January 1, 2025

Emerging Rural Destinations: Multimethod Approach to Decode What Drives Consumer Behavior

Puntos clave

Destination loyalty is directly influenced by both destination image and memorable tourism experience, showing a clear relationship.
Findings revealed that consumer perception of community interaction positively affects satisfaction but not directly loyalty.
Using structural equation modeling and machine learning techniques, this analysis offers a robust understanding of tourist behavior.
Practical recommendations for rural tourism practitioners highlight strategies to engage tourists and enhance their experience.

Resumen

The current study aims to integrate the tourist perspective from both supply and demand sides in predicting consumer satisfaction and loyalty in rural tourism. Grounded in the push-pull framework, the research develops a conceptual model and employs a multi-method approach for validation. Structural Equation Modeling (SEM) and two machine learning techniques Artificial Neural Networks (ANN) and Random Forest (RF) are utilized to ensure robustness in analysis. The findings reveal that both destination image(DI) and memorable tourism experience (MTE) directly impact destination loyalty. Additionally, consumer perception of community interaction (CPCI) positively influences satisfaction but does not have direct effect on destination loyalty. However, CPCI impacts destination loyalty indirectly forming a sequential mediation through MTE, DI and SAT. The key findings from ML-technique suggest consumer expectation as the most crucial determinant. Practically, this study provides several recommendations to RT practitioners about how to use the determinants of RT and identifies moderators to lure tourists to visit the destination.

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