Project Risk Identification Research Articles

Establishing Core Factors of Risk Management Influencing Performance Outcome of Small and Medium Firm's Construction Projects in Gauteng

The quest for delivering successful construction projects has urged South African small and medium enterprises (SMEs) to adopt risk management in their projects. However, it has been evinced that SMEs projects in South Africa especially in the Gauteng province have encountered poor performances. Thus, this article determines core risk management factors influencing project outcome of SMEs. A deductive approach was embraced using a questionnaire. The data were collected from 181 conveniently sampled respondents in Gauteng, graded from Grade 1 to 6 of the CIDB (Construction Industry Development Board) grading system. The Statistical Package for the Social Science (SPSS) version 23 was used to analyse the data by computing exploratory factor analysis and multiple regression analysis. It was revealed that SMEs performance outcome is influenced by eight risk management factors. The influential factors are organisational environment, defining project objectives, resource requirements, risk measurement, risk identification, risk assessment, risk response and action planning and monitoring, review and continuous improvement. The risk management factors established in this article are reliable and valid in projects undertaken by SMEs in the South African construction industry and the findings can serve as a guideline for contractors to achieve success in this context. The study may be repeated in other countries globally, however, it cannot be generalised due to the restrictions pertaining to the geographical area.

A SYSTEMATIC REVIEW AND ANALYSIS OF RISK ASSESSMENT IN HIGHWAY CONSTRUCTION PROJECTS

Before planning and managing risks to reduce the causes of severe risks associated with road construction, it is very important to conduct an evaluation first. Aspects related to risk are convoluted in several steps from design to planning to project fulfillment. This research aims to implement a complete risk management process for highway construction projects. Through this process, there will be a list of risks in the highway construction project (risk identification) and the definition of the most significant risk through the application of the evaluation process (applying risk analysis and valuation). To successfully improve the performance of road projects, it is necessary to identify and assess various risk factors in a project for efficient project fulfillment. The research method begins by reviewing at least 50 articles to find a list of the main risk factors that might be encountered during highway construction. This analysis involves the identification, classification, and assessment of various risks involved in the construction of a highway project.

Risk Influence Analysis Assessing the Profitability of Large Photovoltaic Plant Construction Projects

The global energy system is in a phase of change for power generation technologies which involve traditional fossil fuel-based technologies to renewable energy-based systems, thanks to lower construction costs, mainly for photovoltaic energy, and changes in countries’ energy policies. In the case of Spain, both factors have led to a reactivation of renewable technologies, which can be found from the data on requests for access and connection to the electricity transmission network that are being processed in Red Eléctrica de España (REE). The requests that were granted access to the network exceeded 100 GW of power in November 2019 alone, and the companies which made the requests must commence electricity production by 2025. During the early stage of approval considerations, it is necessary to carry out an influence study of the risks that can already be identified, as this would enable determining the effects of these risks on the project’s main financial parameters. Based on a risk identification for similar prior projects, experts are typically asked to make their judgments on the influence of such risks on the main economic variables of a project, focusing on the project’s cost, time, and scope. By applying the fuzzy sets, these judgments can be transformed into triangular values that, through Monte Carlo simulation, allow us to assess the influence of these risks on the main financial parameters: the net present value (NPV), internal rate of return (IRR), and payback (PB); as a result of obtaining these parameters, a response to project risks can be planned. To check the functionality of the model, it was applied to a case study involving a construction project for a 250 MW photovoltaic plant located in Murcia (Spain). The application of this methodology allowed us to determine which evaluation criteria are most appropriate based on the philosophy of the PMO (Project Management Office) and the data that were obtained.

