Project Risk Management Research Articles

REPLANTEAMIENTO DE LA PLANIFICACIÓN DE PROYECTOS MINEROS: USO DE NASA-TLX PARA MEDIR UNA NOVEDOSA INTEGRACIÓN ENTRE OTSM-TRIZ Y DSM

This research introduces an integrated methodology combining OTSM-TRIZ and the Design Structure Matrix (DSM) to enhance project planning and risk management in mining projects. OTSM-TRIZ, through a Network of Problems (NoP), systematically addresses complex challenges, while DSM analyzes task dependencies, optimizing resource allocation and sequencing. Applied in a real-world Chilean mining company with over 120 workers, the methodology improved outcomes by reducing trial-and-error iterations and boosting efficiency. Workers gained valuable insights into managing project complexity. NASA-TLX was used to explore usefulness authors’ proposal. Keywords: Mining Projects, OTSM-TRIZ, DSM, NASA-TLX

Devising a project risk management method under scrum conditions based on cognitive approach

Any project implemented using Scrum is characterized by the impact of risks, including negative changes in the environment and crisis circumstances. Therefore, the processes related to risk management, which is the object of this paper, become important. The problem solved in this study is to improve the efficiency of projects through the construction of a long-term strategy for reducing the level of risk and avoiding negative consequences for projects in the context of Scrum. The proposed method of risk management has been developed on the basis of the application of the synthesis of management of intelligent decision-making technologies and formalized methods. Difficult external circumstances are characterized by a high degree of uncertainty and do not always contribute to the successful implementation of the project. Therefore, this method of project risk management under Scrum conditions based on a cognitive approach is characterized by a combined combination of cognitive analysis, mathematical modeling, and expert methods. As part of the method, a model of project risk management under Scrum conditions has been built in the form of a fuzzy cognitive map, which could ensure determining the optimal strategic decision in dynamics, taking into account the effects of various factors. The result of applying this method is compliance with time limits, reduction of overspending of resources and losses in the project, as well as adaptation to rapidly changing circumstances and adequate response. The method of project risk management is characterized by solving the problem of formalizing management decision-making procedures and their information support, taking into account the availability of both quantitative and qualitative data. Within the framework of this method, a project risk management procedure under Scrum conditions has been proposed, which contributes to the systematization, monitoring, and control of risks under the conditions of complex, rapidly changing crisis circumstances

Spatial Risk Assessment and Geographic Information System based Approach for Construction Projects Risk Management

Spatial Risk Assessment and Geographic Information System based Approach for Construction Projects Risk Management

The Role of Technology in Promoting Green Finance: A Systematic Literature Survey and the Development of a Framework

Green finance, defined as channeling money into sustainable development activities, is still far lower than needed to achieve net-zero emissions objectives. In this paper, we discuss the role of technologies in developing green finance. We identify that green finance faces three major challenges, including the risk management of green projects, the scarcity of innovative green financing products, and compliance with the regulations. Then, in the context of the existing literature, we explore recent technologies, including blockchain, artificial intelligence (AI), machine learning (ML), data analytics, Internet of Things (IoT), and robotics that are helping to deal with the challenges in green finance. We show that data-driven approaches utilizing AI and ML help in the risk assessment of green projects; FinTech-based crowdfunding platforms provide innovative green financial products and regulatory technologies (RegTech) support in compliance with regulations. We also identify that the environmental footprint of cryptocurrencies is an emerging area in the technologies and green finance domain. Our framework could be helpful to further extend the debate on the role of technology in green finance.

The Impact of Risk Management on Project Success: A Field Study at Humanitarian Organizations in Yemen

The study aimed to determine the impact of risk management (risk identification, risk analysis, risk response and risk monitoring and control) on project success (scope, schedule, cost and quality) at humanitarian organizations operating in Yemen (HOY). The study followed the analytical descriptive approach to meet its objectives. It utilized the simple random technique to select 15 organizations representing 127 HOY and the disproportional stratified random sampling technique to target the respondents. Data was collected through a printed questionnaire from 185 respondents who have roles in managing projects at the targeted organizations. The findings showed that risk management has a significant positive impact on project success. The findings also revealed that among 4 dimensions of risk management process, risk identification and risk monitoring and control were found as the most significant influencers that impact project success at HOY. The study recommends HOY to pay more attention to project risk management to attain higher project success level that ultimately contributes to the performance improvement and sustainability of their organizations. The study also recommends conducting more studies for further confirmations to the hypothesis of the study through testing the study’s variables at industries other than HOY such as banking industries and telecommunications companies.

