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This study aims to explain how cryptocurrency is leveraged for illicit purposes across the global financial system. Specifically, it establishes how cryptocurrency has been changing the nature of transnational and domestic money laundering (ML). It then assesses the effectiveness of conventional anti-money laundering (AML) policy and legislation against the proliferation of crypto laundering, using Canada as a critical case study.

Data was collected from court cases and secondary sources to build cross-case trends of cryptocurrency use in ML. Illicit International Political Economy forms the theoretical foundation for this study, whose contribution is situated in the current literature on crypto-ML.

This study finds that Bitcoin is common among crypto-money launderers, though most also use some form of alt-coin, and that the use of third-party currency exchanges is a prevalent method to create illicit funds and conceal proceeds of crime. The findings validate two hypotheses that illicit use of crypto is prevalent in the first two stages of ML, and that crypto is most often used in conjunction with other fiat currencies. Although law enforcement is improving on monitoring and understanding popular cryptocurrencies such as Bitcoin, alt-coins pose a significant challenge for criminal intelligence. New regulations for third-party currency exchanges are having a positive impact on curtailing crypto-laundering but are shown to be insufficient per se to contain the use of crypto in criminal activity.

This study contributes to a more robust understanding of the use of virtual currency in transnational and domestic ML. It contributes to an emerging body of literature on the role of technological change in enabling the global flow of illicit funds. It also informs public policy on virtual currency in general, and on AML regulation in Canada in particular.

This study aims to explore how to deanonymize cryptocurrency money launderers with the help of machine learning (ML). Money is laundered through cryptocurrencies by distributing funds to multiple accounts and then reexchanging the crypto back. This process of exchanging currencies is done through cryptocurrency exchanges. Current preventive efforts are outdated, and ML may provide novel ways to identify illicit currency movements. Hence, this study investigates ML applicability for combatting money laundering activities using cryptocurrency.

Four supervised-learning algorithms were compared using the Bitcoin Elliptic Dataset. The method covered a quantitative analysis of the algorithmic performance, capturing differences in three key evaluation metrics of F1-scores, precision and recall. Two complementary qualitative interviews were performed at cryptocurrency exchanges to identify fit and applicability of the algorithms.

The study results show that the current implemented ML tools for preventing money laundering at cryptocurrency exchanges are all too slow and need to be optimized for the task. The results also show that while not one single algorithm is most suitable for detecting transactions related to money-laundering, the specific applicability of the decision tree algorithm is most suitable for adoption by cryptocurrency exchanges.

Given the growth of cryptocurrency use, this study explores the newly developed field of algorithmic tools to combat illicit currency movement, in particular in the growing arena of cryptocurrencies. The study results provide new insights into the applicability of ML as a tool to combat money laundering using cryptocurrency exchanges.

The current study aims to investigate if different measures related to online psychosocial well-being and online behavior correlate with social media fatigue.

To understand the antecedents and consequences of social media fatigue, the stressor-strain-outcome (SSO) framework is applied. The study consists of two cross-sectional surveys that were organized with young-adult students. Study A was conducted with 1,398 WhatsApp users (aged 19 to 27 years), while Study B was organized with 472 WhatsApp users (aged 18 to 23 years).

Intensity of social media use was the strongest predictor of social media fatigue. Online social comparison and self-disclosure were also significant predictors of social media fatigue. The findings also suggest that social media fatigue further contributes to a decrease in academic performance.

This study builds upon the limited yet growing body of literature on a theme highly relevant for scholars, practitioners as well as social media users. The current study focuses on examining different causes of social media fatigue induced through the use of a highly popular mobile instant messaging app, WhatsApp. The SSO framework is applied to explore and establish empirical links between stressors and social media fatigue.

The purpose of this paper is to critically evaluate the meaning of being a social entrepreneur in a society marked with multiple transitions. It aims to understand how theoretical concepts of social entrepreneurs, including common dichotomies between economic and social, collective and individual, reflect in social entrepreneurs’ rationale, values and identities.

The study used an exploratory and qualitative approach. Empirical data were gathered during 14 semi-structured interviews with Croatian social entrepreneurs. Thematic analysis was used as an analytical framework.

The findings suggest complexity of social entrepreneurs’ rationale and identities as they face challenges in balancing different goals. Democratic and participative governance appeared to be the weakest link of social enterprises. Identity of social entrepreneurs in the society of multiple transitions is fluid and changes through the continuum from pure social to pure commercial, from more related to civil society to more related to the market, from mostly individual to mostly collective.

The main limits of the study are related to sampling strategy and the small sample size. Generalization is limited by the nature of qualitative research and relies on analytical and naturalistic generalization.

The findings of the study may contribute to ecosystem development that would be more suitable for social enterprise realities in a specific context.

This paper focuses on the individual level and provides rare insights into social entrepreneurs’ rationale, values and identities.

