Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/281860 
Year of Publication: 
2019
Citation: 
[Journal:] UTMS Journal of Economics [ISSN:] 1857-6982 [Volume:] 10 [Issue:] 2 [Year:] 2019 [Pages:] 201-214
Publisher: 
University of Tourism and Management, Skopje
Abstract: 
Because of the large share of travel and tourism revenues in total Croatian GDP, it is worth noting the importance of the hotel industry for the Croatian economy. Therefore, the problem that arises from such an obvious and increasing dependence of our economy on the hotel industry is primarily focused on the sustainability of business models of hotel companies in order to create the preconditions for their successful long-term business operations. Therefore, there is a need to monitor quality of business models that will lead to satisfactory financial results and determine the level of improvement of individual parts of business models significant for the hotel industry for the purpose of defining the quantity, type and source of financing of the necessary investments in the development of key resources and key activities. The paper analyses financial data and indicators on a selected sample using self-organising neural networks (SOM). The analysis points to the fact that it is possible to determine indicators by which the business model of hotel companies can be evaluated with respect to the quantities, types and sources of financing needed for the development of key resources and key activities.
Subjects: 
business model
financial indicators
self-organising neural networks
JEL: 
L21
L25
L53
M21
Document Type: 
Article

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