886 resultados para value and price


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Vols. 1-11 compiled and annotated by J. Proffatt; v. 12-100 by A. C. Freeman

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At head of title: Carnegie endowment for international peace. Division of economics and history.

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Includes index.

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To evaluate an investment project in the competitive electricity market, there are several key factors that affects the project's value: the present value that the project could bring to investor, the possible future course of actions that investor has and the project's management flexibility. The traditional net present value (NPV) criteria has the ability to capture the present value of the project's future cash flow, but it fails to assess the value brought by market uncertainty and management flexibility. By contrast with NPV, the real options approach (ROA) method has the advantage to combining the uncertainty and flexibility in evaluation process. In this paper, a framework for using ROA to evaluate the generation investment opportunity has been proposed. By given a detailed case study, the proposed framework is compared with NPV and showing a different results

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Purpose – The purpose of this paper is to explore the role and relevance of external standards in demonstrating the value and impact of academic library services to their stakeholders. Design/methodology/approach – Two UK standards, Charter Mark and Customer Service Excellence, are evaluated via an exploratory case study, employing multiple data collection techniques. Methods and results of phases 1-2 of a three phase research project are outlined. Findings – Despite some limitations, standards may assist the manager in demonstrating the value, impact and quality of academic libraries in a recessional environment. Active engagement and partnership with customers is imperative if academic libraries are to be viewed as vital to their parent organisations and thus survive. Originality/value – This paper provides a systematic evaluation of the role of external accreditation standards in measuring academic library service value and impact.

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After its privatization in 1989, the water and sewerage industry of England and Wales faced a new regulatory régime and implemented a substantial capital investment program aimed at improving water and environmental standards. A new RPI + K regulatory pricing system was designed to compensate the industry for its increased capital costs, encourage increased efficiency, and maintain fair prices for customers. This paper evaluates how successful privatization and the resulting system of economic regulation has been. Estimates of productivity growth, derived with quality adjusted output indices, suggest that despite reductions in labor usage, total factor productivity growth has not improved since privatization. Moreover, total price performance indices reveal that increases in output prices have outstripped increases in input costs, a trend which is largely responsible for the increase in economic profits that has occurred since privatization. * We would like to thank Emmanuel Thanassoulis, Joshy Easaw, Jim Love, John Sawkins, and an anonymous referee for helpful comments on earlier drafts of this paper. The usual disclaimer applies.

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This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.