Quantitative risk allocation approach in public-private partnership projects

Thesis (PhD. (Civil Engineering))

Bibliographic Details
Main Author: Valipour, Alireza
Format: Thesis
Language:English
Published: Universiti Teknologi Malaysia 2024
Subjects:
Online Access:https://openscience.utm.my/handle/123456789/1318
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author Valipour, Alireza
author_facet Valipour, Alireza
author_sort Valipour, Alireza
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description Thesis (PhD. (Civil Engineering))
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institution Universiti Teknologi Malaysia - OpenScience
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spelling oai:openscience.utm.my:123456789/13182024-08-26T17:57:00Z Quantitative risk allocation approach in public-private partnership projects Valipour, Alireza Joint ventures Business—Mathematical models Risk assessment—Research Thesis (PhD. (Civil Engineering)) Risk allocation is an important factor in risk management to ensure successful achievement of the implementation of Public-Private Partnership projects (PPP). Several PPP projects have failed to meet budget, deadlines, and quality inspection. There are 327 unsuccessful PPP projects around the world and Malaysia is the second highest in East Asia with 22 failed projects. Inappropriate risk allocation has led to adversarial relationships between contracting participants and has consequently increased project cost, time and poor quality. Thus, it is very important for the public and private sector to choose a fair risk allocation in order to make strategic decisions. The aim of this study was to develop an optimal quantitative approach to enhance the equitable risk allocation in PPP projects. This study presents a Fuzzy Analytic Network Process model for equitable risk allocation which converts linguistic principles and solves the problem of independence and feedback between criteria and barriers using Analytic Network Process (ANP) method. Objective functions are then developed to minimize the total time, the cost of the project and maximize the quality while satisfying risk threshold constraints. The combinatorial nature of the risk allocation problem describes a multi-objective situation that can be simulated as a knapsack problem (KP). The formulation of the KP is described and solved by applying genetic algorithm. A total of 42 risks was identified and evaluated. The finding of this study shows "construction completion delay” was the most important risk with the highest rank. Finally, of 42 significant risks, 16 was allocated to the public sector, 11 were allocated to the private sector and 15 were shared between public and private sector as the best package of shared risks. The results of this investigation can be implemented by the government to enhance risk allocation process which may encourage the participation of the private sector through better risk allocation. As a conclusion, a new method has been developed regarding equitable quantitative risk allocation. It helps the project owners as well as contractors and subcontractors to better manage risk, cost and time savings and at the same time improve the overall quality of PPP projects Faculty of Civil Engineering 2024-08-21T15:08:53Z 2024-08-21T15:08:53Z 2015 Thesis Dataset https://openscience.utm.my/handle/123456789/1318 en application/pdf application/pdf application/pdf application/pdf Universiti Teknologi Malaysia
spellingShingle Joint ventures
Business—Mathematical models
Risk assessment—Research
Valipour, Alireza
Quantitative risk allocation approach in public-private partnership projects
title Quantitative risk allocation approach in public-private partnership projects
title_full Quantitative risk allocation approach in public-private partnership projects
title_fullStr Quantitative risk allocation approach in public-private partnership projects
title_full_unstemmed Quantitative risk allocation approach in public-private partnership projects
title_short Quantitative risk allocation approach in public-private partnership projects
title_sort quantitative risk allocation approach in public private partnership projects
topic Joint ventures
Business—Mathematical models
Risk assessment—Research
url https://openscience.utm.my/handle/123456789/1318
work_keys_str_mv AT valipouralireza quantitativeriskallocationapproachinpublicprivatepartnershipprojects