Introduction to the theory and application of data envelopment analysis: a foundation text with integrated software
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| Format: | Book |
| Language: | English |
| Published: |
Norwell, Mass. [u.a.]
Kluwer Academic Publishers
2003
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| Edition: | 2. print |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXI, 281 S. graph. Darst. |
| ISBN: | 0792374290 9780792374299 |
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| 100 | 1 | |a Thanassoulis, Emmanuel |e Verfasser |0 (DE-588)171896742 |4 aut | |
| 245 | 1 | 0 | |a Introduction to the theory and application of data envelopment analysis |b a foundation text with integrated software |c by Emmanuel Thanassoulis |
| 250 | |a 2. print | ||
| 264 | 1 | |a Norwell, Mass. [u.a.] |b Kluwer Academic Publishers |c 2003 | |
| 300 | |a XXI, 281 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Data envelopment analysis | |
| 650 | 4 | |a Industrial efficiency |x Measurement | |
| 650 | 4 | |a Industrial productivity |x Measurement | |
| 650 | 0 | 7 | |a Produktivitätsmessung |0 (DE-588)4175810-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Effizienzanalyse |0 (DE-588)4151072-0 |2 gnd |9 rswk-swf |
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| 689 | 0 | 1 | |a Effizienzanalyse |0 (DE-588)4151072-0 |D s |
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Record in the Search Index
| _version_ | 1804138060830474240 |
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| adam_text | Contents
List of Tables xiii
List of Figures xv
Preface xvii
Abbreviations xxii
1- INTRODUCTION TO PERFORMANCE 1
MEASUREMENT
1.1 Introduction 1
1.2 Why Measure Performance? 1
1.3 Performance Measurement Methods in Outline 4
1.3.1 Unit of assessment 4
1.3.2 Performance Indicators 5
1.3.3 Modelling Methods of Comparative Performance 6
Measurement
1.3.3.1 Parametric methods for measuring 6
comparative performance
1.3.3.2 Non-Parametric Methods for Measuring 9
Comparative Performance
1.4 Some Areas Where Uses of DEA Have Been Reported 13
1.4.1 Financial Services 13
1.4.2 Regulation 15
1.4.3 Police Services 17
1.5 Conclusion 19
2- DEFINITIONS OF EFFICIENCY AND RELATED 21
MEASURES
2.1 Introduction 21
2.2 Unit of Assessment and Input-Output variables 21
2.3 Pareto-efficiency and Measures of Input and Output 22
Efficiency.
viii DATA ENVELOPMENT ANALYSIS
2.4 Input Overall, Allocative and Technical Efficiencies 26
2.5 An Illustration 29
2.6 Questions 31
Appendix 2.1: Mathematical Definitions 32
Appendix 2.2: Deriving Graphical Measures of Input 34
Efficiencies
3. DATA ENVELOPMENT ANALYSIS UNDER 37
CONSTANT RETURNS TO SCALE: BASIC
PRINCIPLES
3.1 Introduction 37
3.2 Basic Steps in Measuring Efficiency by DEA 37
3.2.1 Constructing a Production Possibility Set in the 38
Single-input Single-output Case
3.2.2 Using the PPS to Derive Efficiency Measures 40
3.3 Using Linear Programming to Measure Efficiency in the 41
Single-input Single-output Case
3.4 Using DEA To Measure Technical Input Efficiency in 45
the Single-Output Multi-input Case: A Graphical
Illustration
3.5 Using Linear Programming to Measure Technical Input 49
Efficiency in the Single-output Multi-input Case
3.6 Using DEA to Measure Technical Output Efficiency in 52
the Single-input Multi-output Case: A Graphical
Illustration
3.7 Using Linear Programming to Measure Technical 54
Output Efficiency in the Single-input Multi-Output Case
3.8 Questions 57
Appendix 3.1: Introduction to Linear Programming 59
Appendix 3.2: Postulates for Constructing the 64
Production Possibility Set in DEA Under
Constant Returns to Scale
4. DATA ENVELOPMENT ANALYSIS UNDER 65
CONSTANT RETURNS TO SCALE: GENERAL
