APPLICATION OF LINEAR REGRESSION FOR PREDICTING DIGITAL TRAJECTORIES OF BENINESE MUNICIPALITIES

  • Doctoral School of Engineering Sciences (EDSI), University of Abomey-Calavi (UAC), Benin.
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Background: Anticipating digital development trajectories is crucial for strategic planning and resource allocation in municipal governance. This research applies linear regression analysis within a Decision Support System (DSS) framework to predict digital development trajectories of Beninese municipalities, building on data infrastructure and K-Means clustering results from companion studies. Objective:To establish a framework for implementing regression models capable of forecasting the evolution of key territorial digitization indicators, while defining methodological and technical prerequisites for predictive approaches.

Methods:Using a standardized 45-indicator framework across multiple thematic domains, sixyears of historical data covering all 77 municipalities (462 municipality-year observations) were analyzed. Regression models incorporated temporal trend analysis and municipality-specific specifications. Validation was performed through temporal and cross-sectional approaches.


[Narcisse Arsene Dagba, Aziz Saibou and Theophile Aballo (2025); APPLICATION OF LINEAR REGRESSION FOR PREDICTING DIGITAL TRAJECTORIES OF BENINESE MUNICIPALITIES Int. J. of Adv. Res. (Aug). 958-968] (ISSN 2320-5407). www.journalijar.com


Narcisse Arsène DAGBA
Doctorant, École Doctorale des Sciences de l’Ingénieur, Université d’Abomey-Calavi, Bénin
Benin

DOI:


Article DOI: 10.21474/IJAR01/21586      
DOI URL: https://dx.doi.org/10.21474/IJAR01/21586