Montalvo, Carlos and Moghayer, Saeed (2011): State of an innovation system: theoretical and empirical advance towards an innovation efficiency index.
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Innovation is currently seen as a cornerstone not only for economic development but also as an intrinsic human activity that could help to face the great challenges of human kind. Given the importance of innovation in the new European 2020 Strategy, measuring progress but also monitoring what drives innovation becomes crucial for policy development. Following upon this strategy the new European flag initiative “Innovation Union” called for a new “single” indicator on innovation. Currently the information infrastructure on innovation in Europe contains a number of indicators. Most of the current indicators at the national or sector levels use a performance theoretical framework based on an efficiency model of inputs and outputs. The last five editions of CIS have been a bastion of innovation policy research during the last decade. Despite this, CIS has been criticised for not having an umbrella framework that unifies its different underpinnings to explain what drives innovation to actual innovation and economic outcomes. In this paper we propose a framework that enables the theoretical and empirical linkages between the drivers of innovation to innovation performance via the integration of core features determining innovative behaviour in to a single composite. This index enables to assess the total propensity of firms to innovate and assess the relative innovation performance at the sector and country level. The approach adopted here to create the index overcomes long standing theoretical and methodological issues related to the reduction of complexity in a meaningful form, scope, aggregation, normalisation and validation of innovation composites. The empirical demonstration of the index was done using CIS4 data and the results validate the theoretical structure and robustness of the proposed model. This enables its replication for innovation policy analysis in different settings. The model underlying the proposed index provides not only a depiction of the efficiency of the innovation system but also a link to economic performance and to the factors that determine relative performance.
|Item Type:||MPRA Paper|
|Original Title:||State of an innovation system: theoretical and empirical advance towards an innovation efficiency index|
|Keywords:||Innovation indicators; Innovation performance; innovation efficiency; innovation intensity; theory of planned behaviour; CIS; single indicator; composite indicators; sectoral innovation indicators; behavioral economics; psychological economics;|
|Subjects:||D - Microeconomics > D0 - General > D03 - Behavioral Microeconomics: Underlying Principles
D - Microeconomics > D7 - Analysis of Collective Decision-Making
C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C43 - Index Numbers and Aggregation
O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights
|Depositing User:||Carlos Montalvo|
|Date Deposited:||11 Apr 2012 02:36|
|Last Modified:||02 Oct 2016 13:55|
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior, in J. Kuhl and J. Beckmann (eds). Action-control: From cognition to behavior, Heilderberg: Springer, pp. 11-39.
Ajzen, I. (2005), Laws of human behavior: Symmetry, compatibility, and attitude- behavior correspondence. In A. Beauducel, B. Biehl, M. Bosniak, W. Conrad, G. Schönberger, & D. Wagener (Eds.), Multivariate research strategies (pp. 3-19). Aachen, Germany: Shaker Verlag.
Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Process, 50, 179–211.
Ajzen, I. (2012). The theory of planned behavior. In P. A. M. Lange, A. W. Kruglanski & E. T. Higgins (Eds.), Handbook of theories of social psychology (Vol. 1, pp. 438-459). London, UK: Sage.
Armitage, C.J. and M. Conner (2001), Efficacy of the theory of planned behaviour: A meta-analytic review, British Journal of Social Psychology 40, 471–499.
Beckenbach F. and M. Daskalakis (2008), Behavioural foundations of innovation surveys International Journal of Foresight and Innovation Policy, Vol. 4, Nos. 3/4, 181-199.
Blind, K. (2007), Innovation and regulation, Editorial Special Issue, International Joural of Public Policy, Vol. 2, Nos. 1/2.
Bloch, C. (2007), Assessing recent developments in innovation measurement: the third edition of the Oslo Manual, Science and Public Policy, 34, 1, 23–34.
Cainelli, G., R. Evangelista and M. Savona (2006), Innovation and economic performance in services: a firm-level analysis, Cambridge Journal of Economics, 30, 3, 435-458.
Carlsson, B., S. Jacobsson, M. Holmén and A. Rickne (2002), Innovation systems: analytical and methodological issues, Research Policy, 31, 233–245.
Cherchye, L., Moesen, W., Rogge, N., van Puyenbroeck, T., Saisana, M., Saltelli, A., Liska, R., Tarantola, S., (2008). Creating composite indicators with DEA and robustness analysis: the case of the Technology Achievement Index. Journal of the Operational Research Society 59, 239–251.
Cherchye, L., Moesen, W., van Puyenbroeck, T., (2004). Legitimately diverse, yet comparable: on synthesizing social inclusion performance in the EU. Journal of Common Market Studies 42, 919–955.
Cozzens, S. (1991). Science indicators: description or prescription? Washington: Office of Technology Assessment.
Cronbach, T. (1994), Essential of Psychological Testing, London: Hamper and Row.
De Haan, J. (2010), Towards transition thoery, Doctoral Thesis, Rotterdam: Erasmus Univarsity Rotterdam.
Dutta, S. (Ed.)(2011), The Global Innovation Index 2011: Accelerating Growth and Development, Fontainebleau: INSEAD.
European Commission (Ed.), 2003. Third European Report on Science & Technology Indicators 2003. EUR 20025 EN, Brussels.
European Commossion (2010), Europe 2020 Flagship Initiative: Innovation Union, Communication from the Commission to the European Parliament, The Council, the European Economic and Social Committee and the Committee of the Regions, COM(2010) Brussels, 6.10.2010, 546 final, SEC(2010) 1161.
Eurostat (2004) The Fourth Community Innovation Survey (CIS 4): Methodological recommendations, Luxemburg: EUROSTAT.
