생성형 AI 서비스에 대한 이용자의 평가와 만족도 분석
Analysis on Users' Evaluation and Satisfaction toward Generative AI Service
- 발행
- 2024 등록이 논문은 발행 시점을 확인하지 못해 원문 등록일을 적었습니다. KCI가 2005~2008년에 옛 논문을 몰아서 올린 탓에, 그 시기 등록분은 발행보다 평균 3~5년 늦습니다. 실제 발행연도는 더 이를 수 있습니다.
- 소속·발행
- 서강대학교 경영대학
- 출처
- 국내 KCI
- DOI
- 10.35373/KMES.29.2.5
- 원문
- 원문 보기 ↗
개념
키워드
Keywords：Generative AI, Usefulness, Satisfaction, Decision tree, Random forest, Keywords：Generative AI, Usefulness, Satisfaction, Decision tree, Random forest
초록
Purpose : This study aims to analyze the causal relationship between users’ evaluation on generative AI service and overall satisfaction.
 Methods : The input variable dimensions include easiness to use dimension, usefulness dimension, enjoyment dimension, suitability dimension, and reliability dimension, whereas the response is measured by satisfaction dimension. Analysis is done by decision tree model based on Gini algorithm and random forest model.
 Results : The results of decision tree models reveal that the first splits are mostly done by reliability dimension variables and the next important is usefulness dimension variables. Enjoyment dimension variables and reliability dimension variables are utilized most for the second splits. The random forest model indicates that the first four ranked variables belong to reliability dimension based on the mean_decrease_gini index.
 Conclusion : The findings of this study suggest that reliability dimension, usefulness dimension, enjoyment dimension, easiness to use dimension, and suitability dimension are crucial for users’ overall satisfaction for generative AI service, all of which are worthwhile to denote for policy ma