Dynamic Simulation of Enterprise-Level Strategic Choices in Intelligent Construction: Integration of Evolutionary Game Theory and System Dynamics

The decision-making regarding the development of intelligent construction in construction enterprises is crucial for the transformation and upgrading of the construction industry. This paper constructs an evolutionary game model among construction enterprises and applies system dynamics for simulation analysis of the game model. It explores the impact of key factors on the strategy choices of the game participants. The research findings indicate that the initial state of construction enterprises’ willingness to transition to intelligent construction in the evolutionary game model influences the final stable strategy. Direct benefits, the strength of government incentives, penalty intensity, and reduced costs through joint transition positively affect the probability of construction enterprises implementing intelligent construction, while incremental transition costs and positive spillover effect are negatively correlated. When the direct benefit rate exceeds 5%, costs are jointly reduced by more than 2%, and transition costs are below 35 CNY/m2, it can significantly motivate enterprises to adopt intelligent construction. A certain level of government incentives (at least greater than 5 CNY/m2) has a positive effect on the transformation process; however, once the incentives exceed 10 CNY/m2, their impact stabilizes. Penalties only affect the speed at which the system evolves toward a stable point. Current policy incentives do not require further enhancement. Meanwhile, reducing incremental transition costs is more effective than increasing the intensity of government incentives. The research conclusions contribute to the quantitative analysis of how changes in different key factors affect the dynamic evolution of strategy adjustments by construction enterprises over time, thereby providing corresponding recommendations for transformation and upgrading.

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Publication Details

Journal
Buildings
Published
2025-10-15
DOI
https://doi.org/10.3390/buildings15203719
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic Simulation of Enterprise-Level Strategic Choices in Intelligent Construction: Integration of Evolutionary Game Theory and System Dynamics

Youzhi Shi, Yingling Chen, Meichen Ding
Buildings
Advanced Research in Systems and Signal Processing
article

Dynamic Simulation of Enterprise-Level Strategic Choices in Intelligent Construction: Integration of Evolutionary Game Theory and System Dynamics

Youzhi Shi, Yingling Chen, Meichen Ding
article en

Abstract

The decision-making regarding the development of intelligent construction in construction enterprises is crucial for the transformation and upgrading of the construction industry. This paper constructs an evolutionary game model among construction enterprises and applies system dynamics for simulation analysis of the game model. It explores the impact of key factors on the strategy choices of the game participants. The research findings indicate that the initial state of construction enterprises’ willingness to transition to intelligent construction in the evolutionary game model influences the final stable strategy. Direct benefits, the strength of government incentives, penalty intensity, and reduced costs through joint transition positively affect the probability of construction enterprises implementing intelligent construction, while incremental transition costs and positive spillover effect are negatively correlated. When the direct benefit rate exceeds 5%, costs are jointly reduced by more than 2%, and transition costs are below 35 CNY/m2, it can significantly motivate enterprises to adopt intelligent construction. A certain level of government incentives (at least greater than 5 CNY/m2) has a positive effect on the transformation process; however, once the incentives exceed 10 CNY/m2, their impact stabilizes. Penalties only affect the speed at which the system evolves toward a stable point. Current policy incentives do not require further enhancement. Meanwhile, reducing incremental transition costs is more effective than increasing the intensity of government incentives. The research conclusions contribute to the quantitative analysis of how changes in different key factors affect the dynamic evolution of strategy adjustments by construction enterprises over time, thereby providing corresponding recommendations for transformation and upgrading.

BuildingsVol. 15(20)
Xiamen University (CN), Xiamen University of Technology (CN), Zhejiang University (CN)
Natural Science Foundation of Fujian Province, Xiamen University
Openalex Percentile: Top 62%
Advanced Research in Systems and Signal Processing
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