skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Interdependence in active mobility adoption: Joint modeling and motivational spillover in walking, cycling and bike-sharing
Active mobility offers an array of physical, emotional, and social well-being benefits. However, with the proliferation of the sharing economy, new nonmotorized means of transport are entering the fold, complementing some existing mobility options while competing with others. The purpose of this research study is to investigate the adoption of three active travel modes—namely walking, cycling, and bikesharing—in a joint modeling framework. The analysis is based on an adaptation of the stages of change framework, which originates from the health behavior sciences. Multivariate ordered probit modeling drawing on U.S. survey data provides well-needed insights into individuals’ preparedness to adopt multiple active modes as a function of personal, neighborhood, and psychosocial factors. The research suggests three important findings. (1) The joint model structure confirms interdependence among different active mobility choices. The strongest complementarity is found for walking and cycling adoption. (2) Each mode has a distinctive adoption path with either three or four separate stages. We discuss the implications of derived stage-thresholds and plot adoption contours for selected scenarios. (3) Psychological and neighborhood variables generate more coupling among active modes than individual and household factors. Specifically, identifying strongly with active mobility aspirations, experiences with multimodal travel, possessing better navigational skills, along with supportive local community norms are the factors that appear to drive the joint adoption decisions. This study contributes to the understanding of how decisions within the same functional domain are related and help to design policies that promote active mobility by identifying positive spillovers and joint determinants.  more » « less
Award ID(s):
1847537
PAR ID:
10318053
Author(s) / Creator(s):
;
Date Published:
Journal Name:
International journal of sustainable transportation
ISSN:
1556-8318
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Amputees’ preferences for prosthesis settings are critical not only for their psychological well-being but also for long-term adherence to device adoption and health. Although active lower-limb prostheses can provide enhanced functionality than passive devices, little is known about the mechanism of preferences for settings in active devices. Therefore, a think-aloud study was conducted on three amputees to unravel their preferences for a powered robotic knee prosthesis during user-guided auto-tuning. The inductive thematic analysis revealed that amputee patients were more likely to use their own passive device rather than the intact leg as the reference for the natural walking that they were looking for in the powered device. There were large individual differences in factors influencing naturalness. The mental optimization of preference decisions was mostly based on the noticeableness of the differences between knee profiles. The implications on future design and research in active prostheses were discussed. 
    more » « less
  2. Kainz, W.; Manley, E.; Delmelle, E.; Birkin, M.; Gahegan, M.; Kwan, M-P. (Ed.)
    As of March 2021, the State of Florida, U.S.A. had accounted for approximately 6.67% of total COVID-19 (SARS-CoV-2 coronavirus disease) cases in the U.S. The main objective of this research is to analyze mobility patterns during a three month period in summer 2020, when COVID-19 case numbers were very high for three Florida counties, Miami-Dade, Broward, and Palm Beach counties. To investigate patterns, as well as drivers, related to changes in mobility across the tri-county region, a random forest regression model was built using sociodemographic, travel, and built environment factors, as well as COVID-19 positive case data. Mobility patterns declined in each county when new COVID-19 infections began to rise, beginning in mid-June 2020. While the mean number of bar and restaurant visits was lower overall due to closures, analysis showed that these visits remained a top factor that impacted mobility for all three counties, even with a rise in cases. Our modeling results suggest that there were mobility pattern differences between counties with respect to factors relating, for example, to race and ethnicity (different population groups factored differently in each county),as well as social distancing or travel-related factors (e.g., staying at home behaviors) over the two time periods prior to and after the spike of COVID-19 cases. 
    more » « less
  3. With the advent of new mobility modes and technologies, we have seen meaningful changes in travel behavior. One such new mobility mode is on-demand transit. The Metropolitan Atlanta Rapid Transit Authority deployed its own on-demand transit system, dubbed MARTA Reach, in March of 2022. This paper provides an evaluation of the characteristics of two groups of people related to MARTA Reach: those who were interested in it and used it and those who were interested in it but did not use it. In addition, this paper explores the factors that influence membership in each of those two groups using a binary logit model, revealing the underlying characteristics that are linked with the decision to use or not use the service given prior interest. The findings show that simply providing more service has the strongest effect on adoption. Among 561 survey respondents, 426 expressed that the service area for MARTA Reach was too limited for their needs. Modeling results support this finding, in addition to the following strong predictors of on-demand transit adoption: 1) being a frequent transit user, 2) being satisfied with the current state of fixed-route transit service, 3) being part of a low-income household, 4) living within an on-demand transit service area, and 5) being younger. Understanding these group characteristics and underlying factors can help guide future efforts to provide on-demand transit service, such as by targeting the market segments that share features with the underlying factors that are shown herein to be linked with on-demand transit adoption. 
    more » « less
  4. A longstanding tradition of research linking neighborhood disadvantage to higher rates of violence is based on the characteristics of where people reside. This Essay argues that we need to look beyond residential neighborhoods to consider flows of movement throughout the wider metropolis. Our basic premise is that a neighborhood’s well-being depends not only on its own socioeconomic conditions but also on the conditions of neighborhoods that its residents visit and are visited by—connections that form through networks of everyday urban mobility. Based on the analysis of large-scale urban-mobility data, we find that while residents of both advantaged and disadvantaged neighborhoods in Chicago travel far and wide, their relative isolation by race and class persists. Among large U.S. cities, Chicago’s level of racially segregated mobility is the second highest. Consistent with our major premise, we further show that mobility-based socioeconomic disadvantage predicts rates of violence in Chicago’s neighborhoods beyond their residence-based disadvantage and other neighborhood characteristics, including during recent years that witnessed surges in violence and other broad social changes. Racial disparities in mobility-based disadvantage are pronounced—more so than residential neighborhood disadvantage. We discuss implications of these findings for theories of neighborhood effects on crime and criminal justice contact, collective efficacy, and racial inequality. 
    more » « less
  5. Urban heat exposure is an increasing health risk among urban dwellers. Many cities are considering accommodating active mobility, especially walking and biking, to reduce greenhouse gas emissions. However, promoting active mobility without proper planning and transportation infrastructure to combat extreme heat exposure may cause more heat-related morbidity and mortality, particularly in future with projected climate change. This study estimated the effectiveness of active trip heat exposure mitigation under built environment and travel behavior change. Simulations of the Phoenix metro region's 624,987 active trips were conducted using the activity-based travel model (ABM), mean radiant temperature (T MRT , net human radiation exposure), transportation network, and local climate zones. Two scenarios were designed to reduce traveler exposure: one that focuses on built environment change (making neighborhoods cooler) and the other on travel behavior (switching from shorter travel time but higher exposure routes to longer travel time but cooler routes) change. Travelers experienced T MRT heat exposure ranging from 29°C to 76°C (84°F to 168°F) without environmental or behavioral change. Active trip T MRT exposures were reduced by an average of 1.2–3.7°C when the built environment was changed from a hotter to cooler design. Behavioral changes cooled up to 10 times more trips than changes in built environment changes. The marginal benefit of cooling decreased as the number of cooled corridors transformed increased. When the most traveled 10 km of corridors were cooled, the marginal benefit affected over 1,000 trips/km. However, cooling all corridors results in marginal benefits as low as 1 trip/km. The results reveal that heavily traveled corridors should be prioritized with limited resources, and the best cooling results come from environment and travel behavior change together. The results show how to surgically invest in travel behavior and built environment change to most effectively protect active travelers. 
    more » « less