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Measuring the inequality of accessible trams in Melbourne
Journal of Transport Geography 83 (2020) 102657
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Journal of Transport Geography journal homepage: www.elsevier.com/locate/jtrangeo
Measuring the inequality of accessible trams in Melbourne Dinah Jane Lope, Anil Dolgun
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T
School of Science, Mathematical Sciences, Royal Melbourne Institute of Technology, Melbourne, VIC 3001, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: Inequality Gini coefficient Lorenz curve Tram transport Disability Accessibility
In Melbourne, public policy has recently been enacted to improve access to the tram service with an emphasis upon people with a disability. Achieving that objective requires two elements. One is a low-floor tram and two is an elevated tram stop platform that facilitates boarding the tram. Currently the fleet of trams in Melbourne is made up of high-floor and low-floor designs, thus accessible services are unevenly distributed. In addition, construction of new tram stop platforms has been uneven. This suggests a form of inequality in accessible tram services for the disabled. Several studies of transport services have addressed this issue using the Gini coefficient and Lorenz curve calculations as seen in studies of disadvantaged groups such as the elderly. This research utilizes those approaches to estimate the current access of the disabled population to trams services in Melbourne. The approach compares the geography of the total and accessible tram services with the geography of the total and disabled population using the Gini coefficient and Lorenz curve. The results show that there is inequality in the accessible trams amongst people with a disability in Melbourne (Gini = 0.66) as 70% of the disabled population has access to only 22% of the accessible tram supply. In comparison, considering the total tram supply and the entire population, (Gini = 0.48) 70% of the population shares 40% of the tram supply. Hence, at this stage the provision of accessible tram services for people with a disability falls well below that of the general population. These results provide an insight into the current tram service inequality and can be used as a reference for future tram system investment. Further, the approach could be used to increase awareness of this matter and encourage an inclusive and sustainable public transport planning and development in both local and global contexts.
1. Introduction Public Transport Victoria (PTV) and Yarra Trams (the tram service operator) are continuously working to make the transportation system accessible, as expressed in the main priority of the Accessible Public Transport Plan 2013–17 and Accessibility Action Plan 2015–18. The state's action plan also aims to encompass connectivity between modes of transport. These policy documents aim to provide universal access and remove accessibility barriers especially to people with any form of disability, in compliance with the Disability Discrimination Act 1992. In addition, Yarra Tram's Action Plan 2019–2022 continues to address this goal by recognising the different needs of people with a disability as seen in its recent Communication Access Symbol accreditation. Melbourne has an integrated public transport system which includes trains, trams and buses. Over the years, it has made a huge improvement in making all trains and 80% of buses accessible. However, it is facing a significant challenge in improving the accessibility of the tram service. Trams run mainly in Melbourne's central business district and
⁎
inner suburbs whereas buses and trains travel further to the outer suburbs. It provides free travel in the city centre and the iconic City Circle Tram offers free travel to the city's major sights and attractions. Being the largest tram network in the world, the current Melbourne tram network will require extensive infrastructure and upgrades in order to meet transport disability standards (Victoria State Government - Department of Transport, 2013; Public Transport Victoria, 2019; Yarra Trams, 2015, 2019a; Australian Government, 2018; Visit Melbourne, 2019). In 2018, 4.4 (17.7%) million Australians had a disability of which 17% live in Victoria. Over three quarters (76.8%) of this population reported a physical disorder as their main condition, the most common types are musculoskeletal disorders including arthritis and back problems, and approximately one quarter (23.2%) reported a mental or behavioural disorder. Looking at the public transport usage by people with a disability, 4.1 million aged five years or more were identified in the Census and 40.9% record using public transport with no difficulty. However, for
Corresponding author at: School of Science, Mathematical Sciences, Royal Melbourne Institute of Technology, Melbourne, VIC 3001, Australia. E-mail addresses: [email protected] (D.J. Lope), [email protected] (A. Dolgun).
https://doi.org/10.1016/j.jtrangeo.2020.102657 Received 22 August 2019; Received in revised form 19 January 2020; Accepted 21 January 2020 0966-6923/ © 2020 Published by Elsevier Ltd.
Journal of Transport Geography 83 (2020) 102657
D.J. Lope and A. Dolgun
Fig. 1. Two main types of Trams (photo credits: James Morgan, Daniel Bowen)
2. Research context
those who have experienced difficulty in accessing the public transport system their main issue is getting in or out of the vehicle due to the steps (Australian Bureau of Statistics, 2018). Melbourne's trams can be divided into two types, the high-floor (old) and low-floor (new), as shown in Fig. 1. The high-floor trams have stairs making them inaccessible to disabled people with impaired mobility. Meanwhile, low-floor trams are the current and more developed tram infrastructure where the design ensures the entry is level with the tram stop platform. In addition, the low-floor trams have other disability-friendly features such as electronic displays, color-contrasting grab handles, automated announcements and areas allocated for mobility aids such as wheelchairs and scooters. In 2017, approximately 35% of the Melbourne's total tram fleet are low-floor trams. In addition, for a tram to be fully accessible, it requires a specially designed stop platform. There are approximately 400 accessible stop platforms out of 1700 scattered across tram routes in Melbourne (Public Transport Victoria, 2019; Yarra Trams, 2019b). It is likely that the combination of the distribution of persons with a disability, allied to the availability of low ride trams and the location of platform stops suggests there is likely to be some inequity in accessibility for those with impaired mobility. Inequity in transport has been assessed using several transport indices that measure a number of transport-related and socio-related factors (Delbosc and Currie, 2011; Kaplan et al., 2014; Ricciardi et al., 2015; Fransen et al., 2015; Deboosere and El-Geneidy, 2018; Ben-Elia and Benenson, 2019). Some research (Ricciardi et al., 2015), established another factor focusing on facilities for people with varying mobility needs. In the past, disadvantaged groups such as the elderly were taken into account in measuring transport inequity however the question arises, can the person use the transport? The existence of a transport service does not accordingly imply that it is applicable to each person or group. This research aims to fill in this gap in analysis done to date by measuring the inequality of accessible tram services in Melbourne. Equality instead of equity will be used in this research by using a comparison of the tram data in view of the entire population compared to that of a disability population – if normal people have n number of available tram services there should also be an equal number n available tram services to disabled people.
Social exclusion is a multi-dimensional and complex concept which involves denied access to resources, goods and services that is available to the majority. It limits the ability of a person to be a part of a bigger community which affects cohesion and equity in society (Levitas et al., 2007; Lucas, 2012). It is of great interest to the policy makers to review equity in society to discern access deficits and ensure everyone receives the same level of goods and services, especially, disadvantaged groups. Looking at people with a disability, the inaccessibility to areas or services creates inequality when the rest of the population who can readily access the service, which is then a form of social exclusion. Thus, legislation such as the Disability Discrimination Act 1992 is important to be in place to protect the rights of this disadvantaged group and provide guidelines for inclusive planning and future development (Australian Government, 2018).
