The green development in China through the lens of complex cybernetics: Insight for a new era

Aihua Lin, Pierluigi Toma, Minfeng Zhang and Giulio Fusco

Technological Forecasting and Social Change, 2024, vol. 208, issue C

Abstract: Measuring the level of green development is far from being a well-assessed problem, due to both the broad meaning of green development and the presence of randomness in environmental changes. In this paper, we develop the sustainable development evaluation index system from different perspectives, including resource utilization, green development management, green development quality, environmental protection, growth quality and green lifestyle. This evaluation index system is further viewed as a cybernetic system. Following a rough set approach, we properly address the issue of uncertainty and develop a robust estimation methodology. Neighborhood rough set and rough set methods based on genetic algorithms (GAs) have been used to identify the key indicators within the system. First, the results illustrate how a cybernetic approach deals with green policy and economic growth. Second, such a cybernetic approach provides new insights into identifying the main attributes for a sustainable development. Finally, stategies of improving green development in different parts of China are provided, concluding this paper.

Keywords: Green development; Optimization; Cybernetics; Rough set based on genetic algorithms (GAs) (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524004554
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:208:y:2024:i:c:s0040162524004554

DOI: 10.1016/j.techfore.2024.123657

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().