From Intuition to Automation: A Comparative Study of Traditional Investment Decisions and Robo-Advisory Adoption Among Retail Investors in Indonesia

Abstract The development of digital technology has transformed the investment decision-making process from being based on human analysis to automated algorithm-based solutions such as robo-advisors. This study aims to compare traditional and technology-based investment decision-making approaches among retail investors in Indonesia, focusing on adoption, perceived trust, and effectiveness of robo-advisor use. Using quantitative descriptive-correlational approach to compare traditional and technology-based investment decision-making methods, this study collected survey data from 120 individual. The results show a significant positive correlation between trust in traditional methods and the use of investment applications, although the adoption rate of robo-advisors is still low. The main barriers faced are low digital literacy and lack of trust in automated systems. These findings emphasize the importance of targeted investor education and increased transparency on robo-advisory platforms. This study contributes to the literature on fintech adoption in emerging markets and offers practical insights for fintech developers and policymakers.