A Research Program on the Gift as Economic Primitive, and the Register of Everything That Could Show It Wrong This document states a research program and the conditions under which it should be abandoned. The program's hard core is a single claim about direction: that value can be organized to move only forward — from giver to receiver to the next receiver — and that a system built on that constraint circulates better than one that permits return to the source. Four chapters name the ways the core can break: whether receiving creates the capacity to give, whether the constraint survives a change of currency, whether it survives past the family, and whether it survives the giver. Each chapter is attached to pre-registered predictions, published here as a register of sixty-six items with their falsifiers, their instruments, and their status. The program is published at a deliberate moment: almost nothing in it has been run. Two desk censuses have returned results, both null or partial-null. There have been no field tests. The first is gated on a product launch in August 2027. A register published after the data arrives cannot be distinguished from a register assembled to fit it; this one is published while the outcome is unknown, which is the only condition under which it constitutes evidence of anything. --- Provenance. This paper is part of the THonly research corpus, dedicated to the public domain under CC0 1.0. The canonical version is at https://thonly.org/research/which-way-value-moves. Its SHA-256 is 89dfd48398c1c23ec6613ae953a3b326a469f8a14e76258fcdabc46fea156d5b, independently timestamped to the Bitcoin blockchain via OpenTimestamps and signed under RFC 3161 by three trust authorities, one of them eIDAS-qualified. AI co-authorship is disclosed. Miss Aquarius is the consistent name used for the AI collaboration across all venues.
Vanessa Itacaramby Pardim, Luis Hernan Contreras Pinochet, Jhenifer Amore Castanho, Marcos dos Santos · 5 authors
Purpose This study aims to examine how heterogeneous stakeholder groups within the Brazilian non-fungible tokens (NFT) visual arts ecosystem prioritize acquisition criteria and evaluate market alternatives. Design/methodology/approach The study applies a quantitative multi-criteria decision-making approach to data from 128 participants grouped into artists/creators, designers/creative entrepreneurs, collectors/investors, and analysts/intermediaries. The criteria weights are derived using the method based on the removal effects of criteria, and five NFT-related alternatives are ranked using 11 compensatory multi-criteria decision-making techniques. Ranking robustness was assessed through stability and rank correlation analyses. Findings The results indicate stakeholder-sensitive decision patterns rather than sharply separated evaluative structures. NFT auctions have emerged as the dominant alternative for creative and analytical actors, whereas crowdfunding-based NFT projects are consistently preferred by collectors and investors. Criterion importance varies moderately among stakeholder groups, whereas alternative rankings exhibit greater stability across several aggregation methods. Practical implications The findings provide actionable insights for artists, platform managers, investors, and policymakers by demonstrating how different stakeholder groups evaluate NFT acquisition mechanisms. Understanding these differentiated decision patterns can support more targeted platform design, governance structures, and strategic positioning in NFT-based markets. Social implications This study highlights the importance of transparency, security, and stakeholder-sensitive governance in NFT-based creative ecosystems, particularly in emerging markets where digital assets remain institutionally unstable. Originality/value This study integrates institutional logics, digital innovation ecosystems, and multi-criteria decision-making to analyze NFT-related decisions from a multi-stakeholder perspective. It shows how NFT governance mechanisms and platform strategies can be aligned with different stakeholder priorities.
Prediction markets such as Polymarket are increasingly cited as real-time probability estimates for financial outcomes, yet it remains unknown whether their prices are consistent with the risk-neutral probabilities implied by options markets pricing the same events. Using 2,671 daily observations across 24 Gold and Silver CME futures threshold contracts over a six-month period, this paper finds that Polymarket systematically overprices the upside relative to Black-76 implied probabilities by 8.9 percentage points for Gold and 5.3 percentage points for Silver, a finding robust to seven independent checks and consistent in direction with a contemporaneous independent study on Bitcoin threshold contracts. The divergence exhibits AR(1) half-lives under three days, narrows significantly as expiry approaches, and cannot be fully explained by transaction costs or the commodity risk premium. These results suggest systematic mispricing in prediction market binary threshold contracts, though the observed magnitudes should be interpreted as upper bounds on behavioural mispricing given the structural wedge between risk-neutral and real-world probability measures.
