Science and Technology

Working from home: Changes in transport demand in Perth

Changes in transport demand in Perth

Focusing on Perth, WA, this project aims to ascertain the extent to which Working from Home (WFH) has been undertaken and will continue to be.

Digging deeper, the project will look at aspects such as:

  • the productivity impact when WFH is compared to the workplace, from the perspectives of individuals, employers, and the economy at large
  • the proportion of reduced travel demand that is attributable to WFH
  • the utility of WFH as a future demand management tool for the mitigation of congestion on all transport networks
  • the potential for higher levels of WFH to enable expansions of the transport network to be deferred or avoided; and the facilitation steps that would be required if it became desirable to expand the level of WFH in the longer term

Participants

Project background

The COVID-19 lockdown in Australia saw significant changes to inhabitants’ activity and mobility patterns, brought about by swift changes to national and State regulations. There has been an unprecedented level of individuals’ experience with working from home (WFH), as well as increased participation in online learning, shopping and services (e.g. medical).

Although not as dramatic as in other countries and cities, in Perth, WA, the result of lockdown saw a significant drop in public transport patronage and traffic flows (by private car) and increases in walking and cycling (for transport and for recreation/health), as well as freight journeys (the latter considered an essential service).

While teleworking has been promoted as a travel demand management measure over the past two decades, there has been limited uptake in practice. In WA, the average homeworking rate was 3.4% of all employees, but with variation by occupation category – with administrative workers (6.3%), managers (5.0%) and professionals (4.8%) having greater proportions of homeworkers as compared to other occupation groups (Babb et al., 2017).

The COVID disruption saw an increase of 32% of employed workers working from home, and that is after accounting for job losses, with commensurate declines in traffic volumes, congestion levels, air pollution and increases in active modes (Beck & Hensher, 2020; De Vos, 2020). At the same time public transport patronage declined significantly.

This disruptive episode has highlighted a lack of in-depth knowledge on the spatial incidence of homeworking, the extent of travel reduction, and the use of local facilities (such as co-worker spaces) whilst WFH.

The lockdown period thus provides a unique opportunity to build new knowledge on these issues, on the back of actual experience, and develop approaches to perpetuate and mainstream some of the more positive behaviours and outcomes, in particular for employers, employees, transport infrastructure provision and macro-economic benefits.

See the full list of iMOVE projects here

Project objectives

Employer perspectives

A1:

To understand employer perspectives on working from home – selected by industry type; public/private sector; occupation type) to understand the extent to which their employees WFH is mandated, which groups of employees (aligned with ANZSIC classes); approaches to supporting and managing productivity, productivity outcomes; policy toward travel modes permitted to travel to workplace; attitudes towards continued WFH practices – support needs and wider policy issues.

A2:

To understand employee perspectives on working from home and how they are changing – stratified by industry, by type of occupation (aligned with ANZSIC classes) and spatially – focus on: the extent of time they worked from home; the extent to which in-home-based activities replaced out-of-home activities; the changes to their travel patterns; the experience of WFH; the desire to continue working from home (by frequency of WFH, by time-of-day, by changes to internal home environment needed if it were to become permanent, by expectations of facilities they would need in their local neighbourhood to support WFH).

B1: Transport demand

To estimate transport demand changes – making use of insights from Employer and Employee perspectives (A1 and A2), the study will translate employers and employees’ appetite and ability for continued WFH practices into scenarios of reduced commuting, with a focus on the level of reduced demand in the peak.

Indicative results from A1 and A2 will be translated into quantifiable measures and used to form transport impact matrices for different industry/occupation classes and demographics eg. age group. Assumptions about the levels of WFH and new activity patterns help shape scenarios that will feed into the WA Strategic Transport Modelling Framework STEM for assessing traffic impacts.

B2: Scenarios-based network impacts

To determine scenario-based network impacts – explore the impact of WFH on the multi-modal transport network of Perth.

C1: Economic and social benefits

To value the economic and social benefits of working from home – estimated from easy to measure changes to travel demand, uncertain changes to organisational productivity, and complex and integrated economic processes due to shifts in household consumption patterns.

C2: Policy response

To provide broad guidelines on the appropriate policy response including the likely net savings of WFH, magnitude of WFH expected by industry and employees, recommendations for employers and transport agencies, as well as pathways to achieve traffic reductions and consequently decreased needs for further infrastructure investments.

