Prof. Božidar Tepeš Faculty of Teacher Education, University of Zagreb Mr. Ivan Mijić Diplomatic Academy, Ministry of Foreign Affairs and European Integration, Croatia Krunoslav Tepeš City Office for Transport Planning, City of Zagreb 1 TWO STATISTICAL MODELS ON EUROPEAN AND CROATIAN INFORMATION SOCIETY Prof. Božidar Tepeš Faculty of Teacher Education, University of Zagreb Mr. Ivan Mijić Diplomatic Academy, Ministry of Foreign Affairs and European Integration, Croatia Krunoslav Tepeš City Office for Transport Planning, City of Zagreb

Two statistical models on European and Croatian information society Information society Benchmark indicators Factor analysis Causal model Some new results Conclusion 2

Information society From statistical point of view, Information society (IS) is connected with Information and communication technology (ICT). Organisation for economic and co-operation and development (OECD) presented conceptual model of IS with elements: ICT supply (producers and production ICT goods and services) ICT demand (users and uses, households, individuals and businesses) ICT infrastructure (investments and services) ICT products and content (price, quality and flows of information) ICT demand and ICT infrastructure as part of IS are electronic commerce (e-commerce) 3

Benchmark indicators EU Commission (2002) presented the eEurope 2005 Action Plan. This provides policy actions for European institutions and member states to accelerate the development of the IS in Europe. Commission proposes fourteen policy indicators and twenty two supplementary indicators. For candidate countries indicators are benchmarks indicators. Eight basic benchmarks were used in this article: Percentage of households or individuals having access to the Internet at home (A1) Percentage of individuals regularly using the Internet (A2) Percentage of persons employed using computers connected to the Internet (B1) Number of basic public services fully available6 on-line (D1) Percentage of population using Internet to seek health (F1) Percentage of enterprises total turnover from e-commerce (G1) Percentage of enterprises with broadband access (J1) Percentage of households or individuals with broadband access (J2) Eurostat has benchmarks data for EU countries. Central bureau of statistics of Croatia and IDC Adriatics have benchmarks data for Croatia. 4

Factor analysis From Eurostat statistics, we are using eight measured variables (benchmarks indicators) for twenty seven EU countries for six years. Using statistical software Statistica first factor or principle component describe 75%¸of total variance of all measured variables. We named this first factor Intensity of IS (Y). The relation between first factor and measured variables is: 5

Intensity of IS 6

Causal structure We are looking for partial correlation coefficients between two measured variables and all others. Six partial coefficients in Table 1. are absolutely greater than 0.3 Causal structure are in Picture 1. A1A1A1A1A2B1D1F1G1J1J2 A A B1 D10.40 F1 G1 J10.47 J2 7 B1A2A1J1J2 D1F1

Causal model For causal model we are looking for causal V-structure A  C  B when partial correlation coefficients are |  AB.C |>0.3. V-structure, representing two causes A and B have a common effect C, act the opposite way. 8 B1A2A1J1J2 D1F1

Some new results 9

Conclusion Our research of IS form statistical point of view is statistical modeling of IS. Model show causal structure of IS and the most important goals for development of IS. We can see position of Croatia in development of IS or knowledge society. Our model have only eight measured variables, and more realistic model of IS must have more variables. At the same time, period of research was only four year for Croatia. Development of IS is connected with globalization and model of IS must include more countries than EU countries. 10

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