The impact of public environmental concern on environmental pollution: The moderating effect of government environmental regulation

Abstract

As environmental problems continue to intensify, public environmental awareness and participation have become key forces in a modernized environmental governance system. Recognizing the importance of public participation in environmental governance, this study explores the influence of public pressure on environmental pollution and its implications for China’s long-term environmental management efforts. Using statistical and internet search data from 284 prefecture-level cities between 2011 and 2020, the study finds that a 1% increase in public environmental concern leads to a 0.009% reduction in pollution. The study also highlights the strengthening effect of government environmental regulation on the impact of public environmental concern. Moreover, regional heterogeneity analysis reveals a stronger effect of public environmental concern in cities facing low economic pressure. The findings of the study provide a reference for the construction of a coordinated and sustainable environmental governance model in China as well as in developing countries.

How Environmental Regulations Affect Green Total Factor Productivity—Evidence from Chinese Cities

“…Following this, local governments are very concerned about the public opinion on environmental protection in their regions, and when the public searches and posts about environmental protection topics on social media, the local governments in their regions will place more emphasis on the importance of environmental regulation in the government's work reports. It has been found that when people are more concerned about environmental issues in their cities, they will be more active in filing judicial lawsuits against high-polluting enterprises in their areas, complaining to higher administrative authorities or negatively criticising the government on local government websites [42,43], which will put greater public opinion pressure on the local government, thus prompting the local government to reduce high-polluting, high-energy-consuming, and high-emission industries [44,45], and pay more attention to the concept of environmental protection, thus increasing the local green total factor productivity. Accordingly, the following hypotheses are proposed: Hypothesis 2.…”

Can digital transformation promote green innovation in enterprises? the moderating effect of heterogeneous environmental regulations

“…Green innovation refers to the value creation activities that allow businesses to improve their environmental performance by enhancing or producing green technologies, processes, and products to lessen their negative impact on the environment [ 20 , 21 ]. As we can see from section 2.1, digital transformation leads to technological advances, drives down costs and economies of scale, all of which are theoretically conducive to green technological progress.…”

Assessing the Community Perception in San Jose, Occidental Mindoro, of Proper Waste Disposal: A Structural Equation Modeling Approach

“…Figure 1 shows the theoretical framework for assessing the community's perception of proper waste disposal. The researchers utilized the studies of [9], which incorporate the Theory of Planned Behavior (TBP), and [10], which states that policies and the role of the government are essential for proper waste disposal. Thus, these variables are Environmental Knowledge (EK), Environmental Concern (EC), Role of Government (RG), Policy and Regulation (PG), Personal Values (PV), Social Norms (SN), Environmental Attitudes (EA), Convenience (C), Intentions (I), and Waste Management Behavior (WMB) have been investigated in the current study.…”

“…This study utilized a descriptive correlational research design in which the researcher will send online questionnaires via link survey using Messenger and the researcher's social media accounts. The validity and reliability of the data in question are known to be enhanced by an increase in sample size [10]. The sample size of the research study was determined using Slovin's formula.…”