Initial Trust, Not Risk, Drives Cryptocurrency Adoption Among Nonusers

Cryptocurrencies promise decentralized, peer-to-peer payments secured by blockchain networks, yet their use for everyday transactions remains stubbornly limited. A new survey-based study of 402 UK adults who have never used cryptocurrency suggests that the decisive psychological barrier is not fear of risk but the absence of something subtler: initial trust, the willingness to rely on a system before ever having transacted with it. The research, published in Financial Innovation, finds that initial trust strongly predicts willingness to use cryptocurrencies, while perceived risk, contrary to classical financial decision-making models, does not significantly dampen that willingness.

The study, led by Ahmed Geebren, drew on trust theory and the Initial Trust Model developed by McKnight and colleagues, which holds that trust formed before direct experience rests on disposition to trust, institution-based trust, and trusting beliefs about ability, integrity, and benevolence. In conventional digital finance, such as online banking and mobile wallets, initial trust is typically underwritten by regulatory oversight, brand reputation, and consumer protection. Cryptocurrencies strip away those institutional anchors, relying instead on cryptographic protocols and network consensus, so prospective users must infer trustworthiness from system-level cues such as transparency, security, privacy, and usability.

Data were collected through an online survey between 14 December 2023 and 7 February 2024, a period of heightened public attention to cryptocurrency markets driven by Bitcoin price volatility and ongoing regulatory announcements. Only respondents who answered that they had never used cryptocurrency were permitted to proceed past screening questions, ensuring the sample consisted solely of nonusers. Participants were recruited through social media platforms including LinkedIn, Twitter, and Facebook using nonprobability convenience sampling, a method the author acknowledges limits generalizability to the broader UK population. The final sample was 59 percent male and 40.5 percent female, with 91 percent aged 18 to 54 and high educational attainment: 55 percent held undergraduate and 28 percent postgraduate degrees.

The survey measured nine potential antecedents of initial trust, including disposition to trust, transparency, anonymity, ease of use, convenience, transaction fees, privacy, security, and knowledge, using seven-point Likert scales adapted from validated instruments. A pilot study with 13 UK nonusers confirmed internal consistency, with Cronbach’s alpha values ranging from 0.71 to 0.92. The full dataset was analyzed using partial least squares structural equation modeling, chosen for its robustness to nonnormal data, its capacity to estimate multiple mediation effects, and the study’s predictive orientation. The model comprised 12 latent constructs and 12 structural paths.

The results were striking in their explanatory power. The model accounted for 80 percent of the variance in initial trust, 45 percent in perceived risk, and 52 percent in willingness to use, all exceeding the conventional threshold for substantial explanatory power. Six antecedents significantly enhanced initial trust: transparency, with the strongest effect in the model; privacy; ease of use; security; knowledge; and anonymity. Three hypothesized drivers failed to reach significance: disposition to trust, convenience, and transaction fees. The author interprets this pattern as evidence that trust formation in decentralized finance is structural rather than economic, driven by verifiable technical and informational cues rather than generalized trust tendencies or cost considerations.

Initial trust itself proved to be the central mechanism. It strongly reduced perceived risk and exerted a powerful positive influence on willingness to use cryptocurrencies. Mediation analysis following the Zhao and colleagues framework showed that initial trust transmitted the effects of transparency, anonymity, ease of use, security, privacy, and knowledge to willingness to use. For anonymity and privacy, the mediation was full, meaning these attributes influenced adoption only insofar as they were first interpreted as trustworthy signals; in decentralized systems without institutional safeguards, control-related features do not inherently produce positive behavioral intentions unless users believe the system will protect them. For transparency, ease of use, security, and knowledge, mediation was partial, with significant direct paths to willingness remaining.

The most counterintuitive finding concerned perceived risk. Although initial trust significantly lowered perceived risk, perceived risk did not significantly predict willingness to use, and it did not mediate the trust-willingness relationship. The author draws on behavioral economics and uncertainty avoidance theory to explain this: when facing unfamiliar technologies, people tend to rely on heuristic trust judgments rather than deliberate risk calculations. In the early stages of adoption, perceived system credibility may exert a greater psychological pull than concerns about volatility or loss, a departure from classical models that position risk as a primary determinant of behavioral intention.

Cross-validated predictive ability testing supported the model’s out-of-sample robustness, with positive Q2-predict values for perceived risk, initial trust, and willingness to use, and the PLS-SEM model significantly outperformed both indicator-average and linear model benchmarks. A multigroup analysis comparing 237 male and 163 female respondents found no significant gender-based differences in any structural path, suggesting the relationships are stable across gender within the sample. Common method bias was addressed through procedural remedies at the design stage and statistical checks, including full collinearity assessment with variance inflation factors below the critical threshold of 5 and Harman’s single-factor test, in which a single factor explained at most 20 percent of variance.

The study carries practical implications for developers, regulators, and policymakers. For platform providers, the findings point toward transparency dashboards, clear audit trails, simplified onboarding, and educational tools as the most effective levers for building initial trust among hesitant nonusers. For UK regulators, including the Financial Conduct Authority and the Bank of England, which have introduced advertising restrictions, consumer protection measures, and stablecoin regulatory proposals, the results suggest that communicating regulatory intentions more clearly could reduce perceived uncertainty, since enforcement gaps mean user perceptions often lag behind regulatory objectives. Surveys cited in the study indicate that 11 to 13 percent of UK adults have owned cryptocurrency, primarily for investment rather than payments, and everyday retail acceptance remains niche.

The author is careful to flag the study’s limitations. The convenience sample may not represent the wider population of UK nonusers, the cross-sectional design captures perceptions at a single moment and cannot establish causality or track how trust evolves, and the model excludes macrolevel factors such as market volatility, regulatory transparency, and institutional oversight. Cultural and contextual factors were not measured, and cross-country comparisons could reveal how different regulatory frameworks shape trust. Future research might also examine how emerging AI-driven mechanisms, such as automated smart contract auditing and blockchain integrity scoring, introduce new forms of algorithmic trust assurance. Within those bounds, the study offers a clear empirical message: for people who have never touched cryptocurrency, the path to adoption runs through visible, credible trust signals, and trust, once formed, can outweigh risk concerns entirely.

Subject of Research: Initial trust formation and willingness to use cryptocurrencies among UK nonusers

Article Title: Cryptocurrency and initial trust formation: an empirical investigation into the dynamics of willingness to use in financial transactions

Article References: Geebren, A. (2026). Cryptocurrency and initial trust formation: an empirical investigation into the dynamics of willingness to use in financial transactions. Financial Innovation, 12(1), Article 164. https://doi.org/10.1186/s40854-026-00926-9

Image Credits: AI Generated

DOI: 10.1186/s40854-026-00926-9

Keywords: cryptocurrency, initial trust, PLS-SEM, perceived risk, UK survey, blockchain, financial technology, technology adoption, decentralized finance, nonusers, trust theory, digital payments