Failure analysis of corporations with multiple hospitality businesses

Abstract

This paper investigates the symptoms of failure in public corporations with multiple hospitality businesses and examines whether a new case-based deep-layer predictive analysis methodology is more appropriate than conventional approaches to failure analysis. The symptoms correlated with multi-business hospitality failures were determined using a novel bootstrapping u-test. Further, a case-based deep-layer predictive analysis of multi-business hospitality failures was conducted using an independently incremental process, dependent retrieval process, pre-early-warning process, and early-warning process. The descriptive results suggest that Chinese corporations with multiple hospitality businesses should focus on managerial efficiencies (i.e., diversification under liabilities and recovery of accounts receivable), and financial efficiencies (i.e., earnings and returns when expanding hospitality businesses). Moreover, case-based deep-layer models were found to be helpful in predicting the failure of corporations with multiple hospitality businesses, as they better fit symptom-based fusion failure correlations and indicate warning signs of failure more reliably.