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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.

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. 

Preface xv
Section I: Data Envelopment Analysis (DEA) 1(280)
1 General Description
3(22)
1.1 Introduction
3(1)
1.2 Structure
4(6)
1.3 Contributions in Sections I and II
10(3)
1.4 Abbreviations and Nomenclature
13(11)
1.4.1 Abbreviations Used in This Book
13(5)
1.4.2 Nomenclature Used in This Book
18(5)
1.4.3 Mathematical Concerns
23(1)
1.5 Summary
24(1)
2 Overview
25(20)
2.1 Introduction
25(1)
2.2 What is DEA?
26(7)
2.3 Remarks
33(2)
2.4 Reformulation from Fractional Programming to Linear Programming
35(3)
2.5 Reference Set
38(1)
2.6 Example for Computational Description
39(5)
2.7 Summary
44(1)
3 History
45(22)
3.1 Introduction
45(1)
3.2 Origin of L1 Regression
46(4)
3.3 Origin of Goal Programming
50(3)
3.4 Analytical Properties of L1 Regression
53(2)
3.5 From Ll Regression to L2 Regression and Frontier Analysis
55(4)
3.5.1 L2 Regression
55(1)
3.5.2 L1-Based Frontier Analyses
55(4)
3.6 Origin of DEA
59(2)
3.7 Relationships between GP and DEA
61(3)
3.8 Historical Progress from L1 Regression to DEA
64(1)
3.9 Summary
64(3)
4 Radial Measurement
67(28)
4.1 Introduction
67(3)
4.2 Radial Models: Input-Oriented
70(5)
4.2.1 Input-Oriented RM(v) under Variable RTS
70(2)
4.2.2 Underlying Concept
72(2)
4.2.3 Input-Oriented RM(c) under Constant RTS
74(1)
4.3 Radial Models: Desirable Output-Oriented
75(4)
4.3.1 Desirable Output-oriented RM(v) under Variable RTS
75(2)
4.3.2 Desirable Output-oriented RM(c) under Constant RTS
77(2)
4.4 Comparison between Radial Models
79(3)
4.4.1 Comparison between Input-Oriented and Desirable Output-Oriented Radial Models
79(2)
4.4.2 Hybrid Radial Model: Modification
81(1)
4.5 Multiplier Restriction and Cross-reference Approaches
82(6)
4.5.1 Multiplier Restriction Methods
82(2)
4.5.2 Cone Ratio Method
84(2)
4.5.3 Cross-reference Method
86(2)
4.6 Cost Analysis
88(6)
4.6.1 Cost Efficiency Measures
88(1)
4.6.2 Type of Efficiency Measures in Production and Cost Analyses
89(2)
4.6.3 Illustrative Example
91(3)
4.7 Summary
94(1)
5 Non-Radial Measurement
95(20)
5.1 Introduction
95(2)
5.2 Characterization and Classification on DMUs
97(2)
5.3 Russell Measure
99(4)
5.4 Additive Model
103(2)
5.5 Range-Adjusted Measure
105(1)
5.6 Slack-Adjusted Radial Measure
106(2)
5.7 Slack-Based Measure
108(3)
5.8 Methodological Comparison: An Illustrative Example
111(2)
5.9 Summary
113(2)
6 Desirable Properties
115(34)
6.1 Introduction
115(2)
6.2 Criteria for OE
117(2)
6.3 Supplementary Discussion
119(1)
6.4 Previous Studies on Desirable Properties
120(2)
6.5 Standard Formulation for Radial and Non-Radial Models
122(4)
6.6 Desirable Properties for DEA Models
126(14)
6.6.1 Aggregation
126(2)
6.6.2 Frontier Shift Measurability
128(3)
6.6.3 Invariance to Alternate Optima
131(1)
6.6.4 Formal Definitions on Other Desirable Properties
132(1)
6.6.5 Efficiency Requirement
133(1)
6.6.6 Homogeneity
134(2)
6.6.7 Strict Monotonicity
136(1)
6.6.8 Unique Projection for Efficiency Comparison
137(1)
6.6.9 Unit Invariance
138(1)
6.6.10 Translation Invariance
139(1)
6.7 Summary
140(2)
Appendix
142(1)
Proof of Proposition 6.1
142(1)
Proof of Proposition 6.6
143(2)
Proof of Proposition 6.7
145(1)
Proof of Proposition 6.8
146(1)
Proof of Proposition 6.10
147(1)
Proof of Proposition 6.11
