Cryptocurrency awareness, acceptance, and adoption: the role of trust as a cornerstone

The study addresses how awareness, acceptance (perceived ease of use and perceived usefulness), and trust influence the adoption of cryptocurrencies. Grounded in the Technology Acceptance Model (TAM), the authors posit that increased awareness enhances perceptions of ease of use and usefulness, which in turn foster adoption. Trust is proposed as a key moderating factor that strengthens the relationships between awareness, acceptance, and adoption, especially important in decentralized, low-oversight financial technologies. The purpose is to explain determinants of cryptocurrency adoption and inform policies and strategies for broader integration into financial systems.

Theoretical background centers on TAM, where perceived ease of use (PEOU) and perceived usefulness (PU) predict technology adoption intentions. Prior work consistently validates TAM across technologies, but cryptocurrency as a medium of exchange remains under-examined. Conceptually, cryptocurrency is defined as blockchain-based, decentralized digital currency with attributes of transparency and immutability, yet faces barriers including regulation, security, environmental concerns, and unequal wealth distribution. The context includes global trends and a developing-country lens (Pakistan) with rising internet penetration and potential for financial inclusion. Hypotheses: H1—awareness positively influences adoption; H2—PEOU mediates the awareness–adoption link; H3—PU mediates the awareness–adoption link; H4a/H4b—trust moderates the mediated pathways via PEOU and PU, strengthening the effects of awareness on adoption through these acceptance factors.

Design: Cross-sectional survey analyzed with partial least squares structural equation modeling (PLS-SEM). Instrumentation: Five-point Likert scales adapted from prior literature. Constructs and items: (1) Cryptocurrency awareness (8 items; Sagheer et al., 2022). (2) Cryptocurrency ease of use (6 items; Chen & Aklikokou, 2020). (3) Cryptocurrency usefulness (6 items; Albayati et al., 2020). (4) Cryptocurrency trust (5 items; Shahzad et al., 2018). (5) Cryptocurrency adoption (5 items; Shahzad et al., 2018). Sampling and data collection: Targeted individuals aged 18–40 in Lahore, Pakistan. Screening ensured familiarity with digital tools and internet use. Distributed 551 questionnaires (physical and online); 332 valid responses retained (usable response rate 60.2%). Demographics: 54% female; ages 18–30 (71%), 31–40 (29%); education largely bachelor's (45%) and master's (35%); 66% students. Measurement model assessment: Reliability—Cronbach’s alpha and composite reliability all >0.7. Convergent validity—AVE for all constructs >0.5. Discriminant validity—Fornell-Larcker criterion satisfied (square roots of AVE exceed inter-construct correlations). Structural model: Bootstrapping in PLS-SEM estimated direct, mediating, and moderating effects; reported path coefficients (β), t-values, p-values, and R² for endogenous constructs.

Main effects: • H1 supported—Awareness → Adoption: β=0.192, p=0.014. • Awareness → Ease of use: β=0.470, p<0.001. • Awareness → Usefulness: β=0.288, p<0.001. • Ease of use → Adoption: β=0.220, p=0.001. • Usefulness → Adoption: β=0.134, p=0.017. • Trust → Ease of use: β=0.224, p<0.001. • Trust → Usefulness: β=0.220, p<0.001. Mediation: • H2 supported—Awareness → Ease of use → Adoption: β=0.103, p=0.004. • H3 supported—Awareness → Usefulness → Adoption: β=0.038, p=0.030. Moderation: • H4a supported—Trust positively moderates the awareness–ease of use–adoption pathway: β=0.164, p=0.013. • H4b supported—Trust positively moderates the awareness–usefulness–adoption pathway: β=0.117, p=0.030. Model fit (explanatory power): • R² Ease of use=0.515; R² Usefulness=0.148; R² Adoption=0.189. Interpretation: Greater awareness increases adoption both directly and indirectly via higher perceived ease and usefulness. Trust strengthens these mediated relationships, enhancing the conversion of awareness into favorable acceptance perceptions and subsequent adoption.

Findings demonstrate that awareness is a primary driver of cryptocurrency adoption, directly and through acceptance factors aligned with TAM. Perceived ease of use and usefulness act as key mechanisms translating awareness into adoption, highlighting the importance of user-friendly experiences and clear utility in everyday transactions. Trust plays a crucial moderating role by reducing uncertainty and perceived risk, thereby amplifying the impact of awareness on perceptions of ease and usefulness and, ultimately, adoption. These results extend TAM to a decentralized financial context and emphasize psychological enablers—especially trust—in influencing technology acceptance and use.

The study extends TAM to the cryptocurrency context by incorporating awareness as an antecedent to perceived ease of use and usefulness and introducing trust as a moderator. Results show that awareness significantly enhances adoption directly and via ease of use and usefulness, while trust strengthens these pathways. The work supports TAM’s generalizability in nascent financial technologies and underscores that human factors—awareness and trust—are pivotal alongside technical underpinnings like blockchain. Practically, stakeholders should invest in education, usability, security, and proportionate regulation to foster public confidence and adoption. Future research should examine long-term sustainability, evolving regulations, and additional behavioral and societal determinants, and track changes over time as technologies and platforms mature.

• Sample composition: Predominantly graduates/younger, tech-savvy respondents; findings may not generalize to less-educated or older populations. • Geographic scope: Data from Lahore, Pakistan; broader sampling across other Pakistani cities and cross-country comparisons are needed. • Omitted variables: Factors such as government support, social influence, and technological design not included; future models could integrate these. • Construct focus: Emphasis on adoption-centric variables; long-term sustainability and cryptocurrency-specific facets (e.g., mining) were not examined. • Methodology: Cross-sectional, single-time-point survey using adapted instruments limits causal inference; longitudinal designs are recommended.