An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs

David Lowe; J P Pantouvakis

An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs

David Lowe, J P Pantouvakis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recent research at UMIST has resulted in the production of “ProCost”, a piece of software that predicts the final price of a proposed building at an early stage. This paper analyses the results of a nationwide questionnaire survey, as well as the outcomes of a series of interviews with three major UK based Quantity Surveying firms. The results of this research show that the vast majority of cost estimators believe that a single figure cost estimate is insufficient to meet their forecasting needs. For this reason, different formats for breaking down building costs into sub-elements are investigated. Based on the chosen format, regression analysis is used to develop a series of predictive models. One of these models is discussed in the current paper and the values predicted by it are compared with actual values. An analysis of the variance between the two follows.

Original language	English
Title of host publication	Proceedings of the 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management”
Editors	J P Pantouvakis
Pages	255-262
Number of pages	8
Publication status	Published - 2004
Event	3rd Scientific Conference on Project Management, “Clustering in Construction Project Management" - Thessaloniki, Greece Duration: 24 Sept 2004 → 25 Sept 2004

Conference

Conference	3rd Scientific Conference on Project Management, “Clustering in Construction Project Management"
Country/Territory	Greece
City	Thessaloniki
Period	24/09/04 → 25/09/04

Keywords

Cost estimation
elemental cost analysis
neural networks
regression analysis

Cite this

@inproceedings{e73d507bce2c4fb0aefd7c9a7d2386a8,

title = "An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs",

abstract = "Recent research at UMIST has resulted in the production of “ProCost”, a piece of software that predicts the final price of a proposed building at an early stage. This paper analyses the results of a nationwide questionnaire survey, as well as the outcomes of a series of interviews with three major UK based Quantity Surveying firms. The results of this research show that the vast majority of cost estimators believe that a single figure cost estimate is insufficient to meet their forecasting needs. For this reason, different formats for breaking down building costs into sub-elements are investigated. Based on the chosen format, regression analysis is used to develop a series of predictive models. One of these models is discussed in the current paper and the values predicted by it are compared with actual values. An analysis of the variance between the two follows.",

keywords = "Cost estimation, elemental cost analysis, neural networks, regression analysis",

author = "David Lowe and Pantouvakis, {J P}",

note = "3rd Scientific Conference on Project Management, “Clustering in Construction Project Management” ; Conference date: 24-09-2004 Through 25-09-2004; 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management{"} ; Conference date: 24-09-2004 Through 25-09-2004",

year = "2004",

language = "English",

isbn = "960-254-642-5",

pages = "255--262",

editor = "Pantouvakis, {J P}",

booktitle = "Proceedings of the 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management”",

}

Lowe, D & Pantouvakis, JP 2004, An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs. in JP Pantouvakis (ed.), Proceedings of the 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management”. pp. 255-262, 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management", Thessaloniki, Greece, 24/09/04.

An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs. / Lowe, David; Pantouvakis, J P.
Proceedings of the 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management”. ed. / J P Pantouvakis. 2004. p. 255-262.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs

AU - Lowe, David

AU - Pantouvakis, J P

N1 - 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management” ; Conference date: 24-09-2004 Through 25-09-2004

PY - 2004

Y1 - 2004

N2 - Recent research at UMIST has resulted in the production of “ProCost”, a piece of software that predicts the final price of a proposed building at an early stage. This paper analyses the results of a nationwide questionnaire survey, as well as the outcomes of a series of interviews with three major UK based Quantity Surveying firms. The results of this research show that the vast majority of cost estimators believe that a single figure cost estimate is insufficient to meet their forecasting needs. For this reason, different formats for breaking down building costs into sub-elements are investigated. Based on the chosen format, regression analysis is used to develop a series of predictive models. One of these models is discussed in the current paper and the values predicted by it are compared with actual values. An analysis of the variance between the two follows.

AB - Recent research at UMIST has resulted in the production of “ProCost”, a piece of software that predicts the final price of a proposed building at an early stage. This paper analyses the results of a nationwide questionnaire survey, as well as the outcomes of a series of interviews with three major UK based Quantity Surveying firms. The results of this research show that the vast majority of cost estimators believe that a single figure cost estimate is insufficient to meet their forecasting needs. For this reason, different formats for breaking down building costs into sub-elements are investigated. Based on the chosen format, regression analysis is used to develop a series of predictive models. One of these models is discussed in the current paper and the values predicted by it are compared with actual values. An analysis of the variance between the two follows.

KW - Cost estimation

KW - elemental cost analysis

KW - neural networks

KW - regression analysis

M3 - Conference contribution

SN - 960-254-642-5

SP - 255

EP - 262

BT - Proceedings of the 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management”

A2 - Pantouvakis, J P

T2 - 3rd Scientific Conference on Project Management, “Clustering in Construction Project Management"

Y2 - 24 September 2004 through 25 September 2004

ER -

An investigation into the implementation of a predictive model for the early stage estimation of elemental building costs

Abstract

Conference

Keywords

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Cite this