For this purpose and by using evidence from other research in the area; the overall conclusion was that, according to project actors, risk management process is strongly linked to the performance of the project in terms of quality, time and budget or cost. Thus, the effective managing risk process must permeate all areas, functions and processes of the project. Therefore, the aim must be to negotiate risks, assess these or even make these marketable and reduce them emphatically. In this, a decisive factor in its success is, in the end, the interaction of all elements represented. A risk and control culture borne and experienced by all parties involved in the project has the effect of a connecting bracket that can safeguard the effectiveness of the structural and organizational measures of managing risk; the main key to this is the parties involved in risk management process. Effective managing risk process requires commitment and also the risk-conscious behaviour of each individual. The motivation as well as the interplay of the parties involved in the project in the end determines the quality of the work and thereby the project success. However, in each project, residual risks remain. This means that it remains a strategic decision on whether these risks have been taken and can be borne if they occur.
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Intransitive objects and their resulting causal powers may not be directly observed rather they must be theoretically speculated (Johnson & Duberley, 2006:166). Aspects of the performance system are clearly tangible in nature: measurement, communication and targets. These conform to the dominant Operations Management paradigm and growing preference for use of empirical methods (Meridith, 2009; Sanders, 2009; Theoharakis et al., 2007). However the incorporation of risk extends the performance system to include managerial interpretation and subjective description of risk requires acknowledgement of the role of social mediation in the relationship. I believe the world of risk management may not be reduced to such a closed system image. There is greater complexity affecting the world than may be observationally accounted for and perception of empirical regularities. This is not totally sufficient for establishing knowledge in this field – this is the Realist’s view.
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During my time at Intel, the security group’s mission evolved toward this goal as we helped define solutions to a variety of technology challenges. For example, my team recognized as early as 2002 that implementing wireless networks within Intel’s offices could help make the workforce more productive and increase their job satisfaction by letting them more easily connect using their laptops from meeting rooms, cafeterias, and other locations. At the time, many businesses avoided installing wireless networks within their facilities because of the risk of eavesdropping or because of the cost. We learned pretty quickly that when we restricted wireless LAN deployments or charged departments additional fees to connect, we actually generated more risks. This was because the departments would buy their own access points and operate them in an insecure fashion. We recognized that the benefits of installing wireless LANs across the company outweighed the risks, and we mitigated those risks using security controls such as device authentication and transport encryption. By 2004, that approach had enabled ubiquitous wireless and mobile computing that propelled productivity and actually reduced risks.
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I also wish to thank all those in Intel’s information risk and security team. Without their skills and passion, I would not have learned so much during the past 11 years. It is because of them that I have been able to execute my role and write this book. Many individuals contributed time, energy, and expertise—either to me, helping me grow my knowledge over the years; directly to the book; or to the creation of other documents that I used as source materials. The following deserve special thanks: Brian Willis, Kim Owen, Steve Mancini, Dennis Morgan, Jerzy Rub, Esteban Gutierrez, Rob Evered, Matt Rosenquist, Tim Casey, Toby Kohlenberg, Jeff Boerio, Alan Ross, Tarun Viswanathan, Matt White, Michael Sparks, Eran Birk, Bill Cahill, Stacy Purcell, Tim Verrall, Todd Butler, Stuart Tyler, Amir Itzhaki, Carol Kasten, Perry Olson, Mary Rossell, Marie Steinmetz, Fawn Taylor, Grant Babb, Eamonn Sheeran, and Dave Munsey.
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In the risk assessment stage the risks are scored. In many risk assessment methods this score is determined by multiplying the chance of occurrence with the potential consequences, see for example Well-Stam et al. (2013, p. 31). However, this implies that the flu (high chance x low consequence) would be scored the same as malaria (low chance x high consequence). A more sophisticated risk assessment method is described by Keizer et al. (2002). In this method the participants individually assess the factors for their riskiness on three 5-point scales, where 1 is Safe and 5 is Fatal. The risk facilitator then compares the participants’ scores and assigns the factors to four classes; three classes indicate consensus on the level of riskiness and one class indicates a distribution of opinions. The latter class is very important, because it shows that clarification is required for everyone to better understand this factor. Pasman & Reiniers (2014) further note that in order to increase the quantitative risk assessment maturity the calculation model should be standardized and results should be formulated in such way that misinterpretation is prevented. To prevent quantitative risk assessment outputs to lead their own lives the output should be treated more carefully (Rae, Alexander, & McDermid, 2014); i.e. the underlying thoughts should always be taken into account.
