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°øÀ¯ ¼÷¹Ú ¼ÒºñÀÚ °æÇèÀÇ ±¸¼º ¿ä¼Ò¿¡ °üÇÑ ¿¬±¸ / A Study on the Components of Shared Accommodation Consumer Experience |
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ÀÌ¿¬Áø(Li, Yanzhen) ;ÀÓÈ£±Õ(Lim, Ho-Kyun) |
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Çѱ¹¹®È°ø°£°ÇÃàÇÐȸ ³í¹®Áý, Åë±Ç Á¦78È£ (2022-05) |
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°øÀ¯ ¼÷¹Ú; °æÇè ¿ä¼Ò; ÅؽºÆ® ¸¶ÀÌ´×; ¿¡¾îºñ¾Øºñ ; Shared Accommodation; Experience Component; Text Mining; Airbnb |
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The popularity of Airbnb has dramatically affected the accommodation industry. With the development of sharedaccommodation, it is necessary to understand the main influencing factors of shared accommodation experience. This research attempts to propose a theoretical framework for shared accommodation experience based on theories related toaccommodation experience and verifies the proposed theoretical framework through text data mining technology. This study usesOctoparse to capture the text content of consumer reviews of 300 homestays on the Seoul area page of the Airbnb platform,and a total of 18,105 online reviews are collected. Afterward, the collected text was analyzed by TF-IDF and N-Gram using theonline analysis platform Textom tool. The research results show that the experience of shared accommodation consumers ismainly affected by the physical environment(Physical setting-room, Location), human interaction, and price. This result isconsistent with the conclusion of the theoretical part. This article provides a reference for other researchers of sharedaccommodation experience. |