Prelims Cracker
Prelims Cracker

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India Electric Mobility Index

Prelims Cracker
  • Context (PIB): NITI Aayog launched the India Electric Mobility Index (IEMI), India’s first-of-its-kind tool to assess subnational EV readiness.

About India Electric Mobility Index

  • India Electric Mobility Index is a composite index measuring the electric mobility ecosystem maturity across states & UTs.
  • Objective: It supports evidence-based policymaking & promotes inter-state learning on EV transition.
  • Dynamic Scoring: Scores evolve with changes in EV policy, adoption, and infrastructure development.

Methodology

  • Score Range: Each state or UT is rated from 0 to 100 using weighted metrics.
  • Indicator Set: The index uses 16 indicators grouped under three key thematic pillars.
    1. Electrification: Measures EV penetration across personal, commercial, & public transport segments.
    2. Charging Readiness: It evaluates grid integration, station density, & allied charging infrastructure.
    3. Innovation: It captures manufacturing scale, R&D output, and EV startup ecosystem activity.

State Performance Highlights (2024)

  • The index highlights thematic leadership across EV adoption, infrastructure, and innovation.
  • Overall Leader: Delhi ranked highest overall, followed by Maharashtra and Chandigarh.
  • EV Deployment: Delhi, Maharashtra, & Chandigarh emerged as frontrunners in transport electrification.
  • Infra Readiness: Haryana, Karnataka, Ladakh, and Himachal Pradesh led in infrastructure readiness.
  • Innovation Strength: Delhi, Tamil Nadu, Maharashtra, and Karnataka were key innovation frontrunners.
  • SmallState Leader: Chandigarh led among small states and UTs, followed by Goa and Delhi.

Significance of India Electric Mobility Index

  • IEMI links mobility outcomes to federal competition and policy responsiveness.
  • Public Benchmarking: The index enables transparent tracking of EV progress across states and UTs.
  • Federal Competition: It fosters cooperative federalism through competitive rankings & peer learning.
  • Scheme Optimisation: Findings help recalibrate FAME & PLI schemes using subnational outcome data.
  • Data Ecosystem: It promotes more substantial EV data collection and integration at the state level.
  • Transparency Lever: Public rankings enhance accountability in electric mobility performance.

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