A SYSTEMATIC LITERATURE REVIEW OF SUSTAINABILITY APPROACHES IN RECREATION MANAGEMENT
Bibliographic record
Abstract
This study systematically examined how the concept of sustainability has been addressed in recreation management across managerial, environmental, social, and behavioral dimensions by reviewing studies published between 2018 and 2025. Following the PRISMA 2020 guidelines, searches were conducted in Scopus, Web of Science, Google Scholar, and TR Dizin databases, yielding 412 records and seven additional sources. After removing 52 duplicates, 62 full-text articles were assessed, and 18 met the inclusion criteria for analysis. Data were analyzed using open and axial coding in Microsoft Excel and NVivo 14, with inter-coder reliability measured at κ = 0.86. Bibliometric validation was conducted using VOSviewer 1.6.20. Findings were clustered under four main themes: managerial approaches, participation and pro-environmental behavior, nature-based recreation and environmental management, and trends and research gaps in Turkish literature. Newcastle–Ottawa Scale assessments indicated that most studies presented low to moderate risk of bias. Overall, sustainability is predominantly framed through environmental protection, while managerial integration, governance, and performance assessment dimensions remain underdeveloped, particularly in local contexts. The results highlight that sustainable recreation management should evolve beyond environment-centered approaches toward institutionalization through social participation, leadership, resource management, and measurable performance indicators. Based on the findings, it is recommended to develop multidimensional assessment frameworks that integrate environmental indicators with managerial performance and participatory governance in sustainable recreation management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.046 | 0.043 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".