Bridging the Digital Finance Gap in the United States: Analyzing the Socioeconomic and Behavioral Determinants of Cryptocurrency Adoption
Year: 2025
Type: article
Study design: Observational Study
Abstract: This study examines the socioeconomic, behavioural, and demographic factors influencing cryptocurrency adoption in the United States, utilising nationally representative data from the 2023 Survey of Household Economics and Decision Making. Using binary logistic regression, the analysis examines the impact of financial access, perceived well-being, income, education, employment, and demographic variables on the adoption of cryptocurrency. Results reveal that individuals lacking access to $400 in emergency funds are significantly more likely to adopt cryptocurrency, indicating its role as an alternative financial tool for underserved populations. Conversely, lower-income groups are less likely to adopt, suggesting that structural barriers, such as limited digital access and inadequate financial literacy, hinder adoption despite financial need. A U-shaped relationship is observed between education and adoption, where moderate levels (e.g., bachelor’s degrees) are associated with higher adoption rates. Full-time and part-time employment, younger age, and male gender also increase the likelihood of adoption. Additionally, White, non-Hispanic individuals are less likely to adopt compared to other racial and ethnic groups, pointing to possible differences in perceived institutional trust. These findings suggest that cryptocurrency adoption reflects not only financial stress but also the ability to act, which is influenced by access, exposure, and behavioural factors. The study underscores the importance of inclusive fintech design and policy measures that address both infrastructural and psychological barriers to digital financial inclusion.
Authors: Daniel Duah, Bismark Kofi Owusu Sarfo, William Vortia, Prosper Appiah-Bediako, Richard Owusu
Institutions: Worcester Polytechnic Institute, Westcliff University
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: hybrid
OpenAlex ID: W4414216049