2.1. Equity in transport In the field of transport, several studies in the past were conducted to explore equity or equality to include transport-related and/or sociorelated factors. Carleton and Porter (2018) compared the concepts of using the term equity and equality, equity as being fair and equality as being equal or sameness. These terms are often interchanged as providing equality and equity in transport analysis and suggested equity can be more achievable, on a case to case basis. Delbosc and Currie (2011) defined two types of equity. However, Ricciardi et al. (2015) in their study on transport equity mentioned an emerging type of equity (number 3 below): 1. Horizontal equity provides equal treatment to everyone in the population, 2. Vertical Equity suggests varying services across income and social class, favouring the less fortunate. 3. Vertical Equity with regards to mobility need and ability suggests equal distribution of services and facilities considering the different mobility needs and abilities of each individual or group. The third concept provides the framework for the analysis that follows. 2
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coeficient of 1 means perfect inequality where all income belongs to 1 person while a Gini coefficient of 0 means perfect equality where every person has exactly the same income (Guo, 2012; Salverda and Checchi, 2015; Farris, 2010). In 1914, Gini discussed in an article the relation of the Gini coefficient to the Lorenz curve (Ceriani and Verme, 2012). Defining the relationship in mathematical terms, the Gini coefficient is the ratio of the areas in the Lorenz curve (see Fig. 3). Suppose A is the area between the line of perfect equality and observed Lorenz and B is the area under the Lorenz curve, then the Gini coefficient (G) is:
2.2. Transport-related factors There are several transport-related factors used to include in measuring transport equity. In a study conducted by Delbosc and Currie (2011), in order to assess the distribution of the overall transport supply which includes bus, tram and train services, the walk-distance catchments around census tracts was included in the calculation of the public transport index. This method of calculation the transport supply was then tested for inequality with the use of the Lorenz curve and Gini coefficient. On the other hand, Kaplan et al. (2014) explored the inclusion of transit connectivity to measure the supply of transport. The result of this study showed that the connectivity level depending on the needs of the area can influence spatial equity. For example, high or good connectivity between populated locations and areas with job and high-education opportunities will stand out compared to those areas lacking that connectivity. These studies provided an insights relevant to evaluating a multi-modal transport system. Fransen et al. (2015) considered time-related factors as part of the transport supply measure such as services during peak/off-peak hours and time interval which identified suburban areas with high public transport gaps and high variance over time due to the time-variability of the transport service supply. On the other hand, Ben-Elia and Benenson (2019) incorporated total travel times to or from destinations by public transport and car to assess the effectiveness of a bus reform. Results of this study identified improvement in long commuting bus trips after the reform took place.
G = A/(A + B )
(1)
and since,
A + B = 0.5
(2)
thus,
G = A/(0.5) = 2A = 1 − 2B,
(3)
where 0 ≤ G ≤ 1. In cases where the Lorenz curve is not entirely known but some values at a given interval, using interpolation techniques, the Gini coefficient can be approximated as n
G=1−
∑ (Yk −1 + Yk )(Xk − Xk −1), k=1
(4)
whereXk is the cumulative proportion of population in increasing order i.e. X1 ≤ X2 ≤ … ≤ Xn); for k = 0, 1…, n, with X0 = 0, Xn = 1 and Yk is the cumulative proportion of income in non-decreasing order i.e. Y1 ≤ Y2 ≤ … ≤ Yn); for k = 0, 1, …, n, with Y0 = 0, Yn=1. The Gini coefficient and the Lorenz curve are used to complement each other in measuring the inequality of a distribution. The Gini coefficient provides an overall single value to represent the inequality while the Lorenz curve provides its corresponding graphical presentation for various quantiles. However, as a limitation of the Gini coefficient is that it is not easily decomposed or added – that is, the total population measure is not equal to the sum of the measure of its subgroups (Shkolnikov et al., 2003; Bellù and Liberati, 2006; United Nations Economic Analysis and Policy Division, 2015).
2.3. Social-related factors Transport equity can also be viewed by taking into account sociodemographic factors such as disadvantaged groups, elderly, low-income, vehicle ownership (Delbosc and Currie, 2011; Ricciardi et al., 2015) as well as accessibility to jobs and metropolitan areas (Deboosere and El-Geneidy, 2018). In Australia, Delbosc and Currie (2011) explored equity in the overall transport system in Melbourne in relation to employment and their results suggested minimal differences in equity between the population and population and employment. Moreover, the overall transport supply was assessed across different age groups, income level and vehicle ownership. Findings showed higher transport supply in inner Melbourne for youth and groups with low income as well as locations with no-vehicle households. Meanwhile, Ricciardi et al. (2015) in Perth explored equity amongst disadvantaged groups such as the elderly residents, low-income households and no-car households in Perth and results suggested that these groups have less equitable transport distribution as compared to the population. In Canada, Deboosere and El-Geneidy (2018) explored accessibility to jobs as well as jobs with low income for vulnerable groups and their findings suggested that in general, some vulnerable groups have a higher transport accessibility than others in their respective cities. These analyses have yet to explore the issues surrounding disability but provide an array of methodologies which have been considered in the approach of this study.
3.2. Gini coefficient and Lorenz curves applied to transport research The Gini coefficient and Lorenz curve are actively used in the field of transport being a robust measure of inequality. To date, continuous and substantial number of studies is recorded applying the measure (Delbosc and Currie, 2011; Kaplan et al., 2014; Ricciardi et al., 2015; Xia et al., 2016; Jang et al., 2017; Ben-Elia and Benenson, 2019). In 2011, Delbosc and Currie (2011) started the application of the Gini coefficient and Lorenz curve in measuring the inequality of Melbourne's overall transport system. This study was followed by an application in Perth by Ricciardi et al. (2015). This study will follow the earlier research and estimate the Gini coefficient and Lorenz curve to measure inequality of access to tram transport in Melbourne. In the approach, people with a disability are ordered according to their access to the accessible trams using the approximated Eq. (4) and graphical representation (see Fig. 4) where Xk is the cumulative proportion of disability population in increasing order i.e. X1 ≤ X2 ≤ … ≤ Xn); for k = 0, 1, …, n, with X0 = 0, Xn = 1 and Yk is the cumulative proportion of the accessible tram services in non-decreasing order i.e. Y1 ≤ Y2 ≤ … ≤ Yn); for k = 0, 1, …, n, with Y0 = 0, Yn=1. The supply of total and accessible trams are computed in relation to the studies of Delbosc and Currie (2011) and Ricciardi et al. (2015) using the following formulas, respectively and are geographically aggregated by two areas, Local Government Area (LGA) and Statistical Area Level 2 (SA2) to match the total and disabled population data:
3. Methodology 3.1. Gini coefficient and Lorenz curve Gini coefficient was first introduced by Italian Statistician Corrado Gini in 1912 in his book ‘Variability and Mutability’ and several formulations and representations existed in the literature over the years (Gini, 1912). Also known as Gini index or Gini ratio, is a popular and widely used summary measure of income inequality providing a single value from 0 to 1 to represent the level of inequality. A low Gini coefficient means a more equal distribution while a high Gini coefficient means a more unequal distribution. In extreme cases, a Gini 3
Journal of Transport Geography 83 (2020) 102657
D.J. Lope and A. Dolgun n
Total Tram Supplyarea =
is defined as people who always need supervision or help to undertake daily activities which most people perform at least daily such as communication, self-care and mobility as a result of a health condition, disability and/or older age. The Census data uses a self-reported approach to determine disability status which is deemed to be appropriate in understanding the geographical distribution of this group (Public Health Information Development Unit, 2017). The total disabled population includes people living in nursing homes with long-term residential accommodation, aged and retired accommodation, psychiatric hospitals and hostels for disabled and geographically aggregated by LGA available for years 2011 and 2016 and SA2 for year 2011.
∑ (SLj) (5)
j=1
and, n
Accessible Tram Supplyarea =
∑ (ASLj j=1
× Accessj ) (6)
where SL is the service level measure (i.e, the number of tram arrivals per week), ASL is the accessible service level measure (i.e., the number of accessible tram arrivals per week), j = 1, 2, …, n is the number of tram stops in the area, and Access is a binary variable (0, 1) denoting the existence of a stop platform.
3.4.2. Tram transport data The tram data is extracted from the Public Transport Victoria (PTV), Yarra Trams and VicSig websites (Public Transport Victoria, 2019; Yarra Trams, 2019c; VicSig Rail Resource, 2019). The timetables for each tram number is scraped from the PTV website. The total tram routes which include the stop ID and stop address for each tram number and accessible stop platforms are scraped from the Yarra Trams website. Meanwhile, the frequency of accessible trams is estimated based on the proportion of allocated low-floor and high-floor trams for each route from the supplying depot according to the Yarra Trams and VigSic websites.