MODELS
4.1 Introduction 65
4.2 A General Purpose Linear Programming Model for 65
Assessing Technical Input Efficiency
4.3 A General Purpose Linear Programming Model for 68
Assessing Technical Output Efficiency
4.4 Value-Based DEA Models 71
4.5 Interpretation of Value-Based DEA Models 74
CONTENTS ix
4.6 Efficient Peers and Targets in DEA 78
4.6.1 Targets 78
4.6.2 Efficient Peers 80
4.7 Input and Output Allocative Efficiencies 81
4.7.1 Cost Minimising Efficiencies 81
4.7.2 Revenue Maximising Efficiencies 83
4.8 Questions 85
5. USING DATA ENVELOPMENT ANALYSIS IN 89
PRACTICE
5.1 Introduction 89
5.2 Choosing Inputs and Outputs in A DEA Assessment 89
5.3 Information Obtained in the Course of a DEA 92
Assessment
5.4 Interpreting the Solution of a DEA Envelopment Model 93
5.4.1 Pareto-Inefficient DMUs 94
5.4.2 Pareto-Efficient DMUs 97
5.5 Interpreting the Solution of a Value-based Dea Model 98
5.5.1 Pareto-Efficient DMUs 99
5.5.2 Pareto-Inefficient DMUs 103
5.6 An Illustrative Use of Warwick DEA Software 105
5.7 Practical Tips for Carrying Out DEA Assessments 111
5.8 Questions 114
Appendix 5.1: Warwick DEA Software 119
Appendix 5.2 120
6. DATA ENVELOPMENT ANALYSIS UNDER 123
VARIABLE RETURNS TO SCALE
6.1 Introduction 123
6.2 The Concept of Returns to Scale 124
6.3 Assessing DEA Efficiency Under Variable Returns to 125
Scale: A Graphical Illustration
6.4 Assessing DEA Efficiency Under Variable Returns to 129
Scale: The Generic Envelopment Model
6.5 Value-based DEA Models Under VRS 136
6.6 Scale Efficiency, Returns to Scale and Most Productive 139
Scale Size
6.6.1 Scale Efficiency 140
6.6.2 Identifying Returns to Scale By Means of DEA 142
Models
6.6.3 Most Productive Scale Size 147
6.7 Practical Use of DEA Models Under VRS 153
x DATA ENVELOPMENT ANALYSIS
6.7.1 Envelopment Models 153
6.7.2 Value-based Models 154
6.8 DEA Assessments Under VRS By Means of Warwick 155
DEA Software
6.9 DEA Assessments Under Non-Increasing or Non- 158
Decreasing Returns to Scale
6.10 Questions 160
7. ASSESSING POLICY EFFECTIVENESS AND 163
PRODUCTIVITY CHANGE USING DEA
7.1 Introduction ]63
7.2 Disentangling Managerial And Policy Efficiency: An 164
outline
7.3 Disentangling Managerial and Policy Efficiency: The 168
generic approach
7.4 Disentangling Managerial and Policy Efficiency: I l
Illustrative examples
7.5 Assessing Productivity Change By Means of DEA: A 75
graphical introduction to the Malmquist Index
7.6 Assessing Productivity Change By Means of DEA: The 81
Malmquist Index in the general case
7.7 Assessing Productivity Change Using Malmquist 1°4
Indices: Illustrative example
7.8 Capturing the Impact of Scale Size Changes on 189
Productivity
7.9 The Cost Malmquist Type Index 191
7.10 Questions 194
Appendix 7.1 196
8. INCORPORATING VALUE JUDGEMENTS IN DEA 199
ASSESSMENTS
8.1 Introduction 199
8.2 Why we May Want to Incorporate Value Judgements in 199
DEA Assessments
8.3 Methods for Incorporating Value Judgements in DEA 201
8.4 Using Weights Restrictions to Incorporate Value 201
Judgements in DEA
8.4.1 Restrictions Applied to DEA Weights 202
8.4.2 Restrictions Applied to Virtual Inputs and Outputs 203
8.5 Some Approaches to Estimating the Parameters of 204
Weights Restrictions
CONTENTS xi
8.6 Interpreting the Results of DEA Models with Weights 209
Restrictions
8.6.1 Effects of Weights Restrictions on the 210
Interpretation of the Efficiency Measure Yielded
By a DEA Model
8.6.2 Effects of Weights Restrictions on DEA Targets 211
8.6.3 Additional Effects of Absolute Weights 212
Restrictions
8.7 Using unobserved DMUs to incorporate value 212
Judgements in DEA
8.7.1 A Procedure for Improving Envelopment in DEA 214
8.7.2 Advantages and Drawbacks of UDMUs in 217
Incorporating Value Judgements in DEA.
