car parking | Charting Transport

Who drives to work in Australia’s CBDs?

Wed 9 April, 2025

Central Business District (CBD) generally have expensive car parking, congested radial roads, and public transport that is usually frequent, direct, and often fast. CBDs in larger cities are naturally strong markets for public transport.

Yet around three hundred thousand Australians drove to work in CBDs of Australian cities in 2016. Who are these people, and why might they have chosen to drive? And could they be enticed away from private transport?

I’ve touched on these topics a little in the past (see: The journey to work and the city centre (Australian cities 2001-2011), What can the 2021 census tell us about commuting to work in Australia’s big CBDs during the COVID19 pandemic?), but some recent social media discourse, an increase in the Melbourne central area parking levy, and the introduction of congestion pricing in New York has inspired me to tackle this question afresh and dig a bit deeper.

This post explores the factors of distance from rapid transit, income, occupation, public v private sector, hours worked, age, gender, parenting status, and distance from work.

Short on time? Just want the answers? Skip to the summary of findings.

About the data

I am focussing on mostly 2016 census data, as the 2021 census was heavily impacted by the COVID19 pandemic, with Sydney and Melbourne in lockdown on census day. Of course, travel behaviour in 2025 will be a bit different to 2016, however I would expect a lot of the mode choice fundamentals to be very similar for people making trips to CBDs (some might just be commuting fewer days per week).

I’ve looked at CBDs in all Australian cities with a population of 100,000+ (except the Sunshine Coast and Gold Coast that lack a clear central CBD). Furthermore, I’ve included some of the larger suburban employment clusters in Sydney that look and feel like CBDs (something quite unique to Sydney – see Suburban employment clusters and the journey to work in Australian cities). Private mode shares are very high for the smaller CBDs, so many of the charts in this post will focus on the larger CBDs where differences in private mode shares can be seen against many variables.

For each CBD I’ve chosen Destination Zones (DZs) that represent the core area of employment density – there is usually a high-contrast in density between a central area and its surroundings that enables a logical grouping of DZs. For the larger city CBDs, I’ve used the same areas as this post.

A lot of smaller cities have a major hospital facility close to the CBD, but just beyond the other areas of higher employment densities, and I’ve erred on the side of not including these destination zones, as we already know that hospitals have peculiar mode shares for employees (likely owing to shift work).

My analysis focuses on mostly on private transport mode share – that is people who used one or more modes of private transport (car, truck, motorbike, taxi), and no modes of public transport (train, tram, bus, ferry). Most – but not all – of these people drove a vehicle, but I’m going to use “driving” as a shorthand for headings in this post.

I don’t have access to unit-record census data, so I cannot easily apply regression-style models to determine factors for individual mode choice. Instead I’ll separately examine the relationship between mode share and various combinations of personal variables (as I often do on this blog).

Did commuters drive because they lived far from rapid transit?

I think of rapid transit as transit services where vehicles move at decent speed on a direct path along their own right of way with no delays from other traffic. This includes train lines, metros, busways, and potentially light rail (however most light railways in Australian cities are not completely separated from regular road traffic).

If people don’t have rapid transit close to their home, you’d expect private transport to be a more attractive option for commuting to CBDs.

The following chart shows the private transport mode share of journeys to major city CBDs by home distance from a train or busway station:

Probably unsurprisingly, people living further from a rapid transit station were generally slightly more likely to use private transport to get to work, as public transport was probably less convenient (they would need to use a feeder bus, bicycle, or car to reach a station, or use slower on-street buses or trams all the way).

Perth private mode shares flatlined (on average) for distances of 2+ km from a station, suggesting Perth still has relatively attractive CBD public transport options for these areas (which includes both high frequency feeder bus services and direct to CBD bus services). However at the same time, Melbourne had lower CBD private transport mode shares than Perth at all distances from train stations.

However the differences in mode share between the cities were often as significant as the differences by station proximity for any one city.

A full 40% of Adelaide CBD commuters who lived within 1 km of a train station used private transport to get to work (probably not helped by the non-central location of Adelaide Train Station).

BUT, if you look at the distribution of commuter home locations by distance from train stations you get a different picture.

In Melbourne and Sydney almost half of CBD commuters lived within 1 km of a train or busway station, and they certainly had a lower private transport mode share. But still, 35% of Melbourne CBD private commuters, and 28% of Sydney CBD private transport commuters lived within 1 km of a train or busway station. That is, despite having good access to high quality public transport they choose private transport.

There must be another reason why these people chose private transport. It might be related to service quality (crowding was a significant issue on Melbourne’s train network in 2016), or it might be something else. I can only easily investigate this in terms of demographic variables so lets get into that.

Did commuters drive because they were on higher incomes?

Here’s the private transport mode share of commuters by personal weekly income for all of the CBDs:

This chart shows a very clear trend – that private transport mode share peaked for people in the highest income bracket in most CBDs (especially large CBDs and suburban Sydney CBDs). No doubt this includes many executives who aren’t fussed by – or don’t themselves pay – parking costs (and possibly also car operating costs). I’ve shown before there’s generally a strong relationship between mode split and paid parking, but these people at the top income band were probably not being influenced much by price signals.

In fact, I recently spoke to an executive who was considering opting for a work car. He said that on an out-of-pocket basis it was cheaper for him to drive to work in his CBD than to use public transport!

Back to the chart.. If you ignore the top income band, for the larger CBDs private transport mode share was low and only rose slowly with income. The Sydney regional centres of North Sydney and Chatswood seem to show the strongest relationship between increasing income and increasing private mode share.

But what if we look at the volumes of commuters by income? The next chart shows the income distribution of private transport commuters, together with all commuters for reference (highest incomes on the left):

This chart shows that private commuter trips heavily skewed towards the highest income bands. Almost 37% of people who used private transport to the Sydney CBD had a weekly income in the top band ($3000+), yet that income band only accounted for 20% of overall commuters.

So it’s pretty clear that income had a strong relationship with private transport mode share, with commuters on high income more likely to drive and being disproportionately represented in general traffic and car parks. Having said that, a majority of commuters in the top income band still did not use private transport in Sydney, Melbourne, and Perth.

CBD parking levies will therefore disproportionately impact high income commuters (or their employers).

So we have disproportionate representation of high income earners and people living near rapid transit station driving to work. How are these dimensions related?

Did commuters drive because they had a high income, even though they lived close to rapid transit stations?

For this analysis I’ve combined the dimensions of income and proximity to rapid transit. Here is private transport mode share across these two dimensions:

The relationship between income and private transport mode share generally held up at all distances from a rapid transit station, and the relationship between distance from a rapid transit station and private mode share held up across most income bands.

So we know that people on high incomes were over-represented in private transport trips, and they also had relatively higher private transport mode shares even if they were close to rapid transit stations.

So were CBDs filled with the cars of high income commuters who lived close to rapid transit but choose not to use it? The following chart shows these commuters as a proportion of all commuters, and as a proportion of private commuters:

These commuters were certainly over-represented in the private transport volumes, but still didn’t make up a large proportion of the private transport volume.

Did commuters drive because of their occupation?

A common refrain when it comes to mode choice is that some types of workers cannot use public transport because they carry a lot of gear around with them.

Another explanation for high private transport mode share might be people more likely to be working shift work, and therefore needing to travel at times when public transport is less frequent, or perhaps not available at all.

To explore this question, the following chart shows average private transport mode share by occupation (ANZSCO level 1) and income, across Australia’s five largest city CBDs. The line thickness represents the number of commuters with occupation and income range (I’ve excluded low volume data points).

Observations:

Machinery operators and drivers had very high private transport mode share – but there weren’t many of them and those that make the chart were on high incomes. I am guessing many commuted using their work vehicle, or were train drivers who might have registered a CBD station as their place of employment but might not have driven there (in other exploration I’ve found unusually long commute distances for employees in destination zones around Melbourne’s two main train stations).
Community and personal service workers tended to have higher private transport mode shares, particularly those on higher incomes – and I suspect many of these might have worked shifts, and therefore commuted when public transport is less available/attractive.
Labourers, community and personal service workers, technicians and trades, and sales workers had a strong relationship between income and private mode share.
Managers and professionals did not show strong increasing private transport mode share with increasing income, except for the top income band. I suspect these are largely office workers commuting in traditional peak periods where public transport is an attractive and competitive option.
For managers, professionals, and clerical and administrative workers, private transport mode shares were higher for those earning less than $800 per week, than those earning closer to $1000 per week. I suspect many of these people might have been working part-time and/or shift work, where public transport might be less convenient. More on that shortly.
Clerical and administrative workers showed a slightly stronger relationship between income and private transport trends towards higher incomes. I suspect this occupation actually includes a lot of finance professionals but I’m not quite sure why they would have a higher private transport mode share than other professionals (maybe they worked longer hours?).

But how much did each of these occupation categories contribute to total private transport trips to CBDs?

If you study this chart, you’ll see that managers were the most over-represented occupation making up private transport trips, with the starkest difference in North Sydney. Professionals were actually under-represented in private transport trips in all cities, particularly the largest CBDs.

And those machinery operators and drivers who had such high private transport share – made up only a tiny portion of CBD workforces.

So were some types of managers more likely to use private transport than others? Here’s a heatmap table looking at private transport mode share by occupation AND industry of employment:

Some more distinct patterns emerge here. Managers in the construction, mining, rental, hiring and real estate services, manufacturing, and accommodation and food service industries had significantly higher private transport mode shares than managers in other industries. I suspect these could be explained by high salaries (eg mining), shift work (accommodation and food services), and need for a vehicle during the work day (rental, hiring, and real estate).

You can also see some other high private transport mode shares that seem pretty explainable:

47% for public administration and safety / community and personal service workers – which probably includes a lot of police who might have done shift work,
42% for professionals in health care and social assistance – probably including many shift working hospital staff,
57% for sales workers in rental, hiring, and real estate services, who possibly need their car for work and/or are allowed to take company cars home.

So far I’ve been speculating about mode shares for more specific occupation types, but it is possible to drill down the ANZSCO codes to understand things more deeply. First up, here are the average private transport mode shares and commuter volumes for level 2 occupation categories:

The highest private transport mode share was for mobile plant operators, but also there were only 421 such commuters across the five cities. The first large occupation category with a high private transport mode share was Chief Executives, General Managers and Legislators.

