Sustainable Energy Efficient Human-Centered Digital Solutions for ESG Megacities Development

Abstract

This study demonstrates algorithms that assist municipal administrations to make the best environmental decisions. The algorithms developed by large alpha-class municipal governments with assistance of department of environmental agency data analyst. Mathematical and econometric modeling techniques as well as optimum solution theories adhered to develop a model, and the criteria is functionality, which reflects a balance between maximum profit, comfort in living circumstances, the environment, and the need to avoid a market failure scenario. The ensuing results allow for the most optimal administrative decisions, such as the rate of environmental taxes. The empirical findings show that higher environmental, social and governance performance and digital finance has improved the corporate financing efficiency, as well as the influence of ESG performance on energy efficiency, all at a 1% significance level.