Risk Level Of Project Research Articles

Investment Risk Assessment of Dispersed Wind Power in Low Wind Speed Area Using a Hybrid Multi-Criteria Decision-Making Approach Based on Hesitant Fuzzy Linguistic Environment

Reducing the phenomenon of wind curtailment is essential to improve the level of wind power consumption. Wind power development in China has shifted to southeast region and dispersed wind power has developed rapidly and gradually become the new main force. However, various obstacles limit the smooth progress of dispersed wind power in low wind speed area. An important point is the absence of targeted risk analysis and evaluation methods. Therefore, the principal contribution of this paper is to find out the critical risk factors of such projects and propose the risk assessment model. First, 18 critical risk factors are identified using the constructed five-dimensional risk analysis model. Second, the hesitant fuzzy linguistic term set with credibility is utilized to collect evaluation information on one hand and to improve the multicriteria decision-making methods involved on the other hand. Third, the risk evaluation and ranking for 10 provinces that mainly develop dispersed wind power is carried out. The evaluation results indicate that the risk level of dispersed wind power projects is “Relatively Low” in most study provinces and the risk levels of Guangdong and Fujian are higher. It is worth noting that the consistency between the evaluation results and the distribution of wind resources can be used to guide the formulation of stimulus policies. Besides, the ranking results show some preference for investment choice. Finally, dual sensitivity analysis tests the stability of the model and shows the ranking results under different decision preferences. Scenario analysis gives the possible risk scenarios and evaluation results in the future. This study can provide insightful inspiration to wind power investors, risk management practitioners, and policymakers.

Regional strategies as an uncertainty reducing factor for investors

The process of strategic investment decisions making in the context of regional production diversification requires a detailed analysis of factors that potentially affect the expected results. The model construction of cash flows generated by a project with strategic potential for the enterprise requires a detailed study of both internal technological characteristics that determine the potential results of its implementation and external factors. In the system for evaluating such characteristics, the risk of making an investment decision is important. If the internal characteristics lend themselves to relatively reliable estimates, then the external ones are often extremely uncertain. A factor that significantly reduces the uncertainty of internal corporate evaluations is the availability and consistent implementation of the company’s strategy - a document that is fully accessible to managers and inaccessible to competitors. At the same time, in order to reduce external uncertainty when choosing a region for implementing an investment project, the presence of a regional development strategy, its quality and degree of implementation becomes a significant factor. The article examines the impact of such strategic instruments on reducing the risk level of investment projects, provides arguments in favor of the need for the development and consistent implementation of regional strategies that form the basis for more accurate justification by investors of cash flows that vary depending on the regions of implementation.

The hybrid Fuzzy Fault and Event Tree analysis in the geotechnical risk management in HDD projects

ABSTRACT Horizontal Directional Drilling (HDD) technology is one of the most popular trenchless construction methods for installing pipelines under various obstacles. The geotechnical risk level of HDD projects is one of the key parameters when assessing the project feasibility and making costing of the project. It is also a starting point for introducing the geotechnical risk management strategy which aims to reduce the number of installation failures and their negative consequences. The objective of this work was to develop a new geotechnical risk management model for HDD projects. The risk management process was carried out applying the hybrid Fuzzy Fault and Event Tree analysis. Applying the fuzzy set theory in the proposed model made it possible to decrease the lack of precision and difficulties with gaining the crisp values of the basic events probability, which occur in the conventional Fault Tree Analysis. It allowed to model risk management actions clearly and effectively. Forty-seven risk remediation strategies for all the identified geotechnical risks were proposed. Four types of risk response strategies were considered: risk retention, risk transfer, risk elimination and risk reduction. The practical application of the proposed risk management model for HDD projects was shown on four examples.

