Download the full-sized PDF of A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilitiesDownload the full-sized PDF


Download  |  Analytics

Export to: EndNote  |  Zotero  |  Mendeley


This file is in the following communities:

Faculty of Graduate Studies and Research


This file is not currently in any collections.

A fuzzy consensus building framework for early alignment of construction project teams on the extent of their roles and responsibilities Open Access


Other title
Fuzzy logic
Roles and Responsibilities
Type of item
Degree grantor
University of Alberta
Author or creator
Elbarkouky, Mohamed
Supervisor and department
Robinson Fayek, Aminah (Civil and Environmental)
Examining committee member and department
Pedrycz, Witold (Electrical and Computer Engineering)
Al Hussein, Mohamed (Civil and Environmental Engineering)
de la Garza, Jesus (Civil and Environmental Engineering, Virginia Tech)
Mohamed, Yasser (Civil and Environmental Engineering)
Department of Civil and Environmental Engineering

Date accepted
Graduation date
Doctor of Philosophy
Degree level
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 owner’s, 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.
License granted by Mohamed Elbarkouky ( on 2010-09-22T20:47:26Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication

File Details

Date Uploaded
Date Modified
Audit Status
Audits have not yet been run on this file.
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 2312370
Last modified: 2015:10:12 20:28:39-06:00
Filename: Mohamed_Elbarkouky_Fall_2010.pdf
Original checksum: 2351785a184f8c18c6addac2e9328f1d
Well formed: true
Valid: false
Status message: Invalid page tree node offset=606194
Status message: Outlines contain recursive references.
File title: Elbarkouky Complete Thesis 23 Sept 2010
Activity of users you follow
User Activity Date