8.8 Questions 219
Appendix 8.1: Some Features of the DEA Efficiency 222
Measure Under Weights Restrictions
Appendix 8.2: Some Features of Targets Yielded by Dea 225
Models Under Weights Restrictions
9. EXTENSIONS TO BASIC DEA MODELS 227
9.1 Introduction 227
9.2 Assessing Efficiency Under Exogenously Fixed Input- 227
Output Variables
9.3 Identifying Preferred Pareto-Efficient Input-Output 235
Levels by DEA
9.3.1 Case Where no Input or Output May Deteriorate 236
9.3.2 Case Where Some Input or Output May 238
Deteriorate
9.4 Assessing Dmus in the Presence of Categorical 244
Variables
9.5 Questions 248
10. A LIMITED USER GUIDE FOR WARWICK DEA 251
SOFTWARE
10.1 Introduction 251
10.2 Preparing your Data Input before you Invoke the 252
Programme
10.3 Initiating a Run of the Programme 253
10.4 Options Menu 253
10.5 The Run Menu 258
10.6 The Advanced Menu 265
10.7 File Handling 267
10.8 Some Common Error Messages 268
xii DATA ENVELOPMENT ANALYSIS
Author Index 271
Topic Index 273
References 277
List of Tables
2.1 Units of Input per Unit of Output 29
3.1 Observed Input-Output Correspondences 38
3.2 Input Levels at Tax Offices ( Resident) 45
3.3 Operating Expenditure and Activity Levels 52
3.4 Patients per Operating Expenditure 53
3.5 Labour Hours per 1000 Accounts 57
3.6 Data on a Set of Tax Offices 58
3.7 Processing Lime (hours) per Unit of Each Product 59
3.8 Lindo Output on Model [MA3.1.1] 61
3.9 Primal Model in Standard Maximisation Form 62
3.10 Dual to Model [MA3.1.2] 63
4.1 Input-Output Data of Distribution Centres 67
4.2 Data on Tax Offices 86
4.3 Hours of Work and Financial Products Sold 87
4.4 Revised Data for the Salespersons of Question 5 88
4.5 Data on Salespersons when Unit Revenues are Available 88
5.1 Data on Bank Branches 105
5.2 Peers to Branch B1 Scaled by Output 110
5.3 Warehouse Input-Output Data 114
5.4 Data on Building Materials Stores 116
5.5 Data on Salespersons 118
6.1 Data on Customer Services Offices 126
6.2 Data on Distribution Centres 131
6.3 Sample Input-Output Data $ 138
6.4 Pizza Sales 160
6.5 Clothes Sales Data 161
6.6 Input Output Data on Local Property Tax Offices 162
7.1 Managerial Efficiencies (%) 176
7.2 Policy Efficiencies (%) 177
xiv DATA ENVELOPMENT ANALYSIS
7.3 Decomposition of the Malmquist Index of the 180
Productivity Change of the Company Operating at F in
Period t and at G in Period t+1, Figure 7.5
7.4 Decomposition of the Malmquist Index of DMU j0 183
7.5 Capturing the Impact of Scale on the Malmquist Index of 190
Productivity Change
7.6 Output Levels Per Unit of Input 194
7.7 Output Levels Per Unit Input 194
8.1 Example Data Set 213
8.2 Latest Full Quarter of the Year 219
8.3 Newspaper Circulation Data 220
8.4 Revised Data for Residential Care Homes 221
9.1 Sales in ( $m) and Floor Space (m2) 231
9.2 Input-Output Variables for Assessing Market Efficiency 232
9.3 Most Recent Data on Tax Offices 248
9.4 Hours of Work and Financial Products Sold 249
9.5 Input-Output Data for Comparing Police Forces 249
9.6 Data on Salespersons 250
List of Figures
1.1 Performance Measurement and Control 3
1.2 An Illustration of Parametric Methods for Efficiency 8
Assessments
1.3 An Illustration of an Assessment by Data Envelopment 10
