EU Policy for Digital Society [605902]

EU Policy for Digital Society
Thierry Burger-Helmchen and Georgeta-Madalina Meghisan-Toma
Abstract This chapter focuses on the main steps towards a digital society at the
level of the European Union ’s countries. The first subchapter entitled “EU Digital
Single Market Regulatory Frame” provides information about the Digital Single
Market Strategy for Europe. The subchapter entitled “ICT Sector Influence on
EU-28 Economic Growth” underlines the main influences of ICT sector (ICT
demand and ICT supply, national corruption and lifelong learning as moderating
variables) on GDP. The subchapter “EU-28 Digital Divide” focuses on the main
elements that create digital gap between the countries of the European Union.
Reading the full chapter, the students will understand the progress of EU-28
countries towards a digital society and economy, together with the effort of the
European Commission to create proper regulatory frame. This study is a necessary
tool for the students, focusing on the main elements that need to evolve in order to
reach a single digital market.
Key points:
1. To analyse the steps towards a digital society within EU-28 countries;
2. To understand the EU Digital Single Market regulatory frame;
3. To assess the relationship between economic growth and ICT sector;
4. To draw attention on the digital gap between the states of the EU-28;
5. To raise awareness towards further developments of the digital society.
T. Burger-Helmchen ( *)
Faculty of Economics and Management, BETA-CNRS, University of Strasbourg, Strasbourg,
France
e-mail: [anonimizat]
G.-M. Meghisan-Toma
Faculty of Economics and Business Administration, University of Craiova, Craiova, Romania
Romanian Academy, National Institute for Economic Research “Costin C. Kiritescu”,
Bucharest, Romania
e-mail: [anonimizat]
©Springer International Publishing AG, part of Springer Nature 2018
A. M. Dima (ed.), Doing Business in Europe , Contributions to Management
Science, https://doi.org/10.1007/978-3-319-72239-9_9195

1 Introduction
The Internet developed fast during the recent years, bringing many implications
within the society. In the knowledge-based society, Internet is the most dynamicmedia means (Salman and Abd.Aziz 2015 ). Information and communication tech-
nologies (ICTs) are “at the core of this fast-changing economy” (Van Laar et al.2017 ). Moreover, any area of professional or private life “has been overlooked by
the web-based technologies” (Wang and Tucker 2016 ).
Level of Internet access led to a whole new rage of services. On the other hand,
digital divide inequalities are closely linked to ICT access, together with the
purpose the individuals use the ICT access. A series of analysis emphasizing the
digital divide have been drawn (Vicente and Lopez 2010 ; Cruz-Jesus et al. 2016 ;
Vicente and Novo 2014 ;C¸ ilan et al. 2008 ;V a´rallyai et al. 2015 ).
Many authors studied the connection between ICT development and economic
growth. Cisco ( 2003 ) uses the longitudinal approach of time series analysis to explain
the positive effect of the investment in ICT on the UK economic growth(1992–2000). Two years later, Chu ( 2005 ) reveals the correlation between the profit
of the IT companies from New Zeeland and the economic growth of the country
(1987–2001).
Another method of analysis is the cross-sectional approach on multiple coun-
tries. Northrop ( 2002 ) underlines the connection between IT infrastructure, social
infrastructure and economic factors. OECD analysis (2008) on 19 countries empha-sizes the GDP growth ’s impact on broadband technology penetration.
Other authors combined both methods in their analysis on the connection between
ICT investment and GDP growth. Jin and Cho ( 2015 ) made use of panel data on a
13th years length of time (1999–2012) on ICT and GDP indicators from
128 countries.
2 EU Digital Single Market Regulatory Frame
The European Cohesion Policy is designed to reduce “gaps between development
levels in the various regions” (Miron et al. 2009 ). In the Digital Single Market Strategy
for Europe (2015) adopted by the European Commission, the digital single market isdefined as “ one in which the free movement of goods, persons, services and capital is
ensured and where individuals and businesses can seamlessly access and exerciseonline activities under conditions of fair co mpetition, and high level of consumer and
personal data protection, irrespective of their natio nality or place of residence ”.
(European Commission, A Digital Single Market Strategy for Europe, 2015)
In order to facilitate the adoption of the digital single market, the Digital Single
Market Strategy for Europe (2015) focuses on (European Commission, A DigitalSingle Market Strategy for Europe, 2015):
•Better online access for consumers and businesses across Europe:196 T. Burger-Helmchen and G.-M. Meghisan-Toma

