Using linked data to evaluate the impact of research and development in Europe: A structural equation model

3Citations
Citations of this article
27Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Europe has a high impact on the global biomedical literature, having contributed with a growing number of research articles and a significant citation impact. However, the impact of research and development generated by European countries on economic, educational and healthcare performance is poorly understood. The recent Linking Open Data (LOD) project has made a lot of data sources publicly available and in human-readable formats. In this paper, we demonstrate the utility of LOD in assessing the impact of Research and Development (R&D) on the economic, education and healthcare performance in Europe. We extract relevant variables from two LOD datasets, namely World Bank and Eurostat. We analyze the data for 20 out of the 27 European countries over a span of 10 years (1999 to 2009). We use a Structural Equation Modeling (SEM) approach to quantify the impact of R&D on the different measures. We perform different exploratory and confirmatory factorial analysis evaluations which gives rise to four latent variables that are included in the model: (i) Research and Development (R&D), (ii) Economic Performance (EcoP), (iii) Educational Performance (EduP), (iv) Healthcare performance (HcareP) of the European countries. Our results indicate the importance of R&D to the overall development of the European educational and healthcare performance (directly) and economic performance (indirectly). The results also shows the practical applicability of LOD to estimate this impact. © 2013 Springer-Verlag.

Cite

CITATION STYLE

APA

Zaveri, A., Nickenig Vissoci, J. R., Daraio, C., & Pietrobon, R. (2013). Using linked data to evaluate the impact of research and development in Europe: A structural equation model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8219 LNCS, pp. 244–259). https://doi.org/10.1007/978-3-642-41338-4_16

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free