Risk Management In Construction Projects Research Articles

Factors influencing financial risk management in construction projects

The infrastructural and economic development of a country merely depends on the construction industry and its growth. There are many risk factors involved with the construction industry during planning, execution and commissioning of the projects. Dealing with the risk factors in construction industry have been known as a crucial management process in order to achieve the overall objectives of the industry in terms of cost, time, safety, quality and environmental sustainability. This report is related with the financial aspects which directly take part in the industry for which studies have been conducted with various engineers, contractors and labors in and around north-western districts of Tamilnadu. The perspectives at different levels of management have been concluded with the standard questionnaire format that has been investigated and their results are analyzed based on the current scenario. With the help of these surveys and data analysis by Relative Importance Index (RII), the most related factors among the identified factors were found to be labour risk, material risk, credit risk, planning risk, execution and environmental related factors. The suggestions and recommendations have been expressed to overcome those risk moderations.

RISK MANAGEMENT IN THE IMPLEMENTATION OF PROCUREMENT PROCEDURES FOR THE NUCLEAR POWER PLANTS CONSTRUCTION

In this paper, the authors consider approaches to risk management in the nuclear industry and carry out a risk analysis in the implementation of procurement procedures for the nuclear power plants construction. The problem under study is relevant on the scale of the construction of typical large industrial facilities, goods, works and services for which they are supplied through the public procurement system. This study is significant both in the practical field of application of existing methods for assessing project risks, and in the theoretical field of studying various combinations of methods for qualitative and quantitative risk measurement. The risk analysis was carried out on the basis of data on equipment purchases made during the construction of the Leningrad NPP-2. The authors made a forecast of the delay from the date of delivery of equipment under the contract. To develop recommendations on the formation of a temporary reserve for the supply of equipment, three concluded contracts for the supply of equipment for the construction of power units of the Akkuyu NPP (Turkey) were selected. As a result of the study, recommendations were formulated for risk management of the NPP construction project implemented through the public procurement system.

Safety Risk Estimation of Construction Project Based on Energy Transfer Model and System Dynamics: A Case Study of Collapse Accident in China.

Analyzing and understanding the occurrence and evolution mechanisms of construction accidents are important for construction safety management. This study proposed a hybrid approach of integrating the energy transfer model (ETM) and system dynamics (SD) theory to delineate the entire evolution stage of the construction accident. Specifically, the Fengcheng Power Plant construction platform collapse accident (FPCA) was taken as a practical case study. First, the ETM is applied to demonstrate the evolving nature of the accident. Then, the network of the accident-causing factors is constructed using the SD theory to analyze the dynamic change characteristics. The results indicate that the accident was caused by risk factors with complex interactions at the management level. An energy constraint failure occurred when the transfer of dangerous energy transpired at the physical entity level, inducing the event. The proposed approach can provide a useful reference for safety risk estimation and management in future major construction projects.

Data-Driven Process Mining Framework for Risk Management in Construction Projects

Construction Projects are exposed to numerous risks due to their complex and uncertain nature, threatening the realization of the project objectives. However, Risk Management (RM) is a less efficient realm in the industry than other knowledge areas given the manual and time-consuming nature of its processes and reliance on experience-based subjective judgments. This research proposes a Process Mining-based framework for detecting, monitoring, and analysing risks, improving the RM processes using evidence-based event logs, such as Risk Registers and Change-Logs within previous projects’ documents. Process Mining (PM) is a data-driven methodology, well established in other industries, that benefits from Artificial Intelligence(AI) to identify trends and complex patterns among event logs. It performs well while intaking large amounts of data and predicting future outputs based on historical data. Therefore, this research proposes a Bayesian Network (BN)-based Process Mining framework for graphical representation of the RM processes, intaking the conditional dependence structure between Risk variables, and continuous and automated risk identification and management. A systematic literature review on RM, PM, and AI forms the framework theoretical basis and delineates the integration areas for practical implementation. The proposed framework is applied to a small database of 20 projects as the case study, the scope of which can be tailored to the enterprise requirements. It contributes to creating a holistic theoretical foundation and practical workflow applicable to construction projects and filling the knowledge gap in inefficient and discrete conventional RM methods, which ignore the interdependencies between risk variables and assess each risk isolated.