Evaluating the project management maturity in the construction industry of developing countries, Ghana in perspective

This study evaluates construction contractors' project management maturity levels, examining various factors such as ISO certification, capacity building programs, contractor type (road vs. building), and specific knowledge areas. Data was gathered through surveys and assessments to evaluate the maturity of different processes and practices. The findings reveal various maturity levels across the industry, with significant variations among contractors. Common challenges include gaps in risk management, safety protocols, and overall project management practices. Factors such as ISO certification and capacity-building programs positively impacted maturity levels. However, targeted training and education are crucial for addressing specific knowledge gaps. The analysis identifies critical recommendations for improving project management maturity in the construction industry, including fostering a culture of continuous improvement, promoting knowledge sharing, implementing tailored training programs, and developing industry-specific standards. By addressing these challenges and implementing appropriate strategies, the construction industry can enhance project outcomes, reduce costs, and improve competitiveness.

Generalized Modular Method of Project Risk Management

The article discusses risk management models and frameworks implemented during the development of multi-user cross-platform distributed IT projects. For this class of pro-jects, the use of quantitative risk assessment methods, rules for absorbing and adding risks, which make it pos¬sible to systematically assess the likelihood of negative events and their impact on each stage of the project, are observed. Authors propose a method of modular risk management, present the main indicators for assessing the progress of the implementation of the i-th module and its operational ma¬nagement, and provide a formula for calculating project efficiency. These calculated indicators can be used to estimate the cost of resources at a certain point in time, estimate the timeframe for completing the module, and decide on the feasibility of further development.

Evaluating Internal Control Mechanisms in Malaysian Public Sector Initiatives: Insights from the Public Accounts Committee (PAC) Reports

This study examines internal control challenges in Malaysian government projects, drawing on Public Accounts Committee (PAC) reports from 2019 to 2022. The focus on this period stems from the shift in PAC chairmanship from government to opposition, which enhanced perceived independence. However, the literature suggests that the PAC’s success depends more on collaborative decision-making than on the chairman’s political affiliation. Analyzing 29 government agencies across various sectors revealed recurring weaknesses in internal controls. The study employed the Committee of Sponsoring Organizations of the Treadway Commission’s (COSO) Internal Control-Integrated Framework (ICIF) to systematically identify these weaknesses. A content analysis method was used to examine the themes, which were grouped into five ICIF components: control environment, risk assessment, control activities, information and communication, and monitoring. Weaknesses in the control environment include conflicts of interest, compromised ethical values, inadequate governance, and a lack of accountability and transparency. Risk assessment deficiencies were found in financial risk management, procurement and acquisition risks, geopolitical and strategic risks, intellectual property and technology risks, and project management risks. Control activity weaknesses involved poor resource and process management, non-compliance, and flawed decision-making. Information and communication issues included poor documentation, inadequate system integration and data sharing, limited stakeholder engagement, weak communication protocols, and poor information management. Monitoring deficiencies were noted in regulatory compliance, contract management, financial oversight, monitoring systems, and disbursement tracking. Addressing these weaknesses in internal controls is crucial for minimizing the risks of fraud, waste, and loss of public trust

The need for a risk management framework for data science projects: a systematic literature review

Many data science endeavors encounter failure, surfacing at any project phase. Even after successful deployments, data science projects grapple with ethical dilemmas, such as bias and discrimination. Current project management methodologies prioritize efficiency and cost savings over risk management. The methodologies largely overlook the diverse risks of sociotechnical systems and risk articulation inherent in data science lifecycles. Conversely, while the established risk management framework (RMF) by NIST and McKinsey aims to manage AI risks, there is a heavy reliance on normative definitions of risk, neglecting the multifaceted subjectivities of data science project failures. This paper reports on a systematic literature review that identifies three main themes: Big Data Execution Issues, Demand for a Risk Management Framework tailored for Large-Scale Data Science Projects, and the need for a General Risk Management Framework for all Data Science Endeavors. Another overarching focus is on how risk is articulated by the institution and the practitioners. The paper discusses a novel and adaptive data science risk management framework – “DS EthiCo RMF” – which merges project management, ethics, and risk management for diverse data science projects into one holistic framework. This agile risk management framework DS EthiCo RMF can bridge the current divide between normative risk standards and the multitude of data science requirements, offering a human-centric method to navigate the intertwined sociotechnical risks of failure in data science projects.