Analysis
2.1 A DMU Transforms Inputs into Outputs 22
2.2 Measures of Input and Output Efficiency 25
2.3 Contrasting Technical and Input Allocative Efficiencies 27
2.4 Feasible Input Levels for Securing a Unit of Output 30
A2.1.1 Deriving the Technical Input Efficiency of DMU A 34
3.1 Constructing a Production Possibility Set 39
3.2 Tax Offices Plotted in Input Space 46
3.3 The Production Possibility Set (PPS) Derived From TO1- 47
TO4
3.4 Measuring Technical Input Efficiency 48
3.5 Computing the Technical Output Efficiency of Hospital E 53
5.1 Illustrative Input File to Warwick DEA Software 106
5.2 The WarwickDEA Software Screen Before Data Has Been 106
Read in
5.3 Warwick DEA Software Menu Options after Data Has Been 107
Read in
5.4 The Execute screen for Specifying Output Content and 107
Format from the Warwick DEA Software
6.1 Assessing SOs using CRS 126
xvi DATA ENVELOPMENT ANALYSIS
6.2 Assessing SOs using DEA under VRS 128
6.3 Interpreting Scale Efficiency 141
6.4 Illustrating IRS, CRS and DRS 143
6.5 Illustrating the Conditions in (6.7) 146
6.6 Illustration of Warwick DEA Software screen for 157
Assessments in the Input Orientation under VRS
6.7 An Illustration of Non-Increasing Returns to Scale 158
6.8 An Illustration of Non-Decreasing Returns to Scale 158
7.1 Separating Managerial and Policy Efficiencies 166
7.2 Assessing Policy Efficiency Using Adjusted Input Levels 167
7.3 Centres C1-C3 Constitute the Active Units (DMUs) 174
7.4 Measuring Productivity Change 179
7.5 Measuring Productivity Change when the Efficient 180
Boundary Moves Over Time
7.6 Moving Year 2 Data to the List of Inactive DMUs 187
7.7 Selecting All Year 1 Data Plus Centre 1 Year 2 Data 188
(above) and, Excluding the Assessed Unit (Centre 1 year 2
data) as Comparator (below).
7.8 Measuring the Impact of Scale Size on Productivity 189
8.1 Imposing the Weights Restriction 20 uD - up 0 209
8.2 Extended Production Possibility Set 213
9.1 Measuring Input Efficiency when Input 2 is Exogenously 228
Fixed
9.2 Setting Radial and Phase 2 Priories to Reflect that Only 235
OUTLETSALES Are Not Exogenously Fixed
9.3 Alternative Targets to Render DMU U2 Pareto-Efficient 236
9.4 Using DM Specified Ideal Targets to Arrive at Pareto- 239
Efficient Targets
9.5 Giving Equal Priority to the Improvement of Labour and 243
Packages Delivered
|
| adam_txt |
Contents
List of Tables xiii
List of Figures xv
Preface xvii
Abbreviations xxii
1- INTRODUCTION TO PERFORMANCE 1
MEASUREMENT
1.1 Introduction 1
1.2 Why Measure Performance? 1
1.3 Performance Measurement Methods in Outline 4
1.3.1 Unit of assessment 4
1.3.2 Performance Indicators 5
1.3.3 Modelling Methods of Comparative Performance 6
Measurement
1.3.3.1 Parametric methods for measuring 6
comparative performance
1.3.3.2 Non-Parametric Methods for Measuring 9
Comparative Performance
1.4 Some Areas Where Uses of DEA Have Been Reported 13
1.4.1 Financial Services 13
1.4.2 Regulation 15
1.4.3 Police Services 17
1.5 Conclusion 19
2- DEFINITIONS OF EFFICIENCY AND RELATED 21
MEASURES
2.1 Introduction 21
2.2 Unit of Assessment and Input-Output variables 21
2.3 Pareto-efficiency and Measures of Input and Output 22
Efficiency.
