A multi-granular linguistic model for management decision-making in performance appraisal

The performance appraisal is a relevant process to keep and improve the competitiveness of companies in nowadays. In spite of this relevance, the current performance appraisal models are not sufficiently well-defined either designed for the evaluation framework in which they are defined. This paper proposes a performance appraisal model where the assessments are modelled by means of linguistic information provided by different sets of reviewers in order to manage the uncertainty and subjectivity of such assessments. Therefore, the reviewers could express their assessments in different linguistic scales according to their knowledge about the evaluated employees, defining a multi-granular linguistic evaluation framework. Additionally, the proposed model will manage the multi-granular linguistic labels provided by appraisers in order to compute collective assessments about the employees that will be used by the management team to make the final decision about them.

[1]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..

[2]  Robert L. Cardy,et al.  Performance Appraisal: Alternative Perspectives , 1993 .

[3]  Ulrich Derigs,et al.  SYNOPSE: a model-based decision support system for the evaluation of flight schedules for cargo airlines , 1998, Decis. Support Syst..

[4]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[5]  Piero P. Bonissone,et al.  Selecting Uncertainty Calculi and Granularity: An Experiment in Trading-off Precision and Complexity , 1985, UAI.

[6]  G. Bortolan,et al.  The problem of linguistic approximation in clinical decision making , 1988, Int. J. Approx. Reason..

[7]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[8]  Luis Martínez,et al.  Sensory evaluation based on linguistic decision analysis , 2007 .

[9]  Jonathan Lawry,et al.  A methodology for computing with words , 2001, Int. J. Approx. Reason..

[10]  Cristina G. Banks,et al.  Performance Appraisers as Test Developers , 1985 .

[11]  Francisco Herrera,et al.  Managing non-homogeneous information in group decision making , 2005, Eur. J. Oper. Res..

[12]  Robert T. Clemen,et al.  Making Hard Decisions: An Introduction to Decision Analysis , 1997 .

[13]  Francisco Herrera,et al.  A fusion approach for managing multi-granularity linguistic term sets in decision making , 2000, Fuzzy Sets Syst..

[14]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[15]  Slawomir Zadrozny,et al.  Computing with Words in Decision Making Through Individual and Collective Linguistic Choice Rules , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[16]  Lotfi A. Zadeh,et al.  A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[17]  Francisco Herrera,et al.  A multigranular hierarchical linguistic model for design evaluation based on safety and cost analysis , 2005, Int. J. Intell. Syst..

[18]  Badredine Arfi Fuzzy Decision Making in Politics: A Linguistic Fuzzy-Set Approach (LFSA) , 2005, Political Analysis.

[19]  John B. Miner Development and application of the rated ranking technique in performance appraisal , 1988 .

[20]  J. García-Lapresta,et al.  Majority decisions based on difference of votes , 2001 .

[21]  Francisco Herrera,et al.  A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[22]  Isabelle Lavallée,et al.  Human resources management. , 2009, International journal of orthodontics.

[23]  Andrew P. Sage,et al.  Uncertainty in Artificial Intelligence , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[24]  Francisco Herrera,et al.  The 2-Tuple Linguistic Computational Model. Advantages of Its Linguistic Description, Accuracy and Consistency , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[25]  Jian-Bo Yang,et al.  A Fuzzy Model for Design Evaluation Based on Multiple Criteria Analysis in Engineering Systems , 2006, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[26]  Paul P. Wang Computing with Words , 2001 .

[27]  C. Fletcher Performance appraisal and management: The developing research agenda , 2001 .

[28]  José L. Verdegay,et al.  On aggregation operations of linguistic labels , 1993, Int. J. Intell. Syst..

[29]  Kevin R. Murphy,et al.  Performance appraisal: An organizational perspective. , 1991 .

[30]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[31]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decision-making , 1988 .

[32]  Thierry Marchant,et al.  Evaluation and Decision Models: A Critical Perspective , 2000 .

[33]  Antonio Jiménez-Martín,et al.  A decision support system for multiattribute utility evaluation based on imprecise assignments , 2003, Decis. Support Syst..

[34]  Ching-Hsue Cheng,et al.  Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation , 2002, Eur. J. Oper. Res..

[35]  Chen T. Chen,et al.  Applying Linguistic Decision-Making Method to Deal with Service Quality Evaluation Problems , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[36]  Ronald R. Yager,et al.  An approach to ordinal decision making , 1995, Int. J. Approx. Reason..

[37]  G. Milkovich,et al.  The Current State of Performance Appraisal Research and Practice: Concerns, Directions, and Implications , 1992 .

[38]  James N. Baron,et al.  Strategic Human Resources: Frameworks for General Managers , 1999 .

[39]  Ana Pradera,et al.  Double aggregation operators , 2004, Fuzzy Sets Syst..