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      1. Ekonomi och Ledarskap
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      Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis

      AvToshiyuki Sueyoshi,Mika Goto

      Inbunden, Engelska, 2018

      Del i serien Wiley Series in Operations Research and Management Science

      1 070 kr

      Beställningsvara. Skickas inom 11-20 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Introduces a bold, new model for energy industry pollution prevention and sustainable growthBalancing 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 growthCovers the fundamentals of DEA, including theory, statistical models, and practical issues of conventional applications of DEAExplores new statistical modeling strategies and explores their economic and business implicationsExamines applications of DEA to environmental analysis across the complete range of energy industries, including coal, petroleum, shale gas, nuclear energy, renewables, and moreSummarizes important studies and nearly 800 peer reviewed articles on energy, the environment, and sustainabilityEnvironmental 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.

      Produktinformation

      • Utgivningsdatum:2018-03-16
      • Mått:155 x 231 x 38 mm
      • Vikt:1 043 g
      • Format:Inbunden
      • Språk:Engelska
      • Serie:Wiley Series in Operations Research and Management Science
      • Antal sidor:720
      • Förlag:John Wiley & Sons Inc
      • ISBN:9781118979341

      Utforska kategorier

      • Entreprenörskap inom Ekonomi och Ledarskap
      • Miljövetenskap och miljöpolitik inom Naturvetenskap och teknik
      • Energiindustri inom Ekonomi och Ledarskap

      Mer om författaren

      TOSHIYUKI SUEYOSHI, PhD, is a full professor at New Mexico Institute of Mining and Technology, Soccorro, New Mexico, USA. Dr. Sueyoshi has published more than 300 articles in well-known international (SCI/SSCI listed) journals. MIKA GOTO, PhD, is a full professor at Tokyo Institute of Technology, Tokyo, Japan. Dr. Goto has published more than 100 articles in well-known international (SCI/SSCI listed) journals.