So while private transport mode shares do vary by occupation and industry, it seems to boil down to higher private transport mode share for people working shift work, people whose day job involves operating a motor vehicle, and tradies who clearly need to bring specialist equipment, amongst others. However these workers are a fairly small proportion of all CBD workers.

I’ve dug even deeper down to ANZSCO level 4 occupations. The top ten occupations with the highest private transport mode share (minimum 100 commuters) were:

86% automobile drivers (no surprise here, this presumably this includes taxi drivers)
81% bus and coach drivers (but only 165 workers across the five cities)
81% earthmoving plant operators
80% primary school teachers (that was unexpected!)
79% surgeons (likely some shift work)
75% fire and emergency workers (no doubt including many shift workers)
75% truck drivers
74% wall and floor tilers
73% air conditioning and refrigeration mechanics
72% aged and disability carers (many shift workers?)

Working down the list, other occupations of interest (to me) include:

legislators at 67% – sometimes parliament sits until very late at night
registered nurses at 61% – many shift workers no doubt
chief executives and managing directors at 55% – not quite as high as I expected – 46% in Sydney, 52% in Melbourne, and 73+% in the other cities (for interest: public transport mode shares were 45% in Sydney and 37% in Melbourne)
train and tram drivers at 48% – but much higher in Perth, Brisbane, and Adelaide (only 42% in Melbourne and 23% in Sydney)
police at 47% – likely many shift workers
software and applications programmers at 8% – at the very bottom of the list

And here’s the top ten occupations (at level 4) that used private transport to get to work, by volume :

5.1% Barristers & Solicitors*
4.5% Accountants and accounting clerks*
3.1% Advertising, public relations and sales managers
2.3% Contract, program and project administrators
2.2% Management and organisation analysts
2.0% ICT managers
1.9% Chief executives and managing directors
1.7% General Clerks
1.7% Real Estate Sales Agents
1.7% General Managers

These ten occupations accounted for 26.7% of all private transport commuter trips to work in CBDs in the five cities in 2016. I would expect many people with these occupations to also be on high incomes.

*I’ve (arbitrary) bundled two similar occupations here.

Were private sector commuters more likely to drive?

While private sector workers had the highest private transport mode share in most of the big cities (except Perth), there are big differences between occupations, so I think it’s worth looking at private mode shares by both occupation and sector of employment:

Local government professionals had the lowest private transport mode share in Sydney, Melbourne, and Brisbane.

The starkest difference between public/private sectors was in the “community and personal service workers” occupation category. I would expect many of the state government workers in this category to be hospital staff and police, many of whom would have been working shift work.

Any approach to congestion pricing in CBD areas might want to give consideration to these essential shift workers, who generally made up around 5% of CBD commuters (on a Tuesday at least, and it will vary by CBD).

Did commuters drive because they worked more hours per week?

The census asks people how many hours they worked in the previous week – which hopefully also generally reflects how many hours they might have worked in the week of the census (there will be some minor exceptions, such as people returning from leave). The following chart shows the relationship between hours worked and private transport mode share across all the CBDs:

For the smaller CBDs there was very high mode private share, no matter what the working hours, so I will focus in the on larger CBDs.

In the larger CBDs:

Private transport mode share was lowest for those reporting 35-39 hours. About a quarter of these were public sector workers – the highest public sector share for any grouping of worked hours.
Private transport mode share had a mini-peak for 25-34 hours, which probably represents many people working part time 3-4 days per week. Perhaps these people were juggling other responsibilities and activities (eg parenting, studying) and decided a car better supported their complex multi-stop travel journeys? We will come back to parenting shortly.
Private transport mode share increased as hours worked increased from 35+ hours, peaking at those working 49+ hours in the week. Perhaps people working very long hours could not afford the extra time to use any other mode, perhaps they commuted outside traditional peak periods (perhaps as shift workers, or just because of very long days in the office), and/or perhaps they were very high income earners (more on this shortly).

One word of caution on this is that some people on higher incomes might not have worked many hours in the week before the census for random reasons (eg they were on leave). When I look at the approximate average income per hour worked of people who worked 1-15 hours, it was much higher than all other hours-worked bands.

Here’s a view of the distribution of commuters (private transport commuters and all commuters) by hours worked in the last week for larger CBDs:

Commuters using private transport absolutely skewed toward people working longer hours (compared to all commuters). In particular a large share of private transport commuters worked 49 hours or more, which I’d suggest is pretty extreme overtime (these people are probably also time-poor so might be prepared to pay a premium for a faster mode of transport).

People working long hours naturally tended to have higher incomes. I’ve roughly estimated the average hourly income for each range of worked hours, and this shows a big step up in hourly income at 40 hours per week, and then another step up for those working 49+ hours per week. People working 40+ hours were also much more likely to be working in the private sector.

However not everyone working long hours was on a high income, so I’m wondering if these variables are strongly co-correlated.

Here’s a chart showing private transport mode share by hours worked and weekly income for the five big city CBDs combined:

The chart suggests that both hours worked and weekly income were relatively independent drivers of mode share. Private transport mode share was higher for people on higher incomes regardless of hours worked. Private transport mode share was lowest for people working 35-39 hours across all income bands, except people on the lowest incomes working limited hours.

There were just under a thousand people working 49+ hours on a relatively low weekly income of $500-$649 who had a 37% private transport mode share across the five big cities. perhaps these people were working multiple jobs and/or shift work. These commuters were probably doing it tough with high transport costs and lower incomes – but thankfully there weren’t many of them.

Were older and/or parenting commuters more likely to drive?

In answering this question I’m going to also throw in the dimension of gender, as these three dimensions have shown up to be quite significant when it comes to mode shares generally in my previous analysis (see: How and why do travel patterns vary by gender and parenting status?).

Technical note: I am talking about gender, but the data reported by ABS is actually based on (binary) sex.

Here’s how private transport CBD commuter mode shares vary across age, gender, and parenting status:

There’s a bit going on here:

For males, there’s generally a strong relationship with private transport mode share increasing with increasing age.
For females, private transport mode share generally increased with age, but sometimes flatlined or declined for females over 50.
Parents generally had higher private transport mode shares, with dads having higher shares than mums in the largest centres, but then curiously mums had higher private shares in the smaller CBDs.
For non-parenting workers, males had higher private transport mode shares in the bigger CBDs, but again this curiously flipped for the smaller CBDs.

Here’s the distribution of CBD commuters by age for private commuters, and all commuters:

Private transport commuters are significantly skewed towards older age bands in most CBDs. Commuters over the age of 40 made up 41% of all Sydney CBD commuters, but accounted for 57% of private transport journeys. Melbourne was similar.

Here’s the distribution of parenting status for private commuters and all commuters:

Parents were slightly over-represented in private transport commuters in most CBDs, but the majority of private commuters were still non-parents.

Here’s the gender distribution (reminder: ABS census data only includes binary sex):

Males were over-represented in private transport commuters, but not always by a large margin.

So are older commuters more likely to drive to work simply because they are more likely to be earning high incomes?

It looks like there was a strong relationship between age and mode choice, regardless of income band.

I suspect the peak in lower income commuters in their 40s might reflect part time parenting commuters. Younger people on higher incomes were much less likely to choose private transport.

This is all similar to previous analysis on public transport mode share in general against these variables (see: Why are young adults more likely to use public transport? (an exploration of mode shares by age – part 4). Older people generally used public transport less often, regardless of income and parenting status.

Did commuters drive because they were a long way from their CBD?

For people who drove to work in CBD, how far did they live from their CBD? And so, will CBD parking levies disproportionately hit people in the inner or outer suburbs?

The next chart shows the distribution of CBD commuter home locations by distance from CBDs for all commuters, and private transport commuters (ABS calculates or estimates the on-road distance between each employee’s home and work location).

For very short journeys driving probably isn’t competitive with walking, so in all cities few private transport commutes were less than 2.5 km.

But if you look at the further distance bands, there’s not a lot of difference between private commuters compared to all commuters. In Melbourne private commuters skew slightly further out, while in Sydney they skew slightly further in. It varies a little by city.

It is also worth noting that CBD commuters don’t tend to live a long way from the CBD, because not many people make life choices that require long distance commutes. Around two-thirds of Sydney and Melbourne CBD commuters lived within 20km of the city.

The following chart show the mode split of people who travelled to work, based on their distance from home to work:

Observations:

Active transport dominates very short trips, especially in the biggest CBDs. Walking is way cheaper than public or private transport, and possibly often faster. Public transport mode share for very short journeys was tiny, except for the Melbourne CBD which is probably explained by the Free Tram Zone in the CBD area making very short tram trips to work free (although a similar effect doesn’t show up for Perth CBD’s Free Transit Zone).
Active transport mode share fades away by 5 km from the CBD, and then it’s a contest between private and public transport. Public transport won the largest share in the biggest CBDs, while private transport dominated for the smaller CBDs.
For distances of more than 5 km, the split between public and private transport shows different patterns in different CBDs.
- For Perth, Wollongong, Geelong, and the Sydney secondary CBDs of North Sydney, Parramatta, Chatswood, St Leonards, and Kogarah, public transport mode share increased with increasing distance. The secondary CBDs in Sydney are all well connected by the train network, and perhaps this is competing well with road tolls for private transport that generally increase with distance travelled. Perth, Wollongong, and Geelong are well connected by rail for many long distance commuters which might influence this pattern (rail being relatively cost and time competitive for longer distance trips).
- For many CBDs the mode split remains fairly flat across distances, except for a spike in private mode share for trips 50-100km in Brisbane, Adelaide, and Parramatta.
- Kogarah keeps showing up with wacky patterns in these charts. Public transport mode share is only strong for trips of 20-50 km, which probably represents many trips where metropolitan train travel is highly time and cost competitive.

This means that there isn’t a clear over-representation of private transport users for shorter or longer distances across the cities (beyond ~5km from CBD). Private transport commuters tend to travel similar distances to public transport commuters.

As something of an aside – another way of looking at this data is the estimated approximate average distance to work (I have to estimate these because journey lengths are reported in bands rather than precise figures). The following chart shows the approximate average distance to work, and the width of the bars is scaled to the relative mode share of each mode. So a skinny line shows the average distance of a minority mode.

Technical note: To calculate the approximate average distance from home, I take a weighted average of the mid-distances of each reported distance band, with the weighting based on the number of commuters reported in each distance band (I hope that makes sense!).

