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Measuring efficiency of innovation using combined Data Envelopment Analysis and Structural Equation Modeling: empirical study in EU regions

Author

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  • Kleoniki Kalapouti

    (Aristotle University of Thessaloniki)

  • Konstantinos Petridis

    (University of Macedonia)

  • Chrisovalantis Malesios

    (Democritus University of Thrace)

  • Prasanta Kumar Dey

    (Aston University)

Abstract

The main aim of this paper is to investigate the impact of patent applications, development level, employment level and degree of technological diversity on innovation efficiency. Innovation efficiency is derived by relating innovation inputs and innovation outputs. Expenditures in Research and Development and Human Capital stand for innovation inputs. Technological knowledge diffusion that comes from spatial and technological neighborhood stands for innovation output. We derive innovation efficiency using Data Envelopment Analysis for 192 European regions for a 12-year period (1995–2006). We also examine the impact of patents production, development and employment level and the level of technological diversity on innovation efficiency using Structural Equation Modeling. This paper contributes a method of innovation efficiency estimation in terms of regional knowledge spillovers and causal relationship of efficiency measurement criteria. The study reveals that the regions presenting high innovation activities through patents production have higher innovation efficiency. Additionally, our findings show that the regions characterized by high levels of employment achieve innovation sources exploitation efficiently. Moreover, we find that the level of regional development has both a direct and indirect effect on innovation efficiency. More accurately, transition and less developed regions in terms of per capita GDP present high levels of efficiency if they innovate in specific and limited technological fields. On the other hand, the more developed regions can achieve high innovation efficiency if they follow a more decentralized innovation policy.

Suggested Citation

  • Kleoniki Kalapouti & Konstantinos Petridis & Chrisovalantis Malesios & Prasanta Kumar Dey, 2020. "Measuring efficiency of innovation using combined Data Envelopment Analysis and Structural Equation Modeling: empirical study in EU regions," Annals of Operations Research, Springer, vol. 294(1), pages 297-320, November.
    • Handle: RePEc:spr:annopr:v:294:y:2020:i:1:d:10.1007_s10479-017-2728-4
    DOI: 10.1007/s10479-017-2728-4
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