Distinguishing tourism destinations with behavioural data

Speaker(s): 

Defining tourism destination is complicated theoretical and empirical task. Historically, there have been many different approaches towards defining tourism destination. Traditional theories look at a destination as a geographical area such as a country, an island or a town (Hall 2000). New approaches go beyond the static viewpoint and consider tourism destinations as socially constructed spatial units (Framke 2002, Saarinen 2004). They are constantly changing and it is hard to define the boundaries of a destination (Saraniemi & Kylänen 2011). According to Kuusik (2011), even events (concerts, festivals, etc.) can be considered as destinations if the event itself was the main reason for the visitor to take the trip.
The aim of this paper is to develop a methodology for distinguishing tourism destinations in a certain area by using behavioural data gathered through mobile telephone positioning data. The spatio-temporal focus of visits can be studied statistically by using the daily mobility data of visitors. The need for defining tourism destination more precisely comes from practical experiences. The opportunity to differentiate destinations helps us to manage and market tourism destinations more effectively. Because there are competing and cooperating destinations and quite often destinations have seasonally different dimensions.
In our study, we use behavioural indicators such as the space-time mobility of visitors in a destination by using passive mobile positioning data (Ahas & Mark 2005, Ahas et al 2008). This is the phone use data which is automatically stored in the memory files of mobile operators for call activities or movements of handsets in the network. The database consists of locations of call activities, times, countries of origin of called phones and random IDs for visits and visitors.
A case study is carried out in Estonia to determine whether Saaremaa, the biggest island of Estonia and a well-known tourism resort, can be considered as an individual destination for foreign tourist or is it a part of a bigger national destination. Saaremaa
is an important tourism attraction in the Baltic Sea area with its historical milieus, buildings and landscapes and it is also a famous Spa and conference tourism area. Regression analysis are carried out in order to test whether the length of stay in Saaremaa depends on the visitor’s nationality, number of counties visited and time of visits. Repeat visitors and first comers are also considered.
Knowing the temporal and spatial distribution of visitors and days of visits helps to avoid duplication in destination management and marketing. Differentiation in tourism destination marketing is good for attracting new markets and target groups and creating new marketing strategies.

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