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Using multiobjective mathematical programming to link national competitiveness, productivity, and innovation

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Abstract

Innovation-driven competitiveness is critical for a country’s long run economic performance in today’s knowledge-based global economy. Although several alternative measures of innovation, productivity, and competitiveness have been proposed, these concepts are inherently linked and this justifies the necessity of studying them in an integrated way, giving emphasis on their potential interrelations. This paper proposes a methodological measurement framework based on multiobjective mathematical programming in order to study the linkage among national innovation, productivity, and competitiveness and discover potential performance patterns. The model is applied in a set of European countries for the period 1998–2008. The empirical results reveal important gaps and show that innovativeness, income, and geographic area significantly affect national performances.

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Authors and Affiliations

  1. School of Business, The George Washington University, 2201 G Street, NW, Duquès Hall, Washington, DC, 20052, USA

    Elias G. Carayannis

  2. School of Production Engineering and Management, Technical University of Crete, University Campus, 73100, Kounoupidiana, Chania, Greece

    Evangelos Grigoroudis

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  1. Elias G. Carayannis
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  2. Evangelos Grigoroudis
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Correspondence to Evangelos Grigoroudis.

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Carayannis, E.G., Grigoroudis, E. Using multiobjective mathematical programming to link national competitiveness, productivity, and innovation. Ann Oper Res 247, 635–655 (2016). https://doi.org/10.1007/s10479-015-1873-x

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  • DOI: https://doi.org/10.1007/s10479-015-1873-x

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