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To Be or Not Be Competitive Country: Analysis of Travel and Tourism Competitiveness Index by Multiple Data Mining Techniques

Abstract— Travel and Tourism Competitiveness (TTC) has been raised as an important issue by World Economic Forum (WEF). The measurements of TTC covering 141 countries around the world provide information for all stakeholders of each country to enhance tourism competitiveness since tourism improvement may lead to increasing national growth and wealth. The purpose of this study is to understand the factors contributing to tourism competiveness and their relationships. The Travel & Tourism Competitiveness Index (TTCI) of all countries were collected from WEF reports. Then, the dataset were analysed by three data mining techniques consisting of clustering, classification and association rules mining. The countries are clustered into 8 segments. Characteristics of each cluster and relationships of TTCI are also proposed. The revealed results in this paper can be used by the governments and tourism sectors to develop their strategic plans and management.

Index Terms— travel and tourism competitiveness, data mining, clustering, classification, association rule mining.

Anongnart Srivihok
Department of Computer Science, Faculty of Science, Kasetsart University, THAILAND
Arunee Intrapairot
Department of Management, Faculty of Business Administration, Rajamangala University of Technology Thanyaburi, THAILAND

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Cite: Anongnart Srivihok, Arunee Intrapairot, "To Be or Not Be Competitive Country: Analysis of Travel and Tourism Competitiveness Index by Multiple Data Mining Techniques," Proceedings of 2016 6th International Workshop on Computer Science and Engineering, pp. 206-213, Tokyo, 17-19 June, 2016.