Exploring the Impact of Relevant Factors on the Acceptance of Cryptocurrency Mobile Apps: An Extended Technology Acceptance Model (TAM-3) - Anggalia Wibasuri; Indah Purnomowati; Faurani Santi Singagerda (International Journal of Artificial Intelligence Research, 2022)
This study aimed to deepen the understanding of the decision-making process supporting the acceptance of Cryptocurrency mobile apps by integrating relevant factors into the Traditional Technology Acceptance Model (TAM). The impact of Antecedent System Characteristics (Relevance, Terminology, and Screen Design), Perceived Risk, and Trial ability on the existing TAM-3 constructs was investigated. A survey questionnaire was distributed among mobile cryptocurrency app users, resulting in 41 responses. The proposed framework was evaluated using the SEM-PLS method, including confirmatory factor analysis (CFA), and its construct validity was confirmed. Invariance tests were conducted on both the measurement and structural models. While most findings supported the suggested model, exceptions were found regarding Terminology and Perceived Risk of Cryptocurrency Mobile Application Adoption. The extended TAM factors, unlike the traditional TAM, accounted for 45% of the variance in the actual usage of cryptocurrency mobile apps. The revised model demonstrated improved predictive and explanatory power, particularly in explaining Perceived Ease of Use, which the traditional model could not. The study highlights the occurrence of inconsistencies between the original TAM model constructs and the added constructs when expanding the Technology Diffusion theory. Nonetheless, the model in this study enhances predictive capabilities and provides a comprehensive explanation of users' acceptance of mobile cryptocurrency applications.Keywords: TAM-3, Cryptocurrency, technology diffusion theory, integrating relevant factors, decision making process