viii DATA ENVELOPMENT ANALYSIS
2.4 Input Overall, Allocative and Technical Efficiencies 26
2.5 An Illustration 29
2.6 Questions 31
Appendix 2.1: Mathematical Definitions 32
Appendix 2.2: Deriving Graphical Measures of Input 34
Efficiencies
3. DATA ENVELOPMENT ANALYSIS UNDER 37
CONSTANT RETURNS TO SCALE: BASIC
PRINCIPLES
3.1 Introduction 37
3.2 Basic Steps in Measuring Efficiency by DEA 37
3.2.1 Constructing a Production Possibility Set in the 38
Single-input Single-output Case
3.2.2 Using the PPS to Derive Efficiency Measures 40
3.3 Using Linear Programming to Measure Efficiency in the 41
Single-input Single-output Case
3.4 Using DEA To Measure Technical Input Efficiency in 45
the Single-Output Multi-input Case: A Graphical
Illustration
3.5 Using Linear Programming to Measure Technical Input 49
Efficiency in the Single-output Multi-input Case
3.6 Using DEA to Measure Technical Output Efficiency in 52
the Single-input Multi-output Case: A Graphical
Illustration
3.7 Using Linear Programming to Measure Technical 54
Output Efficiency in the Single-input Multi-Output Case
3.8 Questions 57
Appendix 3.1: Introduction to Linear Programming 59
Appendix 3.2: Postulates for Constructing the 64
Production Possibility Set in DEA Under
Constant Returns to Scale
4. DATA ENVELOPMENT ANALYSIS UNDER 65
CONSTANT RETURNS TO SCALE: GENERAL
MODELS
4.1 Introduction 65
4.2 A General Purpose Linear Programming Model for 65
Assessing Technical Input Efficiency
4.3 A General Purpose Linear Programming Model for 68
Assessing Technical Output Efficiency
4.4 Value-Based DEA Models 71
4.5 Interpretation of Value-Based DEA Models 74
CONTENTS ix
4.6 Efficient Peers and Targets in DEA 78
4.6.1 Targets 78
4.6.2 Efficient Peers 80
4.7 Input and Output Allocative Efficiencies 81
4.7.1 Cost Minimising Efficiencies 81
4.7.2 Revenue Maximising Efficiencies 83
4.8 Questions 85
5. USING DATA ENVELOPMENT ANALYSIS IN 89
PRACTICE
5.1 Introduction 89
5.2 Choosing Inputs and Outputs in A DEA Assessment 89
5.3 Information Obtained in the Course of a DEA 92
Assessment
5.4 Interpreting the Solution of a DEA Envelopment Model 93
5.4.1 Pareto-Inefficient DMUs 94
5.4.2 Pareto-Efficient DMUs 97
5.5 Interpreting the Solution of a Value-based Dea Model 98
5.5.1 Pareto-Efficient DMUs 99
5.5.2 Pareto-Inefficient DMUs 103
5.6 An Illustrative Use of Warwick DEA Software 105
5.7 Practical Tips for Carrying Out DEA Assessments 111
5.8 Questions 114
Appendix 5.1: Warwick DEA Software 119
Appendix 5.2 120
6. DATA ENVELOPMENT ANALYSIS UNDER 123
VARIABLE RETURNS TO SCALE
6.1 Introduction 123
6.2 The Concept of Returns to Scale 124
6.3 Assessing DEA Efficiency Under Variable Returns to 125
Scale: A Graphical Illustration
6.4 Assessing DEA Efficiency Under Variable Returns to 129
Scale: The Generic Envelopment Model
6.5 Value-based DEA Models Under VRS 136
6.6 Scale Efficiency, Returns to Scale and Most Productive 139
Scale Size
6.6.1 Scale Efficiency 140
6.6.2 Identifying Returns to Scale By Means of DEA 142
Models
6.6.3 Most Productive Scale Size 147
6.7 Practical Use of DEA Models Under VRS 153
x DATA ENVELOPMENT ANALYSIS
6.7.1 Envelopment Models 153
6.7.2 Value-based Models 154
6.8 DEA Assessments Under VRS By Means of Warwick 155
DEA Software
6.9 DEA Assessments Under Non-Increasing or Non- 158
Decreasing Returns to Scale
6.10 Questions 160
