Project Risk Analysis Research Articles

A Fuzzy Logic Application to Manage Construction-Cost Escalation

In large-scale projects, such as transport infrastructures, the cost-planning phase stands out as one of the most crucial for the project’s success. Cost and time overruns, during the construction phase, are often the cause of project failure. A meticulous, conscious, and accurate ex-ante analysis of cost and time assessment can greatly contribute to the efficient and effective completion of a project. Various approaches have been developed to estimate and mitigate cost overruns. Such mitigation is subject to careful analysis of project risks, encompassing construction, environmental, social acceptance, and market risks. In this contribution, we propose the implementation of the risk-assessment tool, suggested by the National Anti-Corruption Authority (ANAC), using fuzzy logic to enhance its effectiveness. Thanks to the implementation of fuzzy prioritizations, the risk matrix and the associated risk levels, which are obtained by combining the event’s probability of occurrence and its expected impact on costs, have been clearly and structurally defined. This tool can facilitate risk ranking and, therefore, the implementation of their management strategies during the design and construction phases as well as the consensus-creation process. This application can therefore be used by public authorities as a transparent and manageable tool to assess expected risk during the design and implementation phases of the project.

Risk Analysis in New Product Development Projects in the Technology Industry

Risk Analysis in New Product Development Projects in the Technology Industry

ADAPTATION OF AN AGRICULTURAL PROJECT TO THE REGULATION OF GREENHOUSE GAS EMISSIONS

Using an original methodological approach, a model analysis of the adaptation of an agricultural project to the regulation of greenhouse gas emissions from agricultural land was carried out for the farms in the south of Russia. Emissions from both technological and ecosystem processes were taken into account. Methods of operations research and simulation modeling are applied to the study of two options for regulating greenhouse gas emissions, i.e. through market mechanisms focusing on the cost of carbon units in the EU and through the administrative control, which sets the emission limits. For each of the options, the optimal intensity of use was estimated for each land plot involved in the project.The proposed methodology supplements the scientific and methodological support for the analysis of the largescale agricultural projects under the state regulation of the impact of economic activities on the Earth’s climate. It is applicable to projects with a significant spatial dispersion of plots. As a result of the study, the scientific visions of the climate policy impact on the technological configuration of agricultural production were specified. A significant margin of sustainability of agriculture in the south of Russia to carbon market methods has been revealed; It is shown that as the restrictive administrative approaches are tightened, farmers prefer to stop the intensive use of areas with the highest productivity potential while maintaining the maximum production intensity within the rest. The totality of the results obtained is recommended for practical application for developing and analyzing investment agricultural projects, including the analysis of project risks, as well as for improving the state environmental and climate policy as a tool for analyzing its consequences.

Improving safety design for gas pipeline installation via horizontal directional drilling: a pipe stress analysis approach

Horizontal Directional Drilling (HDD) has today emerged as a significant and efficient Horizontal Directional Drilling (HDD) has today emerged as a significant and efficient technique for installing pipelines for a variety of purposes, including the production of oil, natural gas, water, sewer, electrical, and telecommunications. Due to the complexity of the technology and the intricate interplay of numerous processes, the safety risks associated with process uncertainty are substantial. However, risk analysis for HDD projects is generally done using qualitative methods. One of the most common factors used for HDD risk assessment is Pipe Stress Analysis (PSA). In this article, a combination of material evaluation and PSA for HDD safety design is suggested to improve the risk analysis. The evaluation will commence with an assessment of the material, followed by an examination of the wall thickness. Subsequently, an analysis of HDD design and pipe stress will be conducted. Using 10-inch API 5L Gr. B pipe, the safety design was successfully tested for a gas pipe project. When using HDD, a natural bend value of no less than 415.3 meters must have a horizontal length of 168 meters. According to the curvature, the length of the entire pipe is 169.03 meters. The combined installation stress was less than 1, while the combined operation stress was 114.87 MPa. These two values met the criteria specified in the standard. Overall, those steps were able to ensure that the HDD installation design is safe for construction.