3.3. Other inequality indices In addition to the Gini coefficient, there are several measures of inequality (Eliazar, 2016). Amongst them, the Theil index has an advantage over the Gini coefficient on its decomposition property and it's ability to review the sub-groups relative to each other and to the population where seen as a limitation of Gini. This has provided a good argument and suitability for the index to be applied in the aggregated data of accessible trams of this study. Therefore, this index will also be applied in this study with the following formula and specifications:
T=
1 n
n
∑ i=1
Yi Y ln ⎜⎛ i ⎟⎞, μ ⎝μ⎠
3.4.3. Data processing The population/disability and tram transport data are mainly processed and combined in R software version 3.4.4 using various packages such as rvest, dplyr, magrittr, openxlsx, read.table, tidyr, glue, tidyselect, pdftools, stringr, dineq, ineq, leaflet, htmlwidgets and htmltools. R scripts used to preprocess the data are available upon request from authors. The final data set of the total and disabled population are aggregated by LGA and SA2. However, the tram data is aggregated by locality. Given this, an ASGS coding index from data.gov.au (2019) is extracted in order to match each locality to its appropriate population aggregations in both LGA and SA2. After processing all the data, two main data sets were generated as shown in Table 1 and Table 2 - data set for the total and accessible tram supply and data set for the total and disabled population. This final data is explored in different angles and pairs of variables (disability and tram data) to calculate the inequality indices and plotting the Lorenz curve.
(7)
where Yi is the accessible tram supply per area group, for i = 1, 2, …, n, μ is the average accessible tram supply of the population and 0 ≤ T ≤ ln (n). A Theil index of zero signifies perfect equality and every group has the same proportion of accessible tram supply proportion for the population. On the other hand, a standardised Theil index of one, when Eq. (7) is divided by ln(n), signifies a state of perfect inequality, where one group in the population has all the accessible tram supply. The Index of Dissimilarity (ID), also known as the summation of the Lorenz differences, was used specifically in the area of transport to measure inequality (Rodrigue et al., 2016). Represented by its name, index of dissimilarity is the summation of the vertical deviations from the Lorenz curve from the perfect equality line with the formula: n
ID = 0.5 ∑ ∣Xi − Yi ∣, i=1
(8)
where Xi and Yi are proportions of the elements to their respective total, for i = 1, …, n. Like the Gini coefficient, the closer the value to 1, the higher the dissimilarity from the line of perfect equality. These three indices will be used to measure the inequality of the trams and review the variations between populations and geographical aggregations.
4. Results 4.1. Inequality of Total and accessible Trams Fig. 5 and Table 3 provide the Lorenz curves, Gini coefficient, Theil index and Dissimilarity index for the total and disabled population relative to total and accessible tram services in the year 2016 by LGA.
3.4. Data 3.4.1. Population and disability data The total population and population of people with disability geographically aggregated by Local Government Area (LGA) and Statistical Area 2 (SA2) were obtained via the NCRIS enabled Australian Urban Research Infrastructure Network (AURIN) Portal - a collaborative national network providing clean data sets for government, academic and private sectors sourced over 100 data providers. The disability data was compiled by Torrens University Australia - Public Health Information Development Unit (PHIDU) generated from the Australian Bureau of Statistics Census (Torrens University Australia - Public Health Information Development Unit, 2014b, 2014a, 2018). The data of people with profound or severe disability was developed by the Australian Bureau of Statistics (ABS) five-yearly population Census under the variable Core Activity Need for Assistance. This variable
Table 1 Variable names and descriptions in the tram data set. Variable name
Description
stop_no times tram_no access_times
number of the stop continuous variable containing the number of total tram supply number of the tram continuous variable containing the number of accessible tram supply binary variable (0,1) denoting the existence of stop platform name of the locality name of the Local Government Area (LGA) name of the Statistical Area Level 2 (SA2) the product of access_times and platform variables to denote the real accessible times
platform locality_name lga_name sa_name real_access
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supply map shows a decreasing tram service to the outskirts of Melbourne. However, the larger LGA's have the large populations, as seen in Whittlesea, Boroondara and Whitehorse (see Fig. 7). On the other hand, mapping the accessible tram supply and disabled population side-by-side, the area it is apparent an axis south from Whittlesea, through Darebin, Yarra, Melbourne and Port Philip and passing through the centre has the most number of accessible trams. This pattern in the accessible tram supply is influenced by the routes through the centre. In contrast, Moonee Valley, Maribyrnong (to the west) and Bayside (south) has zero supply of accessible trams (see Fig. 8).
Table 2 Variable names and descriptions in the population data set. Variable name
Description
lga_name sa_name totpop_l16 totpop_l11 disablepop_l16 disablepop_lga11 totpop_s11 disablepop_s11
name of the Local Government Area name of the Statistical Area Level 2 total population by LGA in year 2016 total population by LGA in year 2011 disabled population by LGA in year 2016 disabled population by LGA in year 2011 total population by SA2 in year 2011 disabled population by SA2 in year 2011
5. Discussion
Table 3 Comparison of the total and disabled population inequality indices in year 2016 by LGA.
Total population by LGA 2016 Disabled population by LGA 2016
GC
TI
DI
0.476 0.656
0.404 0.714
0.347 0.650
This research shows varying accessibility to people with a disability as expressed via Gini coefficient and Lorenz curves and two other two inequality indices, Theil and Dissimilarity indices, at two scales, Local Government Area (LGA) and Statistical Area Level 2 (SA2). Insights of this study provides an understanding of the current state of the accessibility of trams especially to those who require this certain type of service, disabled people. The low levels of access that can be seen here provide a foundation for future planning and development as well as a way to monitor the introduction of the low ride trams in coming years. Whittlesea, Darebin, Yarra, Melbourne and Port Philip has the most supply of accessible trams. Unfortunately, the west side of Melbourne which includes Moonee Valley and Maribyrnong and down south of Melbourne and Bayside currently have no access to any accessible tram service. To put the research in context, the overall results have been compared to the Gini coefficients found by Delbosc and Currie (2011) and Ricciardi et al. (2015) as shown in Table 5. The inequality of accessible trams amongst people with a disability in Melbourne (Gini = 0.66, shows 70% of the population shares 22% of the accessible tram supply) is not much different from that found for the overall transport supply in Melbourne (Gini = 0.68, shows 70% of the population shares 19% of the overall transport supply) while different to the situation in Perth (Gini = 0.52, 70% of the population shares 33% of the overall transport supply). Hence, it seems the configuration of the aggregate transport system in Melbourne has a similar effect to that seen with respect to accessible trams even though it is multi modal and serves a larger area. Overall, results show that the supply of accessible trams especially for people with a disability needs further improvement as the share of accessible trams is about half the share of total trams serving the total population. With the government constantly pushing the Disability Discrimination Act 1992 to ensure equal services amongst people with any form of disability, this study has provided an insight on the current accessibility of the tram services for people with a disability across areas in Melbourne and this can be useful for resource planning and development. Given the continuous advancement in accessible infrastructure, the results can be used as a point of reference in comparing
GC: Gini Coefficient, TI: Theil Index, DI: Dissimilarity Index The most recent disability data used in this section is 2016 and the tram service data is 2019.
Comparing the inequality of the total and accessible trams against the total and disabled population groups, respectively, it shows that 70% of the total population shares 40% of the total tram supply with Gini coefficient = 0.48 while 70% of the disabled population shares only 22% of the accessible tram supply with Gini coefficient = 0.66. Accessibility to low floor trams by the disabled is roughly half that of the total tram supply. 4.2. Inequality by LGA and SA2 Fig. 6 and Table 4 provide the Lorenz curves, Gini coefficient, Theil index and Dissimilarity index for the total and disabled population in year 2011 compared by LGA and SA2, respectively. The results for the LGAs replicate those shown above, however for the smaller local areas, the share of supply decreased by 10%. This demonstrates the effect of the different geographical aggregations to the Gini coefficient, Theil index and the Lorenz curves. On the other hand, these different aggregations showed minimal changes to the Dissimilarity index. 4.3. Map of tram supply and population Fig. 7 shows the density map of the total tram supply (left) and total population by LGA while and Fig. 8 shows the density map of the accessible tram supply (left) and disabled population (right) by LGA. The color of the map from light yellow to dark red accordingly denotes low to high number of total/accessible tram supply or low to high number of people/disabled people living in that area. Meanwhile, the gray color stands for LGAs not covered by the tram network. Most of the tram supply is in the centre of Melbourne and its surrounding LGA's, Yarra, Boroondara, Port Philip and Stonnington. The
Table 5 Past and current inequality studies.
