Strategic prioritization framework of circular battery lifecycle strategies in India’s battery-as-a-Service (BaaS): an integrated multi-method empirical analysis in India’s electric vehicle ecosystem

Electric vehicles (EVs) are central to transport decarbonization, yet lithium-ion batteries pose major sustainability challenges across extraction, manufacturing, use, and end-of-life stages. Battery-as-a-Service (BaaS) offers a promising pathway to operationalize circular economy principles by decoupling battery ownership from vehicle ownership and embedding lifecycle responsibility within service providers. However, strategic prioritization of circular lifecycle interventions remains fragmented and weakly theorized, particularly for emerging EV ecosystems characterized by regulatory volatility, technological heterogeneity, and market uncertainty. This study develops and empirically applies an integrated Fuzzy Delphi–Best Worst Method (BWM)–Fuzzy DEMATEL framework to identify, prioritize, and structurally analyze critical battery lifecycle strategies supporting circular BaaS implementation in India. Fuzzy Delphi is employed to establish construct validity and expert consensus under epistemic uncertainty, BWM to derive parsimonious and high-consistency priority weights, and Fuzzy DEMATEL to reveal causal interdependencies and feedback structures among the shortlisted strategies. Based on inputs from 55 cross-sectoral experts spanning industry, policy, and academia, nine critical strategies are retained from an initial pool of thirty. Results indicate that battery takeback schemes, AI-driven lifecycle management, and end-of-lease recovery programs represent dominant driving strategies, while predictive maintenance and digital twin tracking function primarily as dependent enablers whose effectiveness is conditioned by higher-order system capabilities. Methodologically, the study contributes a unified uncertainty-handling decision pipeline integrating consensus formation, consistency-optimized weighting, and causal mapping. Practically, it translates analytical outputs into actionable sequencing rules and governance priorities for circular BaaS ecosystems. The framework offers transferable decision support for policymakers and industry actors seeking to structure circular battery governance in emerging and developed EV markets.