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