Dr. saad ahmed al muhannadi 2015 - ph d - dba

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Information about Dr. saad ahmed al muhannadi 2015 - ph d - dba

Published on December 7, 2016

Author: fabdulkhadar

Source: slideshare.net

1. Multi-Criteria Risk-Based Decision-Making (RBDM) Model for a Multi-Billion-Railway Program (MBRP) THESIS SUBMITTED TO PARIS SCHOOL OF BUSINESS, PARIS, FOR THE AWARD OF THE DEGREE OF DOCTOR OF PHILOSOPHY IN BUSINESS ADMINISTRATION (EXECUTIVE DBA) UNDER THE FACULTY OF BUSINESS ADMINISTRATION BY SAAD AHMED AL MUHANNADI UNDER THE GUIDANCE OF PROF. JOSSE ROUSSEL DEAN OF THE EXECUTIVE DBA PROGRAM PARIS SCHOOL OF BUSINESS, PARIS, FRANCE PSB Paris School of Business 59 rue Nationale 75013 Paris, France December, 2015 1 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

2. DECLARATION I hereby declare that the project entitled “Multi-Criteria Risk-Based Decision-Making (RBDM) Model for a Multi-Billion-Railway Program (MBRP)” is an original record of the Executive DBA done by me under the guidance of Prof. Josse Roussel, Dean of the Exec DBA Program in the Paris School of Business, Paris as part of the Executive DBA Program. I also declare that it was not previously submitted for the award of any academic title. Saad Ahmed Al Muhannadi 2 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

3. ACKNOWLEDGMENTS My sincere gratitude extends to beloved teacher Prof. Josse Roussel, Dean of the Executive DBA Program in the Paris School of Business, Paris, who has continuously guided me throughout the entire process of the research with all constructive comments and suggestions to make this research work “Multi- Criteria Risk-Based Decision-Making (RBDM) Model for a Multi-Billion- Railway Program (MBRP)” more perfect and complete. I am grateful to the Qatar Rail and Staffs, in particular the Head of the Departments for being very supportive throughout my research. My beloved Parents, thanks for your unlimited kindness and supplications. "And say, My Lord, Have mercy on both of them as they cared for me when I was little" Holy Quran*. My DBA Dissertation is dedicated to the “State of QATAR” My beloved family, thanks for the patience and love. I always need your love and care for me today, tomorrow, and then. By God willing, I hope you all will be the best generation of our family and shine your future by knowledge and experience. 3 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

4. Multi-Criteria Risk-Based Decision-Making (RBDM) Model for a Multi-Billion-Railway Program (MBRP) This Research is related to the development of an enhanced model for Risk-Based Decision-Making (RBDM) applicable for a Multi-Billion Railway Program (MBRP). As the MBRP is a typical mega-project, consisting of many contractual, physical, and other components, and stakeholder interests, its design, planning and construction have proven to be very risky due to high costs and longtime spans. Historically, many of such projects had enormous cost overruns and schedule slippages, and thus avoidance of these risks through a well-established process for making decisions is a specific challenge for my DBA research. The RBDM will employ a Multi-Criteria (MC) approach, based on probability of occurrence and consequences of each potential risk during design, planning and construction activities, with both internal and external impacts taken into account. The RBDM model applicable for MBRPs will be validated on a current schedule- driven MBRP in Qatar and compared to other available models. The construction works for a MBRP are ranked high on the potential risk scale, particularly those carried out for the underground structures for railway and metro lines, where many uncertainties (geological and others) are met and need to be defined quantitatively by various approaches. The proposed model will be used to evaluate and select the most suitable risk treatment options for meeting the project schedule without jeopardizing the other criteria. 4 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

5. TABLE OF CONTENTS I. AN OVERVIEW OF THE RESEARCH 01 II. POSITIONING OF THE RESEARCH PROGRAM 07 II.1. Research Objectives 07 II.2. Research Questions 08 II.3. Research Hypotheses 09 II.4. Expected Contribution 09 III. LITERATURE REVIEW 11 III.1. Risk-Based Decision-Making Process 11 III.2. Multi-Criteria Decision-Making 17 III.3. Allocation of Risks 22 III.4. Risk Management 26 III.5. Risk Assessment Tools 29 III.6. Decision-Making Models 34 III.7. Applicability of the Existing Models 37 III.8. Requirements for a new RBDM for MBRPs 44 III.8.1. Qualitative risk analysis 44 III.8.2. Quantitative analysis of uncertainty and risk 45 IV. RESEARCH DESIGN AND METHODOLOGY 49 5 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

6. IV.1. Research Design 49 IV.2. Methodology to be Applied 50 IV.3. Input Data 53 IV.4. RBDM Processes 55 IV.5. Output 65 IV.6. Validation of the RBDM Model 66 IV.7. Data Collection 66 IV.8. Conclusion 67 V. ANALYSIS OF RISK DATA – A MULTIPLE CRITERIA MODEL 69 V.1. Step 1. Qualitative deterministic analysis 69 V.2. Step 2 – Decision-making: Phase I 71 V.3. Step 3 – Quantitative deterministic risk analysis 74 V.4. Step 4 – Quantitative probabilistic risk analysis 76 V.5. Step 5 – Risk treatment options (Decision making: Phase II) 80 V.6 Step 6 – Risk treatment options (Decision making: Phase III) 82 V.7 Suggested risk management approach 87 V.8 General Conclusion of the study – summary of the major findings and data collection methodology 87 V.9 Scope of further exploration 88 VI. REFERENCES 89 VII. QUESTIONNAIRE 110 VII1. INTERVIEW SCHEDULE 114 6 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

7. LIST OF FIGURES Figure 1: Impacts related to schedule of a mega-project 04 Figure 2: The five steps of the risk-based decision making process 11 Figure 3: Risk management process according to ISO 31000:2009 15 Figure 4: General process of risk management 17 Figure 5: Risk management model 28 Figure 6 Risk based decision-making framework for a multi-billion-railway program 52 Figure 7: Risk Data Population 54 Figure 8: Decision tree for the evaluation of risk treatment options 65 Figure 9: Risk Factors and their relative significance 86 7 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

