Abstracts – Browse Results
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Abbasian Hosseini, S A (2015) Social and engineering aspects of construction site management using simulation and social network analysis, Unpublished PhD Thesis, , North Carolina State University.
Abudayyeh, O Y (1991) An automated data acquisition and data storage model for improving cost and schedule control, Unpublished PhD Thesis, , North Carolina State University.
Al-Ibrahim, A (2006) Optimizing roof maintenance and replacement decisions, Unpublished PhD Thesis, , North Carolina State University.
Alsharef, A F A (2022) Leveraging data analytics to improve construction operations and occupational safety, Unpublished PhD Thesis, , North Carolina State University.
Arocho Rosa, I d M (2015) The impact of transportation construction projects and activities on emissions, Unpublished PhD Thesis, , North Carolina State University.
Attia, T M (2002) The impact of communication technologies on group problem-solving performance in construction, Unpublished PhD Thesis, , North Carolina State University.
Bai, Y (1996) Planning and control model for robotic bridge painting, Unpublished PhD Thesis, , North Carolina State University.
Banerjee, S (2022) Developing an organization-wide knowledge repository with intelligent knowledge transference to enhance construction project outcomes, Unpublished PhD Thesis, , North Carolina State University.
Becker, T C (2012) Improving the predictability of construction project outcomes through project level indirect construction cost practices, Unpublished PhD Thesis, , North Carolina State University.
- Type: Thesis
- Keywords: construction cost; construction project; estimating; project cost; professional; project performance; case study; interview
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1347411835
- Abstract:
Indirect construction costs (IDCC) comprise from as little as 10 percent to 40 percent or more of the total cost of construction projects, in part dependent upon the type and nature of the project. Yet at either end of this range of percentages, IDCC account for a significant component of total project costs which justifies the need for practices to estimate, control and manage IDCC. When IDCC practices are not afforded the appropriate attention and resources, key outcomes of construction projects are affected. This research operationally defines IDCC and proposes a structured categorization framework for use in understanding and communicating IDCC functions among construction project participants. Empirical recommendations contained within this dissertation are premised upon data collected through testimonials, interviews and brain-storming of an extensive set of construction industry professionals, specifically including a 25-member Construction Industry Institute research team. Statistical findings are based upon data collected through 56 one-on-one data collection interviews with subject matter experts, and 47 project-level surveys. Qualitative data were filtered, organized, aggregated and technically presented as instructional guidelines, including 12 empirical checklists containing 216 consideration items, nine detailed process flowcharts and 20 practical tools for estimating, controlling and managing IDCC. These recommended practices and tools were verified and validated through rotational progressive reviews by experts and through project level case studies. Quantitative data were statistically analyzed using hypothesis testing and correlation analysis. The statistical methods utilized include Mood’s median test, Mann-Whitney U test, Pearson’s Chi-square test, Spearman rank correlation analysis, and Phi correlation analysis. These tests assess the presence of any statistically significant relationships between 15 representative IDCC practices and six construction project outcome metrics. The two most statistically significant, positively-correlated relationships found are the frequency of project manager-field supervisor meetings for review of IDCC to quality performance metric and to an index representing five hard project performance metrics. In summary, this research operationally defines IDCC, tests the association between IDCC practices and construction project outcomes, and offers process improvement opportunity by recommending leading IDCC practices. The predictability of construction project outcomes can be improved through application of the full collection of IDCC practices outlined and detailed in this research. Financial and time resources are constrained on construction projects, so practitioners may elect to focus their efforts on those specific IDCC practices most closely related to the construction project outcome(s) considered of highest value to the owner.
Chmielewski, H T (2023) Overcoming modeling barriers in long-term interdependent infrastructure systems planning, Unpublished PhD Thesis, , North Carolina State University.
Choi, B (2003) Topics in risk-based design and performance evaluation of structures, Unpublished PhD Thesis, , North Carolina State University.
Dorr, E E (1979) Economies of scale in high school construction and operation, Unpublished PhD Thesis, , North Carolina State University.
Hollar, D A (2011) Predicting preliminary engineering costs for highway projects, Unpublished PhD Thesis, , North Carolina State University.
Isied, M M (2023) Critical assessment of asphalt mixture design procedures and asphalt mixture classification systems, Unpublished PhD Thesis, , North Carolina State University.
Javanmardi, A (2019) Strategies and predictive models for reducing workflow variability in construction production systems, Unpublished PhD Thesis, , North Carolina State University.
Kranz, C N (2021) Optimizing compost incorporation for stormwater infiltration, runoff quality, and vegetation establishment in post-construction soils, Unpublished PhD Thesis, , North Carolina State University.
Lee, D (2023) Development of a real-time automated mobile robotic welding system in construction, Unpublished PhD Thesis, , North Carolina State University.
Lee, J (2005) Value analysis of Wi-Fi agent functions in construction, Unpublished PhD Thesis, , North Carolina State University.
Namian, M (2017) Factors affecting construction hazard recognition and safety risk perception, Unpublished PhD Thesis, , North Carolina State University.
Noghabaei, M (2021) Visual and behavioral data analysis in immersive virtual environments for enhancing construction safety, planning, and control, Unpublished PhD Thesis, , North Carolina State University.
Nuntasunti, S (2004) The effects of visual-based information logistics in construction, Unpublished PhD Thesis, , North Carolina State University.
Orgut, R E (2017) Metrics that matter: Improving project controls and analytics in construction industry, Unpublished PhD Thesis, , North Carolina State University.
Piper, B E B (2014) Optimization methods for improving the resilience of civil infrastructure systems subject to natural hazards, Unpublished PhD Thesis, , North Carolina State University.
Rihani, R A (2006) An investigation of critical success factors for robotic masonry, Unpublished PhD Thesis, , North Carolina State University.
Russell, M M (2013) Allocation of time buffer to construction project task durations, Unpublished PhD Thesis, , North Carolina State University.
Vereen, S C (2013) Forecasting skilled labor demand in the US construction industry, Unpublished PhD Thesis, , North Carolina State University.
Wambeke, B W (2011) Identifying, prioritizing, and reducing variation of construction related tasks, Unpublished PhD Thesis, , North Carolina State University.
Zuluaga Santa, C M (2018) Protecting bridge maintenance workers: Evaluating fall protection supplementary devices using virtual prototyping and wearable technology, Unpublished PhD Thesis, , North Carolina State University.