Type of Submission
Refereed Article
Abstract
The purpose of this study was to develop logit models for predicting bankruptcy in the hospitality industry. Using the financial data of 16 U.S. hospitality firms that went bankrupt between 1999 and 2004 and 16 non-bankrupt matching firms, this study estimated logit models for predicting bankruptcy up to 2 years in advance. The logit models, resulting from forward stepwise selection procedures, could correctly predict 91% and 84% of bankruptcy cases 1 and 2 years earlier, respectively. The estimated models imply that a hospitality firm is more likely to go bankrupt if it has lower operating cash flows and higher total liabilities. The models suggest that a prudent sales growth strategy accompanied by tighter control of operating expenses and less debt financing can help enhance a firm’s ability to meet its financial obligations and thereby reduce bankruptcy risk.
Recommended Citation
Kim, Hyunjoon and Gu, Zheng
(2010)
"A Logistic Regression Analysis for Predicting Bankruptcy in the Hospitality Industry,"
Journal of Hospitality Financial Management: Vol. 14:
Iss.
1, Article 24.
Available at:
https://scholarworks.umass.edu/jhfm/vol14/iss1/24