Abstract:
General Background: Medical tourism represents one of the fastest-growing segments of the global tourism industry, contributing significantly to national economies and healthcare service development. Specific Background: Within this sector, tourist patient experience—shaped by service quality, tourism facilities, and medical services—has become central to marketing strategies and destination competitiveness. Knowledge Gap: Despite extensive discussion on medical tourism attributes, limited empirical evidence clarifies which experiential factors most strongly determine tourist loyalty in emerging destinations such as Holy Karbala. Aims: This study investigates the determinants of tourist loyalty in medical tourism marketing, focusing on the roles of tourist satisfaction, service quality, facilities, and environmental security at Al-Kafeel Hospital. Results: Based on survey data from 580 foreign tourist patients analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal that tourist satisfaction is the strongest predictor of loyalty (β = 0.50; f² = 0.30), followed by service quality (β = 0.35; f² = 0.18) and facilities (β = 0.28). Environmental security shows no statistically significant relationship with loyalty (p = 0.058). The structural model demonstrates strong explanatory power (R² = 0.65), with confirmed reliability and convergent validity (CR > 0.7; AVE > 0.5). Novelty: The study provides an empirically validated structural model highlighting satisfaction as the central construct in medical tourism marketing within a Middle Eastern healthcare context. Implications: The results support prioritizing service quality improvement, facility development, and systematic satisfaction monitoring to strengthen patient retention and strategic marketing performance in medical tourism destinations.
Highlights
• Patient contentment demonstrates the highest predictive value for repeat visitation and recommendation behavior.
• Healthcare and hospitality attributes contribute significantly to behavioral commitment.
• The structural model explains 65% of variance in patronage intention.
Keywords
Medical Tourism; Tourist Satisfaction; Tourist Loyalty; Service Quality; PLS-SEM
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References
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