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This paper identifies the current practices and challenges related to the planning, management, and operation of microtransit systems as well as the concerns associated with the (lack of) policies in place. Our work focuses on the U.S. experience and is primarily based on an in-depth analysis of six microtransit systems using a combination of quantitative and qualitative data. We investigate and classify the multiple ways public agencies form public-private partnerships to institute microtransit service in their jurisdictions and discuss the relative advantages and disadvantages of the different service delivery models. We also thoroughly examine the contracts public agencies formed with private entities to disentangle the various cost elements associated with the launch and operation of a microtransit system. Our policy discussion emphasizes the lack of sustained funding sources for microtransit and the funding formulas that lead to a reduction or loss of public transportation funding when a jurisdiction replaces a fixed route service with microtransit. We also explain the requirements for ADA compliance in microtransit systems and highlight that service equivalency between disabled and non-disabled riders is not guaranteed when only some of the microtransit vehicles and operators are ADA compliant and certified. In terms of operation practices, we describe the safety risks that microtransit users may face on a day-to-day basis due to algorithm-driven virtual pick-up and drop-off locations, and the unwillingness of some service providers to enforce inclusive practices and ensure that individuals without electronic payment options and smartphones can gain access to the service. Furthermore, we discuss the challenges with balancing supply and demand in microtransit systems, and the need for allowing for both on-demand and pre-scheduled trip requests in order to ensure that critical and time-sensitive work, school, and medical trips are accommodated and prioritized. • Quantitative and qualitative data from six microtransit implementations. • Classification of public-private partnerships for microtransit service. • Explanation of technology fees and vehicles and drivers' costs in microtransit contracts. • Lack of sustained funding sources, and ADA compliance not guaranteed. • Challenges related to operation, such as the safety of algorithm-driven virtual stops. [ABSTRACT FROM AUTHOR]

This research investigates the socioeconomic and travel characteristics of student transit users in comparison to other young adults and quantifies behavioral differences in public transit access between these two population groups. Using data from a 2015 system-wide on-board survey in the Denver-Aurora region, CO, we seek to understand whether college and university students make more environmentally sustainable choices when accessing bus and light rail transit as well as identify the determinants of their choices. Our results indicate that student transit riders live in larger households with more vehicles per household member and are located substantially farther from the city center and the light rail compared to other young adults. The majority of student light rail users drive alone to light rail stations and typically do not park at the station that is the closest to their home. On the other hand, most other young adults walk to light rail stations. We also find that travel time and vehicle ownership per household member have a significantly lower impact on student choices. The identified travel differences and behavioral variations between the two population groups may be associated with the lack of affordable housing for students in the central and transit-rich neighborhoods of large metropolitan areas. [ABSTRACT FROM AUTHOR]

As the successful design and implementation of alternative mechanisms for funding transit infrastructure, such as value-capture schemes, are becoming more critical, identifying the timing, duration, and spatial extent of the capitalization of accessibility benefits for nearby communities is becoming more and more important. This research makes a significant contribution to the analysis of the spatiotemporal impacts of transit systems by quantifying variations in the spatial distribution of causal effects from project announcement to long-run operation. The study develops a quasi-experimental framework based on advanced difference-in-differences specifications that enable us to capture the distribution of average treatment effects in space and time. The methodology is applied to the light rail system in Charlotte, NC, which includes an original line and its extension. A dataset comprised of the single-family house sales from the last thirty years is compiled for the study area, which contains neighborhoods in the vicinity of the light rail and two comparison areas. The estimated impacts demonstrate significant heterogeneity, on multiple facets. We find that although the shape of the spatial distribution of effects changes over time experiencing increasing curvature, the results consistently indicate highest positive impacts for properties located within 0.25 and 0.5 miles of a transit station. Differential effects are also identified between the original light rail line and its extension, such as lack of anticipation effects for the line extension. Although these results are specific to a single locale, the methods demonstrated through this study can be applied to other areas and transit systems of similar scale. [ABSTRACT FROM AUTHOR]

A plethora of studies has explored the relationship between transit investments and property prices, but very little is known about how new transit projects and transit-oriented development affect nearby businesses and whether they contribute to commercial gentrification. This research presents a quasi-experimental econometric framework for studying transit-induced commercial gentrification from project announcement to post operation using business microdata. Previous urban economics and planning research informs the identification of retail and service business categories associated with the phenomenon of commercial gentrification, including local businesses, chain stores, and businesses offering non-essential or upscale products. Negative binomial models with a difference-in-differences specification enable the temporal and spatiotemporal analysis of business entries, exits, and turnover and the estimation of transit-induced impacts. The developed methodology is demonstrated through an empirical example: the study of the effects of the LYNX Blue light rail line in Charlotte, NC, over a 20-year period. Our study makes a significant contribution to the limited quantitative research on transit and commercial gentrification and is the first to focus on the causal relationship between the two. The application of the analysis framework to other metropolitan areas with transit systems in the future will inform transportation and urban planners on the type of businesses that could be primarily affected and the timing and extent of these effects, and help them design effective and targeted business assistance programs. • Quasi-experimental econometric framework for transit-induced commercial gentrification. • Transitions in the composition of the retail and service business sectors. • Difference-in-differences estimation of business entries, exits, and turnover. • Spatiotemporal analysis of businesses from post announcement to post operation. • Lower entries, exits, and turnover for some business types near the Charlotte light rail. [ABSTRACT FROM AUTHOR]

During the last 50 years, a number of economic forces led to noteworthy changes in the geography of poverty in the US. Employment decentralization and lack of affordable housing have resulted in many low-income households migrating to suburban areas, and as of today, the majority of the low-income population of metropolitan regions resides in the suburbs. Focusing on the Triangle Region, NC, this study systematically explores the changes in the geography of poverty and transit access over time to better understand how accessibility to transit has changed for the low-income residents. Spatial panel data models are also estimated to investigate the relationship between poverty and transit access at the neighborhood level and how it varies spatially and temporally, while accounting for unobserved heterogeneity and spatial autocorrelation. Results indicate that between 1990 and 2015, the outer-ring suburbs experienced the highest increase in both poverty and transit access, although improvements in transit access were lower in the recently urbanized areas within the outer-ring suburbs. Inner-ring suburbs experienced a substantial rise in poverty rate and low-income population, and a comparable increase in transit access. Central cities remained the areas with the highest poverty rate and transit access in the Triangle Region but experienced smaller changes over time compared to suburban areas. The findings of the econometric analysis suggest that poverty rate and transit access are not significantly related at the neighborhood level when time-invariant unobservable characteristics are accounted for. [ABSTRACT FROM AUTHOR]