业务
持续性
过渡(遗传学)
环境经济学
经济
公共政策
过渡管理(治理)
经济体制
自然资源经济学
政府(语言学)
风险分析(工程)
产业组织
电流(流体)
工作(物理)
可持续发展
计算机科学
作者
Rudraksh S. Gupta,Arjun Tyagi,Sanjeev Anand
出处
期刊:
[Elsevier BV]
日期:2026-07-17
卷期号:13: 100805-100805
标识
DOI:10.1016/j.nxener.2026.100805
摘要
The transportation industry is responsible for up to 17% of worldwide CO 2 emissions, making the widespread uptake of electric vehicles (EVs) a crucial method for achieving decarbonization targets. Although previous research has identified many barriers with respect to the adoption of EVs, but have mostly studied these barriers independently or in limited geographical contexts, leaving a significant gap in the holistic and hierarchical understanding of how multiple barrier categories interact and constrain the adoption simultaneously, especially in emerging economies like India. This study bridges this gap by systematically identifying and prioritizing 20 barriers to EV adoption in 5 categories (infrastructure, economic, policy, technological, and social) through an integrated approach of a structured literature review and expert elicitation with 20 domain specialists from government, industry, and academia across 7 Indian regions. Then, the Fuzzy Analytic Hierarchy Process (FAHP) was used to rank these barriers, and its intrinsic consistency ratio was used to reduce the bias of experts and to address the ambiguity inherent in multi-criteria judgements. Results reveal that infrastructure-related barriers, particularly the absence of a charging ecosystem and grid vulnerability, are the highest priority barriers, closely followed by economic barriers such as high initial investment and battery replacement costs. Notably, no single barrier acts alone, implying that concurrent multi-barrier policy interventions are required to expedite EV market penetration. These findings add to the international literature by providing a replicable decision framework based on the FAHP to allow for context-specific prioritization of EV barriers, thus representing a methodological advance over single-criterion approaches, as well as actionable guidance for policymakers wishing to design targeted and evidence-based EV adoption strategies.
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