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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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References

  • Carayannis, E., & Grigoroudis, E. (2012). Linking innovation, productivity, and competitiveness: Implications for policy and practice. Journal of Technology Transfer, 39(2), 199–218.

    Article  Google Scholar 

  • Carayannis, E. G., & Gonzalez, E. (2003). Creativity and innovation = competitiveness? When, how, and why? In L. V. Shavinina (Ed.), The international handbook on innovation (pp. 587–606). Amsterdam: Pergamon.

    Chapter  Google Scholar 

  • Carayannis, E. G., & Provance, M. (2008). Measuring firm innovativeness: Towards a composite innovation index built on firm innovative posture, propensity and performance attributes. International Journal of Innovation and Regional Development, 1(1), 90–107.

    Article  Google Scholar 

  • Carayannis, E. G., & Sagi, J. (2001). “New” vs. “old” economy: Insights on competitiveness in the global IT industry. Technovation, 21(8), 501–514.

    Article  Google Scholar 

  • Carayannis, E. G., & Sagi, J. (2002). Exploiting opportunities of the new economy: Developing nations in support of the ICT industry. Technovation, 22(8), 517–524.

    Article  Google Scholar 

  • Chakrabarti, A. K. (1990). Innovation and productivity: An analysis of the chemical, textiles and machine tool industries in the US. Research Policy, 19(3), 257–269.

    Article  Google Scholar 

  • Clark, J., & Guy, K. (1998). Innovation and competitiveness: A review. Technology Analysis and Strategic Management, 10(3), 363–395.

    Article  Google Scholar 

  • Diewert, W. E., & Nakamura, A. O. (2007). The measurement of productivity for nations. In J. J. Heckman & E. E. Leamer (Eds.), Handbook of econometrics, 6 Part A (pp. 4501–4586). Amsterdam: Elsevier.

    Google Scholar 

  • Drucker, P. (1985). Innovation and entrepreneurship: Practice and principles. New York: Harper and Row.

  • Ehrgott, M. (2005). Multicriteria optimization. Berlin: Springer.

    Google Scholar 

  • Ehrgott, M., & Wiecek, M. M. (2005). Multiobjective programming. In J. Figueira, S. Greco, & M. Ehrgott (Eds.), Multiple criteria analysis: State of the art surveys (pp. 667–722). New York: Springer.

    Chapter  Google Scholar 

  • European Union. (2012). European competiveness report 2012: Reaping the benefits of globalization. European Commission, Brussels.

  • Grigoroudis, E., & Siskos, Y. (2002). Preference disaggregation for measuring and analysing customer satisfaction: The MUSA method. European Journal of Operational Research, 143(1), 148–170.

    Article  Google Scholar 

  • Grigoroudis, E., & Siskos, Y. (2010). Customer satisfaction evaluation: Methods for measuring and implementing service quality. New York: Springer.

    Book  Google Scholar 

  • Grupp, H., & Schubert, T. (2010). Review and new evidence on composite innovation indicators for evaluating national performance. Research Policy, 39(1), 845–860.

    Article  Google Scholar 

  • Guan, J. C., Yam, R. C. M., Mok, C. K., & Ma, N. (2006). A study of the relationship between competitiveness and technological innovation capability based on DEA models. European Journal of Operational Research, 170(3), 971–986.

    Article  Google Scholar 

  • Hair, J., Anderson, R., Tatham, R., & Black, W. (1995). Multivariate data analysis. Englewood Cliffs: Prentice-Hall International.

    Google Scholar 

  • Hollanders, H. (2009). Measuring innovation: The European Innovation Scoreboard. In E. Villalba (Ed.), Measuring creativity. European Commission Joint Research Centre Luxembourg, pp. 27–40.

  • Hollanders, H., & Arundel, A. (2007). Differences in socio-economic conditions and regulatory environment explaining variation in national innovation performance and policy implications. European Commission, Brussels: INNO-Metrics Thematic Paper.

