765 resultados para Cost Planning
Resumo:
While a growing body of research analyses the functional mechanisms of the cultural or creative economy, there has been little attention devoted to understanding how local governments translate this work into policy. Moreover, research in this vein focuses predominately on Richard Florida's creative class thesis rather than considering the wider body of work that may influence policy. This article seeks to develop a deeper understanding of how municipalities conceptualize and plan for the cultural economy through the lens of two cities held up as model ‘creative cities’ — Austin, Texas and Toronto, Ontario. The work pays particular attention to how the cities adopt and adapt leading theories, strategies and discourses of the cultural economy. While policy documents indicate that the cities embrace the creative city model, in practice agencies tend to adapt conventional economic development strategies for cultural economy activity and appropriate the language of the creative city for multiple purposes.
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Since the widely publicized revitalization success story of the Guggenheim Museum Bilbao, local governments have been scrambling to create their own flagship cultural projects. Because of the broad public sponsorship of such projects, urban planners need a full understanding of the associated potentials and problems. However, little research specifically examines the localized complexities of the flagship cultural strategy. Examining projects in Los Angeles, San Francisco, and San Jose, California, the article illustrates that much more than impressive architecture influences their catalytic ability. Flagship cultural projects are highly dependent on a variety of contextual factors and, therefore, should be positioned to build on existing arts and related commercial activity rather than gamble that they will generate new development from scratch.
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The US National Institute of Standards and Technology (NIST) showed that, in 2004, owners and operations managers bore two thirds of the total industry cost burden from inadequate interoperability in construction projects from inception to operation, amounting to USD10.6 billion. Building Information Modelling (BIM) and similar tools were identified by Engineers Australia in 2005 as potential instruments to significantly reduce this sum, which in Australia could amount to total industry-wide cost burden of AUD12 billion. Public sector road authorities in Australia have a key responsibility in driving initiatives to reduce greenhouse gas emissions from the construction and operations of transport infrastructure. However, as previous research has shown the Environmental Impact Assessment process, typically used for project approvals and permitting based on project designs available at the consent stage, lacks Key Performance Indicators (KPIs) that include long-term impact factors and transfer of information throughout the project life cycle. In the building construction industry, BIM is widely used to model sustainability KPIs such as energy consumption, and integrated with facility management systems. This paper proposes that a similar use of BIM in early design phases of transport infrastructure could provide: (i) productivity gains through improved interoperability and documentation; (ii) the opportunity to carry out detailed cost-benefit analyses leading to significant operational cost savings; (iii) coordinated planning of street and highway lighting with other energy and environmental considerations; iv) measurable KPIs that include long-term impact factors which are transferable throughout the project life cycle; and (v) the opportunity for integrating design documentation with sustainability whole-of-life targets.
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Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.
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The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.
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The 2009 H!Nl 'swine flu' pandemic was the first influenza pandemic of the twenty-first centmy. Unlike the first influenza pandemic of the twentieth century, the so-called 'Spanish flu' which killed millions of people worldwide, the 2009 pandemic was relatively mild. While the mildness of the 2009 pandemic meant that the 'Yorld was spared from the impact of a high-mortality event that would cause widespread social and economic disruption, the 2009 pandemic did provide an opportunity to road-test pandemic readiness. In other work we have assessed Australia's pandemic plans and emergency management legislation, finding that both provide flexible and adaptive forms of regulation that are capable of adapting to the scale and severity of a pandemic or other public health emergency. 1 In this chapter we consider whether pandemic planning adequately addresses the needs of vulnerable individuals and groups, both within countries and between them. Central to this is the question of whether vulnerability is itself a useful concept for both law and policy, and if so, the implications of expressly incorporating the concept of vulnerability into pandemic planning.
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This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.
