PROGNOSTICATION OF CRISIS-FREE DEVELOPMENT FOR HOTEL DOMAIN IN DNIPRO CITY - LYSENKO, Olena (Herald of Khmelnytskyi National University. Economic sciences, 2024)
With its dynamic structure, the world market of hotel services undergoes perpetual changes and develops in interaction with other markets of goods and services under impact of the market environment. Therefore, nowadays hotels have to adjust to a new kind of tourists who appear more and more selective about standards of accommodation facilities. The present paper’s focus is to encompass data on hotel rooms’ offer in the city of Dnipro, Ukraine. These data compose space series, precisely because they were collected at a specific moment of time, but from diverse and geographically scattered objects. Regressive mathematical models were thereupon elaborated in order to discover trends in price level changes for the requested hotel rooms. The models created give a chance to assess the trends of price rise or fall and the likelihood of running into crisis economic situations. The work is dedicated to analysis of trends in hotel rooms’ price changes as well as to assessment of these changes via elaboration of regressive economic mathematical models of space-time series. Gravity and significance of the study lies in the analysis and assessment of trends in price changes for hotel rooms of popular segment. Evaluation of economic tendencies in the hotel industry is relevant not only for Dnipro city, but also for forthcoming development of hotel segment for Ukraine in general. Extensive statistical data collected are up-to-date, as the figures are taken from online booking resources, as of November 2023. The analysis conducted is based on resort to mathematical modeling and therefore utilizes Microsoft Excel mathematical and statistical tools. The analysis held demonstrated presence of a mathematically defined tendency towards increase in price levels for hotel rooms. The function of price for scrutinized hotel rooms reflects apparent boost and overpasses the increase limit of the respective exponential function based on the same space numerical series.