Studying travel-related individual assessments and desires by combining hierarchically structured ordinal variables

Ordinal measures are frequently encountered in travel behavior research. This paper presents a new method for combining them when a hierarchical structure of the data can be presumed. This method is applied to study the subjective assessment of the amount of travel by different transportation modes among a group of French clerical workers, along with the desire to increase or decrease the use of such modes. Some advantages of this approach over traditional data reduction technique such as factor analysis when applied to ordinal data are then illustrated. In this study, combining evidence from several variables sheds light on the observed moderately negative relationship between the personal assessment of the amount of travel and the desire to increase or decrease it, thus integrating previous partial (univariate) results. We find a latent demand for travel, thus contributing to clarify the behavioral mechanisms behind the induced traffic phenomenon. Categorizing the above relationship by transportation mode shows a desire for a less environmental-friendly mix of modes (i.e., a greater desire to use heavy motorized modes and a lower desire to use two-wheeled modes), whenever the respondents do not feel to travel extensively. This result, combined with previous theoretical investigations concerning the determinants of the desire to alter trips consumption levels, shows the importance of making people aware of how much they travel.

Knut M. WittkowskiEmail:

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Marco Diana   is a permanent researcher working at the Department of Hydraulics, Transport and Civil Infrastructures of Politecnico di Torino, Italy. His research interests include the study of innovative forms of public transport services and the analysis of multimodality behaviors. Tingting Song   is a Scientific Programmer at The Rockefeller University, Center for Clinical and Translational Science, Biostatistics, Epidemiology, and Research Design Core, New York, NY, USA. She works on algorithms for non-parametric methods and their applications in medical research. She maintains the muStat package on CRAN.r-project.org and the Web server on muStat.rockefeller.edu. Knut M. Wittkowski   is a Senior Research Associate at The Rockefeller University and Head of Biostatistics, Epidemiology, and Research Design at its Center for Clinical and Translational Science, New York, NY, USA. His research focuses on methods, meta data, and user interfaces to integrate nonparametric statistics into research and decision support systems.