Effects of Data Envelopment Analysis on Performance Assessment: A Cognitive Approach

This paper examines the Data Envelopment Analysis (DEA) methodology from a cognitive perspective. Specifically, it analyzes (a) the role of DEA scores as an overall efficiency measure and (b) to what extent the presence of DEA scores for a non-financial performance appraisal influences a posterior financial performance assessment. The study confirms that the efficiency score acts as a strong performance marker when deciding on which decision making units (DMUs) should be awarded for their non-financial performance. Furthermore, it shows that the results of the non-financial performance evaluation may act as an anchor which significantly influences a posterior financial assessment. These insights have practical consequences for planning, reporting, and controlling processes that incorporate DEA efficiency scores. Effects of Data Envelopment Analysis on Performance Assessment: A Cognitive Approach

[1]  Katrin R. Harich,et al.  Brand equity: the halo effect measure , 1995 .

[2]  Cláudia S. Sarrico,et al.  Pitfalls and protocols in DEA , 2001, Eur. J. Oper. Res..

[3]  Marshall W. Meyer,et al.  Subjectivity and the Weighting of Performance Measures: Evidence from a Balanced Scorecard , 2003 .

[4]  Donald E. Conlon,et al.  Justice at the millennium: a meta-analytic review of 25 years of organizational justice research. , 2001, The Journal of applied psychology.

[5]  N. Avkiran,et al.  Pushing the DEA research envelope , 2010 .

[6]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[7]  Yong Zha,et al.  Dealing with missing data based on data envelopment analysis and halo effect , 2013 .

[8]  R. Kohli,et al.  Representation and Inference of Lexicographic Preference Models and Their Variants , 2007 .

[9]  Heinz Ahn,et al.  Measuring the relative balance of DMUs , 2012, Eur. J. Oper. Res..

[10]  Richard S. Segall,et al.  Linkage Discovery with Glossaries , 2014 .

[11]  D. Moore Conflicts of Interest: Commentary: Conflicts of Interest in Accounting , 2005 .

[12]  Marko Sarstedt,et al.  Is there a tacit acceptance of student samples in marketing and management research? , 2010, Int. J. Data Anal. Tech. Strateg..

[13]  Ken T. Trotman,et al.  The Balanced Scorecard: The Effect of Strategy Information on Performance Evaluation Judgments , 2011 .

[14]  Léopold Simar,et al.  Estimating and bootstrapping Malmquist indices , 1999, Eur. J. Oper. Res..

[15]  G Gigerenzer,et al.  Reasoning the fast and frugal way: models of bounded rationality. , 1996, Psychological review.

[16]  Natalia Karelaia,et al.  Thirst for confirmation in multi-attribute choice: Does search for consistency impair decision performance? , 2006 .

[17]  Jill R. Hopper,et al.  A Research Tool to Increase Attention to Experimental Materials: Manipulating Presentation Format , 2003 .

[18]  James M. Peters,et al.  Decision making, cognitive science and accounting: An overview of the intersection , 1993 .

[19]  R. Merton The Matthew Effect in Science , 1968, Science.

[20]  B. Newell,et al.  Empirical tests of a fast-and-frugal heuristic: Not everyone "takes-the-best" , 2003 .

[21]  Matthew Q. McPherson,et al.  Are Hospital Pharmacies More Efficient if They Employ Nurses , 2010 .

[22]  Lan Guo,et al.  Reducing conflict in balanced scorecard evaluations , 2007 .

[23]  Robin M. Hogarth,et al.  Simple Models for Multiattribute Choice with Many Alternatives: When It Does and Does Not Pay to Face Trade-offs with Binary Attributes , 2005, Manag. Sci..

[24]  T. Gilovich,et al.  Heuristics and Biases: Introduction – Heuristics and Biases: Then and Now , 2002 .

[25]  Thomas L. Albright,et al.  Debiasing Balanced Scorecard Evaluations , 2004 .

[26]  Michael D. Shields,et al.  Effects of Accounting‐Method Choices on Subjective Performance‐Measure Weighting Decisions: Experimental Evidence on Precision and Error Covariance , 2005 .

[27]  David R Shanks,et al.  On the role of recognition in decision making. , 2004, Journal of experimental psychology. Learning, memory, and cognition.

[28]  R. Peterson On the Use of College Students in Social Science Research: Insights from a Second‐Order Meta‐analysis , 2001 .

[29]  Arndt Bröder,et al.  Challenging some common beliefs: Empirical work within the adaptive toolbox metaphor , 2008, Judgment and Decision Making.

[30]  Timothy D. Wilson,et al.  Mental contamination and the debiasing problem. , 2002 .

[31]  Gerd Gigerenzer,et al.  The recognition heuristic: A decade of research , 2011, Judgment and Decision Making.