Saskia Hufnagel, Colin King, Alina-Theresa Schnedl, Milind Tiwari
Non-fungible tokens (NFTs) bring many opportunities for artists, investors, and creators, but they also have a dark side with significant potential for use in financial crimes. Drawing on relevant caselaw, a systematic review and topic modeling of literature, we map common examples of NFT-related crime, including fraud, money laundering, theft, and market-related offenses. This empirical review lays the groundwork for the core contribution of this article, that is, application of the “crime triangle” to NFT-related crime. Recognizing heterogeneity in NFT-related crime, we detail five scenarios where such crime can occur and analyze these in the context of the crime triangle (inner and outer). This enables us to identify potential gaps and vulnerabilities in current crime prevention strategies. Given challenges in policing cybercrime, and specifically NFT-related crime, we argue that the crime triangle provides a useful heuristic tool for understanding the nature of NFT-related crime and for preventing such crime from happening.
This study examines the transformation of artistic ownership in fine arts through blockchain-based non-fungible tokens (NFTs). It explores how NFTs reshape traditional systems of provenance, authenticity, and value creation by decentralising ownership verification and embedding transaction records within blockchain infrastructure. Using a qualitative research design based on secondary data analysis, the study synthesises findings from academic literature, industry reports, and case studies of NFT marketplaces and institutional adoption. The analysis is grounded in Actor-Network Theory, Institutional Theory, and Cultural Economics, enabling a multidimensional interpretation of technological, institutional, and economic change. Findings indicate that NFTs reconfigure artistic ownership through programmable smart contracts, disrupt traditional intermediary roles in the art world, and introduce new forms of digital scarcity that drive speculative valuation. However, challenges such as regulatory ambiguity, environmental concerns, and market volatility remain significant. The study concludes that NFTs represent not merely a technological innovation but a structural transformation of ownership systems in contemporary fine arts. Keywords: Blockchain, NFTs, Artistic Ownership, Fine Arts, Digital Art Markets, Cultural Economics, Institutional Change
Rahman Najia, Mahbub Md. Seratul, Amin Md. Ruhul, Kazi Abdul Mannan
The rapid expansion of non-fungible tokens (NFTs) has transformed the digital art ecosystem by enabling decentralised ownership, new economic models, and global market access for artists and collectors. However, the sustainability of NFT-based art remains highly contested, particularly in relation to environmental, economic, and social dimensions. This study investigates stakeholder perceptions of sustainability in NFT-based art through a qualitative analysis of secondary data, including academic literature, industry reports, and documented narratives of artists and collectors. Grounded in socio-technical systems theory and sustainability transition theory, the study explores how technological developments, market dynamics, and social discourses shape sustainability perceptions. The findings reveal a complex and often contradictory landscape: while NFTs are perceived as empowering tools that enhance artistic autonomy and financial opportunities, they are also criticised for their environmental impact, speculative nature, and ethical challenges. Technological innovations such as proof-of-stake mechanisms and green NFTs are gradually reshaping perceptions, though scepticism persists. The study concludes that sustainability in NFT-based art is a socially constructed and evolving concept requiring integrated technological, economic, and social approaches. Keywords NFT art; sustainability perception; blockchain technology; digital art economy; green NFTs; socio-technical systems; sustainability transition
How do art entrepreneurs make decisions about adopting blockchain technologies? This study examines the link between non-fungible token (NFT) adoption and business outcomes. Through survey data from 35 Czech art market stakeholders, including curators, art dealers and galleries, we investigate the strategic decision to adopt NFT technology through the lens of digital entrepreneurship and digital affordance theory. Our results highlight the potential of NFTs in addressing historical challenges of the art industry, such as provenance tracking, authenticity verification and transaction transparency while also identifying challenges and adoption barriers, such as regulatory uncertainties. We also show that while respondents rate blockchain systems as potentially useful, the actual NFT adoption rate remains low. These findings provide actionable insights for stakeholders and contribute to entrepreneurship literature by investigating entrepreneurial decision-making in markets adopting digital innovations.