For the Sydney CBD, public transport trips had a slightly longer average commuting distance than private transport, but for the Melbourne CBD it was the other way around. There’s no clear pattern for the larger CBDs.

However for the smaller CBDs public transport tended to have much longer average distances (with Toowoomba the longest). This suggests public transport was more competitive for longer travel distances to smaller cities.

In summary – who drove to work in Australian CBDs in 2016?

My analysis has found that people with the following characteristics were significantly over-represented in private transport CBD commuting in Australia’s largest cities:

commuters on the highest incomes
commuters working very long hours
commuters living further from rapid transit stations
commuters who were parenting
older commuters (particularly for males)
males
commuters likely to be doing shift work – particularly police and medical workers

CBD commuters living within around 5 km of large CBDs and within around 2.5 km of smaller CBDs were more likely to use active transport for obvious reasons. Beyond these near-CBD areas, there were not clear relationships between mode split and distance from CBD.

There were also some types of commuters who had high private transport mode shares, but made up only a small volume of CBD commuters so were not significantly over-represented in private transport commuting. These included:

Part-time workers on high incomes
Workers who need a motor vehicle as part of their day job

What can public transport agencies do to try to shift these private transport CBD commuters towards public transport?

Many of these private transport commuters were on high incomes, and didn’t choose public transport, even though it was relatively close to home. These commuters probably won’t respond to fare reductions, but they (or their employers) may respond to private transport disincentives (eg parking levies, reduced parking availability, (de)congestion charging, changes to tax incentives).

For commuters working part time, shift work, and/or long hours, public transport agencies might want to ensure there is a reasonably frequent services from early morning until well into the evening on rapid transit lines. In 2017 Sydney boosted off peak train frequencies to 15 minutes or better over a very long span of hours, and patronage grew strongly (until the pandemic hit).

For parenting commuters, perhaps locating childcare centres, kindergartens, and schools closer to rapid transit stations might make it easier to mix work and parenting responsibilities while travelling on public transport. But of course relocating such facilities is hardly trivial, and high land values around rapid transit stations would also be a challenge. It may however assist with getting higher public transport mode shares for school travel, which is a significant travel demand in peak periods.

I haven’t been able to explore the issue of public transport service quality and mode choice, but ensuring public transport has sufficient capacity and reliability would obviously be desirable, and I suspect might be particularly important to people on higher incomes and/or working longer hours who consider themselves time-poor.

Of course the absence of rapid transit is associated with higher private transport mode share in most cities. Public transport agencies might want to consider which parts of their cities are generating higher concentrations of private transport CBD commuters, and whether that might be related to public transport service quality. All cities will have areas remote from rapid transit stations, but only some of these areas will have higher concentrations of CBD employees.

My next post on this topic will look at the spatial distribution CBD commuter mode shares and private commuter volumes in the larger cities.

3 Comments | Australian Cities, Brisbane, Gender, Melbourne, Mode share, Mode shift, Parenting, Perth, Road Traffic, Sydney | Tagged: car parking, Census Journey to Work | Permalink
Posted by chrisloader

How did Perth’s CBD end up with 19% more private transport commuters in 2021?

Sat 3 June, 2023

Note: Since publishing this post, it has come to my attention that Perth’s Fremantle train line was closed on census day in 2021, which may have impacted mode shares in Perth.

ABS census data tells us that Perth’s CBD experienced a massive 19% jump in the number of private transport commuter trips between 2016 and 2021. That’s over 5000 more journeys – mostly as car drivers – and is quite likely to have made traffic congestion worse.

So how did that happen? Where were these extra commuters travelling to? Were there particular changes in the modal mix in different parts of the CBD? Was this growth enabled by a big increase in car parking capacity? And what has been happening to car park pricing?

This post digs a little deeper following my last post that explored the impact of COVID on journey to mode shares in Australian cities in 2021.

A quick recap of overall changes in journey to work in the Perth CBD

Here’s the volume of Perth CBD commuters by main mode, including working at home in 2011, 2016, and 2021:

See my last post for my definition of the Perth CBD. A trip involving any public transport is classed as public, a trip that involves only walking or cycling is classed as active, and any other form of travel is classed as private.

At the 2021 census, Perth was COVID-free with relatively few restrictions on intra-state movement or activity.

Total employment in the CBD grew by a massive 26% from 82,214 in 2016 to 103,944 in 2021. Private transport trips increased by 19%, but because this was less growth than overall employment growth there was actually a commuter mode shift away from private transport of 1.6% (from 36.5% to 34.9%).

The biggest increase in CBD worker volumes was in those who worked at home.

Public transport commuting to the CBD increased by only 85 trips between 2016 and 2021, but still accounted for more trips than private transport.

LATE EDIT: It’s just come to my attention that the Fremantle train line was closed on the day of the 2021 census (10 August), which will have suppressed public transport mode share in the western suburbs.

My last post concluded there was likely a significant mode shift from public transport to remote working. There was some mode shift away from public transport and towards remote working and private transport for some middle age groups, although some of this shift is likely to be a normal trend seen as people age (and become parents). I was unable to identify occupations that saw a substantial mode shift from public transport to private transport, although some occupations saw a lot more private transport growth than public transport growth.

This post now takes that analysis a bit further by looking at spatial variations in the modal mix by workplace location.

Where were the extra private transport commuters working?

Here’s the change in private commuter trips for each destination zone around the Perth CBD:

Note: the circles aren’t always drawn in the middle of each destination zone, aren’t intended to highlight any particular location within each zone, and may not be representative of major car park locations.

There were both increases and decreases around the CBD. I’m going to focus in more detail on the following high-growth destination zones that I’ve arbitrarily named by a dominant building, precinct, or bordering streets:

Most of the zones that saw a big increase in private transport commuter trips also saw a big increase in public transport trips.

Capital Square saw jobs more than triple between 2016 and 2021 as a major new development was completed (including the new Woodside headquarters). It had the largest increase in private transport trips, but even more new trips were by public transport. The development includes five levels of car parking on a fairly large site (at least 659 car parks according to some planning documents). It also saw the largest growth in active transport commuter trips of any destination zone in the Perth CBD.

The zone I have labelled Kings Square (which includes Perth Arena and the new Shell and HBF buildings) saw only slightly more new public transport trips than new private transport trips, despite Perth train station being inside the zone.

The Royal Perth Hospital zone had almost all of its net job growth accounted for by private transport, some of which would have been shift workers. This is consistent with my last post that found a large increase in private transport commuters under the “carers and aids” and “health and welfare support” occupation groups. The hospital is directly adjacent to McIver train station, served by multiple train lines.

One mixed-use block between Terrace Road, Victoria Avenue, Adelaide Terrace, and Hill Street had an increase in private trips and a decrease in public trips. It’s difficult to speculate why this occurred due to the diverse mix of land uses.

The Elizabeth Quay zone saw more growth in private trips than public trips, despite being immediately adjacent to Elizabeth Quay train station. I’ve not been able to identify any large new car parks in the area. Car parks immediately north of the development site were offering $25 all-day car parking at the time of writing which I suspect the average employee might not consider particularly affordable.

The Brookfield Place and Central Park zones mostly saw a big increase in the number of remote workers.

Outside the CBD, the biggest decline in private trips was -1863 in a zone near West Leederville station where the Princess Margaret Hospital for Children closed in 2018 (replaced by the Perth Children’s Hospital in Nedlands).

Where was there a shift from public to private transport?

The following map shows destination zones where there was a decline in public transport trips and an increase in private transport trips (no zones showed the opposite flow):

Just under than half of the destination zones around the Perth CBD saw some sort of net shift to private transport, and most of these were very small numbers. In total these zones account for 492 trips within for my definition of the Perth CBD, about 0.5% of all workers. A net shift from public transport explains less than 10% of the total increase in private transport commuter trips.

This is consistent with analysis in my last post (which disaggregated by birth cohorts and occupations) and again suggests the growth in private trips was broadly in line with the overall growth in CBD employment. It also fits with the hypothesis that the biggest mode shift was from public transport to remote working.

Another way of analysing mode shift is to look the percentage change in private transport mode share by zone:

In the western part of the main CBD area there were many zones with a large mode shift away from private transport, and many of these zones had high employment density.

In fact, the next chart shows how employment density and private transport mode share changed between 2016 and 2021 in the Perth CBD, with the thin end of each ‘comet’ being 2016 and the thick end being 2021 (I’ve arbitrarily named several more destination zones based on major landmarks or surrounding streets).

Note: some destination zones include significant land that is not built up (eg parkland, water bodies, and/or freeway interchanges) and these will have understated employment density. This incudes Convention/Exhibition and Elizabeth Quay.

The dominant pattern is that the zones with high and increasing employment density mostly saw declining private transport mode share, although the “Terrace / Hill / Victoria” block was a standout exception having increasing employment density and increasing private mode share.

How did the CBD absorb so many more car commuters?

It’s hard to know for sure but some possible explanations include:

New car parking supply: I’ve already mentioned the Capital Square development that included five levels of parking. Locals might know of other new large CBD car parks, but I’ve struggled to identify any large car parks on Parkopedia or Google Maps that didn’t already exist in 2016. Many new office buildings don’t appear to include large car parks.
Perth was in a “mining downturn” in 2016: The Perth CBD only added 1.7k jobs between 2011 and 2016, and there was no significant increase in private commuter trips. According to a Property Council report in August 2016, Perth was experiencing very high office vacancy rates (21.8%) and had been experiencing a decline in office space demand that started around 2013. So it seems quite plausible that car parking supply grew between 2011 and 2016, but commuter parking demand only grew strongly after 2016.
Reduced short-term parking demand? Perhaps there has been a decline in demand for short-term parking (through the normalisation of online business meetings) enabling more all-day parking. But I’m just speculating.

Someone reading this from the parking industry might be able to share some insights (please add comments).

What’s been happening to Perth CBD car parking prices?

Like Sydney and Melbourne, Perth has a CBD parking levy – an annual fee collected by government per space. Here’s what’s been happening to the levy prices in real terms:

The parking levy increased substantially in real terms in 2010 and again between 2014-2016, but in recent years has not been keeping up with inflation. Between 2016 and 2021 there was almost no real change in the levy.

So what’s been happening to car park prices?

