443 resultados para Risk measures


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China has a reputation as an economy based on utility: the large-scale manufacture of low-priced goods. But useful values like functionality, fitness for purpose and efficiency are only part of the story. More important are what Veblen called ‘honorific’ values, arguably the driving force of development, change and value in any economy. To understand the Chinese economy therefore, it is not sufficient to point to its utilitarian aspect. Honorific status-competition is a more fundamental driver than utilitarian cost-competition. We argue that ‘social network markets’ are the expression of these honorific values, relationships and connections that structure and coordinate individual choices. This paper explores how such markets are developing in China in the area of fashion and fashion media. These, we argue, are an expression of ‘risk culture’ for high-end entrepreneurial consumers and producers alike, providing a stimulus to dynamic innovation in the arena of personal taste and comportment, as part of an international cultural system based on constant change. We examine the launch of Vogue China in 2005, and China’s reception as a fashion player among the international editions of Vogue, as an expression of a ‘decisive moment’ in the integration of China into an international social network market based on honorific values.

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Background Advanced paternal age (APA) is associated with an increased risk of neurodevelopmental disorders such as autism and schizophrenia, as well as with dyslexia and reduced intelligence. The aim of this study was to examine the relationship between paternal age and performance on neurocognitive measures during infancy and childhood. Methods and Findings A sample of singleton children (n = 33,437) was drawn from the US Collaborative Perinatal Project. The outcome measures were assessed at 8 mo, 4 y, and 7 y (Bayley scales, Stanford Binet Intelligence Scale, Graham-Ernhart Block Sort Test, Wechsler Intelligence Scale for Children, Wide Range Achievement Test). The main analyses examined the relationship between neurocognitive measures and paternal or maternal age when adjusted for potential confounding factors. Advanced paternal age showed significant associations with poorer scores on all of the neurocognitive measures apart from the Bayley Motor score. The findings were broadly consistent in direction and effect size at all three ages. In contrast, advanced maternal age was generally associated with better scores on these same measures. Conclusions The offspring of older fathers show subtle impairments on tests of neurocognitive ability during infancy and childhood. In light of secular trends related to delayed fatherhood, the clinical implications and the mechanisms underlying these findings warrant closer scrutiny.

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Risks and uncertainties are inevitable in engineering projects and infrastructure investments. Decisions about investment in infrastructure such as for maintenance, rehabilitation and construction works can pose risks, and may generate significant impacts on social, cultural, environmental and other related issues. This report presents the results of a literature review of current practice in identifying, quantifying and managing risks and predicting impacts as part of the planning and assessment process for infrastructure investment proposals. In assessing proposals for investment in infrastructure, it is necessary to consider social, cultural and environmental risks and impacts to the overall community, as well as financial risks to the investor. The report defines and explains the concept of risk and uncertainty, and describes the three main methodology approaches to the analysis of risk and uncertainty in investment planning for infrastructure, viz examining a range of scenarios or options, sensitivity analysis, and a statistical probability approach, listed here in order of increasing merit and complexity. Forecasts of costs, benefits and community impacts of infrastructure are recognised as central aspects of developing and assessing investment proposals. Increasingly complex modelling techniques are being used for investment evaluation. The literature review identified forecasting errors as the major cause of risk. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. For risks that cannot be readily quantified, assessment techniques commonly include classification or rating systems for likelihood and consequence. The report outlines the system used by the Australian Defence Organisation and in the Australian Standard on risk management. After each risk is identified and quantified or rated, consideration can be given to reducing the risk, and managing any remaining risk as part of the scope of the project. The literature review identified use of risk mapping techniques by a North American chemical company and by the Australian Defence Organisation. This literature review has enabled a risk assessment strategy to be developed, and will underpin an examination of the feasibility of developing a risk assessment capability using a probability approach.

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This report fully summarises a project designed to enhance commercial real estate performance within both operational and investment contexts through the development of a model aimed at supporting improved decision-making. The model is based on a risk adjusted discounted cash flow, providing a valuable toolkit for building managers, owners, and potential investors for evaluating individual building performance in terms of financial, social and environmental criteria over the complete life-cycle of the asset. The ‘triple bottom line’ approach to the evaluation of commercial property has much significance for the administrators of public property portfolios in particular. It also has applications more generally for the wider real estate industry given that the advent of ‘green’ construction requires new methods for evaluating both new and existing building stocks. The research is unique in that it focuses on the accuracy of the input variables required for the model. These key variables were largely determined by market-based research and an extensive literature review, and have been fine-tuned with extensive testing. In essence, the project has considered probability-based risk analysis techniques that required market-based assessment. The projections listed in the partner engineers’ building audit reports of the four case study buildings were fed into the property evaluation model developed by the research team. The results are strongly consistent with previously existing, less robust evaluation techniques. And importantly, this model pioneers an approach for taking full account of the triple bottom line, establishing a benchmark for related research to follow. The project’s industry partners expressed a high degree of satisfaction with the project outcomes at a recent demonstration seminar. The project in its existing form has not been geared towards commercial applications but it is anticipated that QDPW and other industry partners will benefit greatly by using this tool for the performance evaluation of property assets. The project met the objectives of the original proposal as well as all the specified milestones. The project has been completed within budget and on time. This research project has achieved the objective by establishing research foci on the model structure, the key input variable identification, the drivers of the relevant property markets, the determinants of the key variables (Research Engine no.1), the examination of risk measurement, the incorporation of risk simulation exercises (Research Engine no.2), the importance of both environmental and social factors and, finally the impact of the triple bottom line measures on the asset (Research Engine no. 3).

