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Korean Journal of Leisure, Recreation & Park - Vol. 49, No. 4, pp. 47-56
Abbreviation: KSLRP
ISSN: 1598-0413 (Print)
Print publication date 31 Dec 2025
Received 27 Oct 2025 Revised 27 Nov 2025 Accepted 19 Dec 2025
DOI: https://doi.org/10.26446/kjlrp.2025.12.49.4.47
최상의 여가만족 핵심 변인 탐색: 국민여가활동조사(2022-2024)를 기반으로
황희성1 ; 황선환2
1서울시립대학교
2서울시립대학교
Exploring Core Variables for Optimal Leisure Satisfaction: An Analysis of the National Leisure Activity Survey (2022-2024)
Hwang, Hee-Sung1 ; Hwang, Sun-Hwan2
1University of Seoul
2University of Seoul
Correspondence to : Hwang, Sun-Hwan E-mail: shhwang@uos.ac.kr

This study sought to elucidate predictive factors that contribute to optimal leisure satisfaction, a crucial determinant of quality of life in contemporary society. Although prior research has established a positive relationship between leisure and happiness, it has been limited in delineating the specific conditions under which optimal effects are achieved. The "paradox of choice" phenomenon further necessitates personalized leisure recommendations to help individuals navigate an overwhelming array of options. Accordingly, this study statistically analyzed three years (2022-2024) of raw data from the National Leisure Activity Survey, conducted by the Ministry of Culture, Sports and Tourism, to identify the common characteristics of a group reporting the highest levels of leisure satisfaction and happiness.

K-means cluster analysis was employed to identify a "Top-Tier Satisfaction Group" from approximately 10,000 respondents annually. Subsequently, logistic regression analysis was performed to determine the predictive variables that significantly influence membership in this group.

The analysis identified 27 significant variables, which were then categorized based on their temporal consistency: three "Core Variables" (significant across all three years), twelve "Major Variables" (significant for two years), and twelve "Potential Variables" (significant for one year). Notably, "satisfaction with public cultural and leisure facilities within one's living area," "one's occupation," and "primary leisure space used outside the home" emerged as the most stable, core predictors of optimal leisure satisfaction.

These findings are of academic significance as they present a data-driven, sophisticated predictive model that moves beyond identifying simple correlations. The results provide a robust empirical foundation for the development of personalized AI-based leisure recommendation systems and for the formulation of national policies aimed at enhancing public well-being through leisure.