Measuring Eco-Innovation: Towards Better Policies to Support Green Growth

• Autorzy: Dominik Rozkrut
• Języki publikacji: EN

Abstrakty

EN

Green growth strategies thus need to be robust, what requires carefully designed tools. One of the prerequisites is the appropriate green growth measurement framework. It should allow discerning the effectiveness of policies in delivering green growth. This is where this paper tries to offer a new angle by searching for appropriate indicators that can capture different aspects of eco-innovation. Eco-innovation can be defined as innovation that results in a reduction of environmental impact. Country data from the 2008 Community Innovation Survey is used in the analysis. Dataset consist of 14 variables on environmental benefits and motivations. The aim of the presented study is to reduce the number of variables into factors to discover which of available variables form coherent subsets. It is argued here that such approach can help to construct appropriate indicators, that can capture different aspects of eco-innovation, that are crucial from the point of view of policy-making and policy evaluation.(original abstract)

Słowa kluczowe

EN

Eco-innovation; Economic growth; Environmental protection; Measurement; Eco-development strategy

PL

Ekoinnowacje; Wzrost gospodarczy; Ochrona środowiska; Pomiary; Strategia ekorozwoju

• Czasopismo: Folia Oeconomica Stetinensia
• Rocznik: 2014
• Tom: 14
• Numer: nr 1
• Strony: 137--148

Twórcy

autor

Dominik Rozkrut

• University of Szczecin, Poland

Bibliografia

• Batóg, B. & Wawrzyniak, K. (2010). Models With Varying Parameters as a Tool to Classify Polish Voivodships in 2002-2008. Folia Oeconomica Stetinensia, 9 (1), 139-150.
• Caliński, T. & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3 (1), 1-27.
• Duda, R.O., Hart, P.E. & Stork, D.B. (2001). Pattern Classification and Scene Analysis (2nd ed.). New York: Wiley.
• Eco-innovation indicators (2006). Copenhagen: European Environment Agency.
• Eurostat (2012). Data retrieved May 1, 2012, http://epp.eurostat.ec.europa.eu.
• Frenz, M. & Lambert, R. (2008). Innovation modes and productivity in the UK. Report to the Science, Innovation and Analysis Unit. DIUS Research Report, 8 (12), Department for Innovation, Universities and Skills.
• Gabriel, K.R. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58 (3), 453-467. [CrossRef]
• Gabriel, K.R. (2002). Goodness of fit of biplots and correspondence analysis. Biometrika 89, 423-436.
• Gatnar, E. (2002). Tree-based models in statistics. In: Eds. K. Jajuga, A. Sokołowski, H.H. Bock. Classification, Clustering and Data Analysis (pp. 399-408). Berlin: Springer.
• Jajuga, K., Walesiak, M. & Bąk, A. (2003). On the general distance measure. In: Eds. M. Schwaiger, O. Opitz. Exploratory data analysis in empirical research (pp. 104-109). Berlin-Heidelberg: Springer-Verlag.
• Walesiak, M. & Dudek, A. (2007). ClusterSim: Searching for optimal clustering procedure for a data set, www.R-project.org. R package version 0.30-7.
• Milligan, G. & Cooper, M. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50 (2), 159-179. [CrossRef]
• OECD, Eurostat - Statistical Office of the European Communities (2005). Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd Edition, The Measurement of Scientific and Technological Activities. Paris/Luxembourg: OECD Publishing.
• OECD (2008). OECD Framework for Effective and Efficient Environmental Policies. Retrieved May 1, 2012, www.oecd.org/dataoecd/39/19/41644480.pdf.
• OECD (2011a). Better Policies to Support Eco-innovation, OECD Studies on Environmental Innovation. Paris: OECD Publishing.
• OECD (2011b). Towards Green Growth. OECD Green Growth Studies. Paris: OECD Publishing.
• Rozkrut, M. (2006). Application of Correspondence Analysis and Other Methods to Research on Economic Development in Poland. Folia Oeconomica Stetinensia, 5, 143-153.

Identyfikatory

DOI

10.2478/foli-2014-0110