Making accessibility work in practice

Accessibility, the ease of reaching destination, is the most comprehensive land use and transport systems performance measure (Levinson & Wu, 2020; Wachs & Kumagai, 1973; Wu & Levinson, 2020). Accessibility has been applied in planning research since the 1950s (Hansen, 1959), and still today, we find major barriers to adopting it in practice (Handy, 2020). Advances in computing and software have enabled researchers to generate complex measures of accessibility with higher spatial and temporal resolutions moving accessibility research at a fast pace, while the implementation of accessibility, in practice, lags (Boisjoly & El-Geneidy, 2017). Even simple measures, such as the cumulative opportunities measures of accessibility, confront challenges in adoption.

As land-use and transport professors, we use cumulative opportunities measures to introduce the accessibility concept to students, and we teach them the elevator pitch for introducing it to decision-makers. If you are a public transport planner applying a new network design or want to highlight disparities in the existing system, showing the decision-maker the number of jobs that can be reached within 30 min of travel time by public transport can be your way to communicate your solution or highlight the problem. We found this pitch to be effective in many cases when linking accessibility concepts to future practitioners and decision-makers. For other problems, explaining dual access, for example, how many minutes it takes to reach a given opportunity (e.g. a hospital) or a set of opportunities (the three nearest grocery stores), may be more useful (Cui & Levinson, 2020b).

The widespread idea of the 15- (or 5-, or 10-, or 20-, or 30-) Minute City over the past few years is a clear indication of how easy it is to grasp the idea of cumulative opportunities measure, in this case for active travel as the main mode. Accessibility is a mode-specific measure generated for public transport, automobile, walk or bike to a specific set of destinations (opportunities), such as jobs or hospitals. The practitioner has one of two ways to solve the lack of accessibility using a specific mode, either change the land use in the area, allowing more of these destinations to be located nearby, or change the transport system, reducing travel time to these destinations.

The concept of accessibility is easy to grasp with cumulative opportunities measures (Geurs & van Wee, 2004). Critiquing this measure by showing that a 30-minute travel time is an arbitrary selection that ignores the jobs at 31 min is a good path to introduce gravity-based measures. Gravity-based measures discount the opportunities by distance or travel time, making the farther away jobs less attractive, as people are less willing to travel long distances. The gravity model generates the effective number of opportunities as if they were at the doorstep. But this discounted number of jobs that can be reached from a location may be hard for some decision-makers to comprehend, as it requires more maths.

Starting with access to jobs using a single mode is always a first step in explaining accessibility, followed by explaining other destinations to future practitioners, like accessibility to hospital beds. This helps in introducing competition measures. Having access to 200 hospital beds within 30 min of travel time by automobile in a region with 200,000 residents versus a region with 2,000,000 residents is a good example to introduce the competition measures of accessibility. Even decision-makers can usually grasp the scarcity of the resources relative to the number of people who need it.

At the aggregate, accessibility can be used easily as a planning tool, showing the improvement in accessibility due to a new project (Manaugh & El-Geneidy, 2012b) or the disparities of the distribution of access to low wage jobs in a region in a cross-sectional or a longitudinal approach (Foth, El-Geneidy, & Manaugh, 2014). Difference (change) maps are widely used in research for these purposes. Despite the power of maps in showing the impacts of a project or land-use change at the regional scale, some observers might still have a hard time in understanding why we should aim at improving access to jobs. For example, some people state that everyone requires just one job, assuming this job pays well, so why should a public transport planning authority aim at improving access to jobs by public transport. The response to this question lies in the hands of researchers who should work harder in highlighting the benefits of planning for accessibility to achieve a goal that the agency has in mind. While some research relates accessibility to various outcomes, such research needs to be developed further to provide stronger evidence on the impacts of improving accessibility. In our previous research with colleagues, we have shown that improving accessibility by public transport in a region will lead to increase in public transport use at various scales (stop, route, census tract and system levels) (Cui, Boisjoly, Miranda-Moreno, & El-Geneidy, 2020; Diab, DeWeese, Chaloux, & El-Geneidy, 2020; Owen & Levinson, 2015; Wu, Levinson, & Owen, 2021b).

