ABSTRACT FROM AUTHOR]

Numerous cities are undergoing the ageing of populations. Developing a transport system that incorporates mobility needs, preferences, and demands of elderly people is crucial to such a demographic shift. Understanding the travel behavior and characteristics of elderly people is the first and foremost step towards this goal. In stark contrast with Western car-dominant places, numerous East Asian modern cities (e.g., Hong Kong, Beijing, and Shanghai) have high levels of public transportation use. Experience gained from existing studies in the West cannot be applied to Hong Kong, a typical transit-dependent city. In light of this, based on the 2011 Travel Characteristic Survey data and Poisson and negative binomial regression models, this study identifies factors that significantly affect the number of daily trips taken by (or trip frequency of) elderly people in Hong Kong. The paper finds that both socio-demographic (e.g., age and housing type) and built environment characteristics significantly affect the trip number of elderly people. Interestingly, it is determined that car availability does not play a significant role in the trip generation process, but public transportation accessibility truly matters. This outcome remarkably differs from findings in Western car-dominant cities. Moreover, to discern whether the elderly are a homogenous group, this study estimates separate models for the young elderly (aged between 60 and 74) and the very old (aged 75 or above). It is observed that the effect of public transportation accessibility on elderly mobility varies among elderly subgroups: public transportation accessibility significantly affects the trip frequency of the young elderly, but not that of the very old. Finally, a multitude of policy measures with the aim of upgrading elderly mobility is proposed. [ABSTRACT FROM AUTHOR]

Hong Kong is a transit-oriented city with an extremely high public transportation share (approximately 90%). Additionally, in this city, the percentage of older people aged 60 or above is predicted to reach 38.0% in 2064. Thus, the provision of age-friendly public transportation is timely and enormously significant. Only with a better understanding of mobility behaviors of older people, it is possible to tailor transportation systems and optimize market strategies to cater to their actual needs and preferences. Based on the 2011 Travel Characteristic Survey data, this paper calibrates a mixed binary logit model and a conditional logit model to uncover older people's travel propensity, as well as destination and departure time choices. The findings include: (1) a host of socio-demographic variables and land-use attributes affect travel propensity; (2) owning an automobile and driving license are too weak to exert significant influence on travel propensity. This finding is in contrast with the conventional wisdom in car-dominant cities where car ownership and license-holding status are significant predictors of mobility; (3) there are random taste variations among respondents regarding travel propensity; and (4) time-constant destination and time-variant origin-destination pair characteristics influence older people's destination and departure time decisions. Based on the results, a few policy suggestions (e.g., reducing the actual and perceived costs associated with interchanges, time-varying public transport service) are discussed. We believe that these policy sights can act as a valuable reference to transportation planning which addresses the mobility of older people, especially in the metropolitan cities which provide similar public transport services. [ABSTRACT FROM AUTHOR]

• Short EBSS trips mainly substitute walking and the BSS. • Long EBSS trips mostly substitute cars, buses, and the subway. • The integration of the EBSS and transit has reduced carbon emissions. • The CO 2 emissions per km are 19.47 g. • The EBSS has saved 75.52% of CO 2 emissions. This paper presents a quantitative analysis of the mode substitution and usage-phase carbon emission impacts of the electric bike-sharing system (EBSS) on urban transportation using self-administrated survey data and EBSS operating data. The substitution probabilities of a given EBSS trip for different transport modes is determined using the Bayesian inference method. Emission impact is measured by comparing the current emissions to those generated by other transport modes without the EBSS. Remarkably, the partial-trip substitution impact of the EBSS on car travel is investigated, where the EBSS serves as a connection to public transit. The results show that the EBSS barely generates new trips; most short-distance EBSS trips were transferred from walking and conventional bike-sharing, and most long-distance trips were shifted from cars, buses, and the subway. Around 5% of EBSS trips less than 2 km were transferred from the car by integrating with public transit while accounting for over half of the emission reduction. Based on our method, the CO 2 emissions per km of EBSS are 19.47 g, with 6.91 g generated by e-bikes due to electricity consumption and 12.56 g by trucks for battery swapping and bike relocation. The studied EBSS has saved 75.52% of CO 2 emissions that other transport modes could have generated. [ABSTRACT FROM AUTHOR]

• To-bus accessibility and by-bus accessibility significantly affect housing prices in the bus-dependent city. • Spatial heterogeneity exists in the price effects of bus accessibility. • Bus frequency exerts a larger price effect in the peripheral area than in the central. Accessibility to transit facilities is perceived to affect property prices. However, accessibility by transit has rarely elicited adequate scholarly attention in property price analyses. Additionally, previous studies on how transit accessibility affects property prices mainly focused on rail and bus rapid transit systems, while conventional bus transit, which is very popular in many contexts, has seldom been investigated. Moreover, whether there is spatial heterogeneity in the price (or capitalization) effects of conventional bus accessibility remains to be explored. To fill these gaps, this study aims to investigate the role of accessibility to and by bus in determining housing prices in a bus-dependent city where urban transit service is offered mainly by a bus system rather than other transit systems. Using a database of 4966 condominium units in Xiamen, China, this study develops a battery of spatial econometric models to estimate global and local relationships between to-bus and by-bus accessibility and housing prices. The findings are as below: (1) to-bus accessibility (measured by the number of nearby bus stops) is positively associated with nearby housing prices; (2) by-bus accessibility (measured by travel time to city centers by bus and bus frequency) significantly affects nearby housing prices; (3) spatial heterogeneity exists in the price effects of bus accessibility; and (4) bus frequency exerts a larger price effect in the peripheral area than in the central. Finally, practical and policy implications are discussed. [ABSTRACT FROM AUTHOR]

