amsys 14(4): e4

Research Article

Towards using Segmentation-based Techniques to Personalize Mobility Behavior Interventions

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  • @ARTICLE{10.4108/amsys.1.4.e4,
        author={Paula J. Forbes and Silvia Gabrielli and Rosa Maimone and Judith Masthoff and Simon Wells and  Antti Jylh\aa{}},
        title={Towards using Segmentation-based Techniques to Personalize Mobility Behavior Interventions},
        journal={EAI Endorsed Transactions on Ambient Systems},
        volume={1},
        number={4},
        publisher={ICST},
        journal_a={AMSYS},
        year={2014},
        month={10},
        keywords={persuasion, behaviour intervention. Segmentation, sustainability, mobility},
        doi={10.4108/amsys.1.4.e4}
    }
    
  • Paula J. Forbes
    Silvia Gabrielli
    Rosa Maimone
    Judith Masthoff
    Simon Wells
    Antti Jylhä
    Year: 2014
    Towards using Segmentation-based Techniques to Personalize Mobility Behavior Interventions
    AMSYS
    ICST
    DOI: 10.4108/amsys.1.4.e4
Paula J. Forbes1,*, Silvia Gabrielli2, Rosa Maimone2, Judith Masthoff1, Simon Wells3, Antti Jylhä4
  • 1: University of Aberdeen, Computing Science, Meston building, Meston Walk, Aberdeen, AB24 3UE, UK;
  • 2: Create-Net,Trento, Italy
  • 3: University of Aberdeen, Computing Science, Meston building, Meston Walk, Aberdeen, AB24 3UE, UK
  • 4: University of Helsinki, Finland
*Contact email: paula.forbes@abdn.ac.uk

Abstract

This paper describes our initial work towards a segmentation-based approach to personalized digital behavior change interventions in the domain of sustainable, multi-modal urban transport. Segmentation is a key concept in market research, and within the transport domain, Anable has argued that there are segments of travelers that are relatively homogenous in terms of their mobility attitudes and behaviors. We describe an approach aimed at tailoring behavior change notifications by using segmentation-based techniques for user profiling. We report results from a Mechanical Turk study in which we obtained a crowd-sourced categorization of motivational messages. This is a first step towards understanding how to better deliver persuasive messages to relevant users profiles and situational contexts in the urban mobility domain. We conclude by discussing future steps of our work that should inform the deployment of persuasion profiling techniques to achieve sustainable mobility goals.