Freight trip generation by firms

Traffic congestion problems are a constant cause of concern in today's centres of economic activity. While measures that deal with these problems, generally focus on the use of private cars, increasing freight traffic as a cause of road congestion should not be ignored. Forecasts of freight traffic at a local and regional scale are necessary to predict traffic flows on specific routes, and might be helpful in planning adequate infrastructure for future industrial estates. Such forecasts, however, require knowledge of the generation of freight trips by firms, a field in which little research has been done so far. This paper describes an attempt to uncover the relationship between firm characteristics and freight traffic. The main purpose of the research described in the paper, is to build a freight trip generation model which takes differences between sectors of industry into account. Inquiries were held in the Netherlands, collecting data from various types of industry. In this paper, the data of these inquiries are analysed in order to identify the characteristics of firms that are primarily responsible for the number of freight trips that are generated by those firms. Trip generation factors are derived by calculating trip intensity (regressing the daily number of freight trips against magnitude of firms) per sector. These factors appear to vary substantially between sectors. Although sector specific trip generation factors can vary between countries as well, the collected foreign material indicates that the ranking of sectors in terms of their trip intensity may be quite stable. The study shows that trip intensity can vary over sectors by an order of magnitude, thus making this material of interest for city and infrastructure planning purposes. Specific attention will be given to the problems encountered in this type of research, which is based on firm-level survey data from a heterogeneous population. This concerns the determination of sample, survey method (both telephone and mail was done in this work), the optimisation of response rates and survey design.