Fermatean Fuzzy Decision-Analytics-Based Assessment of Policy Mechanisms for Promoting Electric Mobility

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Original abstract

Electric mobility (e-mobility) has emerged as a promising pathway for reducing greenhouse gas emissions, improving energy security, and supporting sustainable transportation systems. However, its widespread adoption in Africa remains constrained by economic, infrastructural, and regulatory challenges, making the prioritization of effective policy mechanisms a complex decision-making problem. This study adopts the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF-SWARA) method to systematically evaluate the policy mechanisms required to accelerate e-mobility adoption under uncertainty. By incorporating Fermatean fuzzy sets, the proposed framework effectively captures the ambiguity and subjectivity inherent in expert judgments, resulting in a more robust and reliable assessment process. Data were collected from four domain experts who evaluated seven policy mechanisms, and the FF-SWARA method was employed to determine their relative importance. The findings indicate that improving energy availability is the most influential policy mechanism, followed by implementing innovative fiscal incentives and strengthening emission standards while restricting the importation of used internal combustion engine (ICE) vehicles. These results emphasize that successful e-mobility deployment in Africa requires a coordinated approach that simultaneously addresses energy infrastructure, financial incentives, and regulatory reforms. The study contributes to the decision sciences and sustainable transportation literature by demonstrating the applicability of the FF-SWARA method to strategic policy evaluation in emerging economies. From a practical perspective, the findings provide policymakers with a transparent and systematic framework for prioritizing investments and designing evidence-based policies that support the transition toward cleaner and more sustainable transportation systems. The study also identifies limitations and suggests future research directions, including the integration of additional multi-criteria decision-making methods and the validation of the proposed framework across different regional and national contexts.

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