UC Santa Barbara

Understanding daily rhythms of activity and travel behavior is fundamental for developing new generations of travel demand forecasting models. These models enable the design of transportation systems better customized to the needs of people living in a region or city. This thesis aims to understand daily activity and travel behavior of a previously unexplored country, Qatar. More specifically, the daily time allocation and travel behavior patterns within Qatar are explored. In addition, we investigate if there are differences in various nationalities and household types. Finally, findings from this thesis on Qatar are compared with published data from a Western country, the United States. Qatar offers a unique opportunity to identify any behavioral differences in daily activity and travel among ethnic groups while accounting for differences among household types (households with children and households without children). Based on existing literature, households from any ethnicity with children travel more than households without, and we do not expect any deviation in Qatar. Daily patterns are studied using survey data of 30,708 household residents and 1,047 laborers collected in Qatar during 2018. Laborers are defined as single, working-age, male foreigners who reside temporarily in Qatar on labor contracts. Household residents are immigrants or Qatari citizens living together with all members of their household, including family and non-family members. We applied sequence analysis jointly with cluster analysis for the laborers and the household residents to identify distinct travel behavior patterns. In addition, we used Multinomial Logit Regression (MNL) Models to study membership in different clusters of daily activity and travel patterns. Results for the laborer data reflect four daily patterns, but a simple pattern of going to work, working, and returning home is the most prominent. On the other hand, the results for household residents consisted of seven distinct daily patterns. These seven patterns include a group of people who stay at home all day; two workdays (with discernible differences in a lunch break and participation in after-work activities); two discretionary days (occurring at different times throughout the day); a pattern of mixed activities; and a school day. Cluster analysis reveals diverse schedules within Qatar and some apparent similarities with previously published patterns in the United States that used similar analytical techniques and data collection methods. Examples include commuting to and from work, which characterizes the morning movement from home to work locations and returning home in the afternoon. A key difference in the composition of the work week between the two countries is that Qatar’s work week begins on Sunday and ends on Thursday. A more in-depth look at the household types provided insights into differences among nationalities and household structure in travel behavior. The household residents in Qatar originate from 137 different countries. The multivariate analysis of the household residents using MNL models shows similarities in daily patterns for people from Qatar, Sudan, and Egypt compared to people from the Philippines and India. In Qatar, households with children travel slightly more than households without children, except for School Days. In addition, a large portion of the overall Qatar survey respondents are stay-at-home persons who are more likely to be women, domestic employees, and older adults. Overall, similar travel behavior patterns were detected within Qatar and the United States, indicating that current Western transportation policies could be transferred to Qatar. Furthermore, findings from this thesis can inform future research that seeks to explore whether the travel behavior patterns are region-specific or unique to a specific cultural and social context.