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Measuring university performance using a knowledge‐based balanced scorecard

Measuring university performance using a knowledge‐based balanced scorecard Purpose – The application of fuzzy multiple attribute decision making (FMADM) approach in evaluation of organizations has grown recently, and it is combined with knowledge‐based university evaluation parameters in this study. The paper seeks to propose a FMADM approach for measuring university performance on the four knowledge‐based perspectives of a balanced scorecard. Design/methodology/approach – The approach first summarizes the evaluation indexes extracted from the university performance literature. Then, the relative weights of the chosen evaluation indexes are calculated using the fuzzy analytic hierarchy process (FAHP). The fuzzy sets theory was adapted to university performance analysis. Findings – The results reveal the critical aspects of the evaluation criteria as well as the gaps to improve university performance in order to achieve the aspired/desired level. Research limitations/implications – The paper reveals the key issues in the existing performance evaluation method, especially in the university context. Practical implications – This research analyses the performance of a university based on the knowledge‐based indexes in the four BSC perspectives, using a FME‐MADM approach. It considers specific knowledge‐based metrics for each perspective. Originality/value – Although implementation of the performance measures in universities are now widespread, there is no considerable literature that sufficiently addresses the various issues faced by organizations during university implementation. The paper proposes application of the balanced knowledge‐based scorecard to universities aiming at evaluating performance annually. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Productivity and Performance Management Emerald Publishing

Measuring university performance using a knowledge‐based balanced scorecard

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
1741-0401
DOI
10.1108/17410401111182215
Publisher site
See Article on Publisher Site

Abstract

Purpose – The application of fuzzy multiple attribute decision making (FMADM) approach in evaluation of organizations has grown recently, and it is combined with knowledge‐based university evaluation parameters in this study. The paper seeks to propose a FMADM approach for measuring university performance on the four knowledge‐based perspectives of a balanced scorecard. Design/methodology/approach – The approach first summarizes the evaluation indexes extracted from the university performance literature. Then, the relative weights of the chosen evaluation indexes are calculated using the fuzzy analytic hierarchy process (FAHP). The fuzzy sets theory was adapted to university performance analysis. Findings – The results reveal the critical aspects of the evaluation criteria as well as the gaps to improve university performance in order to achieve the aspired/desired level. Research limitations/implications – The paper reveals the key issues in the existing performance evaluation method, especially in the university context. Practical implications – This research analyses the performance of a university based on the knowledge‐based indexes in the four BSC perspectives, using a FME‐MADM approach. It considers specific knowledge‐based metrics for each perspective. Originality/value – Although implementation of the performance measures in universities are now widespread, there is no considerable literature that sufficiently addresses the various issues faced by organizations during university implementation. The paper proposes application of the balanced knowledge‐based scorecard to universities aiming at evaluating performance annually.

Journal

International Journal of Productivity and Performance Management – Emerald Publishing

Published: Nov 1, 2011

Keywords: University performance evaluation; Knowledge‐based balanced scorecard; Fuzzy screening; Fuzzy analytic hierarchy process; Fuzzy sets theory; Universities; Organizational performance; Balanced scorecard

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