APPLICATION OF K-MEANS ALGORITHM FOR CLASSIFICATION OF BENINESE MUNICIPALITIES ACCORDING TO THEIR DIGITAL DEVELOPMENT PROFILE

Background: Optimizing digital territorial development policies requires a thorough understanding of municipal digital profiles and their heterogeneity. This study explores the application of the K-Means clustering algorithm to categorize the 77 Beninese municipalities according to their digital development profile using comprehensive data from the foundational Decision Support System (DSS)described in our companion study.

Objective: To develop an innovative methodological approach for analyzing territorial digital disparities and establish municipal typologies to optimize digital territorial planning policies.

Methods: Based on a standardized 45-indicator framework across multiple thematic domains collected through our Decision Support System, this research applies K-Means clustering with optimal cluster determination through silhouette analysis. The dataset comprises 20,790 data points providing robust foundation for unsupervised learning analysis.