The Artificial Intelligence as a decision-making instrument for Modeling and Predicting Small Cities’ Attractiveness: Evidence from Morocco

Authors

Sohaib Khalid, MASAFEQ Laboratory, National Institute of Statistics and Applied Economics, MoroccoFollow
Driss Effina, MASAFEQ Laboratory, National Institute of Statistics and Applied Economics, MoroccoFollow
Khaoula Rihab Khalid, LERSRG Laboratory,University of Sultan Moulay Slimane,Be ́ni-Mellal, MoroccoFollow
Mohamed Salem Chaabane, Laboratory of Systems Engineering (LaGes), Research Team Geomatic Sciences (SGEO), Hassania School of Public Works, MoroccoFollow

Author Country (or Countries)

Morocco

Abstract

This study analyzes residential attractiveness in small Moroccan cities using statistical models. Net migration rates are commonly used to assess attractiveness. The study estimated net migration rates for each city and employed a structural econometric model with logistic regression to identify influential variables that affect the net migration rate. These variables were then used in a predictive model with an artificial neural network algorithm. The logistic model revealed insights, highlighting the complexity of residential attractiveness influenced by factors like job supply, accessibility, and housing conditions. The artificial neural network model provided accurate predictions (over 80%), aiding policymakers in decision-making and prospective analyses.

Digital Object Identifier (DOI)

https://dx.doi.org/10.18576/amis/170517

Recommended Citation

Khalid, Sohaib; Effina, Driss; Rihab Khalid, Khaoula; and Salem Chaabane, Mohamed (2023) "The Artificial Intelligence as a decision-making instrument for Modeling and Predicting Small Cities’ Attractiveness: Evidence from Morocco," Applied Mathematics & Information Sciences: Vol. 17: Iss. 5, Article 17.
DOI: https://dx.doi.org/10.18576/amis/170517
Available at: https://digitalcommons.aaru.edu.jo/amis/vol17/iss5/17