Risk Level Of Project Research Articles

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

Temporal and Spatial Evolution of Public–Private Partnership (PPP) Project Risks in China: 2003–2019

The implementation of public–private partnership (PPP) is perturbed by multiple factors, and it is difficult for the Chinese government to fully control the risks of PPP projects. Based on the DPSIR model, this study constructed the PPP projects risk evaluation index system by using the TOPSIS method. Then the spatial variation, standard deviation ellipse, and gray dynamic model were used to analyze the spatial–temporal dynamic evolution characteristics of the risk level of PPP projects from 2003 to 2019 and to make reasonable predictions of the future spatial distribution pattern. This study yielded the following five results: (1) the average risk level of China’s PPP projects is 0.722, with a decreasing trend of fluctuation and relatively stable risk; (2) high-risk provinces for PPP projects decrease, medium-risk provinces increase; (3) the spatial variability of risk is increasing, and the spatial differentiation is significant, showing a spatial evolution pattern of “west > central > east,” but areas with low-risk values are clearly migrating to the east; (4) the spatial distribution pattern of risk has a north-easterly orientation, with a “north-west to north-east” trend in the path of movement; (5) There are differences in the spatial distribution patterns in the east–west and north–south directions, and the spatial spillover effect is not obvious. Based on the above results, the risk center of China’s PPP projects will be shifted to the northeast in 2025–2035. Our study captures the evolution of PPP project risks in China in both temporal and spatial dimensions, which can provide lessons for optimizing global PPP project risk management.

Risk Assessment of Mining Heritage Reuse in Public–Private-Partnership Mode Based on Improved Matter–Element Extension Model

With the development and utilization of resources, mineral-resource cities face the dilemma of resource depletion, the environmental restoration of mines, and industrial transformation. Reusing their mining heritage is a good way for these cities to change their mono-industrial structure and vigorously develop successor industries. Due to the complexity of reusing mining heritage, introducing the “Public–Private-Partnership” (PPP) mode can be a good solution to the problems of the government’s mining heritage reuse, such as large capital investment and a long construction-cycle time. To accurately classify the risk of reuse of mining heritage in the PPP mode, 26 indicators are selected to construct the evaluation index system of mining heritage reuse in the PPP mode based on five aspects: social capital-side, contractor-side, government-side, civilian-side, and the natural environment. The path coefficients of the structural equation model are used to calculate the weights of the indicators. The improved matter–element extension model is constructed to evaluate the reuse of mining heritage in the PPP mode. The Jiaozuo-Centennial Mining Heritage Park project is the object of research for applying the model. The results show that the risk evaluation index system combines the risk factors from the stakeholders’ perspective. The risk-evaluation model of the mining heritage reuse PPP project is constructed based on the combination of the improved matter–element extension model, the calculation of the asymmetric closeness, and the structural equation modeling method, which solves the drawbacks of the traditional model, such as the difficulty of determining the weights of the indicators, the incomplete scope of the material element domains, and the poor calculation of the comprehensive correlation degree. The case analysis shows that the risk level of the Jiaozuo-Centennial Mining Heritage Park project is Level II. This aligns with the actual situation and verifies the feasibility of the risk-evaluation model applied to the actual project. The research in this paper fills the gap in the risk model of mining heritage reuse in the PPP mode, enriches the theoretical system of risk evaluation of mining heritage reuse projects, and provides reference significance for similar mining heritage development projects in the future.

