Integrating Lifecycle Assessment and Fuzzy BWM to Evaluate Sustainable Automotive Design Alternatives

This study is motivated by growing environmental pressures, regulatory demands, and consumer expectations that compel the automotive industry to redesign products and supply chains for sustainability. The research addresses the problem of evaluating multiple vehicle technologies under uncertainty, where existing approaches often focus narrowly on emissions or cost. To overcome this, the study proposes an integrated framework combining lifecycle assessment principles with the fuzzy best-worst method, enabling robust prioritization of 30 sustainability criteria across environmental, economic, material, energy efficiency, and product lifecycle dimensions. The framework is applied to 12 automotive design alternatives, including combustion engine, hybrid, battery electric, hydrogen fuel cell, and recyclable vehicle models. Results based on expert evaluations show that hybrid electric vehicles achieved the highest sustainability ranking, followed by lightweight material and recyclable vehicle designs, reflecting a strong emphasis on reducing carbon emissions (global weight = 0.082) and operational costs (global weight = 0.071). The study contributes a practical decision-support tool for manufacturers to navigate trade-offs between environmental responsibilities and economic viability. Findings also provide policymakers with evidence to support incentives and regulatory frameworks promoting sustainable automotive technologies.