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Unveiling the aesthetic “wow factor”: The role of aesthetic incongruity and image quality in NFT art valuation with computer vision

Author

Listed:
  • Chong Guan

    (SUSS Academy, Singapore University of Social Sciences)

  • Ding Ding

    (Singapore University of Social Sciences)

  • Jing Ren

    (Singapore University of Social Sciences)

  • Jiancang Guo

    (Netvirta Singapore Pte. Ltd.)

Abstract

This study investigates the intricate interplay between visual (in)congruity and visual quality within the context of Non-Fungible Tokens (NFTs). Drawing upon foundational theories on mental schema, and uniqueness in extended self-representation, we develop a comprehensive theoretical framework that illuminates the influence of visual cues on consumer psychology and market dynamics in the burgeoning NFT art ecosystem. Leveraging a dataset comprising 2895 images from NFT art collections, we employ computer vision to discern patterns and extract visual features underpinning transaction pricing dynamics. Subsequently, we analyze the interaction effect between visual (in)congruity and visual quality on NFT art valuation. Aesthetic incongruity has been shown to contribute to the enhancement of prices, but this effect is contingent on the perceived aesthetic quality being high. Our study underscores the transformative potential of visual (in)congruity in shaping consumer perceptions and market dynamics within the NFT ecosystem. By elucidating the interplay between visual aesthetics and valuation mechanisms, we offer valuable insights pertaining to the creation, valuation, and investment of NFTs. This enriches scholarly discourse and informs practical strategies for market participants and stakeholders navigating the dynamic landscape.

Suggested Citation

  • Chong Guan & Ding Ding & Jing Ren & Jiancang Guo, 2024. "Unveiling the aesthetic “wow factor”: The role of aesthetic incongruity and image quality in NFT art valuation with computer vision," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-16, December.
    • Handle: RePEc:spr:elmark:v:34:y:2024:i:1:d:10.1007_s12525-024-00722-2
    DOI: 10.1007/s12525-024-00722-2
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    References listed on IDEAS

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    Cited by:

    1. David Kuo Chuen Lee & Chong Guan & Yinghui Yu & Qinxu Ding, 2024. "A Comprehensive Review of Generative AI in Finance," FinTech, MDPI, vol. 3(3), pages 1-19, September.

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    More about this item

    Keywords

    NFT art; Aesthetic incongruity; Image quality; Computer vision; Digital aesthetics; NFT valuation;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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