Earticle

초록

영어

The purpose of this study is to investigate the improvement of prediction performance and changes in variable importance in SEM-ANN two-stage analysis. 366 cosmetics repurchase-related survey data were analyzed and the results were presented. The results of this study are summarized as follows. First, in SEM-ANN two-stage analysis, SEM and ANN models were trained with train data and predicted with test data, respectively, and the R² was showed. As a result, the prediction performance was doubled from SEM 0.3364 to ANN 0.6836. Looking at this degree of R² improvement as the effect size  of Cohen (1988), it corresponds to a very large effect at 110%. Second, as a result of comparing changes in normalized variable importance through SEM-ANN two-stage analysis, variables with high importance in SEM were also found to have high importance in ANN, but variables with little or no importance in SEM became important in ANN. This study is meaningful in that it increased the validity of the comparison by using the same learning and evaluation method in the SEM-ANN two-stage analysis. This study is meaningful in that it compared the degree of improvement in prediction performance and the change in variable importance through SEM-ANN two-stage analysis.

목차

Abstract
1. 서론
2. 문헌연구
2.1 선행연구 검토
2.2 선행연구의 한계
3. 연구방법
3.1 분석도구
3.2 SEM-ANN 2단계 분석 과정
4. 데이터 분석
4.1 연구변수 및 데이터
4.2 측정모델 분석
4.3 SEM 분석
4.4 ANN 분석
4.5 SEM과 ANN 분석결과 비교
5. 결론
5.1 연구의 요약
5.2 연구의 시사점
5.3 연구의 한계와 향후 연구의 제언
References
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키워드

저자

• 권순동 [ Sun-Dong Kwon | Professor of MIS Department in Chungbuk National University ] Corresponding Author
• 조의 [ Yi Zhao | Lecture Professor of MIS Department in Chungbuk National University ] Co-Author
• 방화룡 [ Hua-Long Fang | Assistant Professor of College of Liberal Arts, Cheongju University ] Co-Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005