How do consumers form preferences when they cannot rely on established quality standards? We examined this question in the context of non-fungible token (NFT) art markets, where buyers lack evaluative anchors such as provenance, conventional aesthetic criteria, or institutional endorsement. We demonstrated that view counts, a social cue that reflects others' attention, are one key attribute. Across a 150-day observational dataset (N = 1,459,979), a pre-registered 20-wave panel study, and six experiments, we documented that artworks that attract early views accumulate disproportionately greater attention over time, while other artworks fall further behind. We showed that this “snowballing” effect is driven by investment motives. When consumers approach markets with the motive to invest rather than collect, they rely on others' attention as a proxy for market value. Two structural features of the NFT market amplify this reliance: high price volatility and purely digital ownership, both of which heighten the salience of investment outcomes. By attenuating volatility or introducing tangible ownership cues, we diminished this reliance on social signals. Our findings extend theory on social influence and digital consumption, demonstrating that in the absence of objective quality standards, social cues shift from supplementary information to the primary basis for preference formation.
By blurring the boundary between art and financial assets, non-fungible tokens (NFTs) have created regulatory ambiguity and criminogenic vulnerabilities in digital markets. The article applies the Howey Test to an original dataset of NFT-related cases that involve financial crime. As it turns out, functionally NFTs often resemble securities: they are characterized by information asymmetries, speculative dynamics, and weak oversight. These structural gaps make NFTs attractive to facilitate fraud, money laundering, wash trading, and nefarious exploitation on decentralized platforms and incidentally by way of traditional auction houses. NFTs highlight systemic limitations of analog regulatory frameworks to contain criminogenic risk posed by virtual assets. To enhance transparency, accountability, and consumer protection in evolving digital economies, the article concludes on a paradigm shift toward an adaptive, outcomes-based regulatory approach.
Australia's Anti-Money Laundering and Counter-Terrorism Financing Amendment Act 2024 (Cth), effective 1 July 2026, extends the national AML/CTF regime to designated non-financial businesses and professions. While art dealers are not expressly targeted by the reforms, the statutory definitions give rise to significant interpretive challenges at the intersection of art law and the regulatory framework, with potentially far-reaching consequences for the art market. This article critically examines three such challenges: the historical artist versus artisan distinction embedded in the legislation's reference to "goldsmith's or silversmith's wares"; the functional classification of objects that straddle the boundary between fine art and decorative art; and the degree of physical attachment required for an artwork to constitute a "precious product" by virtue of its material composition. The article further considers the extension of the regime to virtual assets, including non-fungible tokens, and its implications for digital art transactions. It concludes that the current definitional framework risks producing arbitrary regulatory outcomes, capturing certain art objects while excluding others of comparable money laundering risk, and recommends that art market participants adopt a precautionary compliance approach (including robust know your client procedures and readiness to satisfy designated services obligations) pending further regulatory guidance from AUSTRAC.
This research paper delves into the evolving domain of Non-Fungible Tokens (NFTs) within the unique backdrop of India’s art and entertainment industry, a realm where NFTs have garnered global attention as a novel digital asset class enabling the tokenization and ownership of distinct digital content. The paper’s key focus areas are threefold: First, it will scrutinize the legal framework governing NFTs in India, including existing laws, regulations, legal status, copyright, intellectual property, and taxation aspects, offering comparative insights from international NFT regulations. Second, the study will assess the economic implications of NFTs on artists, creators, and collectors, evaluating benefits, challenges, and illustrative case studies, while also delving into NFT market dynamics, trends, and the roles of key players and platforms. Third, it will explore the cultural and artistic implications of NFTs, examining their influence on artistic creation and the preservation of cultural heritage, as well as their impact on the relationship between traditional and digital art forms in India. Furthermore, the research will discuss future prospects and challenges within the Indian NFT landscape, considering potential developments, risks, and uncertainties, and offering recommendations for policymakers, artists, and industry participants. In conclusion, this research aims to illuminate the legal and economic facets of NFTs in India’s art and entertainment industry, fostering a deeper understanding of NFT implications for diverse stakeholders and providing invaluable guidance for navigating this dynamic landscape. This research endeavour aims to illuminate the legal and economic facets of NFTs in India’s art and entertainment industry. By offering a comprehensive analysis of the present state and future prospects, this paper provides valuable insights for stakeholders navigating this evolving NFT landscape. It also contributes to a deeper understanding of NFT implications for India’s cultural and artistic heritage, offering guidance for informed decision-making in this emerging digital era.