Research on Time Management and Risk Management of Small and Medium-Sized Enterprises

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.

Research on risk management of ship maintenance projects based on multi agent swarm model simulation method

In recent years, the role of naval ship power has become increasingly prominent in regional conflicts and military operations worldwide, and the powerful capabilities demonstrated by naval forces have also been valued by countries around the world. While naval forces are frequently deployed to carry out various tasks, the intensity of equipment wear and tear on ships is also significantly increasing, posing a huge challenge to the maintenance and support capabilities of ship equipment. In the actual process of ship equipment maintenance, a series of risk factors such as cost, schedule, and quality will have a significant impact on the entire ship maintenance project, and even affect the success or failure of the entire project. This article first decomposes the project process of ship maintenance projects, further analyzes the various risk factors of ship maintenance projects based on the project decomposition situation, and then distinguishes the overall project, project process, and project risk factors to establish an intelligent agent group model for simulation analysis. Through the above simulation analysis, we will conduct in-depth research on the specific impact of project risks on ship maintenance projects, and analyze and verify the positive role and practical significance of project risk management in project risk control and project efficiency improvement. In the process of the above research content, methods and measures for risk management of ship maintenance projects are proposed, providing scientific and efficient risk management suggestions for such projects, improving the scientific management efficiency of ship maintenance projects, and contributing to the improvement of the quality and efficiency of project management.

A Bibliometric Analysis of Risk Management in Road Construction Project

Risk management in road projects is a process of controlling construction work and development that significantly affects the success of road project work. This research aims to investigate the latest developments in the world, with a specific focus on those related to risk management in road construction. The study intends to shed light on emerging trends and innovations in the field by exploring global advancements. The primary goal is to contribute valuable insights that can enhance the understanding and implementation of risk management strategies in road construction projects. These publications were obtained by scrutinizing keywords such as road construction, risk management, and construction projects. Utilizing Publish or Perish facilitated the extraction of data relevant to our research topic. Subsequently, the acquired data was transformed into a new format using Microsoft Excel. This dataset encompasses citation counts, author names, and publication years. Leveraging this information and Microsoft Excel, we constructed a chart or figure to present a comparative analysis. Additionally, VOSViewer was employed to create a visual representation illustrating relationships between research keywords.

A two-stage stochastic programming model for comprehensive risk response action selection: A case study in Industry 4.0

Effective project risk management is critical in environments where both micro-level and macro-level risks are present. Traditional models often focus on micro-level risks, neglecting broader macroeconomic uncertainties such as geopolitical instability and supply chain disruptions. This research introduces a two-stage stochastic programming model designed to optimize the selection of Risk Response Actions (RRAs) under uncertainty while addressing both types of risk. The model incorporates “here-and-now” decisions at the planning stage and “wait-and-see” decisions as uncertainties unfold, enabling adaptive risk management throughout the project lifecycle. To solve the model efficiently, we employ an evolutionary algorithm combined with Sample Average Approximation (SAA) to handle the computational complexity of multiple scenarios. The model is applied to a real-world case study involving the integration of IoT and ERP systems in a smart factory in Iran, a project characterized by significant macroeconomic and geopolitical risks. Our key contribution lies in providing a comprehensive risk response strategy selection model that simultaneously addresses micro- and macro-level risks while incorporating strategic flexibility through outsourcing decisions. The results demonstrate that our model outperforms traditional deterministic models, offering enhanced resilience against macro-level risks and improved project performance under uncertainty. These findings provide valuable insights for project managers aiming to increase resilience and adaptability in volatile environments. By integrating both internal and external risk factors, our model offers a robust tool for managing complex projects, enhancing decision-making and project outcomes in uncertain conditions

Dynamic Analysis and Temporal Governance of Safety Risks: Evidence from Underground Construction Accident Reports

