Fuzzy Similarity Consensus Model for Early Alignment of Construction Project Teams on the Extent of Their Roles and Responsibilities
Publication: Journal of Construction Engineering and Management
Volume 137, Issue 6
Abstract
A fuzzy similarity consensus (FSC) model is presented for alignment of construction project owner and contractor project teams to their roles and responsibilities, identifying and reducing fundamental problems of conflicts, duplication, and gaps in roles and responsibilities as early as the project initiation stage. The model achieves its objective by incorporating consensus and quality of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project. The roles and responsibilities of the owner and contractors are described to different extents using seven linguistic terms defined by triangular membership functions and constructed using a three-step Delphi approach, which allows experts to develop common understanding of the meaning of the terms by determining their overlap on a fuzzy linguistic scale. A modified similarity aggregation method (SAM) aggregates experts’ opinions in a linguistic framework using a consensus weight factor for each expert that is based on the similarity of his or her opinion relative to the other experts to ensure that the experts’ final decision is a result of common agreement. A fuzzy expert system (FES) determines an importance weight factor, representing expert quality for each expert; opinions are aggregated using this factor and the consensus weight factor. The FSC model contributes to the construction industry by solving a fundamental problem for project owners who want to identify and reduce potential conflicts between their project teams on the extent of their roles and responsibilities prior to the construction stage. Also, the FSC model provides an improvement over previous consensus-based approaches, which rely on a subjective assessment of experts’ important weights in aggregating their opinions, and it modifies the SAM to adapt it to a linguistic environment.
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Acknowledgments
The authors would like to express their sincere appreciation of the experts at the participating owner organization and their EPC contractors. This work was financially supported by the NSERC Associate Industrial Research Chair in Construction Engineering and Management at the University of Alberta under a Natural Sciences and Engineering Industrial Research Chair Grant No. UNSPECIFIEDNSERC IRCPJ 349527-05.
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 137 • Issue 6 • June 2011
Pages: 432 - 440
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Nov 8, 2009
Accepted: Sep 25, 2010
Published online: Oct 26, 2010
Published in print: Jun 1, 2011
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