The City of Perth itself operates a large number of CBD car parks and in 2021/22 parking revenue accounted for 36% of its total income (source: budget 2022-23).

Thanks to the incredible resource that is the Wayback Machine, I’ve been able to dig out prices at their CBD car parks right back to 2001-02. For the sake of manageable analysis I’ve focussed on four relatively large central CBD car parks – Concert Hall (399 spaces), Convention Centre (1428 spaces), Elder Street (1052 spaces) and Pier Street (680 spaces). Here’s how those prices have changed over time, in nominal and real terms:

The 2010 and 2015 jumps in the pricing levy were clearly reflected in retail parking prices.

In real terms, parking prices peaked around 2015-2017 and have been in decline since then. Prices for several car parks were cut substantially in 2017/18 – perhaps as a belated response to a reduction in office commuter demand during the mining downturn. Then parking prices were frozen from 2019 to 2022 – presumably due to the pandemic.

So despite the massive increase in CBD parking demand, the City of Perth reduced – rather than increased – all-day parking prices, and so has probably also missed out on significant additional revenue. This has arguably helped facilitate the big increase in commuter traffic volumes, along with the likely associated urban amenity impacts of more traffic in the CBD.

The City of Perth is a democratic local government so it’s probably not going to behave in an entirely economically rational way when it comes to price setting. Prices are also locked in for each financial year so are much less dynamic. So what have commercial parking operators been doing?

Unfortunately I’ve not been able to use the Internet Archive to find historical commercial car parking prices in the Perth CBD back to 2016. What I can tell you is that “flexi” online parking at the Wilson Parking run Central Park car park has risen from $19 in October 2021 to $26 in May 2023 – suggesting commercial operators are not afraid to change their pricing. That said, the Kings Complex car park (517 Hay Street, near Pier Street) has had no increase in its online daily rate between October 2021 and May 2023 ($18).

So what is Perth’s parking policy?

The current Perth parking policy (2014) states:

“This policy recognises that vehicular access to, from and within central Perth is a critical element in ensuring its continued economic and social viability. It also continues to recognise the need to preserve and enhance the city’s environment. The policy aims to address these needs by supporting the provision of a balanced transport network in order to manage congestion and provide for the efficient operation of the transport network to, from and within the city centre.”

I suspect the term “balanced transport” is indicative of not trying to shift travel towards more sustainable, non-car modes. And I guess it would also be hard for the City of Perth to start discouraging something that generates more than one third of its annual revenue. Although an increase in prices might increase revenue, even if it reduces demand.

Furthermore, the Western Australian government is also continuing to widen Perth’s freeways, in the hope this might reduce traffic congestion. I’m not sure many cities have succeeded with such strategies, but good luck Perth!

Finally…

Wasn’t Perth public transport patronage below pre-pandemic levels in 2021?

I noted above that there were just 85 additional public transport commuters to Perth’s CBD in 2021 compared to 2016. But Perth’s overall public transport patronage in August 2021 was around 22%* below that in August 2016. If the number of CBD public transport commuters didn’t decline, the overall patronage decline must represent a mode shift away from public transport for trips to other destinations and/or for purposes other than travelling to work (and/or a decline in the number of such trips made by any mode).

*August 2016 had one more school weekday and one fewer Sunday than August 2021 which means we cannot directly compare total monthly patronage of the two months but they will be fairly close. It would be much cleaner to compare average school weekday patronage figures between months and years, but unfortunately few agencies publish such numbers (Victoria does now).

1 Comment | Employment density, Mode share, Mode shift, Perth, Pricing, Working at home | Tagged: car parking, Census Journey to Work, Hospitals, Pricing | Permalink
Posted by chrisloader

What impact does paid car parking have on travel mode choice in Melbourne?

Thu 3 October, 2019

Paid parking is often used when too many people want to park their car in the same place at the same time. Does it encourage people to cycle or use public transport instead of driving? Does that depend on the type of destination and/or availability of public transport? Are places with paid parking good targets for public transport upgrades?

In this post I’m going to try to answer the above questions. I’ll look at where there is paid parking in Melbourne, how transport mode shares vary for destinations across the city, and then the relationship between the two. I’ll take a deeper look at different destination types (particularly hospitals), explore the link between paid parking and employment density, and conclude with some implications for public transport planners. There’s a bit to get through so get comfortable.

This post uses data from around 158,000 surveyed trips around Greater Melbourne collected as part of a household travel survey (VISTA) between 2012 and 2018, as well as journey to work data from the 2016 ABS census.

Unfortunately the data available doesn’t allow for perfect analysis. The VISTA’s survey sample sizes are not large, I don’t have data about how much was paid for parking, nor whether other parking restrictions might impact mode choice (e.g. time limits), and I suspect some people interpreted survey questions differently. But I think there are still some fairly clear insights from the data.

Where is there paid parking in Melbourne?

I’m not aware of an available comprehensive car park pricing data set for Melbourne. Parkopedia tells you about formal car parks (not on street options) and doesn’t share data sets for free, while the City of Melbourne provides data on the location, fees, and time restrictions of on-street bays (only). So I’ve created my own – using the VISTA household travel survey.

For every surveyed trip involving parking a car, van, or truck, we know whether a parking fee was payable. However the challenge is that VISTA is a survey, so the trip volumes are small for any particular place. For my analysis I’ve used groups of ABS Destination Zones (2016 boundaries) that together have at least 40 parking trips (excluding trips where the purpose was “go home” as residential parking is unlikely to involve a parking fee). I’ve chosen 40 as a compromise between not wanting to have too small a sample, and not wanting to have to aggregate too many destination zones. In some cases a single destination zone has enough parking trips, but in most cases I have had to create groups.

I’ve tried to avoid merging different land uses where possible, and for some parts of Melbourne there are just not enough surveyed parking trips in an area (see appendix at the end of this post for more details). Whether I combine zones or use a single zone, I’m calling these “DZ groups” for short.

For each DZ group I’ve calculated the percentage of vehicle parking trips surveyed that involved someone paying a parking fee. The value will be low if only some circumstances require parking payment (eg all-day parking on weekdays), and higher if most people need to pay at most times of the week for both short and long stays (but curiously never 100%). The sample for each DZ group will be a small random sample of trips from different times of week, survey years, and durations. For DZ groups with paid parking rates above 20%, the margin of error for paid parking percentage is typically up to +/- 13% (at a 90% confidence interval).

Imperfect as the measure is, the following map shows DZ groups with at least 10% paid parking, along with my land use categorisations (where a DZ group has a specialised land use).

There are high percentages of paid parking in the central city, as you’d expect. Paid parking is more isolated in the suburbs – and mostly occurs at university campuses, hospitals, larger activity centres, and of course Melbourne Airport.

The next chart shows the DZ groups with the highest percentages of paid parking (together with the margin of error).

Technical note: the Y-axis shows the SA2 name, rather than the (unique but meaningless) DZ code(s), so you will see multiple DZ groups with the same SA2 name.

At the top of the chart are central city areas, major hospitals, several university campuses, and Melbourne Airport.

Further down the chart are:

larger activity centres – many inner suburban centres plus also Dandenong, Frankston, Box Hill, and curiously Springvale (where some controversial parking meters were switched off in 2017),
the area around Melbourne Zoo (Parkville SA2 – classified as “other”),
some inner city mixed-use areas,
two shopping centres – the inner suburban Victoria Gardens Shopping Centre in Richmond (which includes an IKEA store), and Doncaster (Westfield) – the only large middle suburban centre to show up with significant paid parking (many others now have time restrictions), and
some suburban industrial employment areas (towards the bottom of the chart) – in which I’ve not found commercial car parks.

These are mostly places of high activity density, where land values don’t support the provision of sufficient free parking to meet all demand.

While the data looks quite plausible, the calculated values not perfect, for several reasons:

Some people almost certainly forget that they paid for parking (or misinterpreted the survey question). For example, on the Monash University Clayton campus, 45% of vehicle driver trips (n = 126) said no parking fee was payable, 2% said their employer paid, and 12% said it was paid through a salary arrangement. However there is pretty much no free parking on campus (at least on weekdays), so I suspect many people forgot to mention that they had paid for parking in the form of a year or half-year permit (I’m told that very few staff get free parking permits).
Many people said they parked for free in an employee provided off-street car park. In this instance the employer is actually paying for parking (real estate, infrastructure, maintenance, etc). If this parking is rationed to senior employees only then other employees may be more likely to use non-car modes. But if employer provided is plentiful then car travel would be an attractive option. 22% of surveyed trips involving driving to the Melbourne CBD reported parking in an employer provided car park, about a quarter of those said no parking fee was required (most others said their employer paid for parking).
As already mentioned, the sample sizes are quite small, and different parking events will be at different times of the week, for different durations, and the applicability of parking fees may have changed over the survey period between 2012 and 2018.
The data doesn’t tell us how much was paid for parking. I would expect price to be a significant factor influencing mode choices.
Paid parking is not the only disincentive to travel by private car – there might be time restrictions or availability issues, but unfortunately VISTA does not collect such data (it would be tricky to collect).

How does private transport mode share vary across Melbourne?

The other part of this analysis is around private transport mode shares for destinations. As usual I define private transport as a trip that involved some motorised transport, but not any modes of public transport.

Rich data is available for journeys to work from the ABS census, but I’m also interested in general travel, and for that I have to use the VISTA survey data.

For much of my analysis I am going to exclude walking trips, on the basis that I’m primarily interested in trips where private transport is in competition with cycling and public transport. Yes there will be cases where people choose to walk instead of drive because of parking challenges, but I’m assuming not that many (indeed, around 93% of vehicle driver trips in the VISTA survey are more than 1 km). An alternative might be to exclude trips shorter than a certain distance, but then that presents difficult decisions around an appropriate distance threshold.

Here’s a map of private transport mode share of non-walking trips by SA2 destination:

Technical note: I have set the threshold at 40 trips per SA2, but most SA2s have hundreds of surveyed trips. The grey areas of the map are SA2s with fewer than 40 trips, and/or destination zones with no surveyed trips.

For all but the inner suburbs of Melbourne, private transport is by far the dominant mode for non-walking trips. Public transport and cycling only get a significant combined share in the central and inner city areas.

Where is private transport mode share unusually low? And could paid parking explain that?

