Predicting likelihood of cost overrun in educational projects

Asiedu, Richard Ohene; Frempong, Nana Kena; Alfen, Hans Wilhelm

doi:10.1108/ecam-06-2015-0103

Cited by 23 publications

(16 citation statements)

References 39 publications

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“…A MAPE of 26 per cent at the validation stage is also consistent with Wang et al (2000) and Bode (1998) with a deviation of 24.5 and 24 per cent, respectively. According to Asiedu et al (2016), an MAPE of 26 per cent can be regarded as good and is much better than the MAPE values of 138 and 60.7 per cent obtained by the studies conducted by Asiedu et al (2017) and Asiedu et al (2016), respectively. Model 2 is eventually selected with a good predictive ability at the validation stage (coefficient of determination, R 2 = 88.5 per cent).…”

Section: Artificial Neural Network Model Developmentmentioning

confidence: 63%

“…According to Stoy et al (2007); the positive coefficients of IC, SB and H could indicate that massive or large projects enable efficient use of production factors which in effect would result in speed of construction than in smaller projects, thereby shortening the duration of the entire bridge construction project. The shortening of duration can be attributed to the principle of economy of scale, where larger projects tend to be well planned and better managed than smaller projects because the stakes are often high (Asiedu et al, 2017). This could possibly be the reason for the negative coefficient of BW in equation ( 6).…”

Section: Discussion Of Mlr and Ann Modelsmentioning

confidence: 99%

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Duration estimation model for bridge construction projects in Ghana

Nani

Mensah

Adjei-Kumi

2017

JEDT

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Purpose A major concern for construction professionals at the rural road agency in Ghana is the problem of fixing contract duration for bridge construction projects in rural areas. The purpose of the study was to develop a tool for construction professionals to forecast duration for bridge projects. Design/methodology/approach In all, 100 questionnaires were distributed to professionals at the Department of Feeder Roads to ascertain their views on the work items in a bill of quantities (BOQ) that impact significantly on the duration of bridge construction projects. Historical data for 30 completed bridge projects were also collected from the same Department. The data collected were executed work items in BOQ and actual durations used in completing the works. The qualitative data were analysed using the relative importance index and the quantitative data, processed and analysed using both the stepwise regression method and artificial neural network (ANN) technique. Findings The identified predictors, namely, in-situ concrete, weight of prefabricated steel components, gravel sub-base and haulage of aggregates, used as independent variables resulted in the development of a regression model with a mean absolute percentage error (MAPE) of 25 per cent and an ANN model with a feed forward back propagation algorithm with an MAPE of 26 per cent at the validation stage. The study has shown that both regression and ANN models are appropriate for predicting the duration of a new bridge construction project. Research limitations/implications The predictors used in the developed models are limited to work items in BOQs only of completed bridge construction projects as well as the small sample size. Practical implications The study has developed a working tool for practitioners at the agency to forecast contract duration for bridge projects prior to its commencement. Originality value The study has quantified the relationship between the work items in BOQs and the duration of bridge construction projects using the stepwise regression method and the ANN techniques.

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Section: Artificial Neural Network Model Developmentmentioning

confidence: 63%

Section: Discussion Of Mlr and Ann Modelsmentioning

confidence: 99%

Duration estimation model for bridge construction projects in Ghana

Nani

Mensah

Adjei-Kumi

2017

JEDT

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“…Ramanathan et al, 2012;C. T. Ramanathan et al, 2011;) Pakistan 9 (Afzal et al, 2019;Akram et al, 2017;Choudhry et al, 2014Choudhry et al, , 2018Choudhry & Rehman Nasir, 2012;Hanif et al, 2016;Maqsoom et al, 2018;Samiullah Sohu et al, 2017;Zafar et al, 2016) China 6 (Afzal et al, 2019;Lou & Yin, 2010;Ma, 2011;Mansur et al, 2019;Wang & Yuan, 2011;Yuanyue & Huimin, 2018) Ghana 5 (Asiedu et al, 2017;Asiedu & Adaku, 2019;Coffie et al, 2019) Nigeria 4 (Akinradewo et al, 2019;Akinsiku et al, 2014;Amadi & Higham, 2019;Amusan et al, 2018;Hingham, 2016) Saudi Arabia 4 (Alghonamy, 2015;Mahamid, 2013Mahamid, , 2018Seddeeq et al, 2019) South Africa 4 (Khabisi, 2012;Monyane et al, 2018;Mulalo et al, 2018 (Jung et al, 2016;Kavuma et al, 2019;Qiao et al, 2019) Vietnam 3 (S. Kim et al, 2017;S. Y. Kim et al, 2018;Pham et al, 2020) Others 21 (Afzal et al, 2019;Al-hazim et al, 2017;Alzebdeh et al, 2015;Apolot & Tindiwensi, 2013;…”