Risk Evaluation of Cold Chain Marine Logistics based on the Dempster-Shafer (D-S) Evidence Theory and Radial Basis Function (RBF) Neural Network

Wang, L.; Zhang, G., and Hao, Q., 2019. Risk evaluation of cold chain marine logistics based on the Dempster-Shafer (DS) evidence theory and radial basis function (RBF) neural network. In: Li, L.; Wan, X.; and Huang, X. (eds.), Recent Developments in Practices and Research on Coastal Regions: Transportation, Environment and Economy. Journal of Coastal Research, Special Issue No. 98, pp. 376–380. Coconut Creek (Florida), ISSN 0749-0208.Cold chain marine logistics on fresh agriculture products takes a long time and has a degree of high risk because it is necessary to evaluate the logistics risk with scientific methods in a complex marine environment. This article analyzes the risk factors of cold chain marine logistics. The risk evaluation index system of cold chain marine logistics is established and a new method for logistics risk evaluation based on the Dempster-Shafer (D-S) evidence theory and the radial basis function (RBF) neural network is introduced. The evaluation data of experts is fused effectively by the D-S evidence theory. The risk level of logistics projects is identified by the RBF neural network. Then, 24 cold chain marine logistics projects were selected as samples to verify the effectiveness of this method and to prove that RBF is more superior to the back-propagation (BP) neural network for logistical risk evaluation. This method can overcome the shortcomings of expert evaluation data dispersion and the dependence on experts.

A fuzzy evidential reasoning-based approach for risk assessment of deep foundation pit

Traditional risk assessment methods, such as the probabilistic methods, are not effectively used in the construction works of a deep foundation pit (DFP) when data set collected are incomplete or vague input takes place. A new method based on fuzzy evidential reasoning approach is proposed in this paper to assess the overall risk level of a DFP construction project. Firstly, the method defines risks as the products of occurrence likelihood multiplying consequence severity, which is further depicted by trapezoidal fuzzy numbers. Thereafter, the fuzzy analytical hierarchy process is adopted to calculate the weighs of different hazardous events that may occur in a DFP construction project. The overall risk level of a DFP project therefore could be achieved through aggregating the risk level of all hazardous events based on evidential reasoning algorithm. However, due to the existence of intersections among more than two continuous fuzzy evaluation grades rather than between two adjacent grades, the prevailing aggregation method is not suitable any more. So, a new aggregated probability mass along with the reassigning method in relation to the degree of belief belonging to the fuzzy intersection of two grades is thus put forward in this paper, as a result to make the evidential reasoning possible. A case study on risk assessment of the DFP of underground traffic project of Zhengzhou comprehensive transportation hub in China is introduced to illustrate the application of the proposed method. The result indicates that the overall risk level of a DFP project could be assessed effectively under the scenario that more than two continuous fuzzy evaluation grades intersect rather than only two adjacent grades. Moreover, comparing with the traditional methods, the result obtained in the case study by using the proposed method seems to be more reasonable.

Exploring Critical Variables That Affect the Policy Risk Level of Industrial Heritage Projects in China

With the rapid development of the transformation and urbanization of Chinese social structures, more and more industrial heritage renewal projects are emerging. However, there are significant policy risks associated with Chinese industrial heritage renewal projects. Through a literature review, a total of 20 policy risk factors were determined, and a total of 10 industrial heritage renewal project managers in six regions nationwide conducted a pilot study. A questionnaire survey was conducted to collect 398 evaluations of these 20 risk factors from relevant professionals. Secondly, through confirmatory factor analysis, a six-part policy risk assessment model was established. The results indicated that the critical variables that affect the policy risk level were: (1) industry maturity, (2) tax policy, (3) financial freedom, (4) the rule of law, (5) local market size, and (6) local market experience. Moreover, there are significant opportunities and policy risks in Chinese industrial heritage renewal projects, and appropriate strategies can capture these opportunities and mitigate risks. As there are few pieces of research on the policy risks of industrial heritage renewal projects in China, this study has a certain reference significance for the policy risk management of industrial heritage renewal projects in China.

THE CURRENT STATE OF PROJECT RISK ASSESSMENT AND EDUCATION NEEDS IN PROJECT RISK MANAGEMENT

Current trends show that education in the field of project risk management is a very actual topic. Long - term projects, which was realized in 2018, was mainly focused on R&D across the world. Short - term projects, was focused on innovation and improve manufacturing processes. Many projects failed because project managers did not manage project risks. Project managers have less knowledge and skills on how to effectively manage project risks, especially risks in the planning phase of projects.
 The main aim of this article is to analyze the current state of usage project risk assessment across the world, based on own empirical research, which was provided, by authors in 2018 and 2019 (mainly level of usage project risk management methods, experience and level of education). The research focused on analyzing the current state of project risk assessment among continents. The authors focused on the average level of use qualitative and quantitative project risk analysis by project managers, level of project risk management experience by project managers and complexity of learning in using of qualitative and quantitative project risk management methods and tools. Some recommendation were established to educate project managers in the field of project risk management.

