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    A Development of Hotel Bankruptcy Prediction Model on Artificial Neural Network

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    https://www.riss.kr/link?id=A101701322

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on the basis of business performance data of each branch. here are many traditional statistical models for bankruptcy prediction such as Multivariate Discriminant Analysis or Logit Analysis. However, we chose Artificial Neural Network because the method has accuracy rates of prediction better than those of other methods. We first selected 100 good enterprises and 100 bankrupt enterprises as experimental data and set up a bankruptcy prediction model by use of a tool for Artificial Neural Network, NeuroShell. The model and its experiments, which demonstrated high efficiency, can certainly provide great help in decision making in the field of hotel management and in deciding on the bankruptcy or financial solidity of each branch of serviced residence hotel.
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    This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on t...

    This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on the basis of business performance data of each branch. here are many traditional statistical models for bankruptcy prediction such as Multivariate Discriminant Analysis or Logit Analysis. However, we chose Artificial Neural Network because the method has accuracy rates of prediction better than those of other methods. We first selected 100 good enterprises and 100 bankrupt enterprises as experimental data and set up a bankruptcy prediction model by use of a tool for Artificial Neural Network, NeuroShell. The model and its experiments, which demonstrated high efficiency, can certainly provide great help in decision making in the field of hotel management and in deciding on the bankruptcy or financial solidity of each branch of serviced residence hotel.

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    참고문헌 (Reference)

    1 G. W. Emery, 20 (20): 1982

    2 정상준, "퍼지이론과 베이지안 갱신 기반의 과거 주행정보를 이용한 차량항법 장치의 교통상황 예측과 최적경로 계획" 한국컴퓨터정보학회 14 (14): 159-167, 2009

    3 조영성, "추천시스템에서 구매 패턴 예측을 위한 SOM기반 고객 특성에 의한 군집 분석" 한국컴퓨터정보학회 19 (19): 193-200, 2014

    4 R. Elam, "The effect of lease data on the predictive ability of financial ratios" 50 : 24-43, 1975

    5 W. B. Johnson, "The corss-sectional stability of financial ration patterns" 14 : 1035-1048, 1979

    6 I. G. Dambolena, "Ratio stability and corporate failure" 35 (35): 1017-1026, 1980

    7 G. Foster, "Quarterly accounting data: time -series properties and predictive- ability results" 1 : 1-21, 1977

    8 G. A. Hanweak, "Predicting bank failure,”Research Papers in Banking and Economics" FRB 11 : 1977

    9 M. E. Zmijewski, "Methodological issues related to the estimation of financial distress prediction models" 22 : 59-82, 1984

    10 K. C. Laudon, "Management Information Systems" Prentice-Hall 2014

    1 G. W. Emery, 20 (20): 1982

    2 정상준, "퍼지이론과 베이지안 갱신 기반의 과거 주행정보를 이용한 차량항법 장치의 교통상황 예측과 최적경로 계획" 한국컴퓨터정보학회 14 (14): 159-167, 2009

    3 조영성, "추천시스템에서 구매 패턴 예측을 위한 SOM기반 고객 특성에 의한 군집 분석" 한국컴퓨터정보학회 19 (19): 193-200, 2014

    4 R. Elam, "The effect of lease data on the predictive ability of financial ratios" 50 : 24-43, 1975

    5 W. B. Johnson, "The corss-sectional stability of financial ration patterns" 14 : 1035-1048, 1979

    6 I. G. Dambolena, "Ratio stability and corporate failure" 35 (35): 1017-1026, 1980

    7 G. Foster, "Quarterly accounting data: time -series properties and predictive- ability results" 1 : 1-21, 1977

    8 G. A. Hanweak, "Predicting bank failure,”Research Papers in Banking and Economics" FRB 11 : 1977

    9 M. E. Zmijewski, "Methodological issues related to the estimation of financial distress prediction models" 22 : 59-82, 1984

    10 K. C. Laudon, "Management Information Systems" Prentice-Hall 2014

    11 E. Turban, "Information Technology for Management" Pearson 2014

    12 C. L. Merwin, "Financial small corporations in five manufacturing industries 1926-1936" 105 : 1942

    13 E. I. Altman, "Financial ratios, discriminant analysis and the prediction of corporate bankruptcy" 3 : 589-609, 1968

    14 W. Beaver, "Financial ratios as predictors of failure-empirical research in accounting;selected studies" 5 : 71-111, 1966

    15 J. Ohlson, "Financial ratios and the probabilistic prediction of bankruptcy" 1 : 109-131, 1980

    16 M. J. Gombola, "Financial ratio patterns in retail and manufacturing organizations" 2 : 45-56, 1983

    17 E. Turban, "Electronic Commerce" Pearson 2013

    18 D. Martin, "Early warning of bank failure: a logit regression approach" 1 : 249-276, 1977

    19 E. Turban, "Decision Support Systems & Intelligent Systems" Pearson 2010

    20 K. Takahashi, "Corporate bankruptcy prediction in Japan" 2 : 229-247, 1984

    21 R. F. Smith, "Change in the financial structure of unsuccessful industrial corporations" Bureau of Business Research of University of Illinois 1935

    22 D. Fletcher, "A comparison of the ratios of successful industrial enterprises with those of failed companies" 2 : 1932

    23 C. L. Norton, "A comparison of general price level and historical cost financial statements in the prediction of bankruptcy" 1 : 72-87, 1979

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
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    2007-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2006-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
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    학술지 인용정보

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    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.44 0.44 0.44
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
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