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

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

doi:10.1080/1528008x.2016.1169471

Cited by 23 publications

(22 citation statements)

References 33 publications

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“…It seems that the effectiveness of each method is sample based, i.e., dependent on the learning and testing set, the examined time period, and the considered financial ratios. For example, our results are in agreement with Barreda et al [42], that found that the discriminant model is more accurate than the logit for the bankruptcy prediction of hospitality firms within U.S. equity markets for the period 1992-2010. However, our results are in disagreement with Pereira et al [13], that concluded that the discriminant and logit model have similar predictive ability when examining the business failure in the hospitality industry for the period 2009-2013 in Portugal.…”

Section: Discussionsupporting

confidence: 93%

Bankruptcy Prediction: The Case of the Greek Market

Papana

Spyridou

2020

Forecasting

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Financial bankruptcy prediction is an essential issue in emerging economies taking into consideration the economic upheaval that can be caused by business failures. The research on bankruptcy prediction is of the utmost importance as it aims to build statistical models that can distinguish healthy firms from financially distressed ones. This paper explores the applicability of the four most used approaches to predict financial bankruptcy using data concerning the case of Greece. A comparison of linear discriminant analysis, logit, decision trees and neural networks is performed. The results show that discriminant analysis is slightly superior to the other methods.

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Section: Discussionsupporting

confidence: 93%

Bankruptcy Prediction: The Case of the Greek Market

Papana

Spyridou

2020

Forecasting

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“…The key financial indicators used in their study were return on asset (ROA), quick ratio, debt equity, and asset turnover. Barreda et al (2016) found the MDA model outperformed the logit model for overall bankruptcy forecasting. Gémar et al (2016) examined the likelihood of survival in the Spanish hotel industry using a sample of 1,033 hotels spanning from 1997 to 2009.…”

Section: Business Failure Models In Tourism and Hospitality Sectorsmentioning

confidence: 97%

“…On the basis of the results of their study, Pereira et al (2017) claimed that forecasting business failure might enable policymakers to design macroeconomic policies and tourism development programs accordingly. Barreda et al (2016) investigated the likelihood of corporate failure in four categories of business in the hospitality sector in the United States, namely, restaurants, hotels, resorts, and casinos. In their study, the authors used the logit model and MDA to determine which of these two models provide the more accurate forecast on a dataset spanning from 1992 to 2010.…”

Section: Business Failure Models In Tourism and Hospitality Sectorsmentioning

confidence: 99%

Examining Ownership Equity as a Psychological Factor on Tourism Business Failure Forecasting

Korol

Spyridou

2020

Front. Psychol.

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This paper examines ownership equity as a predictor of future business failure within the tourism and hospitality sectors. The main goals of this study were to examine which ratios are the most important for a tourism business failure forecasting model and how significant is the "total percentage of equity ownership by company directors" ratio compared with other ratios associated with the probability of bankruptcy. A stepwise weight assessment ratio analysis (SWARA) was applied, and 12 tourism bankruptcy experts evaluated key ratios. Total percentage of equity ownership by company directors is considered a psychological factor, and it was identified as the fourth most important ratio for a business failure forecasting model. Academicians and practitioners can use the findings of this study whenever developing a forecasting model for tourism and hospitality enterprises.

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“…The evaluation criteria are as follows, that is: total accuracy, true positive ratio (TPR), and true negative ratio (TNR). This evaluation method has been used by many researches (Barreda, Kageyama, Singh, & Zubieta, ; Kim, ; Li et al, ; Li et al, ; Li & Sun, ) to show high effectiveness in prediction, among all the available measures (Amendola, Restaino, & Sensini, ; Demšar, ; Engelmann, Hayden, & Tasche, ). The evaluation criteria are illustrated as follows.

Total Accuracy = ((), TP + TN) / ((), TP + TN + FP + FN);

TPR = TP / ((), TP + FN);

TNR = TN / ((), TN + FP) .

…”

Section: Empirical Studymentioning

confidence: 99%

Asset restructuring performance prediction for failure firms

Hui

Chen

Hong

et al. 2019

J Corp Accounting Finance

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Blind Peer Reviews 7 The U.S. Dollar index cycle: Depreciation coming?Damir TokicThe recent U.S. Dollar Index countertrend rally will likely reverse to the longer-term downtrend due to: (a) narrowing interest rate differentials, (b) rising U.S. budget deficit, and (c) the geopolitical trend of dedollarization. 11Disclosure characteristics of firms being investigated by the SEC Christopher J. DemalineThe purpose of this study is to explore the characteristics of managers' 10-K disclosures concerning U.S. Securities and Exchange Commission (SEC) investigations. This study examined the quantitative linguistic characteristics of 171 company disclosures discussing the firms' involvement in an SEC investigation related to fraudulent financial reporting. The results suggest that these disclosures have a relatively negative sentiment and were relatively difficult to read. The results failed to provide sufficient statistical evidence to support the notion that managers systematically attempt to blame external parties for the potential wrongdoing and related investigation. The study results add to the stream of research related to impression management in corporate disclosures while also supplementing research on how companies respond to negative events such as regulatory investigations. This study may be of interest to financial regulators, investors, and accounting standards setters, all of whom are interested in maximizing the usefulness of financial information. 25This study aims to forecast asset restructuring performance for failing public firms and to test the effectiveness of different strategies of assets restructuring by using ten models, including: standalone models of multivariate discriminant analysis (MDA), logistic regression (Logit), probit, case-based reasoning (CBR), support vector machine (SVM), and their bagged ensembles. Moreover, this study proposes a knowledge base by collecting positive and

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

Cited by 23 publications

References 33 publications

Bankruptcy Prediction: The Case of the Greek Market

Bankruptcy Prediction: The Case of the Greek Market

Examining Ownership Equity as a Psychological Factor on Tourism Business Failure Forecasting

Asset restructuring performance prediction for failure firms

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