Optimum risk allocation model for construction contracts: fuzzy TOPSIS approach

Risk allocation, a responsibility-sharing scheme for each party in a risk management process, is an important decision-making process for project success. Although previous studies have discussed risk allocation extensively, no comprehensive quantitative modeling approach for risk allocation exists....

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Bibliographic Details
Published inCanadian journal of civil engineering Vol. 39; no. 7; pp. 789 - 800
Main Authors KHAZAENI, Garshasb, KHANZADI, Mostafa, AFSHAR, Abas
Format Journal Article
LanguageEnglish
Published Ottawa, ON NRC Research Press 01.07.2012
National Research Council of Canada
Canadian Science Publishing NRC Research Press
Subjects
Analysis
Applied sciences
Building
Buildings. Public works
Computation methods. Tables. Charts
Construction industry
Contracts
Decision making
Exact sciences and technology
Fuzzy algorithms
Fuzzy logic
Fuzzy sets
Fuzzy systems
imputation du risque, gestion du risque, gestion des risques dans les contrats, prise de décision multicritère, TOPSIS
Management
Methods
Project management. Process of design
risk allocation, risk management, contract risk management, multi criteria decision making, TOPSIS
Risk management
Structural analysis. Stresses
Canada
Multicriteria analysis
Decision making
Project management
Fuzzy set
Risk management
Responsibility
Application
Contract
Modeling
Construction industry
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Summary:Risk allocation, a responsibility-sharing scheme for each party in a risk management process, is an important decision-making process for project success. Although previous studies have discussed risk allocation extensively, no comprehensive quantitative modeling approach for risk allocation exists. Such a model, specific for contract negotiation, would conduct authorities through the risk allocation process to determine the best risk-bearing participant. The purpose of this paper is to provide a quantitative model for the risk allocation process. This model should support decision making in risk management in a way that addresses the concerns of inappropriate risk allocation. Because linguistic principles and qualitative expert knowledge are the essential ingredients of any risk allocation process, the modeling scheme utilizes fuzzy set theory, which incorporates the quantification and reasoning of natural language.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0315-1468
1208-6029
DOI:10.1139/l2012-038