Enhancing China’s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling

China has been at the forefront of adopting emerging technologies to drive its economic transformation towards sustainability. The country's green GDP accounting framework aims to capture the environmental costs and benefits associated with economic activities, providing a more comprehensive measure of the nation's true wealth and progress. However, the effective implementation of this framework has been hindered by challenges related to data collection, verification, and transparency. This study explores the potential of integrating blockchain technology and artificial neural networks (ANNs) into China's green GDP accounting framework to enhance the transparency, reliability, and sustainability of its economic development. China has been at the forefront of adopting emerging technologies to drive its economic transformation towards sustainability, and the green GDP accounting system aims to capture the environmental costs and benefits associated with economic activities. However, the effective implementation of this framework has been hindered by challenges related to data collection, verification, and transparency. The researchers propose that the integration of blockchain and ANNs can address these challenges. Blockchain's decentralized, transparent, and tamper-resistant features can improve data management, real-time monitoring, and secure traceability of environmental indicators. ANNs, with their ability to analyze complex data patterns, can enhance the analysis and prediction of the transparency of environmental indicators, the reliability of green GDP accounting, and sustainable economic growth (SEG). The study analyzes the technical capabilities of these technologies and examines the regulatory and institutional changes required to facilitate their integration into China's national accounting system. The results show valuable insights for policymakers, economists, and sustainability experts on the potential of blockchain and ANNs to enhance the accuracy, reliability, and transparency of green GDP accounting. The successful implementation of this integrated approach could significantly contribute to China's efforts to achieve its ambitious environmental goals and promote sustainable economic development.

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Publication Details

Journal
Scientific Reports
Published
2024-11-25
DOI
https://doi.org/10.1038/s41598-024-75994-x
Citations
4
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.12
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article

Enhancing China’s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling

Nengchao Wang, Jun Li, Guanfeng Cai, Yunhao Zhao
4 citations
Scientific Reports
Blockchain Technology Applications and Security
3.12
article

Enhancing China’s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling

Nengchao Wang, Jun Li, Guanfeng Cai, Yunhao Zhao
article en
4 citations

Abstract

China has been at the forefront of adopting emerging technologies to drive its economic transformation towards sustainability. The country's green GDP accounting framework aims to capture the environmental costs and benefits associated with economic activities, providing a more comprehensive measure of the nation's true wealth and progress. However, the effective implementation of this framework has been hindered by challenges related to data collection, verification, and transparency. This study explores the potential of integrating blockchain technology and artificial neural networks (ANNs) into China's green GDP accounting framework to enhance the transparency, reliability, and sustainability of its economic development. China has been at the forefront of adopting emerging technologies to drive its economic transformation towards sustainability, and the green GDP accounting system aims to capture the environmental costs and benefits associated with economic activities. However, the effective implementation of this framework has been hindered by challenges related to data collection, verification, and transparency. The researchers propose that the integration of blockchain and ANNs can address these challenges. Blockchain's decentralized, transparent, and tamper-resistant features can improve data management, real-time monitoring, and secure traceability of environmental indicators. ANNs, with their ability to analyze complex data patterns, can enhance the analysis and prediction of the transparency of environmental indicators, the reliability of green GDP accounting, and sustainable economic growth (SEG). The study analyzes the technical capabilities of these technologies and examines the regulatory and institutional changes required to facilitate their integration into China's national accounting system. The results show valuable insights for policymakers, economists, and sustainability experts on the potential of blockchain and ANNs to enhance the accuracy, reliability, and transparency of green GDP accounting. The successful implementation of this integrated approach could significantly contribute to China's efforts to achieve its ambitious environmental goals and promote sustainable economic development.

Scientific ReportsVol. 14(1)
Qingdao Huanghai University (CN)
Decent work and economic growth
Openalex Percentile: Top 7%
Blockchain Technology Applications and Security
3.12
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