Chau, A D (2018) Conceptual cost estimation decision support system in university construction projects. PhD thesis, University of Alabama, USA.
Abstract
Recently, many construction organizations have shifted from offline to online data storage platforms, such as MS SharePoint. Construction companies are storing more historical data than ever. The question is how these historical data can be structured and analyzed to make actionable decisions and bring competitive advantages. This dissertation discusses a reliable solution for using historical data in construction. In this project, we developed a decision support system which predicts conceptual costs of construction projects and supports decision-making for long-term capital planning in public universities. A prototype system was developed based on historical data for roofing projects at the University of Alabama. We collected this historical data via a web-based data entry form subsystem. The developed system uses ridge regression models to train historical data, which helps reduce multicollinearity. K-fold cross-validation and evolutionary algorithm are used to fit ridge regression models. This system has a user-friendly interface and supports what-if analysis which allows the user to see multiple scenarios of the estimation. Also, the system has an automated process which adjusts inflation based on construction start date. Finally, validation has shown that the system can improve in the accuracy in conceptual estimation of roofing projects at the University of Alabama.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Moynihan, G P |
| Uncontrolled Keywords: | accuracy; competitive advantage; decision support; construction project; inflation |
| Index terms: | dissertation, public university, automated process, platform, construction organization, regression model, competitive advantage, estimation, evolutionary algorithm, validation, inflation, decision-making, roofing, construction project, data storage, cost estimating, decision support, accuracy, construction company, prototype |
| Subjects: | market analysis, algorithms, production management, automation and robotics, digital design, economic analysis, research dissemination and communication, organization, data management, educational institutions, decision analysis, statistical analysis, design practice, professional development, modelling and simulation, financial and cost management |
| Topics: | Cost Management, Business Strategy, Information Management, Research Practice, Digital Applications, Design Practice, Risk Management, Engineering Principles, Project Management, Education |
| Descriptive scope: | 3 PCA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here