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The risk evaluation of PPP projects: A technique based on probabilistic linguistic terms with weakened hedges

Authors :
Wang Lina
Xu Zeshui
Source :
Journal of Intelligent & Fuzzy Systems. 41:1173-1191
Publication Year :
2021
Publisher :
IOS Press, 2021.

Abstract

Risk management is a significant part of the success of a public-private partnership (PPP) project. There are four phrases for the process of risk management: Constructing a risk management environment, identifying risk factors, evaluating risk factors, and allocating risk factors. After identifying risk factors, it is imperative to analyze and evaluate critical risk factors, which can help participants formulate strategies to allocate risk factors, and thus alleviate the possible adverse results. The objectives of analyzing and evaluating risk factors focus on two aspects: The possibilities of risk occurrence and the degrees of risk loss. On behalf of determining the critical risk factors effectively, we take the probability degree and linguistic expressions into consideration to manifest experts’ perspectives. We consider critical risk factors in terms of the probabilistic linguistic terms with weakened hedges from the evidential reasoning approach view. The linguistic terms with weakened hedges are applied to express the degree of risk risk loss, and the possibilities of risk occurrence collect from the probabilities of linguistic terms with weakened hedges. First, the commonality function and plausibility function are applied to correct the possibilities of risk occurrence for linguistic terms with weakened hedges. Next, we build a risk evaluation model from experts’ risk propensity and risk perceptions. Moreover, a case study of the risk analyzing and evaluating process of a PPP project is applied to illustrate the availability and effectiveness of the proposed model. We contrast the introduced model with other approaches. Finally, the advantages of this model intend to improve the linguistic terms with weakened hedges for the probabilistic linguistic terms with weakened hedges and evaluate risk factors considering the evidence reasoning approach.

Details

ISSN :
18758967 and 10641246
Volume :
41
Database :
OpenAIRE
Journal :
Journal of Intelligent & Fuzzy Systems
Accession number :
edsair.doi...........555b2d84c0c69a1e7ed4dae139e1389e
Full Text :
https://doi.org/10.3233/jifs-210101