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Prediction of Hotel Bankruptcy Using Multivariate Discriminant Analysis, Logistic Regression and Artificial Neural Network

  • Journal of Tourism Sciences
  • Abbr : JTS
  • 2006, 30(2), pp.53-75
  • Publisher : The Tourism Sciences Society Of Korea
  • Research Area : Social Science > Tourism

SooYoungKim 1

1세종사이버대학교

Accredited

ABSTRACT

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.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.