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More About This Title Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis
English
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.
English
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.
English
PREFACE xv
SECTION I DATA ENVELOPMENT ANALYSIS (DEA) 1
1 General Description 3
1.1 Introduction 3
1.2 Structure 4
1.3 Contributions in Sections I and II 10
1.4 Abbreviations and Nomenclature 13
1.4.1 Abbreviations Used in This Book 13
1.4.2 Nomenclature Used in This Book 18
1.4.3 Mathematical Concerns 23
1.5 Summary 24
2 Overview 25
2.1 Introduction 25
2.2 What is DEA? 26
2.3 Remarks 33
2.4 Reformulation from Fractional Programming to Linear Programming 35
2.5 Reference Set 38
2.6 Example for Computational Description 39
2.7 Summary 44
3 History 45
3.1 Introduction 45
3.2 O rigin of L1 Regression 46
3.3 O rigin of Goal Programming 50
3.4 Analytical Properties of L1 Regression 53
3.5 From L1 Regression to L2 Regression and Frontier Analysis 55
3.5.1 L2 Regression 55
3.5.2 L1?-based Frontier Analyses 55
3.6 O rigin of DEA 59
3.7 Relationships between GP and DEA 61
3.8 Historical Progress From L1 Regression to DEA 64
3.9 Summary 64
4 Radial Measurement 67
4.1 Introduction 67
4.2 Radial Models: Input?-Oriented 70
4.2.1 Input?-Oriented RM(v) under Variable RTS 70
4.2.2 Underlying Concept 72
4.2.3 Input?-Oriented RM(c) under Constant RTS 74
4.3 Radial Models: Desirable Output?-Oriented 75
4.3.1 Desirable Output?-oriented RM(v) under Variable RTS 75
4.3.2 Desirable Output?-oriented RM(c) under Constant RTS 77
4.4 Comparison Between Radial Models 79
4.4.1 Comparison Between Input?-Oriented and Desirable Output‑Oriented Radial Models 79
4.4.2 Hybrid Radial Model: Modification 81
4.5 Multiplier Restriction and Cross?-Reference Approaches 82
4.5.1 Multiplier Restriction Methods 82
4.5.2 Cone Ratio Method 84
4.5.3 Cross?-reference Method 86
4.6 Cost Analysis 88
4.6.1 Cost Efficiency Measures 88
4.6.2 Type of Efficiency Measures in Production and Cost Analyses 89
4.6.3 Illustrative Example 91
4.7 Summary 94
5 Non?-Radial Measurement 95
5.1 Introduction 95
5.2 Characterization and Classification on DMUs 97
5.3 Russell Measure 99
5.4 Additive Model 103
5.5 Range?-Adjusted Measure 105
5.6 Slack?-Adjusted Radial Measure 106
5.7 Slack?-Based Measure 108
5.8 Methodological Comparison: An Illustrative Example 111
5.9 Summary 113
6 Desirable Properties 115
6.1 Introduction 115
6.2 Criteria For OE 117
6.3 Supplementary Discussion 119
6.4 Previous Studies on Desirable Properties 120
6.5 Standard Formulation for Radial and Non?-Radial Models 122
6.6 Desirable Properties for DEA Models 126
6.6.1 Aggregation 126
6.6.2 Frontier Shift Measurability 128
6.6.3 Invariance to Alternate Optima 131
6.6.4 Formal Definitions on Other Desirable Properties 132
6.6.5 Efficiency Requirement 133
6.6.6 Homogeneity 134
6.6.7 Strict Monotonicity 136
6.6.8 Unique Projection for Efficiency Comparison 137
6.6.9 Unit Invariance 138
6.6.10 Translation Invariance 139
6.7 Summary 140
6.A Appendix 142
6.A.1 Proof of Proposition 6.1 142
6.A.2 Proof of Proposition 6.6 143
6.A.3 Proof of Proposition 6.7 145
6.A.4 Proof of Proposition 6.8 146
6.A.5 Proof of Proposition 6.10 147
6.A.6 Proof of Proposition 6.11 147
7 Strong Complementary Slackness Conditions 149
