Enhanced Destination Choice Models Incorporating Agglomeration Related to Trip Chaining While Controlling for Spatial Competition

It is common knowledge that travelers often choose clusters or groups of nearby destinations that can be visited conveniently in a single tour. This propensity is becoming increasingly important in the context of rising fuel costs. However, gravity models, as well as most destination choice models, ignore these agglomeration effects and treat each trip or destination choice as independent. Some models have captured economies of agglomeration related to trip chaining through the use of accessibility variables. Accessibility variables, however, generally do not identify trip chaining effects uniquely, but measure differential spatial competition that arises because nearby destinations are generally better substitutes than distant ones. Because spatial competition effects generally dominate trip chaining agglomeration effects, models with a single accessibility variable have been called competing destinations models following Fotheringham. This paper presents an advance on Fotheringham's approach by introducing two distinct accessibility variables to represent agglomeration and spatial competition among destinations separately rather than their net effect. These new agglomerating and competing destination choice models were applied in Knoxville, Tennessee. The new models, which outperformed both gravity and competing destinations models, began to present a new alternative to activity-based models by allowing the incorporation of some of the most important trip chaining effects in trip-based travel demand models. For example, a sensitivity test showed that a new factory employing 1,000 workers would attract 125 new nonwork trips to the surrounding area on an average day as a result of stops on the way to and from work.