Underpinning risk dimensions of sponsored institutional R&D projects through cutting-edge fuzzy TOPSIS and fuzzy DEMATEL approaches

PurposeThis study aims to enhance the success of Sponsored Institutional R&D Projects (SIRPs) by investigating the influence of risk dimensions over four criteria Cost overrun, Time overrun, Schedule overrun, and Quality of projects. The study identifies risk dimensions and prioritizes and explores causal relationships to guide risk mitigation strategies during project execution.Design/methodology/approachThis study was conducted with qualitative data obtained through a systematic questionnaire from 10 domain experts associated with SIRPs. Through an extensive literature review, the study identifies the ten risk dimensions, Fuzzy TOPSIS was employed for prioritizing the explored risk dimensions and Fuzzy DEMATEL explored the qualitative causal relationships among these dimensions. The sensitivity analysis was conducted to validate the robustness of findings by adjusting the weightage assigned to experts.FindingsThe findings reveal financial risk as the highest ranked and business risk as the least influential among identified dimensions. The study also highlights management risk as the most significant, followed by business risk and sensitivity analysis concludes that the findings are robust, lacking significant judgment bias.Research limitations/implicationsThis study contributes to risk management strategies for SIRPs, to ensure timely completion within the allocated budget. The findings of the study can be implemented in other such SIRPs. The study also informs funding agencies' policies and project monitoring mechanisms and advancing project management practicesOriginality/valueIts originality lies in being the first to systematically identify and prioritize risk dimensions, adding significant value to SIRP management and academic discourse on project management and risk analysis.

Project Risk Analysis and Early Warning of Culture and Tourism Group Financial Leasing Company

Under the background of strict regulation, due to the cyclical adjustment of the financial leasing industry, some top companies have maintained a growth trend in asset size and net profit. Internal differentiation has emerged in the financial leasing industry, increasing operational pressure, and a slowing trend in asset size growth. Although the overall pressure on credit quality has eased, downward pressure on asset quality is widespread, and the recovery period for narrowing profit space is still long. With the continuous upgrading and iteration of digitization, intelligence, and specialization, Culture and Tourism Group Financial Leasing Company should strengthen its professional ethics, improve its risk analysis and prediction capabilities, design integrated business guidelines for due diligence information collection and risk analysis, rely on big data to build a leasing asset identification, evaluation, monitoring, and early warning system, and establish a comprehensive, multi angle, and lean risk analysis and early warning mechanism. Through case analysis, problems are identified in a timely manner, and continuous reflection and improvement are made. Business process diagrams are drawn according to different scenarios, crisis warning indicators are set up, and a lean risk management team is formed. Crisis warning signals are continuously tracked and released, and processes and asset quality management are continuously improved. A lean risk control system is established to reduce risk losses and create benefits for the enterprise.

Quantitative Risk Analysis for Construction Projects Considering Risks Correlations and Fuzzy Logic

Construction projects have a high level of uncertainty because of several risk factors. Risks may affect projects in many ways resulting in time delays or cost overruns. Thus, the evaluation of uncertainty is required to get a reliable schedule. This research proposes a method for project scheduling considering risks. Expert judgment is used to identify and analyze risks. Potential risks are identified through Failure Mode Effect Analysis (FMEA). Risks impact is evaluated through fuzzy logic and Monte Carlo Simulation (MCS). The simulation considered the relationship between risks, and risks and activities.

