Hogan, D B (1998) Modeling construction cost performance: A comprehensive approach using statistical, artificial neural network and simulation methods. PhD thesis, Columbia University, USA.
Abstract
The main objective of this research is to develop a comprehensive approach to modeling that can be used by construction organizations to improve their performance. This research addresses three widely described classes of problems that are important to construction managers of large-scale projects. The first is the need to understand a large construction organization's historical performance. The second is the need to predict the performance of a single construction project. The third is the need to predict the performance of multiple construction projects over time. Each of the problem areas described above are illustrated with research projects in which the author has recently participated that provide new approaches to and methodologies for the three general problem areas. In each case, models have been developed using cost as the primary indicator of project performance. The tools used to construct the models in this dissertation include multivariate statistics and regression, artificial neural networks, monte carlo simulation and systems dynamics. The methodologies developed herein include approaches to quantifying information that is less than perfect and, in some cases, qualitative in nature.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | artificial neural network; construction project; performance; Monte Carlo simulation; simulation; systems dynamics; neural network; project performance |
| Index terms: | large construction organization, construction organization, Monte Carlo simulation, construction cost, project performance, dissertation, statistics, modelling, neural network, artificial neural network, construction project, methodology, construction manager, systems dynamics |
| Subjects: | research methods, production management, project management theory and practice, decision-making and optimization, research dissemination and communication, profession, mathematical modelling, organization, modelling and simulation, artificial intelligence, analytical methods, financial and cost management, economic analysis |
| Topics: | Digital Applications, Cost Management, Business Strategy, Engineering Principles, Research Practice, Project Management, Roles and Professions |
| 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