Determinants of Accepting New Payment Technologies: The Case of Crypto-Wallets

Abstract

We study the determinants of adopting new payment technologies and the extent to which stated intentions predict economically relevant behavior. Using a large-scale online experiment (N = 802), we compare three measurement approaches — survey-based intentions, choice experiment, and a real payment decision — in the context of crypto-wallet adoption. We extend the Technology Acceptance Model (TAM) to incorporate perceived risk, trust, and use-case relevance, and validate the resulting structure through factor analysis. We document that intention is primarily shaped by use-case relevance, ease of use, and perceived risk. However, its predictive power is context-dependent. In a hypothetical portfolio-allocation task, intention predicts allocations to crypto-wallets only when alternatives are familiar or low-risk, but not when they are complex or highly risky. In contrast, intention strongly predicts a consequential real choice — whether to receive a bonus payment via a crypto-wallet. Across all measures, use-case relevance emerges as the most robust determinant, while other factors vary by decision context. Our findings highlight systematic differences across measurement approaches and underscore the value of combining survey and choice based measures to assess technology adoption.