Abstract
Smart construction sites (SCSs) haven’t been widely and effectively implemented given the interest conflicts of multi-stakeholders. The purpose is to explore the governance mechanism of SCSs under multi-stakeholder interactions to provide countermeasures for promoting SCSs. Speculative punishment and reputational incentives were creatively introduced to discuss their influences on the behaviors of SCS stakeholder, and the synergy of the government and the market mechanism in the SCS development is discussed. First, a four-subject evolutionary game model including the government, project owners, contractors and technology providers was established. Second, the governance processes of SCSs were analyzed according to evolutionary stable strategies (ESSs). Finally, the influences of parameter variations on players’ strategies were illustrated by numerical simulations and further proposed the governance mechanism of SCSs. This study presents some findings: (1) Project owners are more sensitive to the government’s incentives than other stakeholders. And the increased cooperation benefits for project owners and contractors are beneficial for the SCS development, while the externalities of SCSs easily result in project owners’ free riding. (2) Speculative punishment improves the implementation effectiveness but hinders the adoption of SCSs. Reputational incentives and losses are beneficial for increasing stakeholders’ enthusiasm. (3) The governance processes of SCSs are divided into four stages where the government and the market mechanism play different roles. Policy recommendations for the government and strategic references for enterprises are offered based on research findings.
| Original language | English |
|---|---|
| Journal | International Journal of General Systems |
| DOIs | |
| Publication status | Published - 27 Nov 2025 |
Keywords
- evolutionary game
- governance mechanism
- multi-stakeholder
- Smart construction site
ASJC Scopus subject areas
- Control and Systems Engineering
- Theoretical Computer Science
- Information Systems
- Modelling and Simulation
- Computer Science Applications
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