Abstract: Recently, in accordance with the fourth industrial revolution and emerging Fin-Tech environment (Financial+Technology, big data, IT convergence, algorithms, learning machine, etc.). Computer asset management techniques using statistical analysis techniques have greatly developed. In order to obtain more advanced asset management services, this study investigate the characteristics of the Robot-advisor and the characteristics of the individual which influence the intention of the individual to use the Robot-advisor service. investigate the technical characteristics of robo-adviser through researching data on the Robo-adviser, develop a research model for technology acceptance theory and establish a hypothesis. The study model is based on the Technology Acceptance Model (TAM). The independent variables were selecting cost, reliability, convenience as the characteristics of the Robot-advisor, selecting personal innovation, self-efficacy and social impact as the characteristics of the individual, selecting the use of easy and usefulness as characteristic variables, using experience and prior knowledge as controlling variables, analyzing the effect on intention to use. The study result show that convenience, self-efficacy, social impacts affect the ease of use and that all variables and availability of service characteristics and personal characteristics affect usability. And use of easy and usability affected the intent to use the Robo-advisor. The results of using experience to controlling variables were not significantly different due to short using duration of domestic service, low use experience and low respondents. This study analyze that investors in the early stages of the Robo-advisor service use the Robo-advisor service regardless of time and place and use to easy the technical service and high efficiency and it is important to provide safe and reliable the Robo-advisor services.
Jae Hun Sa, Ki Bum Lee, Sung In Cho, Sang Hee Lee and Gwang Yong Gim, 2018. A Study on the Influence of Personality Factors on Intention to Use of Robo-Advisor. Journal of Engineering and Applied Sciences, 13: 7795-7802.