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Estimating Marginal Mental Efforts of Activity Schedule Adjustment Operators by Using Sequence Alignment Joh, Chang-Hyeon ; Ettema, Dick ; Timmermans, Harry

By: Contributor(s): Series: ; 2134Publication details: Washington DC Transportation Research Record: Journal of the Transportation Research Board, 2009Description: s. 171-177ISBN:
  • 9780309142663
Subject(s): Bibl.nr: VTI P8167:2134Location: Abstract: Results are reported of a study that attempts to estimate marginal mental efforts of various operators (delete activity, insert activity, substitute activity) from activity rescheduling data by using sequence alignment as a measure of the amount of effort. The study makes several contributions to the literature on activity-based analysis and modeling. First, it is one of the few attempts to examine the decision process supposed to lead to the decision outcome, focusing on mental effort. Second, it adopts sequence alignment methodology not as a means of calculating the (dis)similarity between activity profiles, but as a measure of mental effort. A genetic algorithm is used to derive the weights of mental effort attached to each type of operator. Results, derived from a computer-based activity diary instrument, support the suggested approach in that observations can be successfully reproduced and that the estimated marginal mental efforts are consistent with general theory.
Item type: Reports, conferences, monographs
Holdings
Current library Status
Statens väg- och transportforskningsinstitut Available

Results are reported of a study that attempts to estimate marginal mental efforts of various operators (delete activity, insert activity, substitute activity) from activity rescheduling data by using sequence alignment as a measure of the amount of effort. The study makes several contributions to the literature on activity-based analysis and modeling. First, it is one of the few attempts to examine the decision process supposed to lead to the decision outcome, focusing on mental effort. Second, it adopts sequence alignment methodology not as a means of calculating the (dis)similarity between activity profiles, but as a measure of mental effort. A genetic algorithm is used to derive the weights of mental effort attached to each type of operator. Results, derived from a computer-based activity diary instrument, support the suggested approach in that observations can be successfully reproduced and that the estimated marginal mental efforts are consistent with general theory.