期刊名称：International Review of Management and Marketing
电子版ISSN：2146-4405
出版年度：2015
卷号：5
期号：4
页码：221-229
语种：English
出版社：EconJournals
摘要：The purpose of this study is to analyze and segment tourists who visit Istanbul and to identify tourist profiles based of those demographic and travel characteristic. The questionnaire, in four languages (German, English, Russian and Turkish) was applied by the researcher to departing tourists between 13-18 January, 2015 at Istanbul International Airport using face to face technic. A total of 508 usable questionnaires were collected and analyzed applying arithmetic mean, t-test, crosstabulation, ANOVA, factor analysis, k-means cluster and multiple correspondence analysis. Factor analysis revealed six different factors among tourists visiting Istanbul. “Destination security” have been identified as the most important factor affecting tourists visiting Istanbul. Then, K-Means Cluster method was applied and produced three meaningful market segments. The clusters are named “natural beauty and information seekers”, “price sensitives” and “independents”. Finally, Multiple Correspondence Analysis was applied to identify statistical relationship among these clusters. Keywords: Segmentation; Factor Analysis; K-Means Cluster Analysis; Multiple Correspondence Analysis; Tourist profile JEL Classifications: L83
其他摘要：The purpose of this study is to analyze and segment tourists who visit Istanbul and to identify tourist profiles based of those demographic and travel characteristic. The questionnaire, in four languages (German, English, Russian and Turkish) was applied by the researcher to departing tourists between 13-18 January, 2015 at Istanbul International Airport using face to face technic. A total of 508 usable questionnaires were collected and analyzed applying arithmetic mean, t-test, crosstabulation, ANOVA, factor analysis, k-means cluster and multiple correspondence analysis. Factor analysis revealed six different factors among tourists visiting Istanbul. “Destination security” have been identified as the most important factor affecting tourists visiting Istanbul. Then, K-Means Cluster method was applied and produced three meaningful market segments. The clusters are named “natural beauty and information seekers”, “price sensitives” and “independents”. Finally, Multiple Correspondence Analysis was applied to identify statistical relationship among these clusters. Keywords: Segmentation; Factor Analysis; K-Means Cluster Analysis; Multiple Correspondence Analysis; Tourist profile JEL Classifications: L83
