{"title":"Deconstructing synergistic carbon reduction mechanisms in large-scale construction governance: A Monte Carlo simulation based on a cross-scale model","authors":"Zhizhe Zheng , Yikun Su , Junhao Liu","doi":"10.1016/j.asej.2025.103513","DOIUrl":null,"url":null,"abstract":"<div><div>This study develops a cross-scale collaborative optimization model to explore synergistic carbon emission reduction (SCER) mechanisms in governance networks for large-scale construction projects. Monte Carlo simulations validate the model and provide actionable guidance. Key results indicate optimal cost-effectiveness ratios for additional capability deployment between [0.439, 1.371], and policy leverage ratios between [0.425, 1.097]. Contractual governance emerges as pivotal, with value allocation ratios between general contractors and engineering commands ranging from 0.415 to 0.590, and between general contractors and subcontractors from 0.349 to 0.661. Relational governance, in contrast, shows weaker, nonlinear effects. The engineering commands excessive intervention slightly inhibited SCER during project execution. This study advances low-carbon construction governance by providing a quantitative framework for balancing cost, value distribution, and policy support.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103513"},"PeriodicalIF":5.9000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2090447925002540","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This study develops a cross-scale collaborative optimization model to explore synergistic carbon emission reduction (SCER) mechanisms in governance networks for large-scale construction projects. Monte Carlo simulations validate the model and provide actionable guidance. Key results indicate optimal cost-effectiveness ratios for additional capability deployment between [0.439, 1.371], and policy leverage ratios between [0.425, 1.097]. Contractual governance emerges as pivotal, with value allocation ratios between general contractors and engineering commands ranging from 0.415 to 0.590, and between general contractors and subcontractors from 0.349 to 0.661. Relational governance, in contrast, shows weaker, nonlinear effects. The engineering commands excessive intervention slightly inhibited SCER during project execution. This study advances low-carbon construction governance by providing a quantitative framework for balancing cost, value distribution, and policy support.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.