A Case Study of Risk Management of Automotive Industry Projects Using RFMEA Method

Considering the market need and customer attraction, automakers are always trying to define new projects and present products with new capabilities in the market. That is why a significant part of car companies’ development research is focused on the definition of new projects. Principally, project risk management in car companies is essential and thus given special attention. There are different theories and methods of project risk control. However, since there is complete awareness of FMEA-related issues (Failure Mode and Effects Analysis) in automotive companies due to the establishment of the quality management system, the project's risk analysis using FMEA method to control the risk of automotive industry projects is presented in this paper by a real example. For this purpose, FMEA indicators tables are designed and presented proportionally to project risk management. Results of this research show that using failure mode and effects analysis for project risk management ensures the detection of project's weaknesses and provides a practical model for identification and reduction of project risks.

Framework for Risk Identification of Renewable Energy Projects Using Fuzzy Case-Based Reasoning

Construction projects are highly risk-prone due to both internal factors (e.g., organizational, contractual, project, etc.) and external factors (e.g., environmental, economic, political, etc.). Construction risks can thus have a direct or indirect impact on project objectives, such as cost, time, safety, and quality. Identification of these risks is crucial in order to fulfill project objectives. Many tools and techniques have been proposed for risk identification, including literature review, questionnaire surveys, and expert interviews. However, the majority of these approaches are highly reliant on expert knowledge or prior knowledge of the project. Therefore, the application of such tools and techniques in risk identification for renewable energy projects (e.g., wind farm and solar power plant projects) is challenging due to their novelty and the limited availability of historical data or literature. This paper addresses these challenges by introducing a new risk identification framework for renewable energy projects, which combines case-based reasoning (CBR) with fuzzy logic. CBR helps to solve problems related to novel projects (e.g., renewable energy projects) based on their similarities to existing, well-studied projects (e.g., conventional energy projects). CBR addresses the issue of data scarcity by comparing novel types of construction projects to other well-studied project types and using the similarities between these two sets of projects to solve the different problems associated with novel types of construction projects, such as risk identification of renewable energy projects. Moreover, the integration of fuzzy logic with CBR, to develop fuzzy case-based reasoning (FCBR), increases the applicability of CBR in construction by capturing the subjective uncertainty that exists in construction-related problems. The applicability of the proposed framework was tested on a case study of an onshore wind farm project. The objectives of this paper are to introduce a novel framework for risk identification of renewable energy projects and to identify the risks associated with the construction of onshore wind farm projects at the work package level. The results of this paper will help to improve the risk management of renewable energy projects during the construction phase.

Risk analysis by integrated fuzzy expected value method and fuzzy failure mode and effect analysis for an elevated metro rail project of Ahmedabad, India

Risk identification and analysis for complex mega infrastructure projects has become an integral part of the present day project management process. This paper aims to develop an integrated Fuzzy Expected Value Method (FEVM) and Fuzzy Failure Mode and Effect Analysis (FFMEA) method for a complex infrastructure project such as the construction of an elevated corridor for metro rail in Ahmedabad, India. The design and methodology adopted in this research work was a primary data survey, where the major risky activities of an elevated metro rail infrastructure project were identified through interactions with experts, questionnaire surveys, and personal experience. The identified risks were analyzed for likelihood, impact, severity, detection, occurrence and risk priority numbers. Further computations of fuzzy risk severity (FRS), fuzzy risk priority score (FRPS), and risk rankings were carried out through the new application of integrated fuzzy EVM and fuzzy FMEA methods. It has been found that land acquisition, feasibility, tendering, segment erection, segment casting, obligatory span, construction planning, launching girder, road widening, piles and piers activities were highly risky and had very high fuzzy risk severity and FRPS values (0.605–0.775). Risk mitigation measures were proposed for all critical activities of the elevated metro project in Ahmedabad.

