Multicriteria ranking using weights which minimize the score range

Various schemes have been proposed for generating a set of non-subjective weights when aggregating multiple criteria for the purposes of ranking or selecting alternatives. The maximin approach chooses the weights which maximise the lowest score (assuming there is an upper bound to scores). This is equivalent to finding the weights which minimize the maximum deviation, or range, between the worst and best scores (minimax). At first glance this seems to be an equitable way of apportioning weight, and the Rawlsian theory of justice has been cited in its support.We draw a distinction between using the maximin rule for the purpose of assessing performance, and using it for allocating resources amongst the alternatives. We demonstrate that it has a number of drawbacks which make it inappropriate for the assessment of performance. Specifically, it is tantamount to allowing the worst performers to decide the worth of the criteria so as to maximise their overall score. Furthermore, when making a selection from a list of alternatives, the final choice is highly sensitive to the removal or inclusion of alternatives whose performance is so poor that they are clearly irrelevant to the choice at hand

Measuring Eco-efficiency of Production: A Frontier Approach

Eco-efficiency of production is an important concept both from the viewpoint of society and business community; but as yet, there is no unambiguous way to its measurement. The purpose of this paper is to present a general measurement framework based on production theory and the activity analysis approach. Although we exploit the existing methods and techniques, our approach diverges essentially from the usual treatments of the environmental performance of firms in the productive efficiency analysis. The main difference between our approach and the earlier studies is that we build on the definition of eco-efficiency as the ratio of economic value added to the environmental damage index. Related to this orientation, we also approach eco-efficiency from a more aggregate perspective. Our general framework is illustrated by an empirical application to the evaluation of eco-efficiency of road transportation in Finland.Eco-efficiency, Environmental Pressures, Aggregation, Benefit of the Doubt Weighting, Distance Function, Activity Analysis, Data Envelopment Analysis, Road transportation

Eco-Efficiency Analysis of Consumer Durables Using Absolute Shadow Prices

We develop a method for eco-efficiency analysis of consumer durables by utilizing Data Envelopment Analysis (DEA). In contrast to previous product efficiency studies, we consider the measurement problem from the perspective of a policy maker. The novel innovation of the paper is to measure efficiency in terms of absolute shadow prices that are optimized endogenously within the model to maximize efficiency of the good. Thus, the efficiency measure has a direct economic interpretation as a monetary loss due to inefficiency, expressed in some currency unit. The advantages as well as technical differences between the proposed approach and the traditional production-side methods are discussed in detail. We illustrate the approach by an application to eco-efficiency evaluation of Sport Utility Vehicles.Activity Analysis, Data Envelopment Analysis (DEA), Environmental efficiency, Product evaluation, Sport Utility Vehicles (SUVs)

Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis

Lack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the said problems in a multi-objective framework. Kekurangan keupayaan mendiskriminasi dan kelemahan pengagihan pemberat kekal sebagai isu utama dalam Analisis Penyampulan Data (DEA). Semenjak model DEA berbilang kriteria (MCDEA) pertama yang dibentuk pada akhir tahun 1990an, hanya pendekatan pengaturcaraangol; yakni, GPDEA-CCR dan GPDEA-BCC telah diperkenalkan bagi menyelesaikan masalah berkenaan dalam konteks berbilang kriteria

Quantitative selection of hedge funds using data envelopment analysis

Previous studies have documented that Data Envelopment Analysis(DEA) could be a good tool to evaluate fund performance,especially the performance of hedge funds as it can incorporatemultiple risk-return attributes characterizing hedge fund's nonnormal return distribution in an unique performance score. Thepurpose of this paper is to extend the use of DEA to the contextof hedge fund selection when investors must face multi-dimensionalconstraints, each one associated to a relative importance level.Unlike previous studies which used DEA in an empirical framework,this research puts emphasis on methodological issues. I showedthat DEA can be a good tailor-made decision-making tool to assistinvestors in selecting funds that correspond the most to theirfinancial, risk-aversion, diversification and investment horizonconstraints.hedge funds, data envelopment analysis, fund selection, performance measurement, alternative investment

Avoidable Mortality Risks and Measurement of Wellbeing and Inequality

This paper proposes a data envelopment method to separate avoidable and unavoidable mortality risks. As unavoidable mortality is the result of nature, only avoidable mortality is of relevance in measuring wellbeing and inequality. The new method is applied to a dataset consisting of life tables for 191 countries in the year 2000 to obtain a reference distribution of unavoidable mortality risks. The reference distribution is used to improve on the standard age-at-death measure to obtain an age-at-avoidable-death measure. Comparing with the original measure, age-at-avoidable-death provides a very different picture of wellbeing, and more so when it comes to inequality measures.

Valuing Environmental Factors in Cost-Benefit Analysis Using Data Envelopment Analysis

Environmental cost-benefit analysis (ECBA) refers to social evaluation of investment projects and policies that involve significant environmental impacts. Valuation of the environmental impacts in monetary terms forms one of the critical steps in ECBA. We propose a new approach for environmental valuation within ECBA framework that is based on data envelopment analysis (DEA) and does not demand any price estimation for environmental impacts using traditional revealed or stated preference methods. We show that DEA can be modified to the context of CBA by using absolute shadow prices instead of traditionally used relative prices. We also discuss how the approach can be used for sensitive analysis which is an important part of ECBA. We illustrate the application of the DEA approach to ECBA by means of a hypothetical numerical example where a household considers investment to a new sport utility vehicle.Cost-Benefit Analysis, Data Envelopment Analysis, Eco-Efficiency, Environmental Valuation, Environmental Performance, Performance Measurement

A bi-objective weighted model for improving the discrimination power in MCDEA

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordLack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the said problems in a multi-objective framework. We found GPDEA models to be invalid and demonstrate that our proposed bi-objective multiple criteria DEA (BiO-MCDEA) outperforms the GPDEA models in the aspects of discrimination power and weight dispersion, as well as requiring less computational codes. An application of energy dependency among 25 European Union member countries is further used to describe the efficacy of our approach. © 2013 Elsevier B.V. All rights reserved.US