7. ASSESSING POLICY EFFECTIVENESS AND 163
PRODUCTIVITY CHANGE USING DEA
7.1 Introduction ]63
7.2 Disentangling Managerial And Policy Efficiency: An 164
outline
7.3 Disentangling Managerial and Policy Efficiency: The 168
generic approach
7.4 Disentangling Managerial and Policy Efficiency: I'l
Illustrative examples
7.5 Assessing Productivity Change By Means of DEA: A ' 75
graphical introduction to the Malmquist Index
7.6 Assessing Productivity Change By Means of DEA: The '81
Malmquist Index in the general case
7.7 Assessing Productivity Change Using Malmquist 1°4
Indices: Illustrative example
7.8 Capturing the Impact of Scale Size Changes on 189
Productivity
7.9 The Cost Malmquist Type Index 191
7.10 Questions 194
Appendix 7.1 196
8. INCORPORATING VALUE JUDGEMENTS IN DEA 199
ASSESSMENTS
8.1 Introduction 199
8.2 Why we May Want to Incorporate Value Judgements in 199
DEA Assessments
8.3 Methods for Incorporating Value Judgements in DEA 201
8.4 Using Weights Restrictions to Incorporate Value 201
Judgements in DEA
8.4.1 Restrictions Applied to DEA Weights 202
8.4.2 Restrictions Applied to Virtual Inputs and Outputs 203
8.5 Some Approaches to Estimating the Parameters of 204
Weights Restrictions
CONTENTS xi
8.6 Interpreting the Results of DEA Models with Weights 209
Restrictions
8.6.1 Effects of Weights Restrictions on the 210
Interpretation of the Efficiency Measure Yielded
By a DEA Model
8.6.2 Effects of Weights Restrictions on DEA Targets 211
8.6.3 Additional Effects of Absolute Weights 212
Restrictions
8.7 Using unobserved DMUs to incorporate value 212
Judgements in DEA
8.7.1 A Procedure for Improving Envelopment in DEA 214
8.7.2 Advantages and Drawbacks of UDMUs in 217
Incorporating Value Judgements in DEA.
8.8 Questions 219
Appendix 8.1: Some Features of the DEA Efficiency 222
Measure Under Weights Restrictions
Appendix 8.2: Some Features of Targets Yielded by Dea 225
Models Under Weights Restrictions
9. EXTENSIONS TO BASIC DEA MODELS 227
9.1 Introduction 227
9.2 Assessing Efficiency Under Exogenously Fixed Input- 227
Output Variables
9.3 Identifying Preferred Pareto-Efficient Input-Output 235
Levels by DEA
9.3.1 Case Where no Input or Output May Deteriorate 236
9.3.2 Case Where Some Input or Output May 238
Deteriorate
9.4 Assessing Dmus in the Presence of Categorical 244
Variables
9.5 Questions 248
10. A LIMITED USER GUIDE FOR WARWICK DEA 251
SOFTWARE
10.1 Introduction 251
10.2 Preparing your Data Input before you Invoke the 252
Programme
10.3 Initiating a Run of the Programme 253
10.4 Options Menu 253
10.5 The Run Menu 258
10.6 The Advanced Menu 265
10.7 File Handling 267
10.8 Some Common Error Messages 268
xii DATA ENVELOPMENT ANALYSIS
Author Index 271
Topic Index 273
References 277
List of Tables
2.1 Units of Input per Unit of Output 29
3.1 Observed Input-Output Correspondences 38
3.2 Input Levels at Tax Offices (\ Resident) 45
3.3 Operating Expenditure and Activity Levels 52
3.4 Patients per \ Operating Expenditure 53
3.5 Labour Hours per 1000 Accounts 57
3.6 Data on a Set of Tax Offices 58
3.7 Processing Lime (hours) per Unit of Each Product 59
3.8 Lindo Output on Model [MA3.1.1] 61
3.9 Primal Model in Standard Maximisation Form 62
3.10 Dual to Model [MA3.1.2] 63
4.1 Input-Output Data of Distribution Centres 67
4.2 Data on Tax Offices 86
4.3 Hours of Work and Financial Products Sold 87
