A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities
This thesis presents a Fuzzy Consensus Building Framework (FCBF), which enables construction project parties to align their teams on their roles and responsibilities early on in their projects. The framework introduces a model that (1) incorporates consensus of construction project teams in aggregat...
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ndltd-LACETR-oai-collectionscanada.gc.ca-AEU.10048-14372012-03-21T22:50:08ZRobinson Fayek, Aminah (Civil and Environmental)Elbarkouky, Mohamed2010-09-23T16:44:21Z2010-09-23T16:44:21Z2010-09-23T16:44:21Zhttp://hdl.handle.net/10048/1437This thesis presents a Fuzzy Consensus Building Framework (FCBF), which enables construction project parties to align their teams on their roles and responsibilities early on in their projects. The framework introduces a model that (1) incorporates consensus of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project; (2) classifies the quality of experts in the decision making process by weighting their responses during aggregation, based on their attributes; and (3) resolves residual conflicts between project teams on their perceived shared tasks, using a consensus reaching process. A template of project and construction management tasks is extracted from relevant standard guidelines and interviews with industry peers. Different extents of the roles and responsibilities of the owner and contractors are described using seven linguistic terms. A modified similarity aggregation method (SAM) aggregates experts opinions in a linguistic framework, using a consensus weight factor for each expert. A fuzzy expert system (FES) determines an importance weight factor for each expert, representing expert quality; opinions are aggregated using this factor and the consensus weight factor. Based on the aggregated opinions of experts, the tasks are classified into three responsibility lists: the owners, the contractors, and the shared responsibility list. The fuzzy preference relations consensus (FPRC) approach is applied to the tasks of shared responsibility, and a linguistic consensus measure is applied to resolve potential conflicts between team members on their perceived shared tasks. Using a case study approach, the FCBF is applied to aid a project owner organization in the field of oil and gas to determine its roles and responsibilities in a customized project delivery system, called owner managing contractor (OMC). The FCBF contributes to the construction industry by solving a fundamental problem for project owners: it helps identify and reduce potential conflicts over the extent of project teams responsibilities prior to the construction stage. It also provides an improvement over previous consensus-based approaches, which rely on a subjective assessment of experts importance weights in aggregating their opinions, and it modifies the SAM to adapt it to a linguistic environment.2339232 bytesapplication/pdfen_USAlignmentConsensusFuzzy logicConstructionRoles and ResponsibilitiesA fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilitiesThesisDoctor of PhilosophyDoctoralDepartment of Civil and Environmental EngineeringUniversity of Alberta2010-11Construction Engineering and ManagementAl Hussein, Mohamed (Civil and Environmental Engineering)Mohamed, Yasser (Civil and Environmental Engineering)Pedrycz, Witold (Electrical and Computer Engineering)de la Garza, Jesus (Civil and Environmental Engineering, Virginia Tech) |
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Alignment Consensus Fuzzy logic Construction Roles and Responsibilities |
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Alignment Consensus Fuzzy logic Construction Roles and Responsibilities Elbarkouky, Mohamed A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
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This thesis presents a Fuzzy Consensus Building Framework (FCBF), which enables construction project parties to align their teams on their roles and responsibilities early on in their projects. The framework introduces a model that (1) incorporates consensus of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project; (2) classifies the quality of experts in the decision making process by weighting their responses during aggregation, based on their attributes; and (3) resolves residual conflicts between project teams on their perceived shared tasks, using a consensus reaching process. A template of project and construction management tasks is extracted from relevant standard guidelines and interviews with industry peers. Different extents of the roles and responsibilities of the owner and contractors are described using seven linguistic terms. A modified similarity aggregation method (SAM) aggregates experts opinions in a linguistic framework, using a consensus weight factor for each expert. A fuzzy expert system (FES) determines an importance weight factor for each expert, representing expert quality; opinions are aggregated using this factor and the consensus weight factor. Based on the aggregated opinions of experts, the tasks are classified into three responsibility lists: the owners, the contractors, and the shared responsibility list. The fuzzy preference relations consensus (FPRC) approach is applied to the tasks of shared responsibility, and a linguistic consensus measure is applied to resolve potential conflicts between team members on their perceived shared tasks. Using a case study approach, the FCBF is applied to aid a project owner organization in the field of oil and gas to determine its roles and responsibilities in a customized project delivery system, called owner managing contractor (OMC). The FCBF contributes to the construction industry by solving a fundamental problem for project owners: it helps identify and reduce potential conflicts over the extent of project teams responsibilities prior to the construction stage. It also provides an improvement over previous consensus-based approaches, which rely on a subjective assessment of experts importance weights in aggregating their opinions, and it modifies the SAM to adapt it to a linguistic environment. === Construction Engineering and Management |
author2 |
Robinson Fayek, Aminah (Civil and Environmental) |
author_facet |
Robinson Fayek, Aminah (Civil and Environmental) Elbarkouky, Mohamed |
author |
Elbarkouky, Mohamed |
author_sort |
Elbarkouky, Mohamed |
title |
A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
title_short |
A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
title_full |
A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
title_fullStr |
A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
title_full_unstemmed |
A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
title_sort |
fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities |
publishDate |
2010 |
url |
http://hdl.handle.net/10048/1437 |
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