Citation

Thaithatkul P, Seo T, Kusakabe T, Asakura Y. Transp. Res. Proc. 2019; 37: 401-408.

Copyright

(Copyright © 2019, Elsevier Publications)

DOI

10.1016/j.trpro.2018.12.209

PMID

unavailable

Abstract

In an era of highly developed information and communication technologies, social networks play an important role in all aspects of businesses, including transportation. The use of dynamic ridesharing systems, which are systems in which travelers can find partner(s) to share their upcoming rides in real time, is also expected to be affected by the information propagated by friends on social networks. In this study, we investigate how such information in both online and offline social networks affects travelers' decisions pertaining to ridesharing over days. Because travelers can choose which information to obtain, we also investigate whether the information collected only from nearby friends (in physical space) affects their decisions. To do this, we formulate a day-to-day behavior-based model of a dynamic ridesharing system.

RESULTS obtained from the numerical experiments, which are based on the formulated model, show that with the information propagation on social networks, the more friends that a traveler has, the greater is the number of travelers who use dynamic ridesharing systems.

Language: en

Keywords

day-to-day behavior adjustment; Dynamic ridesharing system; information propagation; social network