Statistical Composite Indicator for Estimating the Degree of Information Society Development

The development of information and communication technologies and the rapid development of the IT sector have greatly contributed to the development of society in general. In recent years, the techniques for measuring the development of information and communication technologies have begun to rise. Subject of this study is to measure the development of the countries’ ICT infrastructure, using statistical composite index. In order to measure the development, we will use composite IDI index, with special emphasis on the improvement of the index. In addition to the existing IDI method of ranking, we will use the I-distance. A comparative analysis of the created and the existing indexes shall be given.

[1]  Veljko Jeremic,et al.  How does the normalization of data affect the ARWU ranking? , 2012, Scientometrics.

[2]  Stefan Finsterle,et al.  Modeling the performance of large-scale CO2 storage systems: A comparison of different sensitivity analysis methods , 2012 .

[3]  Maria Chiara Leva,et al.  A compound methodology to assess the impact of human and organizational factors impact on the risk level of hazardous industrial plants , 2013, Reliab. Eng. Syst. Saf..

[4]  Veljko Jeremic,et al.  A fresh approach to evaluating the academic ranking of world universities , 2011, Scientometrics.

[5]  Marković Aleksandar,et al.  ICT as crucial component of socio-economic development , 2011 .

[6]  Michaela Saisana,et al.  Higher education rankings : robustness issues and critical assessment : how much confidence can we have in higher education rankings? , 2011 .

[7]  Heejin Lee,et al.  ICT Development in North Korea: Changes and Challenges , 2004 .

[8]  L. Ación,et al.  How Reliable Are County and Regional Health Rankings? , 2013, Prevention Science.

[9]  Zoran Radojičić,et al.  ExcEllEncE with lEadErship: the crown indicator of scimago institutions rankings ibEr rEport , 2013 .

[10]  Uncertainty in Ranking the Hottest Years of U.S. Surface Temperatures , 2013 .

[11]  Stefano Tarantola,et al.  Introduction to Sensitivity Analysis , 2008 .

[12]  Sophia P. Dimelis,et al.  ICT growth effects at the industry level: A comparison between the US and the EU , 2011, Inf. Econ. Policy.

[13]  Ganapati P. Patil,et al.  Ranking and Prioritization for Multi-indicator Systems , 2011 .

[14]  Stephen Parker The digital divide is still with us , 2011 .

[15]  Franci Pivec,et al.  Measuring the information society , 2003 .

[16]  A. Saltelli,et al.  Composite Indicators between Analysis and Advocacy , 2007 .

[17]  Andrea Saltelli,et al.  Ratings and rankings: voodoo or science? , 2011, 1104.3009.

[18]  A. Saltelli,et al.  Rickety numbers: Volatility of university rankings and policy implications , 2011 .

[19]  Veljko Jeremic,et al.  Quantity or quality : what matters more in ranking higher education institutions ? , 2012 .

[20]  G. Savić,et al.  An Evaluation of European Countries' Health Systems through Distance Based Analysis. , 2012, Hippokratia.

[21]  María Rosalía Vicente Cuervo,et al.  Assessing the regional digital divide across the European Union-27 , 2009 .

[22]  Aleksandar Markovic,et al.  A new perspective on the ICT Development Index , 2012 .

[23]  Tim Menzies,et al.  Finding conclusion stability for selecting the best effort predictor in software effort estimation , 2012, Automated Software Engineering.

[24]  Louis Leung,et al.  Effects of Internet Connectedness and Information Literacy on Quality of Life , 2010 .

[25]  Terje Haukaas,et al.  Sensitivity measures for optimal mitigation of risk and reduction of model uncertainty , 2013, Reliab. Eng. Syst. Saf..

[26]  S. Tarantola,et al.  State-of-the-art Report on Current Methodologies and Practices for Composite Indicator Development , 2002 .