Work Accident Risk Analysis in Tukad Ayung Bridge Replacement Project

Analysis of the risk of work accidents in the Tukad Ayung Bridge replacement project needs to be carried out by identifying, assessing, and controlling risks using the HIRARC method. This study aims to conduct a work accident risk analysis in the Tukad Ayung Bridge replacement project, precisely in the implementation of concrete girder installation. The data used are qualitative and quantitative data with primary data sources and secondary data. The data collection techniques used are observation, interviews, questionnaires, literature studies, and documentation studies. The data analysis technique used is HIRARC. The results showed that; 1) There are 24 types of work accident risks identified in the concrete girder installation work in the Tukad Ayung bridge replacement project in seven stages of work, namely, the concrete girder preparation stage, girder truss making, erection (segmental girder setting), prestressed steel installation (strand), strand cable stressing work, girder concrete tendon grouting, and diaphragm installation stage, 2) The results of risk analysis on concrete girder installation work on the project The replacement of the Tukad Ayung Bridge, is in the moderate category, which is as many as 12 risks with a percentage of 50%. Furthermore, as many as 11 risks are included in the high category with a percentage of 45.837%. Meanwhile, in the extreme category as much as one risk with a percentage of 4.17%, 3) Risk control efforts that can be carried out from the three levels of risk found, namely moderate, high, and extreme, namely by reducing risk through administrative control, engineering control, and warning system.

Intelligent Risk Analysis of Investment Projects in the Extractive Industry

Intelligent Risk Analysis of Investment Projects in the Extractive Industry

Project Risk Management: modern trends and effective practices

The article is devoted to the management of project risks, with the aim of their timely detection and identification, which in turn will ensure the successful implementation of the project and its completion. Special attention is paid to the stages of project risk management and analysis of methods aimed at minimizing and avoiding project risks.
 The most modern and well-known methods include such methods as: risk avoidance; insurance; self-insurance; risk financing; diversification; risk taking; risk limitation; risk distribution and risk prevention, the complex application of which will ensure the successful implementation of the project and protect the project from the influence of destabilizing external and internal factors.

A hybrid forecasting model to predict the duration and cost performance of projects with Bayesian Networks

This paper presents a new hybrid forecasting model to predict the final time and cost of a project using input parameters from the project scheduling and risk analysis literature. The hybrid method integrates two well-known risk models. A Structural Equation Modeling constructs and validates a theoretical risk model to represent known relations between project indicators and the project performance. A Bayesian Networks is used to train the theoretical model using artificial project data from the literature. These two integrated models are then used to predict the final duration and cost of a new unseen project.The accuracy of this integrated model is compared with other well-known forecasting methods from the literature. The computational experiments on a set of 33 empirical projects show that risk models demonstrate a noteworthy advantage for time and cost forecasting. To show the usefulness of this method, it is compared with a set of known machine learning forecasting algorithms.These static predictions of risk models are also compared with some well-known dynamic forecasting methods that continuously update the time/cost predictions along the project progress. These dynamic models make use of predictors from the earned value management and earned duration management literature. The results show that the static risk models offer more precise forecasts than the dynamic methods in the first half of the project progress for time forecasting, but then loose their power in favor of the dynamic forecasts.

ТЕОРЕТИЧНІ АСПЕКТИ ВИКОРИСТАННЯ МЕТОДУ МОНТЕ-КАРЛО ДЛЯ МОДЕЛЮВАННЯ ОЦІНКИ ЕФЕКТИВНОСТІ ІНВЕСТИЦІЙНИХ ПРОЕКТІВ

This article is dedicated to the theoretical study of applying the Monte Carlo method for evaluating the efficiency of investment projects within enterprises. The author examines the principles and advantages of using this stochastic method in modeling economic parameters and project risks, as well as analyzing the method's capabilities in generating various scenarios for justifying investment decisions based on probabilistic calculations. The article explores methodological aspects of simulation modeling of investments, including the creation of applied mathematical models that simulation real economic processes and situations using pseudorandom numbers to generate random variables. This allows for the determination of potential financial outcomes of investment projects with varying degrees of risk and uncertainty. The historical development of the Monte Carlo method and its contemporary use in investment analysis are highlighted, emphasizing its significance in providing a deep understanding of variations in the initial data of investment projects. Particular attention is paid to the method's ability to adapt and account for uncertainty in complex investment scenarios, making it an indispensable tool for investment analysis. Efficiency indicators of investment projects, which are used to assess the economic benefits of investments, are analyzed. Key indicators include Net Present Value (NPV), Internal Rate of Return (IRR), and Profitability Index (PI). The Monte Carlo method is used to model the probabilities of various financial scenarios and influences the assessment of these indicators, providing a more detailed analysis of potential risks and returns from projects. The article emphasizes the importance of the Monte Carlo method as a foundation for developing new approaches to evaluating investment projects and managing risks. This contributes to a better understanding of how modern approaches to simulation modeling can affect the decisions of investors and managers, especially in situations where classical evaluation methods may be ineffective. Therefore, the application of the Monte Carlo method in modeling investment projects not only helps assess overall efficiency indicators but also allows for a detailed analysis of potential investment project risks, making it an indispensable tool in contemporary investment analysis.