Risk assessment of urban rooftop distributed PV in energy performance contracting (EPC) projects: An extended HFLTS-DEMATEL fuzzy synthetic evaluation analysis

Promoted by the policy, urban rooftop distributed photovoltaic (URDPV) has developed rapidly in China. Besides, the government is gradually applying energy performance contracting (EPC) mode to this field making use of urban rooftop resources and energy service companies’ (ECOs’) technological advantages, but there are still obstacles to further development. One of the main reasons that restrict the further development of EPC-URDPV projects in China is the lack of effective risk assessment method. This paper aims to identify the critical risk factors (CRFs) for such projects, and propose a comprehensive risk assessment framework. Firstly, 11 CRFs are identified based on the literature review and 4-dimensional risk analysis to composed the risk assessment index system. Secondly, the weights of CRFs are determined by the intuitionistic fuzzy-decision making trial and evaluation laboratory (IF-DEMATEL) method. It is worth noting that this paper uses the hesitant fuzzy linguistic term sets (HFLTS) to obtain evaluation information to ensure the completeness and fuzziness of experts’ viewpoints. Then, an extended HFLTS-DEMATEL fuzzy synthetic evaluation method is used to conduct risk assessment. The evaluation results show that the risk levels of EPC-URDPV projects in most study areas are at “Medium” and “Relatively Low” state. The risk level of projects in Shanghai and Fujian is “Relatively High”. Sensitivity analysis results show the stability and reliability of the model. After considering the causes of risk and relevant stakeholders, a risk response is proposed. This study can enrich the methods in the field of risk assessment and provide insightful references to PV investors, decision makers.

Project Social Stability Risk Assessment and the Resolving Measures Research

Project social stability risk analysis use a variety of management theory and technology, quantitative and qualitative, combined with technical, index evaluation and experience judge, among them: risk assessment is mainly adopt risk factor control check list, risk probability matrix, computation of risk index method analysis, estimate, determine project risk level; risk prevention and resolving measures are mainly to lighten, resolve, and avoid the social stability in different stages of the project risk factors, the effective measures to achieve the goal of low degree of risk control and influence.

Risk assessment on offshore photovoltaic power generation projects in China based on a fuzzy analysis framework

China has begun to promote offshore photovoltaic in coastal areas taking its advantages of saving land resources and proximity to load centers. However, the projects are bound to face a series of risk factors as the industry is in its infancy. This paper conducts a risk assessment on offshore photovoltaic power generation projects in China based on a fuzzy framework. Firstly, 16 risk factors affecting offshore photovoltaic power generation projects in China are identified and classified into 4 groups. Secondly, a risk assessment model is constructed involving Hesitant Fuzzy Linguistic Term Sets, Triangular Fuzzy Number and Fuzzy Synthetic Evaluation. Thirdly, this paper conduct an empirical study of China, and the result shows that the risk level of offshore photovoltaic power generation projects in China is medium high. Finally, some response measures are proposed. The risk index system and corresponding countermeasures can provide a reference for project managers to allocate resources to prevent risk events. Besides, the risk assessment model can help project investors to avoid too risky projects. In addition, the risk assessment on offshore photovoltaic power generation projects in China has not been discussed by scholars yet. Thus, this paper contributes to the literature and expand the knowledge.

Social Risk Assessment and Management for Major Construction Projects in China Based on Fuzzy Integrated Analysis

With the vigorous development of major engineering projects in China, the social risks associated with major construction projects not only challenge the success of projects but also threaten social harmony and stability. Therefore, it is of great practical significance to assess and manage social risks. This paper aims to identify and evaluate the social risk factors by conducting a survey and assess the overall risk level of major construction projects (MCPs) with fuzzy integrated approach. First, 35 social risk factors and related stakeholders were identified based on literature analysis and case study. Then, 18 critical social risk factors (CSRFs) were selected and classified into six groups (CSRGs) based on a questionnaire survey. Next, using fuzzy integrated method, the probability of occurrence (PO), magnitude of impact (MI), the integrated risk level (IRL) of each CSRF and CSRG, and the overall risk of MCPs were calculated. As a result, “unfair compensation for housing demolition and land requisition” was the most critical social risk factor, and “policy/legal risk” was the most critical social risk group. The overall risk of MCPs was between moderate and high. At last, a social risk synthetic management framework was established, which can provide reference for policymakers and project decision makers to effectively manage the social risks.