8. LIST OF TABLES Table 1: Selected types of contracts and risk sharing 23 Table 2: The contractor’s risk for two types of contract 24 Table 3: The risk matrix 45 Table 4 Risk Treatment Description per Level 62 Table 5: Risk Treatment Options 63 Table 6: Summary of Qualitative Deterministic Analysis of Risk 70 Table 7: Summary of Qualitative Deterministic Analysis of Risk 72 Table 8: Criteria for Prioritizing the Risk Factors 74 Table 9: Quantitative Deterministic Analysis of Risk Prioritizing the Risk Factors 75 Table 10: Quantification of Risks and Finding the Risk Degrees 77 Table 11: Risk Treatment Description per Level 79 Table 12: Risk Treatment Options 81 Table 13: Prioritized risk factors 82 Table 14: Prioritized risk factors 84 8 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

9. I. AN OVERVIEW OF THE RESEARCH The management of large-scale investment projects is extremely risky and challenging. One of the key success drivers of such (mega) projects is a proper risk management strategy, whereby effective measures can be taken early enough to mitigate any negative impact on schedule, cost or quality. This Research deals with the application of the Risk-Based Decision-Making (RBDM) approach used to prevent schedule slippage and cost overruns on mega-projects. According to the RBDM Guidelines (USCG, 2013), the RBDM “is a process that organizes information about the possibility for one or more unwanted outcomes to occur into a broad, orderly structure that helps decision makers make more informed management choices”. It is well established that such a process, based on adequate models can drastically improve the decision-making process. However, applying the existing models to large (mega) projects, such as a Multi-Billion Railway Program (MBRP) in Qatar, introduces new challenges that should be addressed by developing new methods of approach and fine- tuned large-scale RBDM models. Because of their large scale and long time-frames, mega-projects are inherently risky, carrying their own unique risk potential. Risk management and risk-based decision- making are presently becoming more and more important. However, as many more and 9 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

10. much larger mega-projects are being proposed and built around the world, it is becoming clear that such (mega)projects have strikingly poor performance records in terms of economy, environment and public support (Haimes, 2007). Due to complexity and lack of information on the MBRPs, particularly on the construction of their underground structures, there are many challenging aspects to be addressed during the design, planning and construction works, including their interaction with all other “work packages” thus affecting the overall cost and schedule of a MBRP. There are also different stakeholder interests in place that can impact the risks to a great extent. For example, the MBRP in Qatar and many other multi-billion programs worldwide are sponsored by the governments and play an important strategic and political role to the states. Hence, the multi-billion programs involve many stakeholders with different and changing requirements, while their acceptability threshold for timely delivery of the projects cannot be negotiated. However, the existing RBDM models are not suitable to address complex MBRP schedule problem, the RBDM approach to mega- projects introduces new methodological challenges in managing risks in order to enable such risks to be either reduced, or eluded, transferred from one place to another, or diversified and allocated to the parties best able to handle them. To develop a RBDM model suitable for a MBRP, relevant studies will need to be conducted first in order to investigate which elements of the existing models may be appropriate for the development of an enhanced model specific for a MBRP and thus meet the main objective of my research project. As a rule, there is very little or no reliability of the overall experience from the past projects, so that each particular project requires a tailored approach. Therefore, for 10 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

11. testing the model to be developed, the case of Doha Metro construction in of Qatar will be used. For that purpose, both, quantitative and qualitative (mixed) methods will be used for analyzing the risk data collected both through my field work and through the search of academic literature and other sources. Following the stakeholders preference, priority is given to the overall project schedule criterion, but without compromising cost and other criteria. The schedule slippage of the underground works due to many uncertainties in place can be transferred to the other “work packages”, of a MBRP. In early phase of planning of any mega-project, several alternatives are commonly considered. These alternatives can include different layouts of the infrastructure, different combinations of tunnel and bridges or different construction technologies. The early design phase and the decisions taken at that time have the decisive role on the cost of the MBRPs and mega-projects in general. The optimal solution is commonly selected based on a cost benefit analysis, which appraise costs and benefits expected during the project life (Lee Jr., 2000; HM Treasury, 2003; Flanagan and Jewell, 2005; Nishijima, 2009). For including the non-monetary factors such as traffic safety and social or environmental impacts into the decision-making, the multi-criteria analysis (MCA) can be utilized, which includes the economic efficiency as one of the criteria (Morisugi, 2000; Vickerman, 2000). One of the most important factors influencing the decision whether and how a MBRP is to be built is the estimated time and costs of construction (Reilly, 2000). Realistic estimate of construction time is equally important. The construction time significantly influences the construction costs, because substantial part of the costs comprises of the labor and machinery costs, which are time dependent. Additionally, the 11 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

12. construction often requires restrictions in operation of existing infrastructure and therefore causes secondary costs and is negatively perceived by pubic. Delays of opening of a MBRP operation are in general economically and politically problematic. However, to manage the construction schedule of a mega-project is extremely difficult. From the complexity of a mega-project presented in Figure 1 as presented by Smith (1998), it is clear that too many (direct and indirect) impacts must be taken into account to be able to estimate the schedule slippage, for example. Figure 1: Impacts related to schedule of a mega-project 12 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

13. The evaluation of uncertainties is crucial information for making decisions. Knowing them, the decision maker can decide whether the uncertainty is acceptable, whether some measures to reduce the uncertainty must be taken or whether to select another option. The need of probabilistic prediction of construction time and costs and their communication with the stakeholders has gradually been recognized and the demand for applicable probabilistic models is apparent. There are only few methods and models for quantification of uncertainty in construction time and cost prediction for infrastructure in general (Flyvbjerg, 2006), or for tunnels in particular, e.g. the Decision Aids for Tunneling (DAT) developed at MIT (Einstein, 1996), an analytical model presented by Isaksson and Stille (2005) or a model combining Bayesian networks and Monte Carlo simulation proposed by Steiger (2009). Probabilistic models have not been widely accepted in the practice so far. A first reason is that there was not real demand for the quantitative modeling of uncertainties and risk, because decision makers were not used to work with such information. A second reason is that the existing models often did not provide a realistic estimate of the uncertainties and they therefore did not gain acceptance among the practitioners. However, this situation seems to be changing in the recent years and both the demand and the reliability of the model results have increased. For reliable predictions, it is essential to realistically estimate the parameters of the probabilistic model. At present, such estimates mostly rely on expert judgment. However, these can be strongly biased and unreliable. Therefore, the expert estimates should be supported by analysis of data from previous projects. Špačkova (2012) introduces an advanced Dynamic Bayesian Networks (DBNs) model which takes over some modeling 13 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

