Projected and Perceived Destination Images of the Tsunami Memorial Parks After the Great East Japan Earthquake: A Text Mining Analysis

Sihan Zhang, Qian Wang, Prudens Naura Afzelia, Yan Tang, Yilan Xie, Jing Zhang, Yusuke Matsuyama and Katsunori Furuya ()
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Sihan Zhang: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Qian Wang: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Prudens Naura Afzelia: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Yan Tang: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Yilan Xie: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Jing Zhang: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Yusuke Matsuyama: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan
Katsunori Furuya: Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan

Land, 2024, vol. 13, issue 12, 1-23

Abstract: Following the Great East Japan Earthquake, dark tourism was developed in the Tohoku Region of Japan. Notably, two government-built tsunami memorial parks in Ishinomaki and Rikuzentakata have obtained attention for their profound disaster narratives, iconic disaster sites, and expansive layouts. This study is the first to compare the projected destination image presented by destination management organizations with the perceived destination image held by visitors in these parks, and in dark tourism. Using online text data from both supply and demand sides of dark tourism and text mining analyses such as word frequency analysis, co-occurrence network analysis, and affection tendency examination, we revealed similarities and disparities between these two perspectives. Furthermore, this study concluded dimensions specific to dark tourism sites within the cognitive and affective destination image. Based on the findings, the study provides advice for destination managers to improve these sites, including developing non-dark tourism products and improving infrastructures. Additionally, it proposes placing greater emphasis on themes of revitalization and future development, while fostering visitor engagement in local non-profit and citizen activities to strengthen connections with residents. The findings demonstrate the effectiveness of text mining in comparing projected and perceived destination images in the context of dark tourism sites.

Keywords: memorial landscape; dark tourism; tourist destination image; text mining; the Great Eastern Japan Earthquake; tsunami (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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