Organic farming and multicriteria decisions: An economic survey

Organic food production is a sphere where decision making is multi-facetted and complex. This applies to producers, political decision makers and consumers alike. This paper provides an overview of the economic methods that can aid such multi criteria decision making. We first provide an outline of the many different Multi-Criteria Analysis (MCA) techniques available and their relative advantages and disadvantages. In addition, theoretical and practical problems related to the use of Cost-Benefit Analysis (CBA) and MCA respectively are briefly discussed. We then review the MCA literature on case studies on organic farming. Based on this review we provide directional markers for future research where MCA may possibly be applied and adapted in order to provide useful knowledge and support for decision makers in the context of organic farming

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

On The Applicability of Data Envelopment Analysis for Multiple Attriliute Decision Making in the Context of Information Systems Appraisals

This article elaborates on the applicability of basic and extended data envelopment analysis (DEA) models for various information system (IS) decision use-cases including illustrative examples from an enterprise resource planning (ERP) software investment appraisal. The usage of data envelopment analysis models and their extensions for IS decisions remains limited. This omission seems critical in particular for two reasons. First, organizational studies have shown that in practice business management fails to appreciate the portfolio of investment appraisal techniques available. Second, DEA based methodologies, especially new extensions, promise valuable insights to support the complex IS decision problem. The results indicate DEA applicability in a number of use-cases, e.g. for structural analysis of system alternatives or validation of ranking outcomes

REGIONAL DISPARITIES OF AGRICULTURAL PERFORMANCE IN ROMANIA

The accession to the European Union has opened new challenges for Romanianagriculture, which must implement the principles of the Common Agricultural Policy. These principlesaim at achieving high performance agriculture, capable to ensure food security for the population andto adequately develop the rural area. The paper intends to analyse the performance of Romanianagriculture in relation to the agriculture in the European Union and to highlight the recorded regionaldisparities in order to fully exploit the potential of agriculture. Data Envelopment Analysis is the usedmethod, which provides information for the relative assessment of performance in relation to thedecision-making units, considered a gauge. The results of the analysis show the poor performance ofagriculture in Romania, and the efficiency recorded at the level of the development regions varies.agriculture, Data Envelopment Analysis, sustainable performance, efficiency frontier, developingregions

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions

WHY FUZZY ANALYTIC HIERARCHY PROCESS APPROACH FOR TRANSPORT PROBLEMS?

The evaluation of transport projects has become increasingly complex. Different aspects have to be taken into account and the consequences of the problems are usually far reaching and the different policy alternatives are numerous and difficult to predict. Several pressure or action groups have also emerged causing an even more complex decision making process. The use of multi criteria analysis for the evaluation of transport projects has increased due to this increasing complexity of the problem situation. At the same time, the importance of stakeholders within this evaluation process should have been recognized. Researches on transport projects are generally carried out to provide information to policymakers that have to operate within restrictive parameters (political, economical, social, etc…). Researchers should therefore take greater account of the different priorities of stakeholders such as policymakers, private enterprises and households. These stakeholders should be incorporated explicitly in the evaluation process. The Analytic Hierarchy Process is one of the Fuzzy Multiple Criteria Decision Making methods. It can be applied in a very broad range of applications of decision problems. Logistics, urban planning, public politics, marketing, finance, education, economics are a part of this wide application area. In transport subjects it can be used for the evaluation of transport policy measures or decision making problems. Due to its wide range application area, it has been an exciting research subject for many different field researchers. The aim of this paper is to introduce AHP method and to offer how to benefit it for the preference of urban planners in transport problems. This paper is composed of two main parts. First part consists of the literature survey regarding with the AHP and its application areas. The advantage of methods had been mentioned. Second part focuses on a sample application of AHP technique. The study uses AHP technique to determine the selection criteria in the transhipment port selection decision-making process. Keywords: Analytic Hierarchy Process, Multi criteria analysis, Transshipment port selection.

Evaluating the Efficiency of Candidates for Graduate Study via Data Envelopment Analysis

© ASEE 2007In this paper, we present a DEA approach to measure the relative efficiency of applicants to the graduate programs in engineering. The proposed performance criteria are determined depending on the current evaluation criteria in the School of Engineering at the University of Bridgeport. The steps and implementation of the proposed methodology are explained with the help of a numerical example for the Fall 2004 semester

A dynamic performance evaluation of distress prediction models

YesSo far, the dominant comparative studies of competing distress prediction models (DPMs) have been restricted to the use of static evaluation frameworks and as such overlooked their performance over time. This study fills this gap by proposing a Malmquist Data Envelopment Analysis (DEA)-based multi-period performance evaluation framework for assessing competing static and dynamic statistical DPMs and using it to address a variety of research questions. Our findings suggest that (1) dynamic models developed under duration-dependent frameworks outperform both dynamic models developed under duration-independent frameworks and static models; (2) models fed with financial accounting (FA), market variables (MV), and macroeconomic information (MI) features outperform those fed with either MVMI or FA, regardless of the frameworks under which they are developed; (3) shorter training horizons seem to enhance the aggregate performance of both static and dynamic models

The Use of Data Envelopment Analysis for Product Recovery

Copyright 2003 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.The latest enhancements in industrial technologies, especially the ones in electronics industry, have provided organizations with the ability to manufacture faster and more economical products. This fact, coupled with the growing interest and demand for the latest technology, have led electronic equipment manufacturers to start producing “hightech” and “personalized” products at an increasing rate. This has led to a high rate of obsolescence for electronic products worldwide, even though the majority of these “obsolete” products still function. In this paper, we investigate a product recovery facility where the end-of-life (EOL) products are taken back from the last users and are brought into the facility for processing. We assume that there are multiple types of EOL products and that a combination of these can be disassembled to provide for a sufficient number of demanded components and materials. We then present a data envelopment analysis (DEA) algorithm to determine the number and types of the EOL products that will be required to fulfill the demand. A numerical example is presented to demonstrate the functionality of the methodology.http://dx.doi.org/10.1117/12.51653