Identifying Optimal Tourism Areas in ECOWAS Through K-Means Clustering of Macroeconomic Indicators

Domaine:

socioeconomic

Type de record:

paper

Créateur:

MohJosMir

Éditeur:

Hôte:

This study applies K-means clustering to identify optimal tourism development areas among 15 ECOWAS member states. Eight macroeconomic indicators—Real GDP, GDP growth, CPI, CPI volatility, Terms of Trade Index, Balance of Payments, Trade Intensity Index, and Real Effective Exchange Rate—are extracted from 2005–2025 data and normalized for clustering. The elbow method and silhouette analysis jointly indicate k=3 as the optimal number of clusters. Principal Component Analysis (PCA) reveals that the first two components capture 65.4% of total variance, with economic size and external competitiveness as the dominant discriminators. Three clusters emerge: (1) Large Economies (Nigeria, Ghana), characterized by high GDP but macroeconomic instability; (2) Small/Open Economies (8 countries), exhibiting trade openness but limited market size; and (3) High-Performing Economies (Côte d'Ivoire, Guinea, Benin, Niger, Togo), combining strong growth, low inflation, and favorable external balances. A composite Tourism Optimization Score ranks Guinea first (0.441), followed by Côte d'Ivoire (0.379), Togo (0.372), Benin (0.359), and Senegal (0.336). These findings provide data-driven guidance for tourism investment prioritization in West Africa.

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