Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in California

• Published in: Transportation (Dordrecht) 2020-10, Vol.47 (5), p.2505-2528
• Main Authors: Lee, Yongsung, Circella, Giovanni, Mokhtarian, Patricia L., Guhathakurta, Subhrajit
• Format: Article
• Language: English
• Subjects: Age differences; Attitudes; Birth; Built environment; Childbirth & labor; Cluster analysis; Demographics; Economic crisis; Economic Geography; Economics; Economics and Finance; Engineering Economics; Generation X; Heterogeneity; Innovation/Technology Management; Latent class analysis; Logistics; Marketing; Millennials; Mobility; Multimodality; Organization; Regional/Spatial Science; Stereotypes; Travel; Urban environments; Young adults
• ISSN: 0049-4488; 1572-9435
• DOI: 10.1007/s11116-019-10026-6

Millennials tend to use a variety of travel modes more often than older birth cohorts. Two potential explanations for this phenomenon prevail in the literature. According to the first explanation, millennials often choose travel multimodality at least in part because of the effects of the economic crisis, which affected young adults more severely than their older counterparts. Another explanation points to the fact that millennials may have fundamentally different preferences from those of older birth cohorts. This paper presents an examination of millennials’ travel behavior as compared to the preceding Generation X, based on a survey of 1069 California commuters. It shows that millennials adopt multimodality more often than Gen Xers, on average. However, the analysis also points to substantial heterogeneity among millennials and indicates that, perhaps contrary to expectations and the stereotype in the media, the majority of millennials are monomodal drivers in California. The paper contributes to the literature on millennials’ mobility in several ways. First, it rigorously classifies various forms of travel multimodality (on a monthly basis and distinctively taking trip purpose into account) through the analysis of a rich dataset that includes individual attitudes and preferences; second, it explores gradual changes of multimodality across age and generation; and third, it analyzes the effects of various demographic, built environment, and attitudinal attributes on the adoption of multimodality.