Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory

Uncertainty involved in human judgments is an important cause of error and loss of credibility in outputs provided by performance appraisal (PA) processes. In few existing studies related to the errors and uncertainties in PA process, solutions mainly based on the use of fuzzy tools have been presen...

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Main Authors: Hossein Nahid Titkanlu, Roxana Fekri, Abbas Keramati
Format: Article
Language:fas
Published: Semnan University 2017-12-01
Series:مجله مدل سازی در مهندسی
Subjects:
Online Access:https://modelling.semnan.ac.ir/article_3520_2f9cb8e0785c3b16422bebc7df0dbc4a.pdf
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author Hossein Nahid Titkanlu
Roxana Fekri
Abbas Keramati
author_facet Hossein Nahid Titkanlu
Roxana Fekri
Abbas Keramati
author_sort Hossein Nahid Titkanlu
collection DOAJ
description Uncertainty involved in human judgments is an important cause of error and loss of credibility in outputs provided by performance appraisal (PA) processes. In few existing studies related to the errors and uncertainties in PA process, solutions mainly based on the use of fuzzy tools have been presented in this regard. These solutions have fundamental deficiencies such as inability to cope with epistemic uncertainty and also problems associated with their implementation. Considering these problems, in this paper, a new model based on evidence theory and fuzzy tools has been proposed to model uncertainty in PA process. The proposed model makes it possible for assessors to provide their ratings commensurate with their level of knowledge and also has the ability to deal with uncertainty caused by randomness and ignorance. In the proposed model which has been designed based on multi-source assessment framework, the uncertainty contained in the data obtained from two common evaluation scales, including Visual Analogue Scale and fuzzy linguistic scale, along with data related to the reliability of evaluator, have been modeled in evidence theory structure. These data then have been aggregated with evidence combination rules. The performance, benefits and improvements resulting from the proposed model, compared with other common aggregation methods in P.A models, have been investigated using simulated data and a numerical example. The results show that the proposed model in addition to improving the ability of dealing with uncertainty in P.A processes and facilitating announcing opinion by raters, provides more accurate results than traditional P.A models.
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spelling doaj.art-0c525c2b6ea44e2284526ed57f3c45af2024-02-23T19:04:44ZfasSemnan Universityمجله مدل سازی در مهندسی2008-48542783-25382017-12-01155141143210.22075/jme.2017.11340.11043520Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theoryHossein Nahid Titkanlu0Roxana Fekri1Abbas Keramati2industrial engineering, payam noor university, tehran, iranindustrial engineering, payam noor university, tehran, iranindustrial engineering, tehran unicersity, tehran, iranUncertainty involved in human judgments is an important cause of error and loss of credibility in outputs provided by performance appraisal (PA) processes. In few existing studies related to the errors and uncertainties in PA process, solutions mainly based on the use of fuzzy tools have been presented in this regard. These solutions have fundamental deficiencies such as inability to cope with epistemic uncertainty and also problems associated with their implementation. Considering these problems, in this paper, a new model based on evidence theory and fuzzy tools has been proposed to model uncertainty in PA process. The proposed model makes it possible for assessors to provide their ratings commensurate with their level of knowledge and also has the ability to deal with uncertainty caused by randomness and ignorance. In the proposed model which has been designed based on multi-source assessment framework, the uncertainty contained in the data obtained from two common evaluation scales, including Visual Analogue Scale and fuzzy linguistic scale, along with data related to the reliability of evaluator, have been modeled in evidence theory structure. These data then have been aggregated with evidence combination rules. The performance, benefits and improvements resulting from the proposed model, compared with other common aggregation methods in P.A models, have been investigated using simulated data and a numerical example. The results show that the proposed model in addition to improving the ability of dealing with uncertainty in P.A processes and facilitating announcing opinion by raters, provides more accurate results than traditional P.A models.https://modelling.semnan.ac.ir/article_3520_2f9cb8e0785c3b16422bebc7df0dbc4a.pdfuncertainty؛ performance appraisalmulti-source assessmentevidence theoryfuzzy set theory
spellingShingle Hossein Nahid Titkanlu
Roxana Fekri
Abbas Keramati
Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
مجله مدل سازی در مهندسی
uncertainty؛ performance appraisal
multi-source assessment
evidence theory
fuzzy set theory
title Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
title_full Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
title_fullStr Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
title_full_unstemmed Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
title_short Modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
title_sort modelling uncertainty in performance appraisal process based on evidence theory and fuzzy theory
topic uncertainty؛ performance appraisal
multi-source assessment
evidence theory
fuzzy set theory
url https://modelling.semnan.ac.ir/article_3520_2f9cb8e0785c3b16422bebc7df0dbc4a.pdf
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AT roxanafekri modellinguncertaintyinperformanceappraisalprocessbasedonevidencetheoryandfuzzytheory
AT abbaskeramati modellinguncertaintyinperformanceappraisalprocessbasedonevidencetheoryandfuzzytheory