      Innehållsförteckning

      • PREFACE xvSECTION I DATA ENVELOPMENT ANALYSIS (DEA) 11 General Description 31.1 Introduction 31.2 Structure 41.3 Contributions in Sections I and II 101.4 Abbreviations and Nomenclature 131.4.1 Abbreviations Used in This Book 131.4.2 Nomenclature Used in This Book 181.4.3 Mathematical Concerns 231.5 Summary 242 Overview 252.1 Introduction 252.2 What is DEA? 262.3 Remarks 332.4 Reformulation from Fractional Programming to Linear Programming 352.5 Reference Set 382.6 Example for Computational Description 392.7 Summary 443 History 453.1 Introduction 453.2 O rigin of L1 Regression 463.3 O rigin of Goal Programming 503.4 Analytical Properties of L1 Regression 533.5 From L1 Regression to L2 Regression and Frontier Analysis 553.5.1 L2 Regression 553.5.2 L1-based Frontier Analyses 553.6 O rigin of DEA 593.7 Relationships between GP and DEA 613.8 Historical Progress From L1 Regression to DEA 643.9 Summary 644 Radial Measurement 674.1 Introduction 674.2 Radial Models: Input-Oriented 704.2.1 Input-Oriented RM(v) under Variable RTS 704.2.2 Underlying Concept 724.2.3 Input-Oriented RM(c) under Constant RTS 744.3 Radial Models: Desirable Output-Oriented 754.3.1 Desirable Output-oriented RM(v) under Variable RTS 754.3.2 Desirable Output-oriented RM(c) under Constant RTS 774.4 Comparison Between Radial Models 794.4.1 Comparison Between Input-Oriented and Desirable Output‑Oriented Radial Models 794.4.2 Hybrid Radial Model: Modification 814.5 Multiplier Restriction and Cross-Reference Approaches 824.5.1 Multiplier Restriction Methods 824.5.2 Cone Ratio Method 844.5.3 Cross-reference Method 864.6 Cost Analysis 884.6.1 Cost Efficiency Measures 884.6.2 Type of Efficiency Measures in Production and Cost Analyses 894.6.3 Illustrative Example 914.7 Summary 945 Non-Radial Measurement 955.1 Introduction 955.2 Characterization and Classification on DMUs 975.3 Russell Measure 995.4 Additive Model 1035.5 Range-Adjusted Measure 1055.6 Slack-Adjusted Radial Measure 1065.7 Slack-Based Measure 1085.8 Methodological Comparison: An Illustrative Example 1115.9 Summary 1136 Desirable Properties 1156.1 Introduction 1156.2 Criteria For OE 1176.3 Supplementary Discussion 1196.4 Previous Studies on Desirable Properties 1206.5 Standard Formulation for Radial and Non-Radial Models 1226.6 Desirable Properties for DEA Models 1266.6.1 Aggregation 1266.6.2 Frontier Shift Measurability 1286.6.3 Invariance to Alternate Optima 1316.6.4 Formal Definitions on Other Desirable Properties 1326.6.5 Efficiency Requirement 1336.6.6 Homogeneity 1346.6.7 Strict Monotonicity 1366.6.8 Unique Projection for Efficiency Comparison 1376.6.9 Unit Invariance 1386.6.10 Translation Invariance 1396.7 Summary 1406.A Appendix 1426.A.1 Proof of Proposition 6.1 1426.A.2 Proof of Proposition 6.6 1436.A.3 Proof of Proposition 6.7 1456.A.4 Proof of Proposition 6.8 1466.A.5 Proof of Proposition 6.10 1476.A.6 Proof of Proposition 6.11 1477 Strong Complementary Slackness Conditions 1497.1 Introduction 1497.2 Combination Between Primal and Dual Models for SCSCs 1507.3 Three Illustrative Examples 1547.3.1 First Example 1557.3.2 Second Example 1587.3.3 Third Example 1617.4 Theoretical Implications of SCSCs 1627.5 Guideline for Non-Radial Models 1677.6 Summary 1677.A Appendix 1687.A.1 Proof of Proposition 7.1 1687.A.2 Proof of Proposition 7.4 1697.A.3 Proof of Proposition 7.6 1708 Returns to Scale 1738.1 Introduction 1738.2 Underlying Concepts 1748.3 Production-Based RTS Measurement 1788.4 Cost-Based RTS Measurement 1828.5 Scale Efficiencies and Scale Economies 1858.6 Summary 1889 Congestion 1899.1 Introduction 1899.2 An Illustrative Example 1919.3 Fundamental Discussions 1959.4 Supporting Hyperplane 2009.4.1 Location of Supporting Hyperplane 2009.4.2 Visual Description of Congestion and RTS 2019.5 Congestion Identification 2049.5.1 Slack Adjustment for Projection 2049.5.2 Congestion Identification on Projected Point 2069.6 Theoretical Linkage Between Congestion and RTS 2079.7 Degree of Congestion 2099.8 Economic Implications 2119.9 Summary 21210 Network Computing 21510.1 Introduction 21510.2 Network Computing Architecture 21610.3 Network Computing for Multi-Stage Parallel Processes 21810.3.1 