Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)

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Electric Dreams: Public and Private Transport Innovations through Government Green Subsidies

Authors
Devendra Ramchandra Ghodnadikar1, Radhakrishna Batule2, *, Tarun Madan Kanade3
1Vishwakarma University, Pune, India
2Faculty of Commerce and Management, Vishwakarma University, Pune, India
3Faculty of Management, Symbiosis Institute of Operations Management, Symbiosis International (Deemed University), Pune, India
*Corresponding author. Email: radhakrishna.batule@vupune.ac.in
Corresponding Author
Radhakrishna Batule
Available Online 6 January 2026.
DOI
10.2991/978-94-6463-948-3_25How to use a DOI?
Keywords
Clean Energy Transition; Electric Vehicles; Government Subsidies; Green Technology Policy; Private Transport Electrification; Public Transport Innovation; Sustainable Mobility
Abstract

The critical need to reduce greenhouse gas emissions, fossil fuel reliance, and promote sustainable mobility is transforming the global transportation industry. Government green subsidies have become important policy tools to spur innovation and speed the adoption of electric vehicles (EVs) and associated infrastructure. This article examines how government-led subsidy schemes are accelerating technical and structural changes in public and private transport. The research compares subsidy schemes in India, China, the US, and EU countries. Direct grants, tax advantages, infrastructural financing, and R&D assistance are examined to determine their effects on electric transportation innovation. The research examines how subsidies affect product development, market penetration, and environmental results using case studies from metropolitan city electrified bus fleets to EV start up market disruptors. The study also examines the economic and social effects of these breakthroughs, including green job development, energy security, and fair access to clean mobility. The report also critiques present subsidy schemes for policy instability, uneven access, and battery supply chain sustainability. This research gives policymakers, transport planners, and industry stakeholders concrete insights by merging policy analysis with innovation theory. It proposes strategic, scalable, and inclusive subsidy options to promote long-term decarbonization and transport innovation ecosystems.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
Series
Advances in Intelligent Systems Research
Publication Date
6 January 2026
ISBN
978-94-6463-948-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-948-3_25How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Devendra Ramchandra Ghodnadikar
AU  - Radhakrishna Batule
AU  - Tarun Madan Kanade
PY  - 2026
DA  - 2026/01/06
TI  - Electric Dreams: Public and Private Transport Innovations through Government Green Subsidies
BT  - Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
PB  - Atlantis Press
SP  - 342
EP  - 358
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-948-3_25
DO  - 10.2991/978-94-6463-948-3_25
ID  - Ghodnadikar2026
ER  -