Modeling job accessibility using online map data: An extended two-step floating catchment area method with multiple travel modes

Current quantitative measures of job accessibility rarely consider the interaction between job opportunities and labor force, and the effects of dynamic travel mode choice. Drawing upon multiple open-source datasets, we develop a job accessibility index by extending the two-step floating catchment area method (2SFCA). The job accessibility indices are calculated for different commuting scenarios concerning distance, time, and travel modes. The results suggest that job accessibility is very sensitive to travel modes, and using a single travel mode would contribute to a biased job accessibility index. The job accessibility indices with combined travel modes are more geographically balanced than using a single travel mode. Furthermore, the new index is employed to examine the spatial pattern of job accessibility and explore the relationship between job accessibility, housing, and population in the Pudong district, Shanghai. The new job accessibility indices manifest the impacts of ring roads on the spatial distribution of job accessibility. A comparative analysis shows that the floating population has poor driving-based job accessibility but can access job opportunities using public transit. Also, poor job accessibility leads to low rent prices but has little impact on medium-high rent. Both transit-based and drive-based job accessibility indices are positively related to housing prices. Our study highlights the importance of considering dynamic travel mode choice in job accessibility research. The research outcomes also contribute to the literature on spatial mismatch by revealing the unique relationship between job accessibility, housing, and population in urban China.     

A GIS-based spatial statistical approach to modeling job accessibility by transportation mode: case study of Columbus,Ohio

Improving job accessibility based on transport connectivity helps to address equity issues. Spatial autocorrelation (SA) is also a focus of interest in transportation planning, but has been neglected in analyzing job accessibility in metropolitan areas. In this study, GIS-based job accessibilities by walking, transit, and car are computed for the metropolitan area of Columbus, Ohio, and three transport-based spatial autoregressive (SAR) models are estimated to account for the SA of job accessibility among neighboring block groups, while controlling for built-environment and socioeconomic factors. SA intensities and extents are compared in order to better understand local spatial clusters of job accessibility across the region. Direct and indirect spillover effects due to an investment change in transportation facilities are estimated and provide important transportation planning information. The results also show that walking-accessed jobs are primarily related to physical settings (e.g., land uses) at the local level. Locations with a higher share of zero-vehicle housing units have better job accessibility by transit. There is a spatial mismatch between Asian population clusters and transit-accessed jobs, possibly because of the car-oriented residential clusters around Honda of America Manufacturing in suburban areas. More importantly, locations with a higher share of single-parent households are at a disadvantage in overall job accessibility. Due to its complex transportation needs, a society friendly to single parents should spatially integrate accessible jobs with other needed activities via land-use and transportation planning. Alternatively, car-ownership programs and non-spatial social supports also might be effective to help secure job opportunities and perform daily life activities.     

Informality and accessibility to jobs by public transit: Evidence from the São Paulo Metropolitan Region

Access to opportunities through public transport can have different impacts on individual's life especially in developing countries where opportunities are limited, job informality rates are high, and socioeconomic characteristics gaps are big. The aim of this paper is to explore the relationship between job informality and accessibility to employment by public transport in São Paulo Metropolitan Region (SPMR), Brazil. To do so, we calculate a cumulative-opportunity measure of accessibility to jobs for 633 areas within the SPMR. We use a multilevel mixed-effects logistic regression model to estimate the effect of job accessibility on the likelihood of being informally employed, controlling for individual and other area characteristics. To account for informal sector heterogeneity, two regression models are generated: one for the workers earning below minimum wage and one for the workers earning above minimum wage. The results show that accessibility to jobs is unevenly distributed across the region, largely concentrated in the core of the region, and especially in the high-income areas. The regression results show that for workers earning less than the minimum wage, a higher level of accessibility to jobs by public transport is associated with a lower likelihood of being a worker in the informal job sector. For informal workers earning more than the minimum wage, car ownership seem to be more relevant than transit accessibility in determining the likelihood of being part of the informal job sector. In light of these findings, increasing accessibility by public transport through either expanding transit services to areas with high informality rates to have a better access to formal jobs or supporting the decentralization of formal jobs may be a way to achieve reductions in informality rates, especially among those earning less than the minimum wage.     

