Analysis of Health tourist’s Behaviors Using Data Mining Method (International Tourists)

Background and Objectives: Nowadays, attracting tourists and keeping them in a competitive environment, especially in the health tourist industry, has a high priority. Given the different behaviors of health tourists, analyzing their behavior is important. Methodology: This research is applied in terms of purpose and descriptive method. Data mining methods and powerful Python tools have been used to analyze the data. The combined method of clustering algorithm and communication rules have been used to identify the pattern of tourist behavior. Results: After analyzing the data, the motivation of foreign tourists to travel to Iran was determined and the selected destination was prioritized based on importance and according to the behaviors and different needs of health tourists, different travel packages were designed. Conclusion: By analyzing the behavior of tourists and clustering them according to the type of behavior in each cluster, it is possible to achieve strategies tailored to their needs and predict the future behavior of tourists through their past behavior and was informed of the threats, opportunities, strengths, weaknesses of the system.

Keywords:

Facilitator companies , Health behavior , Data mining , Cluster analysis