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Choice Modelling and Forecasting Demand for Alternative-Fuel Tractors

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Advances in Data Mining. Applications and Theoretical Aspects (ICDM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8557))

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Abstract

This paper presents a study focused on potential demand for agricultural multi-functional electric tractor. In this context, the willingness-to-pay is investigated in order to establish the potential diffusion of an electrical solar tractor, by considering different levels of key attributes related to environmental, technical and economical characteristics of different version of alternative fuel tractors. The study is carried out through a choice-experiment and the application of multinomial discrete choice models, by considering heteroscedasticity of the respondent and heterogeneity across alternatives.

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Author information

Authors and Affiliations

  1. Dept. of Economic and Business, University of Florence, Via delle Pandette 32, 50127, Florence, Italy

    Ginevra Virginia Lombardi

  2. Dept. of Statistics, Informatics, Applications, University of Florence, Viale Morgagni 59, 50134, Florence, Italy

    Rossella Berni

Authors
  1. Ginevra Virginia Lombardi
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  2. Rossella Berni
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

    Petra Perner

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Lombardi, G.V., Berni, R. (2014). Choice Modelling and Forecasting Demand for Alternative-Fuel Tractors. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2014. Lecture Notes in Computer Science(), vol 8557. Springer, Cham. https://doi.org/10.1007/978-3-319-08976-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-08976-8_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08975-1

  • Online ISBN: 978-3-319-08976-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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