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The ongoing economic crisis has profoundly changed the industry of asset manage- ment by putting risk management at the heart of most investment processes. This new risk-based investment style does not rely on return forecasts and is therefore assumed to be more robust. 2011 was marked by several great successes in transforming the practice of asset management with several large institutional investors moving their portfolios to minimum variance, ERC or risk parity strategies. These portfolio con- structions are special cases of a more general class of allocation models, known as the risk budgeting approach. In a risk budgeting portfolio, the risk contribution from each component is equal to the budget of risk defined by the portfolio manager. Unfor- tunately, even if risk budgeting techniques are widely used by market practitioners, there are few results about the behavior of such portfolios in the academic literature. In this paper, we derive the theoretical properties of the risk budgeting portfolio and show that its volatility is located between those of the minimum variance and weight budgeting portfolios. We also discuss the existence, uniqueness and optimality of such a portfolio. In the second part of the paper, we propose several applications of risk budgeting techniques for risk-based allocation, like risk parity funds and strategic asset allocation, and equity and bond alternative indexations.
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for someone to be responsible for running the risk processes, to make sure that it happens smoothly and effectively, to ensure adherence to standards, to encourage and inspire people to be involved and committed to managing risk, and to coordinate data management and risk reporting. However, it is misleading to call this person the Risk Manager. A more accurate job title could be: Risk Coordinator, Risk Facilitator, Risk Champion or Risk Process Manager. These names explain what the role actually does and prevents people from expecting someone else to manage their risks for them.
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In this dissertation, we construct a serial multiple-level SC coordination model by (Q, r) policies in a fuzzy risk environment based our proposed one tier fuzzy version of (Q, r) policy. Sources of risk and uncertainty in our model include demand, lead time, supplier yield and penalty cost, and the naturally imprecise nature of these risk factors in managing inventories is represented using triangular fuzzy numbers. Heuristics analogous to classical (Q, r) policies are presented to determine local optimal policies for multiple-installation instances on the basis of techniques identified in the literature on fuzzy sets. An external coordinator with three roles is introduced and a coordination process is implemented to improve SC performance to meet a target. The biggest advantage of fuzzy logic is that it can be used for any virtual empirical lead time or demand, while the exact solution for non-normal lead time or demand is highly dependent on the distributions. Our models show that fuzzy set theory provides a means of actually quantifying the cost of not knowing the underlying demand distribution and parameters. However, it is also important to notice that the quality of the solution from fuzzy modeling might depend on the expert’s subjective estimation, and the degree of computation complexity in our model might be higher than that of normal approximation especially when penalty cost rate is low.
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The present study has several strengths, contrary to the other domestic studies on dementia, where dementia di- agnoses have mostly been based on questionnaires or the reports of informants; we used the Diagnostic and Sta- tistical Manual of Mental Disorders, fifth edition crite- ria, as well as neurologist’s examinations, to confirm the presence of dementia. Moreover, this was the first do- mestic structured case-control study conducted in NIOC retires for assessing the most common medical risk fac- tors for dementia. Finally, because of the relatively big sample size of the present study and the existence of the similar reliable statistics for the elderly population in NIOC compared to the whole country according to Ira- nian national statistics (www.amar.org.ir), the results of this study can be easily validated by other populations.
Recognized traditional risk factors for CVD include age, sex, family history, hypertension, dysglycemia, dyslipi- demia, and smoking. Newer cardiovascular risk factors include abdominal obesity (measured by waist circum- ference), insulin resistance, infl ammation as measured by high-sensitivity C-reactive protein (hsCRP) levels, lack of consumption of fruits and vegetables, sed- entary lifestyle, and psychosocial stress. While trad- itional parameters are routinely assessed in the clinic, waist circumference should be added to the routine evaluation of cardiovascular risk. In patients whose triglyceride levels are elevated, an apolipoprotein B measurement can replace that of low-density lipopro- tein cholesterol (LDL-C) for the purpose of risk assess- ment and management of CMR.
crisis. A very recent example of bank periodical liquidity management could be borrowed from Merrouche and Schanz (2010).Their study which focuses on the U.K payment system suggests that, early in the day, when settlement banks are not sure that their counter-parties to whom they make payments would pay-back, they stop doing so. In this wise, healthy banks remain unaffected by disruptions caused by operation outage, thus preventing affected banks acting as liquidity sinks. Generally, a bank with operational outage receives money both from the central banks and other banks but is unable to make payments due to more or less, information and/or technology issues which could pose a systematic risk if not sufficiently monitored at the beginning of the day.
