Analyzing project risks within a cultural and organizational setting

In the realm of software project management, predicting and mitigating risks are pivotal for successful project execution. Traditional risk assessment methods have limitations in handling complex and dynamic software projects. This study presents a novel approach that leverages artificial neural networks (ANNs) to enhance risk prediction accuracy. We utilize historical project data, encompassing project complexity, financial factors, performance metrics, schedule adherence, and user‐related variables, to train the ANN model. Our approach involves optimizing the ANN architecture, with various configurations tested to identify the most effective setup. We compare the performance of mean squared error (MSE) and mean absolute error (MAE) as error functions and find that MAE yields superior results. Furthermore, we demonstrate the effectiveness of our model through comprehensive risk assessment. We predict both the overall project risk and individual risk factors, providing project managers with a valuable tool for risk mitigation. Validation results confirm the robustness of our approach when applied to previously unseen data. The achieved accuracy of 97.12% (or 99.12% with uncertainty consideration) underscores the potential of ANNs in risk management. This research contributes to the software project management field by offering an innovative and highly accurate risk assessment model. It empowers project managers to make informed decisions and proactively address potential risks, ultimately enhancing project success.

Risk and risk management in software projects: A reassessment

A software development project can be considered to be risky project due to the uncertainty of the information (customer requirements), the complexity of the process, and the intangible nature of the product. Under these conditions, risk management in software development projects is mandatory, but often it is difficult and expensive to implement. Expert COCOMO is an efficient approach to software project risk management, which leverages existing knowledge and expertise from previous effort estimation activities to assess the risk in a new software project. However, the original method has a limitation because it cannot effectively deal with imprecise and uncertain inputs in the form of linguistic terms such as: Very Low (VL), Low (L), Nominal (N), High (H), Very High (VH) and Extra High (XH). This paper introduces the fuzzy-ExCOM methodology that combines the advantages of a fuzzy technique with Expert COCOMO methodology for risk assessment in a software project. A validation of this approach with project data shows that fuzzy-ExCOM provides better risk assessment results with a higher level of sensitivity with respect to risk identification compared to the original Expert COCOMO methodology.

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Introduction Due to the vastness of various construction practices globally, there is a need for knowledge mapping. Through the utilisation of research on Project Risk Management (PRM) for the Construction Industry, it is possible to carry out an investigation into the processes that pertain to knowledge management. To elaborate on the current research emphasis from three different points of view, namely the influence of political risk, risk assessment, and risk management strategies, the knowledge map analysis method has been elected as the appropriate approach. Knowledge mapping provides a systematic way to visualise research trends, identify gaps, and strengthen the understanding of PRM in international construction projects. Methods This scientific investigation, conducted in the field of risk management research, considers publications related to risk management. The study was conducted as a systematic literature review that adopted bibliometrics approach to explore the data from Dimensions database that have been reviewed using PRISMA 2020 statement. This study intends to present Knowledge Mapping for PRM in the Construction Industry, using data from 2000-2025. The analysis focused on three dominant research dimensions: political risk, risk assessment, and risk management strategies. It uses literature on studies that have been carried out on project risk and provides a comprehensive perspective on the topic. Results The knowledge maps revealed distinct clusters of research activity across the three focal areas. Political risk emerged as a consistent theme in studies addressing international and cross-border construction contexts. Research on risk assessment showed significant methodological diversity, while studies on risk management strategies tended to emphasise both technological tools and organisational processes. Overall, the mapping highlighted increasing scholarly attention to integrated and holistic approaches to PRM. Some under-researched areas, particularly knowledge-transfer processes and cross-national learning mechanisms, were also identified. The findings demonstrate that knowledge mapping is a valuable tool for understanding the evolution and priorities of PRM research in the construction industry. Discussion The study makes use of Knowledge Mapping to offer some suggestions for research areas concerning risk management in international construction projects. These knowledge maps are founded on the investigations that were conducted on project risk management. However, the development of Knowledge Maps offers good contribution to knowledge for best practices in the construction sector. By identifying patterns and gaps, the study provides guidance for future investigations and encourages the development of improved risk management practices in global construction projects. The resulting knowledge maps contribute meaningfully to the field by supporting better decision-making, improving risk-handling capabilities, and informing best practices for the construction sector.

Application suitability for one of the intelligent methods for risk management of software projects has been shown based on the review of existing algorithms for fuzzy inference in the field of applied problems. Information sources in the management of software projects are analyzed; major and minor risks are highlighted. The most critical parameters have been singled out giving the possibility to estimate the occurrence of an adverse situations (project duration, the frequency of customer’s requirements changing, work deadlines, experience of developers’ participation in such projects and others.). The method of qualitative fuzzy description based on fuzzy logic has been developed for analysis of these parameters. Evaluation of possible situations and knowledge base formation rely on a survey of experts. The main limitations of existing automated systems have been identified in relation to their applicability to risk management in the software design. Theoretical research set the stage for software system that makes it possible to automate the risk management process for software projects. The developed software system automates the process of fuzzy inference in the following stages: rule base formation of the fuzzy inference systems, fuzzification of input variables, aggregation of sub-conditions, activation and accumulation of conclusions for fuzzy production rules, variables defuzzification. The result of risk management automation process in the software design is their quantitative and qualitative assessment and expert advice for their minimization. Practical significance of the work lies in the fact that implementation of the developed automated system gives the possibility for performance improvement of software projects.