Relation Extraction of Domain Knowledge Entities for Safety Risk Management in Metro Construction Projects

Gathering experience and organizing knowledge from a large number of engineering construction projects is conducive to more effective and efficient safety risk management in construction projects. Metro construction practitioners often find it difficult to determine what professional knowledge is needed to establish better management. By constructing the knowledge structure of safety risk management, which is composed of domain knowledge entities (DKEs) and their hierarchical relations, practitioners can systematically master the knowledge of safety management, enhance safety management levels, and reduce the occurrence of accidents. Traditionally, domain knowledge structure was determined by experts, the mistakes occur due to the limitations of individual knowledge, and high time costs are unavoidable due to the massive amount of data. Therefore, in this study, we used a rule-based Chinese-language natural language processing (C-NLP) method to automatically extract the hierarchical relations between DKEs from a large dataset of unstructured text documents; we aimed to clarify the affiliation relationship and parallel relationship between DKEs. First, 68,817 sources of literature written in Chinese were collected. Next, the specific syntactic structures of relations of the DKEs were analyzed. Hierarchical extraction rules, including 16 hyponymic indicators and 8 appositive indicators, were revealed based on the linguistic characteristics. Then, the relations were extracted from test dataset. The precision and recall values were used to verify the model. Finally, the hierarchical relations of all the DKEs were extracted, and the knowledge structure was formed. The proposed method of hierarchical relation extraction contributes to the quick automatic construction of knowledge structures and minimizes expert bias. The knowledge structures can be used to guide safety training and can assist practitioners in safety risk management.

Employer Toxic Leadership and Implications for Managing Risk and Stakeholder Management: a Road Improvement Project in Nepal

This is a research paper that is focused on assessing the impacts of Employer Toxic Leadership in terms of Risk and Stakeholders Management of an 81Km road construction project in Nepal. An interpretive methodology was utilised in order to help understand implicitly the management leadership’s impact on the project. The scope for this research was the on-site supervisory team. The targeted population of interest was made up of 15 engineers located at on-site offices in the early construction phase of a road construction project. The research outcomes consisted of six (6) main themes with corresponding nineteen (19) sub-themes.The paper addresses raised issues of toxic leadership impacts within risk and stakeholder management and establishes outcomes and implications for the continuing project construction management. The paper also indicates that the Employer conducts inadequate risk management especially in relation to a variety of stakeholders and thus faces serious project performance issues leading to project failure.The Employer road construction management is considered to be a very weak risk management environment due to institutional toxic leadership style, orientation and lack of professional engagement of project management with stakeholders. The Employer (government department - DoR) has purposely and negatively altered the project quality and delivery expectations resulting in serious questions over its operational governance stance and financial efficacy.

A Scientometric Analysis of Studies on Risk Management in Construction Projects

Risk management is one of the topical areas in construction project management research. However, no attempt has been made in the past decades to explore the emerging themes in this area. This paper reviews the research trends in risk management in construction. The bibliometric data of 1635 publications between 1979 and 2022 were extracted from Scopus using a set of keywords. The study used VOSviewer and Gephi to conduct a scientometric analysis on the extracted publications. The review outcome indicates a significant increase in publications on risk management in construction, with about 205 publications recorded between 2021 and 2022 alone. Based on this analysis, it is projected that the next decade will see significant research on risk management, especially as the construction industry moves towards Industry 5.0 with many uncertainties. Further, the most productive countries of risk management studies in construction include China, the United States, the United Kingdom, Australia, and Hong Kong. Emerging key research areas are discussed using network diagrams and clusters. These areas include the processes in risk management, risk analytical models and techniques, sources of risk and uncertainties, effective knowledge-based systems for improved risk management, risk contingency in construction contracts, risk-integrated project planning and scheduling, and stakeholder management. The findings of this study inform researchers on the current progress of risk management studies in construction and highlight possible research directions that can be considered.

