Evaluation of risk factors in Ghanaian public-private-partnership (PPP) power projects using fuzzy synthetic evaluation methodology (FSEM)

Kukah, Augustine Senanu Komla; Owusu‐Manu, De‐Graft; Badu, Eric; Edwards, David John

doi:10.1108/bij-09-2021-0533

Cited by 18 publications

(8 citation statements)

References 57 publications

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“…There was no significant relationship between TNRp) and socio-political and TNRs. Private investors are mandated to include in their feasibility analysis how their plant would be fed into the national grid (Kukah et al , 2022d, e). The siting and location of the power plant is therefore crucial in mitigating any challenges that may arise due to transmission failure (Ameyaw and Alfen, 2017).…”

Section: Discussionmentioning

confidence: 99%

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Structural equation model (SEM) for evaluating interrelationships among risks inherent in Ghanaian public–private partnership (PPP) power projects

Kukah

Owusu‐Manu

Badu

et al. 2022

ECAM

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PurposeThe demand for power has surged in recent times and continues to increase yearly. In comparison to developed countries, the power industry’s risks, especially in piblic–private partnership (PPP) projects, are more complex and essential in developing countries. Appreciating the inter relationship among these risk factors is crucial. However, there exist no studies developing quantitative models to explain how various PPP power risk factors influence each other, especially in developing countries like Ghana. This study aims to investigate and model the relationship, the probability of occurrence and severity of impact of PPP power risk factors in Ghana.Design/methodology/approachData were collected through ranking type questionnaire in a two-round Delphi survey with 48 respondents using purposive and snowball sampling techniques. partial least squares structural equation modelling (PLS-SEM) was used for analysis of data.FindingsA model was developed to investigate the influence the risk factors inherent in PPP power projects have on each other. Validity of the model was tested based on the data collected. PLS-SEM results indicated the various relationships and interdependencies the risk factors had on each other considering their probability and severity. Both significant and insignificant levels of relationships were found among the various risk factors.Practical implicationsThe SEM that was developed to assess the relationships among the risk factors has great value for policy makers in the energy sector, industry practitioners, researchers and industry practitioners. Strategies can be mapped out to mitigate and effectively allocate the risks with the high interdependencies.Originality/valueRegarding the quantitative impact of the interrelationship among risk factors in PPP power projects, the findings of this research are arguably the first to be presented for the construction sector and contribute to knowledge on PPP practice and further has implications toward achieving power sector risk mitigation.

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Section: Discussionmentioning

confidence: 99%

“…Questionnaire survey is a systematic approach to data collection based on a sample (Darko et al , 2018). It has also seen wide usage in PPP and risk management studies (Owusu-Manu et al , 2021; Kukah et al ., 2022d, e).…”

Section: Methodsmentioning

confidence: 99%

Structural equation model (SEM) for evaluating interrelationships among risks inherent in Ghanaian public–private partnership (PPP) power projects

Kukah

Owusu‐Manu

Badu

et al. 2022

ECAM

Self Cite

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“…Fuzzy synthetic evaluation (FSE) promotes the evaluation of diverse responses for decision-making based on different set of ranking criteria [43]. Previous studies such as Nguyen and Macchion [42] and Kukah, et al [44] mentioned that FSE is appropriate the analysis of diverse factors (or criteria) in different fields. Within the construction project management literature, Xu, et al [45], Wuni, Shen and Osei-Kyei [35] and Ekanayake, et al [46] stated that FSE establishes weights and membership functions that ensures objective analysis of matters associated with the management of construction firms and projects.…”

Section: Analysis Of Datamentioning

confidence: 99%

Fuzzy Analysis of Financial Risk Management Strategies for Sustainable Public-Private Partnership Infrastructure Projects in Ghana

Akomea-Frimpong,

Jin,

Osei-Kyei

2024

Preprint

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Public-private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs towards attainment of sustainable, climate resilience and zero carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries like Ghana where private investment inflow has plummeted due to COVID-19 recession and poor project performance. Thus, this study aims at assessing the key financial risk management strategies in ensuring sustainable PPP infrastructure projects in Ghana. The study utilised primary data from PPP practitioners in Ghana solicited through survey questionnaires. Factor analysis, mean scores and fuzzy synthetic analysis are the data analysis techniques for this study. The results revealed sustainable and green funding models, effective cost reduction initiatives, competent team with committed leadership, and emerging technologies and regulations constitute the key strategies to manage financial risks of sustainable PPP infrastructure projects. Although, future studies must expand the scope of data gathering, the findings of the study enrichen the theoretical understanding of financial risks in sustainable investments in PPP infrastructures. Relevant remedies that will aid the development of practical financial risk management guidelines are provided in this study for PPP practitioners.

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“…The public sector sponsor, according to Xu et al (2010), keeps track of project risks in a risk register that describes hazards relevant to each stage of the project, the likelihood of each risk event occurring and an estimate of the financial consequences. The public sector sponsor and the chosen private bidder would agree on a risk distribution strategy at the conclusion of the discussions, assigning risks to the party best suited to handle them (Owusu-Manu et al , 2018b; Kukah et al , 2022d). The public sector sponsor would typically take on some risks, pass on others to the commercial consortia and share others with it.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To begin with, electricity makes use of high technological components that are custom-built (Kemausuor and Ackom, 2017). Once deployed in a remote location, there are specific connectivity and logistical difficulties encountered (Kukah et al , 2022c; Kukah et al , 2022d). The power sector includes technically demanding projects that typically include many subprojects and necessitate the incorporation of many technical fields (Carbonara and Pellegrino, 2018).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy quantitative risk allocation model (FQRAM) to guide decision-making on risk allocation in Ghanaian public-private partnership (PPP) power projects

Kukah

Owusu‐Manu

Badu

et al. 2023

JFMPC

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Purpose Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana. Design/methodology/approach A total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model. Findings The model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%. Originality/value To the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.

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Evaluation of risk factors in Ghanaian public-private-partnership (PPP) power projects using fuzzy synthetic evaluation methodology (FSEM)

Cited by 18 publications

References 57 publications

Structural equation model (SEM) for evaluating interrelationships among risks inherent in Ghanaian public–private partnership (PPP) power projects

Structural equation model (SEM) for evaluating interrelationships among risks inherent in Ghanaian public–private partnership (PPP) power projects

Fuzzy Analysis of Financial Risk Management Strategies for Sustainable Public-Private Partnership Infrastructure Projects in Ghana

Fuzzy quantitative risk allocation model (FQRAM) to guide decision-making on risk allocation in Ghanaian public-private partnership (PPP) power projects

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