A Bayesian Belief Network Model for Assessing Financial Risk in PPP Healthcare Projects


Aslantas A., Dikmen I., BİRGÖNÜL M. T.

Sustainability (Switzerland), vol.17, no.10, 2025 (SCI-Expanded, SSCI, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 10
  • Publication Date: 2025
  • Doi Number: 10.3390/su17104635
  • Journal Name: Sustainability (Switzerland)
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Aerospace Database, Agricultural & Environmental Science Database, CAB Abstracts, Communication Abstracts, Food Science & Technology Abstracts, Geobase, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Keywords: Bayesian Belief Network, feasibility, financial risk, healthcare, PPP hospital projects, risk assessment, Turkiye
  • Middle East Technical University Affiliated: Yes

Abstract

Public-Private Partnerships (PPPs) are essential for accelerating sustainable development as they combine public goals with private sector efficiency, leading to improved service delivery and less financial burden on governments. It is a project delivery model based on long-term contractual arrangements, where the private sector provides services, including engineering, construction, and operation of public infrastructure, taking financial risks. At the project development stage, the private sector carries out a financial risk assessment to ensure economic returns from a PPP investment and secure funding for the project. In this paper, we present a Bayesian Belief Network (BBN)-based model that can be used to assess financial risks, particularly the level of profitability in PPP projects. The proposed model was developed considering PPP projects in the healthcare sector and validated using data on PPP hospital projects in Turkiye. The findings demonstrate that the BBN model is useful for capturing the interdependencies between risks, resulting in different scenarios, and provides effective decision support for investors in PPP projects. This study contributes to the literature by offering a novel application of probabilistic risk assessment to provide a better understanding of interrelated risk factors that may result in different financial scenarios. The model can be used by the private sector to assess risk, estimate profitability, and develop risk mitigation strategies in PPP healthcare projects, which may increase project success, contributing to social, environmental, and economic sustainability.