Yin-Yen Tseng

Long-Run vs. Short-Run Perspectives on Consumer Scheduling: Evidence from a Revealed-Preference Experiment Among Peak-Hour Road Commuters

Earlier studies on scheduling behavior have mostly ignored that consumers have more flexibility to adjust their schedule in the long run than in the short run. We introduce the distinction between long‐run choices of travel routines and short‐run choices of departure times, using data from a real‐life peak avoidance experiment. We find that participants value travel time higher in the long‐run context, supposedly because changes in travel time can be exploited better through the adjustment of routines. Schedule delays are valued higher in the short run, reflecting that scheduling restrictions are typically more binding in the short run.

Stated Choice Experimental Designs for Scheduling Models

Abstract In this paper, we analyze statistical properties of stated choice experimental designs when model attributes are functions of several design attributes. The scheduling model is taken as an example. This model is frequently used for estimating the willingness to pay (WTP) for a reduction in schedule delay early and schedule delay late. These WTP values can be used to calculate the costs of travel time variability. We apply the theoretical results to the scheduling model and design the choice experiment using measures of efficiency (S-efficiency and WTP-efficiency). In the simulation exercise, we show that the designs based on these efficiency criteria perform on average better than the designs used in the literature in terms of the WTP for travel time, schedule delay early, and schedule delay late variables. However, the gains in efficiency decrease in the number of respondents. Surprisingly, the orthogonal design performs rather well in the example we demonstrated.

Stick to the Plan? A Revealed-Preference Study of Behavioural Impacts of Traffic Information

We estimate a revealed-preference scheduling model of morning peak behaviour that allows us to determine the impact of traffic information on traveller behaviour. Specifically, we distinguish between the marginal impact of expected travel times versus that of deviations from this expectation upon user behaviour. We find that participants that chose to receive a smart-phone with traffic information as a reward in our experiment respond to the deviation of actual travel times from the expectation, which they did not do before. This we interpret as evidence that traffic information indeed affects behaviour. We also find that participants who did not choose the smart-phone, but instead opted for monetary rewards, also respond to the deviation of actual travel times from the expectation. This suggests that these drivers use other sources of information to help their trip planning.