The above chart showed a pretty strong pattern where private transport mode share is lower in the central city and very high in the suburbs. But are there places where private mode share in unusually low compared to surround land uses? These might be places where public transport can win a higher mode share because of paid parking, or other reasons.

Here’s a similar mode share map, but showing only DZ groups that have a private mode share below 90%:

If you look carefully you can see DZ groups with lower than 80% mode share, including some university/health campuses.

To better illustrate the impact of distance from the city centre, here’s a chart summarising the average private transport mode share of non-walking trips for selected types of places, by distance from the city centre:

Most destination place types are above 90% private transport mode share, except within the inner 5 km. The lowest mode shares are at tertiary education places, workplaces in the central city, secondary schools and parks/recreation. Up the top of the chart are childcare centres, supermarkets and kinders/preschool. Sorry it is hard to decode all the lines – but the point is that they are mostly right up the top.

The next chart brings together the presence of paid parking, distance from the CBD, destination place type, and private transport mode shares. I’ve greyed out DZ groups with less than 20% paid parking, and you can see they are mostly more than 3 km from the CBD. I’ve coloured and labelled the DZ groups with higher rates of paid parking. Also note I’ve used a log scale on the X-axis to spread out the paid DZ groups (distance from CBD).

Most of the DZ groups follow a general curve from bottom-left to top-right, which might reflect generally declining public transport service levels as you move away from the city centre.

The outliers below the main cloud are places with paid parking where private modes shares are lower than other destinations a similar distance from the CBD. Most of these non-private trips will be by public transport. The biggest outliers are university campuses, including Parkville, Clayton, Caulfield, Burwood, and Hawthorn. Some destinations at the bottom edge of the main cloud include university campuses in Kingsbury and Footscray, and parts of the large activity centres of Box Hill and Frankston.

Arguably the presence of paid parking could be acting as a disincentive to use private transport to these destinations.

Contrast these with other paid parking destinations such as hospitals, many activity centres, and Melbourne Airport. The presence of paid parking doesn’t seem to have dissuaded people from driving to these destinations.

Which raises a critical question: is this because of the nature of travel to these destinations means people choose to drive, or is this because of lower quality public transport to those centres? Something we need to unpack.

How strongly does paid car parking correlate with low private transport mode shares?

Here’s a chart showing DZ groups with their private transport mode share of (non-walking) trips and percent of vehicle parking trips involving payment.

Technical note: A colour has been assigned to each SA2 to help associate labels to data points, although there are only 20 unique colours so they are re-used for multiple SA2s. I have endeavoured to make labels unambiguous. It’s obviously not possible to label all points on the chart.

In the top-left are many trip destinations with mostly free parking and very high private transport mode share, suggesting it is very hard for other modes to compete with free parking (although this says nothing about the level of public transport service provision or cycling infrastructure). In the bottom-right are central city DZ groups with paid parking and low private transport mode share.

There is a significant relationship between the two variables (p-value < 0.0001 on a linear regression as per line shown), and it appears that the relative use of paid parking explains a little over half of the pattern of private transport mode shares (R-squared = 0.61). But there is definitely a wide scattering of data points, suggesting many other factors are at play, which I want to understand.

In particular it’s notable that the data points close to the line in the bottom-right are in the central city, while most of the data points in the top-right are mostly in the suburbs (they are also the same land use types that were an exception in the last chart – Melbourne Airport, hospitals, some university campuses, and activity centres).

As always, it’s interesting to look at the outliers, which I am going to consider by land use category.

Melbourne Airport

The airport destination zone has around 62% paid parking and around 92% private transport mode share for general trips (noting the VISTA survey is only of travel by Melbourne and Geelong residents). The airport estimates 14% of non-transferring passengers use some form of public transport, and that 27% of weekday traffic demand is employee travel.

Some plausible explanations for high private mode share despite paid parking include:

shift workers travelling when public transport is infrequent or unavailable (I understand many airport workers commence at 4 am, before public transport has started for the day),
unreliable work finish times (for example, if planes are delayed),
longer travel distances making public transport journeys slower and requiring transfers for many origins,
travellers with luggage finding public transport less convenient,
highly time-sensitive air travellers who might feel more in control of a private transport trip,
active transport involving long travel distances with poor infrastructure, and
many travel costs being paid by businesses (not users).

It’s worth noting that the staff car park is remote from the terminal buildings, such that shuttle bus services operate – an added inconvenience of private transport. But by the same token, the public transport bus stops are a fairly long walk from terminals 1 and 2.

The destination zone that includes the airport terminals also includes industrial areas on the south side of the airport. If I aggregate only the surveyed trips with a destination around the airport terminals, that yields 69% paid parking, and 93% private mode share. Conversely, the industrial area south of the airport yields 6% paid parking, and 100% private mode share.

Hospitals

Almost all hospitals are above the line – i.e. high private mode share despite high rates of paid parking.

The biggest outliers are the Monash Medical Centre in Clayton, Austin/Mercy Hospitals in Heidelberg, and Sunshine Hospital in St Albans South.

The Heidelberg hospitals are adjacent to Heidelberg train station. The Monash Medical Centre at Clayton is within 10 minutes walk of Clayton train station where trains run every 10 minutes or better for much of the week, and there’s also a SmartBus route out the front. Sunshine Hospital is within 10 minutes walk of Ginifer train station (although off-peak services mostly run every 20 minutes).

It’s not like these hospitals are a long way from reasonably high quality public transport. But they are a fair way out from the CBD, and only have high quality public transport in some directions.

The DZ containing Royal Melbourne Hospital, Royal Women’s Hospital, and Victoria Comprehensive Cancer Centre in Parkville is the exception below the line. It is served by multiple high frequency public transport lines, and serves the inner suburbs of Melbourne (also well served by public transport) which might help explain its ~45% private transport mode share.

The Richmond hospital DZ group is close to the line – but this is actually a blend of the Epworth Hospital and many adjacent mixed land uses so it’s not a great data point to analyse unfortunately.

So what might explain high private transport mode shares? I think there are several plausible explanations:

shift workers find public transport infrequent, less safe, or unavailable at shift change times (similar to the airport),
visitors travel at off-peak times when public transport is less frequent,
longer average travel distances (hospitals serve large population catchments with patients and visitor origins widely dispersed),
specialist staff who work across multiple hospitals on the same day,
patients need travel assistance when being admitted/discharged, and
visitor households are time-poor when a family member is in hospital.

The Parkville hospital data point above the line is the Royal Children’s Hospital. Despite having paid parking and being on two frequent tram routes, there is around 80% private transport mode share. This result is consistent with the hypotheses around time-poor visitor households, patients needing assistance when travelling to/from hospitals, and longer average travel distances (being a specialised hospital).

We can also look at census journey to work data for hospitals (without worrying about small survey sample sizes). Here’s a map showing the relative size, mode split and location of hospitals around Melbourne (with at least 200 journeys reported with a work industry of “Hospital”):

It’s a bit congested in the central city so here is an enlargement:

The only hospitals with a minority private mode share of journeys to work are the Epworth (Richmond), St Vincent’s (Fitzroy), Eye & Ear (East Melbourne), and the Aboriginal Health Service (Fitzroy) (I’m not sure that this is a hospital but it’s the only thing resembling a hospital in the destination zone).

Here’s another chart of hospitals showing the number of journeys to work, private transport mode share, and distance from the Melbourne CBD:

Again, there’s a very strong relationship between distance from the CBD and private transport mode share.

Larger hospitals more than 10 km from the CBD (Austin/Mercy, Box Hill, Monash) seem to have slightly lower private mode shares than other hospitals at a similar distance, which might be related to higher parking prices, different employee parking arrangements, or it might be that they are slightly closer to train stations.

The (relatively small) Royal Talbot Hospital is an outlier on the curve. It is relatively close to the CBD but only served by ten bus trips per weekday (route 609).

To test the public transport quality issue, here’s a chart of journey to work private mode shares by distance from train stations:

While being close to a train station seems to enable lower private transport mode shares, it doesn’t guarantee low private transport mode shares. The hospitals with low private transport mode shares are all in the central city.

So perhaps the issue is as much to do with the public transport service quality of the trip origins. The hospitals in the suburbs largely serve people living in the suburbs which generally have lower public transport service levels, while the inner city hospitals probably more serve inner city residents who generally have higher public transport service levels and lower rates of motor vehicle ownership (see: What does the census tell us about motor vehicle ownership in Australian cities? (2006-2016)).

Indeed, here is a map showing private transport mode share of non-walking trips by origin SA2:

Technical notes: grey areas are SA1s (within SA2s) with no survey trips.

Finally for hospitals, here is private transport mode share of journeys to work (from the census) compared to paid parking % from VISTA (note: sufficient paid parking data is only available for some hospitals, and we don’t know whether staff have to pay for parking):

There doesn’t appear to be a strong relationship here, as many hospitals with high rates of paid parking also have high private transport mode shares.

In summary:

The distance of a hospital from the CBD seems to be the primary influence on mode share.
Specialised hospitals with larger catchments (eg Children’s Hospital) might have higher private transport mode shares.
The quality of public transport to the hospital seems to have a secondary impact on mode shares.

Activity centres

Suburban activity centres such as Frankston, Box Hill, Dandenong, and Springvale have high private mode shares, which might reflect lower public transport service levels than the inner city (particularly for off-rail origins).

Box Hill is the biggest outlier for activity centres in terms of high private mode share despite paid parking. But compared to other destinations that far from the Melbourne CBD, it has a relatively low private transport mode share. It is located on a major train line, and is served by several frequent bus routes.

In general, there are fewer reasons why increased public transport investment might not lead to higher public transport mode share compared to airports and hospitals. Travel distances are generally shorter, many people will be travelling in peak periods and during the day, there are probably few shift workers (certainly few around-the-clock shift workers).

University campuses

The biggest university outliers above the line (higher private mode shares and higher paid parking %) are Deakin University (Burwood) and La Trobe University (Kingsbury). Furthermore, private transport also has a majority mode share for Monash University Clayton, Victoria University Footscray Park, Monash University (Caulfield) and Swinburne University (Hawthorn).

As discussed earlier, I suspect the rates of paid parking may be understated for university campuses because people forget they have purchased long-term parking permits.

