Technostress and Fintech Usage Intention: Exploring Gen Z's Experience with P2P Services in Indonesia

• Published in: International Conference on Bio-engineering for Smart Technologies (Online) pp. 1 - 4
• Main Authors: Putinagari, Meutia Wanni, Saputra, Muhardi, Nurtrisha, Widyatasya Agustika, Febriyani, Widia
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.05.2025
• Subjects: Accuracy; Biological system modeling; Fintech; fintech adoption model; gen z; Load modeling; Loading; Mathematical models; P2P; paylater services; Predictive models; Reliability; Security; technostress
• ISSN: 2831-4352
• DOI: 10.1109/BioSMART66413.2025.11046105

This study presents a comprehensive model that utilizes technostress factors to measure the behavioral intention of Gen Z in Indonesia towards the fintech application X Paylater. The relationship between key adoption factors is investigated using Partial Least Squares Structural Equation Modeling (PLS-SEM). To improve the accuracy of the model, low-loading indicators (outer loading < 0.70) are removed, which increases reliability and validity. The findings indicate that subjective norms (β = 0.499) and perceived behavioral control (β = 0.280) have a significant impact on behavioral intention, while security concerns (β = −0.059) serve as a barrier to adoption. The model shows strong predictive ability, with behavioral intention showing the highest explanatory power (R 2 = 0.440).