Paper Type
Short
Paper Number
1841
Description
Despite increasing scholarly and practical attention to the generative AI-created visual content (GACVC) questions remain about the factors that enhance intention to consume and the aesthetic evaluation criteria. To fill these gaps in research, we propose a research model through an elaboration of dual process theory and aesthetic appreciation theory. We initiate our research by developing a conceptual framework for aesthetic evaluation specifically tailored to GACVC, leading to the development and validation of a specific scale. Drawing on dual-process theory, we then identify factors influencing GACVC and explore the role of both intuitive and analytical processes in shaping intention to consume based on aesthetic evaluation. Furthermore, this study explores how aesthetic evaluation influences individuals’ intention to consume GACVC based on aesthetic appreciation theory. In doing so, this study contributes to the literatures on generative AI and aesthetic evaluation, offering practical insights into ways GACVC can enhance consumers’ aesthetic evaluation.
Recommended Citation
Boo, Chaeeun; Kim, Yeongseo; and Suh, Ayoung, "Generative AI-Created Visual Content and Aesthetic Evaluation: Bridging Human Intuition and Analytical Judgment" (2024). PACIS 2024 Proceedings. 22.
https://aisel.aisnet.org/pacis2024/track19_userbeh/track19_userbeh/22
Generative AI-Created Visual Content and Aesthetic Evaluation: Bridging Human Intuition and Analytical Judgment
Despite increasing scholarly and practical attention to the generative AI-created visual content (GACVC) questions remain about the factors that enhance intention to consume and the aesthetic evaluation criteria. To fill these gaps in research, we propose a research model through an elaboration of dual process theory and aesthetic appreciation theory. We initiate our research by developing a conceptual framework for aesthetic evaluation specifically tailored to GACVC, leading to the development and validation of a specific scale. Drawing on dual-process theory, we then identify factors influencing GACVC and explore the role of both intuitive and analytical processes in shaping intention to consume based on aesthetic evaluation. Furthermore, this study explores how aesthetic evaluation influences individuals’ intention to consume GACVC based on aesthetic appreciation theory. In doing so, this study contributes to the literatures on generative AI and aesthetic evaluation, offering practical insights into ways GACVC can enhance consumers’ aesthetic evaluation.
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