Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

June 2, 2023


Pages


DOI

Article

Optimization path of corporate ESG performance and compensation performance management under carbon neutral target

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Authors

Xiaoping Que Affiliation:
College of Finance and Economics, Hainan Vocational University of Science and Technology, Haikou, 571126, China


Abstract

Under the development of low carbon economy with the goal of “carbon neutrality”, high-emission enterprises are facing more severe pressure of energy saving and emission reduction, and how to build and corporate payroll performance management system becomes the key to corporate carbon compliance. And in the green finance-assisted green low-carbon sustainable development has become the development direction, (Environmental-Social-Governance, ESG) evaluation system has also increasingly highlighted its importance, the ESG evaluation system as the leading investment concept in the international has been the mainstream. This paper analyzes the problems of enterprise compensation management system, constructs an optimization model of enterprise compensation management based on Genetic Algorithm-Back Propagation (GA-BP) neural network, and proposes measures to optimize enterprise compensation in the context of ESG performance, taking into account the current international enterprise economic policy background. The study proposes policy recommendations to promote the implementation of green and sustainable development concepts and policies during the 14th Five-Year Plan period, and effectively addresses the adaptation of ESG and corporate compensation management under the goal of carbon neutrality.


Keywords

carbon neutrality, ESG evaluation system, compensation management system, GA-BP neural network, sustainability, 91B32


Citation

Que, X. (2023). Optimization path of corporate ESG performance and compensation performance management under carbon neutral target. Applied Mathematics and Nonlinear Sciences, 8(1). https://doi.org/10.2478/amns.2023.1.00173

Published by: Engineering Journals

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