Project Risk Identification Research Articles

Navigating complex riskscapes: the Koudiet Eddraouch GIS substation project in Sub-Saharan Africa

Learning outcomes Risk identification and qualitative assessment are the learning outcomes. Case overview/synopsis The Bharat Bijlee Construction Limited (BBCL) was one of the largest construction companies operating in the power sector in India. After successfully completing a few projects in the Middle East, BBCL decided to expand its presence into African region. The BBCL was awarded a $85m contract for three sub-station projects to modernise Algeria’s power grid system by the “Shariket Karhaba Koudiet Eddraouch Spa”, a state-owned company in charge of power generation, transmission and distribution in Algeria. The project, which is the first of BBCL in Saharan region in Algeria’s, presents many unique situations that company had never encountered before, including sand dunes, severe weather, remote locations, supply chain & logistics, strict contractual deadlines and a high level of construction risk. The project manager for BBCL was sceptic about how well his company would perform under the present project circumstances. How could he better align himself with the client, the various on-site local contractors and the numerous suppliers spread around the world? The case emphasises the identification of various project risks that the project manager might encounter in the project. What do the PESTLE and ASCE frameworks for risk identification each represent, and how are they helpful for the project team in understanding various risks? How should the project’s qualitative risk assessment be conducted? And how can a heat map be a better tool for comprehending the criticality of each risk in the project? Complexity academic level Undergraduate and post graduate courses in project management, civil engineering and architecture domain. Supplementary material Teaching notes are available for educators only. Subject code CSS 2: Built Environment.

Identification of Construction Project Risks in the Indian Context: A Case Study on Building Construction

Abstract: This paper presents a comprehensive investigation into the risk factors prevalent in building construction projects within the Indian context, focusing on their identification, ranking, and management strategies. Through data collected from 206 construction professionals via an online questionnaire, the study employs robust reliability analysis, yielding a high Cronbach's Alpha coefficient of 0.898, affirming the questionnaire's internal consistency and reliability. Utilizing the Relative Importance Index (RII) and Safety Risk Score (SRS), the research ranks critical risk factors, including poor stakeholder communication, inaccurate cost estimation, funding delays, and market demand fluctuations, underlining the necessity of addressing these challenges to mitigate potential impacts on project outcomes. The paper emphasizes the significance of proactive risk management strategies to ensure project success and resilience amidst evolving circumstances, providing valuable insights into construction project risks specific to the Indian landscape and offering recommendations for enhancing risk management practices in the field.

ASSESSMENT OF PROJECT RISK MANAGEMENT IN SELECTED MINING COMPANIES IN ETHIOPIA

Purpose: This study uses qualitative research to assess the project risk management practices of selected mining companies in Ethiopia. Methodology: The study was qualitative, and data was obtained using purposive sampling methods; the study's sample size was based on 41 respondents working actively on mining projects in Ethiopia. The questionnaires covered the main aspects of risk management, including overall project risk management, risk planning, risk identification, risk analysis, and risk monitoring and controlling practices. Findings: The study's findings indicated the absence of systematic risk management policy or guidelines and no organized standard risk management processes. Moreover, project managers primarily manage risk with their team's support. It was found that with risk identification, risk analysis, monitoring, and controlling processes, mitigation of project risks could have been conducted more proactively. Instead, risks are managed upon occurrence by relying primarily on the subjective judgment of the mining specialists, often project managers. Originality/Value: This research assesses the risk management practices of mining companies in Ethiopia for the first time. Recommendations have also been made for companies to develop their risk management knowledge through training and exposure to international practices. This approach will slowly build a systematic approach to risk management practices in the Ethiopian setting. The findings of this article also indicated the need for more research as few papers have been published on mining risks globally, and none have been published in Ethiopia’s context.

Data-Driven Approach to Risk Identification for Major Transportation Projects: A Common Risk Breakdown Structure

Identifying and evaluating risks is one of the most essential steps in risk management in construction projects. When technical and managerial complexity increases in major transportation projects, this becomes even more important. Currently, project teams are assumed to identify risks mostly based on their experience and expertise. It is a major issue that some state departments of transportation (DOT) project teams lack the risk management experience. This study proposes using a data-driven approach to unify and summarize existing risk documents to create a comprehensive risk breakdown structure (RBS). As a preliminary risk identification framework, a consolidated RBS were developed, using content analysis of public risk reports by various DOTs. Then, comparison was made between the developed RBS with 70 US transportation projects' risk registers. Natural language processing techniques, bidirectional encoder representations from transformers, were employed to calculate semantic text similarity to determine what percentage of risks are covered by generic RBS. The results showed that 70 generic risk templates cover almost 81% of the identified risks in the database of 70 major projects which is about 6000 individual risks. Project parties can use these results to discuss and identify context-specific risks as a starting point. The study also determined the interactions between risk items based on their co-occurrence using historical data. Research findings revealed the importance of considering interdependencies between risks in future studies.