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The fourth step is modeling risk management that can be applied by organizations in the form of conventional risk management, setting risk models and managing organizational structures. If risks arising from an activity have been identified, then further action is taken to reduce the risks that arise. This action is called Risk Mitigation. Conventional risk management is carried out by planning risk mitigation actions and is complemented by establishing a risk model based on the level of risk and establishing the organization / agency that will manage / handle the existing risks. Sometimes these risks cannot be eliminated altogether but can only be reduced so that a residual risk will occur. According to Flanagan & Norman , Management of risk is divided into four, namely: Risk Avoidance, namely avoiding or distancing risk by changing project plans to eliminate risks or conditions or to protect project targets from their effects / consequences. Risk Transfer), namely the transfer of risk by seeking the exchange of consequences or consequences of risk to third parties together with ownership of the response. This transfer of risk solely provides management of responsibility to other parties, not eliminating or eliminating it. This form of risk transfer is in the form of insurance by paying a premium. Risk Mitigation, which is conducting an investigation to reduce the probability and / or consequences of adverse risk events to an acceptable level. Risk Acceptance. This technique indicates that the project team decides not to change the project plan related to a risk or is unable to identify other adequate response strategies.
The severity of loss is measured by the deviation from the expected value of the event's possible outcomes. Risk identification is a process that reveals and determines the possible organizational risks as well as conditions, arising risks. By risk identification the organization is able to study activities and places where its resources are exposed to risks according to Williams . Figure 1 Illustrates risk identification elements which can be described by the following basic components: sources of risks; hazard factors; perils; and exposures to risk. Sources of risk are elements of the organizational environment that can bring some positive or negatives outcomes. Hazard is a condition or circumstance that increases the chance of losses or gains and their severity. An error of the firm management about the market expansion for a given product is an example for a hazard factor activity that determines the system risk. Peril is something that is close to the risk and it has negative, non-profitable results. Peril can happen at any time and cause unknown, unpredictable loses. Peril is the cause of losses. Resources exposed to risk are objects facing possible losses or gains. As suggested by Yeo  the terms 'risk' and 'uncertainty' are sometimes used interchangeably. However, more often, the concept of risk is expressed in terms of the probability of occurrence (frequency), and the severity of loss (or gain) that will be a consequence of such an occurrence. They will be affected if the risk event occurs. Nevertheless, Risk Management is becoming a key factor within organizations since it can minimize the probability and impact of information technology project threats and capture the opportunities that could occur during the information technology project life cycle .
Similar to commodities, the IMF country reports represent real estate as the frequent source of risk, mainly because of the sector overheating. The sector bubble blowing up could trigger government aids to construction companies and mortgage exposed banks, and affect budgetary revenues from the sector, then cause negative spillover for economy and general budget revenues. In Canada “the main risk on the domestic side is a sharp correction in the housing market”, because “household debt-to-disposable income has reached nearly 170 percent, which is among the highest in G-7 economies” IMF Canada (2017), Australian “housing market imbalances and higher household vulnerabilities [are combined with] commercial banks‟ housing exposure .. at over 50 percent of total assets” IMF Australia (2018), In Korea “household debt exceeds 90 percent of GDP, increasing vulnerability to both a housing price correction and a sharp rise in interest rates” IMF Korea (2018), In Germany “housing prices [demonstrate] some hot spots” IMF Germany (2017), as well as in Japan some “segments of the real estate market seem to be moderately overvalued” IMF Japan (2017), Chinese “authorities started tightening macro-prudential measures for the real estate sector” IMF China (2017),
Failure of high profile companies during 1970’s and 1980’s in USA was the result behind formation of Committee of the Sponsoring Organizations of the Treadway Commission in 1985. With primary focus on causes of fraudulent financial reporting, COSO was commissioned to study enterprise wide risk management and governance problems. “Internal Control-Integrated Framework report” was the final outcome of COSO project which was published in 1992. In its final report, with focus on internal control, COSO offers a corporate governance framework at enterprise level in five main areas of controlling environment, risk assessment, controlling activities information and communication and monitoring (Committee of the Sponsoring Organisations of the Treadway Commission, 1992). However, COSO report admits that internal controls are not sufficient for bad judgments and wrong decisions. COSO framework also received other criticisms for being too much focus on financial reporting and not requiring enterprise to report their internal control process (Root, 1998; Miccolis, Shah, 2000) in conclusion in the context of Letter of Credit Operation, COSO framework is not proper measure to be in place for exporter for managing the risk of documentary discrepancy due to its general and vague nature , not providing any details on implementation method, its focus on financial reporting and excluding risk management from its internal control definitions.
