Keywords

big data analysis, decision trees, quantitative destination marketing, data mining, Japan

Abstract

The increasing power of technology puts new, advanced statistical tools at the disposal of researchers. This is one of the first research articles to use a data mining tool—namely, decision trees—to analyze the behavior of inbound tourists for the purpose of effective future destination marketing in Japan. The research results of approximately 4,000 observations show that the main motivation for visitors' future return is not driven by experiences had during their most current visit but rather by experiences anticipated in the future, such as visiting hot springs or immersing themselves in beautiful natural settings. The data mining method largely excludes the possibility of the intrusion of researcher subjectivity and is conducive to useful discoveries of certain visitor patterns in large data sets, providing governments and destination marketing organizations with additional tools to better formulate effective destination marketing strategies.

Publication Date

4-3-2017

Original Citation

Shapoval V., Wang., C. Hara T., & Shioya, H. (2017) Data mining in tourism data analysis: Inbound visitors to Japan. Journal of Travel Research.

DOI

10.1177/0047287517696960

Document Type

Paper

Language

English

Source Title

Journal of Travel Research

Publication Version

Post-print

College

Rosen College of Hospitality Management

Location

Rosen College of Hospitality Management

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