7.1 Introduction 149
7.2 Combination Between Primal and Dual Models for SCSCs 150
7.3 Three Illustrative Examples 154
7.3.1 First Example 155
7.3.2 Second Example 158
7.3.3 Third Example 161
7.4 Theoretical Implications of SCSCs 162
7.5 Guideline for Non-Radial Models 167
7.6 Summary 167
7.A Appendix 168
7.A.1 Proof of Proposition 7.1 168
7.A.2 Proof of Proposition 7.4 169
7.A.3 Proof of Proposition 7.6 170
8 Returns to Scale 173
8.1 Introduction 173
8.2 Underlying Concepts 174
8.3 Production?-Based RTS Measurement 178
8.4 Cost?-Based RTS Measurement 182
8.5 Scale Efficiencies and Scale Economies 185
8.6 Summary 188
9 Congestion 189
9.1 Introduction 189
9.2 An Illustrative Example 191
9.3 Fundamental Discussions 195
9.4 Supporting Hyperplane 200
9.4.1 Location of Supporting Hyperplane 200
9.4.2 Visual Description of Congestion and RTS 201
9.5 Congestion Identification 204
9.5.1 Slack Adjustment for Projection 204
9.5.2 Congestion Identification on Projected Point 206
9.6 Theoretical Linkage Between Congestion and RTS 207
9.7 Degree of Congestion 209
9.8 Economic Implications 211
9.9 Summary 212
10 Network Computing 215
10.1 Introduction 215
10.2 Network Computing Architecture 216
10.3 Network Computing for Multi?-Stage Parallel Processes 218
10.3.1 Theoretical Preliminary 218
10.3.2 Computational Strategy for Network Computing 221
10.3.3 Network Computing in Multi?-Stage Parallel Processes 221
10.4 Simulation Study 229
10.5 Summary 241
11 DEA?-Discriminant Analysis 243
11.1 Introduction 243
11.2 Two MIP Approaches for DEA?-DA 245
11.2.1 Standard MIP Approach 245
11.2.2 Two?-stage MIP Approach 248
11.2.3 Differences between Two MIP Approaches 254
11.2.4 Differences between DEA and DEA?-DA 255
11.3 Classifying Multiple Groups 255
11.4 Illustrative Examples 259
11.4.1 First Example 259
11.4.2 Second Example 259
11.5 Frontier Analysis 261
11.6 Summary 263
12 Literature Study for Section I 265
12.1 Introduction 265
12.2 Computer Codes 265
12.3 Pedagogical Linkage From Conventional Use to Environmental Assessment 268
References for Section I 270
SECTION II DEA ENVIRONMENTAL ASSESSMENT 281
13 World Energy 283
13.1 Introduction 283
13.2 General Trend 284
13.3 Primary Energy 286
13.3.1 Fossil Fuel Energy 286
13.3.2 Non?-fossil Energy 293
13.4 Secondary Energy (Electricity) 297
13.5 Petroleum Price and World Trade 299
13.6 Energy Economics 300
13.7 Summary 303
14 Environmental Protection 305
14.1 Introduction 305
14.2 European Union 306
14.2.1 General Description 306
14.2.2 Environmental Action Program 308
14.3 Japan 310
14.4 China 311
14.5 The United States of America 315
14.5.1 General Description 315
14.5.2 Regional Comparison between PJM and California ISO 317
14.5.3 Federal Regulation of PJM and California ISO 318
14.5.4 Local Regulation on PJM 319
14.5.5 Local Regulation on California ISO 320
14.6 Summary 322
15 Concepts 325
15.1 Introduction 325
15.2 Role of DEA in Measuring Unified Performance 327
15.3 Social Sustainability Versus Corporate Sustainability 331
15.3.1 Why Is Social Sustainability Important? 332
15.3.2 Why Is Corporate Sustainability Important? 333
15.4 Strategic Adaptation 336
15.5 Two Disposability Concepts 339
15.6 Unified Efficiency under Natural and Managerial Disposability 341
15.7 Difficulty in DEA Environmental Assessment 343