References

Australian Bureau of Statistics (ABS) (2019), 1220.0 – ANZSCO – Australian and New Zealand Standard Classification of Occupations, First Edition, Revision 1

Allen, T.D., Golden, T.D. & Shockley, K.M. (2015) How Effective Is Telecommuting?Assessing the Status of Our Scientific Findings, Psychological Science in the Public Interest, 16(2), 40-68.

Babb, C., Curtis, C. McLeod, S., & Robertson, D. (2017) Unlocking the potential for working closer to home, Bankwest Curtin Economics Centre, Perth.

Babb, C., Smith, B., Moniruzzaman, M. & Biermann, S. (2014) Congestion abatement through travel demand management: Review of TDM instruments and appraisal and evaluation tools, Planning and Transport Research Centre (PATREC).

Banister, D. & Stead, D. (2004) Impact of information and communications technology on transport. Transport Reviews, 24(5), 611-632.

Beck, M. & Hensher, D.A. (2020) Insights into the Impact of Covid‐19 on Household Travel, Working, Activities and Shopping in Australia – the early days under restrictions. Institute of Transport and Logistics Studies (ITLS) Working Paper.

Cafiso, S., Di Graziano, A., Pappalardo, G. (2013) Using the Delphi method to evaluate opinions of public transport managers on bus safety. Safety Science, 57, 254-263.

Corpuz, G. (2011). An empirical assessment of teleworking using the Sydney Household Travel Survey data. In Australasian Transport Research Forum, Adelaide, 28-30 September, Australia.

De Graaff, T. & Rietveld, P. (2007) Substitution between working at home and out-of-home: The role of ICT and commuting costs. Transportation Research A, 41(2), 142-160.

De Vos, J. (2020) The effect of COVID-19 and subsequent social distancing on travel behaviour, Transportation Research Interdisciplinary Perspectives, Perspectives 5, April.

Dockery, A.M. & Bawa, S. (2014) Is working from home good work or bad work? Evidence from Australian employees. Australian Journal of Labour Economics, 17(2), 163-190.

Dockery, A.M. & Bawa, S. (2018). When two worlds collude: Working from home and family functioning in Australia. International Labour Review, 157(4), 609-630.

Fu, M., Kelly, J.A., Clinch, P., & King, F. (2012) Environmental policy implications of working from home: Modelling the impacts of land-use, infrastructure and socio-demographics. Energy Policy, 47, 416-423.

Google (2020) Mobility Changes, COVID-19 Community Mobility Report, 225 May 2020

Lee, J., Evers, U., Sneddon, J., Rahn, O., & Schwartz, S. (2019) What Do We Value?, Report of The Centre for Human and Cultural Values, UWA, ISBN 978-1-74052-412-4.

Martinus, K. & Biermann, S. (2018) Strategic Planning for Employment Self-Containment in Metropolitan Sub-Regions, Urban Policy and Research, 36(1), 35-47.

Monteiro, N.P. Straume, O.R., & Valente, M. (2019) Does remote work improve or impair firm labour productivity? Longitudinal evidence from Portugal. NIPE Working Papers 14/2019, NIPE – Universidade do Minho.

Nelson, P., Safirova, E., & Walls, M. (2007) Telecommuting and environmental policy: lessons from the ecommute program. Transportation Research D, 12(3), 195-207.

Nguyen, K. (2020) NSW coronavirus social-distancing rules introduced on public transport as authorities confirm one new death

Railsmart (2019) RailSmart Technical Report

Rietveld, P. (2011) Telework and the transition to lower energy use in transport: on the relevance of rebound effects. Environmental Innovation and Societal Transitions, 1(1), 146-151.

Schwartz., N. (2007). Attitude construction: Evaluation in context. Social Cognition, 25(5), 638-656.

Tang, W., Mokhtarian, P.L., & Handy, S.L. (2011) The impact of the residential built environment on work at home adoption and frequency: An example from Northern California. Journal of Transport and Land Use, 4(3), 3-22.

Tirachini, A.H. (2020) Coronavirus: what if we stop repeating that public transport is risky?

Wiggins, N. & Pryor, C. (2020) Coronavirus means changes for your workplace. And the commute there, The New Daily 2 June 2020.

Wooden, M. & Fok, Y.K. (2013) Working at Home: Whatever happened to the revolution? Families, Incomes and Jobs, 8, 106-113.

More from iMOVE Australia

Most Popular

ADVERTISEMENT

To Top