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This project is led by scientists in conservation decision appraisal and brings together a group of experts working across the Lake Eyre Basin (LEB). The LEB covers a sixth of Australia, with an array of globally significant natural values that are threatened by invasive plants, among other things. Managers at various levels are investing in attempts to control, contain and eradicate these invasive plant species, under severe time and resources limitations. To date there has been no basin-wide assessment of which weed management strategies and locations provide the best investments for maximising outcomes for biodiversity per unit cost. Further, there has been no assessment of the extent of ecosystem intactness that may be lost without effective invasive plant species management strategies. Given that there are insufficient resources to manage all invasive plant species everywhere, this information has the potential to improve current investment decisions. Here, we provide a prioritisation of invasive plant management strategies in the LEB. Prioritisation was based on cost-effectiveness for biodiversity benefits. We identify the key invasive plant species to target to protect ecosystem intactness across the bioregions of the LEB, the level of investment required and the likely reduction in invasive species dominance gained per dollar spent on each strategy. Our focus is on strategies that are technically and socially feasible and reduce the likelihood that high impact invasive plant species will dominate native ecosystems, and therefore change their form and function. The outputs of this work are designed to help guide decision-making and further planning and investment in weed management for the Basin. Experts in weed management, policy-making, community engagement, biodiversity and natural values of the Basin, attended a workshop and agreed upon 12 strategies to manage invasive plants. The strategies focused primarily on 10 weeds which were considered to have a high potential for broad, significant impacts on natural ecosystems in the next 50 years and for which feasible management strategies could be defined. Each strategy consisted of one or more supporting actions, many of which were spatially linked to IBRA (Interim Biogeographical Regionalisation of Australia) bioregions. The first strategy was an over-arching recommendation for improved mapping, information sharing, education and extension efforts in order to facilitate the more specific weed management strategies. The 10 more specific weed management strategies targeted the control and/or eradication of the following high-impact exotic plants: mesquite, parkinsonia, rubber vine, bellyache bush, cacti, mother of millions, chinee apple, athel pine and prickly acacia, as well as a separate strategy for eradicating all invasive plants from one key threatened ecological community, the GAB (Great Artesian Basin dependant) mound springs. Experts estimated the expected biodiversity benefit of each strategy as the reduction in area that an invasive plant species is likely to dominate in over a 50-year period, where dominance was defined as more than 30% coverage at a site. Costs were estimated in present day terms over 50 years largely during follow up discussions post workshop. Cost-effectiveness was then calculated for each strategy in each bioregion by dividing the average expected benefit by the average annual costs. Overall, the total cost of managing 12 invasive plant strategies over the next 50 years was estimated at $1.7 billion. It was estimated that implementation of these strategies would result in a reduction of invasive plant dominance by 17 million ha (a potential 32% reduction), roughly 14% of the LEB. If only targeting Weeds of National Significance (WONS), the total cost was estimated to be $113 million over the next 50 years. Over the next 50 years, $2.3 million was estimated to eradicate all invasive plant species from the Great Artesian Basin Mound Springs threatened ecological community. Prevention and awareness programs were another key strategy targeted across the Basin and estimated at $17.5 million in total over 50 years. The cost of controlling, eradicating and containing buffel grass were the most expensive, over $1.5 billion over 50 years; this strategy was estimated to result in a reduction in buffel grass dominance of a million ha in areas where this species is identified as an environmental problem. Buffel grass has been deliberately planted across the Basin for pasture production and is by far the most widely distributed exotic species. Its management is contentious, having economic value to many graziers while posing serious threats to biodiversity and sites of high cultural and conservation interest. The strategy for containing and locally eradicating buffel grass was a challenge to cost based on expert knowledge, possibly because of the dual nature of this species as a valued pastoral grass and environmental weed. Based on our conversations with experts, it appears that control and eradication programs for this species, in conservation areas, are growing rapidly and that information on the most cost-effective strategies for this species will continue to develop over time. The top five most cost-effective strategies for the entire LEB were for the management of: 1) parkinsonia, 2) chinee apple, 3) mesquite, 4) rubber vine and 5) bellyache bush. Chinee apple and mother of millions are not WONS and have comparatively small populations within the semi-arid bioregions of Queensland. Experts felt that there was an opportunity to eradicate these species before they had the chance to develop into high-impact species within the LEB. Prickly acacia was estimated to have one of the highest benefits, but the costs of this strategy were high, therefore it was ranked 7th overall. The buffel grass strategy was ranked the lowest (10th) in terms of cost effectiveness. The top five most cost-effective strategies within and across the bioregions were the management of: 1) parkinsonia in the Channel Country, 2) parkinsonia in the Desert Uplands, 3) mesquite in the Mitchell Grass Downs, 4) parkinsonia in the Mitchell Grass Downs, and 5) mother of millions in the Desert Uplands. Although actions for several invasive plant species like parkinsonia and prickly acacia were concentrated in the Queensland part of the LEB, the actions involved investing in containment zones to prevent the spread of these species into other states. In the NT and SA bioregions of the LEB, the management of athel pine, parkinsonia and cacti were the main strategies. While outside