Page 258 - Invited Paper Session (IPS) - Volume 2

IPS236 Ksenija D. et al.
constructed using a number of indicators impacting the e-commerce for
individuals. Dumičić, Skoko Bonić & Žmuk (2018) conducted statistical analysis
of nine development indicators’ impacting the Internet purchases by
individuals, defined as a share of individuals who made a purchase by using
the Internet in the last 12 months in the total population of a country for 2013.
Further, variety of development indicators influences special forms of internet
purchases were analysed, too. So, online banking analysis, given in Dumičić,
Čeh Časni & Palić (2015), includes variety of multivariate analysis, while
development indicators impacts on online booking for travel and
accommodation is presented in Žmuk, Dumičić & Mihajlović (2014), and
Dumičić, Žmuk & Čeh Časni (2015), showing separate clusters of European
countries. Žmuk & Mihajlović (2018), paid attention to position of the Western
Balkan countries within Europe regarding online booking influenced by
economic and digital development level indicators. Nagy (2016) explored e-
commerce on Hungarian market, and Nagy (2017) compared Hungarian and
Ukrainian digital economy and society. A number of visualised digital economy
impacts of various aspects of customer behaviour is given in Consumer
Barometer, as given at CB (2017).
In this paper, a trend analysis for Y2017IntOrderGoods, over the period 2007 to
2018, follows. The added indicators have been as follows: X1_GDPpcPPS, Level of
internet access for households, given as Percentage of households who have
internet access at home, for the population aged 16 to 74, and (X3_DigitalSkill).
The research hypotheses state, firstly, that a positive correlation exists between
Y2017IntOrderGoods and each of three included explanatory indicators, so that clear
clusters of countries could be created; and there are increased motivation and
opportunities for statistical societies to act in digitalised and globalised World
by improved communication when promoting statistical and digital related
improvements in education, knowledge, literacy and skills. Performed
statistical data description, performed correlation, regression and cluster
analysis, helped testing these hypothesis.

2. Methodology
After investigation on the recent official data availability, Eurostat (2019),
the following indicators have been analysed:

 Y2017IntOrderGoods - Percentage of individuals aged 16-74, who use the
internet for ordering goods or services, being Digital Society related
indicator and the main variable of the interest in this study;
 X1_GDPpcPPS - GDP per capita in PPS, Index, EU-28 = 100;
 X2_AccHome - Percentage of households who have internet access at
home, for the population aged 16 to 74, also called Level of internet
access for households; and

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