Incorporating social media in travel and activity choice models: conceptual framework and exploratory analysis. Issue 2 (3rd April 2018)

• Record Type: Journal Article
• Authors: Chen, Ying; Mahmassani, Hani S.; Frei, Andreas
• Is Part Of: International journal of urban sciences. Volume 22:Issue 2(2018)
• Page Start: 180
• Page End: 200
• Publication Date: 2018-04-03
• Subjects: Social network -- spatial data -- check-ins -- choice set generation -- travel behaviour dynamics; Cities and towns -- Pacific Area -- Periodicals; Cities and towns -- East Asia -- Periodicals; Urban ecology (Sociology) -- Pacific Area -- Periodicals; Urban ecology (Sociology) -- East Asia -- Periodicals; Cities and towns; Urban ecology (Sociology); Pacific Area; Electronic journals; Periodicals; 307.7609505
• DOI: 10.1080/12265934.2017.1331749
• Languages: English
• ISSNs: 2161-6779

Abstract

ABSTRACT: Location-based social networking data provide an important new dimension in understanding travel choice behaviour, providing high levels of location and time accuracy over long time frames in conjunction with explicit friendship network information. Such data allow examination of location choice dynamics and social networking aspects explicitly. This paper presents an exploration of social network based dynamics of choice set generation in the context of activity and travel choice behaviour, especially destination choice. Using data from an online location-based social network, the paper explores the spatiality of destinations and social network influence on travellers' destination choice in the Chicago metropolitan area. The results show that social relationships play a role in travellers' destination choices and that distance plays a strong role in social networks as in location choice. Connectivity through social network structure is examined jointly with individuals' spatial activity engagement; the number of virtual friends is found to significantly influence actual physical travel behaviour. Finally, caveats in using social networking data for behaviour analysis and planning are discussed.