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Diagnosis for Effectiveness: Performance Assessment from a Diagnostic Measurement Perspective with Big Data

Author

Listed:
  • Jiyuan Zhang, Ph.D

    (Department of Human Resources, Nanjing Urban Construction Investment Holding (Group) Co., Ltd, Nanjing, China,)

  • Cody Ding

    (Department of Educational Psychology, Research, &evaluation, University of Missouri-St. Louis, St. Louis, MO, USA,)

Abstract

Although traditional performance assessment of employees and organizations has the potential advantages, there are also potential problematic issues such as detrimental to quality improvement or negative perceptions. The purpose of this paper is to propose a diagnostic assessment framework for monitoring and improving performance of both employees and organizations. This framework is called "diagnosis for effectiveness," which provides information that needs to adjust managing strategies while they are still happening and guides both managers and employees in making decisions about future strategic actions. In addition, we suggest a big data approach via spatial models for evidence-based performance decision.

Suggested Citation

  • Jiyuan Zhang, Ph.D & Cody Ding, 2014. "Diagnosis for Effectiveness: Performance Assessment from a Diagnostic Measurement Perspective with Big Data," International Journal of Business and Social Research, LAR Center Press, vol. 4(6), pages 1-11, June.
    • Handle: RePEc:lrc:larijb:v:4:y:2014:i:6:p:1-11
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    References listed on IDEAS

    as
    1. Angelo S. DeNisi & Robert D. Pritchard, 2006. "Performance Appraisal, Performance Management and Improving Individual Performance: A Motivational Framework," Management and Organization Review, The International Association for Chinese Management Research, vol. 2(2), pages 253-277, July.
    2. DeNisi, Angelo S. & Pritchard, Robert D., 2006. "Performance Appraisal, Performance Management and Improving Individual Performance: A Motivational Framework," Management and Organization Review, Cambridge University Press, vol. 2(2), pages 253-277, July.
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