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This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

Given the rise of sport non-fungible tokens (NFTs) and sponsorships from cryptocurrency companies in the sport industry during the coronavirus disease 2019 (COVID-19) pandemic, this paper aims to critically frame the partnerships between cryptocurrency and sport by exploring the reception of fan tokens amongst supporters of three English Premier League clubs: Manchester City, Everton and Crystal Palace.

Drawing upon the emerging critical scholarship on cryptocurrency and the political economy of professional football, this study uses digital ethnography in an attempt to understand the major themes emanating from the online forum discussions amongst fans in response to the issuance of fan tokens by the aforementioned three clubs, among other types of partnerships with crypto companies.

The supporters’ critical deliberations revolved around the contradictions of fan tokens (as a means for supposed “fan engagement” or for financial speculation) and the utility of cryptocurrency for the public. These reactions in turn showcase a larger tension underlying the financially unstable professional football industry: the contest between the owners and the fan bases over the exchange value (for profit) and use value (for community) of the clubs.

This paper is one of the first studies to adopt a critical framework to examine the emerging partnerships between sports and cryptocurrency companies during the COVID-19 pandemic. It also provides one of the first in-depth analyses of the critical receptions of sport NFTs amongst sport fans. While contributing to the literature on fan activism/protest in the context of the commercialization and commodification of sport, the paper also raises new questions on the responsible use of cryptocurrency/NFT in sport.

The purpose of this study is to identify the possible efficiency gains in using tokenization for the execution of public expenditure on governmental investments.

Through design science research methodology, the exploratory research produced a tokenized prototype in the blockchain, through the Ernst and Young OpsChain traceability solution, allowing automated processes in the stages of public expense. A focus group composed of auditors from the public sector evaluated the possibility of improving the quality of information available in the audited entities, where the tokens created represent and register the actions of public agents in the blockchain Polygon.

The consensus of the experts in the focus group indicated that the use of tokenization could improve the quality of the information, since the possibility of recording the activities of public agents in the metadata of the tokens at each stage of the execution of the expenditure allows the audited entities the advantages of the information recorded on the blockchain, according to the following ranking: first the immutability of audited data, followed by reliability, transparency, accessibility and efficiency of data structures.

This research makes an empirical contribution to the real use of tokenization in blockchain technology to the public sector through a value chain in which tokens were created and moved between the wallets of public agents to represent, register and track the operations regarding public expense execution.

This paper aims to establish a fundamental and comprehensive understanding of non-fungible tokens (NFTs) by identifying and structuring common characteristics within a taxonomy. NFTs are hyped and increasingly marketed as essential building blocks of the Metaverse. However, the dynamic evolution of the NFT space has posed challenges for those seeking to develop a deep and comprehensive understanding of NFTs, their features and their capabilities.

Utilizing common guidelines for the creation of taxonomies, the authors developed (over 3 iterations), a multi-layer taxonomy based on workshops and interviews with 11 academic and 15 industry experts. Through an evaluation of 25 NFTs, the authors demonstrate the usefulness of the taxonomy.

The taxonomy has 4 layers, 14 dimensions and 42 characteristics, which describe NFTs in terms of reference object, token properties, token distribution and realizable value.

The authors' framework is the first to systematically cover the emerging NFT phenomenon. This framework is concise yet extendible and presents many avenues for future research in a plethora of disciplines. The characteristics identified in the authors' taxonomy are useful for NFT- and Metaverse-related research in finance, marketing, law and information systems. Additionally, the taxonomy can serve as an information source for policymakers as they consider NFT regulation.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

This paper aims to explore the problem of power imbalance within decentralized autonomous organizations (DAOs) and propose potential solutions that could contribute to enhancing the democratic nature of DAOs.

In this paper, the authors apply a qualitative methodology. Using a thematic coding analysis, the authors process data collected from interviews with 11 experts.

Multiple factors contribute to the perceived lack of democracy within DAOs, such as token concentration and effective stakeholder communication. Next, quadratic voting has the potential to enhance democracy within DAOs, but this mechanism must be implemented mindfully. Finally, the results were nuanced when it comes to the effectiveness of liquid democracy in DAOs to enhance voter participation and representation.

To the best of the authors’ knowledge, this paper is one of the first research contributions to propose recommendations to address the power imbalance within DAOs and to contribute to the advancement of decentralized decision-making structures.

The scarcity of women in advertising creative departments has been reported globally, particularly in creative managerial roles. This study goes a step beyond this evidence since this paper aims to test whether having at least one token woman in creative managerial positions (token+) may be associated with a larger presence of females in low-level creative jobs compared to creative departments led only by male creative managers.

A content analysis of the credit forms of 839 Spanish campaigns released in 2019 was conducted to determine the gender composition of 116 creative departments with more than three professionals.

Generalized Poisson Regressions indicated that when at least a token woman is present in a creative management role within agency networks, the number of females in low-level positions doubles with respect to creative departments led only by male managers. This relation was not found for independent agencies, though. The results are discussed under the lens of critical mass theory, attraction paradigm and homophily theory.

To the best of the authors’ knowledge, it is the first time in the literature that the relation among the number of token+ advertising female creative managers and the amount of females in lower-level creative positions is tested. This research is also original because the sample is from a non-Anglo-Saxon country. Moreover, the use of the Generalized Poisson Regressions technique is another novelty of this paper.

Situated in the context of India, where women’s representation on corporate boards remains low, this study aims to explore whether and how tokenism impacts the behaviours of female directors.

The boardroom experiences and perceptions of 14 women directors are explored through semi-structured interviews and analysed using an inductive and interpretive process. Also, to get a counter perspective and avoid the social desirability bias from the women participants’ responses, 16 men directors are interviewed.

The study finds that, as gender minorities, women directors' visibility on boards can create performance pressures on these women. To counter gender-based prejudices, women directors consciously alter their behaviours and project both male and female traits consistent with the director role. By doing so, women directors overcome tokenistic stereotypes and are accepted as part of the director in-group, irrespective of their numeric representation on the board.

The research has implications for governments attempting to increase women’s board presence through affirmative actions and for firms aiming to improve the gender diversity of their board composition.

These findings present an alternative perspective on women directors’ board behaviour by exploring the applicability of Western trends on tokenism and critical mass in the context of India, adding to the vast body of literature concerned with minorities on corporate boards.

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

This study aims to review the current EU approach to regulating crypto assets. It highlights the key points, opportunities and risks of the MiCA regulation, which is designed to provide a comprehensive regulatory framework for digital assets in the EU.

To do so, the authors extensively reviewed the literature and reports from several advisory and watchdog bodies and international organizations.

Although MiCA is an ambitious piece of legislation, there are still many unresolved issues and questions that the new regulation raises. Controversially several items have also been excluded from the MiCA regulations, including decentralized finance, non-fungible tokens unless they qualify under the existing cryptocurrency categories, as well as central bank digital currencies.

This study also addresses the Liechtenstein Token Act Regulation, which is considered to have served as a model for the EU MiCA Directive and the regulation of cryptocurrencies at the European level.