Influence of Mode Use on Level of Satisfaction with Daily Travel Routine: A Focus on Automobile Driving in the United States

Abstract

How does the extent of automobile use affect the level of satisfaction that people derive from their daily travel routine, after controlling for many other attributes including socio-economic and demographic characteristics, attitudinal factors, and lifestyle proclivities and preferences? This is the research question addressed by this paper. In this study, data collected from four automobile-dominated metropolitan regions in the United States (Phoenix, Austin, Atlanta, and Tampa) are used to assess the impact of the amount of driving that individuals undertake on the level of satisfaction that they derive from their daily travel routine. This research effort recognizes the presence of endogeneity when modeling multiple behavioral phenomena of interest and the role that latent attitudinal constructs reflecting lifestyle preferences play in shaping the association between behavioral mobility choices and degree of satisfaction. The model is estimated using the generalized heterogeneous data model (GHDM) methodology. Results show that latent attitudinal factors representing an environmentally friendly lifestyle, a proclivity toward car ownership and driving, and a desire to live close to transit and in diverse land use patterns affect the relative frequency of auto-driving mode use for non-commute trips and level of satisfaction with daily travel routine. Additionally, the amount of driving positively affects satisfaction with daily travel routine, implying that bringing about mode shifts toward more sustainable alternatives remains a formidable challenge—particularly in automobile-centric contexts.

Evolution of Mode Use During the COVID-19 Pandemic in the United States: Implications for the Future of Transit

“…Latent constructs play a significant role in shaping mode choice. Environmental friendliness is associated with a lower propensity to use a private vehicle, a finding that is also reported in prior literature ( 16 , 17 ). The social interaction propensity factor is associated with a significant negative effect on work-from-home; indeed, those who enjoy social interactions are less likely to embrace a work-from-home modality in the post-pandemic period.…”

Does Ridehailing Use Affect Vehicle Ownership or Vice Versa? An Exploratory Investigation of the Relationship Using a Latent Market Segmentation Approach

“…The correlations between the two outcomes were positive in both segments, possibly indicating underlying correlated unobserved factors that favor private vehicle usage (personal cars as well as ridehailing vehicles). In contrast to transit and other nonmotorized modes, people generally preferred to travel in private vehicles owing to the greater convenience, comfort, and efficiency ( 26 ). The finding that this correlation was statistically significant and larger in Segment 2 (i.e., vehicle availability influences ridehailing frequency) also highlighted the underlying tendency toward the auto mode.…”

Multidimensional Analysis of Willingness to Share Rides in a Future of Autonomous Vehicles

“…This is likely to be a reflection of the greater exposure to technology experienced by individuals who are both workers and students. Households that constitute a nuclear family were less likely to be transit-oriented; households with children probably reside in lower density suburban neighborhoods and are therefore more car-oriented than other types of households that may reside in urban contexts ( 30 ). Lower income individuals were more transit-oriented whereas high-income individuals depicted a higher level of trust in AV technology.…”

“…Following the pandemic, attitudes reflecting a transit-oriented lifestyle and discomfort around strangers are likely to have altered significantly. Future research is needed to explore the stability of attitudes and behaviors in a post-pandemic world, particularly in the context of emerging transportation technologies and their potential implications on the transportation system (34)(35)(36)(37)(38). On a related subject, one might question the relevance of the latent constructs considered in this study, given that only three latent variables were investigated from a wide range of alternatives.…”