The Application of Analytical Hierarchy Process (AHP) to Determine The Construction Project Risk

Realisation of implementation also has various risk levels that affect project delays, as a result of which project performance is disrupted and causes losses to costs, time and quality of work. This research location is in a construction project at the vehicle test service office, which aims to identify, analyse, evaluate and mitigate risks using the AHP methods. However, the Risk Breakdown Structures method was first conducted to compile a structured description of project risk identification based on risk categories and subcategories. The collected data were analysed using the AHP method to obtain the dominant risk, then mitigate risk by interviewing experts and validating from various sources so that it becomes the basis for conclusions. The risk of delay in the construction project includes four risk categories and twenty subcategories analysed using the AHP method. The results of processing the data on the dominant risk of uncertainty are the increase in the price of building materials by 10.172%, the rise in fuel prices by 7.835%, and the delay in handing over land by 6.710%. As for risk mitigation, construction providers implement and create strategies to save fuel use and generate work methods regarding the scope and time of project implementation.

Review on the Identification and Assessment of Project Risks in International Engineering Contracting Projects

With the steady promotion of the "the Belt and Road" initiative and the introduction of a number of reform measures, the pace of "going global" of Chinese enterprises has been accelerating. More Chinese construction enterprises are actively engaged in overseas engineering construction and have made remarkable achievements. At the same time, the way of project contracting is also constantly upgrading, and the time span, uncertainty and complexity of international project contracting business are increasing, so it is necessary to carry out risk management. In addition, the introduction of relevant policies and regulations at home and abroad has further promoted the construction of overseas risk management of international project contracting enterprises. Therefore, it is necessary to use scientific methods and tools to identify and assess the risks of the project according to the internal and external conditions of the international engineering contracting project, and determine the measures to deal with the risks of the international engineering contracting project according to the results of the risk analysis, its own resource conditions, the environment and other factors. Finally, the corresponding risk response measures and suggestions are put forward based on the actual development strategy of the enterprise and the market environment of international project contracting business.

ANALISA KETIDAKEFEKTIFAN IDENTIFIKASI RISIKO MEMPENGARUHI PENILAIAN KINERJA PROYEK DI PT ALKHA INDUSTRI

PT Alkha Industri (ALKAIND), as one of the leading industrial and design companies in Indonesia. Of course, handling projects worth hundreds of billions of rupiah and multi years requires a professional strategy and management so that the project is on time, does not exceed the costs that have been determined and in accordance with the specifications requested by the employer (client / owner). ALKIND already has project risk management rules/procedures and the project team has carried out project planning with risk management (risk identification). Research conducting analysis provides answers to the effectiveness of making project risk identification can affect the achievement of project targets. The data uses data from the company PT Alkha Industri from 2020 to 2022 for registered projects both completed and in progress. The results of the analysis can be concluded, 1) the risk owner who should identify potential risks in the project is not Project Control personnel because they do not know the potential risks of each function, 2) update risks every month by evaluating the realization of control, 3) risks so that their inherent risk score is reduced, 4) Perform other responses besides mitigating, namely how to avoid risk (avoiding), how to transfer risk (sharing / transferring), controlling risk (controlling) and optimizing risk (exploiting).

Exploring the Benefits of Virtual Reality Adoption for Successful Construction in a Developing Economy

Existing literature has shown that Virtual Reality (VR) is widely utilized in advanced economies to enhance sustainable construction practices. However, its adoption in developing economies remains limited. To this end, this study aims at exploring the potential benefits of implementing VR technology in a developing country. The study collected information on the beneficial aspects of VR from previous research and conducted questionnaire surveys to gather relevant insights from construction project experts in Nigeria. The collected data were analyzed using the Measurement of Alternatives and Ranking According to the Compromise Solution (MARCOS) method and Exploratory Factor Analysis (EFA). The MARCOS method revealed that the key potential benefits of VR include improved communication and collaboration, enhanced project performance, risk identification, digitalization, and safety planning. Furthermore, the study conducted an in-depth investigation of the beneficial areas of VR using EFA, which identified six component groups: pre-contract stage planning, post-contract stage planning, quality control and sustainability, design flexibility and reputation, resource management, and risk management and digitalization. The study provides a comprehensive discussion of the advantages of implementing virtual building methods in developing countries.

