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

2021 ◽  
pp. 1-19
Author(s):  
Wang Lina ◽  
Xu Zeshui
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Risk Evaluation ◽  
Risk Perceptions ◽  
Evaluation Model ◽  
Risk Propensity ◽  
Linguistic Terms ◽  
Proposed Model ◽  
Evidential Reasoning Approach ◽  
Risk Loss

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 probability 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 intended 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.

scholarly journals Modeling Dynamic Trust and Risk Evaluation Based on High-Order Moments

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Yan Gao ◽  
Zhiyong Dai ◽  
Wenfen Liu
Keyword(s):  
Risk Evaluation ◽  
Hypothesis Test ◽  
Evaluation Model ◽  
High Order ◽  
Direct Trust ◽  
Proposed Model ◽  
Dynamic Trust ◽  
The Stability ◽  
Coefficient Of Skewness ◽  
Filter Mechanism

This paper proposes a dynamic trust and risk evaluation model based on high-order moments. The credibility of an entity is measured with trust degree and risk value comprehensively. Firstly, considering the dynamic and time decay characters of trust, a time attenuation function is defined, and direct trust is further expressed. Subsequently, in order to improve the accuracy of feedback trust, a filter mechanism is constructed to eliminate the false feedback, combining coefficient of skewness with hypothesis test. More importantly, the weights of direct trust and feedback trust are derived subjectively and adaptively with the moments and frequency of direct interactions. Furthermore, risk is evaluated with direct risk and feedback risk, which are obtained by mainly using coefficient of variation and coefficient of kurtosis. Risk value can be used to measure the stability of providing services. Simulation results show that the proposed model not only has high accuracy, but also resists effectively collusive attacks and strategic malicious behaviors.

Schedule Risk Management of Railway Station Project

2014 ◽  
Vol 587-589 ◽  
pp. 1830-1835
Author(s):  
Jian Sun ◽  
Yue Ren Tan ◽  
Wei Xu
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Construction Management ◽  
Risk Evaluation ◽  
Delphi Technique ◽  
Risk Prevention ◽  
Risk Matrix ◽  
Railway Station ◽  
Schedule Risk ◽  
Under Construction

Railway station is a comprehensive transportation hub. Its design and construction is far more complex than common public buildings, so as the construction management. This paper mainly explores the schedule risk management of railway station, including risk factors, risk indentation, risk evaluation and risk management. As many similar projects are under construction, Delphi technique method is most favorable for risk indentation. For risk evaluation, risk matrix method and CIM model are recommended to quantify the schedule risk. In the final part, the paper talks about the management of schedule risk. As schedule risk is abstract and its damage relatively slight, the risk prevention and mitigation are most suitable means.

Study on IT Project Investment Risk Evaluation Based on ANP

2011 ◽  
Vol 63-64 ◽  
pp. 557-560 ◽  
Author(s):  
Bing Sheng Liu ◽  
Hui Yan Ma ◽  
Li Lin
Keyword(s):  
Risk Management ◽  
Empirical Analysis ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Investment Risk ◽  
It Projects ◽  
Project Investment ◽  
It Project ◽  
Risk Evaluation Model

This paper has studied the classification of investment risks in IT projects, and got 5 categories of investment risks, which can be subdivided into 14 kinds. Then established the IT project investment risk evaluation model based on ANP and made empirical analysis on it with Super Decision Software. The results we got offered a reference for IT project investment risk management.

The Risk Evaluation Model of Mining Project Investment Based on Fuzzy Comprehensive Method

2013 ◽  
Vol 295-298 ◽  
pp. 2928-2934 ◽  
Author(s):  
Zuo Gong Wang ◽  
Jie Zheng ◽  
Hui Yang Li
Keyword(s):  
Risk Factors ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Assessment Model ◽  
Investment Risk ◽  
Project Investment ◽  
Comprehensive Method ◽  
Mining Project ◽  
Risk Evaluation Model

Mining project investment has a lot of features, such as long period, slow effect, big capital size, irreversible investment, the numerous and complicated risk factors. Therefore, it is necessary to analyze and evaluate the investment risk before accepting project. On the basis of analyzing the mining project risk factors, establishing the risk evaluation index system, establishing the risk assessment model based on fuzzy comprehensive method, then evaluating the investment risk of mining project quantitatively, which provides the decision-making basis, makes the investment more scientific and safer and reduces the risk of investment.

Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

2020 ◽  
pp. 097674792096322
Author(s):  
Abdolmajid Erfani ◽  
Mehdi Tavakolan
Keyword(s):  
Wind Energy ◽  
Cost Estimation ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Risk Identification ◽  
Energy Investment ◽  
Investment Projects ◽  
Proposed Model ◽  
Energy Projects ◽  
Fuzzy Group Decision Making

The recent increasing trend of investments in wind energy projects to support sustainable development requires an appropriate risk evaluation model to ensure the success of these projects. Early studies focus on opinion and discussion from subject matter experts. However, the expertise level in the subject is varied, and evaluation without considering expert competency can cause biased results. On the other hand, most of the project cost estimation models do not consider uncertainty in all cash flow parameters. In response, this article proposes a model that evaluates risks in wind energy investment projects by considering the knowledge and background of experts. Then, an integrated model of risk evaluation and cost estimation is developed. The model consists of three main stages: risk identification based on a systematic literature review (SLR); risk analysis phase 1 based on a modified fuzzy group decision-making; and risk analysis phase 2 based on a Monte Carlo simulation method. The main advantages of the proposed model are: (a) providing a comprehensive risk identification in wind energy investment projects; (b) using a modified fuzzy model to improve the risk assessment process by considering the expert competency in wind energy projects; and (c) establishing an integrated model to evaluate the cash flow of the investment. A wind farm in the Middle East is selected as the case study to examine the usability and practicality of the proposed model. The results show that the most important risks are ‘change in regulation and policy’, ‘dependency on the international market for importing raw materials’ and ‘market competitiveness’. On the other hand, the financial assessment under uncertainty shows that the profitability of the investment can be varied, and it emphasises the importance of an appropriate risk management process to guarantee the success of the investment.

Research on Risk Management of Engineering Project Auction

2011 ◽  
Vol 219-220 ◽  
pp. 1523-1527
Author(s):  
De Bin Fang ◽  
Wen Liu
Keyword(s):  
Risk Factors ◽  
Sensitivity Analysis ◽  
Risk Management ◽  
Evaluation Model ◽  
Practical Significance ◽  
Principal Agent ◽  
Engineering Project ◽  
Analysis Methods

Project auction is an important principal-agent with competition. The uncertainty of market and incompleteness of bidders’ information bring a lot of risks for the project owner, so the research on risk management is of theoretical and practical significance. In this paper, risk factors are identified and measured, based on which, an evaluation model is built up, and then by sensitivity analysis, sensitive factors are found so as to help the owner take the corresponding measures. A case study illustrates that these analysis methods used in this paper are reasonable.

scholarly journals A COMPUTERIZED RISK EVALUATION MODEL FOR PUBLIC-PRIVATE PARTNERSHIP (PPP) PROJECTS AND ITS APPLICATION

2012 ◽  
Vol 16 (3) ◽  
pp. 277-297 ◽  
Author(s):  
Yelin Xu ◽  
Yujie Lu ◽  
Albert P. C. Chan ◽  
Miroslaw J. Skibniewski ◽  
John F. Y. Yeung
Keyword(s):  
Risk Factors ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Risk Level ◽  
Illustrative Case ◽  
Fuzzy Synthetic Evaluation ◽  
Support Tool ◽  
The Third ◽  
Third Stage ◽  
Risk Evaluation Model

PPP projects usually involve more risks than other traditional procurement models because of their complexity. This paper presents the third stage of a funded study, which aims to develop a practical and computerized risk evaluation model for PPP projects. In the first and second stages, a risk hierarchal structure composed of 17 weighted risk factors is developed to describe risk profiles of PPP projects. The weightings and membership functions for risk factors are established using the Delphi survey technique and Fuzzy Set Theory. The risk evaluation model is then developed using a fuzzy synthetic evaluation approach. In the third stage, an automated decision support tool based on the risk evaluation model is designed for PPP practitioners by using Visual Basic for Application (VBA). The computerized tool can not only assist PPP participants to assess a PPP project's overall risk level for auxiliary investment decision, but can also help practitioners to identify the most risky areas of a PPP project for effective risk response. To demonstrate the applicability of the computerized model, an illustrative case is finally provided.

