01157805

Component

While most models of location decisions of firms are based on the principle of utility-maximizing behavior, the present study assumes that location decisions are just part of business cycle models, in which location is considered along other business decisions. The business model results in a series of location requirements and these are matched against location characteristics. Given this theoretical perspective, the modeling challenge then becomes how to find the match between firm types and the set of location characteristics using observations of the spatial distribution of firms. In this paper, several Bayesian classifier networks are compared in terms of their performance, using a large data set collected for the Netherlands. Results demonstrate that by taking relationships between predictor variables into account the Bayesian classifiers can improve prediction accuracy compared to commonly used decision tree. From a substantive point of view, our results indicate that different sets of urban characteristics and accessibility requirements are relevant to different office types as reflected in the spatial distribution of these office firms.

01147878

10-2236

English

17p

2010

Transportation Research Board 89th Annual Meeting

DVD

Figures (2) ; References (27) ; Tables (2)

Decision trees; Location; Office buildings; Systems analysis; Traffic models; Travel behavior

Bayesian analysis; Exploratory studies

Netherlands

Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2010 Paper #10-2236

TRIS, TRB

Jan 25 2010 11:02AM