The following chart shows the full mode split of trips to the University DZ groups in various SA2s (this time including walking trips):

Of the campuses listed, only Hawthorn and Caulfield are adjacent to a train station. Of the off-rail campuses:

Parkville (Melbourne Uni, 43% public transport) is served by multiple frequent tram routes, plus a high frequency express shuttle bus to North Melbourne train station. In a few years it will also have a train station.
Clayton (Monash, 22% PT) is also served by a high frequency express shuttle bus service to Huntingdale train station.
Burwood (Deakin, 19% PT) is on a frequent tram route, but otherwise moderately frequent bus services (its express shuttle bus service to Box Hill train station – route 201 – currently runs every 20 minutes)
Footscray (Park) (Victoria Uni, 14% PT) has bus and tram services to Footscray train station but they operate at frequencies of around 15 minutes in peak periods, and 20 minutes inter-peak.
Kingsbury (La Trobe Uni, 13% PT) has an express shuttle bus service from Reservoir station operating every 10 minutes on weekdays (introduced in 2016).

The success of high frequency express shuttle bus services to Parkville and Clayton may bode well for further public transport frequency upgrades to other campuses.

University campuses are also natural targets for public transport as university students on low incomes are likely to be more sensitive to private motoring and parking costs.

However university campuses also have longer average travel distances which might impact mode shares – more on that shortly.

Central city

Most central city DZ groups are in the bottom-right of the scatter plot, but there are some notable exceptions:

A Southbank DZ around Crown Casino has 65% paid parking and 70% private transport mode share. This was also an exception when I analysed journey to work (see: How is the journey to work changing in Melbourne? (2006-2016)) and might be explained be relatively cheap parking, casino shift workers, and possibly more off-peak travel (eg evenings, weekends).
Similarly, a Southbank DZ group around the Melbourne Convention and Exhibition Centre / South Wharf retail complex has 62% paid parking and around 74% private mode share. Many parts of this area are a long walk from public transport stops, and also there are around 2,200 car parks on site (with $17 early bird parking at the time of writing).
Albert Park – a destination zone centred around the park – has around 54% paid parking and 87% private transport mode share. Most of the VISTA survey trips were recreation or sport related, which may include many trips to the Melbourne Sports and Aquatic Centre. The park is surrounded by tram routes on most sides, but is relatively remote from the (rapid) train network.
Northern Docklands shows up with around 50% paid parking and around 88% private transport mode share, despite being very close to the Melbourne CBD. While this area is served by multiple frequent tram routes, it is a relatively long walk (or even tram ride) from a nearby a train station (from Leven Avenue it is 16 minutes by tram to Southern Cross Station and around 18 minutes to Flagstaff Station, according to Google). The closest train station is actually North Melbourne, but there is currently no direct public transport or pedestrian connection (the E-gate rail site and future Westgate Tunnel road link would need to be crossed).

Inner suburbs

Some places to the bottom-left of the cloud on the chart include inner suburban areas such as South Yarra, Fitzroy, Richmond, Abbotsford, Brunswick, and Collingwood. While paid parking doesn’t seem to be as common, private transport mode shares are relatively low (even when walking trips are excluded). These areas typically have dense mixed-use activity with higher public transport service levels, which might explain the lower private transport mode shares. These areas probably also have a lot of time-restricted (but free) parking.

What is the relationship between paid parking and journey to work mode shares?

For journeys to work we thankfully have rich census data, with no issues of small survey sample sizes.

The following chart combines VISTA data on paid parking, with 2016 census data on journey to work mode shares (note: the margin of error on the paid parking percentage is still up to +/-12%).

The pattern is very similar to that for general travel, and the relationship is of a similar strength (r-squared = 0.59).

There are more DZ groups below the line on the left side of the chart, meaning that the private transport mode share of journeys to work is often lower than for general travel.

Indeed, here is a chart comparing private transport mode share of general travel (VISTA survey excluding walking and trips to go home) with journeys to work (ABS census):

Note the margin of error for private transport mode shares is around +/-10% because of the small VISTA sample sizes.

For most DZ groups of all types, private transport mode shares are lower for journeys to work compared to general travel (ie below the diagonal line). This might reflect public transport being more competitive for commuters than for visitors – all-day parking might be harder to find and/or more expensive. This suggests investment in public transport might want to target journeys to work.

The DZ groups above the line include Flemington Racecourse (census day was almost certainly not a race day so there was probably ample parking for employees, while many VISTA survey trips will be from event days), Deakin Uni (Burwood), and a few others. Some of these DZ groups are dominated by schools, where workers (teachers) drive while students are more likely to cycle or catch public transport.

What about public transport mode shares?

The following chart shows VISTA public transport mode shares (for general travel) against paid parking percentages:

There are similar patterns to the earlier private transport chart, but flipped. The outliers are very similar (eg hospitals and Melbourne Airport in the bottom-right), although the top-left outliers include some destinations in socio-economically disadvantaged areas (eg Braybrook, Broadmeadows, Dandenong).

The DZ group in Blackburn South with no paid parking but 22% public transport mode share contains several schools but otherwise mostly residential areas, and the survey data includes many education related trips.

Are shift workers less likely to use public transport?

Shift workers at hospitals, Melbourne Airport, and the casino might be less likely to use public transport because of the inconvenience of travelling at off-peak shift change times, when service levels may be lower or non-existent.

Here’s a chart showing the mode split of VISTA journeys to work by destination type categories, and also type of working hours:

For hospitals, rostered shifts had a lower public transport mode share, compared to fixed and flexible hours workers, so this seems to support (but not prove) the hypothesis.

Public transport use is actually higher for rostered shift workers at other destination types, but I suspect these are mostly not around-the-clock shifts (eg retail work), and are more likely to be lower paid jobs, where price sensitivity might contribute more to mode choice.

Unfortunately there are not enough VISTA journey to work survey responses for Melbourne Airport to get sensible estimates of mode shares for different work types.

Do longer travel distances result in lower public transport mode shares?

Another earlier hypothesis was that destinations that attract longer distance trips (such as universities, hospitals, and airports) are more likely to result in private transport mode choice, as public transport journeys are more likely to require one or more transfers.

Trip distances to specialised places such as airports, suburban employment areas, universities and hospitals are indeed longer. But the central city also rates here and that has low private transport mode shares.

Digging deeper, here are median travel distances to DZ groups around Melbourne:

The central city has higher median trip distances but low private mode shares, while many suburban destinations (particularly employment/industrial areas, universities, and hospitals) have similar median travel distances but much higher public transport mode shares.

I think a likely explanation for this is that public transport to the central city is generally faster (often involving trains), more frequent, and involves fewer/easier transfers. Central city workers are also more likely to live near radial public transport lines. On the other hand, the trip origins for suburban destinations are more likely to be in the suburbs where public transport service levels are generally lower (compared to trip origins in the inner suburbs).

Cross-suburban public transport travel will often require transfers between lower frequency services, and will generally involve at least one bus leg. Very few Melbourne bus routes are currently separated from traffic, so such trips are unlikely to be as fast as private motoring (unless parking takes a long time to find), but they might be able to compete on marginal cost (if there is more expensive paid parking).

Of course this is not to suggest that cross-suburban public transport cannot be improved. More direct routes, higher frequencies, and separation from traffic can all make public transport more time-competitive.

How does parking pricing relate to employment density?

My previous research has confirmed a strong relationship between job density and lower journey to work private transport mode shares (see: What explains variations in journey to work mode shares between and within Australian cities?). Can this be explained by more paid parking in areas with higher job density?

The following chart compares weighted job density (from census 2016) and paid parking percentages (from VISTA):

Technical notes: Weighted job density is calculated as a weighted average of the job densities of individual destination zones in a DZ group, with the weighting being the number of jobs in each zone (the same principle as population weighted density). I have used a log-scale on the X-axis, and not shown DZ groups with less than 1 job/ha as they are not really interesting

There appears to be a relationship between job density and paid parking – as you would expect. The top right quadrant contains many university campuses, hospitals, and central city areas with high job density and high paid parking percentages.

In the bottom-right are many large job-dense shopping centres that offer “free” parking. Of course in reality the cost of parking is built into the price of goods and services at the centres (here’s a thought: what if people who arrive by non-car modes got a discount?). An earlier chart showed us that employees are less likely to commute by private transport than visitors.

The outliers to the top-left of the chart are actually mostly misleading. An example is Melbourne Airport where the density calculation is based on a destination zone that includes runways, taxiways, a low density business park, and much green space. The jobs are actually very concentrated in parts of that zone (e.g. passenger terminals) so the density is vastly understated (I’ve recommended to the ABS that they create smaller destination zones around airport terminal precincts in future census years).

Inclusion of significant green space and/or adjacent residential areas is also an issue at La Trobe University (Kingsbury data point with just under 50% mode share), RMIT Bundoora campus (Mill Park South), Royal Children’s Hospital (Parkville), Sunshine Hospital (St Albans South), Victoria University (Footscray (Park)), Albert Park (the actual park), and Melbourne Polytechnic Fairfield campus / Thomas Embling Hospital (Yarra – North).

I am at a loss to explain paid parking in Mooroolbark – the only major employer seems to be the private school Billanook College.

Can you summarise the relationship between paid parking and mode shares?

I know I’ve gone down quite a few rabbit holes, so here’s a summary of insights:

Distance from the Melbourne CBD seems to be the strongest single predictor of private transport mode share (as origin or destination). This probably reflects public transport service levels generally being higher in the central city and lower in the suburbs. Destinations further from the central city are likely to have trip origins that are also further from the central city, for which public transport journeys are often slower.
Paid parking seems to be particularly effective at reducing private transport mode shares at university campuses, and the impact is probably greater if there are higher quality public transport alternatives available.
There’s some evidence to suggest paid parking may reduce private transport mode shares at larger activity centres such as Box Hill and Frankston.
Most hospitals have very high private transport mode shares, despite also having paid parking. Hospitals with better public transport access have slightly lower private transport mode shares.
Destinations with around-the-clock shift workers (e.g. hospitals and airports) seem generally likely to have high private transport mode shares, as public transport services at shift change times might be infrequent or unavailable.
Suburban destinations that have longer median travel distances (such as hospitals, airports and industrial areas) mostly have higher private transport mode shares.
Even if there isn’t much paid parking, destinations well served by public transport tend to have lower private transport mode shares (although this could be related to time-restricted free parking).

If you’d like more on factors influencing mode shares, I’ve also explored this more broadly elsewhere on this blog, with employment density (related to parking prices), cycling infrastructure quality, proximity to rapid public transport, and walking catchment density found to be significant factors (see: What explains variations in journey to work mode shares between and within Australian cities?).

