From service and facility quality to loyalty in urban tourism: Mediating role of visitor satisfaction in Jakarta’s public parks
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DOIhttp://dx.doi.org/10.21511/tt.5(1).2026.01
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Article InfoVolume 5 2025-2026, Issue #1, pp. 1-13
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Type of the article: Research Article
Urban public parks are increasingly recognized as important components of sustainable and green urban tourism systems, contributing to destination attractiveness, environmental quality, and visitor well-being. However, limited research explains how the quality of park facilities and services influences visitor behavior within urban tourism markets in emerging megacities. Grounded in the quality–satisfaction–loyalty framework, this study examines the effects of facility quality and service quality on visitor satisfaction and visitor loyalty across Jakarta’s public parks. Using 307 valid responses analyzed via partial least squares structural equation modeling (PLS-SEM), the findings reveal that both quality dimensions significantly enhance visitor satisfaction, which, in turn, strongly drives loyalty. Visitor satisfaction mediates the relationship between quality dimensions and visitor loyalty, with full mediation observed for facility quality and partial mediation for service quality, underscoring its central role in shaping repeat visitation and positive word-of-mouth in urban green tourism contexts. The study contributes to the literature on tourism marketing and sustainable destination management and offers practical implications for tourism authorities and park managers seeking to strengthen satisfaction-driven loyalty in urban tourism markets.
- Keywords
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JEL Classification (Paper profile tab)L83, M31, Z32, R11
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References46
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Tables8
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Figures2
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- Figure 1. Conceptual model
- Figure 2. Structural model output (SEM-PLS)
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- Table 1. Demographic and visitation characteristics of respondents
- Table 2. Construct reliability and convergent validity
- Table 3. Fornell-Larcker criterion
- Table 4. Heterotrait-monotrait (HTMT) ratios
- Table 5. Indicators, factor loadings, and VIF values
- Table 6. Collinearity statistics (VIF)
- Table 7. Explanatory strength, effect size, and predictive relevance of the structural model
- Table 8. Path coefficients and hypothesis testing (with one-tailed, 95% CI)
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