A method to analyse seasonality in the distribution of tourists in Iceland

Iceland has enjoyed increased popularity among tourists during the last few years. In 2010, 459 thousand visitors came to Iceland but in 2015 about 1,3 million visited the country. Before 2010 seasonality was high but has decreased since. This is reflected in the changing amount of overnight stays in the capital area. The same has not happened in other regions of the country where seasonality is still high. It seems that during the off-peak season the visitors are overnighting in the capital region and taking day tours to destinations in South and West Iceland. Overnight stay data does therefore not give complete picture of travel behaviour and how tourists distribute around the country. Therefore a new approach is needed.The paper describes a method that analyses seasonality in the number of tourists at nature destinations in South and West Iceland. The data is obtained from vehicle counters. Seasonality at the destinations is then expressed numerically by computing the Gini coefficient. Finally the Gini coefficients are compared for the destinations, regional overnight stays and departures from Keflavík International Airport.The paper provides a methodological approach to analyse seasonality and the distribution of tourists in an efficient manner.Management implications
- The study provides important tools for analysing seasonality in the distribution of tourists on three levels: Nationally, regionally and at destination level. This is vital when planning tourism and gives a more complete picture of seasonality and the distribution of tourists than using only overnight stay data.
- Managing seasonality at a destination level requires having reliable data about the number of visitors. This can be obtained economically by counting vehicles arriving at the destination.
- For destination management it is important to know the number of tourists at all times during the year. It is important for deciding the amount of infrastructure and the staff required.
- Computing the Gini coefficient is important when comparing seasonality between destinations or regions as well as between years. Having a numerical measure of seasonality makes the comparison reliable and easy.