Use of virtual index for measuring efficiency of innovation systems : a cross-country study

In this study we propose a virtual index for measuring the relative innovativeness of countries. Using a multistage virtual benchmarking process, the best and rational benchmark is extracted for inefficient ISs. Furthermore, Tobit and Ordinary Least Squares (OLS) regression models are used to investigate the likelihood of changes in inefficiencies by investigating country-specific factors. The empirical results relating to the virtual benchmarking process suggest that the OLS regression model would better explain changes in the performance of innovation- inefficient countries.

[1]  Hugo Hollanders,et al.  Using Science and Technology Indicators to support knowledge-based economies , 2006 .

[2]  B. Lundvall Dynamics of Industry and Innovation: Organizations, Networks and Systems National Innovation Systems -analytical Concept and Development Tool National Innovation Systems -analytical Concept and Development Tool National Innovation Systems -analytical Concept and Development Tool , 2022 .

[3]  Charles Edquist,et al.  Systems of Innovation Approaches - Their Emergence and Characteristics , 2013 .

[4]  S. Winter,et al.  An evolutionary theory of economic change , 1983 .

[5]  J. S. Katz,et al.  Indicators for Complex Innovation Systems , 2006 .

[6]  Terttu Luukkonen,et al.  Additionality of EU framework programmes , 2000 .

[7]  C. Lovell,et al.  Stochastic Frontier Analysis: Frontmatter , 2000 .

[8]  William Golden,et al.  National Innovation Systems and Entrepreneurship , 2008 .

[9]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[10]  Bengt-Åke Lundvall,et al.  National Systems of Innovation: towards a theory of innovation and interactive learning London: Pint , 1995 .

[11]  B. Lundvall,et al.  National Systems of Innovation: User-Producer Relationships, National Systems of Innovation and Internationalisation , 2010 .

[12]  Christopher Meyer Relentless Growth: How Silicon Valley Innovation Strategies Can Work in Your Business , 1997 .

[13]  C. Freeman Technology policy and economic performance : lessons from Japan , 1987 .

[14]  Anne Preston,et al.  Women Scientists and Engineers Employed in Industry: Why So Few? , 1994 .

[15]  Tim Coelli,et al.  A multi-stage methodology for the solution of orientated DEA models , 1998, Oper. Res. Lett..

[16]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[17]  L. Mytelka Pathways and Policies to (Bio) Pharmaceutical Innovation Systems in Developing Countries , 2006 .

[18]  Anthony Arundel,et al.  Science, Technology and Innovation Indicators in a Changing World: Responding to Policy Needs , 2007 .

[19]  A. Charnes,et al.  Data Envelopment Analysis Theory, Methodology and Applications , 1995 .

[20]  Valentina Bosetti,et al.  Using Data Envelopment Analysis to Evaluate Environmentally Conscious Tourism Management , 2004 .

[21]  Gianni Lorenzoni,et al.  Creating a Strategic Center to Manage a Web of Partners , 1995 .

[22]  M. Aoki,et al.  Reconstructing Macroeconomics: Demand Saturation-Creation and Economic Growth , 2002 .

[23]  Patrick Llerena,et al.  Evaluating and Comparing the innovation performance of the United States and the European Union Expert report prepared for the TrendChart Policy Workshop 2005 , 2005 .

[24]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[25]  Mats Magnusson,et al.  The value of managerial learning in R&D , 2004 .

[26]  R. Nelson,et al.  National Innovation Systems , 1993 .

[27]  John Maleyeff,et al.  Quantitative Models for Performance Evaluation and Benchmarking: DEA with Spreadsheets and DEA Excel Solver , 2005 .

[28]  Bait Verspagen,et al.  Estimating international technology spillovers using technology flow matrices , 1997 .

[29]  Bengt-Åke Lundvall,et al.  Why Study National Systems and National Styles of Innovation , 1998 .