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The concept of eco-efficiency can be defined with the “product value/environmental influence” ratio. Different models have been proposed to measure eco-efficiency. The main difference among them is the weighting system used to aggregate the environmental results. Data envelopment analysis (DEA) permits this aggregation without requiring a subjective judgment about the weights. In this study, we applied a DEA model to Spanish Mahón-Menorca cheese production to determine the most eco-efficient production techniques. To this end, 16 scenarios of Mahón-Menorca cheese production were built regarding technical (degree of automation) and cleaner production criteria. The environmental impacts were assessed by means of life cycle assessment. We carried out an economic assessment by determining the economic value added and the net income for each scenario. The results are referred to as 1 kilogram (kg) cheese ripened over 105 days. Through DEA, an eco-efficiency ratio between 0 and 1 was obtained. Three scenarios were found to be eco-efficient, with a high degree of automation (enclosed vat and molding and demolding machines) and accelerated cheese ripening. We used Monte Carlo simulation to carry out a sensitivity analysis to compare the influence of price changes on the eco-efficiency ratio. The results emphasize the consistency and stability of the eco-efficient scenarios.
Aggregation of environmental pressures into a single environmental damage index is a major challenge of eco-efficiency measurement. This article examines how the data envelopment analysis (DEA) method can be adapted for this purpose. DEA accounts for substitution possibilities between different natural resources and emissions and does not require subjective judgment about the weights. Although DEA does not require subjective or normative judgment, soft weight restrictions can be incorporated into the framework. The proposed approach is illustrated by an application to assessing ecoefficiency of road transportation in the three largest towns of eastern Finland.
Introduces a bold, new model for energy industry pollution prevention and sustainable growth Balancing industrial pollution prevention with economic growth is one of the knottiest problems faced by industry today. This book introduces a novel approach to using data envelopment analysis (DEA) as a powerful tool for achieving that balance in the energy industries—the world’s largest producers of greenhouse gases. It describes a rigorous framework that integrates elements of the social sciences, corporate strategy, regional economics, energy economics, and environmental policy, and delivers a methodology and a set of strategies for promoting green innovation while solving key managerial challenges to greenhouse gas reduction and business growth. In writing this book the authors have drawn upon their pioneering work and considerable experience in the field to develop an unconventional, holistic approach to using DEA to assess key aspects of sustainability development. The book is divided into two sections, the first of which lays out a conventional framework of DEA as the basis for new research directions. In the second section, the authors delve into conceptual and methodological extensions of conventional DEA for solving problems of environmental assessment in all contemporary energy industry sectors. Introduces a powerful new approach to using DEA to achieve pollution prevention, sustainability, and business growth Covers the fundamentals of DEA, including theory, statistical models, and practical issues of conventional applications of DEA Explores new statistical modeling strategies and explores their economic and business implications Examines applications of DEA to environmental analysis across the complete range of energy industries, including coal, petroleum, shale gas, nuclear energy, renewables, and more Summarizes important studies and nearly 800 peer reviewed articles on energy, the environment, and sustainability Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis is must-reading for researchers, academics, graduate students, and practitioners in the energy industries, as well as government officials and policymakers tasked with regulating the environmental impacts of industrial pollution.
This article examines the concept of eco-efficiency at a regional level as an approach to promote the sustainable transformation of regions, using the regions of Poland as an example. The data envelopment analysis (DEA) method--the input-oriented Charnes, Cooper, and Rhodes (CCR) model--was chosen as the eco-efficiency analysis tool because of its high capability to measure the regional eco-efficiency. The research process was divided into two stages. First, the chosen instruments of mathematical statistics (e.g., Hellwig's method and coefficient of determination) were applied to ensure an appropriate combination of environmental and economic indicators of the eco-efficiency equation. Next, the CCR model was used to calculate the eco-efficiency scores. The results of the study have revealed that the regions of Lubuskie, Mazowieckie, Śląskie, Warmińsko-Maurskie, and Wielkopolskie are relatively eco-efficient, whereas the remaining regions use too many environmental resources in relation to the produced value of goods and services. Six of the eleven eco-inefficient regions in Poland have increasing returns to scale, that is, the usage of natural resources connected with the negative impact upon the environment rises slower than the values of goods and services. Notwithstanding, it is beneficiary from the perspective of sustainability. The obtained research results are a valuable source of management information for the creation of regional environmental protection strategies and a basis for searching for the causes of eco-inefficiency.
