Analysis of Cost-Estimating Competencies Using Criticality Matrix and Factor Analysis

Alroomi, Anwar; Jeong, H. David; Oberlender, Garold D.

doi:10.1061/(asce)co.1943-7862.0000351

Cited by 28 publications

(25 citation statements)

References 4 publications

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“…Alroomi et al [3] developed a core-competency framework and methodology for cost estimators in the construction domain. Using a criticality matrix to prioritize, Alroomi et al [3] used the combined effects of each competency's level of importance of each and its associated gap between its ideal and actual level to measure the different competencies.…”

Section: Background On Construction Project Competencies Project Permentioning

confidence: 99%

“…Using a criticality matrix to prioritize, Alroomi et al [3] used the combined effects of each competency's level of importance of each and its associated gap between its ideal and actual level to measure the different competencies. The factor analysis method was applied to investigate the correlation effects of the different estimating competencies, which resulted in a reduced set of core estimating competency factors representing the core estimating competencies for cost estimators.…”

Section: Background On Construction Project Competencies Project Permentioning

confidence: 99%

“…Previous research has addressed project competencies in construction by describing project competencies, in many situations, as project performance. Additionally, previous research in the areas of project competencies focused mainly on evaluating the different sets of competencies rather than identifying the relationship between project competencies and performance [3,35]. Little research investigated the relationship between project competencies and performance through simple statistical techniques such as correlation and multiple linear regression analysis [15,18].…”

Section: Introductionmentioning

confidence: 98%

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Modeling and evaluating construction project competencies and their relationship to project performance

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Fayek

2016

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Section: Background On Construction Project Competencies Project Permentioning

confidence: 99%

Section: Background On Construction Project Competencies Project Permentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Modeling and evaluating construction project competencies and their relationship to project performance

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Fayek

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“…Principal component analysis (PCA) is the most extensively used method and was used in this case [79]. Table 3 revealed that the communalities of the variables reached 65% except FC6 (60.2%).…”

Section: Exploratory Factor Analysismentioning

confidence: 99%

“…The eigenvalues, percentage of variance and total variance of variables were also shown in Table 4. However, the important variables are those whose eigenvalues are greater than or equal to 1, because the eigenvalue can measure how a standard variable contributes to the principal components [79]. A component with an eigenvalue of less than 1 is considered less important and can be ignored.…”

Section: Extraction Of Initial Factorsmentioning

confidence: 99%

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Xue

Zhang

et al. 2018

Sustainability

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Abstract:High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals' views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including "Management Index", "Construction Dissipation Index", "Productivity Index", "Design Efficiency Index", "Transport Dissipation Index", "Material increment Index" and "Depreciation amortization Index". With these latent factors, a factor analysis evaluation model (FAEM), divided into factor analysis model (FAM) and comprehensive evaluation model (CEM), was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to evaluate cost management level of prefabrication and explore key inducers for high capital cost.

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Relationship Model Between Conceptual Cost Estimation Process of Flyover Development in the Provincial Government of DKI Jakarta with the Accuracy Level

Yussi

Latief

Machfudiyanto

2022

Proceedings of the 5th International Conference on Rehabilitation and Maintenance in Civil Engineering

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Analysis of Cost-Estimating Competencies Using Criticality Matrix and Factor Analysis

Cited by 28 publications

References 4 publications

Modeling and evaluating construction project competencies and their relationship to project performance

Modeling and evaluating construction project competencies and their relationship to project performance

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Relationship Model Between Conceptual Cost Estimation Process of Flyover Development in the Provincial Government of DKI Jakarta with the Accuracy Level

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