A Modeling Approach to Construction Waste Management

Kolaventi, Swarna Swetha; Tezeswi, T. P.; Kumar, M. Vijaya

doi:10.1061/9780784482032.002

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…PLS-SEM is mainly used to confirm the reliability of the sample data from two aspects: firstly, it is the indicator reliability, which is evaluated by the Factor Loading; second, it is the internal consistency of the indicator data, which is mainly measured by the compositional reliability 41,42 and Cronbach's alpha (CA). The validity analysis mainly includes convergent validity and discriminant validity analysis, and the convergent validity of the model can be estimated by calculating the average variance extracted (AVE) 12 value.…”

Section: The Measurement Modelmentioning

confidence: 99%

“…Collected data were analyzed to test whether there were differences in recordable incident rates and lost time work rates between green and nongreen projects. In addition, Olanipekun and coworkers [9][10][11][12][13] conducted analyses of key factors of project management environmental performances from a perspective of construction engineering firms and identified 19 controllable project management factors from relevant literature.…”

Section: Introductionmentioning

confidence: 99%

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Does self‐face awareness influence green building project performance?—An empirical evidence from China

Xie

Chen

Wang

et al. 2023

Energy Science & Engineering

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In the circumstances of "Carbon Peak," it is imminent to implement green construction technology in the construction industry as it is a major source of CO 2 emissions. Nevertheless, little study has been done on the impact of selfface awareness (SA) on green building project performance (GP). On the basis of a large-scale questionnaire survey in China and an in-depth analysis of the four categories (cognition, behavior, satisfaction, and performance), this paper has added an SA dimension, and proposed a new impacting path. Then, based on the improved conceptual model for measuring the impact of green construction behavior on GP, this paper has conducted empirical tests by using a large sample of questionnaire data and partial least square-structural equation modeling method. The results show that: (1) green construction behavior has a positive impact on GP, and the impact of perceived behavioral control of green construction technology is most significant for promoting green construction in the industry, and SA has a significant positive effect on green construction in the industry; (2) environmental perception and perceived behavioral control for green construction technology play a mediating role; and (3) significant differences indeed exist in the multigroup analysis, and the biggest difference is working experiences in the engineering field. Finally, this paper has proposed corresponding management implications based on the above findings. The main contribution of this study is that this study has developed a new dimension (SA) to the model considering Chinese national and cultural differences, in an attempt to reveal the impact of green construction technology on GP in the Chinese context. In addition, the promotion of green construction (PGC) in the construction industry was also added based on the sustainability perspective, which is the first attempt to explore the role of the PGC.

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Section: The Measurement Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Does self‐face awareness influence green building project performance?—An empirical evidence from China

Xie

Chen

Wang

et al. 2023

Energy Science & Engineering

View full text Add to dashboard Cite

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“…It is found that management showed less interest about waste minimization compared to the construction workforce (Lingard et al, 2000), and architects are not aware of either waste minimization or design waste (Osmani et al, 2008). Modeling of factors effecting construction waste by means of structural equation modeling is used to assess direct and indirect relationships between variables (Kolaventiet et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

An assessment of construction waste management in India: A statistical approach

2019

Self Cite

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Construction waste needs to be managed in order to minimize environmental burden in India and conserve existing natural resources. Despite numerous policies and guidelines there is improper construction waste management. Towards addressing this issue, a novel approach is presented to unraval and investigate waste management in India using four methods: quantification of waste by wastivity; grouping of influence factors (IFs) by factor analysis; ranking of IFs by analogous importance index; and determination of attitude by concordance among construction crew. The outcomes forecast wastivity of concrete (4.14%) and steel (1.62%), respectively. Exploratory factor analysis groups factors into five categories. The top influence factor (CMT6, 0.901) according to contractors and academicians is: workers should be given training in identifying recyclable material. Engineers favor enforcement of strict punishment for illegal disposal of wastes in violation of Environmental Protection Agency regulations (CMT7, 0.895). Computed concordance indicates: moderate agreement (0.68) among variables under the construction method; strong agreement among variables in documentation (0.76) and construction equipment (0.81); and very strong agreement among variables in worker intention (1.00) and materials (1.00). The variation in attitude of the workforce towards waste management and the proclivity of policy developers towards protocols which include training of workers in efficient waste management are quantified.

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A Case Study on Estimation and Composition of Construction and Demolition Waste in Bengaluru

Abhishek

Joshi

2021

Lecture Notes in Civil Engineering

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A Modeling Approach to Construction Waste Management

Cited by 8 publications

References 10 publications

Does self‐face awareness influence green building project performance?—An empirical evidence from China

Does self‐face awareness influence green building project performance?—An empirical evidence from China

An assessment of construction waste management in India: A statistical approach

A Case Study on Estimation and Composition of Construction and Demolition Waste in Bengaluru

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