Hospitality Bankruptcy in United States of America: A Multiple Discriminant Analysis-Logit Model Comparison

Albert A. Barreda, Yoshimasa Kageyama, Dipendra Singh, Sandra Zubieta

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


This study examines bankruptcy prediction of hospitality firms within U.S. equity markets. The article investigates whether the Logit model or the Multiple Discriminant Analysis (MDA) accurately predict bankruptcy, specifically it attempts to investigate how accurate Logit and MDA models are. Various key financial variables were utilized as predictors and contrasting samples of both bankrupt and non-bankrupt firms for the period 1992–2010 were used. In this analysis Statistical software SPSS 20 was utilized for the analysis. Results show that for the period 1992–2010, the MDA model outperformed the Logit model for overall bankruptcy prediction. Theoretical and practical implications were offered based on the results. The study is critical given the significant number of hospitality enterprises being intensely impacted by the recent economic downturn. Consequently, the hospitality industry in United States demands higher degree of accuracy from bankruptcy prediction models to forecast economic failure.

Original languageAmerican English
Pages (from-to)86-106
Number of pages21
JournalJournal of Quality Assurance in Hospitality and Tourism
Issue number1
StatePublished - 2 Jan 2017


  • Bankruptcy
  • economic failure
  • hotels
  • logit regression
  • multiple discriminant analysis
  • restaurants


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