Theoretical Preliminary 21810.3.2 Computational Strategy for Network Computing 22110.3.3 Network Computing in Multi-Stage Parallel Processes 22110.4 Simulation Study 22910.5 Summary 24111 DEA-Discriminant Analysis 24311.1 Introduction 24311.2 Two MIP Approaches for DEA-DA 24511.2.1 Standard MIP Approach 24511.2.2 Two-stage MIP Approach 24811.2.3 Differences between Two MIP Approaches 25411.2.4 Differences between DEA and DEA-DA 25511.3 Classifying Multiple Groups 25511.4 Illustrative Examples 25911.4.1 First Example 25911.4.2 Second Example 25911.5 Frontier Analysis 26111.6 Summary 26312 Literature Study for Section I 26512.1 Introduction 26512.2 Computer Codes 26512.3 Pedagogical Linkage From Conventional Use to Environmental Assessment 268References for Section I 270SECTION II DEA ENVIRONMENTAL ASSESSMENT 28113 World Energy 28313.1 Introduction 28313.2 General Trend 28413.3 Primary Energy 28613.3.1 Fossil Fuel Energy 28613.3.2 Non-fossil Energy 29313.4 Secondary Energy (Electricity) 29713.5 Petroleum Price and World Trade 29913.6 Energy Economics 30013.7 Summary 30314 Environmental Protection 30514.1 Introduction 30514.2 European Union 30614.2.1 General Description 30614.2.2 Environmental Action Program 30814.3 Japan 31014.4 China 31114.5 The United States of America 31514.5.1 General Description 31514.5.2 Regional Comparison between PJM and California ISO 31714.5.3 Federal Regulation of PJM and California ISO 31814.5.4 Local Regulation on PJM 31914.5.5 Local Regulation on California ISO 32014.6 Summary 32215 Concepts 32515.1 Introduction 32515.2 Role of DEA in Measuring Unified Performance 32715.3 Social Sustainability Versus Corporate Sustainability 33115.3.1 Why Is Social Sustainability Important? 33215.3.2 Why Is Corporate Sustainability Important? 33315.4 Strategic Adaptation 33615.5 Two Disposability Concepts 33915.6 Unified Efficiency under Natural and Managerial Disposability 34115.7 Difficulty in DEA Environmental Assessment 34315.8 Undesirable Congestion and Desirable Congestion 34515.9 Comparison With Previous Disposability Concepts 34615.9.1 Weak and Strong Disposability 34715.9.2 Null-joint Relationship (Assumption on “Byproducts”) 34715.10 Summary 35016 Non-Radial Approach for Unified Efficiency Measures 35116.1 Introduction 35116.2 Unified Efficiency 35216.2.1 Formulation 35216.2.2 Visual Implications of UE 35716.3 Unified Efficiency under Natural Disposability 35916.4 Unified Efficiency under Managerial Disposability 36216.5 Properties of Non-Radial Approach 36416.6 National and International Firms in the Petroleum Industry 36616.6.1 Business Structure 36616.6.2 National and International Oil Companies 36716.6.3 UE Measures 36716.6.4 UE Measures under Natural Disposability 36916.6.5 UE Measures under Managerial Disposability 36916.7 Summary 37317 Radial Approach for Unified Efficiency Measures 37517.1 Introduction 37517.2 Unified Efficiency 37617.3 Radial Unification between Desirable and Undesirable Outputs 37817.4 Unified Efficiency under Natural Disposability 38117.5 Unified Efficiency under Managerial Disposability 38317.6 Coal-Fired Power Plants in the United States 38517.6.1 ISO and RTO 38517.6.2 Data 38717.6.3 Unified Efficiency 38817.6.4 Unified Efficiency under Natural Disposability 39017.6.5 Unified Efficiency under Managerial Disposability 39117.7 Summary 39217.A Appendix 39318 Scale Efficiency 39518.1 Introduction 39518.2 Scale Efficiency under Natural Disposability: Non-Radial Approach 39618.3 Scale Efficiency under Managerial Disposability: Non-Radial Approach 39918.4 Scale Efficiency under Natural Disposability: Radial Approach 40118.5 Scale Efficiency under Managerial Disposability: Radial Approach 40318.6 United States Coal-Fired Power Plants 40418.6.1 The Clean Air Act 40418.6.2 Production Factors 40618.6.3 Research Concerns 40718.6.4 Unified Efficiency Measures of Power Plants 41018.6.5 Mean Tests 41018.7 Summary 41419 Measurement in a Time Horizon 41719.1 Introduction 41719.2 Malmquist Index 41819.3 Frontier Shift in Time Horizon 41919.3.1 No Occurrence of Frontier Crossover 41919.3.2 Occurrence of Frontier Crossover 42219.4 Formulations for Natural Disposability 42419.4.1 No Occurrence of Frontier Crossover 42519.4.2 