763 resultados para Risk Management, Sicurezza informatica, Telecom Italia, telecomunicazioni, Multi-Project Management, Project Management Office, cyber security


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Reliability of supply of feed grain has become a high priority issue for industry in the northern region. Expansion by major intensive livestock and industrial users of grain, combined with high inter-annual variability in seasonal conditions, has generated concern in the industry about reliability of supply. This paper reports on a modelling study undertaken to analyse the reliability of supply of feed grain in the northern region. Feed grain demand was calculated for major industries (cattle feedlots, pigs, poultry, dairy) based on their current size and rate of grain usage. Current demand was estimated to be 2.8Mt. With the development of new industrial users (ethanol) and by projecting the current growth rate of the various intensive livestock industries, it was estimated that demand would grow to 3.6Mt in three years time. Feed grain supply was estimated using shire scale yield prediction models for wheat and sorghum that had been calibrated against recent ABS production data. Other crops that contribute to a lesser extent to the total feed grain pool (barley, maize) were included by considering their production relative to the major winter and summer grains, with estimates based on available production records. This modelling approach allowed simulation of a 101-year time series of yield that showed the extent of the impact of inter-annual climate variability on yield levels. Production estimates were developed from this yield time series by including planted crop area. Area planted data were obtained from ABS and ABARE records. Total production amounts were adjusted to allow for any export and end uses that were not feed grain (flour, malt etc). The median feed grain supply for an average area planted was about 3.1Mt, but this varied greatly from year to year depending on seasonal conditions and area planted. These estimates indicated that supply would not meet current demand in about 30% of years if a median area crop were planted. Two thirds of the years with a supply shortfall were El Nino years. This proportion of years was halved (i.e. 15%) if the area planted increased to that associated with the best 10% of years. Should demand grow as projected in this study, there would be few years where it could be met if a median crop area was planted. With area planted similar to the best 10% of years, there would still be a shortfall in nearly 50% of all years (and 80% of El Nino years). The implications of these results on supply/demand and risk management and investment in research and development are briefly discussed.

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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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In recent years, there have been significant developments in climate science relevant to agriculture and natural resource management. Assessing impacts of climate variability and use of seasonal climate forecasts have become increasingly important elements in the management "toolkit" for many Australian farmers. Consideration of climate change further increases the need for improved management strategies. While climate risk extension activities have kept pace with advances in climate science, a national review of the Vocational Education and Training system in Australia in relation to "weather and climate" showed that these topics were "poorly represented" at the management level in the Australian Qualifications Framework, and needed increased emphasis. Consequently, a new Unit of Competency concerning management of climatic risk was developed and accredited to address this deficiency. The objective of the unit was to build knowledge and skills for better management of climate variability via the elements of surveying climatic and enterprise data; analysing climatic risks and opportunities; and developing climatic risk management strategies. This paper describes establishment of a new unit for vocational education that is designed to harness recent developments in applied climate science for better management of Australia's highly variable climate. The main benefits of the new unit of competency, "Developing climatic risk management strategies,"were seen as improving decisions in climate and agriculture, and reducing climate risk exposure to enhance sustainable agriculture. The educational unit is now within the scope of agricultural colleges, universities, and registered training organisations as an accredited unit.

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Responding to mixed evidence on the decision-usefulness of annual report disclosures for derivative financial instruments to capital market participants, and concerns identified by practice, this paper examines usefulness in a direct study of user perceptions. Interviews with analysts from Australia’s four major banks reveal essential usefulness, limited by the disclosures’ failure to reflect companies’ actual use of derivatives throughout the period, and inability of users to understand companies’ off-balance sheet risk and risk management practices from information considered generic and boilerplate. The research complements and extends existing archival and survey research and provides new evidence suggesting low-cost ways for increasing usefulness. It supports the International Accounting Standards Board’s disclosure recommendations in its recent Discussion Paper: A Review of the Conceptual Framework for Financial Reporting, but, at the same time, highlights that for these proposed measures to be successful in relation to IFRS 7, they may need to address other issues. The research increases knowledge of the informational requirements of lenders, an important class of financial information user, and supports calls from practice for companies to improve their disclosure of material economic risks.

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The APSIM-Wheat module was used to investigate our present capacity to simulate wheat yields in a semi-arid region of eastern Australia (the Victorian Mallee), where hostile subsoils associated with salinity, sodicity, and boron toxicity are known to limit grain yield. In this study we tested whether the effects of subsoil constraints on wheat growth and production could be modelled with APSIM-Wheat by assuming that either: (a) root exploration within a particular soil layer was reduced by the presence of toxic concentrations of salts, or (b) soil water uptake from a particular soil layer was reduced by high concentration of salts through osmotic effects. After evaluating the improved predictive capacity of the model we applied it to study the interactions between subsoil constraints and seasonal conditions, and to estimate the economic effect that subsoil constraints have on wheat farming in the Victorian Mallee under different climatic scenarios. Although the soils had high levels of salinity, sodicity, and boron, the observed variability in root abundance at different soil layers was mainly related to soil salinity. We concluded that: (i) whether the effect of subsoil limitations on growth and yield of wheat in the Victorian Mallee is driven by toxic, osmotic, or both effects acting simultaneously still requires further research, (ii) at present, the performance of APSIM-Wheat in the region can be improved either by assuming increased values of lower limit for soil water extraction, or by modifying the pattern of root exploration in the soil pro. le, both as a function of soil salinity. The effect of subsoil constraints on wheat yield and gross margin can be expected to be higher during drier than wetter seasons. In this region the interaction between climate and soil properties makes rainfall information alone, of little use for risk management and farm planning when not integrated with cropping systems models.