14. procedures from existing models and extends the scope of the modeled uncertainties and aims at developing models for quantification of uncertainties in the construction process of a linear infrastructure such as rail or roads. In focus of my research is a schedule-driven mega-project, MBRP in Qatar. This Research is related to the development of an enhanced RBDM model applicable for selection of the most suitable risk treatment option(s) for meeting the schedule of a MBRP without jeopardizing the other criteria of the program. As the MBRPs, as well as any other typical mega-project, encompass many contractual, physical, and other components, and stakeholder interests, their design, planning and construction have proven to be very risky due to high costs and longtime spans. Historically, many of such projects had enormous cost overruns and schedule slippages, and thus avoidance of these risks through a well-established process for making decisions is a specific challenge for my DBA research. The proposed research is based on a combination of empirical data and literature review, leading to the development of an analytical (quantitative) framework, followed by a case-study survey. Relevant literature and data are for this research are proposed to be collected authentic sources, like Government publications are reports, including online sources like EBSCO, JSTOR and such other academic databases. The research process of building a new RBDM model applicable to the MBRPs will be, based on my previous and current experience in MBRP management. I will continue to investigate the relevant RBDM models applicable in the current MBRP. Next, based on my review of the existing decision-making models, especially by taking reference from 14 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

15. several RBDM models and by combining them, the new RBDM model, applicable for a MBRP will be built. In the meantime, I will collect the internal and external risk data to validate the model. II. POSITIONING OF THE RESEARCH PROGRAM II.1 Research Objectives The objective of this research is to provide tools for the analysis of MBRP construction uncertainties and risks. The particular aims are to exploit the RBDM methodology to arrive at the models that are the best suited for mega-projects. For the above purpose, relevant studies will be conducted to enhance the existing RBDM models or to develop new ones, with the mandated objective of this project viz. addressing the question of selecting the most suitable risk treatment options; for the particular case of meeting the schedule of a MBRP without jeopardizing the other criteria of the program. The major objectives of this research are as follows: 1. Investigate in detail the existing RBDM models and use them to develop an enhanced model for risk management of a schedule-driven MBRP. 2. Using the proposed RBDM model, evaluate and select the most suitable risk treatment options for meeting the schedule of a MBRP without jeopardizing the other criteria of the program. 15 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

16. 3. Assess the validity of the proposed model by using the Qatar Rail implementation project as a case study. This research aims at developing models for quantification of uncertainties in the construction process of a MBRP. Specifically, the models are to be developed for probabilistic assessment of the construction time. However, probabilistic models have not been widely accepted in practice so far because the existing models often did not provide a realistic estimate of the uncertainties and they therefore did not gain acceptance among the practitioners. But, this situation is changing in the recent years and both the demand and the reliability of the model results have increased. However, only a few methods and models can be used for quantification of uncertainty in construction time and cost prediction for MBRPs (Flyvbjerg, 2006), or for their components such as tunnels in particular, for which an analytical model was developed by Isaksson and Stille (2005) or a model combining Bayesian networks and Monte Carlo simulation proposed by Steiger (2009) and recently a Dynamic Bayesian network (DBN) model of tunnel construction process developed by Špačkova (2012). II.2. Research Questions. The main research question is as follows: “How to select the most suitable risk treatment options for meeting the schedule of a MBRP without jeopardizing the other criteria of the program?” In order to answer the main question, the following sub-questions, which are linked to the research objectives, should be addressed first:  Research sub-questions linked to the objective #1: 1. What are the risks, which may prevent or deter the timely completion of a MBRP? 16 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

17. 2. Which of the existing RBDM models may be risk-specific for a MBRP? 3. What are the limitations of the existing RBDM models when used for a MBRP, and what could be the possible solutions to overcome these limitations? 4. Which benefits of the existing RBDM models can be used to design a new enhanced RBDM model for a MBRP?  Research sub-questions linked to the objective #2: 5. How should the schedule-specific risks be valuated within particular risk treatment options? 6. How should the proposed RBDM model be used to select the most suitable (optimal) risk treatment option for meeting the schedule of a MBRP?  Research sub-questions linked to the objective #3: 7. Which all data collection mechanisms and validation techniques should be used while going for validation of the proposed RBDM model for a MBRP? 8. How should the validity of the proposed model for a MBRP be assessed? II.3. Research Hypotheses The proposed RBDM model will be based on three hypotheses. Hypothesis 1: The optimal risk treatment option provided by the developed model can minimize the risks associated with the MBRP measures in terms of the variance from the scheduled figures and actual figures collected through a case study of MBRP. Hypothesis 2: The optimal risk treatment option provided by the developed model in respect of “meet the schedule” criterion will not have significant adverse impact as regards the optimal results based on other criteria. 17 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

18. Hypothesis 3: The proposed RBDM model can be validated when applied in practice through a case study on the current MBRP in Qatar. II.4. Expected Contribution The main scientific contribution which is expected from this research project will be an enhanced RBDM model and computer tool applicable to schedule-driven mega- projects such as the MBRP in Qatar for selection of the most suitable risk treatment option(s) for meeting the required project be schedule without jeopardizing the other criteria. The RBDM will employ a Multi-Criteria (MC) approach, based on the probability of occurrence and consequences of each potential risk during design, planning and construction activities, with both internal and external impacts taken into account. The RBDM model applicable for MBRPs will be validated on a current MBRP in Qatar, which is believed to suitable to serve as a realistic criterion to validate the model, given that the main stakeholders, including the owner, the general design contractor, the strategic program management contractor, and the construction contractors, are highly project schedule driven and are ready to adopt RBDM techniques. Although the model will be designed to be project-agnostic, the case study will both demonstrate the accuracy and effectiveness of the proposed methodology and help in fine-tuning the model steps with an aim make it applicable for other mega-projects. The validation of the performance of the proposed model will also identify its limitations, which could then open the door for future improvements. A comprehensive comparison with the existing models will be also included. 18 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

