Research on the "multi-agent co-governance" system of unfair competition on internet platforms: Based on the perspective of evolutionary game
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View abstract on PubMed
Summary
This summary is machine-generated.Effective supervision of unfair competition on internet platforms (UCIP) requires moderate government intensity and active participation from industry associations and users. This multi-agent approach guides UCIP governance toward normalization.
Area Of Science
- Economics
- Game Theory
- Internet Governance
Background
- Unfair competition on internet platforms (UCIP) hinders the platform economy's growth.
- Traditional unitary supervision models are insufficient for complex online environments.
Purpose Of The Study
- To construct and analyze a multi-agent co-governance model for UCIP.
- To investigate the evolutionary game dynamics between government and internet platforms under different supervision modes.
- To provide insights for optimizing UCIP supervision mechanisms in China.
Main Methods
- Evolutionary game theory applied to government and internet platform interactions.
- Construction of "multi-agent co-governance" and "unitary supervision" models.
- MATLAB simulations to analyze evolutionary stages and parameter sensitivity.
Main Results
- China's UCIP supervision is transitioning from "campaign-style" to "normalization."
- Optimal government supervision intensity is crucial; excessive or insufficient intensity is detrimental.
- Low participation from industry associations and users slows but doesn't reverse negative evolutionary trends.
Conclusions
- A moderate, normalized government supervision approach is key for effective UCIP governance.
- Sustained engagement from industry associations and platform users, coupled with strong penalties, accelerates the shift towards normalized supervision.
- The study offers a framework for designing improved UCIP supervision strategies.
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