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Estimation of ideal construction duration in tender preparation stage for housing projects

Open Access
|Nov 2023

Abstract

Despite the potential of various methods for calculating construction duration, few studies have focused on the application of these methods in the tender preparation stage, and even fewer have focused on their application in public housing projects. Moreover, research related to construction duration in Turkey has indicated that considerable delays occur in public housing projects. Therefore, we investigated the factors affecting the construction duration of housing projects and developed a novel calculation method for estimating the ideal construction duration. Data on public housing projects were obtained from a major Turkish construction authority. Statistical data analysis was performed using multiple linear regression analysis, chi-squared automatic interaction detection (CHAID), and classification and regression tree (CART) methods. The results revealed that several factors significantly affected the ideal construction duration for each statistical method. The cutoffs and standard errors were calculated to test the validity of all three statistical methods. The regression formula indicated statistical significance when the calculation method was tested. The implementation of the methods for other public housing projects significantly reduced the number of delayed projects. The findings of this study are expected to contribute by way of enabling senior project managers to estimate the ideal construction duration for housing projects during the tender preparation stage.

DOI: https://doi.org/10.2478/otmcj-2023-0014 | Journal eISSN: 1847-6228 | Journal ISSN: 1847-5450
Language: English
Page range: 192 - 212
Submitted on: Jan 1, 2023
Accepted on: May 23, 2023
Published on: Nov 25, 2023
Published by: University of Zagreb
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Hakan Tirataci, Hakan Yaman, published by University of Zagreb
This work is licensed under the Creative Commons Attribution 4.0 License.