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Risk identification often produces nothing more than a long list of risks, which can be hard to understand or manage. The list can be prioritised to determine which risks should be addressed first, but this does not provide any insight into the structure of risk on the project. Traditional qualitative assessment cannot indicate those areas of the project which require special attention, or expose recurring themes, concentrations of risk, or ‘hot‐spots’ of risk exposure. The best way to deal with a large amount of data is to structure the information to aid comprehension. For risk management, this can be achieved with a Risk Breakdown Structure )RBS) a hierarchical structuring of risks on the project. The RBS can assist in understanding the distribution of risk on a project or across a business, aiding effective risk management. Just as the Work Breakdown Structure (WBS) is an important tool for projects because it scopes and defines the work, so the RBS can be an invaluable aid in understanding risk. The WBS forms the basis for many aspects of the project management process; similarly, the RBS can be used to structure and guide the risk management process. This paper presents the concept of the RBS, and gives a number of examples drawn from different project types and industries. Although not necessarily based in FM, the concepts and experience can be applied to any project. The benefits of using the RBS are then outlined, including as an aid for risk identification or risk assessment, comparison of projects, providing a framework for cross‐project risk reporting, and structuring lessons to be learned for future projects. This paper shows how to use the RBS to gain these benefits.

The heavy civil engineering industry (railways, sewage treatment, chemical and pharmaceutical facilities, oil and gas facilities, etc.) is one of the major contributors to the British economy and generally involves a high level of investment. Clients in this industry are demanding accurate cost estimate, proper analysis of out‐turn cost and cost escalation and a high quality risk analysis throughout the construction processes. Current practice in the industry has suggested that there is a lack of structured methodologies and systematic cost escalation approach to achieve an appropriate cost analysis at the outset of projects and throughout the construction processes. In this context the prime objective of this research work is to develop a structured cost escalation methodology for improving estimating management and control in the heavy engineering industry construction processes. The methodology is composed of a forecasting model to predict cost indices of major items in industry and a risk knowledge base model for identifying and quantifying causes of cost escalations. This paper, as part of the research, reviews and discusses a knowledge‐based model for applying a cost escalation factor. The cost escalation factor is made up of market variation, a risk element and a component for bias. A knowledge elicitation strategy was employed to obtain the required knowledge for the model. The strategy included questionnaires, interviews and workshops and deliverables came in the form of influences and their effect on project cost escalation. From these deliverables, the concepts of a decision support model and system specification for applying cost escalation to base estimates is proposed.

Risk analysis plays a vital role in controlling and managing cost overruns in complex construction projects, particularly where uncertainty is high. This study attempts to address an important issue of cost overrun that encountered by metropolitan rapid transit projects in relation to the significance of risk involved under high uncertainty.

In order to solve cost overrun problems in metropolitan transit projects and facilitate the decision-makers for effective future budgeting, a cost-risk contingency framework has been designed using fuzzy logic, analytical hierarchy process and Monte Carlo simulation.

Initially, a hierarchical breakdown structure of important complexity-driven risk factors has been conceptualized herein using relative importance index. Later, a proposed cost-risk contingency framework has investigated the expected total construction cost in order to consider the additional budgeted cost required to mitigate the risk consequences for particular project activity. The results of cost-risk analysis imply that poor design issues, an increase in material prices and delays in relocating facilities show higher dependency and increase the risk of cost overrun in metropolitan transit projects.

The findings and implication for project managers could possibly be achieved by assuming the proposed cost-risk contingency framework under high uncertainty of cost found in this research. Furthermore, this procedure may be used by experts from other engineering domains by replacing and considering the complex relationship between complexity-risk factors.

This study contributes to the body of knowledge by providing a practical contingency model to identify and evaluate the additional risk cost required to compute total construction cost for getting stability in future budgeting.

The construction industry is greatly plagued by risk; too often, this risk is not dealt with adequately, resulting in poor project performance. Communication of construction project risks in practice is poor, incomplete and inconsistent, both throughout the supply chain and through the project lifecycle. Part of the problem is the lack of a formalized approach to the project risk management process. Recently, attempts have been made to overcome this and this paper uses these attempts as a foundation for building a better approach to construction risk management. Underlying this approach is the development of a common language for describing risks and remedial actions. This is grounded in a taxonomy of risk based on a hierarchical risk breakdown structure. In addition, to facilitate the production of a working risk management system, a number of models have been developed using unified modelling language (UML) and IDEFO. Finally, the use of the system has been tested via a working software prototype. This prototype is being used as a basis for discussion with practitioners with regard to the practical requirements of the approach for further development.

The purpose of this paper is to address the current theoretical gap in integrating knowledge and experience into Building Information Model (BIM) for risk management of bridge projects by developing a tailored Risk Breakdown Structure (RBS) and formalising an active link between the resulting RBS and BIM.

A three-step approach is used in this study to develop a tailored RBS for bridge projects and a conceptual model for the linkage between the RBS and BIM. First, the integrated bridge information model is in concept separated into four levels of contents (LOCs) and six technical systems based on analysis of the Industry Foundation Classes specification, a critical review of previous studies and authors’ project experience. The second step develops a knowledge-based risk database through an extensive collection of risk data, a process of data mining, and further assessment and translation of data. A critical analysis is conducted in the last step to determine on which level the different risks should be allocated to bridge projects and to propose a conceptual model for linking the tailored RBS to the four LOCs and six technical systems of BIM.