147(2)
7 Strong Complementary Slackness Conditions
149(24)
7.1 Introduction
149(1)
7.2 Combination between Primal and Dual Models for SCSCs
150(4)
7.3 Three Illustrative Examples
154(8)
7.3.1 First Example
155(3)
7.3.2 Second Example
158(3)
7.3.3 Third Example
161(1)
7.4 Theoretical Implications of SCSCs
162(5)
7.5 Guideline for Non-Radial Models
167(1)
7.6 Summary
167(1)
Appendix
168(1)
Proof of Proposition 7.1
168(1)
Proof of Proposition 7.4
169(1)
Proof of Proposition 7.6
170(3)
8 Returns to Scale
173(16)
8.1 Introduction
173(1)
8.2 Underlying Concepts
174(4)
8.3 Production-Based RTS Measurement
178(4)
8.4 Cost-Based RTS Measurement
182(3)
8.5 Scale Efficiencies and Scale Economies
185(3)
8.6 Summary
188(1)
9 Congestion
189(26)
9.1 Introduction
189(2)
9.2 An Illustrative Example
191(4)
9.3 Fundamental Discussions
195(5)
9.4 Supporting Hyperplane
200(4)
9.4.1 Location of Supporting Hyperplane
200(1)
9.4.2 Visual Description of Congestion and RTS
201(3)
9.5 Congestion Identification
204(3)
9.5.1 Slack Adjustment for Projection
204(2)
9.5.2 Congestion Identification on Projected Point
206(1)
9.6 Theoretical Linkage between Congestion and RTS
207(2)
9.7 Degree of Congestion
209(2)
9.8 Economic Implications
211(1)
9.9 Summary
212(3)
10 Network Computing
215(28)
10.1 Introduction
215(1)
10.2 Network Computing Architecture
216(2)
10.3 Network Computing for Multi-Stage Parallel Processes
218(11)
10.3.1 Theoretical Preliminary
218(3)
10.3.2 Computational Strategy for Network Computing
221(1)
10.3.3 Network Computing in Multi-Stage Parallel Processes
221(8)
10.4 Simulation Study
229(12)
10.5 Summary
241(2)
11 DEA-Discriminant Analysis
243(22)
11.1 Introduction
243(2)
11.2 Two MIP Approaches for DEA-DA
245(10)
11.2.1 Standard MIP Approach
245(3)
11.2.2 Two-stage MIP Approach
248(6)
11.2.3 Differences between Two MIP Approaches
254(1)
11.2.4 Differences between DEA and DEA-DA
255(1)
11.3 Classifying Multiple Groups
255(4)
11.4 Illustrative Examples
259(2)
11.4.1 First Example
259(1)
11.4.2 Second Example
259(2)
11.5 Frontier Analysis
261(2)
11.6 Summary
263(2)
12 Literature Study for Section I
265(16)
12.1 Introduction
265(1)
12.2 Computer Codes
265(3)
12.3 Pedagogical Linkage from Conventional Use to Environmental Assessment
268(2)
References for Section I
270(11)
Section II: DEA Environmental Assessment 281(404)
13 World Energy
283(22)
13.1 Introduction
283(1)
13.2 General Trend
284(2)
13.3 Primary Energy
286(11)
13.3.1 Fossil Fuel Energy
286(7)
13.3.2 Non-fossil Energy
293(4)
13.4 Secondary Energy (Electricity)
297(2)
13.5 Petroleum Price and World Trade
299(1)
13.6 Energy Economics
300(3)
13.7 Summary
303(2)
14 Environmental Protection
305(20)
14.1 Introduction
305(1)
14.2 European Union
306(4)
14.2.1 General Description
306(2)
14.2.2 Environmental Action Program
308(2)
14.3 Japan
310(1)
14.4 China
311(4)
14.5 The United States of America
315(7)
14.5.1 General Description
315(2)
14.5.2 Regional Comparison between PJM and California ISO
317(1)
14.5.3 Federal Regulation on PJM and California ISO
318(1)
14.5.4 Local Regulation on PJM
319(1)
14.5.5 Local Regulation on California ISO
320(2)
14.6 Summary
322(3)
15 Concepts
325(26)
15.1 Introduction
325(2)
15.2 Role of DEA in Measuring Unified Performance
327(4)
15.3 Social Sustainability Versus Corporate Sustainability
331(5)
15.3.1 Why Is Social Sustainability Important?
332(1)
