Harrison, G orcid.org/0000-0002-4324-772X, Grant-Muller, SM and Hodgson, FC (2022) Understanding the influence of new and emerging data forms on mobility behaviours and related health outcomes. Journal of Transport and Health, 24. 101335. ISSN 2214-1405
Abstract
Introduction
Transport and health are complex, evolving and interacting systems, which are increasingly influenced by new and emerging data forms. In this study we address the research question, “How could New and Emerging Data Forms improve understanding of mobility behaviours, and the related health outcomes, of different population subgroups?”
Methods
We build on an existing causal loop diagram (CLD) of the transport-health system to include the influence of New Data & Technologies, through a novel online Delphi approach to system dynamics modelling.
Results
We present an improved CLD of the transport-health system and have identified the potential influence that Persuasive & Monitoring Technologies could have on transport-related health, including insights on the characteristics for representing and assessing them.
Conclusions
The findings presented in this study can improve the design of holistic future-focused transport, health and data policies and the application of system dynamics to these areas, and as such are of relevance to researchers, policy makers and system dynamics practitioners.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | CLD; Causal Loop Diagram; SD; System Dynamics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Sustainable Transport Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Jul 2022 09:35 |
Last Modified: | 25 Jun 2023 23:02 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jth.2022.101335 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188680 |