Using multiobjective mathematical programming to link national competitiveness, productivity, and innovation
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- 作者：Elias G. Carayannis ; Evangelos Grigoroudis
- 关键词：Innovation ; Productivity ; Competitiveness ; Multiobjective mathematical programming
- 刊名：Annals of Operations Research
- 出版年：2016
- 出版时间：December 2016
- 年：2016
- 卷：247
- 期：2
- 页码：635-655
- 全文大小：
- 刊物类别：Business and Economics
- 刊物主题：Operation Research/Decision Theory; Combinatorics; Theory of Computation;
- 出版者：Springer US
- ISSN：1572-9338
- 卷排序：247
文摘
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.