Page 257 - Invited Paper Session (IPS) - Volume 2

IPS236 Ksenija D. et al.
countries with Germany and United Kingdom, all clustered within the separate
cluster, as the absolute European leaders regarding the Digital Society
indicator and Percentage of persons who order goods and services online,
while the South-East European (SEE) countries, being similar, were clustered,
as those at the end of the queue. Here recognized differently developed
clusters of countries, with different percentages of individuals for YIntOrderGoods,
and X3_DigitalSkill, variables taken as examples for digitalisation and globalisation,
have also different communication habits of their NSAs. Activities of the NSAs
should be studied with the goal to standardize their communication, to be
better fitted into the global digitalised World, by communicating over the
common platform, fulfilling their activities’ goals.

Keywords
Globalisation; Digital Skills; Hierarchical clustering; Statistical societies;
FENStatS

1. Introduction
Purpose of this study is to recognize statistical societies’ role and acting
opportunities in the era of digitalisation and globalisation, based on digital
related variables research findings. Since the overall present digitalization
initiates changes in lives of people in all the societies and creates a growth of
economies in countries all over the World, it is considered as the natural
component of our reality. In this research, selected indicators, which influence
the main variable under study, Percentage of individuals who use the internet
for ordering goods or services (Y2017IntOrderGoods), which increased for EU-28 from
30% in 2007 to 60% in 2018, were analysed. Among several considered, one
Digital Society related indicator, called Percentage of individuals who have
basic or above basic overall digital skills (X3_DigitalSkill), showed to be positively
correlated, with the strongest positive influence on the main variable under
study. Three indicators, with fully available data, are included for correlation
and regression analysis: GDP per capita in PPS, Index, EU-28=100; Percentage
of households who have internet access at home, for the population aged 16
to 74; and Percentage of individuals aged 16-74, who have basic or above
basic overall digital skills. Since the descriptive exploration found that the
Luxembourg’s Gross Domestic Product (GDP) per capita in PPS, X1_GDPpcPPS, has
been an extremely high outlier, the further analyses with 31 countries for 2017
were performed: the 27 countries of EU-28, Montenegro, FYR of Macedonia,
Serbia and Turkey. The authors studied mutual interaction of the variables with
correlation, regression and cluster analysis in 2017. Dumičić, Žmuk &
Novkovska (2017) performed regression analysis of e-commerce, focusing the
selected EU candidates and the EU countries. Further, Dumičić, Žmuk &
Mihajlović (2017) executed profile analysis of clustered European countries

244 | I S I W S C 2 0 1 9