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Predictive analysis for removing obstacles in electric mobility: Revolution into EV adoption

Publication Type : Journal Article

Publisher : Elsevier BV

Source : Transportation Engineering

Url : https://doi.org/10.1016/j.treng.2024.100277

Keywords : Electric vehicle (EV), Brashness, Monetary assistance, Ecofriendly apprehension

Campus : Bengaluru

School : School of Engineering

Department : Electrical and Electronics

Year : 2024

Abstract : This study aims to get insights into the overall consumer opinion of electric vehicles (EVs) and the obstacles that hinder their broad adoption. This study seeks to uncover and comprehend the elements associated with consumer purchases through theme analysis, which offers a broader spectrum of expression compared to conventional survey methods. Additionally, it considers a factor as influence of emotions is often disregarded. This study is using electronic word-of-mouth (eWOM) as a primary data source, highlighting the study's relevance to the digital age. Individuals predominantly utilize online platforms to express their opinions and freely disseminate information, which identifies the discrepancies, both tangible and intangible between the features and benefits of EVs and the consumer's expectations. The system results shows that, the enhanced vehicle range can significantly minimize the public charging infrastructure reliance with range of anxiety and long recharge times. The inter connection between the obstacles shows the complexity of overcoming barriers to widespread EV adoption. This study has significance into the interconnections among these obstacles, which enlarge a detrimental cascade impact on the total adoption rate.

Cite this Research Publication : Sujit Kumar, Jayant Giri, Sasanka Sekhor Sharma, Shruti R. Gunaga, Manikanta G, T. Sathish, S.M. Mozammil Hasnain, Rustem Zairov, Predictive analysis for removing obstacles in electric mobility: Revolution into EV adoption, Transportation Engineering, Elsevier BV, 2024, https://doi.org/10.1016/j.treng.2024.100277

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