Determinants of construction duration for building projects in Germany

Dursun, Onur; Stoy, Christian

doi:10.1108/09699981211237139

Cited by 23 publications

(12 citation statements)

References 19 publications

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“…According to Dursun and Stoy (2012), the most reported determinant of construction duration in the literature is the cost of the project. This is largely due to the linkage of project cost to other determinants such as nature of construction site, number of levels, types of building projects and market condition.…”

Section: Discussionmentioning

confidence: 99%

Construction Duration Determinants of Building Projects in Sarawak

2019

BJSSH

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This research utilized the quantitative method and stratified simple random sampling technique to collect data with a view to investigating the determinants of construction duration of building projects in Sarawak. Out of the 180 copies of questionnaire distributed to grade 4, 5, 6 and 7 contractors operating within Bintulu and Sibu in Sarawak, only 36 copies were duly completed, making the valid response rate to be 20 percent. Descriptive analysis and Relative Importance Index (RII) were utilized in analysing the data. The descriptive analysis revealed that availability of construction site, type of building constructed and market condition are the important determinants of construction duration. The result of relative importance index revealed that the availability of construction site is the highest determinant. This study has complemented the existing knowledge on the determinants of construction duration.

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Section: Discussionmentioning

confidence: 99%

Construction Duration Determinants of Building Projects in Sarawak

2019

BJSSH

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“…This was done to eliminate the effect of time and value on the various projects in a similar manner as in Dursun and Stoy (2012).…”

Section: Construction Time Overrunsmentioning

confidence: 99%

Assessing the predictability of construction time overruns using multiple linear regression and Markov chain Monte Carlo

Asiedu

Gyadu-Asiedu

2019

JEDT

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Purpose This paper aims to focus on developing a baseline model for time overrun. Design/methodology/approach Information on 321 completed construction projects used to assess the predictive performance of two statistical techniques, namely, multiple regression and the Bayesian approach. Findings The eventual results from the Bayesian Markov chain Monte Carlo model were observed to improve the predictive ability of the model compared with multiple linear regression. Besides the unique nuances peculiar with projects executed, the scope factors initial duration, gross floor area and number of storeys have been observed to be stable predictors of time overrun. Originality/value This current model contributes to improving the reliability of predicting time overruns.

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“…of stories above ground, no. of stories below ground, building coverage ratio, and construction region Dursun and Stoy (2012) 1695 Not Applicable All Gross floor area, construction cost, type of building, location, availability of building area, and market conditions Jarkas (2015) 187 Applicable Residential/Business Facility No. of stories above ground, no.…”

Section: No Of Data Casesmentioning

confidence: 99%

Development of construction duration prediction model for project planning phase of mixed-use buildings

Kim

Yeom

Kim

2019

Journal of Asian Architecture and Building Engineering

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The nature of the mixed-use building's characteristics should be considered to calculate a proper construction duration for mixed-use buildings in the project planning phase. However, the existing construction duration prediction models are incapable to reflect nature as they were developed mainly for single-use buildings. Therefore, the purpose of this study was to suggest a multiple linear regression model for mixed-use buildings that can help the owner and contractor predict a proper construction duration in the project planning phase. To do so, 1,969 mixeduse building project data were collected. The final prediction model for mixed-use buildings with five independent variables was suggested in this study. Its R2 was 0.637 and Ra2 was 0.635. In addition, the results of the validation showed that the prediction model's average prediction accuracy, MAPE, and RMSE were 88.51%, 75.94, and 11.49% respectively. Given that the prediction model is applied in the project planning phase when there is insufficient information on the project, the results are believed to be at a considerably reliable level. This prediction model will allow the end-user to make simple and quick predictions of a construction duration of a mixed-use building based only on the basic information in the project planning phase.

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Determinants of construction duration for building projects in Germany

Cited by 23 publications

References 19 publications

Construction Duration Determinants of Building Projects in Sarawak

Construction Duration Determinants of Building Projects in Sarawak

Assessing the predictability of construction time overruns using multiple linear regression and Markov chain Monte Carlo

Development of construction duration prediction model for project planning phase of mixed-use buildings

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