Are places with paid parking good targets for public transport investments?

Many of my recent conversations with transport professionals around this topic have suggested an hypothesis that public transport wins mode share in places that have paid parking. While that’s clearly the case in the centre of Melbourne and at many university campuses, this research has found it’s more of a mixed story for other destinations.

While this post hasn’t directly examined the impact of public transport investments on mode shares in specific places, I think it can inform the types of destinations where public transport investments might be more likely to deliver significant mode shifts.

Here’s my assessment of different destination types (most of which have paid parking):

Suburban hospitals may be challenging due to the presence of shift workers, patients needing assistance, visitors from time-poor households, and long average travel distances making public transport more difficult for cross-suburban travel. There’s no doubt many people use public transport to travel to hospitals, but it might not include many travellers who have a private transport option.
Larger activity centres with paid parking show lower private transport mode shares. Trips to these centres involve shorter travel distances that probably don’t require public transport transfers, and don’t suffer the challenges of around-the-clock shift workers, so they are likely to be good targets for public transport investment.
Universities are natural targets for public transport, particularly as many students would find the cost of maintaining, operating and parking a car more challenging, or don’t have access to private transport at all (around 35% of full time university/TAFE students do not have a full or probationary licence according to the VISTA sample). Universities do attract relatively higher public transport mode shares (even in the suburbs) and recent investments in express shuttle services from nearby train stations appear to have been successful at growing public transport patronage.
Melbourne Airport has high rates of paid parking and private transport mode share. It is probably a challenging public transport destination for employees who work rostered shifts. However already public transport does well for travel from the CBD, and this will soon be upgraded to heavy rail. Stations along the way may attract new employees in these areas, but span of operating hours may be an issue.
Job dense central city areas that are not currently well connected to the rapid public transport network could be public transport growth opportunity. In a previous post I found the largest journey to work mode shifts to public transport between 2011 and 2016 were in SA2s around the CBD (see: How is the journey to work changing in Melbourne? (2006-2016)). The most obvious target to me is northern Docklands which is not (yet) conveniently connected its nearby train station. Public transport is also gaining patronage in the densifying Fishermans Bend employment area (buses now operate as often as every 8 minutes in peak periods following an upgrade in October 2018).
Lower density suburban employment/industrial areas tend to have free parking, longer travel distances, and very high private transport mode shares. These are very challenging places for public transport to win significant mode share, although there will be some demand from people with limited transport options.

An emerging target for public transport might be large shopping centres that are starting to introduce paid or time-restricted car parking (particularly those located adjacent to train stations, e.g. Southland). That said, Westfield Doncaster, which has some paid parking (around 19%), has achieved only 6% public transport mode share in the VISTA survey (n=365), athough this may be growing over time. Meanwhile, Dandenong Plaza has around 16% public transport mode share despite only 6% paid parking.

Upgraded public transport to shopping centres might be particularly attractive for workers who are generally on lower incomes (we’ve already seen staff having lower private transport mode shares than visitors). Also, customer parking may be time-consuming to find on busy shopping days, which might make public transport a more attractive option, particularly if buses are not delayed by congested car park traffic.

There’s a lot going on in this space, so if you have further observations or suggestions please comment below.

Appendix: About destination group zones

Here is a map showing my destination zone groups in the central city area which have 15% or higher paid parking. Each group is given a different colour (although there are only 20 unique colours used so there is some reuse). The numbers indicate the number of surveyed parking trips in each group:

Some of the DZ groups have slightly less than 40 parking trips, which means they are excluded from much of my analysis. In many cases I’ve decided that merging these with neighbouring zones would be mixing disparate land uses, or would significantly dilute paid parking rates to not be meaningful (examples include northern Abbotsford, and parts of Kew and Fairfield). Unfortunately that’s the limitation of the using survey data, but there are still plenty of qualifying DZ groups to inform the analysis.

I have created destination zone groups for most destination zones with 10%+ paid parking, and most of the inner city area to facilitate the DZ group private transport mode share chart. I haven’t gone to the effort of creating DZ groups across the entire of Melbourne, as most areas have little paid parking and are not a focus for my analysis.

Leave a Comment » | Employment density, Melbourne, Mode share, Mode shift, Pricing | Tagged: airports, car parking, Hospitals | Permalink
Posted by chrisloader

What might explain journey to work mode shifts in Australia’s largest cities?

Mon 28 May, 2018

[Updated 29 June 2018 with further analysis of parking levies and their impact]

Between 2011 and 2016, journey to work public transport mode shares went up significantly in Melbourne and Sydney but dropped significantly in Perth and Brisbane. Private transport mode shifts did the opposite. Can this be explained by the changing distribution of jobs within cities, or other factors such as changes in transport costs?

In a recent post focused on Brisbane I found that stronger growth in suburban jobs relative to central city jobs could explain around half of the city’s mode shift towards private transport, with other factors (mostly the changes in relative attractiveness of modes) explaining the rest.

So how is job distribution changing in other Australian cities? How much of the mode shifts can be attributed to changing job distribution and how much could be attributed to other factors like changes in transport costs, or increasing employment density?

(for details about how I define public, private and active transport, see the appendix in this post)

How is job distribution changing in Australian cities?

Here’s a view of the changing distribution of all jobs within each city by workplaces distance from the city centre.

(Unfortunately I only have 2006 data for Sydney and Melbourne)

The changes are relatively subtle, but if look at how the bands shift between years, you’ll see increasing centralisation in Sydney but a decentralisation in all other cities between 2011 and 2016.

The strongest decentralisation was in Brisbane and Perth, which also showed the biggest increases in private transport mode share.

However Melbourne saw both a slight decentralisation of jobs and a mode shift away from private transport between 2011 and 2016.

So we need to dig deeper to find out what’s going on here.

How does private mode share vary by distance from the city centre?

The following chart shows private transport mode shares by distance from the city centre for the last two or three censuses for each city. The darkest line for each city is for 2016, with lighter lines being previous years (I only have 2006 data for Melbourne and Sydney).

There’s a clear pattern in all cities that private mode shares are lower in areas closer to the city centre, with Sydney the lowest, followed by Melbourne, Brisbane, Perth, Adelaide, and Canberra (which is also the order of their population size).

Notably Sydney private mode share averaged lower than 90% out as far as 24km from the city centre, whereas Adelaide sees 90% mode shares as close as 2km from the city centre.

If you look carefully you can see that Brisbane increased private transport mode shares in the central city between 2011 and 2016, while private mode shares dropped or were stable in all other cities at most distances.

You can also see that the central city mode shifts away from private transport were largest in Melbourne, something I’ll come back to.

Here’s the same again but for public transport:

Sydney and Melbourne saw mode shifts to public transport at most distances from the city centre, unlike all other cities.

What mode shift can we attribute to changing job distributions?

A city’s mode share (measured by place of work) will be fundamentally impacted by two types of changes between censuses:

Changes in the volume of jobs in each SA2 – because different SA2s generally have different mode shares due to factors like proximity to the city centre and public transport access. If there is stronger jobs growth in areas that already had lower private mode shares, you would get a mode shift away from private transport, all other things being equal.
Changes in the mode share in each SA2 – because different modes became more or less attractive for commuters between census years. This might be due to changes in public transport service quality, transport infrastructure provision, and relative changes in the cost of public transport, private motoring, and commuter parking. It could also be influenced by broader demographic changes.

For each city I have calculated what the city-level private transport mode share would have been in 2016, had mode shares in each workplace SA2 remained exactly the same as 2011, but the job volumes in each SA2s had still changed. The city level mode shift due to SA2 volume changes is then the difference between this hypothetical 2016 mode share and the 2011 mode share. The remainder of the city-level mode shift between 2011 and 2016 results can then be attributed to mode shifts at the SA2 level.

Here’s a chart showing the mode shift impact of both volume changes at the SA2 level, and mode shifts at the SA2 level:

As we noted above, Sydney saw a slight trend to centralisation of jobs between 2011 and 2016, and it had the largest volume change attributed reduction in private mode share (-0.4%). However other factors were responsible for a further 2.5% of the mode shift away from private transport.

The story is similar in Melbourne but to a smaller magnitude in both aspects. Both of these cities also saw increasing inner city job density – which matters – and I’ll back come to that in a moment.

In Brisbane you can see that the total mode shift towards private transport was roughly equally attributable to SA2 volume changes and SA2 mode shifts (as I discussed in my earlier post).

Perth had an overall 1.3% mode shift to private transport, and the majority of this was due to significant jobs growth in the suburbs compared to the CBD (in fact, the SA2 with the largest jobs growth was Murdoch in the southern suburbs). But there were also other factors that led to a mode shift to private transport.

In Canberra – Queanbeyan, volume changes by themselves would have seen a mode shift to private transport, but other factors were larger and led to an overall mode shift away from private transport (although it is actually complicated because the 2011 census day was in a federal parliamentary sitting week, while 2016 was not).

Nothing much changed in Adelaide.

Next I’m going to explore what could be behind the mode shifts at SA2 level, in terms of job density and real transport costs.

Can increases in workplace density impact mode shares?

As discussed in my Brisbane analysis, if the relative attractiveness of modes hadn’t changed, you might still expect a mode shift to public transport in high density employment areas with increasing jobs numbers because you would expect the cost of parking provision to increase with increasing land use density (i.e. more competition for space).

Indeed, in Sydney and Melbourne a number of inner city SA2s became significantly more job dense between 2011 and 2016, and also saw mode shifts away from private transport:

(inspect this data in Tableau)

A similar thing happened in Civic (the main centre of Canberra).

But Adelaide and Perth saw both declining job density and declining private transport mode share, which suggests something else is at play.

Job density didn’t really go down in Brisbane – see my Brisbane post for an explanation (basically, ABS redrew the SA2 boundary along the Brisbane River).

Could changes in the real cost of transport be causing mode shifts?

The following chart shows the real change in urban transport fares in Australian cities since 2000, as measured by the ABS as part of the Consumer Price Index series (which unfortunately includes public transport, taxis, and “ride share” but is for a representative sample of journeys so hopefully mostly dominated by public transport fares):

The lines are somewhat saw-toothed because public transport fares generally only rise once a year, and become better value in real terms over the course of the following 12 months.