Imagining futures: Cognitive processes of desirable or undesirable project prospections

The identification of plausible desirable and undesirable future events is fundamentally a cognitive process of prospecting possible futures. Yet, organizational practices designed for the identification and management of these uncertain futures, specifically project risk management, heed little attention to the role of cognition in these processes. Building on the theory of ‘pragmatic prospection’, we address this gap and examine the cognitive processes involved in prospection of desirable vs. undesirable project futures while identifying opportunities vs. risks. Empirically, we analyse the information search behaviour and post-hoc search verbalization in an experimental project risk and opportunity identification task. We find that risk identification relies often on simpler approaches with lower cognitive load, while opportunities triggered more explicit information search strategies and were more prone to evoke agency within the imagined futures. These findings challenge the assumption – widely held in risk management practice – that risks and opportunities can be approached by the same processes. We conclude with an outlook on how a better understanding of the involved cognitive processes can support foresight activities in project planning and beyond.

COMPARISON OF PROBABILITY IMPACT MATRIX AND FUZZY LOGIC METHODS FOR RISK ANALYSIS OF RURAL INFRASTRUCTURE PROJECTS IN INDONESIA

Through the provision of facilities and infrastructure in the Village, it can be used as an effort to empower the community to accelerate regional economic development that is effective and robust. In its implementation, infrastructure projects have risks that can have an impact on the sustainability of the project. Therefore the research aims to analyze what are the most influential risk factors in Participatory-Based Rural Infrastructure Projects using the PIM (probability impact matrix) and Fuzzy Logic Methods. This research uses a descriptive method with a qualitative and quantitative approach. The collected data will be analyzed using the Fuzzy Logic method. The results of the identification of risk factors for infrastructure projects were identified as many as 23, but after validating the risk identification for rural infrastructure projects, there were 17 identified risk factors. Based on the results of the analysis using the risk matrix, 17 factors have values that tend to be small and overall are at a moderate level. However, after analysis using the Fuzzy Logic method, the risk factor values varied, and there were 8 risk factors that were at a high level, these risk factors included technological failure, land change, negligent social behavior, bad design, inappropriate materials, inappropriate methods, inappropriate Standard Operating Procedures.

РИЗИК-МЕНЕДЖМЕНТ ВОЛОНТЕРСЬКИХ ПРОЄКТІВ

The question of the organization of charitable activities in Ukraine was considered, the specifics of volunteering in modern conditions were determined. The need for risk management in volunteer projects is emphasized. The purpose of the article is to review the theoretical foundations and develop practical recommendations for risk management of volunteer projects. The methodological basis of the research was logical methods of information processing, methods of analysis for identifying project risks, an abstract-logical method for formulating recommendations and conclusions. Presenting main material. The theoretical and methodological principles of charitable activities in Ukraine are considered. The specifics of implementing volunteer projects were analyzed and their risks were identified. It was determined that they are characterized by external risks associated with legislation, the search for donors, communication links, etc., and internal risks, which can include motivational risks, risks associated with compliance with the requirements of the "project triangle", and the risks of project participants. The risks of volunteer projects have been identified. Project risk management measures are proposed, the implementation of which will make it possible to prevent the occurrence of a risky situation or reduce its negative impact on the achievement of project goals. The originality and practical significance of the research is confirmed by the possibility of using the proposed measures as a practical risk management tool for planning volunteer projects. Conclusions and prospects for further research. The proposed identification of project risks and recommendations for their management can be used to further improve the risk management processes of volunteer projects by creating simulation models for evaluating the quantitative characteristics of adverse events.

EARLY STAGE DECISIONS IN MARINE SYSTEMS DESIGN FOR DEEP-SEA MINING

This article studies the prospects for deep seabed mining as a future viable maritime industry, and discuss the commercial, operational, and technical viability of deep seabed mining. By the use of a business development approach originating from the maritime industry, we analyse opportunities for a virtual deep seabed mining project, and identify aspects of stakeholder performance expectations, contextualised by the competitive positioning and identification of related project risks. We discuss strategies and pit-falls when positioning a deep seabed mining venture within the wider mining and metal production value chain, and use a case example in the Northern Atlantic Ocean to study the prospects for a deep seabed mining operation and subsequent system design implications. Furthermore, we contrast to well-established industries like offshore oil and gas, and traditional land-based mining. The study promotes several critical aspects and problem areas when approaching marine systems design for deep seabed mining.

