한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제19권10호
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  • Pages.125-133
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  • 2014
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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인공신경망 기반 호텔 부도예측모형 개발

A Development of Hotel Bankruptcy Prediction Model on Artificial Neural Network

  • 최성주 (원광대학교 대학원 정보관리학과) ;
  • 이상원 (원광대학교 정보전자상거래학부)
  • Choi, Sung-Ju (Dept. of Information Management, Graduate School of Wonkwang University) ;
  • Lee, Sang-Won (Div. of Information and Electronic Commerce, Wonkwang University)
  • 투고 : 2014.09.26
  • 심사 : 2014.10.18
  • 발행 : 2014.10.31
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초록

본 논문에서는 호텔경영을 위한 인공신경망 기반의 부도예측 모형을 개발한다. 부도예측 모형은 호텔에서 관리하는 사업장의 사업성과 이터를 바탕으로 부도 가능성을 평가하여 호텔 전체사업의 부도를 예측하는 특징을 가진다. 부도예측을 위한 전통적인 통계기법은 다변량 판별분석이나 로짓분석 등이 있는데, 본연구는 이들보다 우수한 예측정확성을 갖는 인공신경망 기법을 이용해서 연구를 진행하였다. 이를 위해 우선 우수기업 100개와 도산기업 100개를 선정하여 전체 실험데이터를 구성하고, 뉴로쉘이라는 인공신경망 도구를 이용하여 부도예측모형을 구성하였다. 본 모형 설계와 실험은 서비스드 레지던스 호텔에서 관리하는 각 브랜치의 부도예측과 재무건전성을 판단하기에 효율성이 높아 호텔 경영의 의사결정에 많은 도움이 될 것이다.

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.

키워드

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피인용 문헌

  1. Key Ratios for Long-Term Prediction of Hotel Financial Distress and Corporate Default: Survival Analysis for an Economic Stagnation vol.13, pp.3, 2014, https://doi.org/10.3390/su13031473