A win-win relationship? New evidence on artificial intelligence and new energy vehicles

Jianqiang Gu, Zhan Wu, Yubing Song and Ana-Cristina Nicolescu

Energy Economics, 2024, vol. 134, issue C

Abstract: Investigating the vital role of artificial intelligence is essential to develop the electric vehicle market. This study utilises the wavelet-based QQR methodology to seize the dynamic correlation of artificial intelligence index (AII) and electric vehicle indicator (EVI). Based on quantitative deliberations, the favourable effects of AII on EVI at low-low and high-high quantiles and adverse impacts at high-low and low-high quantiles in the short run confirm the role of artificial intelligence in facilitating the electric vehicle market. However, the favourable effect of AII at medium to high quantiles on EVI at low quantiles refutes it because of the crowding-out effect. Conversely, the positive impact of EVI at medium to high quantiles on AII at low to medium quantiles ascertains the crowding-out effect of electric vehicles, while AII at medium to high quantiles cannot agree on it due to safety and convenience needs. In the mid-to-long term, the interactions of AII and EVI are gradually weakened, and speculative behaviours, crowding-out effects, and safety concerns drive the different cases. Therefore, a win-win situation between them does not always hold, and recommendations are being offered to enhance the significance of artificial intelligence in electric vehicles under the new round of scientific and technological revolution.

Keywords: Artificial intelligence; Electric vehicles; Win-win relationship; Dynamic (search for similar items in EconPapers)
JEL-codes: C32 O33 Q21 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324003219

DOI: 10.1016/j.eneco.2024.107613

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