The Need for Project Risk Management As projects move into deeper waters and higher levels of technical sophistication, complexities and, consequently, risks tend to increase as well. Project Risk Management (i.e., managing the risks of cost and schedule overruns during the drilling and facility development phases of the project) has now become an important tool to ensure project success. With the drilling and development cost of deepwater projects often exceeding $1 billion, owners, partners, and contractors need, more than ever, the ability to:set realistic yet reasonable cost and schedule contingencies;?know the probability of cost overruns and schedule delays;know the probability that the sanctioned cost and schedule will be achieved;understand the accuracy of a cost estimate or schedule; and?ensure that project teams identify risks and implement a Risk Mitigation Plan. In spite of the importance of Project Risk Management, many projects have been frustrated by traditional methods that are time-consuming, confusing and produce questionable results. As a result, decisions to invest in high-risk offshore development projects are still often based on cost estimates and schedules whose accuracy and contingency requirements are little more than "guesstimates." Risk is a Project Variable just like quality, cost, schedule, safety, health or environmental impact. And risk can be managed using good project management methods, similar to these other variables. This is the essence of Project Risk Management. However, when Project Risk Management is done ineffectively, or (as is often the case) not at all, we can call this Project Risk Mismanagement. Characteristics of Project Risk Mismanagement The 10 key indicators discussed below are characteristics of an organization that suffers from Project Risk Mismanagement. (Use this checklist to evaluate your organization!)Projects are authorized primarily based on financial criteria such as profitability, with little quantitative consideration of a project's cost and schedule risk relative to other potential projects. The result is decision-making based on incomplete awareness of potential risks.The corporate culture encourages project "champions" whose perceived priority is to "sell" the project to management. These "champions" are unlikely to recommend killing a project when it is no longer attractive. The result is projects whose unsatisfactory results are only recognized after they are complete.Management seeks to minimize project cost and time by punishing project managers and teams whose projects overrun the approved budget or schedule. The inevitable result is that estimates of cost and time are "padded" to ensure a low probability of overrun.Management rejects the concept of cost or schedule "contingency" and either forbids it to be included in estimates and schedules, or will accept it only if it is a small amount. The result is hidden contingencies that drive up cost and impair effective project controls.Projects are managed and judged individually and not as a portfolio. Therefore, project managers want to be assured their project will not overrun.

Complexity, Maturity and Competency in the Project Risk Management Environment: A Relational Framework

Moreover, there is an increasing amount of literature covering specific geotechnical risk analysis and management topics. Examples of these are the difference between unsafe geotechnical certainty and safe geotechnical uncertainty (Barends, 2005), the role of the human factor in achieving geotechnical reliability (Bea, 2006), objective and subjective ways of geotechnical risk classification (Altabba et al., 2004), and contractual allocation of geotechnical risk (Essex, 2007).

Purpose– While innovation has many similarities to other forms of projects it is characterised by a high failure rate and the need to stimulate creativity. More explicit risk management could help in achieving success in innovation projects. However, too much or inappropriate risk management might stifle the creativity that is core to innovation. So, what project risk management should be applied and where in the innovation project?Design/methodology/approach– A theoretical framework is proposed which combines the generic innovation process with project risk management. The framework was used to analyse the current attitudes to managing innovation risk in a series of companies.Findings– The decision points of the stage-gate innovation process model provide an effective interface for incorporating project risk concepts. The general concepts appear most relevant to innovation management though it is useful to customise them to emphasise the particular characteristics of innovation projects. The experience of using the resultant combined model in a number of diverse case studies indicates the relevance of the model in understanding attitudes towards risk management in innovation. The analysis of the case study companies suggested that risk management needs to be applied in differential manner: simple, unobtrusive techniques early in the innovation life cycle with more substantial, quantitative methods being considered for later stages.Research limitations/implications– It would be useful to extend this research by examining more case studies from other countries and industries.Practical implications– The combined innovation and risk management model provides a framework that diverse companies can appreciate. The framework offers a basis for discussing the most appropriate form of risk management in different innovation-based industries.Originality/value– Although there are many separate models for innovation and project risk management described in the literature, there is very little discussion about explicitly combining these theories. This paper aims to help fill this gap in the knowledge.

