Abstract
The paper proposes a novel two-step approach that evaluates countries’ innovation efficiency and their responsiveness to expansions in their innovation inputs, while addressing shortcomings associated with composite indicators. Based on our evaluations, we propose innovation policies tailored to take into account the diverse economic environments of the many countries in our study. Applying multidirectional efficiency analysis on data from the Global Innovation Index, we obtain separate efficiency scores for each innovation input and output. We then estimate different sensitivities for each country, by applying partial least squares on explanatory and response matrices which are determined by the nearest neighbors of the country under consideration. The findings reveal substantial asymmetries with respect to innovation efficiencies and sensitivities, which is indicative of the diversity of national innovation systems. Considering these two dimensions in combination, we outline three policy directions that can be followed, offering a platform for better-informed decision-making.
DOI
10.1016/j.ejor.2020.02.023
Publication Date
2020-09-16
Publication Title
European Journal of Operational Research
Publisher
Elsevier BV
ISSN
0377-2217
Embargo Period
2024-11-19
First Page
1011
Last Page
1024
Recommended Citation
Tziogkidis, P., Philippas, D., Leontitsis, A., & Sickles, R. (2020) 'A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction', European Journal of Operational Research, , pp. 1011-1024. Elsevier BV: Available at: https://doi.org/10.1016/j.ejor.2020.02.023
Comments
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