A risk allocation model among the elements of freeway projects in public-private partnership (PPP) method using integrated fuzzy multi-criteria decision-making techniques

Jokar, Ebrahim; Aminnejad, Babak; Lork, Alireza

doi:10.1080/14488353.2022.2083288

Cited by 2 publications

(8 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…{Please insert here Figure 2} Moreover, Fig. 3 reports the trend of criteria weights from proposed approach and Jokar et al [29]' study. This figure shows that both approaches confirmed that the 11 th criterion is the most important indicators, which is related to the complications of obtaining licenses.…”

Section: Executionmentioning

confidence: 99%

“…{Please insert here Table 9} Finally, the proposed method is compared with two another approach. In this respect, these methods are related to simple additive weighting (SAW) method and fuzzy-TOPSIS methodology from Jokar et al [29]' study. The computation results and the ranking of the alternatives with these approaches are shown in Table 10.…”

Section: Executionmentioning

confidence: 99%

“…In this section, the comparative analysis based on some comparison factors such as uncertainty modeling, last aggregation approach, group decision analysis, criteria weights determination, and experts' weight computations from Gitinavard et al [36]' study are provided to represent the advantages of the proposed approach regarding the SAW methodology and Jokar et al [29]' study. However, the comparison reports are explained in details as follows:…”

Section: Comparative Analysismentioning

confidence: 99%

“… Uncertainty modeling: This factor is related to a considered process for copping with imprecise information. The proposed of this study like Jokar et al [29]' study consider fuzzy set theory to cover the uncertainty situation.  Last aggregation approach: This factor in concerning with data loss and the proposed approach of this paper unlike two other approaches developed the proposed approach based on last aggregation process.…”

Section: Comparative Analysismentioning

confidence: 99%

“…Moreover, Tian et al [28] developed a picture fuzzy hierarchical VIKOR method to sustainable assessment of water environment treatment-3P projects. In addition, Jokar et al [29] tailored a fuzzy risk management framework by considering the fuzzy AHP, fuzzy TOPSIS, and fuzzy DEMATEL to determine the critical and common risks and assigning each risk to each partner in 3P projects.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An intuitionistic fuzzy weighting and ranking model to evaluate the financing challenges of urban development with public-private partnership projects

2022

View full text Add to dashboard Cite

In today's world, one of the most important and basic parts in urban developments is related to the creation and development of a projects with an infrastructure nature. Meanwhile, these development projects can implement under the public-private partnership (3P) projects that financial challenges are the main factor that can affect the success of the project. In this paper, a novel intuitionistic fuzzy soft computing-based ideal solution based on criteria importance determination and experts' weights computations is tailored. In this sake, the criteria importance is computed based on presented intuitionistic fuzzy preference evaluation method and also the experts' weights are determined by proposing an intuitionistic fuzzy utility degree technique. Moreover, the proposed approach is developed based on last aggregation process to decrease the data loss and cover the preferences judgments of experts thorough the method execution. Finally, a real case study is provided to indicate the process of the method execution and assess the effective criteria in 3P projects of urban development. In addition, a comparative assessment and a sensitivity analysis is considered to show the applicability and sensitiveness/robustness of the proposed approach, respectively.

show abstract

Section: Executionmentioning

confidence: 99%

Section: Executionmentioning

confidence: 99%