A rational and optimal model of decision making for the decision to bid process

Jamshid Parvar; David J Lowe; Margaret W Emsley; John Kelly; Kirsty Hunter

A rational and optimal model of decision making for the decision to bid process

Jamshid Parvar, David J Lowe, Margaret W Emsley, John Kelly (Editor), Kirsty Hunter (Editor)

Executive Education General

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

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Abstract

Important factors in the decision to bid process are identified. A rational and optimal model of decision making for the decision to bid process, which depicts the relationships between these factors and the decision to bid options, is developed. Regression models and neural networks approach are employed to automate the rational and optimal model. Prototyping system development methodology is used as the neural networks system development. The neural networks approach in addition to the ability to model non-linear relationships, demonstrates superior performance in respect of higher accuracy of prediction and classification. The developed neural networks system is harnessed to develop a Decision Support System to support effective and efficient decision making for the decision to bid process.

Original language	English
Title of host publication	Proceedings of the RICS Construction and Building Research Conference
Editors	John Kelly, Kirsty Hunter
Place of Publication	London, UK
Publisher	RICS Foundation
Pages	334-353
Number of pages	20
Volume	1
ISBN (Print)	1-84219-067-9
Publication status	Published - 2001

Keywords

bidding, modelling, decision support system, neural networks

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title = "A rational and optimal model of decision making for the decision to bid process",

abstract = "Important factors in the decision to bid process are identified. A rational and optimal model of decision making for the decision to bid process, which depicts the relationships between these factors and the decision to bid options, is developed. Regression models and neural networks approach are employed to automate the rational and optimal model. Prototyping system development methodology is used as the neural networks system development. The neural networks approach in addition to the ability to model non-linear relationships, demonstrates superior performance in respect of higher accuracy of prediction and classification. The developed neural networks system is harnessed to develop a Decision Support System to support effective and efficient decision making for the decision to bid process.",

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author = "Jamshid Parvar and Lowe, {David J} and Emsley, {Margaret W} and John Kelly and Kirsty Hunter",

year = "2001",

language = "English",

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A rational and optimal model of decision making for the decision to bid process. / Parvar, Jamshid; Lowe, David J; Emsley, Margaret W et al.
Proceedings of the RICS Construction and Building Research Conference. ed. / John Kelly; Kirsty Hunter. Vol. 1 London, UK: RICS Foundation, 2001. p. 334-353.

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

TY - GEN

T1 - A rational and optimal model of decision making for the decision to bid process

AU - Parvar, Jamshid

AU - Lowe, David J

AU - Emsley, Margaret W

A2 - Kelly, John

A2 - Hunter, Kirsty

A2 - Kelly, John

A2 - Hunter, Kirsty

PY - 2001

Y1 - 2001

N2 - Important factors in the decision to bid process are identified. A rational and optimal model of decision making for the decision to bid process, which depicts the relationships between these factors and the decision to bid options, is developed. Regression models and neural networks approach are employed to automate the rational and optimal model. Prototyping system development methodology is used as the neural networks system development. The neural networks approach in addition to the ability to model non-linear relationships, demonstrates superior performance in respect of higher accuracy of prediction and classification. The developed neural networks system is harnessed to develop a Decision Support System to support effective and efficient decision making for the decision to bid process.

AB - Important factors in the decision to bid process are identified. A rational and optimal model of decision making for the decision to bid process, which depicts the relationships between these factors and the decision to bid options, is developed. Regression models and neural networks approach are employed to automate the rational and optimal model. Prototyping system development methodology is used as the neural networks system development. The neural networks approach in addition to the ability to model non-linear relationships, demonstrates superior performance in respect of higher accuracy of prediction and classification. The developed neural networks system is harnessed to develop a Decision Support System to support effective and efficient decision making for the decision to bid process.

KW - bidding, modelling, decision support system, neural networks

M3 - Conference contribution

SN - 1-84219-067-9

VL - 1

SP - 334

EP - 353

BT - Proceedings of the RICS Construction and Building Research Conference

PB - RICS Foundation

CY - London, UK

ER -

A rational and optimal model of decision making for the decision to bid process

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