Implementation of a neural network model for the comparison of the cost of different procurement approaches

Harding, A; Lowe, D; Hickson, A; Emsley, M and Duff, A R (1999) Implementation of a neural network model for the comparison of the cost of different procurement approaches. In: Hughes, W (ed.) Proceedings of 15th Annual ARCOM Conference, 15-17 September 1999, Liverpool, UK.

Abstract

The choice of procurement system for a building project is a very significant one. However, there is currently very little comparative cost data to inform the selection of procurement system, especially the total cost to the client. This paper reports on a model that will make such a comparison possible. This model, which is currently under development at UMIST, is designed to consider 39 project variables, including the choice of procurement system, and estimate the final cost of the project using a neural network. The suitability of a neural network to model this problem has already been established by a pilot study. The advantage of using this type of model is that it permits comparisons between the different procurement methods to be made within the context of that particular project, rather than within projects as a whole. The classification and representation of the different variables to be considered within this model are discussed. In addition to this, the implementation of factor/cluster analysis to reduce the number of variables required by the neural network, and hence increase its accuracy, is explained. Furthermore, the level of confidence of the model and its implications for the implementation of a “What if?” analysis are discussed. This analysis would allow the client to assess how changing certain variables, including procurement, might affect the final cost of the project.

Item Type: Conference Paper (Paper)
Uncontrolled Keywords: cost modelling; early stage estimating; neural networks; procurement
Index terms: procurement system, cluster analysis, estimating, modelling, implementation, estimate, cost data, suitability, procurement method, accuracy, neural network
Subjects: design criteria, professional development, accounting and finance, contractual arrangements, data analysis and analytics, artificial intelligence, financial and cost management, analytical methods
Topics: Digital Applications, Design Practice, Engineering Principles, Information Management, Research Practice, Cost Management, Procurement
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