19. III. LITERATURE REVIEW This section is a review of the literature relevant to the research area under study. Accordingly, it starts with the literature related to risk-based decision making process, various models that are used for decision making by ensuring optimal levels of various risks involved, process of risk management including the step-by-step procedure involved, the relevant ISO standards applicable in project management setting etc. are discussed in this section. III.1. Risk-Based Decision-Making Process The risk-based decision making (RBDM) process is composed of five major steps, as shown in the Figure 2, adapted from Mayers et al (2002). 19 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

20. Figure 2: The five steps of the risk-based decision making process As a good guidance through my future research, these steps are briefly outlined below: Step 1— Establish the decision structure Understanding and defining the decision that must be made is critical. This first component of risk-based decision making is often overlooked and deserves more discussion. The following steps must be performed to accomplish this critical component: Step 1a — Define the decision. Specifically describe what decision(s) must be made. Major category ies of decisions include (1) accepting or rejecting a proposed facility or operation, (2) determining who and what to inspect, and (3) determining how to best improve a facility or operation. Step 1b — Determine who needs to be involved in the decision. Identify and solicit involvement from key stakeholders who (1) should be involved in making the decision or (2) will be affected by actions resulting from the decision-making process. 20 Source: Mayers et al (2002) Step 5 Step 1 Step 3Step 2 Step 4 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

21. Step 1c — Identify the options available to the decision maker. Describe the choices available to the decision maker. This will help focus efforts only on issues likely to influence the choice among credible alternatives. Step 1d — Identify the factors that will influence the decisions (including risk factors). Few decisions are based on only one factor. Most require consideration of many factors, including costs, schedules, risks, etc., at the same time. The stakeholders must identify the relevant decision factors. Step 1e — Gather information about the factors that influence stakeholders. Perform specific analyses to measure against the decision factors. Some common decision analysis tools could help to structure the overall decision-making process. Step 2 — Perform the risk assessment The risk assessment is the process of understanding (1) What bad things can happen, (2) How likely they are to happen and (3) How severe the effects may be. The key to risk assessment is choosing the right approach to provide the needed information without overworking the problem. The following steps must be performed to assess risk: Step 2a — Establish the risk-related questions that need answers. Decide what questions, if answered, would provide the risk insights needed by the decision maker. Step 2b — Determine the risk-related information needed to answer the questions posed in the previous step. For each information specify (1) Information type needed, (2) Precision required, (3) Certainty required and (4) Analysis resources (staff-hours, costs, etc.) available Step 2c — Select the risk analysis tool(s). Select the risk analysis tool(s) that will most efficiently develop the required risk-related information. 21 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

22. Step 2d — Establish the scope for the analysis tool(s). Set any appropriate physical or analytical boundaries for the analysis. Step 2e — Generate risk-based information using the analysis tool(s). Apply the selected risk analysis tool(s). This may require the use of more than one analysis tool and may involve some iterative analysis (i.e., starting with a general, low-detail analysis and progressing toward a more specific, high-detail analysis). Step 3 — Apply the results to risk management decision making To reduce a risk, actions must be taken to manage it in a way to provide more benefit than they cost. They must also be acceptable to stakeholders and not cause other significant risks. The following steps must be performed to manage risk: Step 3a — Assess the possible risk management options. Determine how the risks can be managed most effectively. This decision can include (1) accepting/rejecting the risk or (2) finding specific ways to reduce the risk. Step 3b — Use risk-based information in decision making. Use the risk-related information within the overall decision framework to make an informed, rational decision. This final decision-making step often involves significant communication with a broad set of stakeholders. Step 4 — Monitor effectiveness through impact assessment Impact assessment is the process of tracking the effectiveness of actions taken to manage risk. The goal is to verify that the organization is getting the expected results from its risk management decisions. If not, a new decision-making process must be considered. Step 5 — Facilitate risk communication 22 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

23. Risk communication is a two-way process that must take place during risk-based decision making. At every step in the process, encourage stakeholders to identify the issues of importance to them and present their views on how each step of the process should be performed. Stakeholders should agree on the work to be done in each phase of the risk-based decision-making process. They can then support the ultimate decisions The above is in line with the standardized risk management process according to ISO 31000:2009 (2009), Figure 3. The first, essential step of the process is establishing of the context, which consists of (1) defining scope and aims of the risk management process, (2) describing criteria of success and (3) explaining the constraints and limitations, all based on the stakeholders’ objectives. The risk assessment contains three steps: First, phenomena and events, which might influence the stakeholders’ objectives in either positive or negative way, are identified (risk identification). Second, the causes and likelihood of the events and their impacts are analyzed on a qualitative or quantitative basis (risk analysis). Third, the results of the risk analysis are compared with the acceptance criteria and with the objectives and decisions are made how to treat the risks (risk evaluation). 23 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

24. Figure 3: Risk management process according to ISO 31000:2009 For risk treatment, four general strategies (also known as “4Ts of risk response”, Špačkova, 2012) can be applied: Tolerate the risk if the risk is acceptable, Treat the risk (take measures to decrease the risk), Transfer the risk to another stakeholder or insurance company or Terminate the activity or project, if the risk is unacceptable and other strategies are not applicable. The implementation of the selected risk management strategy must be properly controlled. At each stage of the process, the findings must be properly communicated with the stakeholders. The findings and decisions should be repeatedly revised whenever some new information is available or when the conditions change. Many decisions must be made regarding design, project financing and type of contract. These decisions are made under high uncertainty, such as uncertainty in construction cost, time of completion, impact on third party property or maintenance costs. Assessment of these uncertainties is crucial for making the right decisions. Often, 24 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

