Developing a Model to Estimate Cost of Construction Projects based on Target Costing Approach | ||||
Engineering Research Journal (Shoubra) | ||||
Volume 52, Issue 2, April 2023, Page 137-143 PDF (985.9 K) | ||||
Document Type: Research articles | ||||
DOI: 10.21608/erjsh.2023.175875.1113 | ||||
View on SCiNiTO | ||||
Authors | ||||
Asmaa Saad Alqhisan ; Muhammad Abdel-Monem; KARIM ELDASH | ||||
Civil Engineering Department, Faculty of Engineering at Shobra, Benha University, Cairo, Egypt | ||||
Abstract | ||||
The targeted value design methodology is the most common expression of Target Costing (TC) in the construction industry (design, construction, and delivery stages). It is recognized as an effective tool for reducing costs and managing overruns. However, the correct application of target value design in construction projects is highly dependent on the experience of the estimator. A reliable service provider (i.e., a practitioner) who typically uses objective design relies on subjective, empirical judgments and rules of thumb to propose design solutions that meet stakeholder needs. Lack of a reliable service provider therefore prevents realization of the potential benefits of applying targeted designs. The main objectives of this study is to identify the natural costing, the limitations, and the key development areas of traditional Target Cost. Then solve the cost-focused natural costing of traditional Target Cost (TC). It is done through cost-based performance process that integrates interactions between components of a construction project. It is carried out through a set of cost factors and standardized mathematical modeling achieved. Using optimized modeling techniques is developed in an appropriate programming environment. The proposed model is developed using the MATLAB application. The model represents different operating expenses categories and graphically represents all operating cost. The model optimizes the results of each type of cost so as it shows the target cost distribution and the direct cost distribution to differentiate between them. | ||||
Keywords | ||||
questionnaire survey; analysis; decision tree; production | ||||
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