The aim of the paper is to examine the issue of market recovery and business entities in the pandemic and post-pandemic period. Overall it points out the possibilities of the solution on the basis of interviews and utilizing the models of simulation of the results of companies that have been affected by the crisis. The paper used statistical data obtained by research in the analysed period March - April 2020 and in the examined years 2019 to 2023, including prognostic data from the sources of the Ministry of Finance of the Slovak Republic. Based on the results of selected companies with and without pandemic measures were simulated. Resulting from the research findings, proposed model presents the state of the company affected by the crisis and ways of solving how to get out of this crisis and design further development in the post-pandemic period. The paper pointed out the need to increase expertise in decision-making on the development of the economy of business entities and subsequently the development of the industry with targeted support from the state based on research base in combination with future modelling methods.

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Abstract:The paper addresses the issue of management decision-making using artificial neural networks and their application in hotel management. Today, the development of tourism is of great importance and plays a very important role in the development of national economy. Balanced ranking and prediction model using financial and non-financial indicators with the application of artificial intelligence, allows us to reach a high level of effectivity and accuracy in evaluation of the financial and non-financial health of companies operating in this segment. This approach improves the manager's ability to understand complex contexts and make better decisions for further development. It also brings new managerial and scientific point of view of an in-depth analysis of the performance of these facilities. It can help the development of tourism in terms of the application of modern management techniques built on scientific principles and thereby better integrate science and practice.JEL Classification Numbers: C45, Z32; DOI: http://dx.doi.org/10.12955/cbup.v5.928Keywords: Prediction models, financial health, neural networks, management, tourism. IntroductionTourism development has great importance and plays a significant role in the development of national economies (Šenková and Šambronská, 2014; Council, 2016). Therefore, the efforts of each country are heading to assist in the development of this industry effectively. Management, economics and application of modern methods of economics and management have very important role in this development and thus equally important is managerial decision making. The ability to decide optimally is one of the most crucial parts of hotel manager's everyday job (O'Halloran, 2015). There are several methods that can be used in the field of managerial decision making. Many methods are based on an assessment of the performance of these businesses using the methods of financial analysis, prediction models, Economic Value Added or the methodology of the business performance analysis based on financial (Horváthová and Mokrišová, 2014) and non-financial indicators -Balanced Scorecard (Ivanickova et al., 2016). All these methods provide information to the optimal decision making by managers and to better controlling of these organizations. From modern economics models that can play a major role in the future, the management decision-making methods based on classification and prediction using artificial neural networks (ANN) are the most promising. Artificial neural networks are one of the modern trends in assessment of the financial and nonfinancial health of the business. They are particularly suitable when part of the decision-making processes depends on coincidence and/or deterministic dependency. They are therefore suitable for modeling and exploration of complex, single, often irreversible strategic management decisions (Hanne, 1997). During analytical phase of research, we have conducted many experiments with popular conventional models like Tafler model (Taffler and Tisshaw, 1977),...

Natural healing resources in the form of mineral and thermal waters and climatic conditions, together with a rich history and modern medical procedures, rank Slovakia among the important European countries in the field of spas. At the same time, spa tourism has a significant economic benefit for the country. This study examined the impact of the Coronavirus Disease 2019 (COVID-19) pandemic on spa tourism in Slovakia. The Box-Jenkins methodology was used to model and forecast the time series for selected indicators. The analysis used monthly data on the capacity and performance of spa facilities for 2006–2019 and compared the forecast development for 2020–2021 with the reality as affected by the pandemic. Despite the high quality of the models, the methodology used did not take into account an unexpected event such as a pandemic. Therefore, the models were quite inaccurate and had little predictive value. At the same time, it is clear that the pandemic significantly affected spa tourism.

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