The societal costs and benefits of commuter bicycling: simulating the effects of specific policies using system dynamics modeling.

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dc.contributor.author Macmillan, Alexandra en
dc.contributor.author Connor, Jennie en
dc.contributor.author Witten, Karen en
dc.contributor.author Kearns, Robin en
dc.contributor.author Rees, David en
dc.contributor.author Woodward, Alistair en
dc.date.accessioned 2018-11-01T21:01:37Z en
dc.date.issued 2014-04 en
dc.identifier.citation Environmental Health Perspectives 122(4):335-344 Apr 2014 en
dc.identifier.issn 0091-6765 en
dc.identifier.uri http://hdl.handle.net/2292/43743 en
dc.description.abstract BACKGROUND: Shifting to active modes of transport in the trip to work can achieve substantial co-benefits for health, social equity, and climate change mitigation. Previous integrated modeling of transport scenarios has assumed active transport mode share and has been unable to incorporate acknowledged system feedbacks. OBJECTIVES: We compared the effects of policies to increase bicycle commuting in a car-dominated city and explored the role of participatory modeling to support transport planning in the face of complexity. METHODS: We used system dynamics modeling (SDM) to compare realistic policies, incorporating feedback effects, nonlinear relationships, and time delays between variables. We developed a system dynamics model of commuter bicycling through interviews and workshops with policy, community, and academic stakeholders. We incorporated best available evidence to simulate five policy scenarios over the next 40 years in Auckland, New Zealand. Injury, physical activity, fuel costs, air pollution, and carbon emissions outcomes were simulated. RESULTS: Using the simulation model, we demonstrated the kinds of policies that would likely be needed to change a historical pattern of decline in cycling into a pattern of growth that would meet policy goals. Our model projections suggest that transforming urban roads over the next 40 years, using best practice physical separation on main roads and bicycle-friendly speed reduction on local streets, would yield benefits 10-25 times greater than costs. CONCLUSIONS: To our knowledge, this is the first integrated simulation model of future specific bicycling policies. Our projections provide practical evidence that may be used by health and transport policy makers to optimize the benefits of transport bicycling while minimizing negative consequences in a cost-effective manner. The modeling process enhanced understanding by a range of stakeholders of cycling as a complex system. Participatory SDM can be a helpful method for integrating health and environmental outcomes in transport and urban planning. en
dc.format.medium Print-Electronic en
dc.language eng en
dc.relation.ispartofseries Environmental health perspectives en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights Reproduced with permission from Environmental Health Perspectives en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri https://ehp.niehs.nih.gov/authors/promote-your-work en
dc.subject Humans en
dc.subject Models, Theoretical en
dc.subject Bicycling en
dc.subject Transportation en
dc.subject Cost-Benefit Analysis en
dc.subject New Zealand en
dc.title The societal costs and benefits of commuter bicycling: simulating the effects of specific policies using system dynamics modeling. en
dc.type Journal Article en
dc.identifier.doi 10.1289/ehp.1307250 en
pubs.issue 4 en
pubs.begin-page 335 en
pubs.volume 122 en
dc.rights.holder Copyright: The authors en
dc.identifier.pmid 24496244 en
pubs.end-page 344 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Research Support, Non-U.S. Gov't en
pubs.subtype research-article en
pubs.subtype Journal Article en
pubs.elements-id 427106 en
pubs.org-id Medical and Health Sciences en
pubs.org-id Population Health en
pubs.org-id Epidemiology & Biostatistics en
pubs.org-id Science en
pubs.org-id School of Environment en
dc.identifier.eissn 1552-9924 en
pubs.record-created-at-source-date 2014-04-02 en
pubs.dimensions-id 24496244 en


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