Tripartite Evolutionary Game Analysis on the Employment of University Graduates from the Perspective of the Talent Supply Chain Based on Prospect Theory

From the perspective of the talent supply chain, this paper employs evolutionary game theory to study the decision-making behaviors of university graduates’ employment-related participants, establishes a tripartite evolutionary game model of enterprises, graduates, and universities based on prospect theory, and analyzes the main factors affecting the system game strategy by combining numerical simulation. The evolutionary game theory is a theory that integrates game theory with the analysis of dynamic evolutionary processes, studying the strategy selection and dynamic equilibrium of bounded rational participants in complex environments. The findings are as follows: (1) The decision-makers influence and promote each other, and universities play a very important role in promoting the employment of graduates. (2) In the case of random initial probability, when the additional profit of each decision-maker is greater than their cost, enterprises, graduates, and universities can realize the ideal model of “recruitment, participation in recruitment, active employment assistance”. The higher the initial probability, the faster the system reaches a steady state. (3) Enhancing the risk perception of enterprises, graduates, and universities has a dual effect on the employment ecosystem. (4) The behavioral strategies of enterprises, graduates, and universities are affected by many factors, such as the initial probability, loss aversion degree, profit and loss sensitivity degree, talent loss risk, cost, and unemployment risk.

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Publication Details

Journal
Systems
Published
2025-03-16
DOI
https://doi.org/10.3390/systems13030205
Citations
1
Primary Topic
Human Resource and Talent Management
Type
article
Field-Weighted Citation Impact
2.76
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article

Tripartite Evolutionary Game Analysis on the Employment of University Graduates from the Perspective of the Talent Supply Chain Based on Prospect Theory

Ling-Wei Fan, Kuo Lung Lian, Chuan Zhang, Jingjing Chen
1 citations
Systems
Human Resource and Talent Management
2.76
article

Tripartite Evolutionary Game Analysis on the Employment of University Graduates from the Perspective of the Talent Supply Chain Based on Prospect Theory

Ling-Wei Fan, Kuo Lung Lian, Chuan Zhang, Jingjing Chen
article en
1 citations

Abstract

From the perspective of the talent supply chain, this paper employs evolutionary game theory to study the decision-making behaviors of university graduates’ employment-related participants, establishes a tripartite evolutionary game model of enterprises, graduates, and universities based on prospect theory, and analyzes the main factors affecting the system game strategy by combining numerical simulation. The evolutionary game theory is a theory that integrates game theory with the analysis of dynamic evolutionary processes, studying the strategy selection and dynamic equilibrium of bounded rational participants in complex environments. The findings are as follows: (1) The decision-makers influence and promote each other, and universities play a very important role in promoting the employment of graduates. (2) In the case of random initial probability, when the additional profit of each decision-maker is greater than their cost, enterprises, graduates, and universities can realize the ideal model of “recruitment, participation in recruitment, active employment assistance”. The higher the initial probability, the faster the system reaches a steady state. (3) Enhancing the risk perception of enterprises, graduates, and universities has a dual effect on the employment ecosystem. (4) The behavioral strategies of enterprises, graduates, and universities are affected by many factors, such as the initial probability, loss aversion degree, profit and loss sensitivity degree, talent loss risk, cost, and unemployment risk.

SystemsVol. 13(3)
Northeastern University (CN)
Openalex Percentile: Top 12%
Human Resource and Talent Management
2.76
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