Evaluating the equity implications of ridehailing through a multi-modal accessibility framework

In rapidly-growing metropolitan regions, it is crucial that transportation-related policies and infrastructure are designed to ensure that everyone can participate equitably in economic, social, and civil opportunities. Ridehailing services are touted to improve mobility options, but there is scant research that incorporates this mode within an accessibility framework. This paper employs a generalized cost measure in a multi-modal accessibility framework, namely Access Profile Analysis, to assess the role of ridehailing in providing job access to historically under-resourced parts of Toronto, Canada, referred to by the city as Neighborhood Improvement Areas (NIAs). Ridehailing is analyzed both as a mode of commute and as a feeder to the transit network (a first-mile solution). The results indicate that there are two main determinants of the extent to which ridehailing provides additional accessibility over transit: the transit level of service at the origin zone and the zone's proximity to employment opportunities. The ridehailing mode is shown to increase accessibility especially to closer destinations (jobs), with the highest improvement seen in the city's inner suburbs. On the other hand, integrating ridehailing with public transit does little to improve access to jobs. Compared to the rest of the city, NIAs experience a higher accessibility improvement from ridehailing alone, but not from its integration with transit. Nonetheless, job accessibility remains lower in NIAs than in other areas – even after the introduction of ridehailing.     

Measuring and visualizing place-based space-time job accessibility

Place-based accessibility measures, such as the gravity-based model, are widely applied to study the spatial accessibility of workers to job opportunities in cities. However, gravity-based measures often suffer from three main limitations: (1) they are sensitive to the spatial configuration and scale of the units of analysis, which are not specifically designed for capturing job accessibility patterns and are often too coarse; (2) they omit the temporal dynamics of job opportunities and workers in the calculation, instead assuming that they remain stable over time; and (3) they do not lend themselves to dynamic geovisualization techniques. In this paper, a new methodological framework for measuring and visualizing place-based job accessibility in space and time is presented that overcomes these three limitations. First, discretization and dasymetric mapping approaches are used to disaggregate counts of jobs and workers over specific time intervals to a fine-scale grid. Second, Shen's (1998) gravity-based accessibility measure is modified to account for temporal fluctuations in the spatial distributions of the supply of jobs and the demand of workers and is used to estimate hourly job accessibility at each cell. Third, a four-dimensional volumetric rendering approach is employed to integrate the hourly job access estimates into a space-time cube environment, which enables the users to interactively visualize the space-time job accessibility patterns. The integrated framework is demonstrated in the context of a case study of the Tampa Bay region of Florida. The findings demonstrate the value of the proposed methodology in job accessibility analysis and the policy-making process.     

Job accessibility and the modal mismatch in Detroit

Transportation scholars are challenging traditional formulations of the spatial mismatch hypothesis because previous studies have disregarded the considerable difference between travel modes. This case study of the Detroit metropolitan region uses 2000 census data and a gravity-based model of transportation accessibility to test differences in access to jobs among places and people, and provides support for recent calls for reconceptualizing spatial mismatch. It shows that even though Detroit experiences the greatest distance between African Americans and jobs of any region in the country, most central city neighborhoods offer an advantage in accessibility to jobs compared to most other places in the metropolitan region – as long as a resident has a car. Policies aimed at helping carless people gain access to automobiles may be an effective means of improving the employment outcomes of inner-city residents.     

Job accessibility through public transport and unemployment in Latin America: The case of Montevideo (Uruguay)

Accessibility to job opportunities is one of the factors that explains labor outcomes. For developing countries, public transport plays a key role in providing the population with access to employment opportunities. This paper aims to quantify accessibility by public transport to employment in Montevideo, Uruguay and to explore how accessibility to job opportunities via public transport relates to unemployment. To do so, we calculate a cumulative measure of accessibility to job opportunities for 1063 small zones—approximately 4–6 blocks each—within Montevideo. This measure yields accurate data on accessibility and can be assigned to individual households. Accessibility in Montevideo is unevenly distributed among social strata and is concentrated within the central (and wealthier) areas of the city. In addition, a multilevel logistic regression analysis indicates that greater accessibility to jobs via public transport is associated with a lower probability of being unemployed. This finding suggests that improving accessibility to job opportunities via public transit may enhance individual labor outcomes.     

The first rapid tram line in Poland: How has it affected travel behaviours,housing choices and satisfaction,and apartment prices?

The opening of the Poznań Rapid Tram (pol. Poznański Szybki Tramwaj, PST) in the year 1997 symbolically marked the beginning of a new era in the development of urban transportation systems in Poland. In this paper we would like to address the following question: more than one decade after the opening of the PST, what are its effects in terms of travel behaviours, housing choices and satisfaction, and apartment prices? In order to answer this question, we combined data on travel behaviours and housing choices from a survey based on a sample of nearly 300 households with data on housing prices from over 1400 real estate transaction records from the period between 2010 and 2013. Our results show that the proximity to PST affects travel behaviours, as respondents living close to PST stops confirmed that they use this form of transportation more often. There also seems to be some effect on housing choices; in locations close to PST stops we found many households living in rental housing, particularly university students. Also, about 20% of interviewees declared that they would pay more for apartments located closer to the rapid tram. However, that effect was only partly confirmed through the analysis of transaction prices. Using standard and spatial econometric regressions including variables like apartment size, floor number, amenities, and type of building we found a weak correlation between the proximity to PST and apartment prices. In conclusion, we argue that treating property price effects as the main justification for public transportation projects might be a doubtful choice, because in some cases the principal impacts of such projects might be visible in terms of residents' satisfaction and travel behaviours.     