    Google Scholar 

  • Hollanders, H., & van Cruysen, A. (2008). Rethinking the European Innovation Scoreboard: A new methodology for 2008–2010. INNO Metrics Thematic Paper, European Commission, Brussels.

  • IMD. (2003). World competitiveness yearbook 2003. Institute for Management Development, Lausanne.

  • IMD. (2010). World competitiveness yearbook 2010. Institute for Management Development, Lausanne.

  • Jansen, J. J. P. (2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52(11), 1661–1674.

    Article  Google Scholar 

  • Kao, C., Wu, W.-Y., Hsieh, W.-J., Wang, T.-Y., Lin, C., & Chen, L.-H. (2008). Measuring the national competitiveness of Southeast Asian countries. European Journal of Operational Research, 187(2), 613–628.

    Article  Google Scholar 

  • Keeney, R. L. (1992). Value-focused thinking: A path to creative decision making. London: Harvard University Press.

    Google Scholar 

  • Keeney, R. L., & Raiffa, H. (1976). Decisions with multiple objectives: Preferences and value trade-offs. New York: Wiley.

    Google Scholar 

  • Kirkwood, C. W. (1997). Strategic decision making: Multi-objective decision analysis with spreadsheets. Belmont: Duxbury Press.

    Google Scholar 

  • Krugman, P. (1994). Competitiveness: A dangerous obsession. Foreign Affairs, 73(2), 28–44.

    Article  Google Scholar 

  • Mirkin, B. (2011). Core concepts in data analysis: Summarization, correlation and visualization. London: Springer.

    Book  Google Scholar 

  • Myatt, G. J. (2007). Making sense of data: A practical guide to exploratory data analysis and data mining. Hoboken, New Jersey: Wiley.

    Book  Google Scholar 

  • Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., & Giovannini, E. (2005). Handbook on constructing composite indicators: Methodology and user guide. OECD Statistical Working Papers 2005/3, OECD Publications, Paris.

  • OECD. (2001). Measuring productivity: Measurement of aggregate and industry-level productivity growth. Paris: OECD Publications.

  • Paas, T., & Poltimäe, H. (2010). A comparative analysis of national innovation performance: The Baltic states in the EU context. Working Paper, 78, University of Tartu, Faculty of Economics and Business Administration, Tartu.

  • Porter, M. (1990). The competitive advantage of nations. New York: Simon and Schuster.

    Book  Google Scholar 

  • Pro Inno Europe. (2010). European Innovation Scoreboard (EIS) 2009: Comparative analysis of innovation performance. Enterprise & Industry, Brussels, European Commission.

  • Pro Inno Europe. (2011). Innovation Union Scoreboard 2011. Enterprise & Industry, Brussels, European Commission.

  • Reinert, E. S. (1995). Competitiveness and its predecessors: A 500-year cross-national perspective. Structural Change and Economic Dynamics, 6(1), 23–42.

    Article  Google Scholar 

  • Shane, S. A. (2004). \(50^{\rm th}\) Anniversary article: Technological innovation, product development, and entrepreneurship in Management Science. Management Science, 50(2), 133–144.

    Article  Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (1996). Multivariate analysis. New York: HarperCollins College Publishers.

    Google Scholar 

  • Tofallis, C. (1999). Model building with multiple dependent variables and constraints. The Statistician, 48(3), 371–378.

    Google Scholar 

  • WEF. (2012). The global competitiveness report 2012–2013. Geneva: World Economic Forum.

  • WEF. (2013). Rebuilding Europe’s competitiveness. Geneva: World Economic Forum.

  • Yu, P. L. (1973). A class of solutions for group decision problems. Management Science, 19(3), 936–946.

    Article  Google Scholar 

  • Yu, P. L. (1985). Multiple criteria decision making: Concepts, techniques and extensions. New York: Plenum Press.

    Book  Google Scholar 

  • Zeleny, M. (1974). A concept of compromise solutions and the method of the displaced ideal. Computers and Operations Research, 1(3–4), 479–496.

    Article  Google Scholar 

  • Zeleny, M. (1982). Multiple criteria decision making. New York: McGraw Hill.

    Google Scholar 

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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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