Abdou, A; Lewis, J and Alzarooni, S (2004) Modelling risk for construction cost estimating and forecasting: A review. In: Khosrowshahi, F (ed.) Proceedings of 20th Annual ARCOM Conference, 1-3 September 2004, Edinburgh, UK.
Abstract
Construction cost estimating is considered one of the most essential tasks in the budget development of any project life cycle. However, it is carried out under conditions of uncertainty. Traditional cost estimating methods are unsatisfactory aids to decision making due to lack of their accuracy especially in feasibility or appraisal stages. Risk management is a form of decision-making within the project management process. Previous research indicated that the construction industry in particular has been slow to realize the potential benefits of risk management. With the introduction of microcomputers, the use of project management techniques has become economical, even for small construction projects. However, dealing with qualitative and judgement-based types of problems has been the subject of a lot of research and attempts that led to the Artificial Intelligence (AI) based models and applications. This research work aims at reviewing different approaches for modelling risk and uncertainty in construction cost estimating and forecasting. It starts with an overview of risk management concepts and fundamentals. Following that, it highlights the different analysis and modelling techniques within the risk management field. Finally, a number of previous research work and case-studies for modelling risk in construction cost estimating and forecasting are presented and reviewed.
| Item Type: | Conference Paper (Paper) |
|---|---|
| Uncontrolled Keywords: | artificial intelligence; cost estimating; fuzzy; and risk management |
| Index terms: | risk management, construction project, project management process, decision-making, estimating, artificial intelligence, appraisal, modelling, construction industry, cost estimating, forecasting, accuracy, construction cost, life cycle, project management technique |
| Subjects: | operations management, artificial intelligence, financial and cost management, analytical methods, prediction and forecasting, risk assessment, value management, decision analysis, industry analysis, factor and component analysis, production management, professional development, project management theory and practice |
| Topics: | Risk Management, Project Management, Research Practice, Information Management, Engineering Principles, Cost Management, Digital Applications |
| 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