The findings suggest that the traditional method and BIM can be merged as an integrated solution for risk management by establishing the linkage between RBS and BIM. This solution can take advantage of both the traditional method and BIM for managing risks. On the one hand, RBS enables risk information to be stored in a formal structure, used and communicated effectively. On the other hand, some features of BIM such as 3D visualisation and 4D construction scheduling can facilitate the risk identification, analysis, and communication at an early project stage.

A limitation is that RBS is a qualitative technique and only plays a limited role in quantitative risk analysis. As a result, when implementing this proposed method, further techniques may be needed for assisting quantitative risk analysis, evaluation, and treatment. Another limitation is that the proposed method has not yet been implemented for validation in practice. Hence, recommendations for future research are to: improve the quantitative risk analysis and treatment capabilities of this proposed solution; develop computer tools to support the solution; integrate the linkage into a traditional workflow; and test this solution in some small and large projects for validation.

Through linking risk information to BIM, project participants could check and review the linked information for identifying potential risks and seeking possible mitigation measures, when project information is being transferred between different people or forwarded to the next phase.

This study contributes to the theoretical development for aligning traditional methods and BIM for risk management, by introducing a new conceptual model for linking RBS to BIM.

Successful risk management is influential in different phases of construction projects. It can play a critical role in reducing the possibility of claims as well as related disputes. The risk management knowledge area in large capital projects such as oil and gas is considered a questionable problem in the construction industry. The present study makes an effort to identify the importance of process groups in improving risk management performance.

This study is selected and ranked 36 factors leading to the claim in Iran's oil and gas industry through the Delphi method and a questionnaire. Factors categorized into a risk breakdown structure (RBS) include eight groups. Factors are linked to one of the process groups by a Delphi method. Finally, the relationship between RBS and the five process groups is analyzed using partial least squares structural equation modeling (PLS-SEM).

Findings showed that the planning process group had more confirmed factors than others. Most of the supported communications belonged to the contractor and the owner parties. Also, the cause of delay in the implementation phase due to the contractor performance had a higher relative importance index.

This article, from a project life-cycle perspective, considers the new structure between the risks leading to claims and the key parties to the project. It can be a good criterion for identifying risks and a timelier response to them before the risks turn into disagreements.

Risk analysis has come to be seen as a quantitative process in which risks are measured by the use of probabilities. However, since every new project is essentially unique with no previous data on it, decisions taken as to the nature of the risks are highly subjective and the actions that may be carried out to mitigate the effects of these risks are not clear‐cut; a non‐numerical approach can, therefore, be more useful. The risk management approach detailed here identifies the risks, checks for dependence amongst risks, and assesses the likelihood of occurrence of each risk by using linguistic variables through the medium of fuzzy sets. The use of linguistic variables is a departure from conventional risk analysis methods that rely rather heavily on statistical analysis to quantify the effects of risks on projects. The entire risk management process is explained, and a case study is carried out to demonstrate the use of the ideas treated. The case study concentrates on the activities of the substructure in a multi‐storey building project. The ten largest risks are identified, and dependence among them is assessed through fuzzy set calculations. The assessment of risk dependencies brings about a reduction in the total number of risks analysed, as highly dependent risks are treated together, and the use of linguistic variables brings about a non‐numeric approach to risk analysis with which project managers can be comfortable. The risk management process, through the use of fuzzy sets, is better able to handle project management knowledge on risk analysis which is highly subjective, and varies from project to project.

According to the Project Management Institute, 70% of projects fail globally. The causes of project failure in many instances can be identified as non-technical or behavioral in nature arising from interactions between participants. These intangible risks can emerge in any project setting but especially in project settings having diversity of cultures, customs, beliefs and traditions of various companies or countries. This paper provides an objective framework to address these intangible risks.

This paper presents a structured approach to identify, assess and manage intangible risks to enhance a project team’s ability to meet its objectives. The authors propose a user-friendly framework, Intangible Risk Assessment Methodology for Projects (IRAMP), to address these risks and the factors that cause them. Meta-network (e.g., a network of networks) simulation and established social network analysis (SNA) measures provide a quantitative assessment and ranking of causal events and their influence on the intangible behavior centric risks.

The proposed IRAMP and meta-network approach were utilized to examine the project delivery process of an international energy firm. Data were gathered using structured interviews, surveys and project team workshops. The use of the IRAMP to highlight intangible risk areas underpinned by the SNA measures led to changes in the company’s organizational structure to enhance project delivery effectiveness.

This work extends the existing project risk management literature by providing a novel objective approach to identify and quantify behavior centric intangible risks and the conditions that cause them to emerge.

The purpose of this paper is to systematically develop a delay risk terminology and taxonomy. This research also explores two external and internal dimensions of the taxonomy to determine how much the taxonomy as a whole or combinations of its elements are generalisable.

Using mixed methods research, this systematic literature review incorporated data from 46 articles to establish delay risk terminology and taxonomy. Qualitative data of the top 10 delay risks identified in each article were coded based on the grounded theory and constant comparative analysis using a three-stage coding approach. Word frequency analysis and cross-tabulation were used to develop the terminology and taxonomy. Association rules within the taxonomy were also explored to define risk paths and to unmask associations among the risks.

In total, 26 delay risks were identified and grouped into ten categories to form the risk breakdown structure. The universal delay risks and other delay risks that are more or less depending on the project location were determined. Also, it is realized that delays connected to equipment, sub-contractors and design drawings are highly connected to project planning, finance and owner slow decision making, respectively.

The established terminology and taxonomy may be used in manual or automated risk management systems as a baseline for delay risk identification, management and communication. In addition, the association rules assist the risk management process by enabling mitigation of a combination of risks together.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.