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Measuring innovation in developing countries: some suggestions to achieve more accurate and useful indicators

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  • Judith Sutz

Abstract

The paper contributes to an ongoing international discussion around how to measure innovation in developing countries and how to turn the findings into useful policy tools. It stresses the fact that innovation needs to be understood as a learning process, and concomitantly measuring innovation needs to pay special attention to related aspects that are not usually taken into account. Which people have knowledge in the firm, and which kind of knowledge they have are examples of those aspects. Innovation surveys have not yet displayed major policy impact in developing countries; they usually go little farther from what is already known. They can also give misleading results, for instance by assuming that innovation is a value-free concept, which it is not the case. The paper analyses concretely how to redress these flaws, aiming at a better design of innovation policies in developing countries.

Suggested Citation

  • Judith Sutz, 2012. "Measuring innovation in developing countries: some suggestions to achieve more accurate and useful indicators," International Journal of Technological Learning, Innovation and Development, Inderscience Enterprises Ltd, vol. 5(1/2), pages 40-57.
    • Handle: RePEc:ids:ijtlid:v:5:y:2012:i:1/2:p:40-57
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    References listed on IDEAS

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    Cited by:

    1. Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies," MPRA Paper 109137, University Library of Munich, Germany.
    2. Carolina Pasciaroni & Andrea Barbero, 2019. "Desempeño Innovador y Cooperación. Una Aplicación De La Técnica Oxaca Blinder," Asociación Argentina de Economía Política: Working Papers 4184, Asociación Argentina de Economía Política.

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