Risk Assessment Method and Application of Urban River Ecological Governance Project Based on Cloud Model Improvement

This study classifies risk factors and establishes the risk-evaluation index system for an urban river ecological management project. That system includes construction personnel risk, construction technology risk, construction management factor risk, construction duration factor risk, and other risks. A total of 23 indicators determine the level and standard of each indicator. This study proposes a risk index system that uses the cloud model evaluation method and explains that model’s process. To demonstrate the risk evaluation methodology, it was applied to the ecological management project of Jinghe River in Jinghe New City, China. The results showed that: (1) the urban river ecological management project was subject to “a medium level of personnel risk, management risk, and construction period risk and a relatively high level of technical risk and other risks.” According to the evaluation results, the overall risk level of the project was medium, which is consistent with the risk level of the Jinghe River ecological management project at the current stage. (2) The limitation of the subjective qualitative concept caused by the traditional fuzzy comprehensive evaluation was fully considered in the improved method, and the application of the cloud-model based improved method in risk evaluation of the urban river ecological management project significantly improved the reliability and visualization of the evaluation results. Finally, the urban river ecological management project in China was adopted as an example to prove that the model boasts high stability, and some corresponding countermeasures were also proposed. The research results are expected to provide valuable references and scientific criteria for implementing urban river ecological management projects.

Knowledge Graph Improved Dynamic Risk Analysis Method for Behavior-Based Safety Management on a Construction Site

Construction sites are considered high-risk working environments. Safety risk analysis of construction sites is one of the important aspects of construction safety management. However, existing construction safety risk analysis methods typically face overreliance on subjective experience and cannot reflect the real-time risk level of construction projects. Crucial information about construction accidents implies a complex semantic network that can obtain objective quantitative data and then serve the quantitative analysis of construction safety risk. Therefore, a knowledge-graph-improved dynamic risk analysis method for behavior-based safety (BBS) management on construction sites is proposed. Specifically, this study quantifies the risks and consequences of unsafe behaviors in construction by conducting graph topology analysis based on historical accident data, improves the grey clustering model, and calculates the construction site risk. Thus, the proposed method combines expert experience and objective historical data to give more objective and realistic results. The results of the application of this method on one project show that the improved dynamic analysis method can utilize the historical accident data to achieve a more reasonable overall risk grading for BBS on construction sites; at the same time, the method can determine real-time key BBS indicators; further, the construction safety management measures for key BBS indicators can effectively reduce current BBS risks of a construction project.

Differences in Workers’ Safety Behavior by Project Size and Risk Level of Work in South Korea

Unsafe behavior is the main cause of accidents in the construction industry. Considering the fact that accidents occur more frequently in small projects and on more hazardous works, this study tests the hypotheses that workers’ safety behavior varies (1) with project size, and (2) with the risk level of work. Survey data were collected from a total of 313 construction workers at 21 sites using questionnaires, and the data were analyzed using a series of factor analyses and structural equation modeling. Multigroup factor analysis revealed that the mean safety behavior value for the workers in large projects was greater than that for the workers in small projects, with a statistically significant difference. This indicates that large-project workers tend to behave more safely than small-project workers. However, no statistically significant difference was found for the workers’ safety behavior with regards to the risk level of work. In addition, the differences in the impacts of three factors (management commitment, supervisor’s role, and workers’ perception of safety) on safety behavior depending on the project size and risk level of work were investigated using multigroup structural equation modeling. Management commitment had the greatest impact on workers’ safety behavior in large projects, whereas workers’ perception of safety had the greatest impact in small projects. Regarding the risk level, management commitment had the greatest impact on safety behavior with low-risk work, and workers’ perception of safety had the greatest impact with high-risk work. These results suggest that management commitment is more important to control worker’s safety behavior to prevent accidents for large projects and low-risk works, whereas the workers’ safety perception is more important to prevent accidents for small projects and high-risk works. This study provides a new theoretical basis for explaining the variations in workers’ safety behavior group to group, and facilitates the development of future safety policies and systems. This study also contributes to the establishment of strategic planning and the justification for spending relevant resources to improve workers’ safety behavior.

