Analyzing green building project risk interdependencies using Interpretive Structural Modeling

JOURNAL OF CLEANER PRODUCTION

卷:256

Article

Guan, Li¹  Abbasi, Alireza¹  Ryan, Michael J.¹ 

[1] Univ New South Wales, Sch Engn & Informat Technol, POB 7916, Canberra, BC 2610, Australia

关键词: Green building projects;    Risk management;    Risk interdependencies;    Interpretive structural modeling (ISM);    Matrice d'Impacts Croises Multiplication Appliquee a un Classement (MICMAC) analysis;   

DOI  :  10.1016/j.jclepro.2020.120372

来源: Elsevier

【 摘 要 】

Green building (GB) projects have attracted wide attention in the construction industry in recent years owing to numerous benefits of green practices for sustainable development. However, existing research efforts on GB project risk management are very limited, and no prior in-depth research has focused on studying the risk interdependencies in GB projects from the perspectives of both the project life cycle and multiple project risks. This paper begins by identifying and distinguishing GB project constraints from multiple GB project risks using a systematic literature review and then investigates, based on the Interpretive Structural Modeling (ISM) method, the risk interdependencies taking into account the identified 16 constraint factors, 22 risk factors and 11 objectives throughout a GB project life cycle. The importance of constraints and risk factors associated with GB project objectives was calculated based on the influence transmission through network paths in the established ISM-based model. In addition, the Matrice d'Impacts Croises Multiplication Appliquee a un Classement (MICMAC) approach was used to analyze the drive and dependence powers of risk interdependency elements. Critical constraints and risk factors in the implementation of GB projects can be obtained from the proposed risk analysis model, which contributes to an in-depth risk perception of GB projects for industry practitioners and facilitates GB project risk management in a more effective way. (c) 2020 Elsevier Ltd. All rights reserved.

【 授权许可】

Free