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The relative efficiency analysis of innovation activities with uncertainty: the case of Korean electronic equipment industry

Innovation: Management, Policy & Practice
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  • Innovation
  • Efficiency
  • Data Envelopment Analysis
  • Fuzzy Set Theory
  • Uncertainty
  • Indicators


The evaluation and management of the efficiency of innovation activities is essential for the improvement of innovation performance. However, only a few studies on evaluating innovation efficiency quantitatively have been conducted to date due to the complexity and uncertainty of innovation indicators. Therefore, a new approach to measure innovation efficiency with the consideration of the complexity and uncertainty of innovation indicators is proposed in this study. I suggested an application method of the fuzzy data envelopment analysis (DEA) which is useful for dealing with imprecise data or language variables to measure innovation efficiency quantitatively and applied the method to the Korean electronic equipment industry. The results show that the industry can save 28.7% of inputs by improving its pure innovation efficiency. In order to do this, the industry is recommended to downsize the production scale since decreasing returns to scale (DRS) was found in its production technology.

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