The unequal impacts of time, cost and transfer accessibility on cities, classes and races

Bittencourt, Taina Andreoli; Giannotti, Mariana Abrantes

doi:10.1016/j.cities.2021.103257

Cited by 31 publications

(12 citation statements)

References 28 publications

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“…A few recent studies that use location-based measures have taken the monetary costs into account. Most of these look at how such costs should be considered when https://www.sciencedirect.com/science/article/pii/S0966692322000321 assessing accessibility and inequalities levels (Bittencourt and Giannotti, 2021;Bocarejo et al, 2014;Bocarejo S. and Oviedo H., 2012;El-Geneidy et al, 2016;Guzman et al, 2017;Guzman and Oviedo, 2018;Liu and Kwan, 2020;Ma et al, 2017;Oviedo et al, 2019;Rodriguez et al, 2017;Van Dijk et al, 2015;Venter, 2016). Others analyze the interaction between accessibility and subjective well-being (Lionjanga and Venter, 2018) and propose a transit path finding method that accounts for monetary constraints (Conway and Stewart, 2019).…”

Section: Incorporating Monetary Costs Into Accessibility Measuresmentioning

confidence: 99%

“…The second approach found in the literature introduces monetary costs into accessibility measures by combining two travel impedance functions, one related to travel times and another to monetary costs. Bittencourt and Giannotti (2021), Conway and Stewart (2019) and Rodriguez et al (2017) calculate cumulative opportunities measures by simultaneously considering travel time and travel cost thresholds. In this case, the definition of monetary thresholds, likewise for time thresholds, can be done for example according to average spendings or to values deemed acceptable given a budget constraint.…”

Section: Incorporating Monetary Costs Into Accessibility Measuresmentioning

confidence: 99%

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The impact of transit monetary costs on transport inequality

Herszenhut

Pereira

Portugal

et al. 2022

Journal of Transport Geography

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Section: Incorporating Monetary Costs Into Accessibility Measuresmentioning

confidence: 99%

Section: Incorporating Monetary Costs Into Accessibility Measuresmentioning

confidence: 99%

The impact of transit monetary costs on transport inequality

Herszenhut

Pereira

Portugal

et al. 2022

Journal of Transport Geography

View full text Add to dashboard Cite

“…Since the GHG reduction magnitude per bus is so much higher than LDV replacement, we believe that even under the inefficient upper bound TCO bus electrification should not be discounted by decision-makers. The promotion of buses can provide electric mobility for more people since they are a public good which can be accessed by most (though unevenly [73]), while BEV and PHEV incentives policies promote the ownership of privately-owned personal vehicles. As such, decision-makers should consider working with transit agencies to realize a switch to electric buses in addition to supporting efficient and improved service that will have a long-term impact on reducing single-passenger vehicle dependence and increasing transit ridership [74,75].…”

Section: Discussion On Policy Implementationmentioning

confidence: 99%

Electric Mobility Emission Reduction Policies: A Multi-Objective Optimization Assessment Approach

2022

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The passenger transportation sector is notoriously sticky to decarbonize because it is interlinked with urban form, individual choice, and economic growth. As the urgency to respond to climate change increases and the transport sector disproportionally increases its contributions to global GHG emissions, there is a need for a more meaningful and transparent application of tools to cost GHG emission reduction. This study presents a multi-objective integer optimization (MIO) model to support the costing and GHG reduction estimation of electric mobility road passenger transportation policies. The model considers both cost and GHG emission minimization under resource constraints and background changes in policy interventions within interval ranges for the province of Ontario’s (Canada) in year 2030. All Pareto optimal solutions are included but results that indicate the optimal policy allocation for two discrete targets are discussed in detail; one scenario where $3 billion spending over ten years is the target and another scenario where the target is 40% GHG reduction in year 2030 (relative to 2005 levels). The MIO approach offers an out-of-the-box solution to support the GHG-reducing decision-making process at all levels of government by implementing optimal policy combinations to achieve GHG emission reductions under a target GHG emission reduction target and/or budget.

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“…A few recent studies that use location-based measures have taken the monetary costs into account. Most of these look at how such costs should be considered when assessing accessibility and inequalities levels (Bittencourt and Giannotti, 2021;Bocarejo et al, 2014;Bocarejo S. and Oviedo H., 2012;El-Geneidy et al, 2016;Guzman et al, 2017;Guzman and Oviedo, 2018;Liu and Kwan, 2020;Ma et al, 2017;Oviedo et al, 2019;Rodriguez et al, 2017;Van Dijk et al, 2015;Venter, 2016). Others analyse the interaction between accessibility and subjective well-being (Lionjanga and Venter, 2018) and propose a transit path finding method that accounts for monetary constraints (Conway and Stewart, 2019).…”

Section: Incorporating Monetary Costs Into Accessibility Measuresmentioning

confidence: 99%

The impact of transit monetary costs on transport inequality

Herszenhut¹,

Pereira²,

Portugal³

et al. 2021

Preprint

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Transport equity analyses are often informed by accessibility estimates based solely on travel time impedance, ignoring other elements that might hinder access to activities, such as the monetary cost of a trip. This paper examines how and to what extent simultaneously incorporating both time and monetary costs into accessibility measures may impact transport equity assessment. We calculate job accessibility by transit in the city of Rio de Janeiro, Brazil, using cumulative opportunity measures under distinct combinations of temporal and monetary thresholds, and compare how inequality levels vary across different scenarios. We find that the most common research practice of disregarding monetary costs tends to overestimate accessibility levels. However, stricter monetary constraints do not necessarily result in less equitable scenarios. How accessibility inequality is affected by monetary costs is highly dependent on what combinations of temporal and monetary cut-offs are considered in the analysis. In the case of Rio, opting for lower monetary thresholds when looking at shorter trips leads to inequality levels lower than those found in the no monetary threshold scenario, but results in higher inequality levels when allowing for longer trips. We find that the impact of monetary costs on transport equity analyses depend on a complex interaction between fare policies, the spatial organisation and operational characteristics of transit systems, and the spatial co-distribution of jobs and residential locations. The paper thus highlights that conclusions and policy recommendations derived from transport equity analyses can be affected in non-intuitive ways by the interplay between temporal and monetary constraints. Future research should investigate how different combinations of travel time and monetary costs thresholds affect equity analyses in different contexts.

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The unequal impacts of time, cost and transfer accessibility on cities, classes and races

Cited by 31 publications

References 28 publications

The impact of transit monetary costs on transport inequality

The impact of transit monetary costs on transport inequality

Electric Mobility Emission Reduction Policies: A Multi-Objective Optimization Assessment Approach

The impact of transit monetary costs on transport inequality

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