15.8 Undesirable Congestion and Desirable Congestion 345
15.9 Comparison With Previous Disposability Concepts 346
15.9.1 Weak and Strong Disposability 347
15.9.2 Null?-joint Relationship (Assumption on “Byproducts”) 347
15.10 Summary 350
16 Non?-Radial Approach for Unified Efficiency Measures 351
16.1 Introduction 351
16.2 Unified Efficiency 352
16.2.1 Formulation 352
16.2.2 Visual Implications of UE 357
16.3 Unified Efficiency under Natural Disposability 359
16.4 Unified Efficiency under Managerial Disposability 362
16.5 Properties of Non?-Radial Approach 364
16.6 National and International Firms in the Petroleum Industry 366
16.6.1 Business Structure 366
16.6.2 National and International Oil Companies 367
16.6.3 UE Measures 367
16.6.4 UE Measures under Natural Disposability 369
16.6.5 UE Measures under Managerial Disposability 369
16.7 Summary 373
17 Radial Approach for Unified Efficiency Measures 375
17.1 Introduction 375
17.2 Unified Efficiency 376
17.3 Radial Unification between Desirable and Undesirable Outputs 378
17.4 Unified Efficiency under Natural Disposability 381
17.5 Unified Efficiency under Managerial Disposability 383
17.6 Coal?-Fired Power Plants in the United States 385
17.6.1 ISO and RTO 385
17.6.2 Data 387
17.6.3 Unified Efficiency 388
17.6.4 Unified Efficiency under Natural Disposability 390
17.6.5 Unified Efficiency under Managerial Disposability 391
17.7 Summary 392
17.A Appendix 393
18 Scale Efficiency 395
18.1 Introduction 395
18.2 Scale Efficiency under Natural Disposability: Non?-Radial Approach 396
18.3 Scale Efficiency under Managerial Disposability: Non?-Radial Approach 399
18.4 Scale Efficiency under Natural Disposability: Radial Approach 401
18.5 Scale Efficiency under Managerial Disposability: Radial Approach 403
18.6 United States Coal?-Fired Power Plants 404
18.6.1 The Clean Air Act 404
18.6.2 Production Factors 406
18.6.3 Research Concerns 407
18.6.4 Unified Efficiency Measures of Power Plants 410
18.6.5 Mean Tests 410
18.7 Summary 414
19 Measurement in a Time Horizon 417
19.1 Introduction 417
19.2 Malmquist Index 418
19.3 Frontier Shift in Time Horizon 419
19.3.1 No Occurrence of Frontier Crossover 419
19.3.2 Occurrence of Frontier Crossover 422
19.4 Formulations for Natural Disposability 424
19.4.1 No Occurrence of Frontier Crossover 425
19.4.2 Occurrence of Frontier Crossover 428
19.5 Formulations under Managerial Disposability 430
19.5.1 No Occurrence of Frontier Crossover 430
19.5.2 Occurrence of Frontier Crossover 432
19.6 Energy Mix of Industrial Nations 435
19.7 Summary 437
19.A Appendix 440
20 Returns to Scale and Damages to Scale 443
20.1 Introduction 443
20.2 Underlying Concepts 444
20.2.1 Scale Elasticity 444
20.2.2 Differences Between RTS and DTS 445
20.3 Non?-Radial Approach 447
20.3.1 Scale Economies and RTS under Natural Disposability 447
20.3.2 Scale Damages and DTS under Managerial Disposability 450
20.4 Radial Approach 451
20.4.1 Scale Economies and RTS under Natural Disposability 451
20.4.2 Scale Damages and DTS under Managerial Disposability 454
20.5 Japanese Chemical and Pharmaceutical Firms 455
20.6 Summary 461
21 Desirable and Undesirable Congestions 463
21.1 Introduction 463
21.2 UC and DC 464
21.3 Unified Efficiency and UC under Natural Disposability 469
