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효용적 가치와 지각된 위험이 생성형 AI 추천 의도에 미치는 영향 : 기술수용모형을 중심으로

The Effect of Utilitarian Value and Perceived Risk on Recommendation Intention for Generative AI : Focusing on Technology Acceptance Model

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초록

챗GPT의 등장을 시작으로 생성형 AI에 대한 관심이 높아지고 있다. 그러나 생성형AI에 대한 이용자의 인식과 의도 간의 관련성을 살펴본 연구는 저조한 편이다. 본 연구는챗GPT 사용자들이 챗GPT의 가치와 위험 인식이 챗GPT의 지각된 유용성과 용이성 평가, 그리고 추천 의도에 어떠한 영향을 미치는지 조사하고자 한다. 이를 위해 본 연구는 기술수용모형을 근거로 생성형 AI의 추천 의도에 영향을 미치는 요인을 발굴하고, 이들 간의구조적 관계를 살펴보았다. 구조방정식 모형 분석 결과, 생성형 AI에 대한 지각된 활용가치가 지각된 유용성과 용이성에 정적으로 영향을 미치는 것이 확인되었으며, 지각된위험은 지각된 유용성에 부적으로 영향을 미치는 것이 확인되었다. 또한, 지각된 용이성은유용성에 정적인 영향을 미치는 것이 확인되었다. 마지막으로 지각된 유용성과 용이성은생성형 AI 추천의도에 정적으로 영향을 미치는 것이 확인되었다. 본 연구는 이용자들이챗GPT에 대해 인식하는 바가 챗GPT에 대한 평가와 추천 의도에 어떤 영향을 미치는지조사함으로써, 이용자들이 생성형 AI를 어떻게 평가하고 받아들이는지에 대한 이론적가치를 제공한다. 또한, 개발자들이 이용자의 요구를 이해하고 제품의 실용성 및 사용자경험을 향상시키는 데 큰 실천적 가치가 있다는 것을 보여준다.

Abstract

Since the advent of Chat-GPT, more attention has been paid to generative AI. However, there is insufficient examination of the relationship between user perception and behavioral intention of generative AI. Therefore, based on the technology acceptance model, this study explores the factors that affect the recommendation intention of generative AI and observes the structural relationship between them. The results of the structural equation model analysis show that the perceived utilitarian value of generative AI has a positive effect on the perceived usefulness and perceived ease of use, while the perceived risk has a negative effect on the perceived usefulness. In addition, the perceived ease of use of Chat-GPT has a positive effect on the perceived usefulness. Finally, both perceived usefulness and perceived ease of use were found to have a direct positive effect on the recommendation intention of generative AI. This is the first study conducted on the early-stage Chat-GPT adopters that evaluate the influence of both perceived utilitarian value and perceived risk of Chat-GPT on users' perceived usefulness, ease of use, and recommendation intention of generative AI.

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