4.4 Revised Data for the Salespersons of Question 5 88
4.5 Data on Salespersons when Unit Revenues are Available 88
5.1 Data on Bank Branches 105
5.2 Peers to Branch B1 Scaled by Output 110
5.3 Warehouse Input-Output Data 114
5.4 Data on Building Materials Stores 116
5.5 Data on Salespersons 118
6.1 Data on Customer Services Offices 126
6.2 Data on Distribution Centres 131
6.3 Sample Input-Output Data\$ 138
6.4 Pizza Sales 160
6.5 Clothes Sales Data 161
6.6 Input Output Data on Local Property Tax Offices 162
7.1 Managerial Efficiencies (%) 176
7.2 Policy Efficiencies (%) 177
xiv DATA ENVELOPMENT ANALYSIS
7.3 Decomposition of the Malmquist Index of the 180
Productivity Change of the Company Operating at F in
Period t and at G in Period t+1, Figure 7.5
7.4 Decomposition of the Malmquist Index of DMU j0 183
7.5 Capturing the Impact of Scale on the Malmquist Index of 190
Productivity Change
7.6 Output Levels Per Unit of Input 194
7.7 Output Levels Per Unit Input 194
8.1 Example Data Set 213
8.2 Latest Full Quarter of the Year 219
8.3 Newspaper Circulation Data 220
8.4 Revised Data for Residential Care Homes 221
9.1 Sales in (\$m) and Floor Space (m2) 231
9.2 Input-Output Variables for Assessing Market Efficiency 232
9.3 Most Recent Data on Tax Offices 248
9.4 Hours of Work and Financial Products Sold 249
9.5 Input-Output Data for Comparing Police Forces 249
9.6 Data on Salespersons 250
List of Figures
1.1 Performance Measurement and Control 3
1.2 An Illustration of Parametric Methods for Efficiency 8
Assessments
1.3 An Illustration of an Assessment by Data Envelopment 10
Analysis
2.1 A DMU Transforms Inputs into Outputs 22
2.2 Measures of Input and Output Efficiency 25
2.3 Contrasting Technical and Input Allocative Efficiencies 27
2.4 Feasible Input Levels for Securing a Unit of Output 30
A2.1.1 Deriving the Technical Input Efficiency of DMU A 34
3.1 Constructing a Production Possibility Set 39
3.2 Tax Offices Plotted in Input Space 46
3.3 The Production Possibility Set (PPS) Derived From TO1- 47
TO4
3.4 Measuring Technical Input Efficiency 48
3.5 Computing the Technical Output Efficiency of Hospital E 53
5.1 Illustrative Input File to Warwick DEA Software 106
5.2 The WarwickDEA Software Screen Before Data Has Been 106
Read in
5.3 Warwick DEA Software Menu Options after Data Has Been 107
Read in
5.4 The Execute screen for Specifying Output Content and 107
Format from the Warwick DEA Software
6.1 Assessing SOs using CRS 126
xvi DATA ENVELOPMENT ANALYSIS
6.2 Assessing SOs using DEA under VRS 128
6.3 Interpreting Scale Efficiency 141
6.4 Illustrating IRS, CRS and DRS 143
6.5 Illustrating the Conditions in (6.7) 146
6.6 Illustration of Warwick DEA Software screen for 157
Assessments in the Input Orientation under VRS
6.7 An Illustration of Non-Increasing Returns to Scale 158
6.8 An Illustration of Non-Decreasing Returns to Scale 158
7.1 Separating Managerial and Policy Efficiencies 166
7.2 Assessing Policy Efficiency Using Adjusted Input Levels 167
7.3 Centres C1-C3 Constitute the Active Units (DMUs) 174
7.4 Measuring Productivity Change 179
7.5 Measuring Productivity Change when the Efficient 180
Boundary Moves Over Time
7.6 Moving Year 2 Data to the List of Inactive DMUs 187
7.7 Selecting All Year 1 Data Plus Centre 1 Year 2 Data 188
(above) and, Excluding the Assessed Unit (Centre 1 year 2
data) as Comparator (below).
