The current research advances an interdependence analysis of commuting decisions (i.e. commuting by car versus public transportation), delineating the determinants of an individual's outcomes in terms of own decisions, other commuters' decisions, and the combination or interaction of own and others'
An analysis of the commuter departure time decision
โ Scribed by Mark D. Abkowitz
- Publisher
- Springer US
- Year
- 1981
- Tongue
- English
- Weight
- 808 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0049-4488
No coin nor oath required. For personal study only.
โฆ Synopsis
Transportation planners and transit operators alike have become increasingly aware of the need to diffuse the concentration of peak period travel in an effort to improve gasoline economy and reduce peak load requirements. An evaluation of the potential effectiveness of strategies directed to achieve this end requires an understanding of factors which affect commuter trip timing decisions. The research discussed in this article addresses this particular problem through the development and estimation of a commuter departure time (to work) choice model.
A number of conclusions were drawn based on the departure time model results and related analyses. It was found that work schedule flexibility, mode, occupation , income, age, and transportation level of service all influence departure time choice. The uncertainty in work arrival time and the consequences of various work arrival times may also be determinants of commuter departure time choice.
The estimated model represents improvements over previous work in that it more explicitly considers work arrival time uncertainty and travelers' perceived loss associated with varying work arrival times, and additional socio-demographic factors which can potentially affect departure time choice. Furthermore, the estimated model includes consideration of transit commuters, in addition to single occupant auto and carpool work travelers. The inclusion of transit commuters represents a particularly important contribution for policy analysis, since the model could potentially be used to study the effect of service and employment policies on transit system peak load requirements.
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