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Riesgo: A Knowledge-Based Qualitative Risk Assessment System for PPP Projects

Author(s):
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 4, v. 14
Page(s): 953
DOI: 10.3390/buildings14040953
Abstract:

A successful public-private partnership (PPP) relies heavily on effective risk assessment, given the intricate risk factors and contractual arrangements involved. While quantitative risk assessment methods have received significant attention in the PPP literature, qualitative risk assessment, the sector’s predominant preference, remains underexplored, causing a low level of applicability of academic studies and indicating a noticeable research gap. A qualitative risk assessment tool prototype, Riesgo, is developed in this paper as a customizable, knowledge-based digital risk register incorporating a pre-defined template that guides users using PPP risk factors, compensation and mitigation options, project information requirements, and risk register items. This paper presents the proposed system architecture, explains the research steps adopted in determining the system elements, and delineates the system functions through a use case developed to illustrate the process and information flows. The prototype was verified by 13 PPP experts who employed it for risk assessment, and their feedback was utilized for further development. A validation survey of 21 professionals affirmed Riesgo’s usability and applicability in the industry. The customizable and knowledge-based prototype has the potential to streamline effective risk assessment and guide the users across various PPP phases, such as early risk assessment, feasibility studies, contract preparation, and monitoring.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10773719
  • Published on:
    29/04/2024
  • Last updated on:
    05/06/2024
 
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