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http://hdl.handle.net/10553/135758
Title: | Prediction of tourism zombie companies using artificial intelligence algorithms and accounting data | Authors: | Sánchez Medina, Agustín Jesús Blázquez Santana, Félix Cerviño Cortínez, Daniel Laureano Pellejero Silva, Mónica Avelina |
UNESCO Clasification: | 531290 Economía sectorial: turismo 5303 Contabilidad económica 3325 Tecnología de las telecomunicaciones |
Keywords: | Zombie firms Tourism SMEs Artificial intelligence Machine learning Prediction |
Issue Date: | 2025 | Journal: | European Journal of Tourism Research | 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. | URI: | http://hdl.handle.net/10553/135758 | ISSN: | 1314-0817 | DOI: | 10.54055/ejtr.v39i.3648 | Source: | European Journal of Tourism Research, 39, 3906. |
Appears in Collections: | Artículos |
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