291 resultados para Cost Cutting

em Queensland University of Technology - ePrints Archive


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Value Management (VM) is a proven methodology that provides a structured framework using supporting tools and techniques that facilitate effective decision-making in many types of projects, thus achieving ‘best value’ for clients. It offers an exceptionally robust approach to exploring the need and function of projects to be aligned with client’s objectives. The functional analysis and creativity phases of VM are crucial as it focused on utilising innovative thinking to understand the objectives of clients’ projects and provide value-adding solutions at the early discovery stages of projects. There is however a perception of VM as just being another cost-cutting tool, which has overshadowed the fundamental benefits of the method, therefore negating both influence and wider use in the construction industry. This paper describes findings from a series of case studies conducted at project and corporate levels of a current public funded infrastructure projects in Malaysia. The study aims to investigate VM processes practised by the project client organisation and evaluate the effects of project team involvement in VM workshops during the design-stage of these projects. The focus of the study is on how issues related to ‘upstream’ infrastructure design aimed at improving ‘downstream’ construction process on-site, are being resolved through multi-disciplinary team consideration and decision-making. Findings from the case studies indicate that the mix of disciplines of project team members at a design-stage of a VM workshop has minimal influence on improving construction processes. However, the degree of interaction, institutionalized thinking, cultural dimensions and visualization aids adopted, have a significant impact in maximizing creativity amongst project team members during VM workshop. The case studies conducted for this research have focused on infrastructure projects that utilise traditional VM workshop as client’s chosen VM methodology to review and develop designs. Documents review and semi-structured interview with project teams are used as data collection techniques for the case study. The significant outcomes of this research are expected to offer alternative perspectives for construction professionals and clients to minimise the constraints and strengthen strategies for implementing VM on future projects.

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International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

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Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).