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

Effah Ernest Ameyaw, Albert P C Chan

Research output: Contribution to journalArticlepeer-review

61 Citations (Scopus)


Appropriate risk allocation (RA) between public and private sectors according to their risk management (RM) capabilities is crucial for the success of public-private partnership (PPP) projects. The RA process in PPP water projects is examined, and a methodology based on fuzzy set theory is outlined with RA principles that can be used by public-private participants to arrive at fair RA decisions. Empirical data based on an industry-wide three-round Delphi questionnaire survey is used in this study to outline the methodology. The fuzzy set theory is employed for the RA analysis because it deals well with the complex multi-criteria problem of, and precisely accounts for the fuzziness inherent in human cognitive process that characterize, RA decision-making. Five risk factors are evaluated on each RA principle, analysed and assigned between the public and private sectors. The results show that it is appropriate to allocate risks according to both sectors’ RM capability to manage them, using established RA principles and fuzzy set theory. The methodology renders the decision-making process more systematic and practical because the fuzzy theory approach allows decision makers to express their evaluations of both sectors’ RM capabilities in descriptive qualitative terms. The results should assist public clients to establish efficient RA strategies and develop balanced RA schemes for PPP contracts, with a view to achieving a mutually acceptable RA with the private sector.

Original languageEnglish
Pages (from-to)187-208
Number of pages22
JournalConstruction Management and Economics
Issue number3
Early online date7 May 2015
Publication statusPublished - 2015
Externally publishedYes


  • Fuzzy set theory
  • public-private partnership
  • risk allocation
  • water supply

ASJC Scopus subject areas

  • Management Information Systems
  • Building and Construction
  • Industrial and Manufacturing Engineering


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