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This paper aims to develop a theoretical framework to predict susceptibility to cyber-fraud victimhood.

A survey was constructed to examine whether personality, socio-demographic characteristics and online routine activities predicted one-off and repeat victimhood of cyber-fraud. Overall, 11,780 participants completed a survey (one-off victims, N = 728; repeat victims = 329).

The final saturated model revealed that psychological and socio-demographic characteristics and online routine activities should be considered when predicting victimhood. Consistent with the hypotheses, victims of cyber-frauds were more likely to be older, score high on impulsivity measures of urgency and sensation seeking, score high on addictive measures and engage in more frequent routine activities that place them at great risk of becoming scammed. There was little distinction between one-off and repeat victims of cyber-frauds.

This work uniquely combines psychological, socio-demographic and online behaviours to develop a comprehensive theoretical framework to predict susceptibility to cyber-frauds. Importantly, the work here challenges the current utility of government websites to protect users from becoming scammed and provides insights into methods that might be used to protect users from becoming scammed.

This paper aims to shed light into money laundering using bitcoin. Digital payment methods are increasingly used by criminals to launder money obtained through cybercrime. As many forms of cybercrime are motivated by profit, a solid cash-out strategy is required to ensure that crime proceeds end up with the criminals themselves without an incriminating money trail. The authors examine how cybercrime proceeds can be laundered using services that are offered on the Dark Web.

Focusing on service-percentages and reputation-mechanisms in underground bitcoin laundering services, this paper presents the results of a cash-out experiment in which five mixing and five exchange services are included.

Some of the examined services provide an excellent, professional and well-reviewed service at competitive cost. Whereas others turned out to be scams, accepting bitcoin but returning nothing in return.

The authors discuss what these findings mean to law enforcement, and how bitcoin laundering chains could be disrupted.

These cash-out strategies are increasingly facilitated by cryptocurrencies, mainly bitcoin. Bitcoins are already relatively anonymous, but with the rise of specialised bitcoin money laundering services on the Dark Web, laundering money in the form of bitcoins becomes available to a wider audience.

Incidents of violence perpetrated through digital technology platforms or facilitated by these means have been reported, often in high-income countries. Very little scholarly attention has been given to the nature of technology-facilitated violence and abuse (TFVA) across sub-Saharan Africa (SSA) despite an explosion in the use of various technologies. We conducted a literature review to identify and harmonize available data relating to the types of TFVA taking place in SSA. This was followed by an online survey of young adults through the SHYad.NET forum to understand the nature of TFVA among young adults in SSA. Our literature review revealed various types of TFVA to be happening across SSA, including cyberbullying, cyberstalking, trolling, dating abuse, image-based sexual violence, sextortion, and revenge porn. The results of our online survey revealed that both young men and women experience TFVA, with the most commonly reported TFVA being receiving unwanted sexually explicit images, comments, emails, or text messages. Female respondents more often reported repeated and/or unwanted sexual requests online via email or text message while male respondents more often reported experiencing violent threats. Respondents used various means to cope with TFVA including blocking the abuser or deleting the abused profile on social media.

Are financially illiterate individuals all the same? This study aims to answer this question. Specifically, the authors investigate whether people answering incorrectly and “do not know” to the big five questions about financial knowledge (FK), all identified by previous literature as financially illiterate, are two sides of the same coin, or rather individuals with different socio-economic and demographic characteristics, and whether this leads to different levels of risk of falling victim to financial fraud.

Using a large and representative sample of Italian adults, the authors run both ordered probit and probit regressions to test the determinants of financially illiterate individuals, distinguishing between those answering FK questions incorrectly and those answering “do not know”. The authors also measure the probability of falling victim to financial fraud for the two groups. To check the robustness of our results, the authors run a multinomial regression, a structural equation model and an instrumental variable regression model.

The authors demonstrate that the socio-demographic and socio-economic characteristics of individuals selecting incorrect responses to FK questions are different from those of individuals selecting the “do not know” option. Moreover, the results show that the former are more likely to be victims of financial frauds.

The “one-size-fits-all” approach is not suitable for financial education. It is important to consider socio-demographic and socio-economic characteristics of individuals in order to identify specific targets of education programmes aiming to reduce insecurity and excessive self-confidence as well as to increase objective FK. The study’s findings also identify vulnerable groups to which financial fraud prevention schemes should be targeted.