15.3.2 Why Is Corporate Sustainability Important?
333(3)
15.4 Strategic Adaptation
336(3)
15.5 Two Disposability Concepts
339(2)
15.6 Unified Efficiency under Natural and Managerial Disposability
341(2)
15.7 Difficulty in DEA Environmental Assessment
343(2)
15.8 Undesirable Congestion and Desirable Congestion
345(1)
15.9 Comparison with Previous Disposability Concepts
346(4)
15.9.1 Weak and Strong Disposability
347(1)
15.9.2 Null-joint Relationship (Assumption on "Byproducts")
347(3)
15.10 Summary
350(1)
16 Non-Radial Approach for Unified Efficiency Measures
351(24)
16.1 Introduction
351(1)
16.2 Unified Efficiency
352(8)
16.2.1 Formulation
352(5)
16.2.2 Visual Implications of UE
357(3)
16.3 Unified Efficiency under Natural Disposability
360(2)
16.4 Unified Efficiency under Managerial Disposability
362(2)
16.5 Properties of Non-Radial Approach
364(2)
16.6 National and International Firms in Petroleum Industry
366(7)
16.6.1 Business Structure
366(1)
16.6.2 National and International Oil Companies
367(1)
16.6.3 UE Measures
367(2)
16.6.4 UE Measures under Natural Disposability
369(1)
16.6.5 UE Measures under Managerial Disposability
369(4)
16.7 Summary
373(2)
17 Radial Approach for Unified Efficiency Measures
375(20)
17.1 Introduction
375(1)
17.2 Unified Efficiency
376(2)
17.3 Radial Unification between Desirable and Undesirable Outputs
378(3)
17.4 Unified Efficiency under Natural Disposability
381(2)
17.5 Unified Efficiency under Managerial Disposability
383(2)
17.6 Coal-Fired Power Plants in the United States
385(7)
17.6.1 ISO and RTO
385(2)
17.6.2 Data
387(1)
17.6.3 Unified Efficiency
388(2)
17.6.4 Unified Efficiency under Natural Disposability
390(1)
17.6.5 Unified Efficiency under Managerial Disposability
391(1)
17.7 Summary
392(1)
Appendix
393(2)
18 Scale Efficiency
395(22)
18.1 Introduction
395(1)
18.2 Scale Efficiency under Natural Disposability: Non-Radial Approach
396(3)
18.3 Scale Efficiency under Managerial Disposability: Non-Radial Approach
399(2)
18.4 Scale Efficiency under Natural Disposability: Radial Approach
401(2)
18.5 Scale Efficiency under Managerial Disposability: Radial Approach
403(1)
18.6 United States Coal-Fired Power Plants
404(10)
18.6.1 The Clean Air Act
404(2)
18.6.2 Production Factors
406(1)
18.6.3 Research Concerns
407(3)
18.6.4 Unified Efficiency Measures of Power Plants
410(1)
18.6.5 Mean Tests
410(4)
18.7 Summary
414(3)
19 Measurement in Time Horizon
417(26)
19.1 Introduction
417(1)
19.2 Malmquist Index
418(1)
19.3 Frontier Shift in Time Horizon
419(5)
19.3.1 No Occurrence of Frontier Crossover
419(3)
19.3.2 Occurrence of Frontier Crossover
422(2)
19.4 Formulations for Natural Disposability
424(6)
19.4.1 No Occurrence of Frontier Crossover
425(3)
19.4.2 Occurrence of Frontier Crossover
428(2)
19.5 Formulations under Managerial Disposability
430(5)
19.5.1 No Occurrence of Frontier Crossover
430(2)
19.5.2 Occurrence of Frontier Crossover
432(3)
19.6 Energy Mix of Industrial Nations
435(2)
19.7 Summary
437(3)
Appendix
440(3)
20 Returns to Scale and Damages to Scale
443(20)
20.1 Introduction
443(1)
20.2 Underlying Concepts
444(3)
20.2.1 Scale Elasticity
444(1)
20.2.2 Differences between RTS and DTS
445(2)
20.3 Non-Radial Approach
447(4)
20.3.1 Scale Economies and RTS under Natural Disposability
447(3)
20.3.2 Scale Damages and DTS under Managerial Disposability
450(1)
20.4 Radial Approach
451(4)
20.4.1 Scale Economies and RTS under Natural Disposability
451(3)
20.4.2 Scale Damages and DTS under Managerial Disposability
454(1)
20.5 Japanese Chemical and Pharmaceutical Firms
455(6)
20.6 Summary
461(2)
21 Desirable and Undesirable Congestions
463(20)
21.1 Introduction
463(1)
21.2 UC and DC
464(5)
21.3 Unified Efficiency and UC under Natural Disposability
469(4)
21.4 Unified Efficiency and DC under Managerial Disposability
473(3)
21.5 Coal-Fired Power Plants in United States