21.4 Unified Efficiency and DC under Managerial Disposability 473
21.5 Coal?-Fired Power Plants in United States 476
21.5.1 Data 476
21.5.2 Occurrence of Congestion 477
21.6 Summary 477
22 Marginal Rate of Transformation and Rate of Substitution 483
22.1 Introduction 483
22.2 Concepts 485
22.2.1 Desirable Congestion 485
22.2.2 MRT and RSU 485
22.3 A Possible Occurrence of DC 489
22.4 Measurement of MRT and RSU Under DC 491
22.5 Multiplier Restriction 492
22.6 Explorative Analysis 493
22.7 International Comparison 495
22.8 Summary 503
23 Returns to Damage and Damages to Return 505
23.1 Introduction 505
23.2 Congestion, RTD and DTR 506
23.2.1 UC and DC 506
23.2.2 RTD under UC 508
23.2.3 DTR under DC 510
23.2.4 Possible Occurrence of UC and DC 511
23.3 Congestion Identification under Natural Disposability 512
23.3.1 Possible Occurrence of UC 512
23.3.2 RTD Measurement under the Possible Occurrence of UC 516
23.4 Congestion Identification under Managerial Disposability 519
23.4.1 Possible Occurrence of DC 519
23.4.2 DTR Measurement under the Possible Occurrence of DC 522
23.5 Energy and Social Sustainability In China 524
23.5.1 Data and Empirical Results 524
23.6 Summary 534
24 Disposability Unification 537
24.1 Introduction 537
24.2 Unification between Disposability Concepts 538
24.3 Non?-Radial Approach for Disposability Unification 540
24.4 Radial Approach for Disposability Unification 545
24.5 Computational Flow for Disposability Unification 549
24.6 US Petroleum Industry 551
24.6.1 Data 551
24.6.2 Unified Efficiency Measures 554
24.6.3 Scale Efficiency 557
24.7 Summary 558
25 Common Multipliers 561
25.1 Introduction 561
25.2 Computational Framework 564
25.3 Data Envelopment Analysis–Discriminant Analysis 564
25.4 Rank Sum Test 571
25.5 Japanese Electric Power Industry 571
25.5.1 Underlying Concepts 571
25.5.2 Empirical Results 573
25.6 Summary 580
26 Property of Translation Invariance to Handle Zero and Negative Values 581
26.1 Introduction 581
26.2 Translation Invariance 582
26.3 Assessment in Time Horizon 585
26.3.1 Formulations under Natural Disposability 585
26.3.2 Formulations under Managerial Disposability 588
26.3.3 Efficiency Growth 588
26.4 Efficiency Measurement for Fuel Mix Strategy 590
26.4.1 Unified Efficiency Measures 591
26.4.2 Fuel Mix Strategy 595
26.5 Summary 598
27 Handling Zero and Negative Values in Radial Measurement 601
27.1 Introduction 601
27.2 Disaggregation 602
27.3 Unified Efficiency Measurement 603
27.3.1 Conceptual Review of Disposability Unification 603
27.3.2 Unified Efficiency under Natural Disposability with Disaggregation 606
27.3.3 Unified Efficiency under Managerial Disposability with Disaggregation 607
27.4 Possible Occurrence of Desirable Congestion 609
27.4.1 Unified Efficiency under Natural and Managerial Disposability 609
27.4.2 UENM with Desirable Congestion 610
27.4.3 Investment Rule 613
27.4.4 Computation Summary 614
27.5 United States Industrial Sectors 615
27.6 Summary 622
28 Literature Study for DEA Environmental Assessment 625
28.1 Introduction 625
28.2 Applications in Energy and Environment 626
28.3 Energy 628
28.3.1 Electricity 628
28.3.2 Oil, Coal, Gas and Heat 631
28.3.3 Renewable Energies 633
28.4 Energy Efficiency 634
28.5 Environment 637
28.6 Other Applications 639
28.7 Summary 640
References for Section II 641
INDEX 685
