Abstract
Sustainable urban mobility planning (SUMP) plays a significant role as an integrated strategic management tool in enabling, among others, a participatory approach in urban transport development. A relevant aspect of the transition towards sustainable and smart mobility planning concerns the reconsideration of concepts such as Value of Travel Time (VTT). Rather than “cost of time spent in transport”, new perspectives on VTT aim at conceptualizing and measuring VTT based on individual needs, expectations and perceptions. Among others, attention is paid to individual experience in using transport infrastructure, services and systems while on the move. The ongoing shift towards a broader view of VTT gives importance to subjective “well-being” (SWB) and describes, in quantitative and qualitative terms, the individual value proposition of mobility (VPM). The opportunity to collect mobility and behavioral data via smartphones, to be processed with advanced analytical and modelling techniques, represents a pillar of such shift, since it allows identifying patterns embedded in individual daily activities and mobility choices. These patterns can be visualized to increase self-awareness and better understand one’s own value proposition of mobility.
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Acknowledgements
This article was published with the support of the MoTiV project, funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 770145. The paper was in part supported by the project ERAdiate – Enhancing Research and innovAtion dimensions of the University of Žilina in intelligent transport systems, cofunded from European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 621386.
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Lugano, G., Kurillova, Z., Hudák, M., Pourhashem, G. (2019). Beyond Travel Time Savings: Conceptualizing and Modelling the Individual Value Proposition of Mobility. In: Nathanail, E., Karakikes, I. (eds) Data Analytics: Paving the Way to Sustainable Urban Mobility. CSUM 2018. Advances in Intelligent Systems and Computing, vol 879. Springer, Cham. https://doi.org/10.1007/978-3-030-02305-8_86
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