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This project aims to assess the extent of economic sustainability of working in international markets by Australian construction design-related firms. This investigation also identified barriers and success factors firms experience, which ultimately increases or reduces their exposure to financial risk. This study explored new research territory by developing a detailed understanding of the way three successful firms have maintained their longevity in various international markets. The firms are not considered to be large firms by international standards. The manner in which the firms achieve long term sustainability, deal with problems and barriers in international markets and develop successful strategies rely upon being adaptable to different markets and changes within markets. A model was developed based upon a critical analysis of the literature. An adaptive performance framework for sustainability was developed which had three key areas; internationalisation process, market knowledge and design management. The sustainable business model is underpinned by the management of non-economic factors, which include social, cultural and intellectual capital. The ultimate aim of any firm and the ultimate indicator of success is financial capital. Firms typically develop their own highly sophisticated financial measures themselves however have only an implicit understanding of other softer and less tangible factors that impact upon sustainability. Adaptive performance is the firm’s continual adaptivity of business practices to respond to and thereby achieve client satisfaction by a combination of self, market and project needs assessment.

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This project aims to assess the extent of economic sustainability of working in international markets by Australian construction design-related firms. This investigation also identified barriers and success factors firms experience, which ultimately increases or reduces their exposure to financial risk. This study explored new research territory by developing a detailed understanding of the way three successful firms have maintained their longevity in various international markets. The firms are not considered to be large firms by international standards. The manner in which the firms achieve long term sustainability, deal with problems and barriers in international markets and develop successful strategies rely upon being adaptable to different markets and changes within markets. A model was developed based upon a critical analysis of the literature. An adaptive performance framework for sustainability was developed which had three key areas; internationalisation process, market knowledge and design management. The sustainable business model is underpinned by the management of non-economic factors, which include social, cultural and intellectual capital. The ultimate aim of any firm and the ultimate indicator of success is financial capital. Firms typically develop their own highly sophisticated financial measures themselves however have only an implicit understanding of other softer and less tangible factors that impact upon sustainability. Adaptive performance is the firm’s continual adaptivity of business practices to respond to and thereby achieve client satisfaction by a combination of self, market and project needs assessment.

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Changes in the environment, including increased environmental complexity, require military supply units to employ a more adaptive strategy in order to enhance military agility. We extend the Lumpkin and Dess (1996) model and develop propositions that explore the interrelationships between/amongst entrepreneurial orientation (EO); opportunity recognition, evaluation and exploitation; environmental and organizational factors; and organizational performance. We propose that the innovativeness, proactiveness, and risk-taking dimensions of EO are of primary importance in identifying adaptive solutions and that these relationships are moderated by environmental factors. The autonomy and competitive aggressiveness dimensions of EO are important in implementing solutions as adaptive strategies, especially in a military context, and these relationships are moderated by organizational factors. This chapter extends existing theory developed primarily for the civilian sector to the military. Military organizations are more rigid hierarchical structures, and have different measures of performance. At an applied level, this research provides insights for military commanders that can potentially enhance agility and adaptability.

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This report presents the results of research projects conducted by The Australian Cooperative Research Centre for Construction Innovation, Queensland University of Technology, RMIT University, Queensland Government Department of Main Roads and Queensland Department of Public Works. The research projects aimed at developing a methodology for assessing variation and risk in investment in road network, including the application of the method in assessing road network performance and maintenance and rehabilitation costs for short- and long-term future investment.

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Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

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An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

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In my work with secondary school students who have disengaged from mainstream classrooms, I have often been surprised at the ways they enthusiastically engage with the projects on offer. They have demonstrated that, in apparent contradiction of their classroom behaviour, they still maintain hope in achieving a positive outcome from education. In a long-running schools-university project employing a “students-as-researchers” approach to investigating educational disadvantage, “at-risk” students have produced high quality results. Naturally, I wanted to know what it was about this sort of pedagogy that seemed to work for them. In this chapter, then, I outline the project and discuss some reasons for disengagement. I then address the features of the project that the participants themselves have identified as being instrumental in their re-engagement with formal education. Finally, I consider how these features may be transposed to maintaining the educational engagement of at-risk students in mainstream classrooms.

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Queensland Department of Main Roads, Australia, spends approximately A$ 1 billion annually for road infrastructure asset management. To effectively manage road infrastructure, firstly road agencies not only need to optimise the expenditure for data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. This paper presents the results of case studies in using the probability-based method for an integrated approach (i.e. assessing optimal costs of pavement strength data collection; calibrating deterioration prediction models that suit local condition and assessing risk-adjusted budget estimates for road maintenance and rehabilitation for assessing life-cycle budget estimates). The probability concept is opening the path to having the means to predict life-cycle maintenance and rehabilitation budget estimates that have a known probability of success (e.g. produce budget estimates for a project life-cycle cost with 5% probability of exceeding). The paper also presents a conceptual decision-making framework in the form of risk mapping in which the life-cycle budget/cost investment could be considered in conjunction with social, environmental and political issues.

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A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.