Zou, Tianqi; Khaloei, Moein; Mackenzie, Don. (2020). Effects of Charging Infrastructure Characteristics on Electric Vehicle Preferences of New and Used Car Buyers in the United States. Transportation Research Record, 2674(12), 165 – 175.
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Abstract
The used car market is a critical element for the mass adoption of electric vehicles (EVs). However, most previous studies on EV adoption have focused only on new car markets. This article examines and compares the effects of charging infrastructure characteristics on the preferences for EVs among both new and used car buyers. This study is based on an online stated preference choice experiment among private car owners in the U.S., and the results of comparable binomial logistic models show that new and used car buyers generally share similar patterns in preferences for EVs, with exceptions for sensitivity toward fast charging time, and home charging solutions. Respondents' stated willingness to adopt an EV increases considerably with improvements in driving range, and the effects on new and used car buyers are similar. The study also finds that better availability of charging infrastructure largely increases preference for EVs. The results further reveal that slow and fast charging have complementary effects on encouraging EV adoption as the combination of public slow and fast charging can compensate for the unavailability of home charging.
Shen, Qing; Wang, Yiyuan; Gifford, Casey. (2021). Exploring Partnership Between Transit Agency And Shared Mobility Company: An Incentive Program For App-based Carpooling. Transportation, 48(5), 2585 – 2603.
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Abstract
How should public transit agencies deliver mobility services in the era of shared mobility? Previous literature recommends that transit agencies actively build partnerships with mobility service companies from the private sector, yet public transit agencies are still in search of a solid empirical basis to help envision the consequences of doing so. This paper presents an effort to fill this gap by studying a recent experiment of shared mobility public-private partnership, the carpool incentive fund program launched by King County Metro in the Seattle region. This program offers monetary incentives for participants who commute using a dynamic app-based carpooling service. Through descriptive analysis and a series of logistic regression models, we find that the monetary incentive to encourage the use of app-based carpooling generates some promising outcomes while having distinctive limitations. In particular, it facilitates the growth of carpooling by making carpooling a competitive commuting option for long-distance commuters. Moreover, our evidence suggests that the newly generated carpooling trips mostly substitute single-occupancy vehicles, thus contributing to a reduction of regional VMT. The empirical results of this research will not only help King County Metro devise its future policies but also highlight an appealing alternative for other transit agencies in designing an integrated urban transportation system in the era of shared mobility.
Keywords
Shared Mobility; Public-Private Partnership; App-based Carpooling; Incentive Fund; Transit Agencies; Incentives; Commuting; Public Transportation; Mobility; Regression Analysis; Regression Models; Partnerships; Vehicles; Car Pools; Private Sector; Occupancy; Transportation Systems; Mass Transit; Transportation Planning; Empirical Analysis; Urban Transportation
Rowe, Daniel H.; Bae, Christine; Shen, Qing. (2011). Evaluating the Impact of Transit Service on Parking Demand and Requirements. Transportation Research Record, 2245, 56 – 62.
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Abstract
Many jurisdictions in the United States typically set minimum parking requirements for residential multifamily developments based on old data that were collected in suburban settings with little transit availability. Such parking requirements applied to urban settings with adequate transit service often result in an oversupply of parking, which in turn creates a barrier to smart growth. Not only does the oversupply of parking encourage automobile use and reduce housing affordability, but it also increases development costs, consumes land and natural resources, and increases associated air and water pollution. This research examines the relationship of parking demand and transit service in First Hill Capitol Hill (FHCH) and Redmond, two urban centers in King County, Washington. An alternative method to collect parking demand data is explored. The results show a strong relationship between transit service and parking demand. The FHCH urban center, which abuts downtown Seattle, exhibited higher levels of transit service and lower parking demand. Parking demand in FHCH was observed to be 0.52 parking space per dwelling unit, which was about 50% less than parking demand observed in Redmond, a growing mixed-use suburban center, and 50% less than data reported by the Institute of Transportation Engineers. After a review of the parking policies of each urban center, opportunities to improve regulations including adjusting minimum parking requirements and allowing for reductions in required parking when developers implement solutions to reduce demand for parking were identified.
Zhao, Zhan; Zhao, Jinhua; Shen, Qing. (2013). Has Transportation Demand of Shanghai, China, Passed Its Peak Growth? Transportation Research Record, 2394, 85 – 92.
