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The aim of the given paper is to present the analysis of tourism services by means of time series models and forecasting of evaluation of tourism services. Tourism services are analysed according to various parameters: hotel stay price, hotel services quality (such as cleanness of rooms, check-in, information provision etc.), catering quality and medical service quality. The research has been undertaken on the basis of responses of foreign guests of 13 hotels in Kołobrzeg region taken from 1400 questionnaires divided according to age and sex of respondents. Various econometric models were used for the analysis of statistic regularities. First, customers evaluated quality of their stay in hotels. These data were examined during the 2006-2009 time period as a stochastic process. It was found that the processes are nonstationary, that is why the ARIMA (1,1,1) model was used in the study. On the basis of the analyses and prognoses one can deduce that models of time series make it possible to estimate a tendency that occurs for an analysed parameter, however misprediction is quite possible to appear (up to 30 %). Similar results were achieved during the analysis of evaluation of hotel stay quality on the basis of sex of respondents. One should point out that an average value of male evaluation rate is higher than an average value of female evaluation rate. Time series for analysed variables were integrated into level I(1). A certain co-integrational connection was found between the evaluation of hotel stay and number of stays in a given hotel, where tourists that have already visited a given hotel for several times presumably give a high evaluation rate of hotel stay quality. The result of the analysis of long-term relation between hotel stay and duration of check-in is presented in high mutual dependence of hotel evaluation rate on evaluation of check-in duration. A hotel stay price influences hotel stay evaluation in a negative way, but catering and medical services are considered as standard and do not have any particular influence on hotel stay evaluation. The undertaken study shows that methods that take into account time series can be successfully used in analysis of parameters of tourist comfort and in evaluation of hotel services.
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