As it is commonly believed that tourism contributes positively to economic growth, many developing countries rely on tourism in their efforts to enhance their economic conditions. Serbia has also given priority to the development of tourism industry as a part of its economic growth strategy. In this paper we analyze the long-term effects of tourism on the economic growth of Serbia. More specifically, the tourism-led economic growth (TLEG) hypothesis is tested, which implies that tourism is a trigger of Serbian economic growth. This study investigates the causal relations between tourism growth and economic expansion for the Serbian economy by using cointegration analysis. The obtained results show that the hypothesis of tourism-led economic growth in the Serbian economy is confirmed.

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Hotels offer different types of services which have different impacts on the users’ satisfaction and have an influence in various extents on decision making, when it comes to the selection of hotels. As a part of research, empirical analysis based on the importance of different services which hotels provide, was conducted. The idea of research is to determine the importance of different types of services for users. The survey was conducted on a sample of 850 respondents in Serbia. The study used AHP methodology which is used in the decisionmaking process analysis and is suitable for studies defining the rank of relevance of individual elements. The obtained results presented in the study provide information such as, what services offered by hotels have the greatest importance for users. Based on the obtained results in empirical research, and by applying cluster analysis, two different segments of hotel guests are identified based on the preferred services. Segments are statistically different and can represent various targets in the hotel business policy.

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The previous research studies used mainly the occupancy rate as one of the key indicators of hotel performance. As the hotel occupancy rate varies both throughout the year and for different types of hotels, the use of panel data is more appropriate and more comprehensive compared to the cross-sectional data or time series, which have so far been most commonly used in similar research. Also, the previous research did not take into account the great heterogeneity among the analyzed hotels, nor the correlation of the occupancy rate in relation to its past values. By using the generalized method of moments within the dynamic panel data model, it is possible to take both properties into account. The analyzed data pertain to the hotel industry of Spain. Specifically, the given panel data include a sample of 49 hotels observed over a period of 12 years. The application of dynamic panel analysis shows that the values of hotel occupancy rate are influenced by the values of hotel occupancy rate with a lag one, as well as the values of total marketing expenses with a lag one. It was further determined that the values of incentive management fees, as well as the average daily rate and the consumer price index also have an impact on the observed variable. We are convinced that the presented analysis results will be of significant benefit to hotel managers.