Major project risk assessment method based on BP neural network

In order to prevent risks in major projects, it is of great importance to accurately assess risks in advance. Therefore, in this paper, we propose a novel major project risk assessment method with the BP neural network model. Firstly, we propose an index system for major project risk assessment, which is made up of four parts: 1) Schedule risk, 2) Cost risk, 3) Quality risk, and 4) Resource risk. Secondly, we propose a hybrid BP neural network and particle swarm optimization (PSO) model to evaluate risks in major projects. Especially, major project risk assessment results are achieved from the output layers of the BP neural network which is optimized by the PSO algorithm. In our proposed hybrid model, the fitness for each particle is computed through an optimal function, and then the particle can improve its velocity for the next cycle by searching the optimal value. Furthermore, this process should be repeated when the end condition is satisfied. Finally, experimental results demonstrate that the proposed method is able to evaluate risk level of major projects with high accuracy.

A risk assessment framework for construction project using artificial neural network

The current trend of increasing construction project size and complexity results in higher level of project risk. As a result, risk management is a crucial determinant of the success of a project. It seems necessary for construction companies to integrate a risk management system into their organizational structure. The main aim of this paper is to propose a risk assessment framework using Artificial Neural Network (ANN) technique. Three main phases of the proposed framework are risk management phase, ANN training phase and framework application phase. Thereby, Risk Factors are identified and analysed using Failure Mode and Effect Analysis (FMEA) technique. ANN model is created and trained to evaluate the impact of Risk Factors on Project Risk which is represented through the ratio of contractor’s profit to project costs. As a result, the framework with successful model is used as a tool to support the construction company in assessing risk and evaluate their impact on the project’s profit for new projects.
 Keywords: risk management; risk assessment; Artificial Neural Network (ANN); Failure Mode and Effect Analysis (FMEA); construction project.

A risk assessment framework of PPP waste-to-energy incineration projects in China under 2-dimension linguistic environment

Abstract Risk assessment is critical to insuring the success of waste-to-energy (WTE) projects under public–private partnership (PPP) model as risks are accompanied with the life-cycle of the projects. Uncertainty composed of fuzziness and randomness is an important issue in the risk assessment under increasingly complex environments. The 2-dimension linguistic information is a powerful tool to express the fuzziness of information, and meanwhile, the cloud model perfectly depicts the randomness of information with three numerical characteristics. Combining them together, this paper puts forward a risk assessment framework of PPP WTE incineration projects. Firstly, an evaluation index system for risk assessment of China's PPP WTE incineration projects is constructed, which includes 14 criteria involved in four dimensions of construction and operation risk, macro-economic risk, legal and socio-political risk, and government risk; secondly, a conversion model between 2-dimension linguistic variables and clouds is developed; thirdly, the cloud Choquet integral (CCI) operator is utilized to handle the correlations among risk factors; fourthly, a risk assessment framework is established to assess the overall risk level of several China's PPP WTE incineration projects. From the empirical demonstration and comparison analysis, the proposed framework can effectively deal with such a complicated problem and lead to an outstanding result.

Study on Risk Assessment of Foreign Hydropower EPC Project Based on Improved AHP Method

In order to solve the difficult problem of risk control of foreign hydropower EPC project, a graymodified AHP risk assessment model is proposed. Firstly, based on the weight of each index of the risk evaluation index system, the gray system is used to determine the gray evaluation matrix. Secondly, the fuzzy comprehensive evaluation method is used to evaluate the project risk synthetically. Finally, combined with the case shows that the gray - improved AHP risk assessment model can accurately determine the risk level of foreign EPC projects, reduce the risk to the project caused by the loss.

