Construction of a model which investigates the impact of selected variables on international tourist flows to Turkey

Typescript (photocopy).The study developed a model which explained the impact of selected variables on international tourism flows to Turkey. This study differed from earlier investigations in that it focused directly upon international tourism demand in a developing country and used a country-by-country approach. Ordinary least squares multiple regression technique was used, and individual equations were developed for the following countries: Austria, Canada, France, Greece, Italy, Spain, Switzerland, West Germany, United Kingdom, United States, and Yugoslavia. Two different dependent variables were used in the study: number of tourists and their total expenditures. Both the linear and double logarithmic forms were tested. The double logarithmic, which provided the better fit, was chosen for use in the analysis. All results reported were based on the natural log model, as the coefficients associated with non dummy variables were elasticities of the selected variables. Economic factors which were quantifiable, measurable, and best able to explain and predict tourism demand for Turkey, were used to develop a demand function. The study directly evaluated not only the effects of income, relative prices, and exchange rates, which typically have been included in other models, but it also measured the impact of promotional expenditures upon tourism demand to Turkey. There were similarities and differences among the tourist generating countries, but the study found that exchange rates, relative prices, and per capita income were consistently important contributors in determining the level of international tourist flows to Turkey. In constrast, the study suggested that expenditures invested in promoting Turkey as a tourist destination had minimal impact on international tourist flows to Turkey. Finally, the analyses suggested that international tourism to Turkey is responsive to changes in socio-political and economic conditions. The specific conclusions of the study primarily have short-term applicability. However, the methodology which was developed has long term utility because it is relatively easy to update the model each year to reflect changes in the selected variables