UNDERSTANDING CLUSTER DIFFERENCES IN REGIONAL TOURISM PERCEPTIONS: ANOVA, PRUNED TREE, AND CORRELATION NETWORK ANALYSIS FROM THE MEKONG DELTA REGION
DOI:
https://doi.org/10.18173/2354-1067.2025-0061Từ khóa:
Cluster, regional tourism perceptions, correlation analysis, Mekong DeltaTóm tắt
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.
Tài liệu tham khảo
[1] Rodríguez J, Semanjski I, Gautama S, Van de Weghe N & Ochoa D, (2018). Unsupervised hierarchical clustering approach for tourism market segmentation based on crowdsourced mobile phone data. Sensors, 18(9), 2972. doi: 10.3390/s18092972.
[2] VMCST, (2016). Master plan for tourism development in the Mekong Delta region to 2030.
[3] Loi NA, Phat SN & Nguyen QN, (2023). Factors impacting destination attractiveness of the Mekong Delta, Vietnam. Journal of Law and Sustainable Development, 11(11), e1502–e1502. doi: 10.55908/sdgs.v11i11.1502.
[4] Nguyen TL & Dang KT, (2024). Factors affecting brands and competitiveness of tourism destinations: an analysis of the Mekong Delta. The Singapore Economic Review, 69(08), 2755–2774. doi: 10.1142/S0217590823500510.
[5] Luongo S, Sepe F & Del Gaudio G, (2023). Regional innovation systems in tourism: The role of collaboration and competition. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 100148. doi: 10.1016/j.joitmc.2023.100148.
[6] Richards G, (2020). Designing creative places: The role of creative tourism. Annals of Tourism Research, 85, 102922. doi: 10.1016/j.annals.2020.102922.
[7] Black W & Babin J, (2019). Multivariate data analysis: Its approach, evolution, and impact. In The great facilitator: Reflections on the contributions of Joseph F. Hair, Jr. to marketing and business research (pp. 121–130). Cham: Springer International Publishing.
[8] Everit B & Hothorn T, (2011). An introduction to applied multivariate analysis with R. Springer Science & Business Media.
[9] Pike S, (2017). Destination positioning and temporality: Tracking relative strengths and weaknesses over time. Journal of Hospitality and Tourism Management, 31, 126–133. doi: 10.1016/j.jhtm.2016.11.005.
[10] Vu HM, Lam TM & Prabhakaran S, (2021). Perceptions of key stakeholders towards sustainable tourism development: A case study in Mekong Delta, Vietnam. The Journal of Asian Finance, Economics and Business (JAFEB), 8(4), 717–726. doi: 10.13106/jafeb2021.
[11] Panzera E, (2022). Cultural heritage and territorial identity: The economic consequences of their synergies. In Cultural Heritage and Territorial Identity: Synergies and Development Impact on European Regions (pp. 145–172). Cham: Springer International Publishing. doi: 10.1007/978-3-030-94468-1_6.
[12] Nguyen PT, (2025). Segmenting perceptions of regional tourism linkage via hierarchical cluster analysis: evidence from the Mekong Delta region. Journal of Science, Ho Chi Minh City University of Education, 22(9), 1731–1741.
