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Fuzzy set qualitative comparative analysis (fsQCA) applied to the adaptation of the automobile industry to meet the emission standards of climate change policies via the deployment of electric vehicles (EVs)

机译:模糊集定性比较分析(FSQCA)应用于汽车工业的适应,通过部署电动车(EVS)符合气候变化政策的排放标准

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摘要

Facing global climate change challenges entails a sustainable development of transportation. Governments and automobile manufacturers are highly aware of how a large-scale deployment of Electric Vehicles (EVs) can reduce greenhouse gas (GHG) emissions and mitigate global warming. This study aids the design of the adaptation strategies of the automotive industry to meet global goals on climate change by means of a fuzzy-set qualitative comparative analysis (fsQCA), which makes it possible to measure the level of actors' satisfaction. This allows identification of a combination of factors leading to the outcome while dealing with uncertain environments due to the heterogeneous nature of actors with conflicting of interests. The methodology has been successfully applied to a case study, thus providing greater transparency, fairness, social equity, and consensus among actors.
机译:面对全球气候变化挑战需要可持续发展的运输。 政府和汽车制造商高度意识到电动汽车(EVS)的大规模部署如何减少温室气体(GHG)排放和缓解全球变暖。 本研究辅助汽车行业的适应策略设计,以通过模糊定的定性比较分析(FSQCA)来满足全球目标对气候变化的目标,这使得能够衡量演员满意度的水平。 这允许识别导致结果的结果的组合,同时由于参与者的异构性质而受到利益冲突的情况下的不确定环境。 该方法已成功应用于案例研究,从而提供了更大的透明度,公平,社会公平和共识。

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