Impediment ranking and solutions for enhancing electric freight vehicle uptake in urban logistics

The adoption of electric freight vehicles (EFVs) is integral to achieving sustainable urban freight mobility (UFM); however, their large-scale deployment remains constrained by a number of financial, infrastructural, regulatory, policy, and operational barriers. This study employs a robust multi-criteria decision analysis (MCDA) framework, which integrates fuzzy Delphi, decision-making trial and evaluation laboratory (DEMATEL), and interpretive structural modelling (ISM), to systematically identify, rank, and link critical barriers to EFV deployment. Through an initial literature review and expert-driven assessment, we identify 18 barriers, which are subsequently refined to 13 based on their significance and interrelationships. The results highlight six dominant causal barriers, including inadequate government incentives, unstructured urban market layouts, and high operational costs with prolonged payback periods, all of which create systemic resistance to EFV adoption. Additionally, limited charging infrastructure, an immature EFV resale market, and a lack of dedicated repair centres exacerbate the reluctance of logistics service providers to transition to EFVs. The study also categorizes these barriers into four strategic clusters based on their driving and dependence power, offering a novel hierarchical decision roadmap to facilitate effective policy interventions. Advancing existing DEMATEL methodologies, this research contributes to the discourse on sustainable urban logistics by providing an empirically validated, analytically rigorous framework that informs policymakers, logistics service providers, and urban planners in devising effective strategies for EFV integration. The proposed model facilitates strategic decision-making for achieving low-carbon urban freight systems and offers a scalable approach that is applicable to diverse urban contexts.