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Comparing logit model with discriminant analysis for predicting bankruptcy in Portuguese hospitality sector / José Manuel Pereira, Mário Basto, Amélia Ferreira da Silva

Main Author Pereira, José Manuel Coauthor Basto, Mário
Silva, Amélia Ferreira da Abstract Portugal’s tourism sector is on permanent expansion and contributes significantly to the Portuguese economy. However, it has been facing the problem of business failure. The main goal of this paper is to develop an econometric and a multivariate model for forecasting business failure in the hospitality industry using logit and discriminant analysis. The present paper does not explore the causes of business failure but rather aims to propose a model that may help anticipate failure, so that decision makers can minimize the negative effects of this phenomenon. The results confirm that the models for forecasting business failure contribute positively to setting macroeconomic policies and tourism development support programs and are relevant for investors, stockholders, and decision makers. Analytic European Journal of Tourism Research, vol. 16 (2017), pp. 276-280 Topical name Turismo
Gestão hoteleira
Insolvência Form or physical characteristic Artigos em periódicos
Publicações em acesso aberto CDU 338.48(045) Online Resources Leia aqui este artigo
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Holdings
Item type Current location Call number Vol info Status Date due Barcode Item holds
Article Biblioteca Universidade Europeia (QBN)
Periódicos Biblioteca 		BIPAM-LX PER-14 vol. 16 (2017), pp. 276-280 Presencial/Restrito 3845-9717p
Total holds: 0

Portugal’s tourism sector is on permanent expansion and contributes significantly to the Portuguese economy. However, it has been facing the problem of business failure. The main goal of this paper is to develop an econometric and a multivariate model for forecasting business failure in the hospitality industry using logit and discriminant analysis. The present paper does not explore the causes of business failure but rather aims to propose a model that may help anticipate failure, so that decision makers can minimize the negative effects of this phenomenon. The results confirm that the models for forecasting business failure contribute positively to setting macroeconomic policies and tourism development support programs and are relevant for investors, stockholders, and decision makers.

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