[32]  Lysann Damisch,et al.  Olympic medals as fruits of comparison? Assimilation and contrast in sequential performance judgments. , 2006, Journal of experimental psychology. Applied.

[33]  R. Banker,et al.  The Balanced Scorecard: Judgmental Effects of Performance Measures Linked to Strategy , 2004 .

[34]  Thomas Mussweiler,et al.  Subliminal anchoring: Judgmental consequences and underlying mechanisms , 2005 .

[35]  William N. Dilla,et al.  Relative Weighting of Common and Unique Balanced Scorecard Measures by Knowledgeable Decision Makers , 2005 .

[36]  William Remus,et al.  Graduate students as surrogates for managers in experiments on business decision making , 1986 .

[37]  Lionel Page,et al.  Last shall be first: A field study of biases in sequential performance evaluation on the Idol series , 2010 .

[38]  Arnold Reisman,et al.  Content analysis of data envelopment analysis literature and its comparison with that of other OR/MS fields , 2004, J. Oper. Res. Soc..

[39]  Jennifer Kunz,et al.  Performance measures and learning , 2011 .

[40]  D. Larcker,et al.  Innovations in Performance Measurement: Trends and Research Implications , 1998 .

[41]  Thomas Gilovich,et al.  Research DialogueAnchoring unbound , 2010 .

[42]  Andy Neely,et al.  Performance measurement system design , 1995 .

[43]  Paula van Veen-Dirks,et al.  Financial versus non-financial information: The impact of information organization and presentation in a Balanced Scorecard , 2010 .

[44]  Thomas Gilovich,et al.  Incidental environmental anchors , 2008 .

[45]  Taylor Randall,et al.  Performance Implications of Strategic Performance Measurement in Financial Services Firms , 2003 .

[46]  Daniel M. Oppenheimer,et al.  Heuristics made easy: an effort-reduction framework. , 2008, Psychological bulletin.

[47]  Páll Rikhardsson,et al.  Experienced and Novice Investors: Does Environmental Information Influence Investment Allocation Decisions? , 2008 .

[48]  Emmanuel Thanassoulis,et al.  Data Envelopment Analysis:the mathematical programming approach to efficiency analysis , 2008 .

[49]  Rajiv Ramnath,et al.  Co-engineering Applications and Adaptive Business Technologies in Practice: Enterprise Service Ontologies, Models, and Frameworks , 2009 .

[50]  Steven E. Salterio,et al.  The Balanced Scorecard: The Effects of Assurance and Process Accountability on Managerial Judgment , 2004 .

[51]  Richard Fisher,et al.  Students as surrogates for practicing accountants: Further evidence , 2012 .

[52]  Steven E. Salterio,et al.  The Balanced Scorecard: Judgmental Effects of Common and Unique Performance Measures , 2000 .

[53]  Emmanuel Thanassoulis,et al.  Incorporating Value Judgments in DEA , 2004 .

[54]  P. Fishburn Methods of Estimating Additive Utilities , 1967 .

[55]  Matthew D. Hall,et al.  Accounting information and managerial work , 2010 .

[56]  John Wang,et al.  Encyclopedia of Business Analytics and Optimization , 2018 .

[57]  H. Simon,et al.  Invariants of human behavior. , 1990, Annual review of psychology.

[58]  Emmanuel Thanassoulis,et al.  Introduction to the theory and application of data envelopment analysis , 2001 .

[59]  Prasanta K. Jana,et al.  KD-Tree Based Clustering for Gene Expression Data , 2014 .

[60]  A. Tversky Elimination by aspects: A theory of choice. , 1972 .

[61]  Timothy D. Wilson,et al.  The halo effect: Evidence for unconscious alteration of judgments. , 1977 .

[62]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[63]  M. R. Alirezaee,et al.  The master Malmquist index measurement using DEA-based weighted average efficiency , 2012, Int. J. Data Anal. Tech. Strateg..

[64]  Mahesh Gopinath,et al.  The role of desires in sequential impulsive choices , 2005 .

[65]  Joan L. Luft,et al.  Nonfinancial Information and Accounting: A Reconsideration of Benefits and Challenges , 2009 .

[66]  Flávia Maria Santoro,et al.  A case study on the representation of cognitive decision-making within business process , 2013, Int. J. Inf. Decis. Sci..

[67]  K Aparna,et al.  Comprehensive Study and Analysis of Partitional Data Clustering Techniques , 2015 .

[68]  Vandra L. Huber,et al.  Judgment by heuristics: Effects of ratee and rater characteristics and performance standards on performance-related judgments , 1987 .

[69]  Lawrence M. Seiford,et al.  Data envelopment analysis (DEA) - Thirty years on , 2009, Eur. J. Oper. Res..