25. the solutions that seem to be cheaper and faster based on deterministic estimates are associated with higher uncertainties and risks. Making decisions based on deterministic values is therefore insufficient. The construction process is affected by different types of uncertainties. It is therefore important to distinguish between the common variability of the construction process and the uncertainty on occurrence of extraordinary events, such as failures of the construction process Application of risk management in mega-projects has particularly been motivated by increasing complexity of the construction projects and by pressure for cost savings and for construction time reduction. Identification of risks in early design phase allows significant reduction of life-cycle costs through improvements of the design and planning and through appropriate treatment of the risk in the later phases. Some manuals have been developed specifically for the underground construction and tunneling projects (Clayton, 2001; Eskesen et al., 2004; Staveren, 2006). In these manuals, a special attention is paid to the geotechnical risks, which play a crucial role in the underground construction (Špačkova, 2012). The risk management system for the Gotthard Base Tunnel (GBT) has been discussed by Lieb and Erhbar (2011). The overall risk management process applied to this mega-project is presented in Figure 4. 25 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

26. Figure 4: General process of risk management III.2. Multi-Criteria Decision-Making Decision making about mega-projects should normally include identifying objectives and possible options for achieving the objectives, as well as the criteria to be used to compare the options. Then follow analysis of the options, making choices, and finally feedback. The actual outcome of each of the individual decisions at each stage is not known with certainty. An ever-increasing complexity of mega-projects such as MBRPs offers new and exciting scientific and technological challenges. Sen and Yang (1998) 26 Source: Lieb and Erhbar (2011) ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

27. examine some of the underlying issues on multi-criteria decisions and related modeling strategies, with a view to exploring a generalized multiple-criteria approach to the decision-making in mega-projects. Multi-Criteria Decision Analysis (MCDA) methods are used to reduce complex problems in selection of a preferred alternative. However, Linkov and Steevens (2008) claim that these methods do not necessarily weight the relative importance of criteria and combine the criteria to produce an aggregate score for each alternative. Major transportation projects require huge physical and financial resources and are usually funded by government or public private partnerships. In the conventional approach to project development, government is the project promoter and financier, and private firms, who actually conduct the project, are intended to do the best-case feasibility studies, produce the designs, and earn additional profits by numerous change orders later on. It is going to be harder and harder to get public and political support for mega-projects unless they come up with better-performing delivery models. Another critical approach is to incorporate risk analysis into early project development stage, such as feasibility studies. Therefore, management of large scale projects presents a special challenge for executive politics and of government more widely. Jennings (2012) claims that, by assessing the role of executive politics in the adoption and management of mega-projects, it is possible to undertake comparative analysis of sources of their under-performance in relation to the role of high politics and institutions, executive politics and the consequences of the design of project financing and administration (such as in the balance of risk between the public and private sectors), as well as biases in decision-making about project risks, and uncertainties that can impact upon technical 27 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

28. and economic issues of mega-projects. Priemus (2010) claims that “many of the notorious interim rises in the costs of mega-projects are the result of fresh insight by political bodies who change the scope of the project along the way to make it fit more neatly into the spatial planning and to protect the environment against noise and air pollution, blots on the landscape and other negative effects” and concludes that “missed deadlines and deteriorations in cost-benefit ratios are often the result of changing political views or of a perceived need for political compromises”. However, Nijkamp, P. (2008) argues that “it is not so easy to draw transparent and unambiguous conclusions from these various findings, but in general it seems plausible that uncritical beliefs in mega-projects increase the probability of disappointments in a later stage”. Evidently, all of the direct or indirect participants tend to maintain different interests in the same project, making it extremely difficult to properly align them for project success. In the pursuit of successful project performance, time control is one of the most important functions, especially in megaprojects where various risk variables cause schedule delays. Schedule delays have been a source of great distress to both owner and contractor mainly because time overruns are directly or indirectly connected with cost overruns (Flyvberg et al. 2003). If a mega project is delayed, claims are often filed between owner and contractors. In certain cases, the claims among contracting parties escalates into severe disputes. For this reason, the analysis of schedule delays in mega projects has received continuous interests from both researchers and practitioners. It is very important to make distinction between the cases whether a single or multiple criteria are to be employed. A decision problem may have a single criterion or a single aggregate measure like cost. Then the decision can be made implicitly by 28 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

29. determining the alternative with the best value of the single criterion or aggregate measure. The case with a finite number of criteria and infinite number of feasible alternatives meeting the requirements belongs to the field of multiple criteria optimization. Also, techniques of multiple criteria optimization can be used when the number of feasible alternatives is finite but they are given only in implicit form (Steuer, R. E. 1986). The decision-making problems when the number of the criteria and alternatives is finite, and the alternatives are given explicitly, are called multi-attribute decision making (MADM) problems Franco and Montibeller (2009) note that "it is surprising that much of the MCDA literature has paid relatively minor consideration to the processes of articulating and defining a multi-criteria problem". In many multi-criteria models, particularly so in multi- attribute utility/value models, the objectives are organized as a value tree, which decomposes the overall objective of an evaluation into operational objectives for a more easy assessment of decision alternatives. They also claim that “the process of creating, evaluating and implementing strategic decisions is typically characterized by the consideration of high levels of uncertainty“. Xu (2012) suggests implementation of the Evidential Reasoning (ER) approach to be generally applied for MCDA when analyzing multiple criteria decision making (MCDM) problems under uncertainties. Keeney (1996) cautions, however, against over-emphasis on alternative focused thinking, distinguishing this from value focused thinking. Liu et al. (2011) proposed a risk multi-attribute decision- making (risk MADM) method based on prospect theory for risk decision making problems with interval probability in which the attribute values take the form of the uncertain variables. 29 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

