A Data Mining Approach for Evaluating the Tourist Destination Loyalty

The aim of this study is to evaluate the tourist loyalty through data mining approach. The study has exemined 880 domestic tourists who have stayed in more than one night in four and five star hotels of Isfahan in spring and summer 2014 and 2015. SPSS and Clementine12 was used for data analysis.Also, Mixture Algorithm PSO-KM was applied for tourism clustering.The results showed that tourists can be classified in two categories. The first category have a high average in length of communication with tourism and travel recency and the cost and frequency of travel are less than average. Therefore, the customers are loyal and uncertain. The second category has a high average in travel recency and the length of communication with tourism, cost and frequency of travel is less than average. Therefore the customers are new and uncertain.