Trust as a Mediating Factor in Enhancing Investors' Intention to Use Robo-Advising

Artificial intelligence (AI) has developed rapidly in recent years. Beyond its specialized domains, it has also been applied to an increasing range of other fields. Prior research suggests that traditional financial decisions are typically reached through investors' own judgment, and that such judgment is readily subject to interference from human factors and other considerations, which compromises the accuracy of the resulting decisions. In response, many developers have introduced AI into the financial industry and integrated it with investment services, giving rise to a novel form of advisory known as robo-advising, or intelligent investment advisory. Robo-advising not only breaks with the conventional human-based advisory model through AI technologies, but also helps investors make more effective decisions, thereby reducing potential losses. Existing studies have proposed that the perceived usefulness of robo-advisory technology affects users' attitude and usage intention, and that information transparency likewise affects users' attitude and usage intention, with attitude positively related to usage intention. However, relatively few studies have examined trust as a mediating mechanism through which these factors shape investors' intention to use robo-advisory. Accordingly, this study employs correlation analysis, regression analysis, and structural equation modeling to analyze the data collected from a questionnaire survey and to test the proposed hypotheses. The findings indicate that the perceived usefulness and information transparency of robo-advising are capable of establishing investor trust, and that such trust can alter investors' attitude toward robo-advising, thereby enhancing their usage intention. In addition, this study aims to offer more effective recommendations for robo-advisory technology and to support the continued development of robo-advisory investment services.