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Construction time prediction model for public building projects

Shambel Kifle Alemu (Faculty of Civil Engineering, Arba Minch Institute of Technology, Arba Minch University, Arba Minch, Ethiopia)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 2 June 2021

Issue publication date: 31 May 2022

490

Abstract

Purpose

The aim of the study was to develop a practical construction time model for public building projects in Addis Ababa, Ethiopia.

Design/methodology/approach

This research work used regression analysis and also exploratory scatter and residual plot techniques. Simple and multiple regressions were used for the investigation of the best fit time model. The analyses were carried out using IBM SPSS statistical software, version 20.

Findings

The result revealed that the Bromilow time-cost principle was moderately applicable. However, the cubic regression model (CUB) was found a better time-cost relationship. On the contrary, the study has shown a poor relationship between actual time and gross floor area. Furthermore, multiple linear regression analysis (MLR) consists of three statistically significant variables were found a better fit time model.

Research limitations/implications

The study is limited to only six project scope factors. Further research is recommended to include more building projects of similar type and implications of other factors to improve the reliability of the models.

Practical implications

The developed model was not intended as a replacement for detailed construction scheduling techniques. The resulting model is applicable for front-end predictions of construction duration.

Originality/value

The main parties involved in the building projects should apply the model for benchmarking a precise construction time during the early planning phase.

Keywords

Citation

Alemu, S.K. (2022), "Construction time prediction model for public building projects", Engineering, Construction and Architectural Management, Vol. 29 No. 5, pp. 2183-2206. https://doi.org/10.1108/ECAM-11-2020-0975

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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