7.8 Measuring the Impact of Scale Size on Productivity 189
8.1 Imposing the Weights Restriction 20 uD - up 0 209
8.2 Extended Production Possibility Set 213
9.1 Measuring Input Efficiency when Input 2 is Exogenously 228
Fixed
9.2 Setting Radial and Phase 2 Priories to Reflect that Only 235
OUTLETSALES Are Not Exogenously Fixed
9.3 Alternative Targets to Render DMU U2 Pareto-Efficient 236
9.4 Using DM Specified Ideal Targets to Arrive at Pareto- 239
Efficient Targets
9.5 Giving Equal Priority to the Improvement of Labour and 243
Packages Delivered |
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| any_adam_object_boolean | 1 |
| author | Thanassoulis, Emmanuel |
| author_GND | (DE-588)171896742 |
| author_facet | Thanassoulis, Emmanuel |
| author_role | aut |
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| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
| edition | 2. print |
| format | Book |
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| id | DE-604.BV035099455 |
| illustrated | Illustrated |
| index_date | 2024-07-02T22:13:41Z |
| indexdate | 2024-07-09T21:22:11Z |
| institution | BVB |
| isbn | 0792374290 9780792374299 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016767454 |
| oclc_num | 635306397 |
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| physical | XXI, 281 S. graph. Darst. |
| publishDate | 2003 |
| publishDateSearch | 2003 |
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| publisher | Kluwer Academic Publishers |
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| spelling | Thanassoulis, Emmanuel Verfasser (DE-588)171896742 aut Introduction to the theory and application of data envelopment analysis a foundation text with integrated software by Emmanuel Thanassoulis 2. print Norwell, Mass. [u.a.] Kluwer Academic Publishers 2003 XXI, 281 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Data envelopment analysis Industrial efficiency Measurement Industrial productivity Measurement Produktivitätsmessung (DE-588)4175810-9 gnd rswk-swf Effizienzanalyse (DE-588)4151072-0 gnd rswk-swf Produktivitätsmessung (DE-588)4175810-9 s Effizienzanalyse (DE-588)4151072-0 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016767454&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Thanassoulis, Emmanuel Introduction to the theory and application of data envelopment analysis a foundation text with integrated software Data envelopment analysis Industrial efficiency Measurement Industrial productivity Measurement Produktivitätsmessung (DE-588)4175810-9 gnd Effizienzanalyse (DE-588)4151072-0 gnd |
| subject_GND | (DE-588)4175810-9 (DE-588)4151072-0 |
| title | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software |
| title_auth | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software |
| title_exact_search | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software |
| title_exact_search_txtP | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software |
| title_full | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software by Emmanuel Thanassoulis |
| title_fullStr | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software by Emmanuel Thanassoulis |
| title_full_unstemmed | Introduction to the theory and application of data envelopment analysis a foundation text with integrated software by Emmanuel Thanassoulis |
| title_short | Introduction to the theory and application of data envelopment analysis |
| title_sort | introduction to the theory and application of data envelopment analysis a foundation text with integrated software |
| title_sub | a foundation text with integrated software |
| topic | Data envelopment analysis Industrial efficiency Measurement Industrial productivity Measurement Produktivitätsmessung (DE-588)4175810-9 gnd Effizienzanalyse (DE-588)4151072-0 gnd |
| topic_facet | Data envelopment analysis Industrial efficiency Measurement Industrial productivity Measurement Produktivitätsmessung Effizienzanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016767454&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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