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)
本研究运用模糊集定性比较分析，帮助汽车产业设计适应气候变化的策略，通过识别因素组合来应对不确定环境，案例应用提高了各方满意度与共识。
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.