Major Factors Affecting Construction Waste Management in Infrastructure Projects Using Structural Equation Model
Author | Naji, Khalid K. |
Author | Gunduz, Murat |
Author | Hamaidi, Munther Farouq |
Available date | 2023-12-03T10:46:03Z |
Publication Date | 2022-07-20 |
Publication Name | Journal of Construction Engineering and Management |
Identifier | http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0002358 |
Citation | Naji, K. K., Gunduz, M., & Hamaidi, M. F. (2022). Major factors affecting construction waste management in infrastructure projects using structural equation model. Journal of Construction Engineering and Management, 148(10), 04022101. |
ISSN | 0733-9364 |
Abstract | The construction industry has grown significantly to fulfill the expanding need for accommodation, facilities, welfare, and services resulting from the rapid increase in the global population. Infrastructure projects in particular facilitate transportation and services for both new and existing areas, yet they are also one of the primary producers of construction waste, which is harmful to both society and the environment. Hence, the objective of this paper is to identify the factors affecting construction waste management in infrastructure projects (CWMIIP) and study their respective impacts on construction waste management (CWM) performance. This study makes a unique contribution by not only addressing the factors that influence the development of construction wastes and their importance, but also by giving quantifiable solutions and action plans to reduce the waste. Using a literature review, 26 factors were selected as the major contributors to construction waste in infrastructure projects. An online questionnaire was then developed to collect data on the respective impacts of these factors. A total of 167 complete responses to the questionnaire were collected, and a structural equation model (SEM) was developed to quantitatively measure the impact of each factor on waste management performance. The model was validated using goodness of fit (GOF), multivariate normality, construct validity, reliability, and hypotheses analyses. The results indicate that the most significant factors affecting the generation of construction wastes are "quantity take-off error by contractor,""unforeseen incidents damaging site and/or completed works,""design errors,"and "extreme weather conditions damaging completed works."The model results showed that all predefined hypotheses were supported, except for the positive effect of the logistics group, which was dropped during model development. Individual factors were also divided into groups, and the total impact of each group was assessed; the "management"group had the greatest impact, followed by "execution,""others,"and "procurement."Based on these findings, we make several recommendations to construction industry professionals to reduce waste and mitigate its harmful effects, such as requiring a construction waste management implementation plan before awarding a project to a contractor; engaging with project suppliers to provide execution training for contractor staff; ensuring proper implementation of health, safety, and environmental plans; and purchasing locally available materials. Practical Applications This research built a model based on structural equation modeling that will help researchers better understand the links between building waste management parameters. To examine the impact of each waste component on construction waste management performance, a quantitative model is built based on the data obtained. This quantitative waste management model could be used to track construction waste management performance. The findings of this study are not limited to infrastructure projects because they may be tailored to fit any project. As a result, it is recommended that project contractors and supervision consultants rely on the factors responsible for construction waste generation identified in this study to capture their actual construction waste factors. Also, having a record and log of all construction wastes generated during a project, as well as the reasons for these wastes, would help the organization improve its waste management learning curve for future projects. |
Language | en |
Publisher | American Society of Civil Engineers |
Subject | Confirmatory factor analysis Construction waste management (CWM) Critical success factors (CSF) Importance index Infrastructure Key performance indicators Lean Productivity Rework Structural equation modeling (SEM) Sustainability |
Type | Article |
Issue Number | 10 |
Volume Number | 148 |
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Civil & Architectural Engineering [774 items ]