Abstract
Risk identification is the primary link and a significant basis for risk management. It is difficult to identify critical risk factors (CRFs) in terms of the uncertainty, diversity, and incompleteness of risk factors. The various preferences for different stakeholders could cause different identification results. Hence, we propose the weakened hedged probabilistic linguistic preference relation (WH-PLPR) to identify CRFs from the stakeholders’ preferences. For the WH-PLPR, checking and revising individual consistency is the basic part of the decision support model. Hence, the main contribution of this paper is studied in three parts: First, the concept of the WH-PLPR is given. Some consistency concepts, namely, weakened consistency, additive consistency, and satisfactory consistency of the WH-PLPR are defined. After that, the algorithms for improving the consistency of the WH-PLPR are studied. Then, we identify CRFs from stakeholders’ perspectives with the WH-PLPR information. A case study of a PPP project illustrates the utility and effectiveness of the proposed model. A sensitivity analysis of the WH-PLPR is introduced to illustrate the focus on consistency in the WH-PLPR, as well as the comparison of the consistency of the WH-PLPR with the linguistic hedged preference relations (LHPR) and the probabilistic linguistic preference relations (PLPR), which illustrates that weak consistency is the basis for satisfactory consistency. Moreover, the ranking results of CRFs show robustness for WH-PLPRs reaching satisfactory consistency.
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Acknowledgements
This work was supported by the Natural Science Foundation of China (No. 72071135) and the Scientific Research Foundation of Graduate School of Southeast University (No. YBPY2034).
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A Preference matrix
A Preference matrix
(1) WH-PLPRs from Expert 1
(2) WH-PLPRs from Expert 2
(3) WH-PLPRs from Expert 3
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Wang, L., Xu, Z. & Hao, Z. Consistency measure of the WH-PLPR under the risk identification of PPP projects. Int. J. Mach. Learn. & Cyber. 13, 3441–3461 (2022). https://doi.org/10.1007/s13042-022-01606-7
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DOI: https://doi.org/10.1007/s13042-022-01606-7