Prediction of tourism zombie companies using artificial intelligence algorithms and accounting data

Authors

  • Agustín J. Sánchez-Medina University of Las Palmas de Gran Canaria, Campus de Tafira, 35017, Las Palmas de Gran Canaria, Spain.
  • Félix Blázquez-Santana University of Las Palmas de Gran Canaria, Campus de Tafira, 35017, Las Palmas de Gran Canaria, Spain.
  • Daniel L. Cerviño-Cortínez Universidad del Atlántico Medio, Carretera de Quilmes, 37, 35017 Tafira Baja, Las Palmas de Gran Canaria, Spain. Email: Daniel.cervino@pdi.atlanticomedio.es
  • Mónica Pellejero Mid Atlantic University

DOI:

https://doi.org/10.54055/ejtr.v39i.3648

Keywords:

zombie firms, tourism SMEs, artificial intelligence, machine learning, prediction

Abstract

This paper addresses the problem of the prediction of zombie companies.  Despite their relevance, financial issues represent an area scarcely considered in relation to the tourism industry and this topic has so far remained totally unexplored. Zombie firms cause great damage to the sector in which they compete. However, there is no consensus regarding what actions should be applied to them are not due to the negative consequences of maintaining or liquidating them. In view of this, the key issue is to prevent them from entering this state. It would therefore be useful to have a methodology for predicting years in advance when a company will become a zombie firm. For this purpose, this article has used different artificial intelligence algorithms applied to easily obtained accountant data. Thus, 78.4% of correct predictions have been utilizing a dataset of 356 Spanish small and medium-sized enterprises in the tourism sector.

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Published

2025-01-15

How to Cite

Sánchez-Medina, A. J. S.-M., Blázquez-Santana, F. ., Cortínez, D. ., & Mónica Pellejero. (2025). Prediction of tourism zombie companies using artificial intelligence algorithms and accounting data. European Journal of Tourism Research, 39, 3906. https://doi.org/10.54055/ejtr.v39i.3648