Table 4 Comparison of the LGA and SA2 inequality indices of the total and disabled population.
Total population by LGA 2011 Total population by SA2 2011 Disabled population by LGA 2011
GC
TI
DI
0.457 0.467 0.660
0.377 0.468 0.719
0.351 0.315 0.647
GC: Gini Coefficient, TI: Theil Index, DI: Dissimilarity Index The most recent disability data used in this section is 2016 and the tram service data is 2019.
GC
*70%
Total transport supply Total population Melbourne 2011 Total population Perth 2015
0.68 0.52
19% 33%
Tram dupply (only) Total population Melbourne 2019 Disabled population Melbourne 2019
0.48 0.66
40% 22%
Total transport supply The elderly Perth 2015 Low income Perth 2015 No car Perth 2015
0.56 0.54 0.54
29% 30% 31%
GC: Gini Coefficient, *Transport Supply 5
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Fig. 2. Percentage of high-floor and low-floor trams, 2009–2017 (Yarra Trams, 2015).
Fig. 3. Lorenz curve (Guo, 2012).
Fig. 5. Total/disabled population versus total/accessible tram services in year 2016 by LGA. The most recent disability data used in this section is 2016 and the tram service data is 2019.
changes and improvement that will take place in the years to come. Measuring the inequality of Melbourne's accessible tram services amongst people with a disability provides an insight of the standalone supply of transport to this group who requires a specific type of service. The Yarra Trams is committed to provide accessible trams to all as part of the Yarra Trams Accessibility Action Plan 2015–2018 and 2019–2022 in conjunction with Public Transport Victoria's Accessible Public Transport Action Plan 2013–17 (Yarra Trams, 2015, 2019a; Victoria State Government - Department of Transport, 2013). In terms of providing accessibility to all, the plan aims to roll-out more low-floor trams and build more stop platforms across areas in Melbourne. It is suggested to revisit existing tram stops and operating trams in areas with no accessible tram service as either there is no operating low-floor tram and/or stop platform. Fig. 2 shows the percentage of high and low-floor trams from 2009 to 2017 provided by the Yarra Trams (2015). It shows that Yarra Trams has continuously increased the number of low-floor trams since 2009. As this improvement plans to continue in the years to come as shown in Fig. 9, this research provides a point of comparison as the tram service advances to become fully accessible to all. Furthermore, for future research, it would be useful to track the changes in the accessible tram inequality as the
Fig. 4. Lorenz curve: Disabled population versus accessible tram supply.
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Fig. 6. (a) Total Population versus Total Tram Supply compared by LGA and SA2. (b) Disabled Population versus Accessible Tram Supply compared by LGA and SA2. The most recent disability data used in this section is 2016 and the tram service data is 2019.
Fig. 7. Total tram supply versus total population by LGA.
disability within the aim of inclusive and sustainable public transport planning and development not only in Melbourne but around the world.
number of low-floor trams as well as stop platforms increases over time. Looking to further research it may be possible to develop some related measures for other modes of transport in Melbourne (i.e. trains and buses). In terms of methodology this research has shown the usefulness of the application of the Gini coefficient and Lorenz curve in disability studies. These simple yet informative indices can be useful to provide an analysis of the current situation and the progress of policy in a major issue that the society is facing in this day and age. Moreover, the approach could be used to increase awareness on the matter of
Author Statement Dinah Jane Lope: Conceptualization, Methodology, Software, Validation, Formal analysis, Data curation, Writing-Original draft preparation. Anil Dolgun: Conceptualization, Methodology, Supervision, Writing- Reviewing and Editing. 7
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Fig. 8. Accessible tram supply versus disabled population by LGA.
Fig. 9. Distribution plan of high-floor and low-floor trams, 2019–2031 (Yarra Trams, 2019a).
Acknowledgement
Victoria, 2017)
We would like to thank the editor and anonymous reviewers for their inputs which helped us to improve the quality of our paper.
References Australian Bureau of Statistics, 2018. Disability, ageing and carers, Australia: Summary of findings. URL. https://www.abs.gov.au/AUSSTATS/[email protected]/Latestproducts/4430. 0Main%20Features12018?opendocument&tabname=Summary&prodno=4430.0& issue=2018&num=&view= last accessed 05 December 2019. Australian Government, 2018. Disability Discrimination Act 1992. URL. https://www. legislation.gov.au/Details/C2018C00125 last accessed 03 March 2019.
Appendix A Melbourne metropolitan tram network map (Public Transport 8
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Maps/Network-maps/417bb4810a/PTV_Tram-Network-Map_2017.pdf last accessed 05 December 2019. Public Transport Victoria, 2019. Accessible transport. URL. https://ptv.vic.gov. au/getting-around/accessible-transport/ last accessed 03 March 2019. Ricciardi, A.M., Xia, J.C., Currie, G., 2015. Exploring public transport equity between separate disadvantaged cohorts: a case study in Perth, Australia. J. Transp. Geogr. 43, 111–122. Rodrigue, J.P., Comtois, C., Slack, B., 2016. The Geography of Transport Systems. Routledge. Salverda, W., Checchi, D., 2015. Labor market institutions and the dispersion of wage earnings. In: Handbook of Income Distribution. 2. Elsevier, pp. 1535–1727. Shkolnikov, V.M., Andreev, E.M., Begun, A., 2003. Gini coefficient as a life table function: computation from discrete data, decomposition of differences and empirical examples. Demogr. Res. 8, 305–358. Torrens University Australia - Public Health Information Development Unit, 2014a. Lga11 disability 2011. Accessed from AURIN on 03 March 2019. Torrens University Australia - Public Health Information Development Unit, 2014b. Sa2 disability 2011. Accessed from AURIN on 03 March 2019. Torrens University Australia - Public Health Information Development Unit, 2018. Phidu disabilities (lga) 2016. Accessed from AURIN on 03 March 2019. United Nations Economic Analysis and Policy Division, 2015. Inequality measurement development issues no. 2. URL. https://www.un.org/development/desa/ dpad/wp-content/uploads/sites/45/publication/dsp_policy_02.pdf last accessed 03 March 2019. VicSig Rail Resource, 2019. Trams. URL. http://vicsig.net/index.php?page= trams last accessed 16 May 2019. Victoria State Government - Department of Transport, 2013. Accessible public transport action plan 2013–17. URL. https://transport.vic.gov.au/about/ planning/accessible-public-transport-action-plan-2013-17. Visit Melbourne, 2019. Public Transport. URL. https://www.visitmelbourne.com/ information/getting-here-and-around/public-transport. Xia, J.C., Nesbitt, J., Daley, R., Najnin, A., Litman, T., Tiwari, S.P., 2016. Amulti-dimensional view of transport-related social exclusion: A comparative study of greater Perth and Sydney. Transp. Res. A Policy Pract. 94, 205–221. Yarra Trams, 2015. Accessibility Action Plan 2015–18. URL. https://yarratrams. com.au/media/1105/accessibility_action_plan_accessible_pdf.pdf. Yarra Trams, 2019a. Accessibility Action Plan 2019–2022. URL. https://yarratrams.com. au/media/1550/yarra-trams-accessibility-action-plan-2019-to-2022-final.pdf. Yarra Trams, 2019b. Facts Figures. Last accessed 05 December 2019. Yarra Trams, 2019c. Timetables and Routes. URL. https://yarratrams.com.au/ route-guides.