Daily fluctuations in transit and job availability: A comparative assessment of time-sensitive accessibility measures

Accessibility to jobs by transit is increasingly incorporated into transportation and land-use planning objectives, as it is proven to be a relevant indicator for assessing land-use and transport performance. With a rise in time-sensitive accessibility measures, choosing the appropriate measure is increasingly challenging for engineers, planners and policy-makers. This research presents a comparative analysis of three accessibility measures, two of which are time-sensitive. Relative accessibility measures are generated for five time periods based on a) constant transit service and number of jobs (constant); b) variable transit service and constant number of jobs (static) and c) variable transit service and variable number of jobs available (dynamic). The measures are first assessed by incorporating them into a transit mode share model. Interestingly, findings show that all three measures behaved similarly in the three regression models. Furthermore, all accessibility measures are found to be highly correlated. The study suggests that the most commonly used accessibility measure (constant measure at 8 am) is representative of the relative accessibility (static or dynamic) over the course of the day and is thus appropriate and meaningful to be used by policy-makers, engineers and planners.     

Analysis of job accessibility promoted by ride hailing services: A proposed method

The concept of accessibility as an element of the interaction between land use and transportation is widely applied in studies of urban mobility. The idea that the accessibility of a place can be measured by the variety and quantity of opportunities available at the destination has led to the creation and adaptation of various indicators. The new mode of transport known as ride hailing (RH) has grown in recent years throughout the world, making it necessary to evaluate its impact on modern society, mainly its interaction with other modes. Therefore, this article presents a method to calculate the accessibility of formal jobs generated by public transportation (PT) and RH, to compare the results. For this purpose, we made adaptations to two indicators commonly used in the literature: the Gini index combined with the Lorenz curve; and the location quotient (LQ). The integrated structure is demonstrated in the context of a case study conducted in four districts of the city of Rio de Janeiro, Brazil. By applying the proposed method, we found that in regions with high commercial concentration and number of jobs, with the fares charged in the city, the accessibility to formal jobs generated by RH is greater than that associated with PT when more than two passengers travel together. This information on the competition or complementarity of the two modes can be useful to make decisions for regulation of the transport sector in general, and ride hailing in particular.     

Balancing time: Using a new accessibility measure in Rio de Janeiro

One of the most common applications of accessibility is in evaluating inequality in access to jobs. A vital factor to be incorporated by accessibility indicators when analyzing job accessibility is the competition for job positions by job seekers; otherwise, the results may be inaccurate or misleading. Despite efforts by researchers to develop accessibility measures that capture job competition, they fail to ensure that these measures are practical and easily interpretable and communicable, which in turn makes planners and policymakers continue to opt for more straightforward measures. In this paper we aim to fill this gap by providing a simple accessibility measure that accounts for competition effects, while remaining practical, intuitive, and highly communicable. The proposed indicator – Balancing Time – is applied to assess the inequality in job accessibility in 160 neighborhoods within the city of Rio de Janeiro, and the results are compared with the most popular indicator used in practice, the cumulative opportunities. The findings suggest that Balancing Time overcomes some of the limitations of cumulative opportunities and that it is a useful tool for planners, particularly in the cities with job opportunities concentrated in central areas. Given its simplicity, Balancing Time is especially relevant in the context of the Global South, where most transport agencies face data limitations and have low skilled technical staff.     