30. Multi-attribute decision making techniques can partially or completely rank the alternatives: a single most preferred alternative can be identified or a short list of a limited number of alternatives can be selected for subsequent detailed appraisal. This theory allows complete compensation between criteria, when the gain on one criterion can compensate the lost on another (Keeney and Raiffa 1976). After having determined for each pair of alternatives whether one alternative outranks another, these pairwise outranking assessments can be combined into a partial or complete ranking. In most of the approaches based on the Multi-attribute Utility Theory (MAUT), the weights associated with the criteria can properly reflect the relative importance of the criteria only if the scores aij are from a common, dimensionless scale. The basis of MAUT is the use of utility functions. Utility functions can be applied to transform the raw performance values of the alternatives against diverse criteria, both factual (objective, quantitative) and judgmental (subjective, qualitative), to a common, dimensionless scale. In practice, intervals [0,1] or [0,100] are used for this purpose. Besides the above simple additive model, Edwards (1977) also proposed a simple method to assess weights for each of the criteria to reflect its relative importance to the decision. First, the criteria are ranked in order of importance and 10 points are assigned to the least important criterion. Then, the next-least-important criterion is chosen, more points are assigned to it, and so on, to reflect their relative importance. The final weights are obtained by normalizing the sum of the points to one. However, as Edwards and Barron (1994) pointed out, the comparison of the importance of attributes is meaningless if it does not reflect the range of the values of the alternatives as well. They proposed a variant that in the course of the comparison of the importance of the criteria also 30 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

31. considers the changes from the worst utility value level to the best level among the alternatives. In view of the foregoing it may be summarized that MDCA offers a meaningful approach towards taking holistic and integrative project management decisions that considers multifarious individual decisions, but at the same time ensures proper coordination between all such decisions so that optimal performance of the project as a whole. An integrative approach to treatment of risks of all sorts is adopted here for so that optimal performance is ensured throughout the project management cycle. III.3. Allocation of Risks Due to the various natures of risks which may be encountered in a major construction project and the differing weights which may attach to their consequences (and the differing ‘treatments’ which they may entail), it is not uncommon to break the risks down into commercial (business or project prerequisite and sustainability) risks, construction (and/or operational) risks and third-party (act of God/government). However, one of the dangers of adopting such an approach is that it can tend to reinforce an assumed allocation of risk dependent upon the project delivery method being proposed and the respective interests of the various stakeholders. Table 1 shows how the risk is shared between the employer (also called: client, principal, owner) and the contractor, depending upon the type of contract, as adapted from Flanagan and Norman (1993). 31 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

32. Table 1: Selected types of contracts and risk sharing By way of example, a contractor assessing the risks involved in bidding on a straightforward ‘construct only’ commercial office tower project may assume that so- called ‘project risks’, such as the availability of requisite planning approvals or the principal’s financing, the impact of latent conditions, risks of delay and so on. While contractors, principals and financiers will, however, each attach varying levels of importance to various risks, a consideration of the totality of risks which may be encountered is essential in order to determine their impact and ‘knock on’ effect (Ritchie, 2007). The context in which the contractor undertakes a risk assessment at the tender phase is in accordance with corporate limits documented, for example in tendering guidelines which may also detail limits of liability for key commercial risks. The contracts will then be considered against a number of criteria, such as financial and funding risks, construction performance risks and design risks. The issues for consideration under the financial and funding risks include payment risk and may also extend to issues such as maintaining positive cash flow through the life of the project; payment for on- and off-site materials; and the possible impact of security of payment legislation. Construction 32 Source: Špačkova (2012) ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

33. performance risks, on the other hand, relate to the willingness or otherwise of the contracting party to accept general damages and consequential damages; liquidated damages; the provision of parent company guarantees; the requirement for operating company performance guarantees; guarantees for long-term performance of materials or equipment; and industrial relations risk. Table 2: The contractor’s risk for two types of contract Design and construct building contracts Joint mining and civil construction contracts Delay in award of tender/access to site Mining lease Site conditions Purchase of fleet Design responsibility Interface risk Ambiguities in documentation Wall design Extensions of time Scope of works/fit for purpose Interface risk, fit-out works Cultural heritage Adapted from Ritchie (2007) There are many types of contracts made for mega-projects, such as “Turn-key”, “Split packages”, “Cost plus”, “Build-Operate-and –Transfer” (BOT) etc., each with their contract-specific risk management approach. It will therefore be necessary for modeling purpose to take into account specific features of risks attributed to each type of contract. A contractor assessing the risks involved in bidding on a straightforward ‘construct only’ project may assume that so-called ‘project risks’, such as the availability of requisite planning approvals or the principal’s financing, are matters solely the concern of the principal and, accordingly, focus on so-called ‘construction risks’, such as the impact of latent conditions, risks of delay and so on. While contractors, principals and financiers will, however, each attach varying levels of importance to various risks, a consideration 33 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

34. of the totality of risks which may be encountered is essential in order to determine their impact and ‘knock on’ effect (Ritchie, 2007) Collaborative contracting models have been studied by Cordi et al (2012) on an example of three railway project cases. Such a partnering practice is considered to be a learning process as the mutual experience increases. However, when complexity increases more sophisticated management becomes inevitable, calling also for integration with core project processes, but partnering tools and systems do not seem to provide much guidance. To be successful, a project must meet financial, technical and safety requirements and it must fulfill a time schedule. The criteria of project success from the point of view of different stakeholders can be contradicting and finding an optimal solution is a challenging task. Many decisions must be made regarding design, project financing and type of contract. These decisions are made under high uncertainty, such as uncertainty in construction cost, time of completion, impact on third party property or maintenance costs. Assessment of these uncertainties is crucial for making the right decisions. The stakeholders consider every risk which they identify as being relevant to the project as a whole, and thereafter seek to categorize those risks by the manner in which they are proposed to be ‘treated’, rather than seeking to ‘fit’ risks into general categories or seek to allocate them at the outset to the respective stakeholders as matters of concern only for the other project participants. Instead of simply pricing for risks, there are other opportunities for mitigating risks either by their elimination, retention, reduction or transference. Often these mitigation strategies, particularly risk transference, are given effect contractually via the use of such means as contractual exclusions, limitations of 34 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

