Abstract
The role of transport services in the tourism sector is very important – the tourist has to travel in order to reach a destination. The current economic crisis has profound implications on the entire world economy, also affecting national economies. Transport and tourism are important industries and their role in the overall economic development cannot be neglected. This paper explores the implications of private air transport on the evolution of tourism in Romania. We analyse a set of indicators that is important for the dynamics of these industries and the correlation degree between the tourist traffic indicators and some of the air transport indicators. We apply various econometric and statistical methods as the correlation coefficient and the regression method. The identification of these correlations is necessary for conceiving strategies of neutralisation of negative effects or of enhancement of positive influences in relation to tourism evolution.
 Keywords: Private air transport, tourism, demand, supply, tourism evolution.
Highlights
DATA AND METHODOLOGYThe correlation between tourism indicators and air transport indicators will be tested and the present paper will apply econometric and statistical methods such as correlation and regression coefficient
The role of transport services in the tourism sector is very important - the tourist is forced to travel in order to reach the destination
The authors argue that the size of the demand and supply of transport services is determined by several factors, among which the most important are technology, cost of services, fees, number of bidders and economic and social conditions
Summary
The correlation between tourism indicators and air transport indicators will be tested and the present paper will apply econometric and statistical methods such as correlation and regression coefficient. The basic element in regression is the regression function, which presents the dependency of the Y variable on the X variable factor (Zaharia et al 2010). The regression function can be validated by the dispersion analysis which is calculed by the F test (Fisher Snedecor). The regression model is statistically significant if calculated F is greater than critical F. The model can be considered statistically significant if Significance F is lower than α, where α represents the significance threshold and 1 – α represents the confidence level.
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