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Tripartite Evolutionary Game Analysis of Participants’ Behaviors in Technological Innovation of Mega Construction Projects under Risk Orientation

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 2, v. 13
Seite(n): 287
DOI: 10.3390/buildings13020287
Abstrakt:

Technological innovation of mega construction projects (MCPs) plays a crucial role in promoting upgrades to the construction industry. However, MCPs are complex and the transformation ratio of technological innovation achievements is generally low. To achieve the goal of technological innovation of MCPs which requires organizations from multiple fields to participate, it is critical to find the factors that influence cooperation and subsequently reduce the risk of technological innovation. Therefore, taking the risk as the guide of participants’ behaviors, this study constructs an evolutionary game model by tripartite participation: the owners or the representatives of the users who rely on the MCPs with technological innovation (the Users), the construction production enterprises (the CPEs), and the universities and the research institutes (the URIs). We derive the evolutionary stable strategy and apply matlab2020a for simulation analysis. The findings are as follows: (1) The strategy choice of the participant will be influenced by the strategy choices of other participants. (2) Collaborative cooperation for all parties is the evolutionary stable strategy. (3) The sensitivity of the participants to different parameters is different, and they are more sensitive to the perceived loss of technological innovation risk, risk-taking ratio, technological innovation investment, and cost compression coefficient. Based on the research results, the study provides effective suggestions for the Users and the government. The Users can quantify risk loss, refine risk management and establish collaborative cooperation evaluation indexes, and it is necessary for the government to encourage technological innovation of MCPs.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10712729
  • Veröffentlicht am:
    21.03.2023
  • Geändert am:
    10.05.2023
 
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