A Theory of Digital Currency Adoption in Emerging Markets

Thesis Abstract

The rapid proliferation of digital financial technologies has transformed monetary transactions globally, yet the adoption of digital currencies in emerging markets remains understudied despite their potential to foster financial inclusion and economic development. This research addresses the pressing need to understand the underlying factors influencing digital currency acceptance in such contexts, where socio-economic, technological, and regulatory barriers significantly differ from developed economies. The primary aim of the study is to develop a comprehensive theoretical framework that explicates the determinants and behavioral intentions associated with digital currency adoption in emerging markets, specifically focusing on countries exhibiting high mobile penetration yet low traditional banking access. The specific objectives include identifying key socio-economic, technological, trust-related, and regulatory factors influencing individual adoption intentions; examining the moderating role of financial literacy and digital skills; and proposing a contextualized model based on the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT). To achieve these goals, the study employs a mixed-methods research design, integrating quantitative surveys and qualitative interviews to enhance depth and triangulation. The population comprises adult residents aged 18-60 years within metropolitan regions of three emerging markets—namely Kenya, Vietnam, and Nigeria—where mobile financial services are prevalent. A stratified random sampling technique is used to select 600 respondents for the survey, balanced across urban and semi-urban areas, with an additional 30 key informant interviews conducted with banking officials, regulators, and technology providers to contextualize the quantitative findings. Data collection involves a structured questionnaire developed through literature-based item generation, validated through pilot testing, and supplemented with semi-structured interview guides. Validity and reliability are ensured via confirmatory factor analysis and Cronbach’s alpha coefficients exceeding 0.7. The primary data analysis employs Structural Equation Modeling (SEM) using AMOS to test the proposed theoretical relationships, assess model fit indices, and examine mediation/moderation effects, particularly of financial literacy and digital skills. Thematic analysis is applied to qualitative interview transcripts to extract nuanced insights on behavioral and contextual factors. Expected findings suggest that perceived ease of use, trust in digital currency platforms, perceived usefulness, and perceived security significantly influence adoption intentions, with trust serving as the strongest predictor. Regulatory clarity and digital literacy are hypothesized to moderate these relationships, either facilitating or hindering adoption. Additionally, socio-economic variables such as income level, education, and urban residency are expected to impact behavioral intentions indirectly through perceived benefits and trust. The study’s primary contribution to knowledge lies in the conceptualization of an integrative model tailored for emerging market environments, extending TAM and IDT through the incorporation of trust, regulatory perceptions, and digital literacy as contextual moderators. It provides empirical evidence on the behavioral and infrastructural determinants of digital currency acceptance, filling identified gaps in the literature regarding socio-economic and regulatory influences specific to developing economies. This research concludes that targeted policy interventions aimed at enhancing digital literacy, clarifying regulatory frameworks, and building trust are crucial for accelerating digital currency adoption in emerging markets. Recommendations include strategic collaborations between governments, financial institutions, and technology providers to establish transparent regulatory practices, digital literacy campaigns, and secure technological infrastructure. The study underscores the importance of contextualized models for informing policy and practice, and advocates for further longitudinal research to monitor evolving adoption patterns as digital financial ecosystems mature.