Building reverse commute typologies through urban and suburban socioeconomic characteristics

Davidson, Joshua; Ryerson, Megan S.

doi:10.1016/j.cities.2018.04.007

Cited by 9 publications

(3 citation statements)

References 29 publications

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“…We first identify reverse commute O-D pairs in Philadelphia that travel only within Pennsylvania counties of the Philadelphia metropolitan statistical area, using US Census Longitudinal Employer Household Dynamics (LEHD) data based on criteria described in previous work (Davidson, Feiglin, and Ryerson 2021;Davidson and Ryerson 2018). The analytic dataset contains 68,068 unique, reverse commute O-D observations when measured at the census tract level.…”

Section: Methodsmentioning

confidence: 99%

“…To illustrate this new coverage ratio and ranking approach, we build on previous work and look specifically at the case study of the reverse commuting population in Philadelphia (Davidson, Feiglin, and Ryerson 2021;Davidson and Ryerson 2018). This analysis of reverse commutes is one application of the proposed method that can be adjusted to different commute patterns and locations.…”

Section: Questionsmentioning

confidence: 99%

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A One-seat Ride Coverage Ratio using Administrative Origin Destination Data

Davidson¹,

Feiglin²,

Ryerson³

2023

Findings

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Much remains to be known about the geographic areas in regions that are well (or poorly) served by one-seat transit – direct service where users do not need to conduct transfers. We describe geographic access to one-seat service, by advancing the framework of a spatial coverage ratio for transit when accounting for commuter flows as reflected in administrative origin-destination data. Our methodology integrates relatively simple spatial approaches with open data, allowing transit providers to modulate thresholds for one-seat service. In doing so, operators can develop new priority areas for intervention and line adaptation.

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Section: Methodsmentioning

confidence: 99%

Section: Questionsmentioning

confidence: 99%

A One-seat Ride Coverage Ratio using Administrative Origin Destination Data

Davidson¹,

Feiglin²,

Ryerson³

2023

Findings

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“…The experience from French has indicate that majority suburban jobs has been taken by the workers from another suburbs (Aguiléra, 2005). While the motivation for doing reverse commuting could be explained by amenities-related factors (Aguiléra, Wenglenski and Proulhac, 2009), or socio economic disparity between home and work location (Davidson and Ryerson, 2018), the existence of cross-commuting pattern have not been well comprehended. While several 55 th ISOCARP World Planning Congress Jakarta-Bogor, Indonesia International Society of City and Regional Planners attempt has linked cross-commuting to household characteristics (Tscharaktschiew and Hirte, 2010), many were still presumed utility-maximization related factors as a major cause of the phenomenon (Berliant and Tabuchi, 2015;Viguié, 2015;Wrede, 2015).…”

Section: Introductionmentioning

confidence: 99%

Deciding Where to Live in The Suburb: Linking Utility-Maximization and Residential Mobility in Polycentric Urban Region Context

Sadewo¹,

Hudalah²,

Syabri³

et al. 2019

Proceedings of the 55th ISOCARP World Planning Congress

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In a polycentric urban structure, the commuting pattern which was traditionally directed from the suburban to CBD, is becoming more complex with increasing reverse- and cross-commuting activities. This paper is aimed to provide empirical evidence which validating the importance of utility-maximizing parameters, derived from the monocentric model, in the context of post-suburbanized polycentric urban region. It questioning to which extent of different residential mobility between municipalities could be linked to the variation of such parameters. Focusing on the frontier areas of Jakarta Metropolitan Area (JMA), Indonesia, each municipality within the region is treated as a Decision-Making Unit which intend to maximizing co-location between residential and employment uses. Using the data from the 2017 National Socio-Economic Survey (SUSENAS), the analysis was simply taken by comparing the aggregative-mean of income, housing-cost and transportation cost data from each municipal in JMAs periphery. The Data Envelope Analysis (DEA) was used for measure how these utility-maximizing parameters related with inter-suburban migration flows. The results show that housing cost is the only utility which still has significant impact in polycentric setting. Moreover, the area with lowest utility value tends to be the most efficient in attracting in-migrant. It implies that residential mobility within suburban areas does not motivated by lower housing or transportation cost, nor to get near to major employment location. Thus, workers heterogeneity and behavioral aspect may have played bigger role in residential mobility of polycentric urban setting.

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Commute distance and jobs-housing fit

Blumenberg¹,

Siddiq²

2022

Transportation

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Anecdotal evidence suggests that the affordable housing crisis is forcing households to seek lower cost housing in the outer reaches of major metropolitan areas, helping to explain recent increases in commute distance. To test this relationship, we use spatial regression to examine the relationship between the availability of affordable housing in close proximity to jobs (jobs-housing fit) and commute distance in the Los Angeles metropolitan area. The analysis draws on 2015 Longitudinal Employer-Household Dynamics (LEHD) Origin–Destination Employment Statistics (LODES) by workplace supplemented with data from the 2013–2017 5-Year American Community Survey on affordable housing units. We find substantial variation in jobs-housing fit across Los Angeles neighborhoods. The imbalance is greatest in higher-income neighborhoods located along the coast and in Orange County, south of Los Angeles. Controlling for other determinants of commute distance, a higher ratio of jobs to affordable housing is associated with longer distance commutes. To address growing commute distances, policymakers must greatly expand and protect the supply of long-term rental housing particularly in job-rich neighborhoods.

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Building reverse commute typologies through urban and suburban socioeconomic characteristics

Cited by 9 publications

References 29 publications

A One-seat Ride Coverage Ratio using Administrative Origin Destination Data

A One-seat Ride Coverage Ratio using Administrative Origin Destination Data

Deciding Where to Live in The Suburb: Linking Utility-Maximization and Residential Mobility in Polycentric Urban Region Context

Commute distance and jobs-housing fit

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