Study on the Technological Innovation Supply–Demand Matching Mechanism for Major Railway Projects Based on a Tripartite Evolutionary Game
Abstract
:1. Introduction
2. Literature Review
2.1. Research on Technological Innovation in Major Infrastructure Projects
2.2. Research on Supply–Demand Matching
3. Materials and Methods
3.1. Connotations of Technological Innovation Supply–Demand Matching Mechanisms
3.2. Key Stakeholders and Behavioral Analysis in Technological Innovation Supply–Demand Matching Mechanisms
3.3. Tripartite Game Model Construction for Technological Innovation Supply–Demand Matching Mechanisms
3.3.1. Basic Assumptions and Parameter Settings of Evolutionary Game
3.3.2. Evolutionary Game Payoff Matrix
3.3.3. Replicator Dynamics Equation
4. Results
4.1. The Stability Analysis of Key Entities
4.1.1. Stability Analysis of Governance Entities
4.1.2. Stability Analysis of Collaborative Innovation Platforms
4.1.3. Stability Analysis of Demand-Side Entities
4.2. Stability Analysis of the Technological Innovation Supply–Demand Matching Mechanism
5. Discussions
5.1. The Impact of Key Entities’ Initial Willingness on Mechanism Evolution
5.2. Tripartite Game Parameter Sensitivity Analysis
5.3. Comparative Sensitivity Analysis of Key Agents’ Game-Theoretic Parameters
6. Conclusions and Recommendations
6.1. Conclusions
6.2. Research Implications
6.3. Limitations and Future Research Directions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameter | Parameter Description |
---|---|
denotes governance entities’ payoff under a high-involvement strategy, with payoff normalized to 0 under a low involvement strategy (where > ). | |
represents governance entities′ administrative costs under a high-involvement strategy, with administrative costs normalized to 0 under a low-involvement strategy (where > ). | |
When both collaborative innovation platforms and demand-side entities adopt active matching strategies, high congruence between research demand and supply enables successful technological iteration/leapfrogging, generating social benefit | |
The negative societal externality arising when both the collaborative innovation platform and demand-side entities adopt passive supply–demand matching strategies. | |
signifies demand-side entities’ matching effort coefficient, where higher values indicate more frequent collaborative/sharing behaviors during matching processes (baseline = 1). | |
represents collaborative innovation platforms’ matching effort coefficient, where higher values correspond to intensified coordination/sharing engagements (baseline = 1). | |
Asymmetric active/passive matching exposes unilateral active participants to innovation risks from low congruence between research demand and supply, with denoting demand-side entities’ risk coefficient. | |
Asymmetric active/passive matching exposes unilateral active participants to innovation risks from low congruence between research demand and supply, with denoting collaborative innovation platform’ risk coefficient. | |
Under the high-involvement strategy, governance entities provide demand-side entities adopting active matching with subsidy to enhance technological innovation supply–demand alignment in mega-railway projects. | |
Under the high-involvement strategy, governance entities provide subsidies to collaborative innovation platforms employing active matching strategies, thereby enhancing technological innovation supply–demand coordination in major railway engineering projects. | |
Under a high-involvement strategy, governance entities impose a penalty on passive matching actors, with the constraint ensuring incentive compatibility. | |
denotes demand-side entities’ baseline payoff. | |
represents demand-side entities’ baseline participation costs in research alignment activities. | |
When both collaborative innovation platforms and demand-side entities adopt active matching strategies, demand-side entities obtain additional economic benefits because of technological problem resolution. | |
During technological innovation supply–demand matching processes, unilateral active matching by demand-side entities incurs extra technological innovation risk costs quantified as |
Collaborative Innovation Platforms | |||||
---|---|---|---|---|---|
Active Matching | Passive Matching | ||||
Demand-Side Entities | |||||
Active | Passive | Active | Passive | ||
Governance entities | high | (high, active, active) | (high, active, passive) | (high, passive, active) | (high, passive, passive) |
low | (low, active, active) | (low, active, passive) | (low, passive, active) | (low, passive, passive) |
Strategy | Governance Entities | Collaborative Innovation Platforms | Demand-Side Entities |
---|---|---|---|
0 | |||
0 | |||
Equilibrium Points | Eigenvalues | Sign of the Real Part | ||
---|---|---|---|---|
Equilibrium Points | Stability Conditions |
---|---|
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Zhao, X.; Liu, Y.; Lang, X. Study on the Technological Innovation Supply–Demand Matching Mechanism for Major Railway Projects Based on a Tripartite Evolutionary Game. Systems 2025, 13, 434. https://doi.org/10.3390/systems13060434
Zhao X, Liu Y, Lang X. Study on the Technological Innovation Supply–Demand Matching Mechanism for Major Railway Projects Based on a Tripartite Evolutionary Game. Systems. 2025; 13(6):434. https://doi.org/10.3390/systems13060434
Chicago/Turabian StyleZhao, Xi, Yuming Liu, and Xianyi Lang. 2025. "Study on the Technological Innovation Supply–Demand Matching Mechanism for Major Railway Projects Based on a Tripartite Evolutionary Game" Systems 13, no. 6: 434. https://doi.org/10.3390/systems13060434
APA StyleZhao, X., Liu, Y., & Lang, X. (2025). Study on the Technological Innovation Supply–Demand Matching Mechanism for Major Railway Projects Based on a Tripartite Evolutionary Game. Systems, 13(6), 434. https://doi.org/10.3390/systems13060434