통합기술수용이론을 이용한 금융소비자들의 인공지능 서비스 수용의도 연구
A Study on the Intention of Financial Consumers to Accept AI Services Using UTAUT Model
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초록
Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI knowledge as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the user-intention for AI. It was also found that AI knowledge of users was found to differently influence the user-intention through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness and AI knowledge have positive causation to the intention to use in intelligent financial service. On the facilitating factors, unlike other variables, it was found that the user's acceptance intention was different according to the level of AI knowledge. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the user-intention for AI.
Abstract
Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI knowledge as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the user-intention for AI. It was also found that AI knowledge of users was found to differently influence the user-intention through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness and AI knowledge have positive causation to the intention to use in intelligent financial service. On the facilitating factors, unlike other variables, it was found that the user's acceptance intention was different according to the level of AI knowledge. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the user-intention for AI.
참고문헌 (35)
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