Revisiting storey enclosure method for early estimation of structural building construction cost
Author(s): |
Chau Ngoc Dang
Long Le-Hoai |
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Medium: | journal article |
Language(s): | English |
Published in: | Engineering, Construction and Architectural Management, August 2018, n. 7, v. 25 |
Page(s): | 877-895 |
DOI: | 10.1108/ecam-07-2015-0111 |
Abstract: |
PurposeThe purpose of this paper is to develop several predictive models for estimating the structural construction cost and establish range estimation for the structural construction cost using design information available in early stages of residential building projects. Design/methodology/approachInformation about residential building projects is collected based on project documents from construction companies with regard to the design parameters and the actual structural construction costs at completion. Storey enclosure method (SEM) is fundamental for determining the building design parameters, forming the potential variables and developing the cost estimation models using regression analysis. Nonparametric bootstrap method is used to establish range estimation for the structural construction cost. FindingsA model which is developed from an integration of advanced SEM, principle component analysis and regression analysis is robust in terms of predictability. In terms of range estimation, cumulative probability-based range estimates and confidence intervals are established. While cumulative probability-based range estimates provide information about the level of uncertainty included in the estimate, confidence intervals provide information about the variability of the estimate. Such information could be very crucial for management decisions in early stages of residential building projects. Originality/valueThis study could provide practitioners with a better understanding of the uncertainty and variability included in the cost estimate. Hence, they could make effective improvements on cost-related management approaches to enhance project cost performance. |
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data sheet - Reference-ID
10576659 - Published on:
26/02/2021 - Last updated on:
26/02/2021