The digital art blistering phenomenon has transformed the manner in which art is produced and contextualized in the art markets in the world, though it has occasioned concerns that border issues of ownership, authenticity and provenance which are horrifyingly questioned. Easy reproduction, editing and re transmission, and proving the authorship and protecting of the artists is difficult in digital art. The provided paper explores the possibility of the blockchain technology being a secure and open method of controlling the ownership of the digital art object and enhancing the authenticity records. Blockchain helps in the creation of verifiable histories of digital assets that cannot be changed and this is done by allowing decentralized ledger keeping, cryptographic hash and smart contracts to be used to create the records. The article also involves the research of blockchain-based systems in particular with the involvement of Non-Fungible Tokens (NFTs) as the embodiment of a unique digital piece of art. It proposes a theoretical model that entails artist registration, tokenization of artwork, ownership tracking, and verifications to ensure the safety of provenance and authenticity. The implementation plan will outline the process of the implementation of a blockchain-based tool, namely, the decentralized storage and the automation of smart contracts, which will allow facilitating an effective transaction and the payment of royalty. Furthermore, a comparison of the advantages of introducing blockchain-based systems over traditional models of art ownership is described in terms of the security, transparency, and accessibility. The paper does list such problems as scalability, regulatory uncertainty and environmental issues, despite these advantages. Based on the findings, it can be concluded that blockchain technology can change the digital art ecosystems which provide a reliable platform of ownership verification and empowering artists, and also emphasize the need to conduct further research and sustainable development.
Artistic content, especially in the digital era, is increasingly susceptible to unauthorized appropriation, imitation, and misuse, often with little to no attribution to original creators. In this paper, an unified AI-assisted visual similarity-detecting system with a blockchain-based provenance-checking base is introduced to prevent art appropriation and securely and in interpretable and real-time apply digital copyright. With the help of a hybrid deep learning framework that consists of Vision Transformer (ViT) and ResNet-based architectures, the system compares the stylistic and structural characteristics of the artworks with those of cosine similarity, Euclidean distance, and style loss measurements. The triplet loss-trained visual encoder allows the model to be useful in distinguishing between direct copies, derivative works, and inspired originals. In an image-based art collection (designed as a WikiArt replica, though not a real WikiArt collection) of more than 10,000 examples, the framework obtained a high classification performance of 94.3, and exact copy performance (precision) of 96.4 and inspired work performance (precision) of 88.6. Artwork metadata and visual fingerprints are hashed with SHA-256 and stored on a permissioned blockchain (Hyperledger Fabric) to provide provenance records and immutable and to enforce copyright permissioned via smart contracts. The proposed system is more accurate in detection and explainable than the available tools like Google Reverse Search and the TinEye. It is also supplemented with Grad-CAM-based visual heatmaps and real-time smart contract execution as the dispute resolution. Further development of the model will focus on extending it to video art and 3D designs, as well as generative AI art (e.g., GANs, Diffusion), and the global copyright databases will be integrated to be universal. This system is a strong move towards the protection of the integrity and rights of Web3 digital artists.
Markets for cultural goods require intermediaries who construct the shared conventions, quality signals, and reputational infrastructure through which cultural value is assessed and stabilized. Non-fungible token (NFT) platforms assumed intermediary functions without this institutional apparatus, a condition we term unconventionalized intermediation. Drawing on cultural production scholarship and paradox theory, we analyze Reddit discourse related to NBA Top Shot, a prominent NFT platform, to examine how NFT cultural markets persist under this structural condition. Our analysis reveals three aggregate paradoxes structuring collector participation – precious precarity (disrupted value construction), enslaved freedom (disrupted governance), and resonant isolation (disrupted meaning circulation) – each arising from a specific failure of the cultural production processes that conventionalized intermediaries normally perform. We further identify six management mechanisms through which collectors and platforms collaboratively navigate these tensions. Our findings extend strategic marketing scholarship on digitally mediated cultural markets and offer practical implications for artists, art market institutions, and platform operators.