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The traditional reductionist approach to science has a tendency to create 'islands of knowledge in a sea of ignorance', with a much stronger focus on analysis of scientific inputs rather than synthesis of socially relevant outcomes. This might be the principal reason why intended end users of climate information generally fail to embrace what the climate science community has to offer. The translation of climate information into real-life action requires 3 essential components: salience (the perceived relevance of the information), credibility (the perceived technical quality of the information) and legitimacy (the perceived objectivity of the process by which the information is shared). We explore each of these components using 3 case studies focused on dryland cropping in Australia, India and Brazil. In regards to 'salience' we discuss the challenge for climate science to be 'policy-relevant', using Australian drought policy as an example. In a village in southern India 'credibility' was gained through engagement between scientists and risk managers with the aim of building social capital, achieved only at high cost to science institutions. Finally, in Brazil we found that 'legitimacy' is a fragile, yet renewable resource that needs to be part of the package for successful climate applications; legitimacy can be easily eroded but is difficult to recover. We conclude that climate risk management requires holistic solutions derived from cross-disciplinary and participatory, user-oriented research. Approaches that combine climate, agroecological and socioeconomic models provide the scientific capabilities for establishment of 'borderless' institutions without disciplinary constraints. Such institutions could provide the necessary support and flexibility to deliver the social benefits of climate science across diverse contexts. Our case studies show that this type of solution is already being applied, and suggest that the climate science community attempt to address existing institutional constraints, which still impede climate risk management.

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This project provided information on the genetics of crown rot (CR) resistance to help breeding work, located new parent lines in wheat and barley, and provided an insight into yield losses that occur in commercial varieties with increasing levels of CR for risk management. Genetic experiments found some highly resistant lines were poor parents, and CR resistance was complex. Best parent lines and many specific crosses were identified for further work. New potential parent lines were identified in wheat and barley, some now used in breeding programs. Yield loss can be severe even with low levels of CR when combined with drought stress. CR can reduce yield even with a wet finish.

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Nipah virus (NiV) (Genus Henipavirus) is a recently emerged zoonotic virus that causes severe disease in humans and has been found in bats of the genus Pteropus. Whilst NiV has not been detected in Australia, evidence for NiV-infection has been found in pteropid bats in some of Australia's closest neighbours. The aim of this study was to determine the occurrence of henipaviruses in fruit bat (Family Pteropodidae) populations to the north of Australia. In particular we tested the hypothesis that Nipah virus is restricted to west of Wallace's Line. Fruit bats from Australia, Papua New Guinea, East Timor and Indonesia were tested for the presence of antibodies to Hendra virus (HeV) and Nipah virus, and tested for the presence of HeV, NiV or henipavirus RNA by PCR. Evidence was found for the presence of Nipah virus in both Pteropus vampyrus and Rousettus amplexicaudatus populations from East Timor. Serology and PCR also suggested the presence of a henipavirus that was neither HeV nor NiV in Pteropus alecto and Acerodon celebensis. The results demonstrate the presence of NiV in the fruit bat populations on the eastern side of Wallace's Line and within 500 km of Australia. They indicate the presence of non-NiV, non-HeV henipaviruses in fruit bat populations of Sulawesi and Sumba and possibly in Papua New Guinea. It appears that NiV is present where P. vampyrus occurs, such as in the fruit bat populations of Timor, but where this bat species is absent other henipaviruses may be present, as on Sulawesi and Sumba. Evidence was obtained for the presence henipaviruses in the non-Pteropid species R. amplexicaudatus and in A. celebensis. The findings of this work fill some gaps in knowledge in geographical and species distribution of henipaviruses in Australasia which will contribute to planning of risk management and surveillance activities.

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With Safe Design and Construction of Machinery, the author presents the results of empirical studies into this significant aspect of safety science in a very readable, well-structured format. The book contains 436 references, 17 tables, one figure and a comprehensive index. Liz Bluff addresses a complex and important, but often neglected domain in OHS – the safety of machinery – in a holistic and profound, yet evidence based analysis; with many applied cases from her studies, which make the book accessible and a pleasant lecture. Although research that led to this remarkable publication might have been primarily focused on the regulators, this book can be highly recommended to all OHS academics and practitioners. It provides an important contribution to the body of knowledge in OHS, and establishes one of the few Australian in-depth insights into the significance of machinery producers, rather than machinery users in the wider framework of risk management. The author bases this fresh perspective on the well-established European Machinery Safety guidelines, and grounds her mixed-methods research predominantly in qualitative analysis of motivation and knowledge, which eventually leads to specific safety outcomes. It should be noted that both European and Australian legal aspects are investigated and considered, as both equally apply to many machinery exporters. A detailed description of the research design and methods can be found in an appendix. Overall, the unique combination of quantitative safety performance data and qualitative analysis of safety behaviours form a valuable addition to the understanding of machinery safety. The author must be congratulated on making these complex relationships transparent to the reader through her meticulous inquiry.