35. liability, indemnity clauses, risk transference, guarantees, performance bonds and insertion of a risk premium.(Mead, 2006.,Mead et.al, 2007.) Often, the solutions that seem to be cheaper and faster based on deterministic estimates are associated with higher uncertainties and risks. Making decisions based on deterministic values is therefore insufficient (Spackova,Olga., 2012).All phases of a MBRP construction are influenced by numerous uncertainties that can be categorized in two groups: usual uncertainties in the course of design, construction and operation and occurrence of extraordinary events (failures) causing significant unplanned changes of the expected project development. Distinguishing between the two types of uncertainties is necessary, because the principal divergence of their nature requires different approaches to their analysis. It is further evident that the usual uncertainties influence the occurrence of extraordinary events, (Špačkova, 2012). These dependences must therefore be considered in the quantitative risk analysis. III.4. Risk Management The mega-projects such as multi-billion railway programs (MBRPs) are multifunctional, enormous in size, lengthy in life time, expensive and highly uncertain. This makes the management of such projects extremely risky and challenging. Therefore, one of the key success drivers of mega-projects is a proper risk management strategy whereby effective measures can be taken early enough to mitigate any bad impact on cost, schedule, or quality. Sen and Yang (1998) claim that "The risk-based decision-making (RBDM) can improve the decision-making process". However, applying them on mega- projects, such as MBRPs, introduces new methodological challenges that should be addressed. 35 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

36. For that purpose, an integrated methodology is needed to establish the interrelationship between schedule and cost risk factors in risk-and capital-intensive mega-projects, as well as to develop strategies, allocate capital resources, as well as to manage the risks, and analyze critical decisions. Analyzing the uncertainties and risk is crucial for identifying optimal solutions in all phases of a project, and categorization of uncertainties influencing the project is important for their proper analysis and modeling. However, the transfer of experiences between different projects is not a straightforward task and it cannot be easily automated. At present, the deterministic estimates are used in the majority of cases. However, the construction community recently recognized the limitations of the deterministic approach and more attempts are made to quantify the uncertainties and risks. The foundation of a risk management system is essential to evaluate risk mitigation efforts, set priorities for risk monitoring, and create a contingency planning procedure. Such an approach includes understanding the full complexity, resource requirements, long time horizons, and exposure to interrelated and pervasive drivers of risk in order to enable managers to better anticipate and manage the risks of their mega-projects and lock in the full value of their investments. The interests of many shareholders in megaprojects are typically very strong, which is easy to understand given the enormous sums of money at stake, the many jobs, the national prestige, etc. Therefore, the approach to risk management of mega-projects is differentiated from management of smaller projects by an emphasis on those decisions and commitments that have the greatest risk exposure and therefore requires a comprehensive identification and 36 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

37. rigorous quantification of the uncertainties that represent the biggest threats to on-time and on-budget project delivery, Figure 5. Figure 5: Risk management model An effective risk management requires a detailed understanding of how the risks relate to one another; how they will respond to different management approaches; and how much time, effort, and money will need to be invested before a meaningful impact on the risk is achieved. Andy Jordan (2013) argues that the first step is to understand how each individual risk interacts with others—the relationships between risks: “A change in one risk can have a wide-ranging effect elsewhere in the organization and understanding the relationships is a vital part of an organizational risk management process”. He claims that there are two types of relationship between risks that need to be 37 Source: Westney (2007) ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

38. considered: Risk-driven relationships and Action-driven relationships. In the Risk-driven relationships the risk itself is driving associated risks, so as one risk changes its profile, it drives change in associated risks. In case of Action-driven relationships the actions are taken to control the risk drive changes to related risks. This requires a compromise in risk control activities. Of course, both situations may exist for the same risk. He concludes that “the risks that have the most risk-driven relationships are often the most serious.” Therefore, the only way that decisions can be made with any degree of confidence is with a solid understanding of these relationships between the risks. In recent years the risk based decision-making (RBDM) need has increased concurrently with new and unprecedented mega-project development (Bruzelius et al., 2002; Priemus et al., 2008). The success parameters for any mega-project are in time completion within a specific budget, which meets the required technical performance (Dey, 2002), the so- called golden or iron triangle of project management (Polydoropoulou et al., 2009). III.5. Risk Assessment Tools An overview of commonly used risk assessment tools was presented by Mayers, J (2002): Among the many risk assessment tools he included Pareto analysis, Checklist analysis, Relative ranking/risk indexing, Preliminary risk analysis (PrRA), Change analysis, What-if analysis,. Failure modes and effects analysis (FMEA), Hazard and operability (HAZOP) analysis, Fault tree analysis (FTA), Event tree analysis (ETA), Event and causal factor charting, and Preliminary hazard analysis (PrHA). However, all of these exhibit certain limitations, particularly if applied to mega-projects, such as MBRPs. 38 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

39. Pareto analysis is a ranking technique based only on past data that identifies the most important items among many. This technique uses the 80-20 rule, which states that about 80 percent of the problems are produced by about 20 percent of the causes. It can be used for any type of system, process, or activity as long as enough historical data are available. Usually used to find the most important risk contributors so that more detailed risk assessments can be performed later. Pareto analysis, however, has several limitations. It focuses only on the past and offers a valuable look at key contributors to past problems, but the exclusive reliance on historical data can be misleading. Because the data under-represent events that have not happened yet or have occurred rarely, this can skew decisions and resource allocations, especially when a relatively small total number of problems has occurred. Also, recent changes may invalidate historical trends, or at least reduce their accuracy. Checklist analysis is an evaluation against existing guidelines in the form of one or more risk checklists. It is useful for any type of system, process, or activity, especially when, suitable checklists exist. Checklist analysis, however, is likely to overlook potentially important weaknesses. Also, most checklist reviews produce only qualitative results, with no quantitative estimates of risk-related characteristics. Such approach offers great value for minimal investment, but it can answer more complicated risk- related questions only if some degree of quantification is added, possibly with a relative ranking/risk indexing approach. (Marhavilas et. al., 2011., Learningace, 2013., Osha, 2013). Relative Ranking / Risk Indexing Technique uses measurable features of a facility to calculate index numbers that are useful for comparing risks of different options. The 39 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

