Citation

Shi H, Xiao J, Su R, Goulias KG. Travel Behav. Soc. 2024; 36: e100807.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.tbs.2024.100807

PMID

unavailable

Abstract

Although the relationship between travel and quality of life has garnered much research interest, we find a gap in understanding the correlation among daily activity-travel patterns, location characteristics and happiness. In this study, the 2017 National Household Travel Survey (NHTS) in California and the 2017 and 2013 American Time Use Surveys (ATUS) are merged to estimate the happiness of daily activity-travel schedules. Prior to the merging of ATUS and NHTS data, hierarchical clustering is employed to identify and harmonize daily patterns. Then, the weighted duration proportion of each home activity for each daily patternand the average happy score for each activity are transferred from ATUS to NHTS. The individual happiness index issubsequentlycalculated for NHTS records and determinants of this index analyzed using an ordinary least square regression (OLS) model and a spatial lag model (SLM) to account for spatial correlation. The outcomes demonstrate that the SLM outperforms the OLS, with a better fit to the data and a smaller spatial correlation of unexplained variation. People's daily activity-travel pattern happiness is affected by their personal attributes, household characteristics, land use surrounding their residence, and added spatial correlation with the happiness of their neighbors. This analysis shows the feasibility and potential of transferring data between ATUS and NHTS, substantial and observable heterogeneity in the spatial clustering of happiness, and possible new ways of exploring emotions in activity-travel patterns.

Keywords

Happiness; Quality of life; Sequence analysis; Spatial analysis; Time use survey; Travel survey