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

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