Bastias, A (2006) Towards the application of learning systems for decision support in construction engineering and management. PhD thesis, University of Colorado at Boulder, USA.
Abstract
Construction managers need to make decisions in an uncertain environment, where unexpected variables are present everyday and everywhere. To adequately support their decisions and decrease any negative impact and collateral effect, they use computational tools called decision support systems (DSS). DSS are widely used in the construction industry, presenting many advantages such as historical data available with fast processing of information, accuracy and effectiveness of output with a friendly interface. However, a review of ninety-three DSS in the construction over the past 30 years showed that most of them are static, where the model has fixed its parameters, and member functions. Static models can quickly become obsolete; requiring manual adjustment to be relevant in a dynamic environment such as the construction engineering and management field. A better approach to solving the problem of changes of the decision environment within the construction industry is to develop dynamic models based on learning systems. This research explores the application of learning capabilities in decision support systems in the construction industry by examining questions such as: what is the history and current state of DSS in construction engineering and management research?, what are the key components of a learning system for decision support?, and what are the characteristics of data in the construction engineering and management industry that must be addressed to create a general framework for applying learning systems? The outcome of this research is a general framework to apply the learning components into decision support systems for the construction engineering and management field.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Molenaar, K R |
| Uncontrolled Keywords: | accuracy; construction engineering; decision support; learning |
| Index terms: | construction industry, effectiveness, construction engineering, history, construction manager, accuracy, decision support, management research, static model |
| Subjects: | engineering methods, performance management, professional development, decision analysis, industry analysis, profession, research design and methodology, modelling and simulation, architectural and construction history |
| Topics: | Quality Management, Risk Management, Engineering Principles, Roles and Professions, Research Practice, Information Management |
| Descriptive scope: | 4 PCTA |
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