Abstract

In this study we look at the relationship between shopping and travel trips, especially by car, and ask whether the travel trip has intrinsic value and/or costs for shoppers.

The plan of this paper is as follows: First we establish a baseline about shopping travel, based on recent travel statistics. We then seek, through the transportation and marketing literatures, different approaches to the question of why people travel to stores. This leads us to pose specific hypotheses about shopping-related trips which we then test using activity-based demand modeling. The final sections discuss our results and conclusions. They suggest that the behaviors associated with the adoption of electronic home shopping are complex, and that it is naive to view home shopping as just another channel. Home shopping will not evolve independently of other changes in work, daily routines, and leisure time use.

Abstract

We present a simulation model designed to determine the impact on congestion of policies for dealing with travel time uncertainty. The model combines a supply side model of congestion delay with a discrete choice econometric demand model that predicts scheduling choices for morning commute trips. The supply model describes congestion technology and exogenously specifies the probability, severity, and duration of non-recurrent events. From these, given traffic volumes, a distribution of travel times is generated, from which a mean, a standard deviation, and a probability of arriving late are calculated. The demand model uses these outputs from the supply model as independent variables and choices are forecast using sample enumeration and a synthetic sample of work start times and free flow travel times. The process is iterated until a stable congestion pattern is achieved. We report on the components of expected cost and the average travel delay for selected simulations.

Abstract

A trip generation model has been developed using a time-use perspective, in which trips are generated in conjunction with out-of-home activities, and time spent traveling is another component of overall time use. The model jointly forecasts three sets of endogenous variables – (1) activity participation and (2) travel time (together making up total out-of home time use), and (3) trip generation — as a function of household characteristics and accessibility indices. It is estimated with data from the Portland, Oregon 1994 Activity and Travel Survey. Results show that the basic model, which has ten endogenous time use and trip generation variables and thirteen exogenous variables, fits well, and all postulated relationships are upheld. Test show that the basic model, which divides activities into work and nonwork, can be extended to a three-way breakdown of subsistence, discretionary and obligatory activities. The model can also capture the effects of in-home work on trip chaining and activity participation. We use the model to explore the effects on time use and trip chaining of GIS-based and zone-based accessibility indices.