Determination of Attributes Reflecting Household Preferences in Location Choice Models

Abstract

Challenges coming along with changing mobility behaviour patterns require planning decisions to mitigating negative effects. Land-use and transport interaction models can provide valuable decision support for this purpose. But they require tremendous effort in terms of model design as well as data collection and preparation. We introduce a methodology and procedures with the aim to minimize the magnitude of modelling work with particular attention to the selection of model segmentation and model parameters in a structured and efficient way. The methodology combines literature and statistical analyses for model design. The paper outlines the methodology and presents its application to the design of a location choice model for the city of Berlin, Germany. We demonstrate how household types exhibiting specific location patterns and related accessibility parameters can be identified from the literature and how standard deviation maps and correlation analysis can be used to detect these households and test hypotheses. The results suggest that the methodology is capable to identify segmentations and parameters for usage in choice models, such as location decisions, in an efficient way.