Abstracts – Browse Results
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Al-Qalyuby, H A (2005) Inductive learning methodology using OSHA construction accident and citation data, Unpublished PhD Thesis, , Wayne State University.
Alpmen, A S (2013) Development and implementation of a proactive safety performance evaluation system for general contractors, Unpublished PhD Thesis, , Wayne State University.
Alzeraa, A (2018) Impact of project communications effectiveness on construction disputes, Unpublished PhD Thesis, , Wayne State University.
Arafat, G H (1991) Concept evaluation in structural design utilizing multiattribute utility theory and a knowledge-based approach, Unpublished PhD Thesis, , Wayne State University.
Atin, A (2016) Project risk propagation modeling of engineering, procurement and construction, Unpublished PhD Thesis, , Wayne State University.
Baradan, S (2004) Comparative injury risk analysis of building trades, Unpublished PhD Thesis, , Wayne State University.
Cakan, H (2012) Analysis and modeling of roofer and steel worker fall accidents, Unpublished PhD Thesis, , Wayne State University.
Elkhatib, M M (1995) Developing an integrated highway information system for safety management using gis, Unpublished PhD Thesis, , Wayne State University.
Kazan, E E (2013) Analysis of fatal and nonfatal accidents involving earthmoving equipment operators and on-foot workers, Unpublished PhD Thesis, , Wayne State University.
Koehn, E (1975) Probabilistic system for project management, Unpublished PhD Thesis, , Wayne State University.
Kulaksiz, T (2019) Analysis of factors influencing return on investment (ROI) for building information modeling (BIM) implementation, Unpublished PhD Thesis, , Wayne State University.
Mishra, S (2009) Transportation infrastructure investment decision making under uncertainty and risk, Unpublished PhD Thesis, , Wayne State University.
Naizghi, M S (2021) Factors affecting implementation of earned value management (EVM) in construction projects, Unpublished PhD Thesis, , Wayne State University.
- Type: Thesis
- Keywords: accuracy; aerospace; construction project; earned value management; estimating; value management; project manager; scheduler; regression analysis; statistical analysis; focus group
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2540770520
- Abstract:
Earned Value Management (EVM) has emerged as an effective method to monitor and control project progress and status. The construction industry has been lagging behind others, such as defense and aerospace, in adopting EVM. The current research was undertaken to explore the barriers to EVM implementation in the construction industry, and aimed at investigating the factors affecting EVM adoption and effective utilization in the construction industry. To achieve this goal, the research followed a qualitative approach by gathering information from literature review and initial industry input to design a questionnaire. A total of 354 completed responses from project managers, project engineers, controllers, and schedulers were collected, of which 203 respondents were familiar with (aware of) EVM. Further, out of the 203 respondents who are familiar with EVM, 126 implemented EVM in their projects while the remaining did not. The data acquired were transformed into two dependent variables and several independent variables for statistical analysis. The responses from EVM-familiar industry representatives were used to analyze the factors that influence the first dependent variable (is EVM implemented), and the second dependent variable (how effectively is EVM implemented) coming from these 126 responses were used to perform cross-tabulation and logistic regression analysis. The results showed that the first dependent variable was influenced by management's commitment level, project budget range, availability of resources, extent work breakdown structure (WBS) is aligned with schedule, difficulty of estimating earned value (EV), detail Level of WBS, and Accuracy of planned value (PV). It was also found that the second dependent variable was affected by the extent execution following schedule baseline, accuracy of PV, availability of resources, management commitment level, difficulty of estimating EV, extent WBS is aligned with schedule, and type of contract. The findings of the statistical analyses were discussed and validated via a focus group consisting of a diverse group of experts from the construction industry.
Najib, T (2005) Investigation of success factors for smaller engineering firms, Unpublished PhD Thesis, , Wayne State University.
Vaglica, J (2018) Investigation of factors contributing to building code violations in residential construction, Unpublished PhD Thesis, , Wayne State University.