As smartphone ownership rapidly expands, mobile payment options are gaining popularity due to the portability and convenience they offer. This study examines attitudes towards adopting mobile payment, focusing on the component risk, which consists of multiple dimensions including performance, financial, time, psychological, and social risks. The study uses a quantitative approach, collecting data through a survey distributed to mobile payment users, with 361 respondents in the United States. The survey instrument includes measures of performance and psychological risk, as well as attitudes towards mobile payment acceptance. Data analysis using SPSS 25.0 and AMOS 24.0 reveals that both performance and psychological risk significantly negatively impact attitudes towards mobile payment acceptance, underscoring the importance of mobile payment service providers implementing effective risk management policies to improve users’ positive attitudes towards their platforms.

With their potential for high returns and expanding role in the financial landscape, cryptocurrency investments have garnered the attention of the financial press and investors. Applying an integrated research model based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates the factors influencing individual investors’ attitudes toward cryptocurrency investments and their intention to continue investing. The model incorporates constructs such as performance expectancy, effort expectancy, social influence, perceived risk, perceived privacy, technology competency, perceived enjoyment, and prior experience. Data from 506 cryptocurrency investors located in the United States were collected through a 50-item questionnaire. The findings indicate that performance expectancy and perceived enjoyment positively impact attitudes toward cryptocurrency investments, which, in turn, influence the intention to continue investing. Perceived privacy positively affects performance expectancy, while technology competency enhances effort expectancy. These results offer valuable insights for policymakers and cryptocurrency exchanges to foster sustainable growth in the cryptocurrency market. Despite its contributions, the study acknowledges limitations, including a focus on current investors in the US and the exclusion of factors such as optimism and innovativeness. Future research should explore these aspects across different populations and regions to gain a more comprehensive understanding of cryptocurrency investment behavior.

Cryptocurrencies, as a disruptive innovation in the financial sector, are reshaping traditional investment behaviors. Despite their growing adoption, many individuals remain hesitant to invest, influenced by both psychological and technological factors. This study integrates behavioral finance principles with the Unified Theory of Acceptance and Use of Technology (UTAUT), incorporating perceived security, perceived enjoyment, technology competency, and personality traits to examine their effects on cryptocurrency investment attitudes and intentions. Data from U.S. investors highlight how these factors shape investment decisions, with a particular focus on the moderating role of personality traits in the relationship between attitude and investment intention. Findings reveal that performance expectancy, perceived enjoyment, and perceived security significantly influence attitudes toward cryptocurrency investment and drive investment intention. Interestingly, openness negatively moderates this relationship, suggesting that individuals with high openness may be less likely to act on positive investment attitudes. However, other predictors including facilitating conditions, extraversion, agreeableness, conscientiousness, and neuroticism did not demonstrate any significant influence on investment attitudes or intentions. These insights contribute to the behavioral finance literature by highlighting how psychological and technological factors influence investment behavior. Practical implications extend to businesses, policymakers, and cryptocurrency platforms seeking to better understand and engage potential investors. Future research should explore additional behavioral and technological factors across diverse investor demographics and geographic contexts to further advance knowledge in this evolving field.

Recently, Richard Thaler was awarded a Nobel Prize for his work in developing Behavioral Economics. While much of economics assumes that people act rationally, Areily (2008), expanding on Thaler’s body of work, proves that we are not only often irrational, but we are predictably irrational. When an interviewer asked Thaler how he would spend the roughly $1.1 million in prize money, he responded, “This is quite a funny question.” Thaler added, “I will try to spend it as irrationally as possible.” We know that affective tags for money exist but what specifically are those affective tags? More specifically still, is one of those tags for sources of income “fun,” and if so, does that affect whether the money will be spent on fun? Classical economics would assume that satisfaction comes from the consumption of goods and services, that money is a medium of exchange, and that the source of that medium of exchange does not enter into the choice of the goods or services consumed. Thaler’s (1999) works show that people create mental accounts, indicating that the source of the money may not be as completely irrelevant as classical economics predicted. This is important because where irrational behavior is suboptimal behavior, if we can anticipate it, we can construct environments to support better choices. We find that fun sources of income are significantly more likely to be spent on fun expenditures. However, as the amount of the windfall increases, the amount spent on fun levels off, indicating that this affect may be bounded. We were unable to find statistically significant support that more “adult” sources of income are more likely to be spent on more adult uses, but money from adult sources was significantly more likely to be invested. This is important because understanding more about affective tags and how they affect decisions to use money, we become better predictors of irrational behavior.

This study examines the association between self-employment, otherwise known as entrepreneurship, and student loan debt. Based on data from the 2021 National Financial Capability Study, which were analyzed using a multinomial probit model, our results suggest that households that used student loans to finance the education of one household member are more likely to report that the other member of the household pursued self-employment, with everything else remaining equal. This association between student loans and household self-employment is both economically and statistically significant. Our results highlight the importance of alternative forms of financing for entrepreneurship and expand upon existing knowledge about the unintended effects of student loans. Policymakers should consider these results when analyzing the various intended and unintended benefits of policies affecting the availability of student loans.