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NP4VTT: A new software for estimating the value of travel time with nonparametric models

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  • Hernández, José Ignacio
  • van Cranenburgh, Sander

Abstract

Two-attribute-two-alternative stated choice experiments are widely used to infer the Value-of-Travel-Time (VTT) distribution. Two-attribute-two-alternative stated choice experiments have the advantage that their data can be analysed using nonparametric models, which allow for the inference of the VTT distribution without having to impose assumptions on its shape. However, a software package that enables researchers to estimate nonparametric models promptly is currently lacking. As a result, nonparametric models are underused. This paper aims to fill this software void. It presents NP4VTT, a Python package that enables researchers to estimate and compare nonparametric models in a fast and convenient way. It comprises five nonparametric models for estimating the VTT distribution from data coming from two-attribute-two-alternative stated choice experiments. We illustrate the use of NP4VTT by applying it to the Norwegian 2009 VTT data. We hope this software package will help researchers studying the VTT make more informed decisions concerning the shape of the VTT distribution and encourages the use and development of nonparametric models for choice behaviour analyses.

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  • Hernández, José Ignacio & van Cranenburgh, Sander, 2023. "NP4VTT: A new software for estimating the value of travel time with nonparametric models," Journal of choice modelling, Elsevier, vol. 48(C).
    • Handle: RePEc:eee:eejocm:v:48:y:2023:i:c:s1755534523000283
    DOI: 10.1016/j.jocm.2023.100427
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