The digital art and collectibles industries are undergoing a significant transformation due to a phenomenon known as Non-fungible Tokens (NFTs). Enabled by smart contracts on a blockchain, NFTs thus provide creators with unparalleled control. They can be used to indicate the ownership of any unique object by serving as a deed for that item, whether it exists in the physical or digital world. This research aims to shed light on various obstacles to the widespread adoption of NFTs. A semi-structured interview was conducted with customers of NFT marketplaces to draw out valuable insights across diverse scenarios. The interview method has been utilized to observe and assess the perspectives of individuals who have engaged in marketplace transactions. Furthermore, a cognitive walkthrough was executed to evaluate the marketplace’s usability from a newcomer’s viewpoint. The insights gathered from the interviews and cognitive evaluation have pinpointed significant pain points and opportunities for improvement. The findings show that both experienced users and newcomers are seeking enhancements to the marketplaces before they are willing to embrace this technology on a larger scale. Their recommendations vary from ensuring safer ecosystem development to improving user interfaces. We present a review of our findings from multiple angles, addressing areas where challenges are evident and we suggest potential modifications to boost the promotion of NFTs. In conclusion, based on our results, we recommend an ideal design along with several essential strategies akin to other standard applications that could be implemented in the markets for greater acceptance.
NFT (Non-Fungible Token) art, fueled by blockchain technology and its connection to virtual currencies, gained significant attention beyond the art world. However, after peaking in 2021, interest and trading activity declined and eventually stagnated. This study examines the research landscape and market dynamics of the NFT art system from a systemic perspective, proposing future research directions. We utilize the Technology Adoption Life Cycle (TALC) and the concept of the Chasm, compiling abstracts of 153 Scopus-indexed articles up to October 2024, along with market data from various platforms. Using VOSviewer, we categorize the literature by research type while analyzing transaction data.Our findings reveal that prior research on the NFT art market predominantly focuses on the pre-chasm stage of the TALC, highlighting the innovative nature of digital art as a medium of exchange and the decentralization it promotes. Based on these results, we recommend that future studies investigate the reasons behind the stagnation of the NFT art market, particularly by addressing the challenges of valuing intangible assets from the perspective of market stakeholders. Furthermore, additional research should explore system-level strategies that can enhance broader adoption and support the sustainable growth of NFT art.
This study investigates the correlation between the audio features of top-charting music and Non-Fungible Tokens (NFT) market dynamics, presenting a novel perspective within the realm of behavioral finance. Drawing on the regulatory focus theory and existing research on music's affective influence, the authors argue that popular music, as a reflection of society's collective regulatory focus, can significantly impact trading behaviours in NFTs, an asset class known for its susceptibility to emotional drivers and speculative activity. By employing a Long Short-Term Memory (LSTM) machine learning model and permutation importance technique, the analysis demonstrates that specific musical attributes—such as danceability, loudness, and mode—exhibit predictive power over daily NFT trading volumes. The study not only provides evidence of music's capacity to signal shifts in trading behaviors, offering innovative insights into the drivers of digital asset markets, but introduces a new interdisciplinary approach focusing on the collective regulatory focus reflected in the music.
This paper presents an analysis of five years (2021 - 2025) of conference discourse across six digital art conferences, aiming to trace thematic shifts associated with the rapid development of emerging technologies, namely artificial intelligence (AI), immersive technologies (including XR and the metaverse), and blockchain technologies and non-fungible tokens (NFTs). The results indicate a marked increase in AI-related contributions, while immersive technologies maintain a relatively stable share of the discourse, and blockchain- and NFT-based works remain marginal. Overall, whereas immersive technologies and blockchain-related topics exhibit relative stability, AI shows a significant rise after 2022, emerging as a dominant theme within digital art conference discourse.
