UNDERSTANDING CLUSTER DIFFERENCES IN REGIONAL TOURISM PERCEPTIONS: ANOVA, PRUNED TREE, AND CORRELATION NETWORK ANALYSIS FROM THE MEKONG DELTA REGION

DOI: 10.18173/2354-1067.2025-0061

Abstract

This research explores perceptual differences among tourist clusters to examine regional tourism linkage in the Mekong Delta, Vietnam. Building on prior perception-based segmentation, we re-estimate clusters with higher granularity (k = 3) and statistically validate differences across 25 variables using one-way ANOVA. A pruned decision tree clarifies the minimal set of cues that separates segments, while a correlation-network analysis visualizes how governance, cultural experience, and environmental attributes co-organize in tourists’ mental models. The results indicate 23 variables with significant mean differences (p < 0.001), with governance signals (policy coherence, partnership mechanisms) and cultural events emerging as dominant discriminators. This paper contributes by connecting perception-based segmentation with statistical verification, providing evidence-based outcomes for specific regional tourism strategies. The findings emphasize the significance of symbolic and structural characteristics in influencing tourist perceptions of interprovincial cooperation.