A central asset of eco-efficiency analysis is that it does not depend on a specific evaluation of environmental impacts against economic effects. Several evaluation methods may be used, including those based on willingness-to-pay, panel procedures, and public statements on policy goals. This volume covers all aspects of eco-efficiency analysis and offers a global perspective on the subject.
Efficiency and productivity assessment are essential to ensure the long-term financial sustainability of countries, services and processes. In the last few years, there has been an increasing interest in the environmental effects of economic activities, and the need to assess the environmental and energy efficiency has been internationally recognized. Energy and environmental efficiency assessments of decision-making units (DMUs), such as countries, utilities, processes and services are relevant and have strong implications for companies, regulators, stakeholders, policy makers, and customers. To improve both the decision-making process and the management of DMUs, fundamental and practical knowledge about energy and environmental efficiency and productivity is essential
This open access book analyzes and seeks to consolidate the use of robust quantitative tools and qualitative methods for the design and assessment of energy and climate policies. In particular, it examines energy and climate policy performance and associated risks, as well as public acceptance and portfolio analysis in climate policy, and presents methods for evaluating the costs and benefits of flexible policy implementation as well as new framings for business and market actors. In turn, it discusses the development of alternative policy pathways and the identification of optimal switching points, drawing on concrete examples to do so. Lastly, it discusses climate change mitigation policies’ implications for the agricultural, food, building, transportation, service and manufacturing sectors.
This is the first book to fully introduce a newly developed distance friction minimization (DFM) model, which is one of the new efficiency improvement projection approaches in data envelopment analysis (DEA). The DFM model can produce a most effective solution in efficiency improvement projections for inefficient spatial entities (decision-making units). The book provides a set of fresh contributions to a quantitative assessment of the performance of such policy entities. First it offers a state-of-the art overview of current DEA models and approaches, followed by the operational design of various new types of DEA models, each of them addressing weaknesses in traditional DEA approaches. Then it illustrates the assessment potential of DEA — and its new variants, in particular, the DFM model and subsequent extensions — on the basis of a broadly composed collection of empirical case studies, centering mainly but not exclusively on Japan and other Asian nations.
This book outlines the principles of eco-efficiency and presents case studies of their application from a number of international companies, including 3M and the Dow Chemical Company. The term "eco-efficiency" describes business activities that create economic value while reducing ecological impact and resource use. This book outlines the principles of eco-efficiency and presents case studies of their application from a number of international companies, including 3M and the Dow Chemical Company. It also discusses the value of partnerships--with other companies, business associations, communities, regulators, and environmental and other nongovernmental groups. In the conclusion, the authors argue that business must become more eco-efficient and that governments need to change the conditions under which business operates, including tax and regulatory regimes, to make them more conducive to eco-efficiency.
In today’s competitive environment, airlines are doing everything they can to improve efficiency and productivity. Productivity and Efficiency Measurement of Airlines: Data Envelopment Analysis using R identifies and explains sources of airline efficiency and helps achieve these goals through the use of state-of-the-art measurement techniques. Each chapter measures airline performance through the data envelopment analysis (DEA) model and other DEA variants. This book thoroughly discusses topics such as cost and revenue efficiency performance, carbon emissions performance management, and complex airline data analysis, employing appropriate models for each. Model methodologies are also discussed. The in-depth coverage is useful for all audiences, including students with a basic understanding of models, researchers and airline operators and management. Productivity and Efficiency Measurement of Airlines: Data Envelopment Analysis using R provides R codes to help readers generate results and quantify efficient practices. These results provide airline decision-makers with the essential information they need to create better policies and avoid underperforming practices. Thoroughly summarizes key DEA measurement models for productivity and efficiency ofairlines Guides users in generating airline performance results using DEA model and its variants Features R codes useful for generating empirical results, and best practices, promoting qualitypolicy and management decisions