Global Business and Finance Review | 2026
Authors: Yoon S.; Lee Y.
DOI: 10.17549/gbfr.2026.31.2.191
Journal: Global Business and Finance Review
Year: 2026
Publisher: People and Global Business Association
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
Purpose: This study aims to develop a new framework for rural experiential tourism by analyzing tourists' perceptions of the 6th industry using big data. It identifies critical components that strongly resonate with tourists, creating memorable experiences, and proposes practical, sustainable strategies for industry development. The research provides stake-holders with insights to understand tourist expectations clearly and develop differentiated tourism products and services. Design/methodology/approach: This study collected 13,585 online reviews through web crawling. Frequency and CONCOR analyses segmented the data into four thematic groups. Factor analysis and multiple regression analysis subsequently examined relationships between identified key words and tourist satisfaction. Findings: The four identified groups, namely experience, activity, nature, and attraction, highlight educational, emo-tional, sensory, and participatory elements as essential components for memorable tourism experiences. Interaction between tourists and experience providers enhances the quality of the experience. Walking environments contribute to emotional satisfaction through natural immersion. Perceived value positively affects tourists' willingness to pay, and elements such as landscapes and local seafood significantly enhance sensory and cultural satisfaction, thereby strengthening overall competitiveness in rural experiential tourism. Research limitations/implications: This study's focus solely on rural experiential tourism in Jeju limits broader applicability. Future studies should comparatively analyze tourist perceptions in other regions. Moreover, the pri-mary reliance on text mining and semantic network analysis may restrict deeper contextual interpretations. Online review dependency also poses limitations by potentially excluding elderly or digitally marginalized populations. Nevertheless, findings offer actionable insights, including targeted marketing strategies, differentiated program de-velopment, and community collaboration frameworks to foster regional economic revitalization and sustainable growth. Originality/value: By applying big data-driven text mining and semantic network analysis, this study provides qualitative and quantitative insights into tourist satisfaction. It contributes foundational knowledge and practical guidelines essential for enhancing the competitiveness and sustainability of rural tourism. ⓒ The Author(s).
6th industrialization; Big data; Memorable tourism experience; Rural experience tourism; Semantic network analysis; Text mining; Tourist satisfaction