Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis (Wiley Series in Operations Research and Management Science)

**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. Content: Intro TITLE PAGE COPYRIGHT PAGE CONTENTS PREFACE SECTION I DATA ENVELOPMENT ANALYSIS (DEA) CHAPTER 1 GENERAL DESCRIPTION 1.1 INTRODUCTION 1.2 STRUCTURE 1.3 CONTRIBUTIONS IN SECTIONS I AND II 1.4 ABBREVIATIONS AND NOMENCLATURE 1.4.1 Abbreviations Used in This Book 1.4.2 Nomenclature Used in This Book 1.4.3 Mathematical Concerns 1.5 SUMMARY CHAPTER 2 OVERVIEW 2.1 INTRODUCTION 2.2 WHAT IS DEA? 2.3 REMARKS 2.4 REFORMULATION FROM FRACTIONAL PROGRAMMING TO LINEAR PROGRAMMING 2.5 REFERENCE SET 2.6 EXAMPLE FOR COMPUTATIONAL DESCRIPTION 2.7 SUMMARY CHAPTER 3 HISTORY 3.1 INTRODUCTION3.2 ORIGIN OF L1 REGRESSION 3.3 ORIGIN OF GOAL PROGRAMMING 3.4 ANALYTICAL PROPERTIES OF L1 REGRESSION 3.5 FROM L1 REGRESSION TO L2 REGRESSION AND FRONTIER ANALYSIS 3.5.1 L2 Regression 3.5.2 L1-Based Frontier Analyses 3.6 ORIGIN OF DEA 3.7 RELATIONSHIPS BETWEEN GP AND DEA 3.8 HISTORICAL PROGRESS FROM L1 REGRESSION TO DEA 3.9 SUMMARY CHAPTER 4 RADIAL MEASUREMENT 4.1 INTRODUCTION 4.2 RADIAL MODELS: INPUT-ORIENTED 4.2.1 Input-Oriented RM(v) under Variable RTS 4.2.2 Underlying Concept 4.2.3 Input-Oriented RM(c) under Constant RTS 4.3 RADIAL MODELS: DESIRABLE OUTPUT-ORIENTED4.3.1 Desirable Output-oriented RM(v) under Variable RTS 4.3.2 Desirable Output-oriented RM(c) under Constant RTS 4.4 COMPARISON BETWEEN RADIAL MODELS 4.4.1 Comparison between Input-Oriented and Desirable Output-Oriented Radial Models 4.4.2 Hybrid Radial Model: Modification 4.5 MULTIPLIER RESTRICTION AND CROSS-REFERENCE APPROACHES 4.5.1 Multiplier Restriction Methods 4.5.2 Cone Ratio Method 4.5.3 Cross-reference Method 4.6 COST ANALYSIS 4.6.1 Cost Efficiency Measures 4.6.2 Type of Efficiency Measures in Production and Cost Analyses 4.6.3 Illustrative Example4.7 SUMMARY CHAPTER 5 NON-RADIAL MEASUREMENT 5.1 INTRODUCTION 5.2 CHARACTERIZATION AND CLASSIFICATION ON DMUs 5.3 RUSSELL MEASURE 5.4 ADDITIVE MODEL 5.5 RANGE-ADJUSTED MEASURE 5.6 SLACK-ADJUSTED RADIAL MEASURE 5.7 SLACK-BASED MEASURE 5.8 METHODOLOGICAL COMPARISON: AN ILLUSTRATIVE EXAMPLE 5.9 SUMMARY CHAPTER 6 DESIRABLE PROPERTIES 6.1 INTRODUCTION 6.2 CRITERIA FOR OE 6.3 SUPPLEMENTARY DISCUSSION 6.4 PREVIOUS STUDIES ON DESIRABLE PROPERTIES 6.5 STANDARD FORMULATION FOR RADIAL AND NON-RADIAL MODELS 6.6 DESIRABLE PROPERTIES FOR DEA MODELS 6.6.1 Aggregation6.6.2 Frontier Shift Measurability 6.6.3 Invariance to Alternate Optima 6.6.4 Formal Definitions on Other Desirable Properties 6.6.5 Efficiency Requirement 6.6.6 Homogeneity 6.6.7 Strict Monotonicity 6.6.8 Unique Projection for Efficiency Comparison 6.6.9 Unit Invariance 6.6.10 Translation Invariance 6.7 SUMMARY APPENDIX Proof of Proposition 6.1 Proof of Proposition 6.6 Proof of Proposition 6.7 Proof of Proposition 6.8 Proof of Proposition 6.10 Proof of Proposition 6.11 CHAPTER 7 STRONG COMPLEMENTARY SLACKNESS CONDITIONS 7.1 INTRODUCTION

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
• Exploresnew 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.