This article analyzes the available readiness indexes and maturity models applied for trends designated as “4.0”, with a focus on Industry 4.0, primarily within the countries of Europe. Based upon it, the available indexes and maturity models are organized into the individual layers of the metamodel; a proposal for this metamodel is this article’s main output. Simultaneously, as-yet-uncovered places for the development of existing maturity models, as well as space for further detailed research into the application of Industry 4.0 in theory and in practice, are identified on the basis of this metamodel.

The paper examines economic growth in old and new member countries of the European Union (EU-15 and EU-12) during the years of 1994-2000 and 2001-2008 mainly due to changes in information and communication technology (ICT) capital development. The first group EU-15 is presented by old EU countries and the second group EU-12 is presented by new member countries that joined the EU in 2004-2007. The threefactor Cobb-Douglas production function is estimated through the panel general least squares method. The input factors that might influence the economic growth are labour, ICT capital services and non-ICT capital services. Since ICT capital growth data are not available for all selected economies, the groups of countries were reduced to EU-14 and EU-7. The estimated panel production functions confirmed that the average growth of GDP in the EU-7 countries was supported by the stable growth of labour quantity and ICT-capital and increasing total factor productivity. A short-term drop in non-ICT capital growth with follow-up stagnation was caused rather by lower labour productivity. The research discovered that the drop in GDP growth in the EU-14 countries was a result of the slower growth of non-ICT capital and total factor productivity and the stagnated growth of ICT capital with low elasticity, and showed that even the compensation of growth in labour quality did not prevent a decrease in total factor productivity and economic growth.

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Part 11: Social Impact of EIS and VisualizationInternational audienceThe paper describes corporate social responsibility (CSR) communication on Facebook and Twitter – how the companies use the social media for accomplishing their CSR communication goals. On the sample of ten global companies with the best CSR reputation research tracks down their social media activity, as well as posts, likes and comments of their customers. Observed companies on average dedicate about 1/10 of their social media communication bandwidth to CSR topics, mainly on Facebook. CSR topics do not seem to be of much interest to the readers (CSR posts are mostly ignored), but at least user sentiment related to CSR messages has been proven to be mostly positive. CSR on social networks is well established, leading CSR companies use this communication channel extensively

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