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<p>These days, many governments address the challenges of funding and its scarcity by implementing various schemes, such as Public-Private Partnerships (PPPs), in enormous infrastructure projects. This study proposes a system for estimating the risks of PPP infrastructure projects to assist decision-makers. Additionally, this study employs fuzzy logic to tackle the uncertainty surrounding the challenges of PPPs by incorporating a novel adaptive integration of different risk assessment techniques. Thus, this integration serves as a bridge between industry implementation and academic insights. Previous research identified thirty-one risk factors affecting PPP infrastructure projects. Consequently, a survey was distributed to experts to evaluate the probability and impact of each risk factor. Six innovative steps are applied to assess risk in this research. First, the number of factors is reduced using the Relative Importance Index method. Second, Exploratory Factor Analysis uses a statistical software package to generate a correlation matrix for the factors. Following this, the analytical hierarchy process (AHP) is applied to calculate the weights of the risk factors. Next, another questionnaire is developed to create a pairwise comparison matrix for establishing the weights of the factors. Subsequently, a fuzzy model is constructed. This model was validated using the risk assessment model of the Domestic Wastewater Treatment (DWWT) PPP project in Egypt. Furthermore, the developed model was used for a case study involving the Light Rail Transit (LRT) project in Egypt to assess risks. The validation results confirmed that the model effectively calculates risk assessments.</p>

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Assessing Risk Factors in Infrastructure Public-Private Partnerships

  • 期刊论文

  • 发表日期：

    2025年7月3日

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  • Ahmed Ehab,
  • Khaled Saleh,
  • Mohamed Zakaria,
  • Ahmed Monier

摘要

These days, many governments address the challenges of funding and its scarcity by implementing various schemes, such as Public-Private Partnerships (PPPs), in enormous infrastructure projects. This study proposes a system for estimating the risks of PPP infrastructure projects to assist decision-makers. Additionally, this study employs fuzzy logic to tackle the uncertainty surrounding the challenges of PPPs by incorporating a novel adaptive integration of different risk assessment techniques. Thus, this integration serves as a bridge between industry implementation and academic insights. Previous research identified thirty-one risk factors affecting PPP infrastructure projects. Consequently, a survey was distributed to experts to evaluate the probability and impact of each risk factor. Six innovative steps are applied to assess risk in this research. First, the number of factors is reduced using the Relative Importance Index method. Second, Exploratory Factor Analysis uses a statistical software package to generate a correlation matrix for the factors. Following this, the analytical hierarchy process (AHP) is applied to calculate the weights of the risk factors. Next, another questionnaire is developed to create a pairwise comparison matrix for establishing the weights of the factors. Subsequently, a fuzzy model is constructed. This model was validated using the risk assessment model of the Domestic Wastewater Treatment (DWWT) PPP project in Egypt. Furthermore, the developed model was used for a case study involving the Light Rail Transit (LRT) project in Egypt to assess risks. The validation results confirmed that the model effectively calculates risk assessments.