Data Envelopment Analysis: From Normative to Descriptive Performance Evaluation
©2017
Thesis
XVIII,
282 Pages
Summary
The question of modern performance evaluation has been extensively discussed in the literature, leading to a call for models including non-optimizing behaviors of decision makers and non-financial performance criteria. A promising management instrument is data envelopment analysis (DEA), which enables the aggregation of financial and non-financial indicators into a single measure. This work contributes to a better understanding of DEA from two perspectives: (i) it offers a normative solution to the zero-value weight problem and (ii) it provides the first experimental results on behavioral DEA based on an original taxonomy of cognitive biases related to performance evaluation. Behavioral DEA is a completely new research area which yields plenty of research opportunities.
Excerpt
Table Of Contents
- Cover
- Title
- Copyright
- About the author
- About the book
- This eBook can be cited
- Acknowledgments
- Table of contents
- List of figures
- List of tables
- Abbreviations
- Symbols
- 1. Introduction
- 1.1 Motivation
- 1.2 DEA as a performance evaluation tool
- 1.2.1 Normative DEA and value judgment
- 1.2.2 Descriptive DEA, heuristics and biases
- 1.3 Structure of the thesis
- Part A: DEA as a tool for decision making
- 2. DEA from a normative perspective: efficiency and balance scores
- 2.1 DEA methodology as an instrument for relative performance measurement
- 2.1.1 Relative performance measurement
- 2.1.2 DEA methodology
- 2.2 Endogenous weight determination as a main characteristic of DEA
- 2.2.1 Managerial problems resulting from flexible weights
- 2.2.2 Value judgment in DEA
- 2.3 BDEA: relative balance as a complementary measure
- 2.3.1 Motivation for dealing with weight asymmetry
- 2.3.2 The balance score βo
- 2.3.3 Numerical example
- 2.3.4 Managerial implications of BDEA
- 2.3.5 Relative balance of DMUs: summary, criticism and further research
- 3. Managerial decision making
- 3.1 A brief history of research on managerial decision making
- 3.2 Choice
- 3.2.1 Normative and descriptive choice models
- 3.2.2 Heuristics for choice tasks
- 3.3 Judgment: estimation and classification
- 3.3.1 Brunswik’s lens model for judgment
- 3.3.2 Heuristics for estimation and classification tasks
- 3.4 Probabilistic judgment
- 3.4.1 Normative method: Bayesian inference
- 3.4.2 Heuristics for probabilistic judgment
- 3.5 Enhanced descriptive research on decision making
- 3.5.1 Emotions and mood
- 3.5.2 Social preferences and fairness perception
- 4. Efficiency, balance, and biases: DEA from a descriptive perspective
- 4.1 Behavioral research in management accounting
- 4.2 Behavioral research in operations management and operations research
- 4.2.1 Behavioral operations management
- 4.2.2 Behavioral operations research
- 4.3 Biases in performance evaluation tasks
- 4.3.1 Review of taxonomies of biases
- 4.3.2 Taxonomy of biases for performance evaluation
- 4.4 Efficiency, balance and biases
- 4.4.1 Descriptive research in performance evaluation
- 4.4.2 DEA-based behavioral performance evaluation
- Part B: Experimental studies
- 5. DEA scores as performance markers and the halo effect
- 5.1 Theoretical background
- 5.1.1 Performance markers in choice tasks
- 5.1.2 Relative performance evaluation and the halo effect
- 5.2 Hypotheses and predictions
- 5.3 Method
- 5.3.1 Participants and design
- 5.3.2 Case materials
- 5.3.3 Procedure
- 5.4 Results
- 5.4.1 The role of DEA scores as a performance marker
- 5.4.2 Bonus for non-financial performance: a self-generated anchor
- 5.4.3 Supplemental analysis
- 5.5 Discussion