A framework to dynamic identification of project risks

PurposeMerging and updating project information and recording changes can give dynamic risk identification at all stages of the project. The main purpose of this research is to create an integration in construction information.Design/methodology/approachIn this research, the 5D model was prepared and then all model information was entered into the database designed in SQL Server, the project report tables were coded, and finally, a database with four groups of information was ready for risk identification.FindingsCreating an integrated risk identification platform reduced rework and time and cost control and change management, which were positive effects of risk identification at the right time.Research limitations/implicationsIn order to identify risks, creating multilateral databases whose information integration enables timely completion of the project and compliance with the planning.Practical implicationsThis research is the basis for identifying project risks within the framework of building information modeling and can be an effective contribution to increasing the risk-taking efficiency of the project.Originality/valueAs a matter of fact, marked time and cost are terrific motivating forces for the building industry, materializing with identify risk well-time. In any case, identifying risk engaged with all of the dimensions depend on this industry.

Project Risk Identification Based on the Interaction of Risks from the Approach of Multi-agent Simulation

Risk, which is intrinsically a hidden uncertainty, often conceals in all links of a project, making it groundless for reasoning and demonstration in risk identification. In a practical project, risks combine and interact with each other in a complicated manner, so that it is difficult to directly quantify the probability of their occurrence under the impact of interaction. For this reason, this paper utilizes the common risk identification methods to obtain a risk list, and then constructs a risk interaction network to identify their interaction and determine its strength. Subsequently, the approach of multi-agent simulation is taken to determine the probability of risk occurrence while taking into account the interaction of risks.

An Examination of Project Risk Identification and Prevention Techniques in Ensuring Project Success; A Case Study of Electricity Company of Ghana (ECG)

An Examination of Project Risk Identification and Prevention Techniques in Ensuring Project Success; A Case Study of Electricity Company of Ghana (ECG)

Risk Identification and Analysis for PPP Projects of Electric Vehicle Charging Infrastructure Based on 2-Tuple and the DEMATEL Model

Risk management is critical to the success of electric vehicle charging infrastructure public–private partnership (EVCI-PPP) projects, as risks are present throughout the whole life cycle of projects. However, in EVCI-PPP projects, risk factors are often interdependent and, consequently, the interrelationships among factors affect the risk management, which is ignored in the existing studies. To identify the risk factors of EVCI-PPP projects and analyze their internal influence relations, this paper develops a risk identification and analysis model of EVCI-PPP projects based on the 2-tuple linguistic representation model and the decision-making trial and evaluation laboratory (DEMATEL) model. First, a risk factor set is established including 22 criteria involved in 5 dimensions of political/legal risk, economic/market risk, social/environment risk, project/technical risk, and managing risk. Next, the 2-tuple model is introduced to integrate the decision makers’ evaluation information in a linguistic environment, and the direct relation matrix is calculated. Then, the cause–effect relations and a significant degree of risk factors are interpreted using the extended DEMATEL technique. The results show that economic/market risk is the most significant factor of EVCI-PPP projects, and 22 criteria are classified into 14 cause factors and 8 effect factors. Finally, suggestions are provided for decision-makers to ensure the success of EVCI-PPP projects.

PROJECT RISK IDENTIFICATION OF A NEW PRODUCT IN ENTERPRISE IN SLOVAKIA

Enterprises want to focus on successfully managed projects. Projects must be focused on fulfilling project expectations and setting project objectives. It is necessary to ensure the early identification of project risks. If managers understand and know project risks, they can mitigate them. They can use mitigation to prevent projects from failing, or financial loses in the company. The main aim of this paper is the identification of project risks of a new product in a particular company in the Slovak Republic using the method of brainstorming. Risks can positively but mainly negatively affect the implementation of the proposed project. The proposed project was created based on the methods of analysis, forecasting, comparison, synthesis and provided information from a specific enterprise. The identified risks are grouped into the specified project implementation categories, in order to better identify the identified risks as well as to implement other project risk management steps. The results of the study show that early identification of project risks should be a responsibility for project team members, for top managers and the corporate culture of each enterprise.