Section: Synthesis Of Resultsmentioning

confidence: 99%

Systematic Review of Cost Overrun Research in the Developed and Developing Countries

Ismail

Ramly

Hamid

2021

IJSCET

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For decades, reputation of the construction industry has been tainted by poor cost performance caused by project cost overrun. In addition, studies by scholars worldwide have also found cost overrun to be more serious in developing countries compared to the developed countries. Despite the numerous researches addressing the issue of cost overrun in the construction industry through the years, the issue remains. Acknowledging that maintaining good cost performance is a key factor of project success and that the issue has persisted for decades, this study aims to explore the distinction of cost overrun studies that has been conducted between developed nations and developing nations. In achieving this aim, a systematic literature review is performed by following the integrative steps of PSALSAR (Protocol, Search, Appraisal, Synthesis, Analysis and Report) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for screening and selecting the retrieved studies. The synthesis and screening of literatures have yielded with 152 articles which are then classified into their countries, developed countries (44) and developing countries (108). The results indicated a significant difference in the domain of research on cost overrun between the 2 nations. Despite the numerous studies on cost overrun in the developing nations compared to developed nations, the majority of the studies are not directed to any specific type construction while developed nations have moved forward to focus on more specific projects. The project with the highest attention in the developed nations is transport infrastructure construction projects, particularly rail infrastructure projects. The findings of this study have shown that there have been broad studies conducted on cost overrun in both developing nations and developed nations. However, there is a slight lacking in comprehensiveness of cost overrun studies in the developing nations, perhaps future studies on cost overrun in developing nations can be directed to more specific areas of construction projects such as those that have been performed by researchers of the developed nations.

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“…Samarghandi et al used regression techniques to quantify construction delay factors in Iran for residential projects and educational facilities [22]. Educational facilities have been a particular interest for assessing cost and time overruns, with a more advanced regression analysis executed by Asiedu et al [23]. Samarghandi et al used linear regression techniques where a single dependent variable was correlated with a single independent variable.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The Asiedu et al team used multiple linear regression (MLR), where they identified 10 predictive variables that could influence cost overruns. The MLR analysis determined that five of the variables influenced the overruns [23]. A study of 911 building projects in Ghana also applied MLR analysis in the statistical software R and considered seven predictive variables [24].…”

Section: Literature Reviewmentioning

confidence: 99%

Construction Time Estimation Function for Canadian Utility Scale Power Plants

Kabanda¹,

Romard²,

Yurtsever³

et al. 2021

Energies

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Construction time and time overruns for infrastructure projects have been frequently studied; however, the construction time of power plants has not been studied. This lack of study is problematic, as more renewable energy power plants, such as wind and solar, are planned for many jurisdictions. Accurately estimating the construction time of a power plant will assist construction planning, budget estimates, and policy development encouraging the use of more renewable sources. The construction times of utility scale power plants in Canada were studied using publicly available data. Multiple linear regression analysis techniques were applied to the data to generate construction time estimation functions for all power plants together, and for individual technologies. The analyses reveal that construction time is sensitive to jurisdiction and the decade of construction, indicating that decisions made by individual Canadian provincial governments at different times had statistically significant impacts on construction time. The analyses also indicated that construction time is a strong function of installed capacity, independent of technology. This finding suggests that large solar or wind energy facilities will encounter longer construction times similar to large hydroelectric facilities.

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Predicting likelihood of cost overrun in educational projects

Cited by 23 publications

References 39 publications

Duration estimation model for bridge construction projects in Ghana

Duration estimation model for bridge construction projects in Ghana

Systematic Review of Cost Overrun Research in the Developed and Developing Countries

Construction Time Estimation Function for Canadian Utility Scale Power Plants

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