Worker mobility and the purchase of low CO2 emission vehicles in France: a datamining approach
Raphaël Homayoun Boroumand,
Stéphane Goutte (),
Thomas Péran and
European Journal of Comparative Economics, 2019, vol. 16, issue 2, 171-205
This paper seeks to pattern a non-driven geographical classification of French departmental territorial units based on both mobility behavior and passenger car fleet 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 fleet and French car purchases in terms of engines, tax horsepower and CO2 emissions are similar. This finding should enable state organizations to implement differentiated 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.
Keywords: CO2 emissions; Datamining; Cluster; Worker mobility; Passenger cars; France (search for similar items in EconPapers)
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Working Paper: Worker mobility and the purchase of low CO2 emission vehicles in France: a datamining approach (2019)
Working Paper: Worker mobility and the purchase of low CO2 emission vehicles in France: a datamining approach (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:liu:liucej:v:16:y:2019:i:2:p:171-205
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