Universities play an important role in the promotion and implementation of the 2030 Agenda for Sustainable Development. This study aims to examine the visibility of information about the Sustainable Development Goals (SDGs) on the websites of Spanish and major international universities, by means of a quantitative and qualitative analysis with an online visibility management platform that makes use of big data technology.

The Web visibility of the universities studied in relation to the terms “SDG”, “Sustainable Development Goals” and “2030 Agenda” was determined using the SEMrush tool. Information was obtained on the number of web pages accessed and the queries formulated (query expansion). The content indexed by Google for these universities was compiled, and finally, the search engine optimization (SEO) factors applicable to the websites with the highest Web visibility were identified.

The universities analysed are content creators but do not have very high Web visibility in Web searches for information on the SDGs. Of the 98 universities analysed, only four feature prominently in search results.

Although research exists on the application of SEO to different areas, there have not, to date, been any studies examining the Web visibility of universities in relation to Web searches for information on the 2030 Agenda. The main contributions of this study are the global perspective it provides on the Web visibility of content produced by universities about the SDGs and the recommendations it offers for improving that visibility.

The paper intends to show the role of fear of COVID-19 and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions (CU_PV_DST) in promoting green bank service purchase intention (GBS_PI), despite the antagonistic impacts brought in other sectors and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions (CU_PV_DST) as important mediating variables of the relation.

The structured questionnaire helped collect survey data from 323 small business people. The model relationship was assessed through EFA, CFA by SPSS-AMOS and SEM using bootstrapping procedures in Smart-PLS.

The findings of this study show that there is a significant effect of fear of COVID-19 pandemic (F_COVID-19P) on CU_EMP and GBS_PI. CU_EMP influences GBS_PI, whereas F_COVID-19P influences GBS_PI indirectly via CU_EMP. Furthermore, there is a substantial effect of F_COVID-19P on CU_PV_DST and GBS_PI. Thus, F_COVID-19P significantly influences GBS_PI indirectly via CU_PV_DST.

Capitalizing on the COVID-19 wave by empowering customers technologically, improving the legal framework and increasing the perceived value of green service by using an innovative mechanism. In addition, fostering cultural change and emphasizing altruistic values through green advertisements have been explored in this study.

Green services are healthier for smart/green economy and are health-protective for coping with health risks.

This study helps in understanding the theories used in this context by linking them to F_COVID-19P with CU_EMP, CU_PV_DST and GBS_PI and contributes to the literature of both. Furthermore, this is the only study that has used SEM to study this kind of interrelation.

This review aims to provide an overview of research from different academic disciplines to chart some of the key developments in retail cryptocurrency trading against the backdrop of the wider trading landscape, and how it has evolved in recent years. The purpose of this review is to provide researchers with a broad perspective to highlight the complex range of factors that drive cryptocurrency trading among retail investors.

Peer-reviewed literature from the social sciences, economics, marketing and branding disciplines is synthesised to explicate influential factors among retail cryptocurrency investors.

Online retail trading communities can create narratives that ascribe value to cryptocurrencies leading to consumer herding behaviours. The principles that underpin emotional branding and Fear of Missing Out can promote trading behaviour driven by heuristic processing and cognitive biases. Concurrently, the tenets of controversial marketing and the anti-establishment nature of Bitcoin and other cryptocurrencies serve to bolster in-group out-group categorisations fostering continued investment and market volatility. Consequently, Bitcoin and cryptocurrency trading more broadly offer a powerful combination of excitement from risk-taking akin to gambling buffered by the sanctity of social inclusion.

A broader, unique perspective on retail cryptocurrency trading which assists in better understanding the complexities that underpin its appeal to retail investors.

Blockchain, which was originally created to enable peer-to-peer digital payment systems (bitcoin), is considered to have several benefits for different sectors, such as the real estate one. In a standard European-wide real estate transaction, several intermediaries are involved. As a consequence, these agreements are usually time-consuming and involve extra difficulties to cross-border operations. As blockchain, combined with smart contracts, may have an important role in these transactions, this paper aims to explore its prospective challenges, limitations and opportunities in the real estate sector and discover how the traditional intermediaries have to face a possible implementation of this technology.

This paper analyses the current intermediaries in the real estate sector in European Union (EU), their functions and how can blockchain strengthen the security of these transactions while reducing their time. The author uses a legal methodology to approach it.

Blockchain, combined with smart contracts, has both challenges and opportunities for the real estate sector. On the one hand, it may improve procedures, allow EU transactions and the interconnection between public administration. However, to not reduce parties rights, this blockchain should have some special features, such as the possibility of being amended.

This paper provides a valuable overview of all the intermediaries that could be affected by blockchain protocols. It is of interest of blockchain developers, public administrations and researchers who are working on blockchain and property conveyancing.

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.