Bellù, L.G., Liberati, P., 2006. Inequality Analysis: The Gini Index. FAO, EASYPol Module, pp. 40. Ben-Elia, E., Benenson, I., 2019. A spatially-explicit method for analyzing the equity of transit commuters’ accessibility. Transp. Res. A Policy Pract. 120, 31–42. Carleton, P.R., Porter, J.D., 2018. A comparative analysis of the challenges in measuring transit equity: definitions, interpretations, and limitations. J. Transp. Geogr. 72, 64–75. Ceriani, L., Verme, P., 2012. The origins of the gini index: Extracts from variabilità e mutabilità (1912) by corrado gini. J. Econ. Inequal. 10, 421–443. data.gov.au, 2019. Asgs coding indexes (2016). URL. https://data.gov.au/dataset/dsdga-1646f764-82ad-4c21-b49c-63480f425a4a/details?q= last accessed 16 May 2019. Deboosere, R., El-Geneidy, A., 2018. Evaluating equity and accessibility to jobs by public transport across Canada. J. Transp. Geogr. 73, 54–63. Delbosc, A., Currie, G., 2011. Using lorenz curves to assess public transport equity. J. Transp. Geogr. 19, 1252–1259. Eliazar, I., 2016. Harnessing inequality. Phys. Rep. 649, 1–29. Farris, F.A., 2010. The gini index and measures of inequality. Am. Math. Mon. 117, 851–864. Fransen, K., Neutens, T., Farber, S., De Maeyer, P., Deruyter, G., Witlox, F., 2015. Identifying public transport gaps using time-dependent accessibility levels. J. Transp. Geogr. 48, 176–187. Gini, C., 1912. Variabilità e mutuabilità. contributo allo studio delle distribuzioni e delle relazioni statistiche. Tipografia di Cuppini. Guo, R., 2012. Understanding the Chinese Economies. Academic Press. Jang, S., An, Y., Yi, C., Lee, S., 2017. Assessing the spatial equity of seoul’s public transportation using the gini coefficient based on its accessibility. Int. J. Urban Sci. 21, 91–107. Kaplan, S., Popoks, D., Prato, C.G., Ceder, A.A., 2014. Using connectivity for measuring equity in transit provision. J. Transp. Geogr. 37, 82–92. Levitas, R., Pantazis, C., Fahmy, E., Gordon, D., Lloyd, E., Patsios, D., 2007. The MultiDimensional Analysis of Social Exclusion, January 2007. Department of Sociology and School for Social Policy, Townsend Centre for the International Study of Poverty, and Bristol Institute for Public Affairs, University of Bristol, Bristol. Lucas, K., 2012. Transport and social exclusion: where are we now? Transp. Policy 20, 105–113. Public Health Information Development Unit, 2017. Social Health Atlas of Australia Notes on the Data (Online). URL. http://phidu.torrens.edu.au/dataarchive/sha-aust/2015-onwards/phidu_data_sources_notes_2017. pdf. Public Transport Victoria, 2017. Maps. URL. https://www.ptv.vic.gov.au/assets/PDFs/
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Contents lists available at ScienceDirect
Journal of Transport Geography journal homepage: www.elsevier.com/locate/jtrangeo
Measuring the inequality of accessible trams in Melbourne Dinah Jane Lope, Anil Dolgun
⁎
T
School of Science, Mathematical Sciences, Royal Melbourne Institute of Technology, Melbourne, VIC 3001, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: Inequality Gini coefficient Lorenz curve Tram transport Disability Accessibility
In Melbourne, public policy has recently been enacted to improve access to the tram service with an emphasis upon people with a disability. Achieving that objective requires two elements. One is a low-floor tram and two is an elevated tram stop platform that facilitates boarding the tram. Currently the fleet of trams in Melbourne is made up of high-floor and low-floor designs, thus accessible services are unevenly distributed. In addition, construction of new tram stop platforms has been uneven. This suggests a form of inequality in accessible tram services for the disabled. Several studies of transport services have addressed this issue using the Gini coefficient and Lorenz curve calculations as seen in studies of disadvantaged groups such as the elderly. This research utilizes those approaches to estimate the current access of the disabled population to trams services in Melbourne. The approach compares the geography of the total and accessible tram services with the geography of the total and disabled population using the Gini coefficient and Lorenz curve. The results show that there is inequality in the accessible trams amongst people with a disability in Melbourne (Gini = 0.66) as 70% of the disabled population has access to only 22% of the accessible tram supply. In comparison, considering the total tram supply and the entire population, (Gini = 0.48) 70% of the population shares 40% of the tram supply. Hence, at this stage the provision of accessible tram services for people with a disability falls well below that of the general population. These results provide an insight into the current tram service inequality and can be used as a reference for future tram system investment. Further, the approach could be used to increase awareness of this matter and encourage an inclusive and sustainable public transport planning and development in both local and global contexts.
1. Introduction Public Transport Victoria (PTV) and Yarra Trams (the tram service operator) are continuously working to make the transportation system accessible, as expressed in the main priority of the Accessible Public Transport Plan 2013–17 and Accessibility Action Plan 2015–18. The state's action plan also aims to encompass connectivity between modes of transport. These policy documents aim to provide universal access and remove accessibility barriers especially to people with any form of disability, in compliance with the Disability Discrimination Act 1992. In addition, Yarra Tram's Action Plan 2019–2022 continues to address this goal by recognising the different needs of people with a disability as seen in its recent Communication Access Symbol accreditation. Melbourne has an integrated public transport system which includes trains, trams and buses. Over the years, it has made a huge improvement in making all trains and 80% of buses accessible. However, it is facing a significant challenge in improving the accessibility of the tram service. Trams run mainly in Melbourne's central business district and
⁎
inner suburbs whereas buses and trains travel further to the outer suburbs. It provides free travel in the city centre and the iconic City Circle Tram offers free travel to the city's major sights and attractions. Being the largest tram network in the world, the current Melbourne tram network will require extensive infrastructure and upgrades in order to meet transport disability standards (Victoria State Government - Department of Transport, 2013; Public Transport Victoria, 2019; Yarra Trams, 2015, 2019a; Australian Government, 2018; Visit Melbourne, 2019). In 2018, 4.4 (17.7%) million Australians had a disability of which 17% live in Victoria. Over three quarters (76.8%) of this population reported a physical disorder as their main condition, the most common types are musculoskeletal disorders including arthritis and back problems, and approximately one quarter (23.2%) reported a mental or behavioural disorder. Looking at the public transport usage by people with a disability, 4.1 million aged five years or more were identified in the Census and 40.9% record using public transport with no difficulty. However, for
Corresponding author at: School of Science, Mathematical Sciences, Royal Melbourne Institute of Technology, Melbourne, VIC 3001, Australia. E-mail addresses: [email protected] (D.J. Lope), [email protected] (A. Dolgun).
https://doi.org/10.1016/j.jtrangeo.2020.102657 Received 22 August 2019; Received in revised form 19 January 2020; Accepted 21 January 2020 0966-6923/ © 2020 Published by Elsevier Ltd.
