Evaluating Behavioral Intention and Financial Stability in Cryptocurrency Exchange App: Analyzing System Quality, Perceived Trust, and Digital Currency

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👤 Akhila Reddy Yadulla
🏢 Department of Information Technology, University of the Cumberlands, Williamsburg, KY, USA
👤 Geeta Sandeep Nadella
🏢 Department of Information Technology, University of the Cumberlands, Williamsburg, KY, USA
👤 Mohan Harish Maturi
🏢 Department of Information Technology, University of the Cumberlands, Williamsburg, KY, USA
👤 Hari Gonaygunta
🏢 Department of Information Technology, University of the Cumberlands, Williamsburg, KY, USA

This study evaluates the factors influencing financial stability (FS) and behavioral intention (BI) in a cryptocurrency exchange app, explicitly focusing on system quality (SQ), perceived trust (PT), and digital currency (DC) within the Indonesian context. Utilizing structural equation modeling (SEM) with SmartPLS, the research analyzed data from 345 respondents who are active users of the cryptocurrency exchange app. The results confirmed that SQ significantly enhances PT (β = 0.832, t = 27.216, p < 0.001) and BI (β = 0.718, t = 12.675, p < 0.001). Additionally, DC positively impacts FS (β = 0.578, t = 8.177, p < 0.001), while PT influences both FS (β = 0.391, t = 5.478, p < 0.001) and BI (β = 0.198, t = 3.490, p = 0.001). These findings validate all five proposed hypotheses, highlighting the critical role of SQ and PT in driving FS and user engagement in cryptocurrency exchange apps. The study's measurement model demonstrated good reliability and validity, with Cronbach's alpha values exceeding 0.7 for all constructs: SQ (0.891), PT (0.812), DC (0.767), FS (0.819), and BI (0.745). Composite reliability values were also high, ranging from 0.855 to 0.933. Average Variance Extracted (AVE) values indicated good convergent validity, with SQ (0.822), PT (0.727), DC (0.689), FS (0.743), and BI (0.663). Discriminant validity was confirmed using the Fornell-Larcker criterion. The structural model's fit indices, including an SRMR of 0.045 and an NFI of 0.914, demonstrated a good model fit. The R² values for BI (0.791), FS (0.873), and PT (0.693) indicated substantial explanatory power. Despite its contributions, this study has limitations, including its focus on a single cryptocurrency exchange app in Indonesia, which may affect the generalizability of the findings. Future research should expand the sample to include multiple apps and geographical contexts. Additionally, incorporating other relevant factors, such as user experience and regulatory compliance, could provide a more comprehensive understanding of FS in digital financial services. This research underscores the importance of SQ and PT in achieving long-term success and sustainability in the rapidly evolving digital finance landscape.

Yadulla, A. R., Nadella, G. S., Maturi, M. H., & Gonaygunta, H. (2024). Evaluating Behavioral Intention and Financial Stability in Cryptocurrency Exchange App: Analyzing System Quality, Perceived Trust, and Digital Currency. Journal of Digital Market and Digital Currency, 1(2), 103–124. https://doi.org/10.47738/jdmdc.v1i2.12

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