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Many countries over the last decade, have used performance-based contracting (PBC) to manage and maintain roads. The implementation of PBC provides additional benefits for the government/public such as cost savings and improved conditions of contracted road assets. In Australia, PBC is already being implemented on all categories of roads: national, state, urban and rural. Australian PBC arrangement is designed to turn over control and responsibility for roadway system maintenance, rehabilitation, and capital improvement projects to private contractors. Contractors’ responsibilities include determination of treatment types, the design, programming and the undertaking of works needed to maintain road networks at predetermined performance levels. Indonesia initiated two PBC pilot projects in 2011, the Pantura Section Demak-Trengguli (7.68 kilometers) in Central Java Province and Section Ciasem-Pamanukan (18.5 kilometers) in West Java Province. Both sections are categorized as national roads. The contract duration for both of these projects is four years. To facilitate a possible way forward, it is proposed to conduct a study to understand Australia's experiences of advancing from pilot projects to nation-wide programs using PBC. The study focuses on the scope of contracts, bidding processes, risk allocation, and key drivers, using relevant PBC case studies from Australia. Recommendations for future PBC deployment nation-wide should be based on more research associated with risk allocation. This will include investigation of standard conditions of contract. Implications of the contract clauses for the risk management strategy to be adopted by contractors. Based on the nature of risks, some are best managed by the project owner. It is very important that all parties involved to be open to the new rules of contract and to convince themselves about the potential increased benefits of the use of PBC. The most recent states of challenging issues were explored and described.

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Hendra virus (HeV) causes highly lethal disease in horses and humans in the eastern Australian states of Queensland (QLD) and New South Wales (NSW), with multiple equine cases now reported on an annual basis. Infection and excretion dynamics in pteropid bats (flying-foxes), the recognised natural reservoir, are incompletely understood. We sought to identify key spatial and temporal factors associated with excretion in flying-foxes over a 2300 km latitudinal gradient from northern QLD to southern NSW which encompassed all known equine case locations. The aim was to strengthen knowledge of Hendra virus ecology in flying-foxes to improve spillover risk prediction and exposure risk mitigation strategies, and thus better protect horses and humans. Monthly pooled urine samples were collected from under roosting flying-foxes over a three-year period and screened for HeV RNA by quantitative RT-PCR. A generalised linear model was employed to investigate spatiotemporal associations with HeV detection in 13,968 samples from 27 roosts. There was a non-linear relationship between mean HeV excretion prevalence and five latitudinal regions, with excretion moderate in northern and central QLD, highest in southern QLD/northern NSW, moderate in central NSW, and negligible in southern NSW. Highest HeV positivity occurred where black or spectacled flying-foxes were present; nil or very low positivity rates occurred in exclusive grey-headed flying-fox roosts. Similarly, little red flying-foxes are evidently not a significant source of virus, as their periodic extreme increase in numbers at some roosts was not associated with any concurrent increase in HeV detection. There was a consistent, strong winter seasonality to excretion in the southern QLD/northern NSW and central NSW regions. This new information allows risk management strategies to be refined and targeted, mindful of the potential for spatial risk profiles to shift over time with changes in flying-fox species distribution.

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Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

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Directors and Officers Liability Insurance (“D&O insurance”) has grown and evolved rapidly over the past 80 years to assume an important position in most corporations’ corporate governance and risk management strategies. This article focuses upon certain topical matters of particular concern to directors and officers including the availability of defence costs where a D&O policy is subject to a statutory charge; the commercial desirability of stand-alone “A-side” coverage, being the cover provided directly to directors and officers for loss resulting from claims made against them for wrongful acts; the impact of fraud and/or dishonesty upon D&O cover; and disclosure of the nature and extent of D&O cover to the directors and officers themselves and to third parties – in the latter case such access frequently being necessary to determine the economic viability of pursuing a proposed action against a company and its directors and officers.

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There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.

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We conducted an experiment to investigate the impact of sport scandal on consumer attitudes toward a range of sport stakeholders. We examined the effects of fans’ social identity (fan of scandalized team vs. fan of rival team), scandal severity (single perpetrator vs. multiple perpetrators) and the sponsor brand’s response to the scandal (sponsorship retention vs. termination) on consumers’ attitudes toward the implicated team, the scandal perpetrators, the sport, and sponsor brand. We find evidence of differential reactions to scandal reflecting social identity, such that fans support their own team despite increased scandal severity but negatively judge a rival team’s transgressions. Results suggest that where fans are concerned, sponsors may be better served to continue with a sponsorship following scandal than to terminate, even for some forms of severe scandal. However, termination may receive more positive evaluation from rival team fans; hence continuation of sponsorship needs to accompany a tempered approach.