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Development of a complementary fuzzy decision support system for employees’ performance evaluation

Author

Listed:
  • Sabina Mirzaei Nobari
  • Vahidreza Yousefi
  • Ehsan Mehrabanfar
  • Amir Hossein Jahanikia
  • Amir Mohammad Khadivi

Abstract

This study aims to improve employee evaluation system in one of the leading automobile manufacturers in Iran by designing a fuzzy decision support system (F.D.S.S.). Since this manufacturer is a large-sized company with over 35,000 employees, the number of managers regularly evaluated requires too much capacity from the human resource team and hence increases the rate of possible misjudgements. However, the proposed F.D.S.S. can reduce the rate of unfair or inconsistent assessments by converting qualitative assessments of the panel to linguistic variables. This action increases the precision of assessment and improves the quality of evaluations. The proposed F.D.S.S. is compared with a fuzzy TOPSIS method to confirm its reliability and validity in which the results show consistency with fuzzy TOPSIS. As a result, the F.D.S.S. is implemented for evaluation of managers in this automobile company instead of the traditional method.

Suggested Citation

  • Sabina Mirzaei Nobari & Vahidreza Yousefi & Ehsan Mehrabanfar & Amir Hossein Jahanikia & Amir Mohammad Khadivi, 2019. "Development of a complementary fuzzy decision support system for employees’ performance evaluation," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 32(1), pages 492-509, January.
    • Handle: RePEc:taf:reroxx:v:32:y:2019:i:1:p:492-509
    DOI: 10.1080/1331677X.2018.1556106
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