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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)

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	Llopis Albert, Carlos; Palacios Marqués, Daniel; Simón Moya, Virginia
	This document is a artículoDate2021
	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.
	Llopis Albert, Carlos Palacios Marqués, Daniel Simón Moya, Virginia 2021 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) Technological Forecasting and Social Change 169 120843
	https://doi.org/10.1016/j.techfore.2021.120843