In the context of smart cities, Non-Fungible Tokens (NFTs) are transforming digital art markets by enabling secure, decentralized transactions. As NFT trading grows, incorporating intelligence and adaptability becomes crucial—making Machine Learning (ML) integration essential. However, existing models, particularly Cooperative Game Theoretic Trading (CoGTT) frameworks, underutilize ML across all trading phases. Key gaps include limited real-time adaptability, suboptimal negotiation strategies, and inadequate buyer–seller matchmaking. This research addresses these gaps by integrating ML into a three-phase CoGTT framework—ML-augmented Naive Trading, Min–Max Price Negotiation, and Equilibrium-Based Trading—to enhance decision-making and pricing. The methodology applies ML algorithms such as decision trees, clustering, and reinforcement learning (Q-learning) within a public blockchain–based simulation environment using smart contracts. The simulation uses a customized dataset reflecting both market dynamics and artist credibility. The dataset is synthetically generated to emulate an NFT marketplace while maintaining controlled experimental conditions, which may limit direct applicability to volatile real-world markets. Zero-knowledge proofs (ZKPs) are employed to preserve privacy. ZKPs are employed to preserve privacy. A comparative analysis of ML models for NFT price estimation and strategic bidding demonstrates the effectiveness of combining predictive algorithms with reinforcement learning. Linear Regression and Random Forest models both accurately estimate NFT prices, with Random Forest achieving higher real-time prediction accuracy (R2 = 0.9920). K-Means clustering effectively segments market participants to support targeted negotiation, achieving a silhouette score of 0.8178. Integrating Q-learning with Random Forest enables dynamic bidding strategies that minimize the gap between recommended and actual prices. The discrete action set (decrease, stay, increase) supports interpretable, real-time bid adjustments. These findings highlight the potential for ML-driven NFT trading systems to support scalable, privacy-compliant digital marketplaces in smart cities, aligning trading behavior with market demands through automated, data-driven processes.
This study examines the pricing dynamics of Non-Fungible Tokens (NFTs) in the secondary market using advanced machine-learning techniques. We construct a large dataset of Ethereum-based NFT transactions initially comprising over 500,000 raw blockchain observations spanning multiple NFT segments, including art, collectibles, gaming, metaverse, and utility assets, over the period from November 2018 to March 2023. Following data preprocessing, synchronization across data sources, and the construction of history-dependent features, the analysis focuses on a final analytical sample of approximately 70,000 transactions. To address the challenges of non-fungibility, thin trading, and high price dispersion, we develop an interpretable predictive framework that integrates domain-informed manual feature engineering, automated Deep Feature Synthesis, and dimensionality reduction via Principal Component Analysis. Three non-linear models—Random Forest, XGBoost, and a Multilayer Perceptron—are trained and evaluated using both random and time-aware validation strategies. The results indicate that XGBoost consistently achieves the highest predictive accuracy, both overall and across individual NFT segments, while historical transaction prices emerge as the dominant predictor of future prices. Segment-level analysis reveals substantial heterogeneity in predictability, with art and collectible NFTs exhibiting more stable pricing patterns than gaming and metaverse assets. Overall, the findings highlight strong path dependence and reputation-driven valuation in NFT markets and demonstrate that carefully designed machine-learning models can deliver high predictive performance without sacrificing economic interpretability.
Abstract NFTs or non-fungible tokens are digital assets stored on a blockchain. They can be traded or exchanged for money, cryptocurrencies or other NFTs. Examples include works of art and digital or other tokenised collectables. An important determinant of price for collectables is rarity within a collection. Many trading platforms offer to rank items in terms of rarity but rankings differ considerably and, often, little explanation is given of the methods used. This paper provides a mathematical framework for the analysis of a comprehensive class of collections. It examines individual and joint distributions of attributes over such collections, and shows how these can be combined to provide a rarity ranking for all items in the collection. There is, however, only a limited range of methods that give consistent results over different collections. These are identified as belonging to a one-parameter family of ranking functions. Each gives to every item of a collection a rarity score that is directly comparable between collections. Despite taking account of all possible combinations of attributes when ranking, the method is nonetheless computationally feasible.