Worker Mobility and the Purchase of Low Co2 Emission Vehicles in France: A Datamining Approach

Stéphane Goutte, R. Boroumand, T. Péran, Thomas Porcher
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引用次数: 1

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.
工人流动性和购买低二氧化碳排放车辆在法国:一个数据挖掘方法
本文试图基于交通行为和乘用车构成对法国省领土单位进行非驱动的地理分类。我们没有进行数学回归分析,而是将数据挖掘方法应用于行为、消费和地理变量,将法国领土单位分为8个具有相似特征的集群。主要结果表明,通勤者在交通方式选择方面的行为在不同的集群(农村和高度农村,城市和高度城市集群,…)之间存在很大差异。相反,在发动机、税收马力和二氧化碳排放量方面,法国汽车的结构和法国汽车的购买是相似的。这一目标应使国家组织能够为环境和工业部门执行有区别的公共政策。或者,我们的论文应该帮助工业集团更好地部署符合环境问题的经济战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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