Journal of Transport Geography 83 (2020) 102657
D.J. Lope and A. Dolgun
Fig. 1. Two main types of Trams (photo credits: James Morgan, Daniel Bowen)
2. Research context
those who have experienced difficulty in accessing the public transport system their main issue is getting in or out of the vehicle due to the steps (Australian Bureau of Statistics, 2018). Melbourne's trams can be divided into two types, the high-floor (old) and low-floor (new), as shown in Fig. 1. The high-floor trams have stairs making them inaccessible to disabled people with impaired mobility. Meanwhile, low-floor trams are the current and more developed tram infrastructure where the design ensures the entry is level with the tram stop platform. In addition, the low-floor trams have other disability-friendly features such as electronic displays, color-contrasting grab handles, automated announcements and areas allocated for mobility aids such as wheelchairs and scooters. In 2017, approximately 35% of the Melbourne's total tram fleet are low-floor trams. In addition, for a tram to be fully accessible, it requires a specially designed stop platform. There are approximately 400 accessible stop platforms out of 1700 scattered across tram routes in Melbourne (Public Transport Victoria, 2019; Yarra Trams, 2019b). It is likely that the combination of the distribution of persons with a disability, allied to the availability of low ride trams and the location of platform stops suggests there is likely to be some inequity in accessibility for those with impaired mobility. Inequity in transport has been assessed using several transport indices that measure a number of transport-related and socio-related factors (Delbosc and Currie, 2011; Kaplan et al., 2014; Ricciardi et al., 2015; Fransen et al., 2015; Deboosere and El-Geneidy, 2018; Ben-Elia and Benenson, 2019). Some research (Ricciardi et al., 2015), established another factor focusing on facilities for people with varying mobility needs. In the past, disadvantaged groups such as the elderly were taken into account in measuring transport inequity however the question arises, can the person use the transport? The existence of a transport service does not accordingly imply that it is applicable to each person or group. This research aims to fill in this gap in analysis done to date by measuring the inequality of accessible tram services in Melbourne. Equality instead of equity will be used in this research by using a comparison of the tram data in view of the entire population compared to that of a disability population – if normal people have n number of available tram services there should also be an equal number n available tram services to disabled people.
Social exclusion is a multi-dimensional and complex concept which involves denied access to resources, goods and services that is available to the majority. It limits the ability of a person to be a part of a bigger community which affects cohesion and equity in society (Levitas et al., 2007; Lucas, 2012). It is of great interest to the policy makers to review equity in society to discern access deficits and ensure everyone receives the same level of goods and services, especially, disadvantaged groups. Looking at people with a disability, the inaccessibility to areas or services creates inequality when the rest of the population who can readily access the service, which is then a form of social exclusion. Thus, legislation such as the Disability Discrimination Act 1992 is important to be in place to protect the rights of this disadvantaged group and provide guidelines for inclusive planning and future development (Australian Government, 2018).
2.1. Equity in transport In the field of transport, several studies in the past were conducted to explore equity or equality to include transport-related and/or sociorelated factors. Carleton and Porter (2018) compared the concepts of using the term equity and equality, equity as being fair and equality as being equal or sameness. These terms are often interchanged as providing equality and equity in transport analysis and suggested equity can be more achievable, on a case to case basis. Delbosc and Currie (2011) defined two types of equity. However, Ricciardi et al. (2015) in their study on transport equity mentioned an emerging type of equity (number 3 below): 1. Horizontal equity provides equal treatment to everyone in the population, 2. Vertical Equity suggests varying services across income and social class, favouring the less fortunate. 3. Vertical Equity with regards to mobility need and ability suggests equal distribution of services and facilities considering the different mobility needs and abilities of each individual or group. The third concept provides the framework for the analysis that follows. 2
Journal of Transport Geography 83 (2020) 102657
D.J. Lope and A. Dolgun
coeficient of 1 means perfect inequality where all income belongs to 1 person while a Gini coefficient of 0 means perfect equality where every person has exactly the same income (Guo, 2012; Salverda and Checchi, 2015; Farris, 2010). In 1914, Gini discussed in an article the relation of the Gini coefficient to the Lorenz curve (Ceriani and Verme, 2012). Defining the relationship in mathematical terms, the Gini coefficient is the ratio of the areas in the Lorenz curve (see Fig. 3). Suppose A is the area between the line of perfect equality and observed Lorenz and B is the area under the Lorenz curve, then the Gini coefficient (G) is:
2.2. Transport-related factors There are several transport-related factors used to include in measuring transport equity. In a study conducted by Delbosc and Currie (2011), in order to assess the distribution of the overall transport supply which includes bus, tram and train services, the walk-distance catchments around census tracts was included in the calculation of the public transport index. This method of calculation the transport supply was then tested for inequality with the use of the Lorenz curve and Gini coefficient. On the other hand, Kaplan et al. (2014) explored the inclusion of transit connectivity to measure the supply of transport. The result of this study showed that the connectivity level depending on the needs of the area can influence spatial equity. For example, high or good connectivity between populated locations and areas with job and high-education opportunities will stand out compared to those areas lacking that connectivity. These studies provided an insights relevant to evaluating a multi-modal transport system. Fransen et al. (2015) considered time-related factors as part of the transport supply measure such as services during peak/off-peak hours and time interval which identified suburban areas with high public transport gaps and high variance over time due to the time-variability of the transport service supply. On the other hand, Ben-Elia and Benenson (2019) incorporated total travel times to or from destinations by public transport and car to assess the effectiveness of a bus reform. Results of this study identified improvement in long commuting bus trips after the reform took place.
G = A/(A + B )
(1)
and since,
A + B = 0.5
(2)
thus,
G = A/(0.5) = 2A = 1 − 2B,
(3)
where 0 ≤ G ≤ 1. In cases where the Lorenz curve is not entirely known but some values at a given interval, using interpolation techniques, the Gini coefficient can be approximated as n
G=1−
∑ (Yk −1 + Yk )(Xk − Xk −1), k=1
(4)
whereXk is the cumulative proportion of population in increasing order i.e. X1 ≤ X2 ≤ … ≤ Xn); for k = 0, 1…, n, with X0 = 0, Xn = 1 and Yk is the cumulative proportion of income in non-decreasing order i.e. Y1 ≤ Y2 ≤ … ≤ Yn); for k = 0, 1, …, n, with Y0 = 0, Yn=1. The Gini coefficient and the Lorenz curve are used to complement each other in measuring the inequality of a distribution. The Gini coefficient provides an overall single value to represent the inequality while the Lorenz curve provides its corresponding graphical presentation for various quantiles. However, as a limitation of the Gini coefficient is that it is not easily decomposed or added – that is, the total population measure is not equal to the sum of the measure of its subgroups (Shkolnikov et al., 2003; Bellù and Liberati, 2006; United Nations Economic Analysis and Policy Division, 2015).
2.3. Social-related factors Transport equity can also be viewed by taking into account sociodemographic factors such as disadvantaged groups, elderly, low-income, vehicle ownership (Delbosc and Currie, 2011; Ricciardi et al., 2015) as well as accessibility to jobs and metropolitan areas (Deboosere and El-Geneidy, 2018). In Australia, Delbosc and Currie (2011) explored equity in the overall transport system in Melbourne in relation to employment and their results suggested minimal differences in equity between the population and population and employment. Moreover, the overall transport supply was assessed across different age groups, income level and vehicle ownership. Findings showed higher transport supply in inner Melbourne for youth and groups with low income as well as locations with no-vehicle households. Meanwhile, Ricciardi et al. (2015) in Perth explored equity amongst disadvantaged groups such as the elderly residents, low-income households and no-car households in Perth and results suggested that these groups have less equitable transport distribution as compared to the population. In Canada, Deboosere and El-Geneidy (2018) explored accessibility to jobs as well as jobs with low income for vulnerable groups and their findings suggested that in general, some vulnerable groups have a higher transport accessibility than others in their respective cities. These analyses have yet to explore the issues surrounding disability but provide an array of methodologies which have been considered in the approach of this study.
