Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103367
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Title: Modelling capability-based risk allocation in PPPs using fuzzy integral approach
Authors: Mazher, KM 
Chan, APC 
Zahoor, H
Ameyaw, EE
Edwards, DJ
Osei-Kyei, R
Issue Date: Sep-2019
Source: Canadian journal of civil engineering, Sept 2019, v. 46, no. 9, p. 777-788
Abstract: Appropriate risk allocation and sharing are significant critical success factors for public-private partnership projects, but evidence suggests that poor risk allocation practices prevail. This signifies the need to develop a robust model for assisting stakeholders in risk allocation decision-making. A non-additive fuzzy integral based multiple attribute risk allocation decision approach is proposed to effectively aggregate each stakeholder’s risk management capability assessment on accepted risk allocation principles that are derived from qualitative judgements and experience based knowledge of experts. Data collected from privately financed and developed power and transport infrastructure projects in Pakistan are used to demonstrate and validate the model for key risk factors that exhibit variable risk allocation preferences. Comparison of results with an additive aggregation approach confirms suitability of the adopted methodology as it performs better when modelling risk allocation preferences of experts due to its ability to handle interdependencies in the risk allocation criteria. Apparently, the allocation and sharing of key risks is significantly influenced by market, sector and project contexts.
Keywords: Decision-making model
Fuzzy integral
Fuzzy set theory
Infrastructure public-private partnerships
Risk allocation
Publisher: Canadian Science Publishing
Journal: Canadian journal of civil engineering 
ISSN: 0315-1468
EISSN: 1208-6029
DOI: 10.1139/cjce-2018-0373
Rights: Copyright remains with the author(s) or their institution(s). Permission for reuse (free in most cases) can be obtained from RightsLink (http://www.nrcresearchpress.com/page/authors/services/reprints).
This is the accepted version of the work. The final published article is available at https://doi.org/10.1139/cjce-2018-0373.
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