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

Authors :
Lina, Wang
Zeshui, Xu
Source :
Journal of Intelligent & Fuzzy Systems. 2021, Vol. 41 Issue 1, p1173-1191. 19p.
Publication Year :
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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
41
Issue :
1
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
152233469
Full Text :
https://doi.org/10.3233/JIFS-210101