Rohit Kumar Vishwakarma

Type of the article: Research Article

Abstract
Crypto-assets attract interest as alternatives to centralized financial systems, yet adoption remains limited in advanced economies. This study explores how technological characteristics and human motivations affect adoption intentions, using Czechia as the context of a developed economy. The study applies a dual-stage framework- partial least squares structural equation modelling (PLS-SEM) to test hypotheses on data from 387 Czech adults via face-to-face questionnaires (March-October 2023), and artificial neural network (ANN) analysis to rank factor importance. PLS-SEM findings show Effort Expectancy as the strongest predictor of adoption intention, while Compatibility drives Performance Expectancy, which indirectly drives adoption intention. Relative Advantage significantly shapes Effort Expectancy and indirectly affects adoption intention. However, ANN sensitivity analysis shows technological characteristics dominate overall, with Compatibility showing the highest normalized importance (91.5%), followed by Relative Advantage (79.9%) and Effort Expectancy (50.9%). These results show technological characteristics and human motivations both contribute to adoption intentions, with prominence depending on analytical perspective- ease of use was the strongest direct predictor in PLS-SEM, while Compatibility dominated overall predictive importance in ANN. This indicates that in a stable, resilient financial environment, digital proficiency does not translate into tolerance for complexity; rather, adoption intentions depend on the technology’s ability to align effortlessly with established daily habits. Consequently, the study suggests fostering adoption in developed economies requires reducing structural complexity rather than merely increasing digital literacy.