Assessment of Construction Project «Pure» Risks

Construction industry has many drivers. The main one is investments. The bigger investment is the more importance takes the assessment of construction production. The investor makes the decision to invest based on assessment of construction production, organisational and technological reliability. The rapid technology and construction management tools development obliges the investor and his team to create new approaches. The article authors propose to consider it in the identification, analysis and subsequent management of pure project risks. Pure risks are defined as risk events, which implementation is clearly negative or has a neutral outcome. Generally the pure risks are not directly related to financial risk events and are not considered as classical approaches of risk management, which adversely affects the construction project prediction. Consideration of the pure construction risks at different stages of building production allows considering the project from the point of view of potential risks. So the investor can quickly make the decision to invest in the project and to assess the possible additional costs of construction, as the construction manager for different production stages would be able to foresee and prevent some risks implementation.

PROJECT FINANCE MECHANISM FOR INVESTMENT PROJECT REALIZATION

This article focuses on project finance analysis, one of the most effective mechanisms to accumulate different financial resources in order to implement investment projects. Project finance is considered as a system, including multiple elements (participants, finance objects, contracts, risk management, infrastructure), which are in close relationship and provide financial flows effectiveness. Characteristics of project finance development current stage were identified. Project finance development current stage is focused on sustained economic growth, innovative development and global economy. It is shown that project finance system effective functioning is impossible without project risk management, identification and distribution of risks between project participants. A steady trend of deals and their costs annual increasing, decreasing in proportion of borrower`s own capital in total financial resource amount were identified and based on the global project finance market analysis. The factors affecting the project finance impact were defined: project management effective team presence, use of project management`s modern professional standards and technologies, establishment of communications system between project`s participants, project`s information and financial flows` transparency, use of qualified consultants and experts etc. It was considered that use of the project finance mechanism to implement innovative investment projects assumes particular importance during the establishment and development of digital economy .

Управление рисками инвестиционного проекта

The article presents the results of a study on risk management of an investment project, using the example of projects in the coal mining sector. Issues of identification and evaluation of project risks are considered. An integrated and holistic mechanism for understanding problems related to risk management of investment projects has been formed.

Assessment and Countermeasures for Offshore Wind Farm Risks Based on a Dynamic Bayesian Network

Wind power is a kind of clean energy promising significant social and environmental benefits, and in The Peoples Republic of China, the government supports and encourages the development of wind power as one element in a shift to renewable energy. In recent years however, maritime safety issues have arisen during offshore wind power construction and attendant production processes associated with the rapid promotion and development of offshore wind farms. Therefore, it is necessary to carry out risk assessment for phases in the life cycle of offshore wind farms. This paper reports on a risk assessment model based on a Dynamic Bayesian network that performs offshore wind farms maritime risk assessment. The advantage of this approach is the way in which a Bayesian model expresses uncertainty. Furthermore, such models permit simulations and reenactment of accidents in a virtual environment. There were several goals in this research. Offshore wind power project risk identification and evaluation theories and methods were explored to identify the sources of risk during different phases of the offshore wind farm life cycle. Based on this foundation, a dynamic Bayesian network model with Genie was established, and evaluated, in terms of its effectiveness for analysis of risk during different phases of the offshore wind farm life cycle. Research results show that a dynamic Bayesian network method can perform risk assessments effectively and flexibly, responding to the actual context of offshore wind power construction. Historical data and almost real-time information are combined to analyze the risk of the construction of offshore wind power. Our results inform a discussion of security and risk mitigation measures that when implemented, could improve safety. This work has value as a reference and guide for the safe development of offshore wind power.

Research of the aspects of modeling of the project management of risk of implementation system information support

The object of research is the risk management of the information support system of enterprise management. One of the most problematic places is the identification of anticipated risks and their minimization. The process of risk management is associated with the complexity and duration of the implementation of the information management system of the enterprise and its relatively high cost.In the course of the study, the modeling approaches of the project risk management process were used. Stages of modeling the process of risk management of the project of implementing the information support system are determined. They include the identification and assessment of project risks, an analysis of key risks and opportunities, the definition of strategies and methods for responding to risks. As well as the development and implementation of action plans to minimize risks, measure, monitor and report on risk management activities with an analysis of the results of management decisions. For their implementation, a standard BPwin program procedure is proposed with the possibility of ABC estimation of the cost of performing each stage.Thanks to this, it is possible to control the production costs at every stage of the information support system. In comparison with similar known methods, approaches are suggested that minimize the loss of the management of enterprise management information systems as a result of the impact of risks through predictability and minimizing the risks to which the project is exposed.