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Abstract
On the basis of four comprehensive transportation surveys in Shanghai, China, this study examined the latest trends in Shanghai's travel demand; investigated their social, economic, and spatial drivers; and compared the pace of travel demand growth in three periods: 1980s to early 1990s, early 1990s to mid-2000s, and mid-2000s to the present. The demand growth was relatively slow in the first period and then sped up in the second before it returned to a slower pace in the third period. As for trip purpose, Shanghai's travel is much more diversified than previously, with an increasing share of noncommuting trips (from 28% in 1995 to 46% in 2009). Spatially, travel demand is dispersed from the central district to peripheral districts because of urban expansion and decentralization and from Puxi (west of the Huangpu River) to Pudong (east of the Huangpu River) as a result of significant economic development of the Pudong New Area. Both spatial diffusion and purpose diversification favor the convenience and flexibility of private motor vehicles. Driven by rapid motorization, vehicle travel is growing at a much faster pace than person travel. Overall, the annual growth rate for travel demand in Shanghai reached its peak in 2004 for both person trips and vehicle trips. In absolute numbers, person trip growth has peaked, but vehicle trip growth has not. In response to the growing demand, especially rapid motorization, the local government has made tremendous investments in road infrastructure and public transit, and it has attempted to manage demand through vehicle ownership control.
Keywords
Urban; Impacts; Policy
Wier, Megan L.; Schwartz, Michael; Dannenberg, Andrew L. (2015). Health Impact Assessment: Considering Health in Transportation Decision Making in the United States. TR News (0738-6826), 299, 11 – 16.
Abstract
The article talks about Health Impact Assessment (HIA) when it comes to transportation decision making in the U.S. and discusses the Collaboration between public health professionals and transportation in order to execute HIA.
Keywords
Health Impact Assessment; Public Health -- United States
Schmiedeskamp, Peter; Zhao, Weiran. (2016). Estimating Daily Bicycle Counts in Seattle, Washington, from Seasonal and Weather Factors. Transportation Research Record, 2593, 94 – 102.
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Abstract
This paper examines the relationship between several seasonal and weather factors and bicycle ridership from 2 years of automated bicycle counts at a location in Seattle, Washington. The authors fitted a negative binomial model and then estimated quantities of interest using counterfactual simulation. The findings confirm the significance of season (+), temperature (+), precipitation (), as well as holidays (-), day of the week (+ for Monday through Saturday, relative to Sunday), and an overall trend (+). This paper improves on prior work by demonstrating the use of the negative binomial instead of a Poisson model, which is appropriate given the potential for overdispersion, as observed in these data. In addition to validating the significance of factors identified from the literature, this paper contributes methodologically through its intuitive visualization of effect sizes to nonstatistical audiences. The authors believe that the combination of model type and counterfactual simulation and visualization reflects a reasonable compromise between model complexity and interpretability. Results such as these can aid policy makers and planners in understanding bicycle travel demand elasticities and in guiding interventions aimed at increasing rates of bicycling. The methods presented are fully reproducible and invite adaptation to other locations.
Chen, Peng; Liu, Qian; Sun, Feiyang. (2018). Bicycle Parking Security and Built Environments. Transportation Research: Part D, 62, 169 – 178.
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Abstract
The lack of secure bicycle parking is a serious but often neglected issue that discourages bicycling. Classical environment criminology theories try to explain the pattern of bicycle theft but provide limited insights into the relationship between crime and the built environment. This study examines the association between built environment factors and bicycle theft using a zero inflated negative binomial model to account for data over-dispersion and excess zeros. The assembled dataset provides variables pertaining to the road network, land use, bicycle travel demand, and socio-demographics. The key findings are as follows: (1) Bicycle theft is more likely to occur in areas for commercial purposes, areas with a high population or employment density, and areas with more bike lanes or sidewalks. (2) Bicycle theft is likely to occur at sites with more bike racks or bus stops. (3) Bicycle theft is more likely to occur at mid-blocks than at intersections. (4) Bicycle theft is more likely to occur in neighborhoods with a greater percentage of socially disadvantaged people and in neighborhoods where residents' median age is lower. (5) The likelihood of losing a bicycle is lower in areas with more bicycle trips. In general, the number of bicycle thefts increases in dense areas with more targets and decreases with greater natural guardianship provided by more passersby. With respect to policy implications, governments and transport planners should implement a geographically-differentiated surveillance strategy, encourage bicycling, improve the visibility of bike racks to the public, and promote surveillance and natural guardianship in densely developed areas.
Keywords
Bicycle Parking; Cycling; Bicycle Theft; Sociodemographic Factors; Bicycles; Environmental Aspects; Built Environment; Environment Criminology; Urban Design; Zero-inflated Negative Binomial Model; Crime; Theft; Risk; Opportunities; Behavior; Travel
Moudon, Anne Vernez; Huang, Ruizhu; Stewart, Orion T.; Cohen-Cline, Hannah; Noonan, Carolyn; Hurvitz, Philip M.; Duncan, Glen E. (2019). Probabilistic Walking Models Using Built Environment and Sociodemographic Predictors. Population Health Metrics, 17(1).