A public transport authority, targeting an increase in ridership through a new network design, can use accessibility as a tool to evaluate if the new network will lead to improvements in accessibility in different areas and link that to the population to measure expected ridership from such improvements. Another positive outcome of planning for accessibility is its impacts on reducing vehicle kilometre travelled (VKT) or vehicle miles travelled (VMT) by individuals (DeWeese & El-Geneidy, 2020) depending upon where you are around the world. Many municipalities and transport authorities around the world are working towards reducing VKT/VMT to reduce emissions and the time spent on travel. Linking accessibility to major outcome goals that planning authorities are trying to achieve is, in our opinion, one of the tools researchers can use to accelerate the adoption of accessibility measures in practice. Travel time is, of course, only one of many costs public agencies (and individuals) incur, and monetary costs, as well as externalities, can all be considered in a full-cost accessibility approach (Cui & Levinson, 2018), particularly important for evaluating investments across modes. The monetary costs in addition to time are especially important in evaluating equity, so linking accessibility to a monetary value can be one of the future directions of research (Conway & Stewart, 2019; El-Geneidy et al., 2016).

Accessibility to jobs has always been the most common measure due to the ease of obtaining the number of jobs in an area; in some developing countries, researchers measure accessibility to formal and informal jobs. It is especially useful for benchmarking, comparing the transport-land use system over time and between places (Wu, Avner, et al., 2021a). Our research found that accessibility by public transport to formal jobs leads to a decline in the number of people employed in the informal job sector (Boisjoly, Moreno-Monroy, & El-Geneidy, 2017). Accessibility can also impact income and productivity in a region; some of our previous work has shown the impacts of accessibility on development (Deboosere, Levinson, & El-Geneidy, 2018; Melo, Graham, Levinson, & Aarabi, 2017).

Areas experiencing an increase in accessibility reduced income gaps over time faster. Accessibility to jobs is a proxy to accessibility to services. As a highly skilled individual, I do have a job, and there are a limited number of jobs that can fit my skills in a region, so accessibility to other jobs in the region should not matter to me from an employment standpoint, yet it matters to me from a services standpoint. The more jobs I have around my home, the more services I have, and the less travel I need to make to access these services, so accessibility to jobs proxies for the different opportunities that are serving me leads to a decline in my overall travel (Manaugh & El-Geneidy, 2012a). Considering multiple types of opportunities together is a new avenue for research worth exploring in the future (Cui & Levinson, 2020a). Also, communicating the meaning of accessibility to different groups in a region is another area where research needs to be developed more (Ryan & Pereira, 2021) to provide practitioners with the adequate accessibility measurement tools that reflect the population needs and desires.

One of the interesting impacts of accessibility is its impact on home sales. In one of our first studies on accessibility, we ran a hedonic regression model to measure the impacts of accessibility on home sales and found a statistically significant positive relation between accessibility to jobs and home value and a statistically significant negative association with accessibility to workers, meaning that people want to access opportunities and are willing to pay more for that. Such willingness to pay declines as more people are present around you, showing the importance of competition measures of accessibility (El-Geneidy & Levinson, 2006). Accessibility has been a major factor in the choice of public investments, even before it was formally quantified (Levinson, 2008). Finally, accessibility is an attractor for development; areas experiencing improvement in accessibility over time would generally experience new developments to capitalise on such improvement (Levinson, Giacomin, & Badsey-Ellis, 2016).

There are plenty of planning goals, including accessibility in some cases (Boisjoly & El-Geneidy, 2016), so our job as land use and transport researchers is to work on connecting these goals to various accessibility measures to provide practitioners who want to adopt these measures with the support needed to use such measures in planning practice. At the same time, researchers should keep moving on, improving the existing measures and providing easy-to-use and open-access tools to enable the wide adoption of accessibility for planning for various modes of transport.

We consider our own research as a step towards the implementation of accessibility in practice, but our personal interaction with practice tells us clearly that more must be done to solidify the evidence of the impacts of accessibility towards various planning goals. We promote the use of simple measures like cumulative opportunities, due to the simplicity of explaining them (Committee of the Transport Access Manual, 2020), and the strong correlation that we found with complicated ones (El-Geneidy & Levinson, 2006). That does not discount the utility of other, more complex, measures that are built based on travel behaviour theories while remaining consistent with the accessibility theory (Levinson & Wu, 2020), but this is a call for researchers to explain these measures in a way that makes them easily adoptable in practice and to work more on highlighting the added value from such complexity.

Acknowledgement

Over the past 15 years, the authors have collaborated with various researchers in the accessibility field. If it were not for these interactions and the funding they received from various agencies, they would not be able to write this editorial today. The authors would like to thank all our co-authors and collaborators as well as the funding agencies that funded our accessibility research.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.