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Illustrative Case Study (illustrative + case_study)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	40%

Selected Abstracts

RESEARCH VULNERABILITY: AN ILLUSTRATIVE CASE STUDY FROM THE SOUTH AFRICAN MINING INDUSTRY

DEVELOPING WORLD BIOETHICS, Issue 3 2007
LYN HORN
ABSTRACT The concept of ,vulnerability' is well established within the realm of research ethics and most ethical guidelines include a section on ,vulnerable populations'. However, the term ,vulnerability', used within a human research context, has received a lot of negative publicity recently and has been described as being simultaneously ,too broad' and ,too narrow'.1 The aim of the paper is to explore the concept of research vulnerability by using a detailed case study , that of mineworkers in post-apartheid South Africa. In particular, the usefulness of Kipnis's taxonomy of research vulnerability will be examined.2 In recent years the volume of clinical research on human subjects in South Africa has increased significantly. The HIV and TB pandemics have contributed to this increase. These epidemics have impacted negatively on the mining industry; and mining companies have become increasingly interested in research initiatives that address these problems. This case study explores the potential research vulnerability of mineworkers in the context of the South African mining industry and examines measures that can reduce this vulnerability. [source]

A metapopulation perspective for salmon and other anadromous fish

FISH AND FISHERIES, Issue 4 2007
Nicolas Schtickzelle
Abstract Salmonids are an important component of biodiversity, culture and economy in several regions, particularly the North Pacific Rim. Given this importance, they have been intensively studied for about a century, and the pioneering scientists recognized the critical link between population structure and conservation. Spatial structure is indeed of prime importance for salmon conservation and management. At first glance, the essence of the metapopulation concept, i.e. a population of populations, widely used on other organisms like butterflies, seems to be particularly relevant to salmon, and more generally to anadromous fish. Nevertheless, the concept is rarely used, and barely tested. Here, we present a metapopulation perspective for anadromous fish, assessing in terms of processes rather than of patterns the set of necessary conditions for metapopulation dynamics to exist. Salmon, and particularly sockeye salmon in Alaska, are used as an illustrative case study. A review of life history traits indicates that the three basic conditions are likely to be fulfilled by anadromous salmon: (i) the spawning habitat is discrete and populations are spatially separated by unsuitable habitat; (ii) some asynchrony is present in the dynamics of more or less distant populations and (iii) dispersal links populations because some salmon stray from their natal population. The implications of some peculiarities of salmon life history traits, unusual in classical metapopulations, are also discussed. Deeper understanding of the population structure of anadromous fish will be advanced by future studies on specific topics: (i) criteria must be defined for the delineation of suitable habitats that are based on features of the biotope and not on the presence of fish; (ii) the collection of long-term data and the development of improved methods to determine age structure are essential for correctly estimating levels of asynchrony between populations and (iii) several key aspects of dispersal are still poorly understood and need to be examined in detail: the spatial and temporal scales of dispersal movements, the origin and destination populations instead of simple straying rates, and the relative reproductive success of immigrants and residents. [source]

On the use of reactive power as an endogenous variable in short-term load forecasting

INTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 5 2003
P. Jorge Santos
Abstract In the last decades, short-term load forecasting(STLF) has been the object of particular attention in the power systems field. STLF has been applied almost exclusively to the generation sector, based on variables, which are transversal to most models. Among the most significant variables we can find load, expressed as active power (MW), as well as exogenous variables, such as weather and economy-related ones; although the latter are applied in larger forecasting horizons than STLF. In this paper, the application of STLF to the distribution sector is suggested including inductive reactive power as a forecasting endogenous variable. The inclusion of this additional variable is mainly due to the evidence that correlations between load and weather variables are tenuous, due to the mild climate of the actual case-study system and the consequent feeble penetration of electrical heating ventilation and air conditioning loads. Artificial neural networks (ANN) have been chosen as the forecasting methodology, with standard feed forward back propagation algorithm, because it is a largely used method with generally considered satisfactory results. Usually the input vector to ANN applied to load forecasting is defined in a discretionary way, mainly based on experience, on engineering judgement criteria and on concern about the ANN dimension, always taking into consideration the apparent (or actually evaluated) correlations within the available data. The approach referred in the paper includes pre-processing the data in order to influence the composition of the input vector in such a way as to reduce the margin of discretion in its definition. A relative entropy analysis has been performed to the time series of each variable. The paper also includes an illustrative case study. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Holistic investment assessment: optimization, risk appraisal and decision making

MANAGERIAL AND DECISION ECONOMICS, Issue 6 2009
Georgios Tziralis
Abstract On deciding for the most appropriate investment when capital restrictions exist, investors define their alternatives and analyze each one of them. Traditionally, the definition, appraisal and analysis stages are treated separately. Herein, an innovative holistic method is proposed for bridging these stages. Within this method, investment attributes definition occurs by genetic algorithm optimization, while the analysis of the investment is realized through simulation. The method also proposes the NPV Expected Shortfall and the NPV Risk Preference Index as investment evaluation criteria. An illustrative case study of two mutually exclusive renewable energy investment scenarios is also used for demonstration purposes. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Exploring consumer knowledge structures using associative network analysis

PSYCHOLOGY & MARKETING, Issue 4 2010
Thorsten A. Teichert
This paper offers a new perspective on consumer knowledge analysis that combines Human Associative Memory (HAM) models from cognitive psychology with network analytic approaches in order to gain deeper insights into consumers" mental representations, such as brand images. An illustrative case study compares the associative networks of a manufacturer brand with a retail brand and is used to demonstrate the application and interpretation of various network measures. Network analysis is conducted on three levels: Node-level analysis yields insights about salient brand image components that can be affected through short-term marketing activities. Group-level analysis is concerned with brand image dimensions that characterize a brand and can be strategically influenced in the medium term. Finally, network-level analysis examines the network structure as a whole, drawing parallels to brand imagery, which needs to be managed over the long term. Management implications are derived and suggestions for further research are provided. © 2010 Wiley Periodicals, Inc. [source]