Business and site specific trip generation methodology for truck trips

Abstract

The motivation for this research comes from the recognition that recent developments in supply chain management (SCM) have altered the mechanism of truck trip generation at the individual facility level. This research develops models of truck trip generation (TTG) at the disaggregate level that incorporate strategic supply chain decisions made by individual businesses. The main assumption is that the TTG is an outcome of a series of strategic and operational business decisions. The research team conducted a survey of national retail chains. The data sets obtained from two furniture chains were used to develop binary logit models. Empirical data, although limited, validated the potential of building a disaggregate TTG model at the individual store level. Inclusion of location and store type dummy variables almost always improved model's predictive power, often dramatically. The findings presented in this report also underscore various shortcomings of existing methods. We found that commonly used independent variables such as the store floor space or the number of employees are poor predictor of truck trip generation at retail stores.