3.2. Gini coefficient and Lorenz curves applied to transport research The Gini coefficient and Lorenz curve are actively used in the field of transport being a robust measure of inequality. To date, continuous and substantial number of studies is recorded applying the measure (Delbosc and Currie, 2011; Kaplan et al., 2014; Ricciardi et al., 2015; Xia et al., 2016; Jang et al., 2017; Ben-Elia and Benenson, 2019). In 2011, Delbosc and Currie (2011) started the application of the Gini coefficient and Lorenz curve in measuring the inequality of Melbourne's overall transport system. This study was followed by an application in Perth by Ricciardi et al. (2015). This study will follow the earlier research and estimate the Gini coefficient and Lorenz curve to measure inequality of access to tram transport in Melbourne. In the approach, people with a disability are ordered according to their access to the accessible trams using the approximated Eq. (4) and graphical representation (see Fig. 4) where Xk is the cumulative proportion of disability population in increasing order i.e. X1 ≤ X2 ≤ … ≤ Xn); for k = 0, 1, …, n, with X0 = 0, Xn = 1 and Yk is the cumulative proportion of the accessible tram services in non-decreasing order i.e. Y1 ≤ Y2 ≤ … ≤ Yn); for k = 0, 1, …, n, with Y0 = 0, Yn=1. The supply of total and accessible trams are computed in relation to the studies of Delbosc and Currie (2011) and Ricciardi et al. (2015) using the following formulas, respectively and are geographically aggregated by two areas, Local Government Area (LGA) and Statistical Area Level 2 (SA2) to match the total and disabled population data:
3. Methodology 3.1. Gini coefficient and Lorenz curve Gini coefficient was first introduced by Italian Statistician Corrado Gini in 1912 in his book ‘Variability and Mutability’ and several formulations and representations existed in the literature over the years (Gini, 1912). Also known as Gini index or Gini ratio, is a popular and widely used summary measure of income inequality providing a single value from 0 to 1 to represent the level of inequality. A low Gini coefficient means a more equal distribution while a high Gini coefficient means a more unequal distribution. In extreme cases, a Gini 3
Journal of Transport Geography 83 (2020) 102657
D.J. Lope and A. Dolgun n
Total Tram Supplyarea =
is defined as people who always need supervision or help to undertake daily activities which most people perform at least daily such as communication, self-care and mobility as a result of a health condition, disability and/or older age. The Census data uses a self-reported approach to determine disability status which is deemed to be appropriate in understanding the geographical distribution of this group (Public Health Information Development Unit, 2017). The total disabled population includes people living in nursing homes with long-term residential accommodation, aged and retired accommodation, psychiatric hospitals and hostels for disabled and geographically aggregated by LGA available for years 2011 and 2016 and SA2 for year 2011.
∑ (SLj) (5)
j=1
and, n
Accessible Tram Supplyarea =
∑ (ASLj j=1
× Accessj ) (6)
where SL is the service level measure (i.e, the number of tram arrivals per week), ASL is the accessible service level measure (i.e., the number of accessible tram arrivals per week), j = 1, 2, …, n is the number of tram stops in the area, and Access is a binary variable (0, 1) denoting the existence of a stop platform.
3.4.2. Tram transport data The tram data is extracted from the Public Transport Victoria (PTV), Yarra Trams and VicSig websites (Public Transport Victoria, 2019; Yarra Trams, 2019c; VicSig Rail Resource, 2019). The timetables for each tram number is scraped from the PTV website. The total tram routes which include the stop ID and stop address for each tram number and accessible stop platforms are scraped from the Yarra Trams website. Meanwhile, the frequency of accessible trams is estimated based on the proportion of allocated low-floor and high-floor trams for each route from the supplying depot according to the Yarra Trams and VigSic websites.
3.3. Other inequality indices In addition to the Gini coefficient, there are several measures of inequality (Eliazar, 2016). Amongst them, the Theil index has an advantage over the Gini coefficient on its decomposition property and it's ability to review the sub-groups relative to each other and to the population where seen as a limitation of Gini. This has provided a good argument and suitability for the index to be applied in the aggregated data of accessible trams of this study. Therefore, this index will also be applied in this study with the following formula and specifications:
T=
1 n
n
∑ i=1
Yi Y ln ⎜⎛ i ⎟⎞, μ ⎝μ⎠
3.4.3. Data processing The population/disability and tram transport data are mainly processed and combined in R software version 3.4.4 using various packages such as rvest, dplyr, magrittr, openxlsx, read.table, tidyr, glue, tidyselect, pdftools, stringr, dineq, ineq, leaflet, htmlwidgets and htmltools. R scripts used to preprocess the data are available upon request from authors. The final data set of the total and disabled population are aggregated by LGA and SA2. However, the tram data is aggregated by locality. Given this, an ASGS coding index from data.gov.au (2019) is extracted in order to match each locality to its appropriate population aggregations in both LGA and SA2. After processing all the data, two main data sets were generated as shown in Table 1 and Table 2 - data set for the total and accessible tram supply and data set for the total and disabled population. This final data is explored in different angles and pairs of variables (disability and tram data) to calculate the inequality indices and plotting the Lorenz curve.
(7)
where Yi is the accessible tram supply per area group, for i = 1, 2, …, n, μ is the average accessible tram supply of the population and 0 ≤ T ≤ ln (n). A Theil index of zero signifies perfect equality and every group has the same proportion of accessible tram supply proportion for the population. On the other hand, a standardised Theil index of one, when Eq. (7) is divided by ln(n), signifies a state of perfect inequality, where one group in the population has all the accessible tram supply. The Index of Dissimilarity (ID), also known as the summation of the Lorenz differences, was used specifically in the area of transport to measure inequality (Rodrigue et al., 2016). Represented by its name, index of dissimilarity is the summation of the vertical deviations from the Lorenz curve from the perfect equality line with the formula: n
ID = 0.5 ∑ ∣Xi − Yi ∣, i=1
(8)
where Xi and Yi are proportions of the elements to their respective total, for i = 1, …, n. Like the Gini coefficient, the closer the value to 1, the higher the dissimilarity from the line of perfect equality. These three indices will be used to measure the inequality of the trams and review the variations between populations and geographical aggregations.
4. Results 4.1. Inequality of Total and accessible Trams Fig. 5 and Table 3 provide the Lorenz curves, Gini coefficient, Theil index and Dissimilarity index for the total and disabled population relative to total and accessible tram services in the year 2016 by LGA.
3.4. Data 3.4.1. Population and disability data The total population and population of people with disability geographically aggregated by Local Government Area (LGA) and Statistical Area 2 (SA2) were obtained via the NCRIS enabled Australian Urban Research Infrastructure Network (AURIN) Portal - a collaborative national network providing clean data sets for government, academic and private sectors sourced over 100 data providers. The disability data was compiled by Torrens University Australia - Public Health Information Development Unit (PHIDU) generated from the Australian Bureau of Statistics Census (Torrens University Australia - Public Health Information Development Unit, 2014b, 2014a, 2018). The data of people with profound or severe disability was developed by the Australian Bureau of Statistics (ABS) five-yearly population Census under the variable Core Activity Need for Assistance. This variable
Table 1 Variable names and descriptions in the tram data set. Variable name
Description
stop_no times tram_no access_times
number of the stop continuous variable containing the number of total tram supply number of the tram continuous variable containing the number of accessible tram supply binary variable (0,1) denoting the existence of stop platform name of the locality name of the Local Government Area (LGA) name of the Statistical Area Level 2 (SA2) the product of access_times and platform variables to denote the real accessible times
platform locality_name lga_name sa_name real_access
4
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D.J. Lope and A. Dolgun
supply map shows a decreasing tram service to the outskirts of Melbourne. However, the larger LGA's have the large populations, as seen in Whittlesea, Boroondara and Whitehorse (see Fig. 7). On the other hand, mapping the accessible tram supply and disabled population side-by-side, the area it is apparent an axis south from Whittlesea, through Darebin, Yarra, Melbourne and Port Philip and passing through the centre has the most number of accessible trams. This pattern in the accessible tram supply is influenced by the routes through the centre. In contrast, Moonee Valley, Maribyrnong (to the west) and Bayside (south) has zero supply of accessible trams (see Fig. 8).
Table 2 Variable names and descriptions in the population data set. Variable name
Description
lga_name sa_name totpop_l16 totpop_l11 disablepop_l16 disablepop_lga11 totpop_s11 disablepop_s11
name of the Local Government Area name of the Statistical Area Level 2 total population by LGA in year 2016 total population by LGA in year 2011 disabled population by LGA in year 2016 disabled population by LGA in year 2011 total population by SA2 in year 2011 disabled population by SA2 in year 2011
5. Discussion
Table 3 Comparison of the total and disabled population inequality indices in year 2016 by LGA.