• URT has a positive effect on nearby housing prices. • Transfer stations have a larger effect on nearby property prices than regular stations. • The price effects of URT accessibility are stronger in the suburban area than in the urban. • Practical implications, such as differential, location-specific value capture schemes, are discussed. Urban rail transit (URT) is shown to mitigate numerous contemporary urban problems (e.g., traffic congestion and environmental degradation). To reap such gains, many Chinese cities have actively constructed URT and/or have been on their way of doing so. However, these URT projects often encumber local governments with debt. Value capture schemes can be used to finance URT development. To implement such schemes, we need to understand the relationship between URT and property prices. Despite numerous studies on this topic in other countries, limited empirical studies in urban China have been conducted. Moreover, most previous studies are silent on two issues that are important to value capture, namely: (1) whether transfer stations provide a larger housing price premiums than regular stations, and (2) whether the price effect of URT accessibility is more perceptible in the suburban area than that in the urban. This study contributes to our understanding of these issues by constructing a set of hedonic pricing models using price data from 722 residential complexes in the vicinity of a URT line in Shenzhen, China. Our empirical results show that (1) URT has a positive impact on nearby property prices; (2) the positive impact diminishes quickly as the distance to URT station increases; (3) transfer stations have a larger positive effect on nearby property prices than regular stations; and (4) the price effects of URT accessibility are stronger in the suburban area than in the urban. The first two findings are in line with most previous studies, but the last two findings are seldom reported in existing literature. Practical implications of our findings, such as differential, location-specific value capture schemes, are further discussed. [ABSTRACT FROM AUTHOR]

• Study the alternative mode choice of ride-sourcing users based on survey data. • 54.71% of respondents choose public transit when the ride-sourcing is suspended. • Age, gender, income, car ownership, and trip purpose are significant determinants. • More metro stations around the trip origin could reduce private vehicle use. • Suspension of ride-sourcing services would lead to lower vehicle emissions. Despite the popularity of ride-sourcing services among the public, some cities consider suspending ride-sourcing services because of repeated safety failures and protests from taxi drivers. The impact of such a policy on the transportation system and environment is rarely studied. To fill this gap, we performed a stated preference survey in Chengdu, China, to investigate the alternative mode choice (AMC) of ride-sourcing users. We collected data of 435 trips from 340 respondents. The analysis results show that with suspension, 53.71%, 27.36%, 10.80%, and 7.13% of ride-sourcing trips would shift to public transit, taxi, active mode (walking and cycling), and private car trips, respectively. The mixed logit modeling results show that age, gender, household income, number of cars per person, trip purpose, and transit accessibility significantly influence AMC. Results of Monte-Carlo Markov Chain simulations indicate that vehicle emissions related to ride-sourcing trips will decrease by more than 50% after the suspension. [ABSTRACT FROM AUTHOR]

Understanding the relationship between the built environment and e-scooter sharing (ESS) usage is important because it could help planners determine the high-demand area and design an effective investment plan to promote the use of micromobility. Previous studies usually assume that the relationship is linear, which may lead to inaccurate ridership prediction and ineffective policy. Thus, this study explores the nonlinear and threshold effects of the built environment on ESS ridership in Los Angeles using the gradient boosting decision tree. Fourteen built environment and ten demographic variables are selected as independent variables. We find that the built environment accounts for 91.66% of the total relative importance. The ten most important variables are intersection density, road density, public transit station density, restaurant density, employment density, distance to the center, population density, proportion of park area, parking density, and bike lane density. The nonlinear and threshold effects of the built environment on ESS ridership are determined. By using two spatial analysis units (census tract and census block group) and four temporal analysis units (spring, summer, autumn, and winter), the modifiable areal unit problem and the modifiable temporal unit problem are revealed. [ABSTRACT FROM AUTHOR]

China has entered a stage in which new rural construction and urbanization are rapidly developing. Considerable changes are occurring in rural China, and the built environment is different from that in the past; such difference directly influences the travel mode choice of rural residents. However, our knowledge on how the rural built environment influences the travel mode choice of rural residents in China remains limited. To fill this gap, this study combines on-site measurement methods, geographic information system (GIS) technology, and activity diary survey to obtain basic data regarding the built environment and the daily activities of rural residents. The multinomial logit (MNL) model is used to explore the relationship between the rural built environment and the travel mode choice of rural residents. Results show that building density significantly positively affects private car trips. This finding challenges earlier urban built environment research due to the considerable gap between rural and urban areas. An increase in road density increases the travel frequency of electric bicycles and motorcycles. Accessibility perception and preferences positively affect the probability of choosing to walk. Safety and neighborhood harmony perception positively affect the travel frequency of motorcycles and private cars. Rural residents who prefer a safe living environment are likely to choose walking for their daily travel. Despite the considerable achievements in the construction of rural roads, the frequency of public transportation remains low for rural residents. Therefore, additional attention should be given to the investment and construction of public transport facilities during rural urbanization. [ABSTRACT FROM AUTHOR]