Show me your NFT and I tell you how it will perform: Multimodal representation learning for NFT selling price prediction

Costa, Davide; Cava, Lucio La; Tagarelli, Andrea

doi:10.1145/3543507.3583520

Cited by 14 publications

(1 citation statement)

References 18 publications

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“…Our research seeks to bridge a critical gap by delving deeper into the value proposition of digital possession and the components contributing to its perceived value. Our study advances beyond previous research which was centered around NFTC price composition (Costa et al, 2023;Nadini et al, 2021) and shifts towards focusing on the unexplored consumer preferences and value composition, representing a meaningful contribution of our study (Wu et al, 2023). To fill this research gap, we see NFTC-specific product features and technology characteristics as conceivable indicators and thereby examine NFT consumer behavior based on the SOR model for the first time.…”

Section: Environmental Stimuli From Blockchain Infrastructurementioning

confidence: 94%

Determinants of the purchase intention of non‐fungible token collectibles

Fortagne,

Lis

2023

J of Consumer Behaviour

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Disrupting the concept of ownership in the digital space, non‐fungible tokens (NFTs) have created unprecedented market opportunities and captivated millions of investors. Characterized by artificial scarcity and ensured authenticity, the technical implementation establishes novel parameters for digital ownership and collecting, underscoring a research gap where the determinants of consumer behavior are yet to be studied. This paper presents a research model based on the Stimulus‐Organism‐Response (SOR) model to investigate consumers' purchase intention of NFT‐based collectibles (NFTC) for the first time. To develop our model, we identified distinctive NFTC features (functionality, scarcity, aesthetics, and price value) and blockchain characteristics (security and privacy) affecting the utilitarian and hedonic attitude towards NFTC and finally shape NFTC purchase intention. For empirical validation, we conducted an online survey among an NFT‐interested target group (N = 356) and analyzed the results by structural equation modeling with SPSS Amos. Findings indicate that the utilitarian attitude toward NFTC is affected by perceived functionality and price value from the product side, and perceived blockchain security and privacy from the technology side. The hedonistic attitude toward NFTC is shaped by perceived functionality, scarcity, and aesthetics. Both attitudes, utilitarian and hedonistic, demonstrate a significant impact on purchase intention. A subsequent mediation analysis confirms that NFTC and blockchain characteristics have an indirect effect on purchase intention. In the under‐investigated interface of blockchain technology, digital ownership, and consumer behavior, this work enriches the digital ownership discourse by demonstrating how NFTC create consumer value through product and technology features.

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Section: Environmental Stimuli From Blockchain Infrastructurementioning

confidence: 94%

Determinants of the purchase intention of non‐fungible token collectibles

Fortagne,

Lis

2023

J of Consumer Behaviour

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NFT price and sales characteristics prediction by transfer learning of visual attributes

Pala,

Sefer

2024

The Journal of Finance and Data Science

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Continuous Use of NFT Trading Platforms: A Perspective Integrating the Expectation Confirmation Model and the Information Systems Success Model

Sun

2024

IEEE Access

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To facilitate the sustained development of non-fungible token (NFT) platforms and enhance user stickiness, it is imperative to study the factors that affect users' continuous usage intentions. This research is grounded in the Expectation Confirmation Model and the Information Systems Success Model, and extends these approaches by introducing three elements-economic benefits, perceived trustworthiness, and technological pressure-thereby constructing the research model. Structural equation modeling was employed to analyze data from 304 respondents with experience in using NFT trading platforms. The findings indicate that: (1) technological pressure is positively correlated with perceived ease of use; (2) both service quality and information quality are positively correlated with perceived ease of use and usefulness;(3) perceived ease of use, usefulness, economic benefits, and their impact on individuals and organizations are all positively correlated with continuous usage intention; and (4) system quality is not significantly related to perceived ease of use or usefulness, nor is perceived trustworthiness significantly related to continuous usage intention. Based on these findings, we provide practical recommendations for optimizing NFT platforms and offer guidance for platform developers and operators.

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Show me your NFT and I tell you how it will perform: Multimodal representation learning for NFT selling price prediction

Cited by 14 publications

References 18 publications

Determinants of the purchase intention of non‐fungible token collectibles

Determinants of the purchase intention of non‐fungible token collectibles

NFT price and sales characteristics prediction by transfer learning of visual attributes

Continuous Use of NFT Trading Platforms: A Perspective Integrating the Expectation Confirmation Model and the Information Systems Success Model

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