Effects of Project Risks Management and Sustainability of Manufacturing Industry Projects in Rwanda- A Case Study of Sulfo Industries Ltd

The study assessed project risks management and manufacturing industry project sustainability in Rwanda. Three specific objectives were pursued: to investigate the influence of monitoring and evaluation practices, project risk analysis, and project knowledge and communication on project sustainability. The research followed a descriptive design, utilizing both quantitative and qualitative methods. Out of a total population of 189, 117 respondents were selected through a simple random sampling technique. Data was collected through questionnaires, interviews, and document analysis, and analysis was performed using SPSS version 21. The study revealed several key findings. Project risk analysis was found to have a positive effect on the sustainability of manufacturing industry projects, with a mean of 1.556 and a standard deviation of 0.955. Similarly, risks monitoring and control (mean 1.485, standard deviation 0.813) and project knowledge and reporting (mean 1.501, standard deviation 0.899) were linked to increased sustainability. A strong positive relationship (R=0.884) was identified between these variables. In conclusion, the research underscores the importance of effective project risk management practices, including risk analysis, monitoring, control, and knowledge dissemination, in ensuring the ongoing sustainability of manufacturing projects. The study specifically recommends that Sulfo Industries and other relevant stakeholders should implement these risk management practices to maintain the effectiveness and sustainability of their manufacturing projects in Rwanda.

Implementation of Infrastructure Project Through Public-PrivatePartnership in the Southern Part of West Java Province

The objective of this research is to investigate how infrastructure projects are executed in government-business partnerships. The study aims to accomplish three objectives: (1) evaluate the implementation of these projects, (2) identify the obstacles encountered during project execution, and (3) analyze the strategies utilized in executing disruptive innovation in government-business partnership infrastructure projects. The research employs a qualitative descriptive approach, carried out for a period of one year, from July 2021 to June 2022. The study involves six experts from the Transportation Agency, two individuals from the Department of Public Works and Public Housing, one representative from Regional Planning and Development Agency (RDPA), and one academician, with structured in-person interviews used as the primary data source. The research indicates that executing infrastructure projects through disruptive innovation in construction firms involves several steps, such as preparing for disruption, developing internal and external innovation, using incremental innovations, and utilizing open innovation to explore new technologies and business models. Nonetheless, the study identifies several obstacles encountered during the execution of these projects, including inadequate infrastructure project risk analysis, poor coordination among stakeholders, limited funding allocation, and land availability issues. To mitigate these challenges, the study recommends the need for independent professional consultants, improved project planning, regulatory ease, fiscal incentives for investors, and legal guarantees for private investors to ensure equal rights as state-owned enterprises in executing feasible projects, and good coordination among stakeholders

Risk Analysis and Research for Construction Projects

As the population grows and the demand for public infrastructure increases, more and more construction projects are being carried out. In order to avoid the failure of construction projects due to their high level of complexity, risk anticipation and risk response can be made through the study of project risks, which can greatly improve the success of construction projects. The investment and time spent on a construction project are huge and if the project fails or is delayed, there will be serious consequences. This is why construction project risk management is so important for construction projects. Therefore, this paper analyses the risks of construction projects. It finds that construction project risks can be classified as internal and external risks and suggests improvements to the existing three-step project risk management process Identify-Assess-Respond, adding a project risk review. This paper enriches the study of risk classification and management processes for construction projects and proposes risk management process measures that have implications for future construction projects to deal with risks more efficiently.

