Data Envelopment Analysis: From Normative to Descriptive Performance Evaluation

by Nadia Vazquez Novoa (Author)
©2017 Thesis XVIII, 282 Pages


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.

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

← X | XI →

List of figures

← XII | XIII →

List of tables

← XIV | XV →


AHPAnalytic Hierarchy Process
AMAverage DMU (based on the Arithmetic Mean)
AOSAccounting, Organizations and Society
ARAssurance Regions
BARBehavioral Accounting Research
BCCBanker, Charnes, Cooper Model (DEA with VRS)
BDEABalanced DEA
BDTBehavioral Decision Theory
BfBonus for Financial Performance
BHBusiness Horizons
BnfBonus for Non-Financial Performance
BOMBehavioral Operations Management
BORBehavioral Operations Research
BRIABehavioral Research in Accounting
BSCBalanced Scorecard
CARContemporary Accounting Research
CBECategorization by Elimination
CCRCharnes, Cooper and Rhodes Model (DEA with CRS)
CCR-OOutput-Oriented CCR Model
CRCone Ratio
CRSConstant Returns to Scale
DEAData Envelopment Analysis
DMUDecision Making Unit
DSDecision Sciences
EBAElimination by Aspects
EJOREuropean Journal of Operational Research
EUTExpected Utility Theory
GPGoal Programming
HRMHuman Resources Management
IJPRInternational Journal of Production Research
JAEJournal of Accounting and Economics
JARJournal of Accounting Research
JOMJournal of Operations Management
KPIKey Performance Indicators
MAMassachusetts ← XV | XVI →
MAUTMulti-Attribute Utility Theory
MCDAMultiple Criteria Decision Analysis
MCDMMultiple Criteria Decision Making
MPMedicaments Available on Prescription
MSManagement Science
MSOMManufacturing & Service Operations Management
NJNew Jersey
NYNew York
OMOperations Management
OROperations Research/Oregon (only in the list of references)
OTCOver the Counter
PMSPerformance Measurement Systems
POMProduction and Operations Management
RRange Decoy1
RFRange-Frequency Decoy
ROCReturn on Capital
RSRange Symmetrical
SEUSubjective Expected Utility
SQMStore Squared Meters
TARThe Accounting Review
TDQMTotal Data Quality Management
UDMUUnobserved DMU
USUnited States of America
VRSVariable Returns to Scale
WHWorked Hours
WRWeight 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.


XVIII, 282
ISBN (Softcover)
Publication date
2017 (June)
Behavioral performance evaluation Management decision making Cognitive biases Halo effect Decoy effect
Frankfurt am Main, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2017. XVIII pp., 282 pp., 40 b/w ill., 50 b/w tab.

Biographical notes

Nadia Vazquez Novoa (Author)

Nadia Vazquez Novoa studied Business Administration in Argentina and Germany and pursued her doctoral research at the Technische Universität Braunschweig focusing on management decision making and performance evaluation based on Data Envelopment Analysis (DEA).


Title: Data Envelopment Analysis: From Normative to Descriptive Performance Evaluation
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301 pages