Total population by LGA 2016 Disabled population by LGA 2016
GC
TI
DI
0.476 0.656
0.404 0.714
0.347 0.650
This research shows varying accessibility to people with a disability as expressed via Gini coefficient and Lorenz curves and two other two inequality indices, Theil and Dissimilarity indices, at two scales, Local Government Area (LGA) and Statistical Area Level 2 (SA2). Insights of this study provides an understanding of the current state of the accessibility of trams especially to those who require this certain type of service, disabled people. The low levels of access that can be seen here provide a foundation for future planning and development as well as a way to monitor the introduction of the low ride trams in coming years. Whittlesea, Darebin, Yarra, Melbourne and Port Philip has the most supply of accessible trams. Unfortunately, the west side of Melbourne which includes Moonee Valley and Maribyrnong and down south of Melbourne and Bayside currently have no access to any accessible tram service. To put the research in context, the overall results have been compared to the Gini coefficients found by Delbosc and Currie (2011) and Ricciardi et al. (2015) as shown in Table 5. The inequality of accessible trams amongst people with a disability in Melbourne (Gini = 0.66, shows 70% of the population shares 22% of the accessible tram supply) is not much different from that found for the overall transport supply in Melbourne (Gini = 0.68, shows 70% of the population shares 19% of the overall transport supply) while different to the situation in Perth (Gini = 0.52, 70% of the population shares 33% of the overall transport supply). Hence, it seems the configuration of the aggregate transport system in Melbourne has a similar effect to that seen with respect to accessible trams even though it is multi modal and serves a larger area. Overall, results show that the supply of accessible trams especially for people with a disability needs further improvement as the share of accessible trams is about half the share of total trams serving the total population. With the government constantly pushing the Disability Discrimination Act 1992 to ensure equal services amongst people with any form of disability, this study has provided an insight on the current accessibility of the tram services for people with a disability across areas in Melbourne and this can be useful for resource planning and development. Given the continuous advancement in accessible infrastructure, the results can be used as a point of reference in comparing
GC: Gini Coefficient, TI: Theil Index, DI: Dissimilarity Index The most recent disability data used in this section is 2016 and the tram service data is 2019.
Comparing the inequality of the total and accessible trams against the total and disabled population groups, respectively, it shows that 70% of the total population shares 40% of the total tram supply with Gini coefficient = 0.48 while 70% of the disabled population shares only 22% of the accessible tram supply with Gini coefficient = 0.66. Accessibility to low floor trams by the disabled is roughly half that of the total tram supply. 4.2. Inequality by LGA and SA2 Fig. 6 and Table 4 provide the Lorenz curves, Gini coefficient, Theil index and Dissimilarity index for the total and disabled population in year 2011 compared by LGA and SA2, respectively. The results for the LGAs replicate those shown above, however for the smaller local areas, the share of supply decreased by 10%. This demonstrates the effect of the different geographical aggregations to the Gini coefficient, Theil index and the Lorenz curves. On the other hand, these different aggregations showed minimal changes to the Dissimilarity index. 4.3. Map of tram supply and population Fig. 7 shows the density map of the total tram supply (left) and total population by LGA while and Fig. 8 shows the density map of the accessible tram supply (left) and disabled population (right) by LGA. The color of the map from light yellow to dark red accordingly denotes low to high number of total/accessible tram supply or low to high number of people/disabled people living in that area. Meanwhile, the gray color stands for LGAs not covered by the tram network. Most of the tram supply is in the centre of Melbourne and its surrounding LGA's, Yarra, Boroondara, Port Philip and Stonnington. The
Table 5 Past and current inequality studies.
Table 4 Comparison of the LGA and SA2 inequality indices of the total and disabled population.
Total population by LGA 2011 Total population by SA2 2011 Disabled population by LGA 2011
GC
TI
DI
0.457 0.467 0.660
0.377 0.468 0.719
0.351 0.315 0.647
GC: Gini Coefficient, TI: Theil Index, DI: Dissimilarity Index The most recent disability data used in this section is 2016 and the tram service data is 2019.
GC
*70%
Total transport supply Total population Melbourne 2011 Total population Perth 2015
0.68 0.52
19% 33%
Tram dupply (only) Total population Melbourne 2019 Disabled population Melbourne 2019
0.48 0.66
40% 22%
Total transport supply The elderly Perth 2015 Low income Perth 2015 No car Perth 2015
0.56 0.54 0.54
29% 30% 31%
GC: Gini Coefficient, *Transport Supply 5
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Fig. 2. Percentage of high-floor and low-floor trams, 2009–2017 (Yarra Trams, 2015).
Fig. 3. Lorenz curve (Guo, 2012).
Fig. 5. Total/disabled population versus total/accessible tram services in year 2016 by LGA. The most recent disability data used in this section is 2016 and the tram service data is 2019.
changes and improvement that will take place in the years to come. Measuring the inequality of Melbourne's accessible tram services amongst people with a disability provides an insight of the standalone supply of transport to this group who requires a specific type of service. The Yarra Trams is committed to provide accessible trams to all as part of the Yarra Trams Accessibility Action Plan 2015–2018 and 2019–2022 in conjunction with Public Transport Victoria's Accessible Public Transport Action Plan 2013–17 (Yarra Trams, 2015, 2019a; Victoria State Government - Department of Transport, 2013). In terms of providing accessibility to all, the plan aims to roll-out more low-floor trams and build more stop platforms across areas in Melbourne. It is suggested to revisit existing tram stops and operating trams in areas with no accessible tram service as either there is no operating low-floor tram and/or stop platform. Fig. 2 shows the percentage of high and low-floor trams from 2009 to 2017 provided by the Yarra Trams (2015). It shows that Yarra Trams has continuously increased the number of low-floor trams since 2009. As this improvement plans to continue in the years to come as shown in Fig. 9, this research provides a point of comparison as the tram service advances to become fully accessible to all. Furthermore, for future research, it would be useful to track the changes in the accessible tram inequality as the
Fig. 4. Lorenz curve: Disabled population versus accessible tram supply.
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Journal of Transport Geography 83 (2020) 102657
D.J. Lope and A. Dolgun
Fig. 6. (a) Total Population versus Total Tram Supply compared by LGA and SA2. (b) Disabled Population versus Accessible Tram Supply compared by LGA and SA2. The most recent disability data used in this section is 2016 and the tram service data is 2019.
Fig. 7. Total tram supply versus total population by LGA.
disability within the aim of inclusive and sustainable public transport planning and development not only in Melbourne but around the world.
number of low-floor trams as well as stop platforms increases over time. Looking to further research it may be possible to develop some related measures for other modes of transport in Melbourne (i.e. trains and buses). In terms of methodology this research has shown the usefulness of the application of the Gini coefficient and Lorenz curve in disability studies. These simple yet informative indices can be useful to provide an analysis of the current situation and the progress of policy in a major issue that the society is facing in this day and age. Moreover, the approach could be used to increase awareness on the matter of
Author Statement Dinah Jane Lope: Conceptualization, Methodology, Software, Validation, Formal analysis, Data curation, Writing-Original draft preparation. Anil Dolgun: Conceptualization, Methodology, Supervision, Writing- Reviewing and Editing. 7
Journal of Transport Geography 83 (2020) 102657
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Fig. 8. Accessible tram supply versus disabled population by LGA.
Fig. 9. Distribution plan of high-floor and low-floor trams, 2019–2031 (Yarra Trams, 2019a).
Acknowledgement
Victoria, 2017)
We would like to thank the editor and anonymous reviewers for their inputs which helped us to improve the quality of our paper.
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Appendix A Melbourne metropolitan tram network map (Public Transport 8
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