A method for the ontology-based risk management of PPP construction projects

PurposeWith the increasing complexity of public–private partnership (PPP) projects, the amount of data generated during the construction process is massive. This paper aims to develop a new information management method to cope with the risk problems involved in dealing with such data, based on domain ontologies of the construction industry, to help manage PPP risks, share and reuse risk knowledge.Design/methodology/approachRisk knowledge concepts are acquired and summarized through PPP failure cases and an extensive literature review to establish a domain framework for risk knowledge using ontology technology to help manage PPP risks.FindingsThe results indicate that the risk ontology is capable of capturing key concepts and relationships involved in managing PPP risks and can be used to facilitate knowledge reuse and storage beneficial to risk management.Research limitations/implicationsThe classes in the risk knowledge ontology model constructed in this research do not yet cover all the information in PPP project risks and need to be further extended. Moreover, only the framework and basic methods needed are developed, while the construction of a working ontology model and the relationship between implicit and explicit knowledge is a complicated process that requires repeated modifications and evaluations before it can be implemented.Practical implicationsThe ontology provides a basis for turning PPP risk information into risk knowledge to allow the effective sharing and communication of project risks between different project stakeholders. It can also have the potential to help reduce the dependence on subjectivity by mining, using and storing tacit knowledge in the risk management process.Originality/valueThe apparent suitability of the nine classes of PPP risk knowledge (project model, risk type, risk occurrence stage, risk source, risk consequence, risk likelihood, risk carrier, risk management measures and risk case) is identified, and the proposed construction method and steps for a complete domain ontology for PPP risk management are unique. A combination of criteria- and task-based evaluations is also developed for assessing the PPP risk ontology for the first time.

Relevance of Risk Management in the Delivery of Construction Projects in Developing Countries

Construction projects suffers poor performance due to poor risk management in its process in developing countries. A strict set of understanding regulations must be followed during the construction process to avoid these risks. Unfortunately, it is uneasy in construction projects to completely avoid risks as they are bound to be unknown factors that arises over the course of project execution. Risk management in construction projects is inherently risky but technically complex than projects in industries. It is one of the major rules undertaken by a project manager for an effective management of a construction projects. An effective management approach to projects is required as most times risk is handled through application of contingencies or time that are not determined based on comprehensive analysis of the risks that can affect a particular project. This paper establishes the relevance of risk management in the delivery of construction projects in developing countries. It further gives an overview of performance and addresses the problem inherent in risk managements in construction projects that will allow for achieving a successful project delivery within the context of time frame, minimizing cost overruns and optimizing project quality. The paper recommends that in order to improve the chance of success in construction projects and reduce the potential risks, risk management must be an important part of the decision-making process for a construction enterprise.

Risk Identification in Residential Construction Project: A Systematic Literature Review

Risk is always present in every construction project. Residential building construction projects have various risks and are likely to be affected due to their difficulty and multiple operations and threats. Purpose of this journal is to understanding risk factors in a residential construction project spread over several countries, with various project size and complexity, and to get up to date research information. Risk factors are divided into three categories, namely internal factors, projects, and external factors. Three categories above is further divided into two technical and non-technical risk. This journal review 40 selected journals that discuss risk identification and risk management in residential construction projects. Risk factors in residential projects are generally very diverse and give us an idea that the interrelationships between the parties with an interest in the project contribute to the risk factors themselves occurring in the course of the project. It has been mentioned that the risk factors that occur in residential projects are something that is commonplace in various countries, in this case contributing to the success of the project. Outline on this journal has succeeded in providing information on the extent to which risk factors are currently occurring and there is a high potential for a change in the percentage of risk factors according to the classifications presented in this journal for other construction projects in the future.

Analisis Risiko Dalam Sistem Rantai Pasok Pada Proyek Upgrade Trans Studio Mall Makassar

The supply chain system is the relationship between the parties from the vertical structure to the horizontal structure in the system of a project being implemented. In the supply chain system, there may be uncertainties that pose risks. Construction project risk management needs to be implemented in the supply chain system to determine the success and objectives of project procurement. Thus, the purpose of this research is to determine the risks that occur in the supply chain system in the Makassar Trans Studio Mall upgrade project. Data collection was carried out by direct observation in the field, interviews, and distributing questionnaires to be filled out by the parties to the project according to their respective work experiences. Respondents amounted to 13 people. Data analysis for this study used the Likert scale method using the severity index (SI) formula. From the results of this study after collecting data, it can be concluded that there are 22 risk factors identified. These risks occur with various types of risks, namely 2 risks that are categorized as high, 19 risks that are categorized as moderate, and 1 risk that is categorized as low.

