Risk allocation model for public-private partnership water supply projects in Ghana

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Risk allocation model for public-private partnership water supply projects in Ghana

 

Author: Ameyaw, Effah Ernest
Title: Risk allocation model for public-private partnership water supply projects in Ghana
Degree: Ph.D.
Year: 2014
Subject: Water-supply -- Management -- Ghana.
Construction industry -- Risk management.
Public-private sector cooperation.
Risk assessment.
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Building and Real Estate
Pages: xxix, 413 pages ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2780546
URI: http://theses.lib.polyu.edu.hk/handle/200/7867
Abstract: The last two decades have witnessed a growing trend by governments around the world using the skills and expertise and financial resources of the private sector through public-private partnership (PPP) procurement in delivering public water supply services and infrastructure. Like other countries, the Government of Ghana is turning to the private sector to develop the country's water supply infrastructure, and PPP in the water sector is emerging. Key reasons for adopting this policy are inadequate public funding, the need for improved management and efficiency, growing water demand, and poor asset condition and lack of maintenance. PPPs have diverse modalities including service and management contracts, affermage-leases, concessions, joint ventures and build-operate-transfer (BOT-type) arrangements. In the water industry of low- and middle-income countries, water concessions and BOT contracts are the most popular modalities. PPP water supply projects are a plethora of risk, and the contractual agreements for these projects allocate the risks between the public water utility (government) and the private sector entity. The overall aim of this thesis is to develop a model for successfully allocating risks in PPP water supply projects in Ghana, so that decision-makers can arrive at a fair risk allocation decision. However, the outcome of the study is applicable to other developing countries that share similar characteristics with Ghana. The primary data acquisition tool for this research study is a three-round Delphi questionnaire survey of industry experts from both public and private sectors, with relevant experience in the local water industry and PPP procurement. The expert respondents were selected through purposive sampling and semi-snowballing approaches. Thirty-seven to forty-one PPP experts provided valid responses to various parts of the questionnaire. The panel sizes are justified, given that PPP is at its budding stage in Ghana. Various statistical methods such as arithmetic mean, Cronbach{176}s alpha reliability analysis and factor analysis were used to analyse the obtained data, and the fuzzy synthetic evaluation (FSE) method was subsequently applied for success and risk assessment and risk allocation modelling. Mean score ranking method ranked and prioritized the risk allocation criteria (RAC), critical success factors (CSFs) and critical risk factors (CRFs) associated with PPP water supply projects. This approach established seven important RAC, 14 CSFs and 22 CRFs. Factor analysis generated principal factors for the CSFs. The five critical success factor groups (CSFGs) that ensure successful implementation of water supply projects are Factor 1: Commitment of the partners; Factor 2: Strength of the consortium; Factor 3: Asset quality and social support; Factor 4: Political environment; and Factor 5: National PPP Unit. The CRFs were theoretically categorised into three principal risk factors (PRFs), namely PRF1 Financial and commercial risk, PRF2 Legal and socio-political risk, and PRF3 Technical risk. The proposed model showed that the overall success index (OSI) of the five CSFGs for PPP water projects in Ghana is 6.10, implying that, collectively, the factors are 'very important' and if provided sustained and unremitting attention, would improve the likelihood of successful implementation of PPP water supply projects. Political environment (index = 6.20) is the most critical factor group affecting project success, followed by Asset quality and social support (index = 6.18); National PPP Unit (index = 6.17); Strength of the consortium (index = 6.07); and Commitment of the partners (index = 5.94). The model would aid decision-makers to select the important factors that contribute most significantly to successful implementation of PPP water supply projects, rather than purely relying on qualitative selection of CSFs.
On risk modelling, the fuzzy model showed that the overall risk level of PPP water supply projects is 'high', with an index of 4.78, implying that these projects are risky to the public and private sectors. It, overall, confirmed that PRF1 Financial and commercial risk (index = 4.91) most significantly contributes to the overall risk of PPP water projects, followed by PRF2 Legal and socio-political risk (index = 4.72), and PRF3 Technical risk (index = 4.67). This approach not only aid implementers to determine a project's risk level and high-risk areas in order to develop appropriate countermeasures but also assists private participants (or investors) to select the least risky project. The proposed prototypic fuzzy quantitative risk allocation decision model (FQRADM) for PPP (water supply) infrastructure projects deals with the imprecise and subjective nature of risk allocation decision-making, and handles the simultaneous consideration of the multiple risk allocation criteria and multiple decision-makers. Thus, the model is an eight-tier system, in which outputs of preceding steps are fed into following steps to handle the problems of subjectivity and multi-criteria. The steps include: (i) establish critical risk factors and critical risk allocation criteria (RAC); (ii) define the RAC as input variables (IVs); (iii) compute weighting functions of the IVs; and (iv) evaluate the risk factors against the RAC; (v) establish membership functions of the IVs; (vi) compute the risk carrying capacity indices of the public and private partners; (vii) quantify risk allocation proportions to the public and private partners; and (viii) model output. The output variable of the model is the risk allocation proportions between the government and private partner according to their capabilities to control and manage evaluated risk factors. This risk allocation strategy ensures that both parties have an incentive to manage the risks. Overall, this study could trigger policy development toward PPP practice in Ghana and other developing countries, because these findings have wider implications for legal and regulatory systems, public capacity, financing, public procurement, and politics.

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