Key factors influencing sustainable population growth: A DEMATEL-ANP combined approach

This study highlights the importance of sustainable social demographic growth. It uses a model that combines the Decision-making Trial and Evaluation Laboratory (DEMATEL) with the Analytic Network Process (ANP) to examine key factors affecting this growth and their interactions. The analysis focuses on six critical factors: economic development, education and gender equality, health services, environmental sustainability, immigration policies, and technological advancement. Experiments using government and international organization databases include comparative experiments with deep learning prediction models, ensemble learning models, Causal Inference Models, complex network analysis models, and agent-based models. Comparison metrics cover accuracy, precision, recall, and F1 score. The results indicate that, with a data volume of 4000, the optimized model achieves an accuracy of 0.973, precision of 0.981, recall of 0.969, and an F1 score of 0.89, demonstrating the model's superior performance. The DEMATEL method analyzes the direct relationships among the factors. The results show that economic development and technological advancement have impact scores of 3.91 and 3.43, respectively, indicating their strong influence on other factors and their role in promoting sustainable demographic growth. Education and gender equality, health services, and technological advancement each have impact scores of 3.39, meaning they are significantly affected by other factors and are sensitive in the growth process. Finally, the ANP method is used to calculate the weights of each factor, determining their relative importance in sustainable social demographic growth. The results highlight that economic development level and technological advancement and innovation are core factors influencing sustainable social demographic growth, with significant direct and indirect impacts on other factors and a crucial role in the overall system. These findings provide a scientific basis for formulating relevant policies and interventions, particularly in prioritizing and strengthening economic and technological development strategies. This study offers valuable insights for research in demography, sustainable development, and social policy formulation.