다변량 판별분석과 로지스틱 회귀분석, 인공신경망 분석을 이용한 호텔 도산 예측

• 영문명: Prediction of Hotel Bankruptcy Using Multivariate Discriminant Analysis, Logistic Regression and Artificial Neural Network
• 발행기관: 한국관광학회
• 저자명: 金秀英
• 간행물 정보: 『관광학연구』제30권 제2호, 53~75쪽, 전체 23쪽
• 주제분류: 사회과학 > 관광학
• 파일형태: PDF
• 발행일자: 2006.04.30

영문 초록

This study estimates the possibilities of hotel bankruptcy using various analytic methods such as multivariate discriminant model, logistic regression model and artificial neural network model. The estimated models suggest that debt-burned hotels with low profit margin and return on common stockholders’ equity are more likely to be candidates of bankruptcy. The analysis of in-model variables, along with a cross-group comparison of financial ratios, suggests that bankrupt hotels have heavily relied on debt to finance fast sales growth without paying proper attention to controlling their operating expenses and financing costs. Author suggests in conclusion that to avoid bankruptcy risk hoteliers are encouraged to adopt a prudent growth strategy accompanied by less debt financing and tighter cost control.

목차

I. 서론

II. 이론적 배경

III. 연구방법

IV. 분석결과

V. 결론

참고문헌

키워드

호텔도산예측 다변량판별분석모형 지스코어 로지스틱회귀모형 인공신경망모형 Z score