Personas: A market segmentation approach for transportation behavior change

Ali Arian, Melrose Meiyu Pan, Yi Chang Chiu

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

6 Scopus citations

Abstract

This paper proposes a market segmentation method applied in the field of transportation behavior change using GPS trajectories and socio-demographic data collected from the advanced demand management system ‘‘GoEzy’’ designed by Metropia. User attributes are extracted using several statistical methods such as dynamic time warping, density-based spatial clustering of applications with noise (DBSCAN), and signal processing method to infer users’ sensitivity to incentives, temporal, and spatial travel patterns. Ten personas were generated by K-means clustering, representing different types of people with various travel patterns and sensitivity to incentives. The experiment was conducted on 24 new users to test if the persona could be used as a tool to predict their willingness to change. The results showed that after creating personas for new users and providing them with new incentives, their modified departure time pattern according to the new incentives matched expectations from analysis of the 10 personas.

Original languageEnglish
Title of host publicationTransportation Research Record
PublisherSAGE Publications Ltd
Pages172-185
Number of pages14
Volume2675
Edition11
DOIs
StatePublished - 2021
Externally publishedYes

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