A Data Mining Approach for Evaluating the Tourist Destination Loyalty

Abstract

The aim of this study is to evaluate the tourist loyalty through data miningapproach. The study has exemined 880 domestic tourists who have stayed inmore than one night in four and five star hotels of Isfahan in spring and summer2014 and 2015. SPSS and Clementine12 was used for data analysis.Also,Mixture Algorithm PSO-KM was applied for tourism clustering.The resultsshowed that tourists can be classified in two categories. The first category havea high average in length of communication with tourism and travel recency andthe cost and frequency of travel are less than average. Therefore, the customersare loyal and uncertain. The second category has a high average in travelrecency and the length of communication with tourism, cost and frequency oftravel is less than average. Therefore the customers are new and uncertain.

Keywords

• evaluation of loyalty
• tourist
• data mining
• lrfm