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The analyzed matrix comprises own funds, liquidity, solvency, general risk rate, currency risk, as well as the impact of some exterior phenomena upon the banking system. The shocks came from a sudden increase of the interest, of the exchange rate. Thus, the consequences upon the banks’ joint stock, upon their own funds and upon the solvency indicator were closely observed. Using the simulation method, it was noticed that a series of banks, with capital paid in foreign currency, reach their limit regarding their own funds, and this imposes an increase of the capital 10 . It can be assumed that the implementation of this new indicator will improve the knowledge about the banking system with the help of the inputs received from external factors; this means, in fact, to be aware of the sensitivity of the Romanian banking system.
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A second dimension that should be assessed for Six Sigma IS/IT projects is the extent to which the project results are expected to impact end user processes. For example, changing the work process at a help desk such that calls are documented and responded to within a given time frame affects the internal operation of the IS/IT department, but not necessarily the end user. Changing the process by which an end user requests help more directly involves action by the end user community and therefore has a direct effect on the success of the project. The risk factor that emerges as critical to the success of these projects is end user resistance to change. Resistance to change must be managed from the onset of a project. Failing to do so may result in the benefits of the project not being fully realized. Strategies to manage resistance to change include placing an end user on the project team, inclusion of end user training in the project scope, linking the success of the end user to the success of the project, and allowing for end user input to the project charter. In essence, in the Six Sigma environment, permitting the end user to also take ownership of a project that will eventually affect them reduces their resistance to change.
The Qualitative approach relies on judgments and it uses criteria to determine outcome. A common Qualitative approach is the precedence diagramming method, which uses ordinal numbers to determine priorities and outcomes. Another way of employing qualitative approach is to make a list of the processes of a project in descending order calculate the risk associated with each process and the list that controls that may exist for each risk [10-12].
immediate solutions. As Slavoj !i"ek has recently put it, there has been an enormous pressure simply “to do something”. But doing things is often a way of avoiding talking and thinking about them: “such as throwing $700 billion at a problem instead of reflecting on how it arose in the first place” (!i"ek, 2009:11). The haste to quickly do something, to organise rescue plans, bailouts, and stimulus packages, has also led to a concentration of focus on the more obviously “financial” dimensions of the crisis, along with a tendency to downplay the wider cultural and political background against which it developed and acquired momentum. In this paper, therefore, I’d like to reflect on the crisis as much more than just an economic event. In particular, I’d like to argue that the financial crisis had cultural conditions of possibility that are imbricated with economic factors in complex ways. There is a pressing need, I want to suggest here, to decentre an explicit and singular focus on the financialization that is assumed to be at the heart of the Global Financial Crisis (the GFC), and to instead reflect on these cultural contexts and conditions of possibility. This includes reflecting on some fundamental features of contemporary social and economic life, especially recent redefinitions of the family, the household, home ownership, investment, risk, and the fashioning of everyday financial subject positions and identities. Ultimately the idea that the crisis was the function of exogenous financial forces and associated irrational “herd behaviour” fails to acknowledge the cultural rationality that saw the constitution of the citizen as someone enjoined, indeed required, to invest in their lives through debt-fuelled, and frequently asset-based, consumption that more often than not depended on the home as an object of leveraged investment (see Langley, 2008). In other words, “It’s the culture, stupid!” This process of reflection also requires enough pause to consider how the current period of economic turbulence has come to be understood and symbolised, and the kinds of “stories” it has given rise to. For example, historical analogies have been drawn extensively in attempts to both explain and understand the financial crisis. These analogies rely on an analytical manoeuvre of extrapolation that projects a direct line of connection between past experiences of economic instability and the present. In this sense, they are not so different to the financial models of extrapolation that assumed the future would look just like the recent past. Now, instead of models of growth based on an endlessly booming present we are presented with models of severe depression (and related solutions) inherited from the past.
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Capitalisation-weighted indices presenting clear drawbacks, we propose an alternative ap- proach to indexation, based on sovereign risk. Using the framework described previously, it is possible to decompose the risk of a sovereign bond portfolio into individual country contributions. Given the portfolio weights, we can find the risk contributions. Risk bud- geting is basically the same process in reverse. Given a set of defined risk contributions, risk budgeting provides a portfolio allocation. The problem with traditional indices is that investors may face a high level of risk concentration. To avoid that, investors can start by defining a set of risk budgets that they find appropriate and then derive the corresponding weights. Even if the risk budgets are fixed, the portfolio weights still vary over time as the risk associated with each country fluctuates. This way, when an individual country’s situation deteriorates, this is reflected in its spread and thereby its risk, leading eventually to a reduction of its weight. Risk budgeting thus allows investors to control the distribution of risk over time. However, it does not address the problem of how to choose the right risk budgets.
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