- 6. The decoy effect in relative performance evaluation and the debiasing role of DEA
- 6.1 The decoy effect in choice tasks
- 6.2 Hypotheses and predictions
- 6.3 Method
- 6.3.1 Participants and design
- 6.3.2 Case materials
- 6.3.3 Procedure
- 6.4 Results
- 6.4.1 The decoy effect in a performance evaluation context
- 6.4.2 Using DEA as a debiasing mechanism
- 6.4.3 Supplemental analysis
- 6.5 Discussion
- 7. Summary and future research
- References
- Appendixes
- A) DEA publications in accounting journals
- B) Most productive BAR authors (1962–2012)
- C) Behavioral papers in OM and multidisciplinary journals
- D) Students as surrogates for managers
- E) Vignette Halo effect
- F) Vignette Decoy effect
AHP | Analytic Hierarchy Process |
AM | Average DMU (based on the Arithmetic Mean) |
AOS | Accounting, Organizations and Society |
AR | Assurance Regions |
BAR | Behavioral Accounting Research |
BCC | Banker, Charnes, Cooper Model (DEA with VRS) |
BDEA | Balanced DEA |
BDT | Behavioral Decision Theory |
Bf | Bonus for Financial Performance |
BH | Business Horizons |
Bnf | Bonus for Non-Financial Performance |
BOM | Behavioral Operations Management |
BOR | Behavioral Operations Research |
BRIA | Behavioral Research in Accounting |
BSC | Balanced Scorecard |
CA | California |
CAR | Contemporary Accounting Research |
CBE | Categorization by Elimination |
CCR | Charnes, Cooper and Rhodes Model (DEA with CRS) |
CCR-O | Output-Oriented CCR Model |
CONF | Confirmation-Seeking |
CR | Cone Ratio |
CRS | Constant Returns to Scale |
DEA | Data Envelopment Analysis |
DMU | Decision Making Unit |
DS | Decision Sciences |
EBA | Elimination by Aspects |
Ed. | Editor |
EJOR | European Journal of Operational Research |
EUT | Expected Utility Theory |
GP | Goal Programming |
HRM | Human Resources Management |
IJPR | International Journal of Production Research |
IL | Illinois |
IN | Indiana |
JAE | Journal of Accounting and Economics |
JAR | Journal of Accounting Research |
JOM | Journal of Operations Management |
KPI | Key Performance Indicators |
MA | Massachusetts ← XV | XVI → |
MAUT | Multi-Attribute Utility Theory |
MCDA | Multiple Criteria Decision Analysis |
MCDM | Multiple Criteria Decision Making |
MN | Minnesota |
MP | Medicaments Available on Prescription |
MS | Management Science |
MSOM | Manufacturing & Service Operations Management |
NJ | New Jersey |
NY | New York |
OM | Operations Management |
OR | Operations Research/Oregon (only in the list of references) |
OTC | Over the Counter |
PA | Pennsylvania |
PMS | Performance Measurement Systems |
POM | Production and Operations Management |
PR | Prescriptions |
R | Range Decoy1 |
RF | Range-Frequency Decoy |
ROC | Return on Capital |
RS | Range Symmetrical |
SEU | Subjective Expected Utility |
SQM | Store Squared Meters |
TAR | The Accounting Review |
TDQM | Total Data Quality Management |
TTB | Take-The-Best |
UDMU | Unobserved DMU |
US | United States of America |
VA | Virginia |
VRS | Variable Returns to Scale |
WH | Worked Hours |
WR | Weight Restrictions |
1 Ra (RA in Subchapter 6.3 and ff.) corresponds to the R decoy whose target is alternative a. The case of RF is analogous.
Details
- Pages
- XVIII, 282
- Publication Year
- 2017
- ISBN (PDF)
- 9783631724736
- ISBN (ePUB)
- 9783631724743
- ISBN (MOBI)
- 9783631724750
- ISBN (Softcover)
- 9783631724491
- DOI
- 10.3726/b11277
- Language
- English
- Publication date
- 2017 (June)
- Keywords
- Behavioral performance evaluation Management decision making Cognitive biases Halo effect Decoy effect
- Published
- Frankfurt am Main, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2017. XVIII pp., 282 pp., 40 b/w ill., 50 b/w tab.