Evolutionary game analysis and efficiency test of water pollution control driven by emission trading: Evidence from Zhejiang Province, China

Heliyon, Journal Year: 2024, Volume and Issue: 10(16), P. e36289 - e36289

Published: Aug. 1, 2024

Presently, China is actively endorsing the pilot initiative for remunerative use and trading of emission. By examining operation efficacy emission in context water pollution control, one can contribute to advancement refinement this system, thereby facilitating attainment regional reduction, carbon high-quality development objectives. In pursuit objective, we develop a theoretical framework local government sewage enterprises evolutionary game which includes two scenarios without considering studying influencing factors evolution trajectory subject's. Through stability analysis, interactive mechanism, difference trajectory, response logic decision-making body different situations become clearly visible. Further, system sensitivity are analyzed by solving partial derivation area formula phase diagram. And control Zhejiang Province empirically examined at micro level adopting data first country case Jinhua City. The research reveals following conclusions: Under specific circumstances, incentivize businesses even industries enhance measures as whole. performance degree vary across gaming systems, with public reputation evaluation central inspection serving positive constraints. initial cost paid permits, fixed component firms address pollution, has no effect on enterprises' behavioral actions satisfy regulations. findings furnish governments foundation decision support order optimize regulatory strategies policies.

Language: Английский

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A deep learning classification framework for research methods of marine protected area management

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 368, P. 122228 - 122228

Published: Aug. 24, 2024

The latest emerging transdisciplinary marine protected area (MPA) research scheme requires efficient approaches for theoretically based and data-driven method integration. However, due to the rapid development diversification of methods, it is growingly difficult locate new methods in methodological dimensions integrate them utmost utility. This study proposes a deep learning-based classification framework MPA management focused particularly on data theory capabilities using natural language processing (NLP). It extracted keywords from academic sources performed clustering semantic similarity, generating benchmark texts abstract labeling. By training learning NLP model analyzing abstracts 9049 empirical articles 1986 2024, scores were attributed each article, total 19 major categories 110 segment branches identified qualitative, quantitative, mixed genres. Combination types summarized, yielding data-theory neutralization principle where average tend approximate 0.50. Applying broadens traditional boundaries integration extends synthesis higher numbers, practical 2paradigm future research. Implications include bridging social ecological data, theorizing emergent challenges complex systems integrating construction science. applicable quantification other environmental disciplines can serve as guidance multidisciplinary © 2017 Elsevier Inc. All rights reserved.

Language: Английский

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A Multi-agent Financial Investment Decision Method Based on Evolutionary Game

Journal of Circuits Systems and Computers, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 30, 2024

Data-driven smart investment decisions are important for financial development, which has not received much attention from academia. As a result, this paper resorts to the evolutionary game theory, and proposes novel multi-agent decision method. Specifically, an theory-based decision-making approach is formulated as main model research purpose. By considering strategic choices adaptability among various entities, comprehensive analysis of behavior process entities in market achieved. This combines stock exchanges data providers (Bloomberg Thomson Reuters) conduct case studies on method, verifying its effectiveness feasibility practical applications. comparing traditional methods, it can be seen that proposal significant advantages improving efficiency, reducing risks, responding volatility. delves into method based game, providing new ideas methods academic applications field.

Language: Английский

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Collaborative Digital Governance for Sustainable Rural Development in China: An Evolutionary Game Approach

Agriculture, Journal Year: 2024, Volume and Issue: 14(9), P. 1535 - 1535

Published: Sept. 5, 2024

This paper explores the significance of digital governance for sustainable rural development in China, emphasizing collaborative efforts village administrative organizations, new agricultural business entities, and peasant households. Utilizing an evolutionary game approach, we examine decision-making behaviors stability points these three entities within context governance. Our analysis is grounded a mechanism interest linkage among stakeholders, with numerical simulations used to assess impact key variables parameters on their outcomes. The reveals that organizations are highly sensitive changes performance gains, special subsidies, penalty losses, benefit distribution coefficients. Enhancing can significantly motivate engage In contrast, households demonstrate stronger more consistent willingness collaborate, minimally affected by variable changes, which suggests solid economic social foundation China. underscores need positive incentives robust fault-tolerance foster collaboration organizations. It also highlights importance integrating into framework promote development. These insights provide valuable theoretical practical implications policymakers aiming enhance efficacy inclusivity

Language: Английский

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