Travel-related decisions by bus, servis taxi, and private car commuters in the city of Amman, Jordan

Abstract The purpose of this study is to investigate travel-related decisions undertaken by private car, bus, and servis taxi commuters. Two disaggregate choice models are formulated and estimated. Choice models relate to two essential daily travel-related decisions such as the morning departure time to work and type of “after work” activity. Estimation results suggest among other findings that private car commuters' morning departure time decisions are very much influenced by the presence of young children, whereas bus and servis taxi commuters' departure time decisions are not influenced by the presence of children. In addition, bus and servis taxi commuters tend to pursue household maintenance activities and, less probably, to pursue a chain of activities after work, while private car commuters are likely to carry out a chain of activities after work. Results also show that both home and work locations have differential impacts on commuters' morning departure time decisions, type of “after work” activity, and the choice of mode to pursue the latter. The distance to “after work” activity seems to be instrumental in determining the type of activity to be pursued after work. In addition, the previous day waiting time at the bus or the servis taxi stop turned out to have a profound impact on bus and servis taxi commuters' morning departure time decisions. The work departure time affects the type of “after work” activity. Bus commuters are less likely to pursue social activities if they left work late, whereas private car commuters are likely to pursue social or household maintenance activities regardless of their work departure time. In summary, bus, servis taxi, and private car commuters have different travel patterns at least in the context of the two decisions addressed. These results enhance our understanding of the commuters' travel patterns and behavior, particularly those relating to type of activity after work. This understanding is likely to improve travel demand forecasting mechanisms and hence provide accurate estimates of “after work” travel demand.