FMEA TECHNIQUES USED IN ENVIRONMENTAL RISK ASSESSMENT

Other industries or strategic installations cities after the industrialization process, a large percentage of urban land use, consciously or unconsciously to have been allocated. Investigation and detection of black spots and dangerous in systems and processes to prevent accidents is of particular importance. Risks in the project, are unknown events that may happen in the event of a negative or positive impact on project objectives is effective. Each event has specific causes and consequences are distinguishable. The consequences of these events directly in time, cost and quality. Therefore, effective project risk identification and to determine the effect of special importance. Organizations should be able to use a variety of methods to assess the risk of one or a combination of the select few. This article introduces the risk assessment and FMEA methodology has been focused on the process of doing that.

Design and Development of a Risk Identification and Analysis Tool (RIAT) for Australian Public-Private Partnership Infrastructure Projects

Design and Development of a Risk Identification and Analysis Tool (RIAT) for Australian Public-Private Partnership Infrastructure Projects

Risk management in construction projects

Abstract In the era of galloping globalization, there is no way not to talk about the risk, which has become an indispensable part of everyday life. The risk is present everywhere, in every area of ​​life. One such area is the construction industry, where risk is ever-present element of a great puzzle. Effective risk management, does not apply to the resignation of the risk, which is seemingly the cheapest option activity. The basic problem of this option, however, is its senselessness economic, because what is potentially profitable, it is by definition risky and something that does not pose a risk, it is interesting from an economic point of view, and thus, does not bring tangible benefits. Therefore, the effective risk management will be to find a golden mean in its management, in relation to the implemented project. On the one hand it will involve protection against the risk of negative side, by means of detailed identification and classification of risk, resulted in a comprehensive analysis. On the other hand, the management should be based on checking the maximum benefits of these decisions, using all the tools of mathematical and analytical. A detailed analysis, taking into account all aspects of escorts, including even stakeholder analysis will allow us to effectively risk manage what the future will translate into tangible benefits for our project. Identification of project risks, based primarily on determining what its types may affect the project, together with an indication of their characteristic parameters, and estimating the probability of its occurrence on the project. These conditions can be divided into three groups: assurance, uncertainty and risk, under which, in turn, preserve the three types of investors: risk preference, neutrality toward risk and pure risk aversion and its measurement. The result of risk identification and analysis of the project, will be a list of events showing the cause and the probability of an event, and its final assessment of the impact on the environment.

Risk Management in Implementing Wind Energy Project

Analysis of possible risks in the process of implementing a specific project has been carried out, measures to reduce their negative impact on the project have been developed and proposed. The object of study is a wind energy project, namely a wind farm working as part of the national energy system. The implementation of the project is related to both external and internal risk factors that are characteristic to such projects in the real economy sector under the current conditions. Such risks have been classified and the fractional structure of risk adjustment has been analysed taking into account the properties of the particular wind energy project, which consists of three main components. A description has been given of the innovative technology selected for project implementation, power generation using wind, which is used to limit the negative influence of the above-mentioned risks. The current strategic management tools, such as SWOT analysis and McKinsey matrix, which are useful for the identification of project risks, have been examined. For the wind energy project that is being implemented, the project dot location coordinates were determined in the McKinsey matrix on axes: Advantages against competitors and Market attractiveness. Also, a sector characterising the project development prospects was established to be subsequently used as a tool for risk identification. Following the identification of risks, specific measures of state support and special project management measures were developed and proposed to be implemented with the aim of limiting the negative influence of the possible project risks.