To date, financial illiteracy has been measured as the sum of incorrect and “do not know” responses given to FK questions. This approach does not allow to observe the socio-demographic and socio-economic differences between people choosing the “do not know” option and those answering incorrectly. The paper aims to overcome this limit by investigating the socio-demographic and socio-economic characteristics of individuals selecting “do not know” and incorrect responses, respectively. The authors also investigate whether the two groups have different probabilities of being victims of financial fraud.

Although we have achieved a greater understanding of cryptomarket specifics, evidence on the consumer side of cryptomarkets is still needed – not only regarding the role of cryptomarkets on individual drug-using careers but also on the motives for buying illicit drugs from cryptomarkets. Moreover, research has indicated that national differences exist regarding different variables relating to cryptomarket use and prevalence, as well as to why users are drawn to these markets. In this chapter, the author presents the results of a Belgian case study focusing on drug cryptomarket buyers. Using an online quantitative survey (N = 99) and semi-structured interviews (N = 10), we gain exploratory insight into the motives of Belgian buyers sourcing illicit drugs from cryptomarkets and how they believe these cryptomarkets affect their drug-using careers. Results indicate that most of the respondents had bought drugs offline before buying them from cryptomarkets and that the frequency of their drug use did not change once cryptomarkets were accessed. Almost 60% of our respondents, however, consumed different drugs or a wider range of drugs following their cryptomarket use. Furthermore, most of the respondents purchased from cryptomarkets for their personal consumption, and some of them also shared their supply with friends, that is, social supply. The alternative drug offer was the principal reason why they were using cryptomarkets, followed by curiosity and the price and the quality of the drugs. Although the respondents in this study were well aware of different risks related to market vendors, market administrators, and law enforcement, these risks were considered to be minimal and part of the cryptomarket environment. The results of this case study are informative and highlight areas requiring further research.

Online shopping around the world is growing exponentially, especially during the COVID-19 pandemic. This study aims to examine how an online customer's purchasing experience influences his/her buying intention and willingness to believe in fraud news, as well as the ripple impact of satisfaction and trust, with gender as a moderator in an emerging economy during COVID-19.

Based on the underpinning of the stimulus-organism-behavior-consequence (SOBC) theory, the research model was developed, and collected data from 259 respondents using convenience samples technique. Next, the data were analyzed using partial least squares-based structural equation modeling (PLS-SEM), SPSS (Statistical Package for the Social Sciences) and Hayes Process Macro.

The study results confirmed that the online shopping experience (OSE) has positive impact on customers' satisfaction (CS), purchase intention (PI) and customer trust (CT); CS has positive effects on trust toward online shopping and their future product PI; future product PI significantly affects customers' propensity to believe and act on fraud news (PBAFN). The finding also states that gender moderates the relationships of CS to PI, OSE to PI and PI to PBAFN, but doesn't moderate the CT to PI relationship.

The study findings will assist policymakers and online vendors to win customers' hearts and minds' through confirming satisfaction, trust and a negative attitude toward fake news, which will lead to customer loyalty and the sustainable development of the industry. Finally, the limitations and future research directions are discussed.

The sale of NFTs and the interest in them has “exploded” recently. While there is a lot of information on them, it is not clear what final form they will take. There are several reasons to be uneasy, such as the prevalence of scams, but there are also reasons for optimism and confidence in NFTs. First, they solve the problem of how to own digital assets. Additionally, some of the more reliable and proven cryptoasset exchanges are offering them. However, this innovation will have difficulties reaching a wider audience until more clarity is achieved on two main issues. Therefore, this study aims to clarify what the NFT business models are, and how do they build trust.

This research attempts to identify the NFT business models with case study analysis in three stages. The first stage is a focus group, followed by 16 short case vignettes and finally four longer case studies.

The findings show that there are four NFT business models: (1) NFT creator; (2) NFT marketplace, selling creators’ NFTs; (3) company offering their own NFT (fan token) and (4) computer game with NFT sales.

This research brings the literature on business models and NFTs together to offer clarity on the proven NFT business models.