AI tools mediating the performance expectancy of digital investment platforms: from the perspective of Gen Z in Malaysia

Leong, Wye Kitt and Loh, Jin Lap and Ong, Zhen Hao (2026) AI tools mediating the performance expectancy of digital investment platforms: from the perspective of Gen Z in Malaysia. Final Year Project, UTAR.

PDF Download (1777Kb)

Abstract

Financial technology and artificial intelligence (AI) are rapidly transforming. This rapid advancement significantly transformed digital investment platforms, particularly among Generation Z (Gen Z) users. This study examines the factors influencing the performance expectancy of digital investment platforms in Malaysia, with AI as mediator. Grounded in Technology Acceptance Model (TAM) and Artificial intelligence Device Use Acceptance Model (AIDUA), this study investigates the effects of social influence, perceived usefulness, perceived ease of use, and hedonic motivation on performance expectancy. This study employed a quantitative research design through a structured questionnaire. The data were collected from 446 respondents, primarily Gen Z. After that, the data were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) on SmartPLS. All independent variables, social influence, perceived usefulness, perceived ease of use, and hedonic motivation have significant positive effects on performance expectancy. Furthermore, this study found that AI significantly mediates the relationships between perceived usefulness, perceived ease of use, hedonic motivation, and performance expectancy. However, its mediating role is insignificant between social influence and performance expectancy. The model in this study shows moderate explanatory power, indicating that AI plays a critical role in enhancing users’ expectations of digital investment platforms. This study contributes to the understanding of AI-driven financial behaviour among Gen Z and insights for fintech developers and policymakers to enhance user engagement and platform performance.

Actions (login required)