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Study on Operating Strategy for Recreation Forests through Comparing the Level of User Satisfaction according to Clusters  

Gang, Kee-Rae (Dept. of Landscape Architecture, Graduate School, Kyungpook National University)
Lee, Kee-Cheol (Dept. of Landscape Architecture, Kyungpook National University)
Publication Information
Journal of the Korean Institute of Landscape Architecture / v.38, no.1, 2010 , pp. 39-48 More about this Journal
Abstract
Recreation forests are in the spotlight as the place for personality development, mind and body comfort, companionship, and environment education in forests and valleys. Visitors to recreation forests have been on the increase along with booming in recreation forest building since 1988. Recreation forests are being categorized according to some features such as regional and environmental condition. Recreation forests, however, have not met the expectations of some visitors who want to take a rest with calmness due to the influence of the 5-day-work-week system, increasing interest in rest, leisure, and well-being, and users converge during weekends, summer, and the tourist season. In order to improve visitors' satisfaction efficiently, this study surveyed the level of satisfaction in each cluster based on the precedent study which had classified 85 national or public recreation forests in Korea into clusters. Questionnaires were distributed properly to each cluster and, of the 1,132 questionnaires collected, 1,015 were valid and used for analysis. Reliability of questionnaires and statistical validity of the model were verified. As a result, there are meaningful differences in the ranking of independent variables which affect the level of satisfaction according to clusters. Variables in rest and fatigue recovery have the strongest influence on the level of satisfaction in the clusters of potential factor, internal activation factor, and mixed potential capacity factor. In the use performance and visiting condition factor cluster, appropriateness of visit cost is most influential and, in the education cluster, connectivity with tourist attractions around it is most affective. These results can provide priority in services and maintenance of recreation forests for improving the level of satisfaction and differentiate the distribution of resources according to clusters.
Keywords
Regression Analysis; ANOVA; Recreation; Model Study; Independent Variables; Dependent Variables;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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