Accessibility across transport modes and residential developments in Nairobi

A key goal of urban transportation planning is to provide people with access to a greater number of opportunities for interaction with people and places. Measures of accessibility are gaining attention globally for use in planning, yet few studies measure accessibility in cities in low-income countries, and even fewer incorporate semi-formal bus systems, also called paratransit. Drawing on rich datasets available for Nairobi, Kenya this analysis quantifies place-based accessibility for walking, paratransit, and driving using three different measures: a mobility measure quantifying how many other locations in Nairobi can be reached in 60 min, a contour measure quantifying the number of health facilities that can be reached in 60 min, and a gravity measure quantifying the number of health facilities weighted by a time-decay function. Health facilities are used because they are an essential service that people need physical access to and as a representation of the spatial distribution of activities more broadly. The findings show that place-based accessibility is highest for driving, then paratransit, then walking, and that there are high levels of access to health facilities near the Central Business District (CBD) for all modes. Additionally, paratransit accessibility is comparatively better in the contour and gravity measures, which may mean that paratransit is efficiently providing access based on the spatial distribution of services. The contour measure results are also compared across different residential levels, which are grouped based on neighborhood characteristics and ordered by income. Counterintuitively, the wealthiest areas have very low levels of place-based accessibility for all modes, while poor areas have comparatively better walking access to health facilities. Interestingly, the medium low residential level, characterized in part by tenement apartment buildings, has significantly higher accessibility than other residential types. One way to reduce inequality in access across income groups is to increase spatial accessibility for the modes used by low- and middle-income households, for example with policies that prioritize public transport and non-motorized travel, integrate paratransit with land use development, and provide safe, efficient, and affordable options.     

Transit-based job accessibility and urban spatial structure

Job accessibility is a measure of people, opportunities, and transportation system that are fundamental elements of urban spatial structure. Therefore, job accessibility can be used as a tool to understand urban spatial structure. Studying transit-based job accessibility can provide more insight into inner cities. To study transit-based job accessibility, a person-based approach is needed in order to take full consideration of the elements. However, person-based approaches are substantially restricted by the availability of individual trip data. This paper takes a simulation approach to study transit-based job accessibility. First, transit-dependent worker agents are generated using a population synthesis. Then the agents are enabled with job search and commuting capabilities. Once the agents are deployed in a commuting simulation, individual commuting trips are recorded. An individual job accessibility index is developed based on simulated commuting trips. The index is normalized with an expected value of 1.0 and a measurable uncertainty level, which makes it easy to interpret and suitable for cross-regional studies. A case study is conducted in Tucson, Arizona, where about 10,000 transit-dependent worker agents produce more than 600,000 individual commuting trips during morning and afternoon peak hours. Census block, group-level job accessibility shows a random spatial pattern that coincides with a dispersed urban spatial structure of the case study area.     

Combined impacts of highways and light rail transit on residential property values: a spatial hedonic price model for Phoenix,Arizona

This study analyzes the positive and negative relationships between housing prices and proximity to light rail and highways in Phoenix, Arizona. We hypothesize that the accessibility benefits of light rail transit (LRT) and highways accrue at nodes (stations and highway exits specifically), while disamenities emanate from rail and highway links as well as from nodes. Distance decay of amenities and disamenities is captured using multiple distance bands, and hypotheses are tested using a spatial hedonic model using generalized spatial two-stage least-squares estimation. Results show that proximity to transport nodes was associated significantly and positively with single-family detached home values. As a function of distance from highway exits and LRT stations, the distance-band coefficients form an inverted-U pattern consistent with a positive longer-range distance–decay accessibility effect minus a smaller and shorter-range distance–decay disamenity effect. The positive accessibility effect for highway exits extends farther than for LRT stations. Coefficients for the distance from highway and LRT links, however, were not significant. We also test the effect of highway design on home values and find that below-grade highways have relatively positive impacts on nearby houses compared to those at ground level or above.     

Impacts of high-speed rail on the inequality of intercity accessibility: A case study of Liaoning Province,China

The rapid development of Chinese high-speed rail (HSR) not only improves the convenience of daily transportation, but also promotes the regional economy of cities along the HSR lines. Accessibility improvement and spatial inequality reduction caused by HSR would play a positive role in transportation development projects appraisal and help achieve the regional coordinated development. Our purpose is to assess how much improvement of economic potential accessibility can each city get from the HSR based on the existing highway and HSR networks, as well as the changes in spatial disparity and accessibility distribution patterns. Taking Liaoning Province as a case, this paper studies the spatial pattern and inequality of accessibility in two intercity transportation scenarios using a gravity-based model. The sensitivity analysis of the parameter and the test of different mass indicators are also conducted. The results show that cities in the central areas have better accessibility than peripheral areas. Cities in the peripheral areas and near the HSR lines tend to benefit more from HSR. The inequality of accessibility decreases a lot in cities with HSR access but only has a minor reduction on a whole scale.     

