Multi-Criteria Decision Analysis for Sustainable Vehicle Technologies
Summary
Multi-Criteria Decision Analysis (MCDA) offers structured frameworks for evaluating sustainable vehicle technologies against a spectrum of economic, environmental, social and technical criteria. As mobility shifts towards electric drivetrains, hydrogen-fuel cell systems, synthetic e-fuels and shared micro-mobility solutions, decision-makers face increasingly complex trade-offs between total cost of ownership, lifecycle greenhouse gas emissions, infrastructure requirements and social acceptability. MCDA methods such as Analytic Hierarchy Process, Technique for Order of Preference by Similarity to Ideal Solution and ELECTRE have evolved to incorporate fuzzy and probabilistic extensions that capture uncertainty in expert judgements and stakeholder preferences. Recent methodological advances include hybrid weighting schemes blending objective data with stakeholder inputs, adaptive normalisation techniques and integration with Life Cycle Sustainability Assessment to account for well-to-wheel impacts. Globally, these analyses underpin procurement decisions for fleet operators, guide deployment of charging and refuelling networks, and inform policy frameworks aimed at decarbonising transport. By translating diverse sustainability objectives into a common decision space, MCDA facilitates transparent prioritisation of zero-emission technologies, supports resilience in supply chains and aligns investment with long-term climate targets.
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Multi-Criteria Decision Analysis for Sustainable Vehicle Technologies publication trend
The graph below shows the total number of articles in multi-criteria decision analysis for sustainable vehicle technologies across all publications each year (not limited to Nature Index journals).
Technical terms
Multi-Criteria Decision Analysis (MCDA): A suite of structured methods for evaluating and ranking alternatives against multiple, often conflicting, criteria.
Fuzzy Sets: Mathematical constructs representing uncertain or imprecise information through graded membership values between 0 and 1.
q-Rung Orthopair Fuzzy Sets: An extension of fuzzy sets in which membership and non-membership degrees are independently modelled and raised to the power q for enhanced representation of uncertainty.
Analytic Hierarchy Process (AHP): A pairwise comparison technique that derives priority weights among decision criteria based on expert judgements.
Life Cycle Sustainability Assessment (LCSA): A methodological framework combining environmental, economic and social life cycle analyses to assess the sustainability of products or systems throughout their entire life span.
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS): An MCDA method that ranks alternatives by measuring their distances from an ideal best and an ideal worst solution.
Method based on Removal Effects of Criteria (MEREC): An objective weighting approach that determines criterion importance by analysing the impact of removing each criterion on overall ranking.
Double Normalisation-Based Multi-Aggregation (DNMA): An aggregation technique that applies two normalisation steps to balance attribute scales before combining them into a final score.
References
- Evaluating alternative low carbon fuel technologies using a stakeholder participation-based q-rung orthopair linguistic multi-criteria framework. Applied Energy (2023).
- A Hybrid Intuitionistic Fuzzy-MEREC-RS-DNMA Method for Assessing the Alternative Fuel Vehicles with Sustainability Perspectives. Sustainability (2022).
- Multi-Criteria Decision Analysis of Road Transportation Fuels and Vehicles: A Systematic Review and Classification of the Literature. Energies (2019).
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