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Promoting active mobility: Evidence-based decision-making using statistical models

Author

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  • Hackl, Roland
  • Raffler, Clemens
  • Friesenecker, Michael
  • Kramar, Hans
  • Kalasek, Robert
  • Soteropoulos, Aggelos
  • Wolf-Eberl, Susanne
  • Posch, Patrick
  • Tomschy, Rupert

Abstract

Shifting traffic to active transport modes (eg. walking/cycling) poses one of the most promising ways of tackling the persisting challenges that arise from motorized traffic. However, planning and policy making in walking and cycling domains is frequently impeded by a small-scaled and heterogeneous political landscape that rarely acts based on evidence thus limiting cost-effectiveness and target achievement. This paper proposes a largely data-driven planning approach that builds upon aggregated statistical models explaining walking and cycling modal shares. In addition to investigating a comprehensive set of influencing factors in relevant fields such as environment, climate, infrastructure or demographics, we bring attention to the role of political and administrative commitment in aggregated modal share modeling. Results suggest that our holistic approach is feasible both methodologically and in terms of its applicability in planning practice. As a first step towards evidence-based decision making the incremental effects of individual planning measures can be simulated and thus be used to rank options according to their effectiveness. Another outcome lies in the data-driven identification of spatial target areas for specific agenda setting in terms of awareness, mobility behavior, infrastructure, settlement structure and other planning-relevant domains.

Suggested Citation

  • Hackl, Roland & Raffler, Clemens & Friesenecker, Michael & Kramar, Hans & Kalasek, Robert & Soteropoulos, Aggelos & Wolf-Eberl, Susanne & Posch, Patrick & Tomschy, Rupert, 2019. "Promoting active mobility: Evidence-based decision-making using statistical models," Journal of Transport Geography, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:jotrge:v:80:y:2019:i:c:s0966692318303077
    DOI: 10.1016/j.jtrangeo.2019.102541
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    References listed on IDEAS

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    1. Winston Yap & Jiat-Hwee Chang & Filip Biljecki, 2023. "Incorporating networks in semantic understanding of streetscapes: Contextualising active mobility decisions," Environment and Planning B, , vol. 50(6), pages 1416-1437, July.
    2. Ferretto, Laura & Bruzzone, Francesco & Nocera, Silvio, 2021. "Pathways to active mobility planning," Research in Transportation Economics, Elsevier, vol. 86(C).
    3. Bondemark, Anders, 2023. "Walk this way how do individuals with different preferences for active travel modes respond to walkability?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    4. Robin Lovelace, 2021. "Open source tools for geographic analysis in transport planning," Journal of Geographical Systems, Springer, vol. 23(4), pages 547-578, October.
    5. Pajares, Elias & Büttner, Benjamin & Jehle, Ulrike & Nichols, Aaron & Wulfhorst, Gebhard, 2021. "Accessibility by proximity: Addressing the lack of interactive accessibility instruments for active mobility," Journal of Transport Geography, Elsevier, vol. 93(C).

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