Due to the complexity and dynamics of underground construction projects, safety risk management has experienced significant challenges restricting the sustainable development of underground space. The research on risk causal chains and risk coupling has yet to reveal the dynamic interactive characteristics of these risk factors and their temporal relationships over time. This study utilized a complex system view for safety risk analysis, using 37 accident investigation reports of underground construction projects. Combined with two novel and emerging analytical methods, temporal qualitative comparative analysis and crisp-set qualitative comparative analysis, this study discusses the temporal relationship of risk factors to the cause of accidents and explores the multi-actor coupling characteristics of management risk. The findings indicate that (1) compared with general construction projects, underground construction should pay more attention to management safety risks because they have an obvious time lag effect expressed in all accident causation paths, namely, preceding management risk, management risk, and machine/material risk cross-concurrently, and management risk initiation and (2) underground construction project management risks have three key main paths, namely, single-actor-dominated management deficiency (supervisors, owners, and subcontractors that cause management risks as a single-core actor) and dual-actor-dominated management deficiency (owner and subcontractor as dual core actors of management risk). Multi-actor-dominated management deficiency (owners, subcontractors, and supervisors are the multiple core actors of management risk). This study thus developed a temporal governance framework of underground construction safety risks based on the synergy of multi-actors and proposed risk governance strategies, such as synergistic multi-actor governance, to consider the temporal relationship of safety risk. This study further reveals the temporal and coupling characteristics of safety risks to enrich the risk casual chain theory and risk coupling theory and establish a systematic risk analysis framework for new guidance for safety and risk management for underground construction projects.

Evaluating the Impact of Artificial Intelligence in Managing Construction Engineering Projects

This study evaluates the impact of utilizing artificial intelligence (AI) in managing construction engineering projects. With the increasing complexity and scale of construction projects, AI offers promising solutions to enhance efficiency, accuracy, and decision-making processes. The study investigates the potential benefits, challenges, and practical applications of AI through detailed case studies. The study employs a mixed-methods approach, combining qualitative and quantitative research methods. Data was collected through literature reviews and case studies where AI had been successfully implemented. The analyses included comparisons between projects that used AI and those that did not. The findings demonstrated significant improvements in project efficiency, cost estimation accuracy, and risk management. For instance, AI-powered systems reduced scheduling errors by 35%, leading to more accurate timelines. Additionally, the integration led to a 20% reduction in project durations due to improved resource allocation and proactive risk management. Furthermore, AI-supported systems contributed to a 25% improvement in stakeholder satisfaction. In terms of cost estimation, AI-powered estimation tools improved the accuracy of cost estimates by 30%, helping to reduce budget overruns by 40%. In risk management, AI-supported tools enhanced the accuracy of risk identification by 45%, leading to the early detection of potential issues and the development of effective mitigation strategies that reduced the impact of risks by 30%. Thanks to these improvements, project success rates increased by 20%. These results demonstrate that integrating AI into the management of engineering construction projects can lead to tangible improvements in project efficiency, cost accuracy, and risk management, thereby enhancing stakeholder satisfaction and contributing to more successful project outcomes.

The Impact of Moderation Analysis Between Effective Project Governance and Project Performance Management in Malaysia’s Construction Industry

Objective - The building sector is essential to Malaysia's economic expansion. Despite its significance, large construction companies usually experience delays and project failure, affecting 95% of homebuyers due to 580 delayed projects in 2022. By February 28, 2023, 581 projects had been reported as delayed. Methodology/Technique – This study experimentally examines the relationship between effective project governance and project performance in 390 Malaysian construction companies, using a framework based on agency theory and assessed with partial least squares structured equation modeling. Finding – Benefit management serves as a mediator between project performance and effective project governance, and top management support has a positive moderating influence. Novelty – The study highlights the importance of preventive measures, enhancing team and project manager roles, and forming strategic alliances for improved project governance. Type of Paper: Empirical JEL Classification: H60, H61, M10, M11. Keywords: Effective project governance; project management risk; benefit management; top management support; project performance. Reference to this paper should be referred to as follows: Abdullah, F.C.B; Indiran, L; Krishnan, A; Pavithran, S.N. (2024). The Impact of Moderation Analysis Between Effective Project Governance and Project Performance Management in Malaysia’s Construction Industry, GATR-Global J. Bus. Soc. Sci. Review, 12(3), 114–124. https://doi.org/10.35609/gjbssr.2024.12.3(2)

Impact of project planning and project risk management on project success: moderating role of project managers’ competencies in the construction sector in Afghanistan

