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1 – 4 of 4Chinthaka Niroshan Atapattu, Niluka Domingo and Monty Sutrisna
The current estimation practice in construction projects greatly needs upgrading, as there has been no improvement in the cost overrun issue over the past 70 years. The purpose of…
Abstract
Purpose
The current estimation practice in construction projects greatly needs upgrading, as there has been no improvement in the cost overrun issue over the past 70 years. The purpose of this research was to develop a new multiple regression analysis (MRA)-based model to forecast the final cost of road projects at the pre-design stage using data from 43 projects in New Zealand (NZ).
Design/methodology/approach
The research used the case study of 43 completed road projects in NZ. Document analysis was conducted to collect data, and statistical tests were used for model development and analysis.
Findings
Eight models were developed, and all models achieved the required F statistics and met the regression assumptions. The models’ mean absolute percentage error (MAPE) was between 21.25% and 22.77%. The model with the lowest MAPE comprised the road length and width, number of bridges, pavement area, cut and fill area, preliminary cost and cost indices change.
Research limitations/implications
The model is based on road projects in NZ. However, it was designed to be able to adapt to other contexts. The findings suggest that the model can be used to improve traditional conceptual estimating methods. Past project data is often stored by the project team but rarely used for analysing and forecasting purposes. This research emphasises that past data can be effectively used to predict the project cost at the pre-design stage with limited information.
Originality/value
No research was conducted to adopt cost modelling techniques into the conceptual estimation practice in the NZ construction industry.
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Pramod Malaka Silva, Niluka Domingo and Noushad Ali Naseem Ameer Ali
The construction industry is complex, human-intensive and driven by monetary values. Hence, disputes are widespread. Initial conflicts among parties may develop into a disastrous…
Abstract
Purpose
The construction industry is complex, human-intensive and driven by monetary values. Hence, disputes are widespread. Initial conflicts among parties may develop into a disastrous dispute that costs the project success and good relationships and affects stakeholders' expectations. There has been a focus on causes of construction-related disputes, and studies over the past three decades have attempted to identify a more comprehensive list of reasons for disputes. Some of these studies' limitations were geographical, project delivery methods and project types. The purpose of this study is to identify the most recent and conclusive list of causes of disputes based on current literature by undertaking a systematic literature review (SLR).
Design/methodology/approach
Considering the large number of studies that focused on causes of disputes, this study aims to develop a comprehensive list of causes, using a SLR, as it ensures that all previous articles in multiple databases are reviewed to produce a comprehensive outcome. A six-stage SLR was followed from background study to analysis and reporting.
Findings
Not surprisingly, the number of publications has increased over time, most from the Middle East region. The interconnected nature of the causes was widely emphasised. The SLR has produced eight common core causes of disputes. They are: poor contractual arrangements, employer-initiated scope changes, unforeseen site changes, poor contract understanding and administration, contractor’s quality of works, the inability of the contractor to achieve time targets, non- or delayed payments and poor quality of design. The majority of previous authors realised that disputes could be avoided by parties’ involvement during the early stages, avoiding being opportunistic and acting collaboratively.
Originality/value
Even though numerous studies have been carried out to identify the causes of disputes in the construction industry, none did a SLR. This study aggregates all the previous studies that focused on construction-related disputes systematically. Categorising causes based on the party primarily responsible help various stakeholders by providing a distinct list of factors to avoid that contribute to disputes.
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Chinthaka Niroshan Atapattu, Niluka Domingo and Monty Sutrisna
Cost overrun in infrastructure projects is a constant concern, with a need for a proper solution. The current estimation practice needs improvement to reduce cost overruns. This…
Abstract
Purpose
Cost overrun in infrastructure projects is a constant concern, with a need for a proper solution. The current estimation practice needs improvement to reduce cost overruns. This study aimed to find possible statistical modelling techniques that could be used to develop cost models to produce more reliable cost estimates.
Design/methodology/approach
A bibliographic literature review was conducted using a two-stage selection method to compile the relevant publications from Scopus. Then, Visualisation of Similarities (VOS)-Viewer was used to develop the visualisation maps for co-occurrence keyword analysis and yearly trends in research topics.
Findings
The study found seven primary techniques used as cost models in construction projects: regression analysis (RA), artificial neural network (ANN), case-based reasoning (CBR), fuzzy logic, Monte-Carlo simulation (MCS), support vector machine (SVM) and reference class forecasting (RCF). RA, ANN and CBR were the most researched techniques. Furthermore, it was observed that the model's performance could be improved by combining two or more techniques into one model.
Research limitations/implications
The research was limited to the findings from the bibliometric literature review.
Practical implications
The findings provided an assessment of statistical techniques that the industry can adopt to improve the traditional estimation practice of infrastructure projects.
Originality/value
This study mapped the research carried out on cost-modelling techniques and analysed the trends. It also reviewed the performance of the models developed for infrastructure projects. The findings could be used to further research to develop more reliable cost models using statistical modelling techniques with better performance.
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Chinthaka Niroshan Atapattu, Niluka Domingo and Monty Sutrisna
Cost overrun is one of the critical issues faced in construction projects, as nine out of ten projects will likely go over the budget. In particular, transportation infrastructure…
Abstract
Purpose
Cost overrun is one of the critical issues faced in construction projects, as nine out of ten projects will likely go over the budget. In particular, transportation infrastructure (TI) projects, such as roads and bridges, are vastly affected by cost overruns, which can delay the entire project. This research intends to identify the factors affecting the cost overruns in New Zealand (NZ) TI projects.
Design/methodology/approach
The research was conducted using a questionnaire survey involving ninety-two participants experienced in infrastructure project estimation in NZ. Quantitative methods were used to analyse the data.
Findings
Fifty-three factors were identified through literature under ten categories. Based on the survey, ten significant factors were identified with a high grade of importance. The three most critical factors were “frequent design changes,” “poor planning and scheduling” and “inadequate tender documentation.” It was found that the cost overrun is primarily affected by the pre-contract stage causes.
Research limitations/implications
The data were collected from professionals involved in NZTI projects. Therefore, the implications may be different for other contexts.
Practical implications
The results will improve the current estimation practice by developing a new statistical model considering all the significant variables for NZTI projects.
Originality/value
Although much research is done to identify these factors, they are only considered in a few statistical cost models. These new statistical models mainly focused on technical variable factors similar to the current standard estimation process. However, the results of this research, qualitative and quantitative factors, will be used for the future cost model.
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