Considerable interest has developed recently in the decision-making processes underlying activity schedule adjustment. This paper suggests a method, based on sequence alignment techniques, to measure schedule adjustment behavior and applies the method to develop a model of the factors influencing schedule adjustment, with the use of data from a recent Internet-administered survey. The results indicate that the amount of schedule modification that occurs is largely determined by characteristics of the planned schedule instead of background socioeconomic or activity-related variables. The implications of this finding for future research in this area are considered.
Get full access to this article
View all access options for this article.
References
1.
BhatC. R., and KoppelmanF. S.. A Retrospective and Prospective Survey of Time-Use Research.Transportation, Vol. 26, 1999, pp. 119–129.
2.
ArentzeT. A., and TimmermansH. J. P.. Albatross: A Learning-Based Transportation Oriented Simulation System.European Institute of Retailing and Services Studies, The Hague, Netherlands,2000.
3.
TimmermansH. J. P., ArentzeT. A., and JohC. H.. Analyzing Space-Time Behavior: New Approaches to Old Problems.Progress in Human Geography, Vol. 26, 2002, pp. 175–190.
4.
GärlingT., BrännäsK., GarvillJ., GolledgeR. G., GopalS., HolmE., and LindbergE.. Household Activity Scheduling.Transport Policy, Management and Technology Towards 2001: Selected Proceedings of the Fifth World Conference on Transport Research, Vol. 4, 1989, pp. 235–248.
5.
EttemaD., BorgersA., and TimmermansH. J. P.. Using Interactive Computer Experiments for Investigating Activity Scheduling Behavior.Proc., PTRC 21st Summer Annual Meeting, University of Manchester, P366, 1993, pp. 267–282.
6.
EttemaD., BorgersA., and TimmermansH. J. P.. SMASH (Simulation Model of Activity Scheduling Heuristics): Empirical Test and Simulation Issues. Presented at Conference on Activity-Based Approaches: Activity Scheduling and the Analysis of Activity Patterns, Eindhoven, Netherlands, 1995.
7.
ChenC., and KitamuraR.. On What People Schedule and What They Actually Do. Presented at 9th International Conference on Travel Behaviour Research, Gold Coast, Australia, 2000.
8.
DohertyS. T., and MillerE. J.. A Computerized Household Activity Scheduling Survey.Transportation, Vol. 27, 2000, pp. 5–23.
9.
GärlingT., GillholmR., and MontgomeryW.. The Role of Anticipated Time Pressure in Activity Scheduling.Transportation, Vol. 26, 1999, pp. 173–192.
10.
JohC.-H., ArentzeT., and TimmermansH.. Modeling Individuals’ Activity-Travel Rescheduling Heuristics: Theory and Numerical Experiments. In Transportation Research Record: Journal of the Transportation Research Board, No. 1807, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 16–25.
11.
EttemaD., and TimmermansH.. Modeling Departure Time Choice in the Context of Activity Scheduling Behavior. In Transportation Research Record: Journal of the Transportation Research Board, No. 1831, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 39–46.
12.
EttemaD., TammingaG., TimmermansH. J. P., and ArentzeT.. A Micro-Simulation Model System of Departure Time and Route Choice Under Travel Time Uncertainty. Presented at 10th International Conference on Travel Behaviour Research, Lucerne, Switzerland, 2003.
13.
PolakJ., and HazeltonM.. The Influence of Alternative Traveler Learning Mechanisms on the Dynamics of Transport Systems.Transportation Planning Methods, Vol. 1, 1998, pp. 83–95.
14.
ArentzeT. A., and TimmermansH. J. P.. Modeling Learning and Adaptation Processes in Activity-Travel Choice.Transportation, Vol. 30, 2003, pp. 37–62.
15.
ArentzeT. A., and TimmermansH. J. P.. A Theoretical Framework for Modeling Activity-Travel Scheduling Decisions in Non-stationary Environments Under Conditions of Uncertainty and Learning. Presented at Conference on Progress in Activity-Based Analysis, Maastricht, Netherlands, 2004.
16.
GärlingT., GillholmR., RomanusJ., and SelartM.. Interdependent Activity and Travel Choices: Behavioral Principles of Integration of Choice Outcomes. In Activity-Based Approaches to Travel Analysis (Ettema andD. F., TimmermansH. J. P., eds.), Pergamon, Oxford, United Kingdom, 1997, pp. 135–149.
17.
BurnettP., and HansonS.. Analysis of Travel As an Example of Complex Human Behaviour in Spatially-Constrained Situations: Definition and Measurement Issues.Transportation Research Part A, Vol. 16, 1982, pp. 87–102.
18.
KoppelmanF. S., and PasE. I.. Travel-Activity Behaviour in Time and Space: Methods for Representation and Analysis. In Measuring the Unmeasurable (NijkampP., LeitnerH., and WrigleyN., eds.), Martinus Nijhoff, Amsterdam, 1985, pp. 587–627.
19.
ReckerW. W., and McNallyM. G.. Travel/Activity Analysis: Pattern Recognition, Classification and Interpretation.Transportation Research Part A, Vol. 19, 1985, pp. 279–296.
20.
WilsonC.Activity–Travel Pattern Analysis by Means of Sequence Alignment Methods.Environment and Planning A, Vol. 30, 1998, pp. 1017–1038.
21.
JohC.-H., ArentzeT., and TimmermansH.. Pattern Recognition in Complex Activity Travel Patterns: A Comparison of Euclidean Distance, Signal-Processing Theoretical, and Multidimensional Sequence Alignment Methods. In Transportation Research Record: Journal of the Transportation Research Board, No. 1752, TRB, National Research Council, Washington, D.C., 2001, pp. 16–22.
22.
JohC.-H., ArentzeT. A., and TimmermansH. J. P.. Multidimensional Sequence Alignment Methods for Activity-Travel Pattern Analysis: A Comparison of Dynamic Programming and Genetic Algorithms.Geographical Analysis, Vol. 33, 2001, pp. 247–270.
23.
JohC.-H., ArentzeT. A., HofmanF., and TimmermansH. J. P.. Activity–Travel Pattern Similarity: A Multidimensional Alignment Method.Transportation Research Part B, Vol. 36, 2002, pp. 385–403.
24.
RuizT.Design of a Four-Week Activity Scheduling Survey Using Internet. Presented at Conference on Progress in Activity-Based Analysis, Maastricht, Netherlands, 2004.
