Crespo, NunoCrespo, Cátia Fernandes2018-11-092018-11-0920160148-2963http://hdl.handle.net/10400.8/3636This 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.engNational Innovation SystemsGII datafsQCACountry level of economic developmentCountry innovation outcomesCountry input innovation pillarsjournal articlehttps://doi.org/10.1016/j.jbusres.2016.04.123