Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective

Green construction in infrastructure projects has emerged as a crucial approach for reducing environmental impacts, yet its implementation is fraught with numerous uncertainties. To assess the capacity to maintain and restore green construction performance in complex environments, this study propose...

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Main Authors: Yikun Su, Junhao Liu, Zhizhe Zheng
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Buildings
Subjects:
Online Access:https://www.mdpi.com/2075-5309/15/15/2594
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author Yikun Su
Junhao Liu
Zhizhe Zheng
author_facet Yikun Su
Junhao Liu
Zhizhe Zheng
author_sort Yikun Su
collection DOAJ
description Green construction in infrastructure projects has emerged as a crucial approach for reducing environmental impacts, yet its implementation is fraught with numerous uncertainties. To assess the capacity to maintain and restore green construction performance in complex environments, this study proposes the concept of Green Construction Performance Resilience (GCPR) for infrastructure projects and develops methodologies for its management and optimization. This study constructs a project network based on the labeled property graph (LPG) technique and demonstrates its dynamic evolution throughout the entire project lifecycle. A series of indicators for quantifying GCPR are constructed and applied, enabling the quantification of green construction performance resilience in infrastructure projects. An optimization method for GCPR based on genetic algorithms is proposed. Finally, the applicability and effectiveness of the proposed methodologies are validated through the analysis of real-world infrastructure project cases. The results demonstrate that the project network model can comprehensively capture the complexity of large-scale infrastructure projects, and that the GCPR indicators effectively measure green construction performance resilience, providing valuable decision-making support for project managers. The optimization algorithm has been validated and shown to improve the GCPR level of the project. This study enriches interdisciplinary research on project resilience and project complexity theory and provides project managers with quantitative analysis and visualization tools to facilitate the attainment of green construction performance objectives in infrastructure projects and accelerate the transition towards low-carbon practices.
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spelling doaj-art-a55006d0e56840e187243bb5cdfe4dd22025-08-20T03:36:39ZengMDPI AGBuildings2075-53092025-07-011515259410.3390/buildings15152594Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity PerspectiveYikun Su0Junhao Liu1Zhizhe Zheng2School of Civil Engineering and Transportation, Northeast Forestry University, 26 He Xing Road, Harbin 150040, ChinaSchool of Civil Engineering and Transportation, Northeast Forestry University, 26 He Xing Road, Harbin 150040, ChinaSchool of Energy and Civil Engineering, Harbin University of Commerce, National Center of Technology Innovation for Green and Low-Carbon Building, 1st XueHai Street, Harbin 150028, ChinaGreen construction in infrastructure projects has emerged as a crucial approach for reducing environmental impacts, yet its implementation is fraught with numerous uncertainties. To assess the capacity to maintain and restore green construction performance in complex environments, this study proposes the concept of Green Construction Performance Resilience (GCPR) for infrastructure projects and develops methodologies for its management and optimization. This study constructs a project network based on the labeled property graph (LPG) technique and demonstrates its dynamic evolution throughout the entire project lifecycle. A series of indicators for quantifying GCPR are constructed and applied, enabling the quantification of green construction performance resilience in infrastructure projects. An optimization method for GCPR based on genetic algorithms is proposed. Finally, the applicability and effectiveness of the proposed methodologies are validated through the analysis of real-world infrastructure project cases. The results demonstrate that the project network model can comprehensively capture the complexity of large-scale infrastructure projects, and that the GCPR indicators effectively measure green construction performance resilience, providing valuable decision-making support for project managers. The optimization algorithm has been validated and shown to improve the GCPR level of the project. This study enriches interdisciplinary research on project resilience and project complexity theory and provides project managers with quantitative analysis and visualization tools to facilitate the attainment of green construction performance objectives in infrastructure projects and accelerate the transition towards low-carbon practices.https://www.mdpi.com/2075-5309/15/15/2594infrastructuregreen construction performanceresilienceproject complexity
spellingShingle Yikun Su
Junhao Liu
Zhizhe Zheng
Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective
Buildings
infrastructure
green construction performance
resilience
project complexity
title Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective
title_full Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective
title_fullStr Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective
title_full_unstemmed Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective
title_short Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective
title_sort enhancing the green construction performance resilience in infrastructure projects a complexity perspective
topic infrastructure
green construction performance
resilience
project complexity
url https://www.mdpi.com/2075-5309/15/15/2594
work_keys_str_mv AT yikunsu enhancingthegreenconstructionperformanceresilienceininfrastructureprojectsacomplexityperspective
AT junhaoliu enhancingthegreenconstructionperformanceresilienceininfrastructureprojectsacomplexityperspective
AT zhizhezheng enhancingthegreenconstructionperformanceresilienceininfrastructureprojectsacomplexityperspective