The dynamic evolution of collaborative networks in sustainable development: Untying impact of environmental policy in China using network-based text analysis approach

Abstract

As one of the key subjects of multi-center governance of environmental concerns, public perception is crucial in forming and implementing environmental policy. Based on data science research theory and the original theory of public perception, this study proposes a research framework to analyze environmental policy through network text analysis. The primary contents are bidirectional encoder representation from transformers-convolution neural network (BERT-CNN) sentiment tendency analysis, word frequency characteristic analysis, and semantic network analysis. The realism of the suggested framework is demonstrated by using the waste classification policy as an example. The findings indicate a substantial relationship between perceived subject participation and policy pilot areas and that perceived subject participation is repeating. On this premise, specific recommendations are made to encourage policy implementation.

Analyzing the Nexus Between Environmental Regulations, Green Supply Chain Management, and Corporate Social Responsibility in the Agri-Food Business

“…However, there is a lack of research on the relationship between ERs, CSR, and GSCM [29]. Further research is needed to explore these factors with MBT environmental regulation [30,31]. Therefore, this study explores MBT regulations with CSR and GSCM in agri-food business.…”