75,871 research outputs found

    Multi-criteria analysis: a manual

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    Advancing impact assessments of non-native species: strategies for strengthening the evidence-base

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    The numbers and impacts of non-native species (NNS) continue to grow. Multiple ranking protocols have been developed to identify and manage the most damaging species. However, existing protocols differ considerably in the type of impact they consider, the way evidence of impacts is included and scored, and in the way the precautionary principle is applied. These differences may lead to inconsistent impact assessments. Since these protocols are considered a main policy tool to promote mitigation efforts, such inconsistencies are undesirable, as they can affect our ability to reliably identify the most damaging NNS, and can erode public support for NNS management. Here we propose a broadly applicable framework for building a transparent NNS impact evidence base. First, we advise to separate the collection of evidence of impacts from the act of scoring the severity of these impacts. Second, we propose to map the collected evidence along a set of distinguishing criteria: where it is published, which methodological approach was used to obtain it, the relevance of the geographical area from which it originates, and the direction of the impact. This procedure produces a transparent and reproducible evidence base which can subsequently be used for different scoring protocols, and which should be made public. Finally, we argue that the precautionary principle should only be used at the risk management stage. Conditional upon the evidence presented in an impact assessment, decision-makers may use the precautionary principle for NNS management under scientific uncertainty regarding the likelihood and magnitude of NNS impacts. Our framework paves the way for an improved application of impact assessments protocols, reducing inconsistencies and ultimately enabling more effective NNS management

    THE CASE FOR AND COMPONENTS OF A PROBABILISTIC AGRICULTURAL OUTLOOK PROGRAM

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    An operational program to develop and disseminate probabilistic outlook information for agricultural commodities would allow decision makers to better comprehend the degree of uncertainty associated with future prices. While there are psychological limitations to the estimation or probabilities, this is a skill that can be taught and developed, particularly among experienced forecasters such as outlook specialists. Techniques are available for eliciting probabilities, and weather forecasting experience demonstrates that experts can quantify probabilities in a reliable manner. The components of a program to develop and disseminate outlook probabilities should include a survey of user needs, training programs for participating outlook specialists, and user educational programs. Further research is needed to develop elicitation techniques, and to evaluate costs and benefits.Teaching/Communication/Extension/Profession,

    Consumer credit in comparative perspective

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    We review the literature in sociology and related fields on the fast global growth of consumer credit and debt and the possible explanations for this expansion. We describe the ways people interact with the strongly segmented consumer credit system around the world—more specifically, the way they access credit and the way they are held accountable for their debt. We then report on research on two areas in which consumer credit is consequential: its effects on social relations and on physical and mental health. Throughout the article, we point out national variations and discuss explanations for these differences. We conclude with a brief discussion of the future tasks and challenges of comparative research on consumer credit.Accepted manuscrip

    National Culture\u27s Impact on Effectiveness of Supply Chain Disruption Management

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    The purpose of this research is to understand the national cultural antecedents that may help explain differences in supply chain disruptions mitigation abilities of companies from different countries. An analysis of survey data on disruption planning and response collected from various organizations worldwide was performed using weighted least square regression and factor analysis. We find that culture influences disruption planning and response. Statistical findings suggest that differences in disruption planning and response abilities between companies from different countries could be partly attributed to national culture. All five Hofstede’s dimensions of national culture, i.e., Power Distance, Individualism, Masculinity, Uncertainty Avoidance, and Long-term Orientation were shown to have a significant positive effect on disruption planning and response. National cultural dimensions and economic status of a country could be effectively used to predict disruption planning and response abilities of companies in various countries. Managers could benefit from our research as it could help them assess disruptions mitigation abilities of their partners located in other countries. Increasing international trade and globalization of supply chains accentuate the importance of our research

    Targeting Conservation Investments in Heterogeneous Landscapes: A distance function approach and application to watershed management

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    To achieve a given level of an environmental amenity at least cost, decision-makers must integrate information about spatially variable biophysical and economic conditions. Although the biophysical attributes that contribute to supplying an environmental amenity are often known, the way in which these attributes interact to produce the amenity is often unknown. Given the difficulty in converting multiple attributes into a unidimensional physical measure of an environmental amenity (e.g., habitat quality), analyses in the academic literature tend to use a single biophysical attribute as a proxy for the environmental amenity (e.g., species richness). A narrow focus on a single attribute, however, fails to consider the full range of biophysical attributes that are critical to the supply of an environmental amenity. Drawing on the production efficiency literature, we introduce an alternative conservation targeting approach that relies on distance functions to cost-efficiently allocate conservation funds across a spatially heterogeneous landscape. An approach based on distance functions has the advantage of not requiring a parametric specification of the amenity function (or cost function), but rather only requiring that the decision-maker identify important biophysical and economic attributes. We apply the distance-function approach empirically to an increasingly common, but little studied, conservation initiative: conservation contracting for water quality objectives. The contract portfolios derived from the distance-function application have many desirable properties, including intuitive appeal, robust performance across plausible parametric amenity measures, and the generation of ranking measures that can be easily used by field practitioners in complex decision-making environments that cannot be completely modeled. Working Paper # 2002-01

    Socio‐economic impact classification of alien taxa (SEICAT)

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    1 Many alien taxa are known to cause socio‐economic impacts by affecting the different constituents of human well‐being (security; material and non‐material assets; health; social, spiritual and cultural relations; freedom of choice and action). Attempts to quantify socio‐economic impacts in monetary terms are unlikely to provide a useful basis for evaluating and comparing impacts of alien taxa because they are notoriously difficult to measure and important aspects of human well‐being are ignored. 2 Here, we propose a novel standardised method for classifying alien taxa in terms of the magnitude of their impacts on human well‐being, based on the capability approach from welfare economics. The core characteristic of this approach is that it uses changes in peoples' activities as a common metric for evaluating impacts on well‐being. 2 Impacts are assigned to one of five levels, from Minimal Concern to Massive, according to semi‐quantitative scenarios that describe the severity of the impacts. Taxa are then classified according to the highest level of deleterious impact that they have been recorded to cause on any constituent of human well‐being. The scheme also includes categories for taxa that are not evaluated, have no alien population, or are data deficient, and a method for assigning uncertainty to all the classifications. To demonstrate the utility of the system, we classified impacts of amphibians globally. These showed a variety of impacts on human well‐being, with the cane toad (Rhinella marina) scoring Major impacts. For most species, however, no studies reporting impacts on human well‐being were found, i.e. these species were data deficient. 2 The classification provides a consistent procedure for translating the broad range of measures and types of impact into ranked levels of socio‐economic impact, assigns alien taxa on the basis of the best available evidence of their documented deleterious impacts, and is applicable across taxa and at a range of spatial scales. The system was designed to align closely with the Environmental Impact Classification for Alien Taxa (EICAT) and the Red List, both of which have been adopted by the International Union of Nature Conservation (IUCN), and could therefore be readily integrated into international practices and policies

    Forecasting Metals Returns A Bayesian Decision Theoretic Approach

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    Turning points in commodity returns are important for decisions of policy makers, commodity producers and consumers reliant on medium term outcomes. However, forecasting of turning points has been a neglected feature of forecasting, especially in commodity markets. I forecast turning points in metals price returns using Bayesian Decision Theory. The method produces a probabilistic statement about our belief of a turning point occurring in the next period which, combined with a decision rule based on a loss function generates optimal turning point forecasts. This method produces positive results in forecasting turning points in metals returns, with the simple linear models investigated producing more accurate turning point forecasts than naive models across a number of different evaluation methods for the general case and for the specific example of a producing firm.
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