This research examines the impact of project planning (ProP) and project risk management (RisM) on project success (ProS) while maintaining project managers’ competencies (PMC) as moderators using resource-based view theory concepts. This research addresses the gap in how ProP and RisM lead to ProS in the presence of a PMC as a moderator in construction-based private organisations. Utilising a convenience sampling technique, data were collected from 249 participants working in construction-based organizations across major cities in Afghanistan. Data were analysed using Smart-PLS and SPSS software. Supporting theories for this study are the theory of knowledge reuse and the social exchange theory concepts. Analysis revealed that ProP significantly and positively impacted ProS. RisM was also found to have a positive effect on project success. The results showed that project managers’ competencies moderated the relationship between ProP and ProS. The findings indicated that PMC moderates the connection between project risk management and ProS. Implementing project planning methodologies, a construction project manager’s competency improves team outcomes through risk management and boosts project success. The study’s limitations, future suggestions, and managerial implications are also discussed.

Ramanov Contractors: Adoption of Project Risk Management Framework

The case deals with the concept of project risk management and its adoption in a small-sized contracting firm. It demonstrates the dilemma faced by a typical small-sized contracting firm vis-à-vis setting project objectives, defining key elements for structuring the risk management process, number of data points, choice of techniques of different steps involved in project risk management and development of a team to practice the process flawlessly. The case would be suitable for postgraduate students of the management programme as well as participants of management development programmes on project management.

A spatiotemporal data mining method for advanced prediction and assessment of large combined excavation-induced wall deformations and risks

A holistic and precise assessment of retaining wall deformations is critical for on-site risk management of large combined deep excavation projects, where the risk-related points are highly dispersed, evolving, and interacting. Despite extensive exploration of this topic in previous studies, the omission of intricate spatiotemporal characteristics of wall deformations has resulted in diminished prediction accuracy and stability. To mitigate this deficiency, a spatiotemporal characteristics matrix for all data points and time series was first generated for a deep excavation scenario and used as input for a new hybrid model that combines convolutional neural network (CNN) and long short-term memory (LSTM) with incorporated attention mechanism (CNN-LSTM-Att), which enables the cross-learning mechanism and improves interpretability. In addition, by leveraging the attention weight, a new risk assessment index for retaining wall deformations across various scenarios was formulated. Then the proposed method was applied in a large combined deep excavation in Shanghai, China. The results show that: (1) The incorporation of fed-in characteristic data and the attention mechanism enables the proposed method to produce satisfactory prediction results for the holistic spatiotemporal distribution of a large combined excavation; (2) Compared with other published models, the proposed model shows much better prediction accuracy, interpretability, and stability, especially in medium- and long-term predictions; and (3) The new risk assessment index serves as a reliable decision-making tool for assessing the risk evolution of retaining wall deformations and provides valuable guidance for effective risk management in multi-scenario excavation projects.

GERENCIAMENTO DE RISCOS NO PLANEJAMENTO DAS LICITAÇÕES E CONTRATOS PÚBLICOS

Recent legislative changes in the area of public bidding and contracts, especially the guidelines implemented by Normative Instruction SEGES/MPDG Nº. 05/2017, established a new regime for contracting outsourced services in the Brazilian legal system. This new instrument aims to expand the dispute, in compliance with the principle of competitiveness, resulting in the expansion of the supplier market. IN Nº. 05/2017 establishes the rules and guidelines for the procedure for contracting services under the indirect execution regime within the scope of the Direct, autarchic and foundational Federal Public Administration. The regulation establishes innovative phases: Contracting Planning; Supplier Selection; and Contract Management. The Planning phase consists, according to the IN, of 3 stages: Preliminary Studies; Risk Management; and Terms of Reference or Basic Design. This paper aims to present a Risk Management Plan, developed in the planning phase of contracting a bidding process in the Electronic Auction for Price Registration modality. According to the PMBOK® Guide Sixth Edition p. 395, project risk management includes the processes of conducting planning, identification, analysis, response planning, implementation of responses and monitoring of risks in a project. The objective is to maximize exposure to positive events and minimize exposure to negative events. In this context, through causes, consequences, categories and SWOT analysis, 75 risks were identified. Risk management processes were used in accordance with the PMBOK® doctrine and the Pareto Principle to prioritize 25 risks.