Configurational conditions of national innovation capability: A fuzzy set analysis approach

Anis Khedhaouria () and Roy Thurik
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Anis Khedhaouria: MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier

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Abstract: Building upon the national innovation system perspective and using a fuzzy set qualitative comparative analysis approach (fsQCA), we propose an integrating framework to determine the conditions that lead to high levels of national innovation capability outcomes. We discriminate between five conditions, viz., building national institutions, developing human capital and research systems, improving infrastructures, and facilitating business and market conditions. We do so by analyzing data collected from the Global Innovation Index database containing 74 indicators and 133 countries between 2012 and 2015. The results show no singular path leading to high levels of innovation capability but there are three configurations of conditions. Two configurations highlight that the combination of three distinct conditions is sufficient for a country to reach a high innovation capability (one in which market conditions ‘are not necessary' and one in which institutions ‘are not necessary' conditions). The third configuration highlights that the combination of all five conditions is necessary for a country to reach a very high innovation capability. Some crucial implications of these findings for theory and practice are discussed.

Keywords: Innovation capability; Configurations of conditions; National innovation system; Fuzzy set; Qualitative comparative analysis (search for similar items in EconPapers)
Date: 2017-07
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Citations: View citations in EconPapers (33)

Published in Technological Forecasting and Social Change, 2017, 120, pp.48-58. ⟨10.1016/j.techfore.2017.04.005⟩

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Journal Article: Configurational conditions of national innovation capability: A fuzzy set analysis approach (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02048728

DOI: 10.1016/j.techfore.2017.04.005

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