The general objective of this research was to assess the risk management process and project performance. The descriptive research design with a mixed qualitative and quantitative approach was used to a sample of 118 respondents selected from 168 target population using stratified sampling technique and Sloven’s formula. SPSS Statistical software was used in the analysis of the collected data into descriptive statistics by the help of mean and standard deviation. The inferential statistics were also analyzed as regression and correlation analysis. The results of this research have shown that project risk identification and performance of Mpazi channel construction project has a highly positive and significant relationship, with a coefficient of correlation of 0.970 and sig=.000, which is less than 0.05 level significance. The correlation results have also revealed r=0.979 and sig=0.00 which is less than 0.05 level of significance, hence proving a highly positive and significant relationship between project risk management strategy and performance of Mpazi channel construction project. The correlation results have also shown an r =0.985 and sig=0.00 which is less than 0.05 proving significant and positive relationship between project risk plan response and Mpazi Channel construction project performance. The research also found that a combination of project risk identification, risk management plan and risk plan response contributed to 97.5 percent (R2= 0.975) of the Mpazi Channel construction project success. Thus, the researcher concluded that the project risk management procedure has an impact on the performance of the Mpazi Channel construction project. Basing on the findings of the study, researcher recommends that a formal and planned project risk management procedure should be implemented throughout project planning to key construction personnel, support staff, and laborers. Keywords: Project Risk Management Process, Project Performance, Construction, Rwanda

The article examines the essence of the analysis and assessment of the risks of investment projects in the innovative development of the country's economy. One of the most important tasks for investors in the context of the coronavirus crisis is the analysis, assessment and effective management of risks that can affect investment projects before investing. And also, the investor must identify the factors that negatively affect the project and develop measures to reduce their negative impact. Based on the above, it can be said that improving the risk management methodology and evaluating investment projects based on modern and best practices has become one of the urgent tasks. In this article, the author explains the essence of risk management and presents the main stages of risk management developed by foreign and domestic economists, and also expresses her own opinion about the stages of risk management of investment projects in the form of a scheme. The article also presents the content of the methods of risk analysis that are frequently used in practice. In particular, the author shows the essence of methods for assessing investment risks, such as Break-even point, the sensitivity analysis of the project, the method of Scenarios, the method for assessing the sustainability of the project, Expert evaluation method, Analogy method, and others. We can identify two aims of research: 1) to study the stages of investment risk management, developed by foreign and domestic scientists, and, on their basis, to propose the stages of risk management, developed by the author; 2) to study various methods of risk assessment, which are a key part of investment risk management, and develop proposals for their application in Uzbekistan. To achieve the objectives of the study, the following tasks were identified:  explain the content of the economic categories “risk” and “investment risk”;  explain the content of investment risk management;  study of the process (stages) of investment risk management, developed by foreign and domestic economists;  development by the author of the stages of the investment risk management process;  study and outline methods for assessing the risks of investment projects;  development of recommendations on the application of risk assessment methods in Uzbekistan. Subject of research: methods for assessing the risks of investment projects. Information sources for writing the research was books and articles by foreign and domestic economists.

This study aims to explore SME time management and risk management in R & D projects. First, we define project time management and project risk management, and introduce commonly used tools and models. Next, the definition of SMEs and the type of R & D projects are explained, and the problems faced in time management and risk management are analyzed. We also explored the relationship between project risk management and time management in SMEs. Finally, analysis and selection methods for SMEs when selecting project time management and risk management tools. The purpose of this study is to provide effective time management and risk management solutions for SMEs.

Risk management is often seen as a project manager's job. However, the information and knowledge required make a realistic assessment of project risks is often dispersed among people in and around the project. Also people will tend to focus their attention on different aspects and as a consequence on different risks because their different roles with regard to the project. Our assumption is that it is wise to have a team of relevant people making a joint risk assessment, based on knowledge and information dispersed in, but not necessarily shared by, the team. The team corrects the filters and biases of individuals in their specialized roles and positions and creates both a richer "knowledge base" and increased variety in interpretations. To test these assumptions, we formulated design requirements for a risk management method on the basis of the theory of human group and individual decision-making and information processing. Based on these requirements a risk management method was developed and used in eight IT projects. The results confirmed the assumption that lack of information and bias are relevant issues in risk assessment. The proposed guidelines resulted in a method capable of handling these issues.

Nowadays, one of the characteristic features of construction industry is an increased complexity of a growing number of projects. Almost each construction project is unique, has its project-specific purpose, its own project structural complexity, owner’s expectations, ground conditions unique to a certain location, and its own dynamics. Failure costs and costs resulting from unforeseen problems in complex construction projects are very high. Project complexity drivers pose many vulnerabilities to a successful completion of a number of projects. This paper discusses the process of effective risk management in complex construction projects in which renewable energy sources were used, on the example of the realization phase of the ENERGIS teaching-laboratory building, from the point of view of DORBUD S.A., its general contractor. This paper suggests a new approach to risk management for complex construction projects in which renewable energy sources were applied. The risk management process was divided into six stages: gathering information, identification of the top, critical project risks resulting from the project complexity, construction of the fault tree for each top, critical risks, logical analysis of the fault tree, quantitative risk assessment applying fuzzy logic and development of risk response strategy. A new methodology for the qualitative and quantitative risk assessment for top, critical risks in complex construction projects was developed. Risk assessment was carried out applying Fuzzy Fault Tree analysis on the example of one top critical risk. Application of the Fuzzy sets theory to the proposed model allowed to decrease uncertainty and eliminate problems with gaining the crisp values of the basic events probability, common during expert risk assessment with the objective to give the exact risk score of each unwanted event probability.