구미시 공무원의 생성형 인공지능 사용의도와 실제 사용에 영향을 미치는 요인에 관한 연구: 확장된 UTAUT 모형을 중심으로

초록

This study investigates the factors influencing the intention to use and the actual use of generative artificial intelligence among public officials in Gumi City. An extended UTAUT model was used, setting performance expectancy, effort expectancy, organizational support, perceived risk, innovation culture, digital capability, and social influence as antecedent variables; behavioral intention as a mediating variable; and actual use as the dependent variable. The analysis was based on survey responses from 568 public officials in Gumi City. Data was analyzed using SPSS and AMOS through descriptive statistics, reliability analysis, confirmatory factor analysis, and structural equation modeling. The results indicate that performance expectancy, perceived risk, digital competence, and social influence significantly affected behavioral intention, which in turn had a strong positive effect on actual use. In contrast, the effects of effort expectancy, organizational support, and innovation culture were not statistically significant. These findings suggest that the use of generative AI among local government officials is primarily explained by performance expectancy, digital capability, and social influence. Although perceived risk also affected behavioral intention, its effect size was comparatively limited. This study provides empirical evidence on the relationship between generative AI acceptance and actual use among local government officials. It also offers practical implications for the development of AI diffusion policies, training programs, usage guidelines, and organizational culture strategies within local governments.

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