Occurrence of Frontier Crossover 42819.5 Formulations under Managerial Disposability 43019.5.1 No Occurrence of Frontier Crossover 43019.5.2 Occurrence of Frontier Crossover 43219.6 Energy Mix of Industrial Nations 43519.7 Summary 43719.A Appendix 44020 Returns to Scale and Damages to Scale 44320.1 Introduction 44320.2 Underlying Concepts 44420.2.1 Scale Elasticity 44420.2.2 Differences Between RTS and DTS 44520.3 Non-Radial Approach 44720.3.1 Scale Economies and RTS under Natural Disposability 44720.3.2 Scale Damages and DTS under Managerial Disposability 45020.4 Radial Approach 45120.4.1 Scale Economies and RTS under Natural Disposability 45120.4.2 Scale Damages and DTS under Managerial Disposability 45420.5 Japanese Chemical and Pharmaceutical Firms 45520.6 Summary 46121 Desirable and Undesirable Congestions 46321.1 Introduction 46321.2 UC and DC 46421.3 Unified Efficiency and UC under Natural Disposability 46921.4 Unified Efficiency and DC under Managerial Disposability 47321.5 Coal-Fired Power Plants in United States 47621.5.1 Data 47621.5.2 Occurrence of Congestion 47721.6 Summary 47722 Marginal Rate of Transformation and Rate of Substitution 48322.1 Introduction 48322.2 Concepts 48522.2.1 Desirable Congestion 48522.2.2 MRT and RSU 48522.3 A Possible Occurrence of DC 48922.4 Measurement of MRT and RSU Under DC 49122.5 Multiplier Restriction 49222.6 Explorative Analysis 49322.7 International Comparison 49522.8 Summary 50323 Returns to Damage and Damages to Return 50523.1 Introduction 50523.2 Congestion, RTD and DTR 50623.2.1 UC and DC 50623.2.2 RTD under UC 50823.2.3 DTR under DC 51023.2.4 Possible Occurrence of UC and DC 51123.3 Congestion Identification under Natural Disposability 51223.3.1 Possible Occurrence of UC 51223.3.2 RTD Measurement under the Possible Occurrence of UC 51623.4 Congestion Identification under Managerial Disposability 51923.4.1 Possible Occurrence of DC 51923.4.2 DTR Measurement under the Possible Occurrence of DC 52223.5 Energy and Social Sustainability In China 52423.5.1 Data and Empirical Results 52423.6 Summary 53424 Disposability Unification 53724.1 Introduction 53724.2 Unification between Disposability Concepts 53824.3 Non-Radial Approach for Disposability Unification 54024.4 Radial Approach for Disposability Unification 54524.5 Computational Flow for Disposability Unification 54924.6 US Petroleum Industry 55124.6.1 Data 55124.6.2 Unified Efficiency Measures 55424.6.3 Scale Efficiency 55724.7 Summary 55825 Common Multipliers 56125.1 Introduction 56125.2 Computational Framework 56425.3 Data Envelopment Analysis–Discriminant Analysis 56425.4 Rank Sum Test 57125.5 Japanese Electric Power Industry 57125.5.1 Underlying Concepts 57125.5.2 Empirical Results 57325.6 Summary 58026 Property of Translation Invariance to Handle Zero and Negative Values 58126.1 Introduction 58126.2 Translation Invariance 58226.3 Assessment in Time Horizon 58526.3.1 Formulations under Natural Disposability 58526.3.2 Formulations under Managerial Disposability 58826.3.3 Efficiency Growth 58826.4 Efficiency Measurement for Fuel Mix Strategy 59026.4.1 Unified Efficiency Measures 59126.4.2 Fuel Mix Strategy 59526.5 Summary 59827 Handling Zero and Negative Values in Radial Measurement 60127.1 Introduction 60127.2 Disaggregation 60227.3 Unified Efficiency Measurement 60327.3.1 Conceptual Review of Disposability Unification 60327.3.2 Unified Efficiency under Natural Disposability with Disaggregation 60627.3.3 Unified Efficiency under Managerial Disposability with Disaggregation 60727.4 Possible Occurrence of Desirable Congestion 60927.4.1 Unified Efficiency under Natural and Managerial Disposability 60927.4.2 UENM with Desirable Congestion 61027.4.3 Investment Rule 61327.4.4 Computation Summary 61427.5 United States Industrial Sectors 61527.6 Summary 62228 Literature Study for DEA Environmental Assessment 62528.1 Introduction 62528.2 Applications in Energy and Environment 62628.3 Energy 62828.3.1 Electricity 62828.3.2 Oil, Coal, Gas and Heat 63128.3.3 Renewable Energies 63328.4 Energy Efficiency 63428.5 Environment 63728.6 Other Applications 63928.7 Summary 640References for Section II 641INDEX 685
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