The role of transportation accessibility in regional economic resilience

Whereas the importance of transportation for economic growth is widely acknowledged, past studies on the resilience of regions to economic shocks have not given explicit attention to the role of transportation accessibility on building robust regional economies. This exploratory study examines the regional performance in six U.S. states during the last recession (2008–2009) and post-recession (2010–2014) and evaluates its association with the transportation infrastructure. To account for spatial dependence and interactions, a exploratory spatial data analysis (ESDA), a global spatial autoregressive model, and a local Geographically Weighted Regression (GWR) are employed. Results show that, after controlling for other key aspects of resilience, such as industrial diversity and human capital, the global relationships between rail density, access to intermodal services, and access to local and regional markets were positively associated with regional performance (measured as competitive effect) during the recession. Similarly, positive regional performance before the recession period was associated with positive performance during the recession. The local spatial analysis, however, shows that the associations between the explanatory variables and regional performance vary significantly across space. The analysis and results of this study can contribute to a better understanding of the complex interactions between economic resilience and transportation infrastructure, and guide the development of policies and practices designed to strengthen the ability of regions to be resilient to economic shocks.     

Travelling fair: Targeting equitable transit by understanding job location,sectorial concentration,and transit use among low-wage workers

Low-wage workers have a pressing need for adequate and affordable transportation services. However, the growing polycentricity of North American metropolises means transit providers face the difficult task of serving ever more dispersed employment centers. Deciding where limited project resources would provide the most benefit for disadvantaged populations should be a concern for transit planners and elected officials. The purpose of this research is to determine where low-wage employment zones are, where different types of low-wage jobs concentrate, and determine if job type and location have an effect on transit ridership for low-wage workers. We use a previously proposed method to identify low-wage employment zones in the Greater Toronto Hamilton Area, Canada and measure job type concentration using a gravity approach. We then test to see if job type concentration and employment centres relate to ridership, while controlling for other factors that influence mode share. Our results indicate significant differences in transit use for different occupations exist. These results can help guide more transit investment and research by tackling specific occupation's travel needs.     

Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data

Accessibility metrics are gaining momentum in public transportation planning and policy-making. However, critical user experience issues such as crowding discomfort and travel time unreliability are still not considered in those accessibility indicators. This paper aims to apply a methodology to build spatiotemporal crowding data and estimate travel time variability in a congested public transport network to improve accessibility calculations. It relies on using multiple big data sources available in most transit systems such as smart card and automatic vehicle location (AVL) data. São Paulo, Brazil, is used as a case study to show the impact of crowding and travel time variability on accessibility to jobs. Our results evidence a population-weighted average reduction of 56.8% in accessibility to jobs in a regular workday morning peak due to crowding discomfort, as well as reductions of 6.2% due to travel time unreliability and 59.2% when both are combined. The findings of this study can be of invaluable help to public transport planners and policymakers, as they show the importance of including both aspects in accessibility indicators for better decision making. Despite some limitations due to data quality and consistency throughout the study period, the proposed approach offers a new way to leverage big data in public transport to enhance policy decisions.     

Using principles of justice to assess the modal equity of regional transportation plans

While equity has been an important consideration for transportation planning agencies in the U.S. following the passage of Civil Rights Act of 1964 (Title VI specifically) and the subsequent Department of Transportation directives, there is little guidance on how to assess the distribution of benefits generated by transport investment programs. As a result, the distribution of these benefits has received relatively little attention in transportation planning, compared to transport-related burdens. Drawing on philosophies of social justice, we present an equity assessment of the distribution of accessibility in order to define the rate of “access poverty” among the population. We then apply this analysis to regional transportation plan scenarios from the San Francisco Bay Area, focusing on measures of differences between public transit and automobile access. The analysis shows that virtually all neighborhoods suffer from substantial gaps between car and public transport-based accessibility, but that the two proposed transportation investment programs reduce access poverty compared to the “no project” scenario. We also investigate how access and access poverty rates vary by demographic groups and map low-income communities within access impoverished areas, which could be the subject of further focused investments.     

Immigrant settlement patterns,transit accessibility,and transit use

Public transit is immensely important among recent immigrants for enabling daily travel and activity participation. The objectives of this study are to examine whether immigrants settle in areas of high or low transit accessibility and how this affects transit mode share. This is analyzed via a novel comparison of two gateway cities: Sydney, Australia and Toronto, Canada. We find that in both cities, recent immigrants have greater levels of public transit accessibility to jobs, on average, than the overall population, but the geography of immigrant settlement is more suburbanized and less clustered around commuter rail in Toronto than in Sydney. Using logistic regression models with spatial filters, we find significant positive relationships between immigrant settlement patterns and transit mode share for commuting trips, after controlling for transit accessibility and other socio-economic factors, indicating an increased reliance on public transit by recent immigrants. Importantly, via a sensitivity analysis, we find that these effects are greatest in peripheral suburbs and rural areas, indicating that recent immigrants in these areas have more risks of transport-related social exclusion due to reliance on insufficient transit service.