Defining the Success Status of Construction Projects Based on Quantitative Performance Metrics Thresholds

Aboseif, Eyad; Hanna, Awad S.

doi:10.1061/jmenea.meeng-5123

Cited by 10 publications

(7 citation statements)

References 39 publications

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“…, 2004; Yap et al. , 2019; Aboseif, 2021). In addition to this, great deal of efforts has been spent to measure time or cost performance of construction projects, however, the evaluation of overall construction projects performance has been subjective and less structured (Nassar, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…The complexity explained earlier comes in tandem with another problem marring the construction industry where performance assessment, profitability and market focus longterm business strategies are absent from most of construction companies (Pries et al, 2004;Yap et al, 2019;Aboseif, 2021). In addition to this, great deal of efforts has been spent to measure time or cost performance of construction projects, however, the evaluation of overall construction projects performance has been subjective and less structured (Nassar, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, a project can be evaluated as successful by a stakeholder and not successful by another due to multiple performance metrics that stakeholders consider. A project can have an extra cost of 10% and finish early by 10%, this makes it difficult to say if this project can be classified as successful or not with huge subjectivity involved in such a decision (Aboseif, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Benchmarking of construction projects performance for comparative assessment and performance improvement: a statistical quantitative approach

Aboseif

Hanna²

2023

ECAM

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PurposeThe exact process of construction projects performance assessment and benchmarking still remains subjective relying on qualitative techniques, which does not allow stakeholders to address the issues and the drawbacks of their respective projects as effectively as possible for performance improvement purposes. Hence, this research aims to establish a unified project performance score (PPS) for assessing and comparing projects performance.Design/methodology/approachData were collected from Construction Industry Institute (CII) members and through University of Wisconsin active research projects. Exploratory data analysis was done to investigate the calculated performance metrics and the collected data characteristics. Data were converted into six performance metrics which were used as the independent variables in creating the PPS model. Logistic regression model was developed to generate the unified PPS equation in order to explain the variables that significantly affect construction projects successful post-completion performance. The PPS model was then applied on the collected dataset to benchmark projects in terms of project delivery systems, compensation types and project types in order to showcase the PPS capabilities and possible applications.FindingsThe model revealed that construction cost and schedule growth are the most important metrics in assessing projects performance, while RFIs’ processing time and change orders per million dollars were the features with the least effect on the PPS value. The authors found that integrated project delivery (IPD) and target value (TV) projects outperformed all other project delivery and compensation types. While, industrial projects showed the worst performance, as compared to commercial or institutional projects.Originality/valueThe PPS model can be used to assess the performance of any pool of executed projects, and introducing a novel addition to the field of construction business analytics which is a supplementary tool to successful decision making and performance improvement. Additionally, the bidding selection system can be revolutionized from a cost-based to a performance based one using the PPS model to improve the outcomes of the buyout process.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Benchmarking of construction projects performance for comparative assessment and performance improvement: a statistical quantitative approach

Aboseif

Hanna²

2023

ECAM

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“…First, RFIs have been used to measure design quality (Tilley et al, 1997), a leading indicator of how projects will perform. In the ASCE study "Defining the Success Status of Construction Projects Based on Quantitative Performance Metrics Thresholds," RFIs and Change Orders quantities were used to differentiate between successful and non-successful projects (Aboseif et al, 2022). Similarly, this GC uses the volume of RFIs a project experiences to signify if projects have unanticipated changes and potentially could not meet the existing contractual requirements.…”

Section: Introduction the Rework Problem And Design Qualitymentioning

confidence: 99%

“…If the count of RFIs for a project increases above the weekly average the project has been experiencing, this is considered a warning that the design quality does not reflect the information the GC needs to build. However, one challenge with this approach is that these comparisons were all made without distinguishing between successful and unsuccessful projects (Aboseif et al, 2022).…”

Section: Introduction the Rework Problem And Design Qualitymentioning

confidence: 99%

Assessing Quality Performance Outcomes & the Relationship With RFI and PCI Processes: A General Contractor Case Study

Gordón¹,

Rawlinson²,

Dabhade³

et al. 2023

Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)

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This paper is the third in the series, taking a cross-discipline view of project performance to investigate and understand the potential correlation between system inputs and outputs. In the 2021 paper "The Impact of Implementing a System Approach to Quality: A General Contractor Case Study," the authors compared project performance outcomes and team cultural assessments for 11 projects that had implemented a Systems Approach to Quality (SAQ), the Intervention group, against a similar set of projects that had implemented a compliance-based approach to quality, the Control group. This paper continues to investigate the project performance outputs for these two groups and specifically looks at the Request for Information (RFI) and Potential Change Item (PCI) workflows. This case study considers if RFI and PCI metrics can be used to determine if better quality design contributed to better performance outcomes. Then it considers how RFI and PCI processes relate to SAQ implementation. The authors' findings suggest that applying SAQ resulted in project teams documenting RFIs sooner in the project lifecycle and experiencing faster closure rates compared to the Control group.

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Understanding the relationship between team diversity and the innovative performance in research teams using decision tree algorithms: evidence from artificial intelligence

Liu,

Gong,

et al. 2024

Scientometrics

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Defining the Success Status of Construction Projects Based on Quantitative Performance Metrics Thresholds

Cited by 10 publications

References 39 publications

Benchmarking of construction projects performance for comparative assessment and performance improvement: a statistical quantitative approach

Benchmarking of construction projects performance for comparative assessment and performance improvement: a statistical quantitative approach

Assessing Quality Performance Outcomes & the Relationship With RFI and PCI Processes: A General Contractor Case Study

Understanding the relationship between team diversity and the innovative performance in research teams using decision tree algorithms: evidence from artificial intelligence

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