Four-Way Evolutionary Game Analysis of Government Project Bidding Collusion in a State of Limited Rationality Based on Prospect Theory. (21st January 2022)
- Record Type:
- Journal Article
- Title:
- Four-Way Evolutionary Game Analysis of Government Project Bidding Collusion in a State of Limited Rationality Based on Prospect Theory. (21st January 2022)
- Main Title:
- Four-Way Evolutionary Game Analysis of Government Project Bidding Collusion in a State of Limited Rationality Based on Prospect Theory
- Authors:
- Ma, Chongsen
Chen, Yun
Nie, Sirui - Other Names:
- Fu Hanliang Academic Editor.
- Abstract:
- Abstract : Controlling collusion in government bidding is a prerequisite for ensuring social justice and the smooth operation of projects. Based on the prospect theory, this article establishes a four-party evolutionary game model for tenderers, enterprises with higher willingness to collude, enterprises with lower willingness to collude, and supervising enterprises. The study uses replication dynamics to analyze the stability of strategy selection after the evolutionary game. The results show that higher project base returns increase the probability of collusion, while lower market competition, higher risk aversion, and stronger collusive regulation all reduce the probability of collusion. When regulators adopt a strong regulatory strategy, the remaining project participants tend to choose a noncollusive strategy.
- Is Part Of:
- Computational intelligence and neuroscience. Volume 2022(2022)
- Journal:
- Computational intelligence and neuroscience
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-01-21
- Subjects:
- Neurosciences -- Data processing -- Periodicals
Computational intelligence -- Periodicals
Computational neuroscience -- Periodicals
612.80285 - Journal URLs:
- https://www.hindawi.com/journals/cin/ ↗
- DOI:
- 10.1155/2022/6092802 ↗
- Languages:
- English
- ISSNs:
- 1687-5265
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 20784.xml