Risk Analysis of Transport Requalification Projects in the Urban Mobility Problem Caused by a Mining Disaster

Background: This paper proposes a risk analysis of transport requalification projects in the urban mobility problem caused by a mining disaster related to irregular rock salt extraction in the city of Maceió, Brazil. Methods: The model is composed of three main steps: problem definition, risk management, and decision analysis. For this purpose, we used the Picture Fuzzy-Delphi method for data collection and experts’ judgment elicitation and the Delphi method was used to assess the problem without interference from others. In addition, we used Picture Fuzzy Sets (PFSs) to incorporate uncertain information in the decision-making process. Results: The results of the proposed model demonstrated consistency and relevance to the discussion. The application of methods shows the risks of the project based on a general perspective. It evaluates the sustainability tripod: economic, environmental, and social points of view, assessing the occurrence risk and intensity of the risk. Conclusions: The main objective of the work was achieved; however, some limitations of this study are related to the methods used to assess risks and the options of projects of requalification available at the moment of data analysis. This paper contributes because it systematizes the risk management of projects related to requalification in urban mobility.

Generalized linear diophantine fuzzy Choquet integral with application to the project management and risk analysis

Generalized linear diophantine fuzzy Choquet integral with application to the project management and risk analysis

Occupational Health and Safety (OHS) risk analysis in the villa development project

In the process of working on a construction project, there is no such thing as a work accident, therefore it is necessary to take preventive measures. One of its efforts to prevent workplace accidents is the implementation of Occupational Health and Safety (K3). K3 is a form of effort to ensure the integrity and perfection of the workforce, both physically and spiritually, to create protection and security from the risk of accidents and hazards both physically and mentally. The method used in this research is Hazzard Identification, Risk Assessment and Determining Control. The construction project of Vila House identified 82 occupational risks, therefore 42 risks are classified as low risk and 40 risks are classified as medium risk. The preventive measures that can be taken to minimize the risk of Occupational Health and Safety (K3) are Eliminate Unsafe Conditions and Unsafe action socialization/ Occupational Health and Safety (K3) training, as well as Use of proper and correct (Personal Protective Equipment) and (Work Protective Equipment).

TRANSFORMATION OF VALUES OF THE HIGH TECHNOLOGY PROJECTS FROM A VUCA TO A BANI ENVIRONMENT MODEL

The article is dedicated to the study of impact of a BANI-world conditions to implementation of the high technology industrial projects and in particular of the nuclear industry projects. The purpose of the article is to analyze tendencies of changes of different factors related to the high technology nuclear project implementation against the changing conditions of the environment. The object is the project management methodologies in the BANI environment. The subject is theoretical analysis of the values differentiation in between the VUCA and BANI worlds, key aspects of BANI impacting implementation of the nuclear projects. Tasks to be solved: to analyze the transformation from the VUCA model to the BANI model, to present values and their differentiation as the basis for survival in the new world order, to develop a method for assessing project risks in the BANI environment. Methods: practical empirical analysis of nuclear project risks in comparison with BANI-model forecasts, applied research, project risk management methodology, probability theory. The following results were obtained: the differences between the values of s VUCA and BANI are determined, an understanding of the general changes that have arisen due to the functionality of the environment is provided, the project management methodology applicable in the BANI environment is analyzed, a qualitative and quantitative risk analysis based on BANI projections is implemented on the example of a nuclear project in Ukraine, and the grounds for determining the most influential BANI forecast are proposed. The main results of the research are identification and analysis of values and their differentiation in the process of transformation from the VUCA to the BANI world, proposals for the project management approach which could cover the needs of the nuclear project and the consequences of this transformation. To estimate risks, it was proposed to use qualitative and quantitative methods of risk assessment. The case study of one of the nuclear projects in Ukraine, and a mixed classic-Agile methodology for the management of the nuclear project was performed. Conclusions: risk management of the nuclear projects has to be carried out based on the impact of the BANI-projections to identified risks.

The Generalized Two-Sided Beta Distribution with Applications in Project Risk Analysis

The Generalized Two-Sided Beta Distribution with Applications in Project Risk Analysis