scholarly journals Risky Driving Behavior Recognition Based on Vehicle Trajectory

2021 ◽  
Vol 18 (23) ◽  
pp. 12373
Author(s):  
Shengdi Chen ◽  
Qingwen Xue ◽  
Xiaochen Zhao ◽  
Yingying Xing ◽  
Jian John Lu
Keyword(s):  
Risk Evaluation ◽  
Evaluation Model ◽  
Driving Behavior ◽  
Trajectory Data ◽  
Behavior Recognition ◽  
Risky Driving ◽  
Car Following ◽  
Proposed Model ◽  
Behavior Based ◽  
Risk Evaluation Model

This paper proposes a measurement of risk (MOR) method to recognize risky driving behavior based on the trajectory data extracted from surveillance videos. Three types of risky driving behavior are studied in this paper, i.e., speed-unstable driving, serpentine driving, and risky car-following driving. The risky driving behavior recognition model contains an MOR-based risk evaluation model and an MOR threshold selection method. An MOR-based risk evaluation model is established for three types of risky driving behavior based on driving features to quantify collision risk. Then, we propose two methods, i.e., the distribution-based method and the boxplot-based method, to determine the threshold value of the MOR to recognize risky driving behavior. Finally, the trajectory data extracted from UAV videos are used to validate the proposed model. The impact of vehicle types is also taken into consideration in the model. The results show that there are significant differences between threshold values for cars and heavy trucks when performing speed-unstable driving and risky car-following driving. In addition, the difference between the proportion of recognized risky driving behavior in the testing dataset compared with that in the training dataset is limited to less than 3.5%. The recognition accuracy of risky driving behavior with the boxplot- and distribution-based methods are, respectively, 91% and 86%, indicating the validation of the proposed model. The proposed model can be widely applied to risky driving behavior recognition in video-based surveillance systems.

scholarly journals PROJECT RISK EVALUATION BY USING A NEW FUZZY MODEL BASED ON ELENA GUIDELINE

2018 ◽  
Vol 24 (4) ◽  
pp. 284-300 ◽  
Author(s):  
Pezhman Asadi ◽  
Javad Rezaeian Zeidi ◽  
Toraj Mojibi ◽  
Abdolreza Yazdani-Chamzini ◽  
Jolanta Tamošaitienė
Keyword(s):  
Risk Management ◽  
Fuzzy Inference System ◽  
Risk Evaluation ◽  
Fuzzy Inference ◽  
Management Process ◽  
Project Risk ◽  
Inference System ◽  
Proposed Model ◽  
Risk Management Process ◽  
Risky Projects

The complexity and dynamics of the executive projects have coped contractors with substantial hazards and losses. Project risk management is a critical tool for authority to improve its performance and secure the success of the organization. However, a number of standards and approaches have been developed to formulate the projects based on their risks. The Elena guideline is a systematic standard developed by Iran Project Management Association. This guideline provides the full cycle of the risk management process. Risk evaluation is the key part of the risk management process. On the other hand, different techniques have been developed to model a risk evaluation problem. Fuzzy inference system is one of the most popular techniques that is capable of handling all types of the uncertainty involved in projects. This paper proposes a three-stage approach based on the fuzzy inference system under the environment of the Elena guideline to cope with the risky projects. Finally, an illustrative example of the risk evaluation is presented to demonstrate the potential application of the proposed model. The results show that the proposed model evaluates the risky projects efficiently and effectively.

Supply Chain Risk Evaluation Based on Bayesian Network

2013 ◽  
Vol 680 ◽  
pp. 550-553
Author(s):  
Bo Chao Liu
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Bayesian Network ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Supply Chain Risk ◽  
Logistics Company ◽  
Proposed Model

The evaluation for supply chain risk is very important to show the latent risk and eliminate the risk. In the study, Bayesian network is proposed to evaluate the supply chain risk. The assessment indexes of supply chain risk are analyzed before supply chain risk assessment. Then, the assessment indexes of supply chain risk can be used to construct the supply chain risk assessment model. We apply a certain logistics company to study the evaluation ability of Bayesian network evaluation model proposed here. The experimental results prove the effectiveness of the proposed model.

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