Modelling residual value risk through ontology to address vulnerability of PPP project system. (October 2018)

• Record Type: Journal Article
• Authors: Yuan, Jingfeng; Li, Xuan; Chen, Kaiwen; Skibniewski, Mirosław J.
• Is Part Of: Advanced engineering informatics. Volume 38(2018)
• Page Start: 776
• Page End: 793
• Publication Date: 2018-10
• Subjects: Ontology -- PPP projects -- Residual value risk -- Knowledge management; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2018.10.009
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: A Residual Value Risk framework in PPP addressing the vulnerability is proposed. An ontology-based knowledge modeling for RVR management is proposed. RVR ontology model can be used to visualize and manipulate various representations. Many rules are identified to express the tacit knowledge and monitor RVR in model. Abstract: For facilitating the management of Residual Value Risk (RVR) in Public Private Partnership (PPP) projects, an ontology-based model is established to describe the generation process and complex relationships of RVR. An ontology-based approach is proposed to analyze the RVR in PPPs, which is a framework addressing the vulnerability and a knowledge-based modeling for RVR management. The RVR ontology model is composed of class of Project, Risk, and Vulnerability, as well as taxonomy of risk factors for risk sources (RS), risk events (RE), risk consequences (RC), exposure (V1), resilience (V2) and sensitivity (V3). Meanwhile, different relationships among taxonomies, classes and individuals are expressed in model. Moreover, the object properties for class project and the object properties of inherited/non-inherited relationships are defined. Meanwhile, project-based, risk-based, and vulnerability-based datatype property are further described. Then a real individual is established by using the ontology editing software Protégé. The proposed RVR ontology model can be used to visualize and manipulate various representations in RVR management as well as to implement the work of risk reasoning and analyzing. The proposed RVR ontology framework provides a useful framework to systematize different knowledge of RVRs in PPP projects, in which the related knowledge can be described clearly and effectively. Moreover, the proposed framework can enhance data process function and improve the analysis of RVR probability and vulnerability in PPP projects through sharedness and transferability of RVR knowledge provided by ontology-based RVR model for different stakeholders in PPP projects.