Context-driven ontology-based risk identification for onshore wind farm projects: A domain-specific approach

Risk identification is a knowledge-based process that requires the time-consuming and laborious identification of project-specific risk factors. Current practices for risk identification in construction rely heavily on an expert’s subjective knowledge of the current project and of similar historical projects to determine if a risk may affect the project under study. When quantitative risk-related data are available, they are often stored across multiple sources and in different types of documents complicating data sharing and reuse. The present study introduces an ontology-based approach for construction risk identification that maps and automates the representation of project context and risk information, thereby enhancing the storage, sharing, and reuse of knowledge for the purpose of risk identification. The study also presents a novel wind farm construction project risk ontology that has been validated by a group of industry experts. The resulting ontology-based risk identification approach is able to accommodate project context in the risk identification process and, through implementation of the proposed approach, has identified risk factors that affect the construction of onshore wind farm projects.

Identification of economic risks of investment projects of mainline railway transport infrastructure construction

Study of the issues of identification, analysis, and comparative assessment of the risks of violations of the safety of the main railway transport infrastructure. The aim of the study: is to develop a methodology for the identification of economic risks of investment projects of construction of mainline infrastructure of railway transport. The object of the study: railway transport enterprises involved in all stages of the life cycle of the mainline infrastructure of railroad transport. The subject of the study: tools and procedures for the identification of economic risks of violations of the security of trunk railway transport infrastructure. In the turbulent global economy, the effectiveness of project management is based on the perception of the human factor as the main in the formation of aggregate uncertainty. Large infrastructure companies should pay special attention to the identification, analysis, and assessment of project risks. One of the key figures in Russia's transport communication, influencing not only domestic traffic flows, but also international logistics chains, is JSC "Russian Railways". Disruptions of the transportation process due to the realization of risks at the main infrastructure facilities of JSC "Russian Railways" predetermine economic consequences both for consumers of services, operators, and infrastructure owners.

Influence of Risk Management on Project Implementation, a Case Study of Indoor Residual Spraying Project in Rwanda

The study entitled “Influence of Risk Management on Project Implementation, a case of Indoor Residual Spraying (IRS) Project in Rwanda”. The purpose of the study was to investigate the influence of project risk management on project implementation in Rwanda with reference to Indoor Residual Spraying (IRS) Project. The study was guided by four specific objectives: to examine the influence of project risk identification on implementation of Indoor Residual Spraying (IRS) Project, to assess the influence of Project Risk Analysis on the implementation of Indoor Residual Spraying (IRS) Project, to find out the influence of project risk response planning on the implementation of Indoor Residual Spraying (IRS) Project and to ascertain the influence of Project risk monitoring and control on the implementation of Indoor Residual Spraying (IRS) Project. The research designs that were used in this study are descriptive research design and analytical research design. The study used 83 employees of Indoor Residual Spraying (IRS) Project as sample size. The study used stratified sampling techniques to select whole population to participate in this study. The study used questionnaires, interview guide and documentary review as method of data collection and finally the study used descriptive statistics and inferential statistics such as correlation analysis and multiple linear regression analysis as method of data analysis. For the first objective, the findings revealed that there existed a significant moderate positive correlation (R = 0.552**, p-value=0.002<0.01) between project risk identification and implementation of (IRS) Project and also results revealed that project risk identification have significance positive effect on implementation of (IRS) Project as indicated by β1= 0.199, p=0.000<0.05, t= 3.257. The implication is that an increase of one unit in project risk identification would lead to an increase in implementation of (IRS) Project by 0.199 units. For the second objective, the findings revealed that there existed a significant weak positive correlation (R = 0.375**,p-value=0.000<0.01) between project risk analysis and implementation of (IRS) Project and also the results revealed that project risk analysis have significance positive effect on implementation of (IRS) Project as indicated by β2=1.226, p=0.000<0.05, t=8.797. For the third objective, the findings revealed that there existed significant high positive correlation (R = 0. 797**,p-value=0.003<0.01) between project risk response and implementation of (IRS) Project and also the results revealed that project risk response planning have significance positive effect on implementation of (IRS) Project as indicated by β3= 0.396, p=0.000<0.05, t= 3.781. For the fourth objective, the findings revealed that the study established the existed of a strong positive correlation (R = 0.681**,p-value=0.001<0.01) between project risk monitoring & control and implementation of (IRS) Project and also the regression results revealed that project risk monitoring and control have significance positive effect on implementation of (IRS) Project as indicated by β4= 0.341, p=0.040<0.05, t= 2.085. As such, the project management team should explore ways for enhancing the effectiveness of the tools in risk analysis by providing more orientation of stakeholders on this.