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Abstract
BackgroundIndividual sociodemographic and home neighborhood built environment (BE) factors influence the probability of engaging in health-enhancing levels of walking or moderate-to-vigorous physical activity (MVPA). Methods are needed to parsimoniously model the associations.MethodsParticipants included 2392 adults drawn from a community-based twin registry living in the Seattle region. Objective BE measures from four domains (regional context, neighborhood composition, destinations, transportation) were taken for neighborhood sizes of 833 and 1666 road network meters from home. Hosmer and Lemeshow's methods served to fit logistic regression models of walking and MVPA outcomes using sociodemographic and BE predictors. Backward elimination identified variables included in final models, and comparison of receiver operating characteristic (ROC) curves determined model fit improvements.ResultsBuilt environment variables associated with physical activity were reduced from 86 to 5 or fewer. Sociodemographic and BE variables from all four BE domains were associated with activity outcomes but differed by activity type and neighborhood size. For the study population, ROC comparisons indicated that adding BE variables to a base model of sociodemographic factors did not improve the ability to predict walking or MVPA.ConclusionsUsing sociodemographic and built environment factors, the proposed approach can guide the estimation of activity prediction models for different activity types, neighborhood sizes, and discrete BE characteristics. Variables associated with walking and MVPA are population and neighborhood BE-specific.
Keywords
Walking; Confidence Intervals; Research Funding; Transportation; Logistic Regression Analysis; Built Environment; Socioeconomic Factors; Predictive Validity; Receiver Operating Characteristic Curves; Data Analysis Software; Descriptive Statistics; Psychology; Washington (state); Active Travel; Home Neighborhood Domains; Physical Activity; Physical-activity; United-states; Life Stage; Adults; Attributes; Health; Associations; Destination; Pitfalls
Abu Ashour, Lamis; Dannenberg, Andrew L.; Shen, Qing; Fang, Xun; Wang, Yiyuan. (2021). Paratransit Services For People With Disabilities In The Seattle Region During The Covid-19 Pandemic: Lessons For Recovery Planning. Journal Of Transport & Health, 22.
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Abstract
Introduction: Along with all public transit services, paratransit services for people with disabilities experienced substantially reduced demand and an increased need to provide equitable services while protecting their clients and staff's safety during the COVID-19 pandemic. Paratransit services provide a lifeline for their clients' essential mobility needs, including access to medical appointments and grocery stores. In the absence of pre-existing pandemic response plans, examining transit agencies' responses to provide paratransit services during the pandemic can help inform planning for post-pandemic recovery and future disruptive events. Methods: In September 2020, we conducted semi-structured interviews with 15 decision-makers, planners, and drivers working for the primary transit agency in the Seattle region - King County Metro - and its paratransit contractors. Interview questions were designed to identify current services, policy gaps, and critical challenges for recovery planning and post-pandemic paratransit services. Interview transcripts were analyzed using NVivo software to obtain essential themes. Results: The interviewees provided insights about (1) paratransit service changes in response to the pandemic, (2) anticipated impacts of a returning demand on paratransit service efficiency, equity, and quality during the recovery period, and (3) innovative approaches for maintaining post-pandemic equitable paratransit services while balancing safety measures with available resources. Conclusions: Study findings suggest that paratransit service providers should consider (1) developing guidelines for future disruptive events, (2) examining alternative methods for food delivery to clients, (3) planning scenarios for delivering equitable services in the post-pandemic recovery period, and (4) increasing resilience possibly by establishing partnerships with transportation network companies.
Keywords
Paratransit; Mobility; Equity; Covid19 Pandemic; Scenario Planning; Recovery
Wang, Yunhong; Lee, Hyun Woo; Tang, Wenzhe; Whittington, Jan; Qiang, Maoshan. (2021). Structural Equation Modeling for the Determinants of International Infrastructure Investment: Evidence from Chinese Contractors. Journal Of Management In Engineering, 37(4).
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Abstract
International infrastructure investment can effectively accelerate infrastructure development in developing countries and thus support their social and economic progress. However, little is known of the factors that may determine the flow of international infrastructure investment to those countries. This study aims to bridge that knowledge gap, first by identifying the determinants of international infrastructure investment, and then by developing a structural equation model to reveal their underlying interrelationships. The structural equation model is applied to country-level data regarding international infrastructure investment with Chinese contractors in 141 countries worldwide over the 9-year period from 2009 to 2017. The results show that three determinants, namely infrastructure quality, labor supply, and investment interdependency, have a positive relationship with a country's international infrastructure investment inflow. However, another determinant, institutional environment, has a significantly negative impact, which suggests that when making foreign infrastructure investment, Chinese contractors enter countries with a comparatively poor institutional environment with substantial political risks. The results also highlight how much a robust infrastructure development plan can help developing countries avoid the poor-infrastructure trap, a situation in which poor infrastructure quality discourages international infrastructure investment. These research findings may assist international infrastructure investment firms to make informed decisions with regard to financing and managing projects and help policymakers who focus on attracting foreign investment in infrastructure.
Keywords
Foreign Direct-investment; Public-private Partnerships; Economic-growth; Transport Infrastructure; Developing-countries; Labor Productivity; Fit Indexes; Location; Energy; Firms; Infrastructure Investment; Institutional Environment; Infrastructure Quality; Foreign Direct Investment (fdi) Interdependency; Structure Equation Modeling; Belt And Road Initiative