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Quality & Quantity

, Volume 46, Issue 1, pp 103–115 | Cite as

Performance measurement considering the interdependence of evaluators and criteria

  • Sheu Hua Chen
  • Pei Wen Wang
  • Hong Tau Lee
Research Paper

Abstract

This research constructs a performance evaluation mechanism in regard to the interdependence of evaluators and criteria. The interest in performance evaluation has spawned a number of studies that investigated criteria or evaluators for organizations’ performance evaluation. However, very little attention has been paid to address the relationship between the evaluators and criteria. It is quite clear that there are different standpoints exist in different evaluators, consequently particular evaluators usually emphasize certain groups of criteria more than others. On the other hand, considering different criteria the strength of relation of evaluator changes accordingly. We address the existence of interaction between evaluator and criteria, because the two factors play major roles in the performance evaluation. This consideration gives top managers the chance to explore and realize the relationship between evaluators and criteria. It also reveals the evaluators’ synthetic standpoints about criteria, which are meaningful for managerial purposes.

Keywords

Human resource Performance evaluation Analytical network process Multi-criteria decision making 

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References

  1. Ahmad S., Schroeder R.G.: The impact of human resource management practices on operational performance: recognizing country and industry differences. J. Oper. Manag. 21, 19–43 (2003)CrossRefGoogle Scholar
  2. Chapman D.S., Webster J.: The use of technologies in the recruiting, screening, and selection processes for job candidates. Int. J. Sel. Assess. 11(2/3), 113–120 (2003)CrossRefGoogle Scholar
  3. Collier D.W.: Measuring the performance of R&D department. Res. Manag. 20(2), 30–34 (1977)Google Scholar
  4. Coombs G., Gomez-Mejia L.R.: Cross-functional pay strategies in high-technology firms. Compens. Benefits Rev. 23(5), 40–48 (1991)CrossRefGoogle Scholar
  5. Cooper R.G., Kleinschmidt E.J.: Benchmarking the firm’s critical success factors in new produce development. J. Prod. Innov. Manag. 12, 374–391 (1995)CrossRefGoogle Scholar
  6. Cordero R.: The measurement of innovation performance in the firm: an overview. Res. Policy 19, 185–192 (1990)CrossRefGoogle Scholar
  7. Evans J.R.: An exploratory study of performance measurement systems and relationships with performance results. J. Oper. Manag. 22, 219–232 (2004)CrossRefGoogle Scholar
  8. Hillier F., Lieberman G.J.: Introduction to Operations Research, 6th edn. McGrew-Hill, New York (1995)Google Scholar
  9. Jayaram J., Droge C., Vickery S.K.: The impact of human resource management practices on manufacturing performance. J. Oper. Manag. 18, 1–20 (1999)CrossRefGoogle Scholar
  10. Kavanagh P., Benson J., Brown J.: Understanding performance appraisal fairness. Asia Pac. J. Hum. Resour. 45(2), 132–150 (2007)CrossRefGoogle Scholar
  11. Keller T.R., Holland W.E.: The measurement of performance among research and development employees: a longitudinal analysis. IEEE Trans. Eng. Manag. 29(2), 54–58 (1982)Google Scholar
  12. Kim B., Oh H.: An effective R&D performance measurement system: survey of Korean R&D researchers. Omega Int. J. Manag. Sci. 30, 19–31 (2002)CrossRefGoogle Scholar
  13. Loch C., Stein L., Terwiesch C.: Measuring development performance in the electronic industry. J. Prod. Innov. Manag. 13, 3–20 (1996)CrossRefGoogle Scholar
  14. Meade L., Sarkis J.: A strategic analysis of logistics and supply chain management systems using analytical network process. Transp. Res. 34(3), 201–215 (1998)CrossRefGoogle Scholar
  15. Melnyk S.A., Stewart D.M., Swing M.: Metrics and performance measurement in operations management: dealing with the metrics maze. J. Oper. Manag. 22, 209–217 (2004)CrossRefGoogle Scholar
  16. Moser M.R.: Measuring performance in R&D settings. Res. Manag. 28(5), 31–33 (1985)Google Scholar
  17. Nankervis A., Compton R.L.: Performance management: theory in practice?. Asia Pac. J. Hum. Resour. 44(1), 83–101 (2006)CrossRefGoogle Scholar
  18. Saaty T.L.: Decision Making: The Analytic Hierarchy Process. University of Pittsburg, Pittsburg (1988)Google Scholar
  19. Saaty T.L., Takizawa M.: Dependence/independence: from linear hierarchies to nonlinear network. Eur. J. Oper. Res. 26, 229–237 (1986)CrossRefGoogle Scholar
  20. Saaty T.L.: Decision Making with Dependence and Feedback: The Analytic Network Process. RWS Publications, Pittsburgh (1996)Google Scholar
  21. Sarkis J.: Evaluating environmentally conscious business practices. Eur. J. Oper. Res. 107(1), 159–174 (1998)CrossRefGoogle Scholar
  22. Sarkis J., Sundarraj R.P.: Hub location at digital equipment corporation: a comprehensive analysis of qualitative and quantitative factors. Eur. J. Oper. Res. 137(2), 336–347 (2002)CrossRefGoogle Scholar
  23. Singh K.: Impact of HR practices on perceived firm performance in India. Asia Pac. J. Hum. Resour. 42(3), 301–317 (2004)CrossRefGoogle Scholar
  24. Werner B.M., Souder W.E.: Measuring R&D performance: state of the art. Res. Technol. Manag. 40(2), 34–42 (1997)Google Scholar
  25. Whitley R., Frost P.A.: The measurement of performance in research. Hum. Relat. 24, 161–178 (1971)CrossRefGoogle Scholar
  26. Wilson D.K., Mueser R., Raelin J.A.: New look at performance appraisal for scientists and engineers. Res. Technol. Manag. 37(4), 51–54 (1994)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Distribution ManagementNational Chin-Yi University of TechnologyTaiping CityTaiwan, ROC
  2. 2.Department of Marketing ManagementTransworld Institute of TechnologyDouliu CityTaiwan, ROC
  3. 3.Department of Industrial Engineering and ManagementNational Chin-Yi University of TechnologyTaiping CityTaiwan, ROC

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