FINANCING MANAGEMENT ANALYSIS OF PASIR KOPO DAM CONSTRUCTION PROJECT IN BANTEN PROVINCE

The strategic program of <span lang="EN-US">the</span> Republic of Indonesia<span lang="EN-US">’s Government</span> is <span lang="EN-US">stated</span> in the National Medium-Term Development Plan (RPJMN) for 2020 – 2024<span lang="EN-US">.</span><span lang="EN-US">One of its target</span><span lang="EN-US">is</span><span lang="EN-US">construction of</span> eighteen (18) multipurpose dams. Pasir Kopo Dam is included in the RPJMN target and its expected to provide raw water<span lang="EN-US"> supply</span>, irrigation water<span lang="EN-US">,</span> and increase the potential for electrical energy through <span lang="EN-US">Micro-Hydro Power Plant (</span>PLTMH<span lang="EN-US">)</span>. <span lang="EN-US">However</span>, the dam construction requires a <span lang="EN-US">huge</span> project costs<span lang="EN-US"> which can’t be handled solely by State Budget (APBN)</span>.<span lang="EN-US"> There is funding gap in State Budget for financing the dam construction, so another financing alternative is needed.</span> Public Private Partnership (PPP<span lang="EN-US">)</span><span lang="EN-US">is </span>an alternative financing scheme for dam construction<span lang="EN-US">. PPP is influenced by economic feasibility analysis and identification of influential project risks. The selection of an investment-worthy PPP Scheme in the Pasir Kopo Dam Development Project is expected to be mutually beneficial for all parties involved in the cooperation.</span>

Project Risk Management Process and Performance of Mpazi Channel Construction Project in Nyabugogo, Kigali-Rwanda

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 mitigation of Covid-19 in the perspective of contractor for sustainable construction in Indonesia

Construction has been significantly influenced by COVID-19. In some countries, construction projects are discontinued, and even in some countries where construction work is still permitted, high safety standards are required. Construction site safety is essential during the COVID-19 pandemic. The contractor is responsible for creating a safe workplace at the project site. Therefore, this paper presents project risk identification and mitigation during the covid-19 pandemic based on contractor’s perspective. This research identified the risk factors related to the COVID-19 pandemic that consist of 5 categories: man, materials, machines, methods, and environment. Between these risk factors, worker shortage, site accessibility, and lack of construction materials, caused by the strict large-scale social restrictions (PSBB) policy are the biggest challenges faced by the contractor. The findings of this research develop the project risk categories and mitigation strategies from the contractor’s perspective. It suggests that future construction in addition to planning the design, operate, maintenance, supply chain, and project management must also consider the occurrence of a pandemic.

Sustainability of Business through Project Risk Identification with Use of Expert Estimates

Projects are a tool that enables enterprises to implement innovation and development activities and achieve the goals in the set time, costs and required quality but they also bring risks that need to be adequately identified, analyzed and assessed. Important tools that can be used in project management in the process of risk identification are expert estimates. However, little attention is paid to determining the accuracy of expert estimates. To verify the accuracy of expert estimates, an analysis of all completed projects for a certain period of enterprise that implemented them was performed. The purpose of the study was to determine the accuracy of expert estimates in the enterprise implementing projects. This was ascertained by analyzing all available completed projects and by Barnard’s test at the significance level of α = 0.05. The Phi coefficient of association was used to determine its extent. In the paper, we pointed out how inappropriate expert estimates affect the completion of the project within the specified period.

Risk Identification, Assessments, and Prediction for Mega Construction Projects: A Risk Prediction Paradigm Based on Cross Analytical-Machine Learning Model

Risk identification and management are the two most important parts of construction project management. Better risk management can help in determining the future consequences, but identifying possible risk factors has a direct and indirect impact on the risk management process. In this paper, a risk prediction system based on a cross analytical-machine learning model was developed for construction megaprojects. A total of 63 risk factors pertaining to the cost, time, quality, and scope of the megaproject and primary data were collected from industry experts on a five-point Likert scale. The obtained sample was further processed statistically to generate a significantly large set of features to perform K-means clustering based on high-risk factor and allied sub-risk component identification. Descriptive analysis, followed by the synthetic minority over-sampling technique (SMOTE) and the Wilcoxon rank-sum test was performed to retain the most significant features pertaining to cost, time, quality, and scope. Eventually, unlike classical K-means clustering, a genetic-algorithm-based K-means clustering algorithm (GA–K-means) was applied with dual-objective functions to segment high-risk factors and allied sub-risk components. The proposed model identified different high-risk factors and sub-risk factors, which cumulatively can impact overall performance. Thus, identifying these high-risk factors and corresponding sub-risk components can help stakeholders in achieving project success.