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Innovative Construction Procurement Selection Through An Artificial Intelligence Approach

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Lewis, John Andrew, Odeyinka, Henry and Eadie, Robert (2011) Innovative Construction Procurement Selection Through An Artificial Intelligence Approach. In: 27th Annual ARCOM Conference, Bristol, UK. . Association of Researchers in Construction Management. Vol 2 9 pp. [Conference contribution]

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Abstract

The construction industry in the British Isles has long been accused of being low tech, averse to funding research and development, and reliant on other sectors allied to construction for innovative improvements. One area has been championed as reflecting change, especially post Latham and Egan, and that is construction procurement. The last few decades have witnessed a proliferation of procurement systems and sub-systems. The methodology herein proposes to customise and innovate bespoke construction project procurement strategies through the development of an intelligent system and to discover if the new procurement methods are indeed innovative. The approach has three main phases; firstly the planning and development phase, followed by the empirical phase and thirdly; the final quasiexperimental phase. After a detailed literature review in the planning stage, the empirical phase includes a pilot survey to ascertain the precise nature of innovation within building procurement in the British Isles and establish an appropriateknowledge acquisition model. This model will be utilised within the main survey to populate a database of relevant innovative procurement case histories. In the final quasi-experimental phase; a fuzzy hierarchical case-based reasoning (CBR) platform will be software engineered as an innovative procurement selection mechanism. This will be validated and verified through a Delphi process to ascertain its effectiveness and appropriateness. The outputted fuzzy hierarchical CBR mechanism will be beneficial to the construction professional seeking innovative procurement selection ideas in the strategy and consultation stages of a building project.

Item Type:Conference contribution (Paper)
Keywords:artificial intelligence, building procurement, innovation.
Faculties and Schools:Faculty of Art, Design and the Built Environment
Faculty of Art, Design and the Built Environment > School of the Built Environment
Research Institutes and Groups:Built Environment Research Institute
Built Environment Research Institute > Centre for Sustainable Technologies (CST)
ID Code:20843
Deposited By:Dr Robert Eadie
Deposited On:21 Feb 2012 11:48
Last Modified:16 Mar 2012 09:28

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