The Role of AI-based Live Streaming Features in Shaping Consumer’s Purchase Intentions for New Energy Electric Vehicles: Fuzzy-set Qualitative Comparative Analysis (fsQCA)
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Abstract
The automotive industry's shift toward eco-friendly vehicles has created challenges in boosting consumer purchase intentions for new energy electric vehicles (NEEVs), while rapid AI advancements in marketing present new opportunities for consumer engagement. The objectives of this research were: 1) to study the role of AI-based live streaming features on consumer purchase intentions for new energy electric vehicles (NEEVs), and 2) to develop a comprehensive model of AI-based live streaming to enhance consumer purchase intentions for new energy electric vehicles. The study employed a Fuzzy-set Qualitative Comparative Analysis (fsQCA) methodology within the Stimulus-Organism-Response (SOR) perspective. It involved a structured survey that was distributed to a sample of 301 consumers via an online platform targeting those who owned or used NEEVs. The research utilized fuzzy set calibration to analyze the relationships between variables and to determine the conditions that were necessary and sufficient for high purchase intentions. Results showed that AI content was essential for high consumer purchase intentions, playing a key role in generating interest and engagement. Combining high-quality AI content, effective AI audience interaction, and compelling AI product displays was found to be sufficient for achieving high purchase intentions. The research highlighted the ongoing importance of traditional marketing factors, with trust being a crucial element alongside AI content. The findings suggested that the most effective strategies integrated AI-driven approaches with traditional marketing elements, offering insights into optimizing both to enhance consumer purchase intentions for NEEVs.
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