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Non-renewable resources have been becoming scarcer on a global scale by the day, while energy demand has been rising exponentially. To tackle this problem, organizations worldwide have been striving to learn and adopt green practices to sustain themselves and benefit society. In this context, the current study aims to identify and understand the critical factors that encourage individuals working in construction organizations to adopt green behavior. The current study surveyed 121 top managers working in 150 construction firms deployed across Pakistan. It was found that knowledge and awareness significantly contributed to green behavioral adoption. Additionally, behavioral intention, motivation, and environmental consciousness have been found to positively mediate the impact of knowledge and awareness on green behavior adoption. The findings of this study highlight the important factors to consider when developing future policies. Moreover, the research provides a stepping stone for future researchers to evaluate other sectors and regions in similar contexts to draw comparisons and identify areas for improvement.

Scheduling of the rehabilitation activities of water main networks depends mainly on available budget and planning time. Other factors such as network reliability, criticality, location, contract size, and rehabilitation method(s) affect the optimization of the scheduling process. This paper presents a method for optimized scheduling of rehabilitation work for water distribution networks. The method utilizes unsupervised neural networks (UNNs) and mixed-integer nonlinear programming (MINLP) and performs the scheduling in two stages. In the first stage, UNNs are used to cluster water mains into groups according to locations and rehabilitation methods of water mains. In the second stage, MINLP is used to determine the number of rehabilitation contract packages and the generation of optimized scheduling of these packages considering network reliability, criticality, contract size, and planning time. In order to demonstrate the essential features of the developed method, a case study was analyzed and ...

Canadian municipalities have noted that 59% of their water systems and 68% of their sewer systems required repair. To rehabilitate, replace or construct a water or sewer pipeline, several methods can be used: open-cut or one of several trenchless technologies (TTs). The selection of the method positively affects the surrounding environment. Therefore, the impact on environment (IoE) becomes a vital concern in selecting the appropriate construction or rehabilitation method for water or sewer pipelines. The research presented in this paper aims at developing an IoE model that compares the open-cut and TT methods. The IoE factors and their related data are collected, analysed and categorised based on literature review and expert opinion. Two models are designed in order to assess the IoE of the open-cut and TT methods. Results of the open-cut technique show that the impact on social factor has the maximum relative weight of 0.36; however, the impact on project characteristics has 0.33 and on environment has ...