476(1)
21.5.1 Data
476(1)
21.5.2 Occurrence of Congestion
477(1)
21.6 Summary
477(6)
22 Marginal Rate of Transformation and Rate of Substitution
483(22)
22.1 Introduction
483(2)
22.2 Concepts
485(4)
22.2.1 Desirable Congestion
485(1)
22.2.2 MRT and RSU
485(4)
22.3 A Possible Occurrence of Desirable Congestion (DC)
489(2)
22.4 Measurement of MRT and RSU under DC
491(1)
22.5 Multiplier Restriction
492(1)
22.6 Explorative Analysis
493(2)
22.7 International Comparison
495(8)
22.8 Summary
503(2)
23 Returns to Damage and Damages to Return
505(32)
23.1 Introduction
505(1)
23.2 Congestion, Returns to Damage and Damages to Return
506(6)
23.2.1 Undesirable Congestion (UC) and Desirable Congestion (DC)
506(2)
23.2.2 Returns to Damage (RTD) under Undesirable Congestion (UC)
508(2)
23.2.3 Damages to Return (DTR) under Desirable Congestion (DC)
510(1)
23.2.4 Possible Occurrence of Undesirable Congestion (UC) and Desirable Congestion (DC)
511(1)
23.3 Congestion Identification under Natural Disposability
512(7)
23.3.1 Possible Occurrence of Undesirable Congestion (UC)
512(4)
23.3.2 RTD Measurement under the Possible Occurrence of UC
516(3)
23.4 Congestion Identification under Managerial Disposability
519(5)
23.4.1 Possible Occurrence of Desirable Congestion (DC)
519(3)
23.4.2 DTR Measurement under the Possible Occurrence of DC
522(2)
23.5 Energy and Social Sustainability in China
524(10)
23.5.1 Data
524(1)
23.5.2 Empirical Results
524(10)
23.6 Summary
534(3)
24 Disposability Unification
537(24)
24.1 Introduction
537(1)
24.2 Unification between Disposability Concepts
538(2)
24.3 Non-Radial Approach for Disposability Unification
540(5)
24.4 Radial Approach for Disposability Unification
545(4)
24.5 Computational Flow for Disposability Unification
549(2)
24.6 US Petroleum Industry
551(7)
24.6.1 Data
551(3)
24.6.2 Unified Efficiency Measures
554(3)
24.6.3 Scale Efficiency
557(1)
24.7 Summary
558(3)
25 Common Multipliers
561(20)
25.1 Introduction
561(3)
25.2 Computational Framework
564(1)
25.3 Computational Process
564(7)
25.4 Rank Sum Test
571(1)
25.5 Japanese Electric Power Industry
571(9)
25.5.1 Underlying Concepts
571(2)
25.5.2 Empirical Results
573(7)
25.6 Summary
580(1)
26 Property of Translation Invariance to Handle Zero and Negative Values
581(20)
26.1 Introduction
581(1)
26.2 Translation Invariance
582(3)
26.3 Assessment in Time Horizon
585(5)
26.3.1 Formulations under Natural Disposability
585(3)
26.3.2 Formulations under Managerial Disposability
588(1)
26.3.3 Efficiency Growth
588(2)
26.4 Efficiency Measurement for Fuel Mix Strategy
590(8)
26.4.1 Unified Efficiency Measures
591(4)
26.4.2 Fuel Mix Strategy
595(3)
26.5 Summary
598(3)
27 Handling Zero and Negative Values in Radial Measurement
601(24)
27.1 Introduction
601(1)
27.2 Disaggregation
602(1)
27.3 Unified Efficiency Measurement
603(6)
27.3.1 Conceptual Review of Disposability Unification
603(3)
27.3.2 Unified Efficiency under Natural Disposability with Disaggregation
606(1)
27.3.3 Unified Efficiency under Managerial Disposability with Disaggregation
607(2)
27.4 Possible Occurrence of Desirable Congestion
609(6)
27.4.1 Unified Efficiency under Natural and Managerial Disposability (UENM)
609(1)
27.4.2 UENM with Desirable Congestion
610(3)
27.4.3 Investment Rule
613(1)
27.4.4 Computation Summary
614(1)
27.5 US Industrial Sectors
615(7)
27.6 Summary
622(3)
28 Literature Study for DEA Environmental Assessment
625(60)
28.1 Introduction
625(1)
28.2 Applications in Energy and Environment
626(2)
28.3 Energy
628(6)
28.3.1 Electricity
628(3)
28.3.2 Oil, Coal, Gas and Heat
631(2)
28.3.3 Renewable Energies
633(1)
28.4 Energy Efficiency
634(3)
28.5 Environment
637(2)
28.6 Other Applications
639(1)
28.7 Summary
640(1)
References in Section II
641(44)
Index 685
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.
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