Risk Breakdown Matrix for Risk-Based Inspection of Transportation Infrastructure Projects

At state transportation agencies (STAs), construction inspection is pivotal to ensuring infrastructure quality. Due to current challenges, STAs have been exploring a risk-based inspection strategy. However, the lack of a systematic approach for risk identification and assessment at the construction activity level is the main limitation. Therefore, this paper introduces an integrated risk-based construction inspection framework by developing a risk breakdown matrix (RBM). Using RBM, critical risks are identified and assessed at the construction activity level. The overall framework is evaluated by using the concrete pavement project as a test case. Results show that the framework could provide risk information (e.g., risk rankings) of construction activities as well as the overall project risk level. The major contribution is that the proposed framework can be applied to various infrastructure projects at STAs, allowing for effective inspection resource allocation, reduction of the inspector’s workload, and consistency in inspection practices.

Evaluation of Social Stability Risk of Adjusting Goods Vehicle Calculation Method Based on Optimal Combination Weighting—Cloud Model

In order to solve the social stability risk problem of the adjusting goods vehicle calculation method (AGVCM) in the cancellation of toll stations at expressway provincial boundaries, a social stability risk evaluation model was proposed. Firstly, based on the possible time stages of the AGVCM, we built the social stability risk evaluation index system of the AGVCM including 4 levels, 3 grades, and 60 indicators. Secondly, we used the semantic information of cloud model to transform qualitative description and quantitative evaluation, calculated the risk level for social stability risk evaluation of AGVCM according to an integrated cloud algorithm, and proposed an optimal combination weighting—cloud model for the social stability risk evaluation of AGVCM. Finally, the feasibility of the evaluation model is verified by a case study in Yunnan province in China. The results showed that the cloud model’s numerical characteristic of social stability risk evaluation of AGVCM in Yunnan based on the optimal combination weighting—cloud model is (0.28, 0.073, 0.0008), implying the risk level is “small” and the conclusion is basically consistent with current standards. The model contains rich process information, which is helpful to better effectively eliminate the subjectivity and arbitrariness in the evaluation process of identifying the key factors affecting the project risk level.

Risk evaluation of energy investment projects along the Belt and Road based on cloud model and evidence theory

China's major energy projects along the Belt and Road are characterized by large-scale capital investment, long construction cycles, and complex investment environments, making it more difficult to assess project investment risks. Based on the PESTEL theory, a risk evaluation index system is constructed for energy enterprises' investment projects along the Belt and Road. In view of the uncertainty of energy investment projects, a risk evaluation method combining a cloud model and an evidence theory is proposed. To examine the developed index system and risk evaluation method, an overseas hydropower investment project is chosen and the risk factors are analyzed. The results suggest that the risk level of the enterprise's project is highest, the political and environmental risks are both high, the economic and project risks are both at average level, and the energy risk is relatively low, which verifies the effectiveness of this information fusion method. The method can be used to solve the problem of linguistic ambiguity and uncertainty in multi-attribute decision problems and is applicable to similar investment projects, thus providing a new technical path to assess the investment risks of energy enterprises along the Belt and Road.

Risk assessment of photovoltaic - Energy storage utilization project based on improved Cloud-TODIM in China

“Photovoltaic + energy storage” is considered as one of the effective means to improve the efficiency of clean energy utilization. In the era of energy sharing, the “photovoltaic - energy storage - utilization (PVESU)" model can create a more favorable market environment. However, the various uncertainties in the construction of the PVESU project have become the main obstacles to the development of the PVESU model. This paper aims to evaluate the risk level of China's PVESU projects through an improved Cloud-TODIM (Cloud-an acronym in Portuguese for Interative Multi-criteria Decision Making) method. First of all, 18 critical risk factors are identified using the constructed five-dimensional risk analysis model. Secondly, the improved method is used to calculate the weight of the comprehensive criteria and rank 14 PVESU alternatives. Finally, the accuracy and feasibility of the hybrid method are verified by sensitivity analysis tests concluding the loss decay coefficient adjustment and comparison analysis with the Cloud-TOPSIS(Cloud-Technique for Order of Preference by Similarity to Ideal Solution) method. Meanwhile, in terms of energy storage, some suggestions are made for the future development of China's PVESU project. This study can also provide insightful enlightenment for PVESU project investors, risk management professionals and decision makers.

SAFETY RISK IDENTIFICATION AND ASSESSMENT IN THE STONE CRUSHER AREA AT PRAFI, MANOKWARI REGENCY, WEST PAPUA PROVINCE

Zero accident policy that proclaimed by the Government through the Ministry of Manpower and Transmigration must be implemented properly by all companies that operating in Indonesia. Zero accident can be accomplished by implemented Health and Safety in work (K3) and risk management in all companies, both small and large scale companies. The stone crusher company which operates in Prafi plain, Manokwari Regency, West Papua Province, is a high capital and high company with substantial assets, accidents might have happened during work projects. Assessment of the risk level of a stone crusher project can be done by conducting interviews, identification, observation and research to determine risk factors that may occur during work projects. The analysis shows that the stone crusher project has a low risk level (12%), moderate (39%) to high risk (49%). The high risk level percentage (49%) makes the stone crusher company obliged to carry out K3 management and risk control by involving K3 experts in every work project so that zero accident can be achieved.

AHP-FSE-Based Risk Assessment and Mitigation for Slurry Balancing Shield Tunnel Construction.

Slurry balancing shield construction is a method in which slurry pressure and groundwater pressure are balanced to achieve stability of excavation working face. It is widely used in tunnel construction due to its safety and high-efficiency characteristics. At present, research on safety risk management of slurry balancing shield construction is relatively lacking, and most scholars still mainly focus on technical research. In this paper, based on system engineering theory and from the perspective of whole construction process, a comprehensive evaluation index system for shield construction risk analysis is built by taking “human-machine-material-method-environment” as assessment dimensions. This paper modifies the existing analytic hierarchy process (AHP), combines AHP with fuzzy synthetic evaluation to build a risk analysis model, and quantifies the construction risk by evaluation set and matrix. Combined with case study, the effectiveness of the proposed model is verified, and measures to mitigate safety risks of slurry shield construction are proposed from perspectives of management, economy, and technology. This paper evaluates the overall risk level of project from a systematic perspective, which is an extension of traditional technology-oriented research.

Developing a risk assessment model for banking software development projects based on rough-grey set theory

PurposeRisk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology in all fields and the high failure rate of software development projects, it is essential to predict the risk level of each project effectively before starting. Therefore, the main purpose of this paper is proposing an expert system to infer about the risk of new banking software development project.Design/methodology/approachIn this research, the risk of software developing projects is considered from four dimensions including risk of cost deviation, time deviation, quality deviation and scope deviation, which is examined by rough set theory (RST). The most important variables affecting the cost, time, quality and scope of projects are identified as condition attributes and four initial decision systems are constructed. Grey system theory is used to cluster the condition attributes and after data discretizing, eight rule models for each dimension of risk as a decision attribute are extracted using RST. The most validated model for each decision attribute is selected as an inference engine of the expert system, and finally a simple user interface is designed in order to predict the risk level of any new project by inserting the data of project attributesFindingsIn this paper, a high accuracy expert system is designed based on the combination of the grey clustering method and rough set modeling to predict the risks of each project before starting. Cross-validation of different rule models shows that the best model for determining cost deviation is Manual/Jonson/ORR model, and the most validated models for predicting the risk of time, quality and scope of projects are Entropy/Genetic/ORR, Manual/Genetic/FOR and Entropy/Genetic/ORR models; all of which are more than 90% accurateResearch limitations/implicationsIt is essential to gather data of previous cases to design a validated expert system. Since data documentation in the field of software development projects is not complete enough, grey set theory (GST) and RST are combined to improve the validity of the rule model. The proposed expert system can be used for risk assessment of new banking software projectsOriginality/valueThe risk assessment of software developing projects based on RST is a new approach in the field of risk management. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

A simulation-based risk interdependency network model for project risk assessment

Project risks are mostly considered to be independent in risk management, ignoring interdependencies among them, which can lead to inappropriate risk assessment and reduced efficacy in risk treatment. This study introduces a new Monte Carlo simulation-based risk interdependency network model to support decision makers in assessing project risks and planning risk treatment actions more effectively. The Interpretive Structural Modeling method is integrated into this model to develop a hierarchical project risk interdependency network based on identified risks and their cause-effect relationships. The Monte Carlo method is used to model the stochastic behavior of risk occurrence and to generate numerous possible risk scenarios through simulation. To evaluate single risks and overall project risk level while considering risk interdependencies, five major risk indicators are therefore proposed, namely simulated occurrence probability of a risk, simulated local and global influence of a risk, as well as total risk loss and total risk propagation loss of a project. An additional sensitivity analysis is also included to examine the effects of input uncertainties of this model on risk assessment results. Moreover, two case studies are provided to demonstrate the application and effectiveness of the proposed model. The findings accentuate the significance of considering risk interdependencies in project risk assessment and validate the model's robustness and feasibility in risk management of projects with complex interrelated risks.

Increasing Project Effectiveness by Combining the FMEA Method Results and the Costs of Quality (Based on the Example of an Employee Relationship Management Project)

Abstract Objective: This article presents a project focused on the stabilization of employment in a multi-generational organization in the scope of human resources –specifically, employee relationship management. Methodology: The type of project was evaluated by taking into account different typological criteria. The employee generations were defined by providing time ranges based on dates of birth. All important project stages were presented according to the newest PMI 2017 methodology, with particular attention to the selection of the model of the project team and the division of tasks within the team. The critical path method was used in the description of the course of project activities. Findings: The method of determination of project success factors was specified. Value Added: In accordance with the title of the article, it was, however, shown how one can combine the identification of the level of project risk (using failure mode and effects analysis – FMEA) and the costs of quality to increase the project effectiveness. Recommendations: Projects of this type are important in these organizations where the risk of loyalty is high, which leads to negative economic implications. The advantages from such projects can, however, affect more than the employer.

Radiation protection risk control method of nuclear power project based on sequence optimization

In order to protect the construction safety of nuclear power project and improve the radiation protection effect of nuclear power project, this paper introduces the sequence optimization algorithm to study the risk control method of nuclear power project radiation protection. The radiation risk level of nuclear power project is divided by sequential optimization algorithm, and the control structure of radiation protection risk of nuclear power project is optimized. In this paper, the radiation protection risk detection procedure is used to improve the radiation protection risk detection process of nuclear power engineering, so as to enhance the control effect of radiation protection risk of nuclear power engineering. In order to verify the protective effect of this method, a comparative experiment was designed. The results show that the radiation protection risk control method based on sequence optimization has high control accuracy in the practical application process, which fully meets the research requirements.

CONTINGENCY PERCEPTIONS OF TRADITIONAL VERSUS COLLABORATIVE-BASED CONSTRUCTION CONTRACT CLAUSES

Although contracts are viewed mostly as legal documents whose main objective is to manage risk, its clauses reflect the collaboration level expected between parties. The objective of this paper is to empirically investigate the contracting parties’ perception of collaboration in contract clauses and their correlation to the risk allocation (depicted by the contingency percentage allocated by contracting parties). Through surveys administered to both owners and contractors, survey participants were presented with different project scenarios, including varying degrees of 1) risk allocation in contract clauses (contract collaboration level), 2) project site conditions (project risk level), as well as, 3) prior working relationship with the other contracting party (trust level). Based on these scenarios, participants were asked to allocate a contingency percentage (perception of risk). Results show that clauses identified as low-level collaborative clauses are highly correlated with high contingency percentages. In general, participants representing owners tend to place a lower contingency percentage compared to contractors in all the presented scenarios. This finding reinforces the need to communicate risk perceptions between parties to align their expectations, and thus their estimates of an adequate contingency percentage, ultimately reducing unnecessary project costs. The study also highlights the importance of developing balanced contracts that reflect the trust level exhibited between the parties.

A risk assessment framework of seawater pumped hydro storage project in China under three typical public-private partnership management modes

• Establish unique risk criteria systems of seawater pumped hydro storage under three typical PPP management modes. • Comprehensively evaluate the current risk degree of seawater pumped hydro storage in China. • An improved linguistic hesitant fuzzy sets based cloud model framework is established for risk assessment. • Risk response strategies of seawater pumped hydro storage project in China is proposed. Along with the rapid development of pumped hybrid storage in China, the shortage of inland resources has become a serious problem that restricts its further development. Fortunately, seawater pumped hybrid storage (S-PHS) processes the advantages in saving cost of lower reservoir construction and making full use of coastal resources, which has attracted great attention in China. In view of the characteristics of expanding sources of infrastructure investment funds and improving financial stability of both public and private sectors, varied public-private partnership (PPP) modes are introduced to promote the construction of S-PHS power plant. However, due to lack of experience, high investment, long payback period, and so forth, S-PHS project still holds great uncertain risks in the aspects of economy, environment, technology, etc. Therefore, this paper will study on the risk assessment of S-PHS project under three typical PPP management modes by linguistic hesitant fuzzy sets based cloud model. Result shows that the risk level of S-PHS project locates between “Middle High” and “High”, and PPP-S-PHS processes relatively low risk degree, of which the BOT-S-PHS is the lowest. Moreover, corresponding risk response measures for PPP-S-PHS project are proposed for helping risk prevention and further smooth implementation of PPP-S-PHS project in China.

Risk assessment of offshore photovoltaic projects under probabilistic linguistic environment

Offshore photovoltaic (PV) power generation has received extensive attention for its advantages of saving land resources, high power generation efficiency and proximity to load centers. However, investors are bound to face a series of risks since China’s offshore PV power generation is still in its infancy. To this end, a multi-criteria group decision-making (MCGDM) framework for the risk assessment of offshore PV projects is constructed in this paper. Firstly, 17 risk factors are identified and classified into 4 groups. Probabilistic linguistic term sets (PLTSs) are then introduced to evaluate the criteria values to depict the uncertainty and fuzziness. Furthermore, a probabilistic linguistic ordered average Choquet integral (PLOAC) operator is proposed to aggregate criteria values and deal with the correlations between criteria. In addition, an expert weight-determining model is built based on the entropy and interaction-entropy measures of PLTSs. Finally, the risk levels of the project and each criterion are determined by similarity measure and the corresponding risk countermeasures are given. According to the case study and comparative analysis, the risk level of Zhejiang Ninghai offshore PV project is slightly high. This work provides a scientific theoretical basis for investment decision-making and risk prevention of offshore PV projects.

Impact of safety management system on safety performance: the mediating role of safety responsibility

PurposeSafety management system (SMS) has been widely adopted to explore its influence on safety performance (SP). However, most existing researches recognized SMS as a one-dimension structure and neglected the influences of its subdimensions. Similarly, the impact of safety responsibility (SR) on SP received little attention. This study aims to explore the relationship between subdimensions of SMS and SP, while incorporating the mediating effect of SR.Design/methodology/approachThe research data were gathered from safety management evaluation report of a large real estate enterprise in China during 2010–2017. This paper carries out a series of data analyses to explore the impact of SMS and SR on SP. In order to analyze the synergistic impacts of SMS and SR on SP, path analysis, correlation analysis and mediation analysis were conducted using hypotheses concerning with the main subdimensions.FindingsThe results indicated SMS and SR decreased the project risk level and improved SP of real estate projects. Furthermore, the effect of SR partially mediated the relationship between the SMS and SP.Practical implicationsFindings in this research contribute to improve SP in real estate industry as well as other industries by the active assumption of SR and the successful implementation of SMS.Originality/valueThis research shows the relationship between subdimensions of SMS and SP and the mediating role of SR on SMS–SP relationship to improve SP in real estate industry.