The role of contract incompleteness factors in project disputes: a hybrid fuzzy multi-criteria decision approach

PurposeContract incompleteness with deficiency, inconsistency, defectiveness, and ambiguity in contract clauses, which can cause misunderstandings and misinterpretations, may result with disputes in projects. This study aims to investigate contract incompleteness factors with a hybrid fuzzy multi-criteria decision approach.Design/methodology/approachContract incompleteness factors were ranked by fuzzy VIKOR (Visekriterijumska Optimizacija I Kompromisno Resenje) method, and the most significant factors were subjected to fuzzy decision-making trial and evaluation laboratory (DEMATEL) to examine their causal relationships. The study is not limited to ranking the identified factors solely, since their cause-effect interactions are also essential for proper risk management in construction projects.FindingsHybrid use of multi-criteria analysis reveals that ambiguity in enforceability including excessive demands and significant amendments in the scope of works are the top two causal contract incompleteness factors, while lack of implementation details and focus of focal point, and insufficient supporting and technical documents are the most affected ones.Originality/valueContractual causes of disputes due to contract incompleteness factors other than requirements of the contracts have been rarely investigated in the literature. The research is one of the first studies in the literature investigating the causal relationship among factors in construction contracts, which might lead to project disputes. Findings are expected to improve contract drafting, eventually contributing to effective risk management in construction projects.

Risk Decision-Making of Multiobjective Chaos Search in Construction Projects considering Loss Level and Probability Level

In engineering projects, the coordination and management of multiple objectives is an important part of project management, which has a direct impact on the realization of objectives in terms of project duration, cost, and quality. The current engineering project investment presents the characteristics of large scale, long period, and many risks, which puts forward higher requirements for the multiobjective coordinated management of the project. Therefore, the analysis and optimization of the various objectives of the engineering project is the basis for achieving multiobjective balance and coordination. The comprehensive consideration of the risks faced by the engineering project and the dynamics of the environment in which it is located can make the objective optimization more realistic. On the basis of risk identification and risk evaluation, this paper is committed to considering multiple objective factors that affect the outcome of risk decision-making to achieve the optimization of decision-making schemes and applies multiobjective genetic algorithm to the optimization of decision-making schemes, thus finding a way to optimize the decision-making scheme. This paper analyzes the research progress and status of construction project risk management decision and multiobjective evolutionary algorithm and points out the imperfections of the current research. Then it introduces the related theory of construction project risk management decision, the related terminology of multiobjective optimization problem and the method used in this paper —the principle, process, and characteristics of genetic algorithm and prepares for the following problem solving. In this paper, a mathematical model for multiobjective decision-making of engineering project risk management is established, and the multiobjective genetic algorithm is used to solve the model. Through the analysis of examples, a series of Pareto optimal solutions with good convergence and diversity are obtained, the best combination of various risk control measures is found, and three goals of risk evaluation value, management cost, and risk loss are achieved. The two models with or without risk correlation present certain differences, the model with correlation considered is more accurate and applicable than the model without correlation considered in the existing research.

Valuation of Risk Management in Construction Projects Through the Use of Feedback Mechanisms

Experience feedback data can have different types depending on the civil engineering sector for example experimental measurements, expert information, visual observation, these formats can provide several different practices for capitalizing on experience feedback, processing and finally valuation of the information capitalized for the diagnosis. The current article addresses the application of experience feedback to construction sites. As we shall argue, if the concept of experience feedback is applicable it would appear that the devices implemented in the construction sites are not taken into consideration and that, consequently, this sector faces significant risks. This present study enables us to propose an approach to improve experience feedback by taking into account the existence of different practices in a construction site. We shall argue that the implementation of a safety case makes it possible to promote the creation of a communication link between community of practice centered around experience feedback (REX) which systematically promotes the improvement of the practice of this device.