A Fuzzy Comprehensive Evaluation Model for Sustainability Risk Evaluation of PPP Projects

Evaluating the sustainability risk level of public–private partnership (PPP) projects can reduce project risk incidents and achieve the sustainable development of the organization. However, the existing studies about PPP projects risk management mainly focus on exploring the impact of financial and revenue risks but ignore the sustainability risks, causing the concept of “sustainability” to be missing while evaluating the risk level of PPP projects. To evaluate the sustainability risk level and achieve the most important objective of providing a reference for the public and private sectors when making decisions on PPP project management, this paper constructs a factor system of sustainability risk of PPP projects based on an extensive literature review and develops a mathematical model based on the methods of fuzzy comprehensive evaluation model (FCEM) and failure mode, effects and criticality analysis (FMECA) for evaluating the sustainability risk level of PPP projects. In addition, this paper conducts computational experiment based on a questionnaire survey to verify the effectiveness and feasibility of this proposed model. The results suggest that this model is reasonable for evaluating the sustainability risk level of PPP projects. To our knowledge, this paper is the first study to evaluate the sustainability risk of PPP projects, which would not only enrich the theories of project risk management, but also serve as a reference for the public and private sectors for the sustainable planning and development. Keywords: sustainability risk eva

Fuzzy comprehensive Bayesian network-based safety risk assessment for metro construction projects

This paper presents a systemic decision-support approach to safety risk analysis for metro construction projects under uncertainty using a fuzzy comprehensive Bayesian network (FCBN), which combines the fuzzy comprehensive evaluation method (FCEM) and a Bayesian network (BN). The results of the safety risk assessment based on the FCBN are composed of three aspects: risk probability, risk loss, and risk controllability. In this assessment, two of the aspects—risk loss and risk controllability—are calculated in terms of intervals or fuzzy numbers. Through the application of the FCEM, the levels of risk loss and risk controllability are then estimated. The risk probability is calculated from the BN, in which the relationships among the dependent variables are expressed in the form of a directed graph. A comprehensive safety risk assessment allows engineers to assess potential safety hazards and provides a basis for dynamic early risk warning and control ahead of metro construction, which is acquired by combining the FCEM and the BN. A case study relating to safety risk analysis in the construction of the Dalian Metro in China is used to verify the feasibility of the approach as well as its application potential. A comparison of the results with the actual construction state shows its effectiveness in estimating the risk level of a metro construction project under uncertainty. The proposed approach provides a powerful tool with which planners and engineers can systematically assess and mitigate the inherent risks associated with metro construction.

Interconnection of the Degree of Risk and Life Cycle of the “Green Construction” Investment Projects

This article analyses interconnection of the degree of risk and the life cycle of the “green building” investment projects, which is structured according to the life cycle. Main stages of the implementation of investment and construction project were considered, interconnection of the project life cycle and the level of project risk were presented in the form of graphical model, proposed a mathematical model of the risk calculation at different stages of the project life cycle, which is a function of depending on the different risk parameters.

Research on the evaluation of wind power projects of investment risk

In recent years, with the rapid economic development, wind energy becomes more and more fierce competition in the market. Based on the basic concept of wind power generation, this article will analyze wind power generation in the significance and the role of sustainable development in our country. In the risk analysis, the first based on the analysis of wind power projects characteristics, the various stages of the wind power project risk factors identified by phasing of construction of wind power feasibility study and design phase, investment and financing stage, building construction phase and operations and maintenance phases of the four stages of risk into account, and then build a relatively complete risk assessment system. In this model, the evaluation is treated atter-element determination, and then it will select the appropriate classical field and section domain, by using AHP to 17 sub-indexes were four stages weight distribution, and finally a combination of elements and AHP model, got the project Risk level.

基于ANP-FCE模型的PPP建设项目风险管理研究

通过网络分析法(ANP)结合实例进行风险因子之间相互影响的分析，计算网络层风险元素权重，结合模糊综合评价法(FCE)确定项目风险等级，识别重要的风险因素，及时采取有效措施，对PPP建设项目进行风险控制。 Through the method of ANP, this paper combines the real example to make the analysis of the interaction between the risk factors, and calculates the weight of risk elements in the network layer; this paper also identifies the project risk level which is measured by the fuzzy comprehensive evaluation method (FCE), and identifies the important risk factors and timely takes measures to control the risk of PPP construction project.