40. relative ranking/risk indexing technique can provide a high-level assessment of the risks associated with a range of activities, which is suitable when only relative priorities are needed, as long as a proper scoring tool exists. However, these results can be difficult to tie to absolute risks as the relative ranking/risk indexing technique uses various indexing tools to derive risk scores for particular activities. However, the tools are typically focused on a particular type of risk and for broader, standardized applications; considerably more development and validation time may be needed. Also, relative ranking/risk indexing tools are specifically designed to focus on a particular type of risk which makes it difficult to account for situations outside the scope of the particular tool. (Mayers, 2012, ABS Consulting, 2010, ABS Consulting 2008). Preliminary Risk Analysis (PrRA) is a technique used to define the risk related to important high-risk accident scenarios and to identify the risk of the accidents. However, because the PrRA focuses on potential accidents, the failures leading to accidents are not explored in much detail, so that it introduces a level of uncertainty in the results. Also, the resulting recommendations for reducing risk are typically general in nature instead of focused on attacking specific issues. Change analysis is used for any situation in which change from normal setup, operations, or activities is likely to affect risks. It relies on comparisons of two systems or activities to identify weaknesses in one of the systems in relation to the other However; it is highly dependent on points of comparison. Also, it does not inherently quantify risks and is strongly dependent on the expertise of those participating in the analysis, i.e. on their ability to recognize and evaluate notable differences between the system or activity of interest and the point of comparison. 40 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

41. What-if analysis is a problem-solving approach used to suggest upsets that may result in accidents or system performance problems and make sure the proper safeguards against those problems are in place. It is generally applicable for almost every type of risk assessment application, especially those dominated by relatively simple failure scenarios. However, it is likely to miss some potential problems, because it relies exclusively on the knowledge of the participants and is likely to overlook potentially important weaknesses, being difficult to audit, because there is no formal structure against which to audit. It also gives only qualitative results and no quantitative estimates of risk-related characteristics.(Brown et. al., 1999, Heldman, 2002) Failure modes and effects analysis (FMEA) is a technique that generates qualitative descriptions of potential performance problems and lists of recommendations for reducing risks, but it can also provide quantitative failure frequency or consequence estimates. It is generally used as a system-level and component-level risk assessment technique, applicable to any well-defined system. However, examination of human error is limited as it addresses potential human errors only to the extent that human errors produce equipment failures of interest, while the miss-operations that do not cause equipment failures are often overlooked. Also, its focus is on single-event initiators of specific equipment failures, which are analyzed one by one, so that important combinations of equipment failures may be overlooked. The, examination of external influences is limited to those events only that produce equipment failures of interest and accounts for possible effects of equipment failures only during one mode of operation or a few closely related modes of operation. 41 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

42. Hazard and Operability (HAZOP) analysis is used mostly as a system-level risk assessment technique and generates primarily qualitative results, although some basic quantification is possible. The HAZOP technique requires a well-defined system or activity as it is a rigorous analysis tool that systematically analyzes each part of a system or activity. It is rather time consuming as it systematically reviews credible deviations, identifies potential accidents that can result from the deviations. However, such detailed analysis focuses on one-event causes of deviations so that, if it objective is to identify all combinations of events that can lead to accidents of interest, more detailed techniques should be used. Fault Tree Analysis (FTA) is a technique that visually models how logical relationships between equipment failures, human errors, and external events can combine to cause specific accidents of interest. The probabilities and frequencies can be added to the analysis to estimate risks numerically. It is generally applicable for almost every type of risk assessment application, but examines only one specific accident of interest so that, to analyze other types of accidents, other fault trees must be developed. Also, quantification requires significant expertise because using fault tree analysis results to make statistical predictions about future system performance is complex, so that analysts often become so focused on equipment and systems that human and organizational issues are not taken adequately in their models. (GRI, 2011, FAA & Eurocontrol, 2007). Event Tree Analysis (ETA) is a technique that logically develops visual models of the possible outcomes of an initiating event by the use of decision trees. Probabilities and frequencies can be added to the analysis to estimate risks numerically. It is suited to 42 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

43. almost every type of risk assessment, but it is limited to one initiating event, leading to overly optimistic estimates of risk. Event and Causal Factor Charting is used to understand how an accident occurred by finding the underlying root causes of the key contributors and to make recommendations for fixing the root causes. It is most commonly used when the accident scenario is complicated, involving a chain of events or a number of root causes. However, it does not necessarily ensure that the root causes have been identified, unless the causal factor is the root cause. Also, using event charting can overwork simple problems. Preliminary Hazard Analysis (PrHA) is a technique that focuses on finding hazards, assessing the severity of accidents that could occur involving the hazards, and on finding protective features for reducing the risks of the hazards. This technique is typically conducted early in the process, before other analysis techniques are practical, and thus requires additional follow-up analyses. Also, the quality of the results of a PrHA is highly dependent on the knowledge of the team. At the time, there are few or no fully developed system specifications and little or no detailed design information and therefore, the risk assessment relies heavily on the knowledge of subject matter experts. If these experts do not participate in the risk assessment, or if the system is a new technology having little or no early operational history, the results of the PrHA will reflect the uncertainty of the team in many of its assessments and assumptions.(Mullai, A., 2006., ERC, 2013). III.6. Decision-Making Models Throughout the advancement of the construction sector more and more decision- making models have appeared to help construction projects to evolve toward informed 43 ‫اﻟﻣﮭﻧدي‬ ‫أﺣﻣد‬ ‫ﺳﻌد‬

44. decision-making. Decision-making models have been applied to various areas in the construction sector, such as metropolitan construction projects (Kuo et al., 2012), project contractual commitment (Nguyen et al., 2010), project risk identification and assessment (Mojtahedi et al., 2009), construction on transport project outcome (Polydoropoulou et al.,2009), mega projects cost-benefit analysis, planning and innovation (Priemus et al., 2008), portfolio balancing of engineering (Zeng et al., 2007)and contracting projects (Caron et al., 2007), construction project risk assessment (Deelstra et al., 2003; Špačkova, 2012), project facility design, construction, and life-cycle performance (Kam et al., 2003), and project risk management (Dey, 2002). Besides the decision-making models specific for the construction sector, the decision-making models are also broadly used in other industries and specific areas. Therefore the existing decision-making models can be grouped in two cate

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