Search results

In comparison to other countries, power generation in Sub-Sahara Africa is poor. Public–private partnership (PPP) model has become increasingly popular for addressing infrastructural challenges, especially in the power sector. The purpose of this study is to evaluate and classify the factors that influence public sector involvement in Ghanaian PPP power projects.

Using purposive and snowball sampling techniques, questionnaires were used to gather responses from experts in the PPP power sector in a two round Delphi survey. Analytical tools adopted were descriptive statistics, mean score ranking, Cronbach’s alpha and factor analysis.

The most significant factors that influence public sector involvement in PPP power projects were: achieving improved value for money; access to additional capital; increased certainty of projects; greater efficiency of project delivery services; and improved ability to deliver new infrastructure. From factor analysis, the four components were: value for money and efficiency; capital and skills; innovation and technology; and project delivery.

Government bodies in the power sector will benefit from the findings, as it would aid them develop policies that would strengthen regulatory structures as well as institutions.

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.

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.

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%.

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.

This study aims to investigate the effects of moral hazard on quality and satisfaction of public–private–partnership (PPP) construction projects in Ghana.

After undertaking a literature review, questionnaires were used to elicit responses from respondents. Population consisted of quantity surveyors, project managers, procurement officers, consultants, public agency officers involved in PPP projects, private partners and contractors. A total of 211 questionnaires were received from 250 distributed. Purposive and snowballing sampling techniques were adopted. Analytical tools were Cronbach’s alpha for testing reliability, regression, mean score ranking and relative importance index.

Reduced mutual trust and respect, poor clarity of project objectives; consequence on decision-making; less effective construction process; and increased construction risks were the significant effects of moral hazard on satisfaction of PPP construction projects. Value-based effects; manufacturer-based effects; product-based effects; user-based effects; and transcendent-based effects were the significant effects of moral hazard on quality of PPP construction projects.

Construction stakeholders involved in delivering PPP projects ought to take note of the findings and recommendations arising. Further studies should explore the effects on other project performance indicators apart from satisfaction and quality.

This paper extends knowledge in the area of exploring the effects of moral hazard on PPP project satisfaction and quality. The findings are beneficial to both academia and industry practitioners.

The 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.

Data 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.

A 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.

The 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.

Regarding 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.

This study aims to identify the critical success factors of public private partnership (PPP) power projects in Ghana and further evaluates the most significant critical success factors (CSFs) influencing both the public and private sector participation in PPP power projects.

Ranking-type Delphi survey in two rounds was conducted to establish a comprehensive list of critical success factors of PPP power projects. Using purposive and snowball sampling techniques, experts were targeted for the Delphi survey. Mean score ranking, Cronbach’s alpha coefficient and Kendall’s concordance were used for analysis.

From the list of 37 critical success factors, 9 CSFs were deemed to be extremely significant. The five topmost CSFs were as follows: shared authority, trust and communication between public and private sectors; necessity of power project; debt guarantee to enable private partner to raise funds from the local or international financial markets; appropriate risk allocation and risk sharing; and thorough and realistic assessment of cost, projections and benefits.

The CSFs identified and prioritized in this study have the propensity to trigger policy development towards the PPP power sector in Ghana and developing countries that shares similar context. This is because the study has wide implications for financing, politics, procurement, regulations, legal and capacity building.

The purpose of this paper was to first identify and then model the impact of critical success factors (CSFs) of public–private partnership (PPP) power projects.

Review of empirical literature came out with 20 CSFs which were ranked by experts and industry practitioners through a two-round Delphi questionnaire survey.

These CSFs were grouped into CSF groups (CSFGs) using component analysis, and they served as the input variables for fuzzy analysis. The six components were collaboration and transparency, guarantee and permits, socio-political support, expected profitability, technical feasibility and risk allocation (RA). Overall success index of PPP power projects in Ghana was 5.966 and showed there is high impact of CSFGs on project success. Fuzzy analysis also confirmed RA as the most significant CSFG.

The model developed can serve as a multi-dimension CSF framework that can be used as a success attainment tool for PPP power projects. For policy developers and stakeholders, the model serves as a pointer to issues which the government/public sector must focus on to attract huge investments from the private sector in the power sector.

In the past few years, the public–private partnership (PPP) model has become increasingly popular in the infrastructure projects of developing countries, especially in the power sector. The purpose of this study is to ascertain the motivations for engaging in PPP power projects in Ghana by comparing the public and private sectors.

