TY - CHAP
T1 - Personas
T2 - A market segmentation approach for transportation behavior change
AU - Arian, Ali
AU - Pan, Melrose Meiyu
AU - Chiu, Yi Chang
N1 - Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2021.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85118204014&partnerID=8YFLogxK
U2 - 10.1177/03611981211028623
DO - 10.1177/03611981211028623
M3 - Chapter
AN - SCOPUS:85118204014
VL - 2675
SP - 172
EP - 185
BT - Transportation Research Record
PB - SAGE Publications Ltd
ER -