SciELO - Scientific Electronic Library Online

 
vol.17 número4Mapeamento da maturidade dos sistemas de informação: o caso da hotelaria portuguesaDimensão territorial na internacionalização de destinos turísticos: fatores estruturantes no pós-COVID19 índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay articulos similaresSimilares en SciELO

Compartir


Tourism & Management Studies

versión impresa ISSN 2182-8458versión On-line ISSN 2182-8466

Resumen

GARCIA, Agustín del Castillo  y  MIGUELEZ, Sergio Manuel Fernández. Predictive potential of the global bankruptcy models in the tourism industry. TMStudies [online]. 2021, vol.17, n.4, pp.23-31.  Epub 31-Dic-2021. ISSN 2182-8458.  https://doi.org/10.18089/tms.2021.170402.

The globalisation process and the recent economic crises have increased the development of models to identify the factors related to business bankruptcy. The tourism industry is not immune to this concern, and in the previous literature, bankruptcy prediction models are generally focused on hotels or restaurants. However, there are no experiences of global models for tourism companies. This study develops a global bankruptcy prediction model capable of predicting any activities carried out in the tourism industry with high precision. To this end, a sample of 406 Spanish companies that have developed their activity in three tourism industry sectors (hotels, restaurants, and travel agencies) in the period 2017-2019 has been used. This sample includes bankrupt and non-bankrupt corporations and has allowed the comparison between a global model and various focused models applying artificial neural network techniques. The results have confirmed the superiority of the global model and provide different sample selection and cost minimisation solutions for bankruptcy prediction modelling in the tourism industry.

Palabras clave : Bankruptcy; prediction; tourist firms; artificial neural networks; multi-layer perceptron.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )