Project Risk Assessment Research Articles

Development of a systems approach to assessment of investment project risks: risks of unacceptably low project profitability

A new systems approach to quantitative estimation of financial risks of investment projects was proposed: an integral risk of the project as a whole for all its parameters at once and the risks for each of its parameters separately. At the same time, the very concept of the project risk has been generalized: instead of the conventional risk of unprofitability, a new, more general concept of the risk of unacceptably low project profitability has been introduced. Two levels of the project profitability were considered: a level acceptable to the investor and a realistically achievable level. Corresponding values of design parameters and indices of financial efficiency of the project were found for these levels. Based on the found values, relative margins of investment acceptability and risks of unacceptably low profitability of the project were calculated. A procedure of comprehensive assessment of the risk of unacceptable low profitability of the project for cases of high certainty and partial uncertainty has been developed. Explicit formulas for quantitative risk assessment of unacceptably low profitability of the project have been derived, ranges of values of all risks under consideration have been determined and appropriate recommendations have been given. Explicit formulas for calculating the values of project risks and dynamic points of project acceptability are convenient and useful for software implementation (for example, within the Monte Carlo method). For the Monte Carlo method and the method of scenarios, another alternative approach to assessing the integral risk of unacceptably low project profitability was proposed by the authors based on the direct calculation of unacceptable scenario values of any criterion of the project financial efficiency. A new index of financial efficiency of the project has also been introduced: a discounted period of acceptable return (discounted payback period of the project is its special case).

Modeling Secondary Phenotypes Conditional on Genotypes in Case–Control Studies

Traditional case–control genetic association studies examine relationships between case–control status and one or more covariates. It is becoming increasingly common to study secondary phenotypes and their association with the original covariates. The Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) project, a study of temporomandibular disorders (TMD), motivates this work. Numerous measures of interest are collected at enrollment, such as the number of comorbid pain conditions from which a participant suffers. Examining the potential genetic basis of these measures is of secondary interest. Assessing these associations is statistically challenging, as participants do not form a random sample from the population of interest. Standard methods may be biased and lack coverage and power. We propose a general method for the analysis of arbitrary phenotypes utilizing inverse probability weighting and bootstrapping for standard error estimation. The method may be applied to the complicated association tests used in next-generation sequencing studies, such as analyses of haplotypes with ambiguous phase. Simulation studies show that our method performs as well as competing methods when they are applicable and yield promising results for outcome types, such as time-to-event, to which other methods may not apply. The method is applied to the OPPERA baseline case–control genetic study.

Construction Risk Assessment of Deep Foundation Pit Projects Based on the Projection Pursuit Method and Improved Set Pair Analysis

Accurately evaluating the construction risk of deep foundation pit projects is crucial to formulate science-based risk response measures. Here, we propose a novel construction risk assessment method for deep foundation pit projects. A construction risk evaluation index system based on a work breakdown structure-risk breakdown structure matrix was established to deal with the complex risks of deep foundation pit construction. The projection pursuit method optimized by particle swarm optimization was used to extract the structural features from the evaluation data to obtain objective index weights. The calculation method of the five-element connection number in the set pair analysis was improved to evaluate the static construction risk. The partial derivatives of the five-element connection number were utilized to assess the dynamic construction risk. The Qi ‘an Fu deep foundation pit project in China was selected as a case study. The results show that the construction risk was acceptable and decreased during the construction period, which was consistent with actual conditions, demonstrating the effectiveness of this novel method. The proposed model showed better performance than classical methods (analytic hierarchy process, entropy weight method, classical set pair analysis, fuzzy comprehensive evaluation, gray clustering method, backpropagation neural network, and support vector machine).

VOCs and Odor Episodes near the German-Czech Border: Social Participation, Chemical Analyses and Health Risk Assessment.

People living on both sides of the German–Czech border are subject to episodes of odor air pollution. A joint German–Czech air sampling and risk assessment project was established to identify the substances responsible and their sources. Twenty-four volunteer study participants, 14 from the NW Czech Republic and 10 from Germany (Saxony) reported odors and collected canister samples during sampling periods in winter 2017 and 2018 and autumn 2018. Canister samples and passive samplers were analyzed for volatile organic compounds (VOCs) and passive samplers were analyzed for VOCs and carbonyls. OAVs (Odor Activity Values) and back trajectories were calculated with the aim of identifying the odor sources. Calculated OAVs were in excellent agreement with perceived smells close to an oil processing plant. Odorants identified in fifty canister samples during odor episodes and carbonyl measurements close to the edible oil processing plant were used for health evaluation. Odors reported by participants in Saxony frequently differed from those reported by participants in the Czech Republic. This suggests that certain sources of odor lying on either side of the border only affect that side and not the other with similar considerations regarding health effects. VOCs, including carbonyls, were also sampled at two relatively remote locations during winters of 2017 and 2018; two main sources of odorous compounds were identified at these sites. Analysis of samples taken at sampling sites shows that VOC air pollution and, to a lesser extent carbonyl pollution, originate from both industrial and local sources. Even though levels of sampled substances were not associated with acute effects at any site, long-term exposures to selected compounds could be cause for concern for carcinogenicity at some sites. Odors in Seiffen were associated with carcinogenic compounds in can samples. Although not necessarily representative of long-term exposures to the compounds studied, results such as these suggest that further study is needed to better quantify long-term exposure to potentially harmful compounds, and to either confirm or deny the existence of substantive health risk.

Risk Management Practice Adopted in Road Construction Project

Purpose: Zero risk construction is only a dream not reality as there is nothing certainity in the real world and scientists are only capable of coverting the same into risk with high level data science. The practice of risk management is an attempt to highlight risk elements with a case of urban road construction in Sindhupalchowk district, Province 3, Nepal. Design/Methodology/Approach: The 5-point Likert scale questionnaire survey was done to collect the primary data. Risk Management Practice is documented based on survey response in percentage through charts and graphs. Field visit were done for visual assessment of the construction procedure along with key informant interview and Secondary data of Detail Project Reports, Design and Drawings were effectively analyzed. Cronbach’s alpha was used to measure the reliability and triangulations were done for validity. Findings/Result: The results from this research indicates that contractor’s organization are averagely aware with a mean score of 3.30 about Risk Management Practice and averagely practicing risk management formally with mean score of 2.83. They are averagely analyzing risk management techniques with mean score of 3.07. Mean score is slightly higher based on client’s perspective with score for awareness being 3.93 and score for risk management being practiced formally is 3.13. Risk analysis score based on client’s management is 3.40. Mostly adopted technique of risk identification is monitoring and evaluation report of similar past projects and direct judgment is widely used technique for risk assessment of road construction projects at Sindhupalchowk district based on both client’s and contractor’s perspective. Risk response strategy based on contractor’s perspective is monitoring the risk and preparing contingency plan whereas that for client is transfer of risk. Originality/Value: It is action research which is significant for professional to understand the practices of risk management being adopted by Nepalese Contractors in hilly region of Nepal. Paper Type: Ex-Post Facto Research

Selecting Appropriate Risk Response Strategies Considering Utility Function and Budget Constraints: A Case Study of a Construction Company in Iran

Successful implementation of construction projects worldwide calls for a set of effective risk management plans in which uncertainties associated with risks and effective response strategies are addressed meticulously. Thus, this study aims to provide an optimization approach with which risk response strategies that maximize the utility function are selected. This selection is by opting for the most appropriate strategies with the highest impact on the project regarding the weight of each risk and budget constraints. Moreover, the risk assessment and response strategy of a construction project in Iran as a case study, based on the global standard of the project management body of knowledge (PMBOK) and related literature, is evaluated. To handle the complexity of the proposed model, different state of the art metaheuristic algorithms including the ant lion optimizer (ALO), dragonfly algorithm (DA), grasshopper optimization algorithm (GOA), Harris hawks optimization (HHO), moth-flame optimization algorithm (MFO), multi-verse optimizer (MVO), sine cosine algorithm (SCA), salp swarm algorithm (SSA), whale optimization algorithm (WOA), and grey wolf optimizer (GWO). These algorithms are validated by the exact solver from CPLEX software and compare with each other. One finding from this comparison is the high performance of MFO and HHO algorithms. Based on some sensitivity analyses, an extensive discussion is provided to suggest managerial insights for real-world construction projects.

Assessment of Risk and Uncertainty Factors Inherent in Nigerian Highway Project Using Analytical Hierarchical Process

The study presents a framework through which risk and uncertainties in Nigeria highway projects can be appraised using the analytical hierarchical process model. Pairwise comparison matrix was performed on eleven (11) risk and uncertainty factors that affect highway project performance through a questionnaire survey conducted among two hundred and four (204) respondents, which involved various stakeholders in the highway construction industry using Saaty’s AHP rating scale. The relative weights (significance/impact level) of each of the highway risk factors were estimated during the AHP model development. The results in descending order of risk factors priorities are Standard & Regulations (S&R), Construction (C), Project Staff (PS), Project Sponsor (PSp), Design (D), Project Finance (PF), Economic (E), Equipment (EQ), Environmental & Geotechnical (En&G), Site Location (SL) and Subcontractor (S) with impact levels of 16.6%, 14.2%, 13.9%, 13%, 12.7%, 12.2%, 10.8%, 9.8%, 6.2%, 4.2%, and 3.8% respectively. The model was validated using the statistical consistency test, with the model showing a consistency ratio equal to 0.1. The model was then applied to five (5) highway construction projects which had been constructed to predict the ones with the most and least risks. The result was in tandem with that which was given by the project managers from experiences on the project. This study showed that the Analytical Hierarchical Process (AHP) decision support model can effectively be used for risk assessment and prioritization of highway construction projects for efficient resource utilization in Nigeria.

Risk assessment of unfavorable interorganizational relationships in CSR projects considering the logistic aspects

Purpose: The aim of this paper is to present a new model for risk assessment of unfavorable interorganizational relationships, among other things, in ventures classified as corporate social responsibility (CSR) projects. Design/methodology/approach: Scenario analysis, brainstorm sessions, literature study and own observations of interorganizational projects were used to develop a list of unwanted events and factors determining their occurrence. In the proposed risk assessment model, fault tree analysis and fuzzy logic were applied for qualitative and quantitative risk analysis. Thanks to applying the elements of fuzzy sets theory, it was possible to decrease the uncertainty and lack of precision in obtaining crisp values of the basic events’ probability. Findings: In this work 13 basic events and 41 risk factors determining occurrence of unfavorable interorganizational relationships in ventures were identified and described. The proposed model enabled to carry out qualitative and quantitative risk assessment of unfavorable interorganizational relationships projects. Its practical application was shown in an example of interorganizational CSR project concerning the organization of a mass event, considering its logistics aspects. Research limitations/implications: It is necessary to involve experts in risk assessment. This could be overcome by applying machine learning in future research. Practical implications: The application of the proposed model allows to effectively identify the critical risks, which should be of particular attention during the risk treatment stage. It aims to give a helping hand to all managers and practitioners who want to deliver attainable and successful interorganizational projects, supporting meeting the expectation of the engaged stakeholders. Social implications: Socially responsible activities contribute to solving and counteracting social problems. Originality/value: A novel risk assessment model of unfavorable interorganizational relationships in which 13 basic events and 41 risk determinants were considered. The model was presented at ventures classified as Corporate Social Responsibility projects. Keywords: risk assessment; interorganizational relationships; Corporate Social Responsibility; fuzzy logic; logistics for the organization of a mass event. Category of the paper: Research paper.

Efficient Fine Tuned Trapezoidal Fuzzy-Based Model for Failure Mode Effect Analysis Risk Prioritization

Many industries struggle with different project failures including Enterprise Resource Planning (ERP) implementations projects which has high failure rates too. Failure Mode Effect Analysis (FMEA) is an extensively utilized to analyze failure modes in risk assessment in various industry projects including ERP implementation projects. Nevertheless, in the traditional FMEA system, ignoring the Interdependencies among various failure modes as well as the relative importance of risk and non-injective and non-subjective nature of conventional RPN functions leads to challenges in analysing and assessing the risk. This may mislead in the addressing the prioritization of the Risk. Therefore, an efficient FMEA framework is proposed using Fine Tuned Trapezoidal Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution (FTTF-TOPSIS). The developed FMEA framework focuses to avoid data complications while preparing or collecting the data by using a hierarchical matrix management for data preparation. Uncertain risk, cost, and relative dependency are considered as additional parameters regarded by the work to calculate RPN. Mathematical models such as conservative method together with the Square Root Kragten Method (SRKM) are used to find the relative dependency along with uncertain risks. Thereafter, a highly reasonable along with credible outcome to rank the risk, FTTF-TOPSIS is employed. Finally, to demonstrate the proposed method’s efficiency together with benefits, a comparation is made with the other models.

Comprehensive Methodology of Risk Assessment of Construction Projects in Current Circumstances

Comprehensive Methodology of Risk Assessment of Construction Projects in Current Circumstances

Organizational Learning and Risk Management Maturity: Systematic and Meta-Analyses Approach

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of investigating the role of developers in the economic development of the country. The relevance of this scientific problem decision is that the risk management maturity on the part of developers is often underestimated when researching developing real estate markets. Systematization of the literary sources and approaches for solving the problem of risk management proved the presence of a significant number of studies that confirm the hypothesis that some of the developers have not reached the normalized risk management maturity scale. The main purpose of the paper is to explore the role of organizational learning in enhancing risk management maturity, as a means of setting research agenda for its empirical evaluation in emerging economies. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, the article systematizes the scientific literature on the importance of organizational learning in managing real estate investment maturity risks in emerging economies like Nigeria. The object of the research was indexed studies on Web of Scholar, Google Scholar, Emerald and Pubmed databases. Qualitative analysis methods have become a methodical toolkit for determining the parameters of organizational learning that contribute to the achievement of risk management maturity. The paper confirms and theoretically proves that risk knowledge acquisition, integration and transformation had potentials of respectively leading to sustainable risk identification, assessment and mitigation in property development projects. The results of the study form the basis for the understanding by scholars, practitioners and policy makers of their contribution to scientific research on the issues of a risk management mature property development sector in emerging economies. The strengths of this study are that it aims to identify the importance of organizational learning in risk management mature property investment in emerging markets.

Risk assessment of sewage treatment Public Private Partnership projects in China

Risk assessment of sewage treatment Public Private Partnership projects in China

Next-generation risk assessment of chemicals - Rolling out a human-centric testing strategy to drive 3R implementation: The RISK-HUNT3R project perspective.

In many industrial sectors, there is a need for reliable ways to evaluate the safety of chemicals with methods anchored to human biology and pathology. For this purpose, many animal-free new approach methods (NAMs) have been developed and implemented in various stages of risk assessment. Now it is time to assemble individual NAMs into a comprehensive next-generation risk assessment (NGRA) strategy. The European Horizon 2020 RISK-HUNT3R project (Risk assessment of chemicals integrating human-centric next-generation testing strategies promoting the 3Rs) has been designed to promote a combination of computational toxicology, in vitro toxicology, and systems biology. It is anticipated that this approach will lead to faster and more accurate risk assessment procedures. The RISK-HUNT3R NGRA strategy will be developed to address the implementation of a comprehensive NAM toolbox into the regulatory framework. Critical conceptual approaches of the project include i) the integration of human-relevant data on biotransformation and elimination, ii) the translation of high-content mode-of-action datasets into predictions of adverse outcomes, iii) development of quantitative adverse outcome pathways (qAOPs), and iv) quantification of uncertainties associated with the predictions based on NGRA strategies. Many of the project steps will be used iteratively to generate datasets with sufficient quality and certainty for NGRA. Scientists and regulators will work together on case studies to evaluate practical applicability of NAMs and strategies to combine information therefrom. Here we delineate how the strategy will be deployed to establish an overall NGRA framework for chemicals, pesticides, food additives, and drugs.

Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L24 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

Hanoi urban transportation projects risk assessment

The urban transport projects are taking place rapidly in Hanoi, especially from 2016 to 2030. The urban transportation projects face risks. There are objective risks and there are many subjective risks. All risks affect the pro-ject efficiency. The clear assessment of risks will be the basis for providing appropriate risk management solutions. This paper applies the survey method and the possibility - severity matrix to assess the risks and separate the risks according to the dangerous level. The risk assessment is considered of two criteria the risk possibility and the risk severity. The findings revealed 17 dangers in the medium danger zone (yellow area) and 09 threats in the high danger zone (red area). This demonstrates that urban transportation projects face several hazards, and risk management is challenging for managers. It necessitates managers who are capable of effectively analyzing and evaluat-ing risks.

Календарное планирование инвестиционных проектов в условиях ограниченности ресурсов и неопределённости

Investment project scheduling problem is an important problem in the field of production management. Determining the optimal start time for activity allows ensuring a higher level of project's profit. The article considers an investment project that involves the implementation of a given number of activities for a certain period of time. Each of the activities is characterized by the duration of its implementation, the cost of resources and the income that it provides. In addition, the technological and organizational relationships between the activities are known. This, in particular, can be expressed in the need to complete one activity before doing another. The sources of project financing are the organization's own funds, as well as income received when performing activities. The article considers a situation when all project resources can be presented in monetary form. The project budget is assumed to be known in advance. The planning of the budget, as well as income and expenses for the project, is carried out by years. The net present value (NPV) was used to evaluate the results of the project implementation. This indicator represents the value of the profit from all planned activities, discounted to the time the investment started. Thus, the investment project scheduling problem that we are considering is to find the optimal start time for each of the activities, at which the restrictions on the sufficiency of funds, the interconnection of activities are met and the maximum NPV is ensured. In the proposed statement of the resource-constrained project scheduling problem, the only parameters expressing the uncertainty of the conditions for the implementation of the project are the components of the payment flow. We considered a situation in which the timing of the project and individual activities, as well as the company's own funds, are not subject to fluctuations. Random project parameters were considered independent. The article presents an overview of approaches to project risk assessment for different ways of taking into account the uncertainty factor. In particular, options for scenario analysis, outcome tree construction and simulation were considered. Using the genetic algorithm developed by the authors, a series of computational experiments was carried out. The analysis was carried out for cases of discrete and continuous distribution of project parameters. Based on the results of the experiments, schedules were found that are optimal for various values of random project parameters. For each schedule, the risk of stopping the project due to lack of funds was determined. The found schedules were compared by average NPV values, as well as by risk level. Conclusions were drawn about the choice of schedule, taking into account the cost of raising borrowed funds.

Constructing a Risk Assessment Framework for Building Integrated Photovoltaic (BIPV) Projects from the Perspective of Four‐Dimensional Risk

Building photovoltaic integration (BIPV) technology can effectively solve the urban energy shortage, environmental damage, and other environmental problems, which is of great significance to the sustainable development of the urban. However, the practical application of BIPV technology has been very slow, and BIPV projects have encountered numerous obstacles and risks in the process of promotion and construction. Although some researchers have conducted qualitative studies on these obstacles and risks, systematic risk assessment methods for BIPV projects are missing. This study aims to systematically develop a framework to assess the risk of BIPV projects to address this gap. First, a comprehensive risk indicator system is established using literature analysis and expert interview methods. Second, DEMATEL (decision‐making trial and evaluation laboratory) is used to calculate constant rights. Then, the risk assessment is carried out from the perspective of four‐dimensional risk including severity, possibility, urgency, and uncontrollability. The variable weight theory is used to calculate variable weight. The data fusion and risk level determination are realized by the matter‐element extension model. Finally, a case study is conducted to verify the feasibility and applicability of the BIPV project risk assessment framework. The results show that the comprehensive risk grade of the BIPV project in Qingdao is III, which belongs to medium risk. In addition, some suggestions are made based on the evaluation results. This study can enrich the methods in the field of risk assessment, and the results can provide a valuable reference for BIPV project investors and decision‐makers.

Project Management in Public Administration. Risks and Challenges

Project risk is the object of interest of people and institutions implementing and financing project activities. Each project brings new challenges and risks but also a chance to gain knowledge and development. That is why project management is becoming a standard that receives more and more attention. At the stage of launching a project, it is necessary to conduct risk analysis, which allows risks identification, characterisation and proper assessment. This analysis enables the development of a risk prevention plan, indicating ways to respond to challenging situations when they occur. It also allows the introduction of risk monitoring methods. The specified stages of risk management are well known in public administration, especially to those institutions that raise funds for implementing projects and then manage them. In public administration, institutions implementing projects are obliged to carry out management control, and some responsibilities related to risk management have been imposed on applicants. Therefore, it becomes necessary for project managers and unit managers to understand its (risk) importance for achieving the objectives of the organisation’s projects and the potential benefits that can be obtained after its effective implementation. Organisations that can take into account risk management awareness in projects will be able to use the risk management process to improve the results and increase the satisfaction of all parties interested in the implementation of projects. This article aims to present the identification and risk assessment in projects and challenges faced by the public administration, including the security system, which has been dynamically acquiring funds for implementing projects in recent years.

A Sustainability-Based Risk Assessment for P3 Projects Using a Simulation Approach

Integrating sustainability in the risk management process is an emergent problem, especially for efficient infrastructure delivery. For the case of complex projects like public–private partnerships (P3), traditional management practices offer a limited capacity to address long-ranging risk impacts on the social, economic, and environmental fabric within and around the project boundaries. Although P3 projects are objective-based contracts, present risk models rarely delineate risk impacts on focused project objectives. The relevant studies are very scarce creating a limited understanding of available approaches to conducting sustainability-based risk management for P3 projects. As risk and sustainability are two inherently subjective concepts with multiple interpretations, their combined assessment within a single framework demands a pragmatic approach. Therefore, the current study presents a model for conducting a sustainability-based risk assessment of P3 infrastructure projects through global data. Monte Carlo simulation is employed to further define the probabilistic risk ranges and risk ranks over relevant triple-bottom-line-based sustainability indicators for highway sector P3 projects. Findings are further demonstrated through two highway case studies and relevant mitigation strategies are also suggested. In the end, an implementation framework and future recommendations for the application of study findings on actual projects are also suggested. The study has useful implications for practitioners and researchers alike aiming for the delivery of sustainable complex projects.

Construction Safety Risk Assessment of Large-Sized Deep Drainage Tunnel Projects

Frequent extreme climate events and rapid global urbanization have amplified the occurrence of accidents such as waterlogging or the overflow of pollution in big cities. This has increased the application scenarios of large-sized deep drainage tunnel projects (LSDDTPs). The scientific and accurate evaluation of the construction safety risks of LSDDTP can effectively reduce the corresponding economic losses and casualties. In this paper, we employed the hierarchical holographic model to construct the safety risk list of LSDDTPs in terms of the risk source and construction unit. Based on social network analysis, we then screened key indicators and calculated the weights of all secondary indicators from the correlation between risk factors. We subsequently developed a construction safety risk assessment model of LSDDTPs based on the matter-element extension method. The Donghu Deep Tunnel Project in Wuhan, China, was selected as a case study for the proposed method. The results of empirical research demonstrated that eight indicators (e.g., failure to effectively detect the change of the surrounding environment of the tunnel project) were key factors affecting the construction safety risk of IV, which is within the acceptable risk level. Our proposed model outperformed other methods (the fuzzy comprehensive evaluation, analytic hierarchy process, entropy weight method, and comprehensive weight method) in terms of scientific validity and research advancements.