Model for predicting the success of public–private partnership infrastructure projects in developing countries: a case of Ghana

ABSTRACT

This paper develops a practical tool for predicting public–private partnership (PPP) project success in developing countries using Ghana as example. The predictive model examines the causal relationship between CSFs and success criteria for PPP projects. First, a conceptual model for PPP projects success was proposed. Second, the theoretical model was tested by means of a questionnaire survey with experienced PPP experts. Using the regression analysis technique, a predictive model for PPP project success was developed. The regression model shows three best predictors of PPP project success in Ghana, these include; appropriate risk allocation and sharing, sound economic policy and right project identification. Various statistical tests including ANOVA, tolerance and variance inflation factor (VIF), homoscedasticity and Durbin–Watson tests confirmed the validity and goodness of fit for the model. The substantive model will enable PPP practitioners including designers, public clients and engineers in Ghana and other neighbouring developing countries particularly sub-Saharan Africa to predict the likely success of their PPP projects prior to their implementations.

KEYWORDS:

• Public–private partnerships
• projects success
• critical success factors
• success criteria
• regression analysis
• Ghana

Acknowledgements

This paper forms part of a research project entitled ‘A best practice framework for PPP implementation for infrastructure development in Ghana’ from which other papers have been produced with different objective/scope but sharing the same background and methodology. The research project described is fully supported by the Hong Kong PhD Fellowship Scheme from the Research Grants Council (RGC) of the Hong Kong Special Administrative Region and The Hong Kong Polytechnic University, Hong Kong.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Albert P. C. Chan http://orcid.org/0000-0002-4853-6440