Freeman, C. (1988), Japan: a new national system of innovation. In: Dosi, et al. (Eds.), Technical Change and Economic Theory, London: Francis Pinter, pp. 330–348.
Freeman, C. and L. Soete ( 1997). The Economics of industrial inovation. Pinter, London. GAO, (1979). Science Indicators: Improvements needed in design, construction, and interpretation. Washington.
Godin , B. (2003), The emergence of S&T indicators: why did governments supplement statistics with indicators? Research Policy, 32, 679–691.
Gollwitzer, P.M., and Bargh, J.A. (eds) (1996). The psychology of action: Linking cognition and motivation to behavior. New York: The Guilford Press.
Guan J. and K Chen (2011) Modeling the relative efficiency of national innovation systems, Research Policy (in press available on line).
Guttman, R. in Gratch, H., (Ed.). (1973). Twenty years of social research in Israel. Jerusalem: Jerusalem Academic Press.
Hagedoorn, J. and M. Cloodt (2003), Measuring innovative performance: is there an advantage in using multiple indicators? Research Policy, 32, 1365–1379.
Hollanders H. and A. van Cruysen (2008). Rethinking the European Innovation Scoreboard: A New Methodology for 2008-2010, Report to Pro-INNO, European Commission DG Enterprise and Industry.
Katz, J. S. (2006), Indicators for complex innovation systems, Research Policy 35 893–909. Kleinknecht, A., Van Monfort, K and E. Brouwer (2002), The non-trivial coice between innovation indicators, Economics of Innovation and New Technologies, 11, 2, 109-121.
Kleinwoolthuis, R., M. Lankhuizen and V. Gilsing (2005), A system failure framework for innovation policy, Technovation, 25, 609-19.
Korzybsky, A. (1994), Science and Sanity: An Introduction to Non-Aristotelian Systems and General Semantics, 5th edn, Englewood, N.J: Institute of General Semantics.
Lundvall, B.-Å. (Ed.), (1992), National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning, London, Pinter Publishers.
Mairesse, M. and P. Hohnen (2008), Innovation surveys and innovation policy, paper presented at the conference “En route vers Lisbonne” Luxembourg: 4-5 December 2008.
Michell, J. (1997), ‘Quantitative science and the definition of measurement in psychology’, British Journal of Psychology, 88, 355–83.
Mintzberg, H. (1994), The rise and fall of strategic planning. New York: The Free Press. Malerba, F. (2002) Sectoral systems of innovation and production, Research Policy; 31(2). Montalvo C. (2002), Environmental policy and technological innovation: Why do firms adopt or reject new technologies? Cheltenham, UK and Northampton, MA.: Edward Elgar, pp. 300.
Montalvo, C. (2006), What triggers change and innovation, Technovation, 26(3): 312-323. Montalvo, C. (2007), Explaining and predicting the impact of regulation on innovation: towards a dynamic model, International Joural of Public Policy, Vol. 2, Nos. 1/2, 5-31.
Montalvo, C. (2011), Analysis of market and regulatory factors influencing sectoral innovation patterns. Interim report to the Sector Innovation Watch. Europe INNOVA initiative, Brussels: European Commission Directorate General Enterprise and Industry.
Montalvo, C., P. ten Brink, C. Sartorious, M. Sotoudeh, D. Stromberg, C. Bowyer, M. Fergusson, J. Anderson, F. Sprei, A. Alhback, J. Nassén, R. Nemeskeri, P. Bodo, S. Schilder, F. Heil, G. Angerer, O. Wolf, L. Delgado, M. van Dijk, and F. Lippman (2007). Policy pathways to promote eco-innovations – Scientific summary report. European Sixth Framework Program, Contract no. 502487, Project “Policy pathways to promote the development and adoption of cleaner technologies (POPA-CTDA)”, Delft: TNO - The Netherlands Organisation for Applied Scientific Research.
Morgenthaler, S. (2001), Robustness in Statistics, International Encyclopedia of the Social & Behavioral Sciences, 13379-13385.
Nardo, M., M. Saisana, A. Saltelli and S. Tarantola (2005), Tools for Composite Indicators Building, Ispra: DG Joint Research Centre Institute for the Protection and Security of the Citizen, Econometrics and Statistical Support to Antifraud Unit.
Nasierowski, W. and F.J. Arcelus ( 2003), On the efficiency of national innovation systems, Socio-Economic Planning Sciences 37, 215–234.
Nelson, R.R. (Ed.), (1993), National Systems of Innovation. A Comparative Analysis, Oxford: .Oxford University Press.
OECD (2011), OECD science, technology and industry scoreboard 2011, Paris: OECD Publising.
OECD/Eurostat (2005), Guidelines for Collecting and Interpreting Innovation Data — The Oslo Manual, 3rd edn. Paris: OECD.
Sartorious, C. (2008), Promotion of stationary fuel cells on the basis of subjectively perceived barriers and drivers, Special Issue on Diffusion of cleaner technologies: Modeling, case studies and policy Journal of Cleaner Production, 16, 1, Supplement 1, S171-S180.
Schubert T., P. Neuhäusler, R. Frietsch, C. Rammer and H. Hollanders (2011), Innovation indicator - Methodology Report, Bonn: Deutsche Telekom Stiftung.
Suurs, R.A.A. (2009), Motors of sustainable innovation: Towards a theory of technological innovation systems, Doctoral Thesis. Utrecht, Utrecht University.
Weissenberger-Eibl, M.A., R. Frietsch, H. Hollanders, P. Neuhäusler, C. Rammer, T. Schubert (2011), BDI – Innovation indicator report 2011, Boon: Deutsche Telekom Stiftung.