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Worker mobility and the purchase of low CO2 emission vehicles in France: a datamining approach

Author

Listed:
  • Raphaël Homayoun Boroumand

    (City University London)

  • Stéphane Goutte

    () (LED - Université Paris 8)

  • Thomas Péran

    (Paris School of Business)

  • Thomas Porcher

    (ESG Research Lab - ESG Management School)

Abstract

This paper seeks to pattern a non-driven geographical classication of French departmental territorial units based on both mobility behavior and passenger car eet composition. With no mathematical regression analysis but applying datamining methodology to behavior, consumption and geography variables, we have grouped French territorial units into 8 clusters with similar characteristics. The main results reveal that commuters' behavior with respect to the choice of transport mode varies substantially across clusters (rural and highly rural, urban and highly urban clusters, ...). Conversely, the structure of the French vehicle eet and French car purchases in terms of engines, tax horsepower and CO2 emissions are similar. this nding should enable state organizations to implement dierentiated public policies for environmental and industrial sectors. Alternatively, our paper should help industrial groups to better deploy their economic strategies in line with environmental concerns.

Suggested Citation

  • Raphaël Homayoun Boroumand & Stéphane Goutte & Thomas Péran & Thomas Porcher, 2019. "Worker mobility and the purchase of low CO2 emission vehicles in France: a datamining approach," Working Papers halshs-01968001, HAL.
  • Handle: RePEc:hal:wpaper:halshs-01968001
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01968001
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    References listed on IDEAS

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    Keywords

    CO2 emissions; Datamining; Cluster; Worker mobility; Passenger cars; France;

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