Many cities have seen above-CPI public transport fare increases at various times, most notably Brisbane in 2010-2014. Melbourne has had above CPI fare increases, but also reduced zone 1+2 fares in 2015 which lead to a reduction on the ABS measure (the fare reduction only really applied to people travelling across zones 1 and 2 – which roughly summarised means travel between the outer and inner suburbs). Brisbane fares peaked in 2014, which was followed by a freeze and then a large reduction in 2017.

By contrast, here is the (negative) growth in the cost of “private motoring” (which includes vehicles, fuel and maintenance):

Private motoring costs have declined in real terms since 2000, although they increased a little during the second half of 2017.

The next chart shows the change in ratio between the two costs. Urban transport fares have become less competitive than private motoring over time in all cities:

But if we are looking at changes between census figures, we should probably also look at cost changes between the times of each census. Here’s how prices changed in real terms between the September quarters of 2011 and 2016 (which cover the August census dates):

The real cost of private motoring dropped in all cities, but so did the real “average” cost of urban transport fares in Sydney and Melbourne (the Melbourne drop being mostly around large fare reductions for travel across zones 1 and 2).

The biggest differences in cost changes were in Brisbane and Perth (around 18%), which I think will go a fair way to explaining why these cities had the biggest shifts to private transport attributable to SA2 mode shifts.

Brisbane saw a rapid increase in public transport fares between 2011 and 2014 which is likely to have changed many commuting habits, but those habits may or may not have changed back when fares were subsequently reduced (e.g. if someone bought a car due to fare increases, they may not have subsequently sold their car when fares reduced). Perth certainly had less mode shift at the SA2 level compared to Brisbane, which might support this hypothesis.

What about changes in car parking costs?

The ABS CPI’s private motoring cost index does not include car parking costs – which would be difficult as they vary considerably with geography.

However we do know about central city car parking levies that governments charge in a bid to reduce road congestion and fund inner city transport initiatives. Sydney, Melbourne, and Perth apply levies to central city non-residential car parking spaces, and ultimately these levies will need to be recovered through parking prices.

I’ve calculated these levies in 2017 dollars (adjusting for inflation as measured in June quarters), and here’s how they have changed since 2000:

Melbourne increased its central city parking levy by 40% per space in 2014 (category 1), and created a new lower-priced levy area in some neighbouring areas to the north and south in 2015 (category 2, see map). This is likely to have contributed to the larger mode shifts away from private transport in the central city area of Melbourne compared to most other cities (particularly considering there were similar changes in average private motoring and urban transport fares in Melbourne between 2011 and 2016).

Sydney’s category 1 fee applies in the Sydney CBD area, Milsons Points and North Sydney. It was $2390 in 2017, and has only risen with indexation since 2009 (when it was doubled). A lower category 2 levy applies in the business districts centres of Bondi Junction, Chatswood, Parramatta, and St Leonards.

Perth has an annual licence fee per bay which ranged from $1039 to $1169 in 2017. The Perth fee was increased by around 167% in 2010, and there were also above-inflation increases from 2014. The fee increased 63% in real terms between 2011 and 2016 for “long stay” spaces, and 69% for “tenant” spaces.

I am not aware of any such fees or levies in place in Brisbane or Adelaide (a proposal for Adelaide was voted down).

So how are CBD parking prices changing?

Unfortunately good data is a little hard to find, but this Colliers Car Parking White Paper provides “average daily rates” for CBDs for 2009-2015, and early bird rates for 2015. I expect most commuters would pay early bird rates – which average between 28% and 62% of daily rates depending on the city (quite some variation!). I’ve adjusted the pre-2015 figures for inflation to be in 2015 dollars:

In real terms, “average daily” parking costs have declined in Melbourne, rocketed up in Brisbane and Canberra, and moved less in Sydney and Perth. I don’t know whether these reflect trends in early bird prices. And we don’t know how prices changed between 2015 and the census year of 2016.

So how much are parking levies contributing to parking prices?

I have to make some assumptions (guesstimates) here. Regular weekdays represent about 60% of the days of the year. If we assume say 80% of the levy is recovered from weekday commuter parking (there generally being less demand for parking on weekends), we can calculate the average weekday commuter cost of the levy to be 27% of the Sydney early bird price, 25% of the Melbourne early bird price, and 15% of the Perth early bird price. Certainly not insignificant.

Here’s a summary of the levy and “average daily” price changes and mode shifts in the central city parking levy areas:

Changes 2011 to 2016
Parking levy area or CBD SA2	Levy real increase	Average daily real price change (2011 to 2015)	Private mode shift	New private trips	Private share of new trips
Perth	63%	-5%	-0.8%	-60	-3%
Melbourne – category 1	40%	-11%	-5.3%	3200	5%
Melbourne – category 2	(new)	n/a	-6.4%	5315	30%
Sydney CBD	0%	+1%	-2.6%	6204	9%
Brisbane City SA2	n/a	+64%	+1.7%	3135	68%
Adelaide SA2	n/a	-11%	-1.5%	2567	35%
Canberra Civic SA2	n/a	+71%	-3.2%	746	30%

Firstly, “average daily” parking prices don’t seem to be following the changes in parking levies in Perth and Melbourne (category 1 area). Other factors influencing parking prices will include supply (influenced by competition for real estate and planning rules) and demand (influenced by employment density) with the market ultimately determining prices.

Car park operators appear to be absorbing the increased cost of the levy (although we don’t know the trends in early bird prices so we cannot be entirely sure). But that’s not to say that the levy hasn’t had any impact on prices – for example, the price reductions might have been larger if the levies had not increased.

Secondly, price changes do not appear to be correlated with mode shifts as you might expect (except Canberra). Brisbane prices increased dramatically, but so did private mode share! Price reductions in Perth, Adelaide, and Melbourne did not result in increased private transport shares.

Maybe other factors are driving mode shift away from private transport in those cities. Maybe early bird prices are trending differently to “average daily” prices. Maybe increased traffic congestion persuaded people to shift modes. Maybe there were significant price changes between 2015 and 2016. Maybe most existing public transport users were not aware of reductions in parking prices.

I don’t know what happened to parking prices in the new category 2 areas of Melbourne but there was a large mode shift away from private transport (-6.4%), and they may well be linked. Indeed, Infrastructure Victoria has recently recommended the category 2 area be expanded to include the inner-eastern suburbs of Richmond, South Yarra, Windsor and Prahran. And the Grattan Institute has recommended increasing the levy to match Sydney’s rates.

Curiously, when I look at City of Melbourne Census of Land Use and Employment (CLUE) data, the category 1 area (approximated with CLUE areas) had an increase of only around 367 non-residential parking bays between 2011-12 and 2015-16 (a four year period), a lot less than the additional 3200 private trips, which might suggest increased average occupancy.

Also, it is likely that a significant portion of people who drive to city centres are not paying for their parking costs (eg employer provided car parking). Employers may simply be absorbing price increases.

For more interesting discussion and research about car parking in the City of Melbourne, see a recent discussion paper and background report prepared by Dr Elizabeth Taylor.

Did changes in population distribution impact mode shares?

While this post has been focused on changes by workplace location, it is possible to separate the overall mode shifts into the two components by home location. Here are the results:

In Sydney, Melbourne, and Canberra, stronger population growth in areas that already had low private mode shares in 2011 made a small contribution to overall mode shifts away from private transport. These cities have all seen densifying population in inner city areas better served by public transport.

The distribution of population growth in Perth and Brisbane had a small effect in the opposite direction.

And again, nothing much changed in Adelaide.

What about active transport?

Cycling-only mode share was pretty stable in most cities (except Canberra up 0.2%). Walking-only mode share declined in Sydney (-0.2%), Brisbane (-0.3%), Adelaide (-0.4%), Perth (-0.3%) but was steady in Melbourne and increased in Canberra (+0.2%). So Canberra has the biggest shift to active transport.

Can you summarise all that?

If your head is spinning with all that information, here’s a summary of what some of the major factors could be in each city between 2011 and 2016. I say “could be” because I’ve not looked at every possible factor influencing mode share.

Sydney: the 2.9% mode shift away from private transport was probably mostly to do with increasing job density in employment centres (more on that in my next post), but was also partly by a shift to more centralised jobs, and increasing population density in places well served by public transport.

Melbourne: The 1.8% mode shift away from private transport probably had a fair bit to do with increasing central city job density, the significant spatial expansion of the central city parking levy area and rates (although we don’t know if early bird prices also rose), a reduction in some public transport fares, and strong population growth in areas well served by public transport.

Brisbane: The 1.9% mode shift towards private transport appears roughly half about the decentralisation of jobs, and half the reduced attractiveness of public transport – particularly following significant fare rises between 2010 and 2014, and possibly/arguably declines in service quality.

Perth: The 1.2% mode shift towards private transport was probably mostly due to a decentralisation of jobs, and partly due to public transport becoming less cost competitive with private transport (despite an increase in the central city parking levy). Urban sprawl is probably also a factor.

Adelaide: The 0.2% mode shift to private transport is probably mostly due to public transport becoming less cost competitive with private transport. Changes in job and population distribution, and employment density do not appear to have had a significant impact.

Canberra: The 1.0% mode shift away from private transport was probably the result of competing forces of higher jobs growth in car-dominated workplace areas with increasing job density in dense employment centres, increasing central city parking prices, higher population growth in areas better served by public transport (and possibly cycling facilities), and also the fact census 2016 was not a parliamentary sitting week while 2011 was (so really, it’s hard to be too sure!).

You might want to add your own views about changes in the service quality of public transport and cycling infrastructure in each city. I also haven’t looked at the impact of major new public transport infrastructure and service initiatives (such as the opening of new train stations), which we know does impact mode shares at a local level (maybe that’s for a future post).

I hope you found this interesting. My next post will look at suburban employment centres, and their role in changing mode shares in cities.

2 Comments | Australian Cities, Brisbane, Employment density, Melbourne, Mode shift, Pricing, Sydney, Urban density | Tagged: car parking, Census Journey to Work, Density, Pricing | Permalink
Posted by chrisloader

Charting Transport

What might explain journey to work mode shifts in Australia’s largest cities?

How is job distribution changing in Australian cities?

How does private mode share vary by distance from the city centre?

What mode shift can we attribute to changing job distributions?

Can increases in workplace density impact mode shares?