the scientific research goals of study, this work highlighted a number of important incidental findings that led us to make the following recommendations for future research and implementation of weed management in the Basin: • Ongoing stakeholder engagement, extension and participation is required to ensure this prioritisation effort has a positive impact in affecting on-ground decision making and planning. • Short term funding for weed management was identified as a major reason for failure of current efforts, hence future funding needs to be secure and ongoing. • Improved mapping and information sharing is essential to implement effective weed management. • Due to uncertainties in the outcomes and impacts of management options, strategies should be implemented as part of an adaptive management program. The information provided in this report can be used to guide investment for controlling high-impact invasive plant species for the benefits of biodiversity conservation. We do not present a final prioritisation of invasive plant strategies for the LEB, and we have not addressed the cultural, socio-economic or spatial components necessary for an implementation plan. Cost-effectiveness depends on the objectives used; in our case we used the intactness of ecosystems as a surrogate for expected biodiversity benefits, measured by the extent that each invasive plant species is likely to dominate in a bioregion. When other relevant factors for implementation are considered the priorities may change and some actions may not be appropriate in some locations. We present the costs, ecological benefits and cost-effectiveness of preventing, containing, reducing and eradicating the dominance of high impact invasive plants through realistic management actions over the next 50 years. In doing so, we are able to estimate the size of the weed management problem in the LEB and provide expert-based estimates of the likely outcomes and benefits of implementing weed management strategies. The priorities resulting from this work provide a prospectus for guiding further investment in management and in improving information availability.
Resumo:
This study elucidated the shadow price of greenhouse gas (GHG) emissions for 1,024 international companies worldwide that were surveyed from 15 industries in 37 major countries. Our results indicate that the shadow price of GHG at the firm level is much higher than indicated in previous studies. The higher shadow price was found in this study as a result of the use of Scope 3 GHG emissions data. The results of this research indicate that a firm would carry a high cost of GHG emissions if Scope 3 GHG emissions were the focus of the discussion of corporate social responsibility. In addition, such shadow prices were determined to differ substantially among countries, among sectors, and within sectors. Although a number of studies have calculated the shadow price of GHG emissions, these studies have employed country-level or industry-level data or a small sample of firm-level data in one country. This new data from a worldwide firm analysis of the shadow price of GHG emissions can play an important role in developing climate policy and promoting sustainable development.
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Both environmental economists and policy makers have shown a great deal of interest in the effect of pollution abatement on environmental efficiency. In line with the modern resources available, however, no contribution is brought to the environmental economics field with the Markov chain Monte Carlo (MCMC) application, which enables simulation from a distribution of a Markov chain and simulating from the chain until it approaches equilibrium. The probability density functions gained prominence with the advantages over classical statistical methods in its simultaneous inference and incorporation of any prior information on all model parameters. This paper concentrated on this point with the application of MCMC to the database of China, the largest developing country with rapid economic growth and serious environmental pollution in recent years. The variables cover the economic output and pollution abatement cost from the year 1992 to 2003. We test the causal direction between pollution abatement cost and environmental efficiency with MCMC simulation. We found that the pollution abatement cost causes an increase in environmental efficiency through the algorithm application, which makes it conceivable that the environmental policy makers should make more substantial measures to reduce pollution in the near future.
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This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.
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It is known that in an intertemporal competitive economy, a tradable permit system may not achieve efficiency without setting appropriate permit interest rates (i.e., rewards for holding permits). To find the rates, however, we need to know in advance the path of efficient permit prices, which is difficult to obtain. This study intends to solve this problem in two ways. First, we analyze a special case in which the permit interest rates are given by a simple rule. For example, if the marginal abatement cost of pollution emission is constant, then the appropriate rate is to equal the monetary interest rate. As is the case for global warming, if the damage is caused in the future far beyond the planning period of the environmental program, the appropriate rate coincides with the marginal self-recovery of environmental stock under certain conditions. As a second approach, we propose a tradable permit system with a permit bank, as a mechanism by which the permit interest rates are generated endogenously without governmental intervention other than the issuance of permits. However, we also show that this approach raises the problem of indeterminacy of the equilibrium. © 2013 Springer Science+Business Media Dordrecht.
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Japan's fishery harvest peaked in the late 1980s. To limit the race for fish, each fisherman could be provided with specific catch limits in the form of individual transferable quotas (ITQs). The market for ITQs would also help remove the most inefficient fishers. In this article we estimate the potential cost reduction associated with catch limits, and find that about 300 billion yen or about 3 billion dollars could be saved through the allocation and trading of individual-specific catch shares.
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This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.