@article {Paula:2014:2032-927X:1,
title = "Towards using Segmentation-based Techniques to Personalize Mobility Behavior Interventions",
journal = "EAI Endorsed Transactions on Ambient Systems",
parent_itemid = "infobike://doaj/2032927x",
publishercode ="doaj",
year = "2014",
volume = "1",
number = "4",
publication date ="2014-01-01T00:00:00",
pages = "1-6",
itemtype = "ARTICLE",
issn = "2032-927X",
url = "https://www.ingentaconnect.com/content/doaj/2032927x/2014/00000001/00000004/art00005",
doi = "doi: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{\"a}",
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.",
}