AUTHOR=Barykin Sergey Evgenievich , Sergeev Sergey Mikhailovich , Kapustina Irina Vasilievna , Poza Elena de la , Danilevich Denis Vladimirovich , Mottaeva Angela Bahauovna , Andreeva Larisa Olegovna , Niyazbekova Shakizada Uteulievna , Karmanova Anna Evgenievna 

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

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.938768

DOI=10.3389/fenrg.2022.938768

ISSN=2296-598X

ABSTRACT=This study demonstrates algorithms that assist municipal administrations in making the best environmental decisions. They were created by large alpha-class municipal governments with assistance from the DEA and panel data analysis. Quarantine measures have significantly altered the structure and expansion of megacities during the last two years. The regulatory influence of such dispositive judgments is typically directed at economic companies with externalized activity. Relaxing epidemiological limits indicates a reduce safety of living circumstances, hence it is necessary to give choices for administrative decisions now. Tourists, cultural, scientific, and athletic event goers, students, educational institution attendees, and job seekers all migrate to these megacities. As a result, demand for municipal resources (common property resources) fluctuates throughout the year. The authors make use of mathematical and econometric modeling techniques as well as optimum solution theories. 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 ESG performance and digital finance improve corporate financing efficiency, as well as the influence of ESG performance on energy efficiency, all at a 1% significance level.