Modeling the mode choice by an individual is a challenging task. In this paper, vehicle choice of lessees is discussed. Prediction of vehicle choice occurs by fitting three different logit models: standard, nested and cross-nested multinomial logistic regression. Both nested and cross-nested logit relax error term distribution assumptions and therefore allow for correlations across alternative vehicle choices. It is shown that allowing for correlation across alternatives is the proper way of modeling lessees' vehicle choice.

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Price Waterhouse Coopers Advisory N.V. Amsterdam, The Netherlands
12th International Conference on Ambient Systems, Networks and Technologies
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands

Feilzer, (), J.-W, Stroosnier, D, Dugundji, E.R, & Koch, T. (2021). Predicting lessee switch behavior using logit models. In Procedia Computer Science (pp. 380–387). doi:10.1016/j.procs.2021.03.048