Intelligent Risk Management in Construction Projects: Systematic Literature Review

As digitalization leads to the development of the global economy and artificial intelligence stimulates technological innovation, integrating smart management methods into project management is becoming more and more critical to the development of the construction industry. As an influential branch of engineering management, intelligent risk management in the construction field will be a future research direction. Hence, the aim of this study is to find the gaps and future research trends in intelligent risk management field by Systematic Literature Review. In order to achieve these objectives, 436 articles were selected from the WOS and Scopus databases to be analyzed by CiteSpace scientometric software, and the results were classified into collaborative network analysis, co-citation analysis, and public network analysis. From the analysis, China had the highest number of publications, while the United States was the most influential country in this field. The researchers at different institutions in this field have formed research teams despite the lack of collaboration between the authors and their institutions. In co-cited references, the emphasis was on traditional methods and applications of risk analysis, with fewer citations of novel methods. According to the keywords, the clusters of keywords, and the temporal evolution of the keywords, and combining the conceptual model, 5 research gaps areas were discovered. In order to fulfill these challenges and barriers, this study found the future research trends, including: developing digital management platform for intelligent construction management and risk management; building a decision-making system for risk management to find an optimum solution; refining building digital models which would be the basis of digital management platform; identifying and category the characteristic construction risk factors by using machine learning techniques, just like text mining or knowledge graph; building an API to embed decision making system into digital management platform, and the intelligent risk management system in real-time projects to verify its possibility.

MSCA based Deep Recurrent Neural Network for Statistics Risk Management in Construction Projects

MSCA based Deep Recurrent Neural Network for Statistics Risk Management in Construction Projects

Analysis of Risk Management in Construction Projects Using SPSS method

Risk management is about projects Risk analysis, identification like seeing and responding Defined as a formal process. It is negative events Reduce probability and impact While positive events Opportunities and impact includes increasing, among others to meet project objectives. Construction Risk Management is Occurs in construction projects To reduce the impact of risks Evaluate procedures is the process of implementation. This risk the management process is risk management Complete to build project Involves planning, which is planning Managers identify risks, Allows monitoring and mitigation. Project like project manager Management Software Risk Management Makes the process much easier. Full Risk with the feature Gantt chart Develop a management plan, then real-time dashboards and manage your projects with reports Monitor. Try it for free today of the construction planning process Construction risk management in early stages The project was created. What is this project Risks can occur and take them Describes the risk response to judgment? And to take ownership of the problem Someone on the team to resolve it This includes recruiting. Construction Risk Management and Fire Prevention Plan There are many benefits to creating, including: Increased safety and workers well being of improved company Reputation. with workplace accidents Avoid associated costs. Construction projects are a building or to build a structure It is an organized effort. Civil Engineering and Architecture In the fields, construction Projects are an infrastructure or Integrates the building firmly involves the process. Evaluation parameters: Political instability risk, Economic risk,Social risk, Work quality risk, Time and cost risk, Technological risk, Documents and information risk, Stakeholder’s risk.

Discussion on Construction Safety Risk Management of Electric Power Construction Project

Discussion on Construction Safety Risk Management of Electric Power Construction Project

Research on Risk Management of Transmission and Distribution Line Construction Project

Research on Risk Management of Transmission and Distribution Line Construction Project

Building Schedule Risks Simulation by Using BIM with Monte Carlo Technique

Risk management in construction projects has great importance through its impact on the basic objectives of the construction projects, as controlling the risks of the construction projects helps reduce cost overruns and time overruns and improve the quality of the construction projects. This paper aims to highlight the role of BIM in risk management in construction projects by generating a predictive risk model using Monte Carlo simulation to analyze a number of risks and generating a 3D model and 4D model to show the effect of risks. The predictive risk model can help project managers control the risks that affect the construction projects and enhance communication between all stakeholders for the project. The methodology was applied to two risk scenarios, the optimistic scenario for risks, and the pessimistic scenario for risks in one of the construction projects in Iraqi through the use of four commercial programs working together. The study concluded that the building information modeling technique has great importance in reducing the risks affecting the construction project by showing the effect of these risks during the project’s construction phases and controlling them.