Global Innovation Index: moving beyond the absolute value of ranking with a fuzzy-set analysis

Crespo, Nuno; Crespo, Cátia Fernandes

http://hdl.handle.net/10400.8/3636

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Authors

Crespo, Nuno

Crespo, Cátia Fernandes

Abstract(s)

This study constitutes a novel application of fuzzy-set qualitative comparative analysis to Global Innovation Index (GII) data. Building on the National Innovation System approach, this study posits that a country may achieve high innovation performance via several combinations of causal conditions. These conditions are the five input pillars of GII: institutions, human capital and research, infrastructure, market sophistication and business sophistication. By defining two subsamples of countries (high-income and low-income countries), several interesting findings emerged. Several causal combinations of conditions lead to high innovation performance in both groups of countries. In order to obtain better innovation performance, the low-income countries evidence more multifaceted solutions. Results show that none of the conditions are necessary for predicting high innovation performance in both samples. Additionally, in the low-income group of countries, none of the conditions, individually, is, sufficient to predict higher innovation performance, while in the high-income group of countries the infrastructure and human capital and research conditions, on their own, are sufficient to obtain better innovation performance. Results indicate that the political decision-making processes required for improving the level of innovation need to be different for each group of countries.