Applying a probabilistic neural network to hotel bankruptcy prediction
Using a probabilistic neural network and a set of financial and nonfinancial variables, this study seeks to improve the ability of the existing bankruptcy prediction models in the hotel industry. Our aim is to construct a hotel bankruptcy prediction model that provides high accuracy, using inform...
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| Format: | Article |
| Language: | English |
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University of Algarve, ESGHT/CINTURS
2016-01-01
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| Series: | Tourism & Management Studies |
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| Online Access: | https://tmstudies.net/index.php/ectms/article/view/785/pdf_3 |
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| author | Manuel Ángel Fernández-Gámez Ana José Cisneros-Ruiz Ángela Callejón-Gil |
| author_facet | Manuel Ángel Fernández-Gámez Ana José Cisneros-Ruiz Ángela Callejón-Gil |
| author_sort | Manuel Ángel Fernández-Gámez |
| collection | DOAJ |
| description | Using a probabilistic neural network and a set of financial and nonfinancial variables, this study seeks to improve the ability of the
existing bankruptcy prediction models in the hotel industry. Our aim is
to construct a hotel bankruptcy prediction model that provides high
accuracy, using information sufficiently distant from the bankruptcy
situation, and which is able to determine the sensitivity of the
explanatory variables. Based on a sample of Spanish hotels that went
bankrupt between 2005 and 2012, empirical results indicate that using
information nearer to bankruptcy (one and two years prior), the most
relevant variable is EBITDA to current liabilities, but using information
further from bankruptcy (three years prior), return on assets is the
best predictor of bankruptcy. |
| format | Article |
| id | doaj-art-41b6180d95cf450fbb16f0117dd2379e |
| institution | Kabale University |
| issn | 2182-8466 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | University of Algarve, ESGHT/CINTURS |
| record_format | Article |
| series | Tourism & Management Studies |
| spelling | doaj-art-41b6180d95cf450fbb16f0117dd2379e2025-02-02T03:42:34ZengUniversity of Algarve, ESGHT/CINTURSTourism & Management Studies2182-84662016-01-01121405210.18089/tms.2016.12104Applying a probabilistic neural network to hotel bankruptcy predictionManuel Ángel Fernández-Gámez0Ana José Cisneros-Ruiz1Ángela Callejón-Gil2University of Malaga, Faculty of Economics, Department of Finance and Accounting, 29071 Malaga, SpainUniversity of Malaga, Faculty of Economics, Department of Finance and Accounting, 29071 Malaga, SpainUniversity of Malaga, Faculty of Economics, Department of Finance and Accounting, 29071 Malaga, SpainUsing a probabilistic neural network and a set of financial and nonfinancial variables, this study seeks to improve the ability of the existing bankruptcy prediction models in the hotel industry. Our aim is to construct a hotel bankruptcy prediction model that provides high accuracy, using information sufficiently distant from the bankruptcy situation, and which is able to determine the sensitivity of the explanatory variables. Based on a sample of Spanish hotels that went bankrupt between 2005 and 2012, empirical results indicate that using information nearer to bankruptcy (one and two years prior), the most relevant variable is EBITDA to current liabilities, but using information further from bankruptcy (three years prior), return on assets is the best predictor of bankruptcy.https://tmstudies.net/index.php/ectms/article/view/785/pdf_3hotel bankruptcy predictionprobabilistic neural networksbankruptcy variables sensitivityspanish hotel industry |
| spellingShingle | Manuel Ángel Fernández-Gámez Ana José Cisneros-Ruiz Ángela Callejón-Gil Applying a probabilistic neural network to hotel bankruptcy prediction Tourism & Management Studies hotel bankruptcy prediction probabilistic neural networks bankruptcy variables sensitivity spanish hotel industry |
| title | Applying a probabilistic neural network to hotel bankruptcy prediction |
| title_full | Applying a probabilistic neural network to hotel bankruptcy prediction |
| title_fullStr | Applying a probabilistic neural network to hotel bankruptcy prediction |
| title_full_unstemmed | Applying a probabilistic neural network to hotel bankruptcy prediction |
| title_short | Applying a probabilistic neural network to hotel bankruptcy prediction |
| title_sort | applying a probabilistic neural network to hotel bankruptcy prediction |
| topic | hotel bankruptcy prediction probabilistic neural networks bankruptcy variables sensitivity spanish hotel industry |
| url | https://tmstudies.net/index.php/ectms/article/view/785/pdf_3 |
| work_keys_str_mv | AT manuelangelfernandezgamez applyingaprobabilisticneuralnetworktohotelbankruptcyprediction AT anajosecisnerosruiz applyingaprobabilisticneuralnetworktohotelbankruptcyprediction AT angelacallejongil applyingaprobabilisticneuralnetworktohotelbankruptcyprediction |