Questionnaires were used to elicit responses from respondents using a two-round Delphi survey. Mean score ranking was used to rank the motivation factors, while reliability analysis was conducted using Cronbach alpha coefficient, and level of agreement was tested using Kendall’s concordance. One-sample t-test assessed the relative significance of these motivation factors.

For the public sector, the topmost motivations were achieving improved value for money; access to additional capital; increased certainty of projects; greater efficiency of project delivery services; and improved ability to deliver new infrastructure. For the private sector, the topmost motivations were obtaining of investment support; improvement in private sector’s international image; synergy with public sector; sharing of risks; and gaining of profits.

The findings of this study will lead to increased knowledge on the motivation factors for the public and private sectors engaging in PPP power projects in Ghana.

The output of this research contributes to the checklist of motivation factors for engaging in PPP power projects and contributes to the development of PPP practice.

This paper aims to evaluate the risk factors and determines the overall risk level (ORL) of public-private-partnership (PPP) power projects in Ghana using fuzzy synthetic evaluation methodology (FSEM).

In this paper review of literature led to the development of a 67-factor risk list which was ranked by experts and industry practitioners through a questionnaire survey.

These factors were grouped into principal risk factors (PRFs) using component analysis and they served as the input variables for fuzzy analysis. The seven components were: Contract and Payment risks, Environmental risks, Financial and Cost risks, Legal and Guarantee risks, Operation risks, Socio-Political and Performance risks (SPR) and Tender and Negotiation risks. Study showed that the ORL of Ghanaian PPP power projects is high implying they are risky to both the public and private sectors. Fuzzy analysis also confirmed SPR as the most critical principal factor.

This study is significant and demonstrates that fuzzy methodology can be used as a useful risk evaluation tool and risk assessment framework for private investors, policy makers and public sector.

Demand for private investment in infrastructure, notably in the power sector remains high, and this is anticipated to expand with the passage of time. Very little research currently exists on the power sector and specifically the private sector influencing factors (PSIFs) for entering into public–private partnerships (PPPs). The purpose of this study is to explore influencing factors for private sector participation in PPP power projects in Ghana.

Using purposive and snowball sampling techniques, questionnaires were used to gather responses from experts in the PPP power sector domain in a two-round Delphi survey. Reliability analysis was conducted using Cronbach’s alpha coefficient and level of agreement tested using Kendall’s concordance. Mean score ranking, analysis of variance (ANOVA) and Chi-square test were the main analysis conducted on the influencing factors.

The most significant PSIFs were: obtaining of investment support; improvement in private sector’s international image; synergy with public sector; sharing of risks; and gaining of profits. From ANOVA results, all the influencing factors had no significant different perception between the number of years in PPP practice and the motivations for the private sector entering into PPP power projects. Using Chi-square, the association between the variables indicated they were statistically significant.

The findings in this study are significant for multinational power generation firms that seek to enter the Ghanaian energy sector to help fill the generation gap and deficit.

The output of this research contributes to the checklist of influencing factors for private sector participation in PPP power projects and enhances the development of PPP practice.

In comparison to other countries, power generation in Sub-Saharan Africa is poor. The demand for power has surged in recent times and continues to increase at a fast rate. The public–private partnership (PPP) model has been identified as an option to address the challenges in the power sector. The purpose of this research paper is to critically explore the reasons for entering into PPP power projects in Ghana by the public and private parties.

Questionnaires were used to elicit responses from respondents using a two-round Delphi survey. From 60 respondents contacted in round one, 48 responses were obtained, and these 48 respondents further took part in round two. Mean score ranking was used to rank the reasons for entering into PPP power projects, while analysis of variance (ANOVA) was run to test significant difference in perceptions among the respondents.

From round 2 of the Delphi survey, the significant reasons for public sector entering into PPP power projects were as follows: achieving improved value for money, access to additional capital, increased certainty of projects and greater efficiency of project delivery services. For private sector, most significant reasons were as follows: obtaining of investment support, improvement in private sector’s international image and synergy with public sector. From ANOVA analysis, there were significant different perceptions among some of factors on the respondent profile variables and the reasons for entering into PPP power projects, while other factors did not have significant different perception.

Significant reasons for both public and private sectors identified would be incorporated by the government when PPP policy guidelines and laws are reviewed. This will aid in the effective implementation of PPP for power projects.