Purpose Safety and productivity are key concerns in the construction projects. While safety looks to the construction workers need to work in a safe environment, productivity affects the project’s profitability and is of a paramount importance from the project owner’s view. The different perspective to the safety and productivity from these two major players in construction projects poses a potential for the conflict between the two. This problem can be fundamentally addressed by methods concurrently improving project safety and productivity. The paper aims to discuss this issue. Design/methodology/approach To this aim, a discrete event simulation (DES) based framework applicable was proposed for complex and hazardous operations. The utility of the framework was tested using a case study of an eight-story residential building in the north-east part of Tehran, Iran. The excavation and stabilization operation was identified as the most hazardous and critical operation in this case. The framework could improve safety and productivity of this operation by 38 and 4 percent, respectively. Findings This framework is a complement to the conventional construction project safety and productivity planning methods. Its main application is in complex and hazardous construction operations. Originality/value For the first time, a comprehensive framework for concurrently improving safety and productivity of an entire project was proposed in this research. DES was used as the main modeling tool in the framework to provide an ex-ante evaluation foundation applicable to a wide range of construction projects.
PurposeMotivated by the high cost of material movements in road construction projects, past studies have used analytical methods to optimize materials logistics plans. A key shortcoming of these methods is their inability to capture the uncertain, dynamic and complex characteristics of the road construction material logistics. Failure to incorporate these characteristics can lead to sub-optimal results. The purpose of this study is to propose the use of discrete event simulation (DES) to address the existing shortfall.Design/methodology/approachDespite the powerful capabilities of DES models in capturing the operational complexities of construction projects, they have not been previously utilized to optimize the material logistics of road construction projects. The proposed DES-based method in this research captures the operational details of material logistics and uses a heuristic approach to overcome the combinatorial problem of numerous choices. The method was applied to a 63.5 km real-world road construction project case to demonstrate its capabilities.FindingsSix different material types from 28 material sources were used in the case. Approximately 1.5% of the material logistics costs were saved by following the proposed method and choosing appropriate material sources.Originality/valueThis research contributes to the body of knowledge by leveraging the capabilities of DES and presenting a novel method for improving the materials logistics plan of road construction projects. The proposed method provides practitioners with the basis for capturing the key operational details that were overlooked in the past. The proposed method can be adopted in road construction projects to reduce the overall material procurement cost.
This paper proposes a model for a financial assessment of construction companies. This model is derived from the combination of data envelopment analysis (DEA), entropy method (EM), and TOPSIS. In the first step of the model, the financial ratios are calculated based on balance sheets and income statements. In the next step, the 15 ratios are categorized and classified utilizing a combination of TOPSIS and EM methods. Finally, they are aggregated in six indicators. Then, the BCC model of DEA with the type of output-oriented is used for these six indicators to calculate companies' relative efficiency. In the paper's conclusion, the model is examined in 20 construction companies that obtained analysis could have a high value for comparing the companies.
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