– Online sales harmonised legislation by Legislative proposals for simple and
effective cross-border contract rules for consumers and businesses” (2015)and Review of the Regulation on consumer protection cooperation (2016);
– Improvement of price transparency in cross-Europe delivery services, by
Measures in the area of parcel delivery (2016);
– Limitation of markets geo-blocking, by Legislative proposals to tackle
unjustified Geo-blocking (2015), Competition sector inquiry intoe-commerce, relating to the online trade of goods and the online provisionof services (2015);
– Updating the copyright framework, by Legislative proposals to reform the
copyright regime (2015), Review of the Satellite and Cable Directive (2015/
2016);
– VAT general reform, by Legislative proposals to reduce the administrative
burden on businesses arising from different VAT regimes (2016);
•Creating the right conditions and a field for advanced digital networks and
innovative services:
– Development of Telecoms Single Market package, by “Legislative proposals
to reform the current telecoms rules” (2016);
– Review of the Audio-visual Media Services Directive (2016);
– Creating fitted legislation for online platforms, that limits illegal content on
the Internet, by Comprehensive analysis of the role of platforms in themarket, including illegal content on the Internet (2015);
– Adoption of the Network and Information Security Directive, by Review of
the E-Privacy Directive (2015) and Establishment of a Cyber security con-tractual public-private partnership (2016);
• Maximising the growth potential of the digital economy, by:
– Launch of the European Cloud initiative, by Initiatives on data ownership,
free flow of data and on a European Cloud (2016);
– ICT standardisation, by Adoption of a priority ICT Standards Plan and
extending the European Interoperability Framework for public services (2015);
– Development of digitally skilled employees and e-government, by New
e-Government Action Plan including an initiative on the “once-only” princi-ple and an initiative on building up the interconnection of business registers
(2016).
The importance of the Digital Single Market Strategy comes from the great
potential to the growth of the European Digital Economy, due to the fact that 90%of the jobs will require a certain level of digital skills, in the nearest future
(European Commission 2017).
The main purpose of the European Union member states is to become digital
economies and societies. Digital Economy and Society Index (DESI) ranks eachEU country, depending on five elements: Connectivity (25%), Human Capital(25%), Use of Internet (15%), Integration of Digital Technology (20%), DigitalPublic Services (15%).EU Policy for Digital Society 197

Digital Economy and Society Index of the European Union 28, by aggregate
scores was 0.519 (2016), 0.498 (2015) and 0.456 (2014). European Union registers
a slow progress of the DESI 2016. The main dimensions of Digital Economy and
Society Index of EU-28, for the year 2016, are resumed in Graphic 1.
Connectivity refers to Internet connection. The EU-28 Connectivity aggregate
score is 0.591 for the year 2016. The sub-dimensions of Connectivity have the
following weighted scores for EU-28 countries (2016):
• Fixed broadband (21.8% of 33%): Fixed broadband coverage; Fixed broadband
take-up.
• Mobile broadband (11% of 22%): Mobile broadband take-up; Spectrum;
• Speed (18.6% of 33%): Next Generation Access (NGA) Coverage; Subscrip-
tions to fast broadband.
• Affordability (7.62% of 11%): Fixed broadband price.
The three main objectives of the European Union for the year 2025, focusing on
the importance of Internet connectivity for the Digital Society, are ( http://europa.
eu, accessed 22.01.2017): Gigabit connectivity for places driving socio-economic
developments; 5G coverage for all urban areas and all major terrestrial transportpaths; access for all European households to internet connectivity offering at least100 Mbps.
Human capital represents on one hand, the skills of consumers in order to use
the service and, on the other hand, the skills of workforce to provide digital goodsand services. The European Union-28 Human Capital aggregate score is 0.591 for
the year 2016. The main sub-dimensions of EU-28 Human capital have the follow-ing weighted scores for EU-28 (2016):
• Basic skills and usage (29.2% of 50%): Internet users; Basic digital skills.
Graphic 1 EU 28 performance in DESI 2016 (Source: authors ’compilation after European
Commission Digital Economy and Society Index Report, 2016)198 T. Burger-Helmchen and G.-M. Meghisan-Toma

• Advanced skills and development (29.9% of 50%): Information-communication
technology (ICT) specialists; Science, Technology, Engineering and Mathemat-ics (STEM) Graduates.
The European Commission proposes several actions for new Skills Agenda for
Europe (European Commission Press Release, 2016): strengthening the foundationof basic skills; key competences and higher, more complex skills; making voca-tional education and training (VET) a first choice; focus on digital skills; early
profiling of migrants ’skills and qualifications; better information for better choices;
more work-based learning and business-education partnerships.
Use of Internet represents the main ways to make use of the Internet service:
consumption of online content, communication and transactions. The European
Union-28 Use of Internet aggregate score is 0.453 for the year 2016. This score iscalculated by taking into consideration the weighted scores for EU 28 countries(2016) for the following sub-dimensions:
• Content (14.6% of 33%): News; Music, videos and games; Video on demand.
• Communication (10.1% of 33%): Video calls; Social networks.• Transactions (20.6 of 33%): Banking; Shopping.
Beginning with June, 15th 2017, as foreseen in the Telecom Single Market
Regulation, the consumers, travelling to European Union ’s countries, will pay the
same amount as they pay at home, for their calls, SMS and Internet data (EuropeanCommission 2016).
Integration of digital technology underlines the efficiency of business digita-
lization and e-commerce option. The European Union-28 Integration of digital
technology aggregate score is 0.362 for the year 2016. This score is calculated asthe weighted average of two sub-dimensions at the level of EU-28 countries (2016):
• Business digitization (21.6% of 60%): Electronic information sharing; Radio-
frequency identification (RFID); Social Media; E-invoices; Cloud.
• E-commerce (14.6% of 40%): Small and medium-sized (SME) enterprises
selling online; E-commerce turnover; Selling online cross-border.
According to the European Commission, there are 33 sectors within the
European Union economy that “are considered copyright-intensive, accountingdirectly for over 7 million jobs, or 3% of employment in the EU” (EuropeanCommission Press 2017).
The main objectives of EU copyright proposals are: more cross-border access to
content online; wider opportunities to use copyrighted materials in education,research and cultural heritage; better functioning of copyright marketplace
(European Commission 2017).
Digital public services refer to the interaction of the businesses and citizens
with the Public Administration, using digital technologies. The European Union-28
Digital public services aggregate score is 0.554 for the year 2016. This score isEU Policy for Digital Society 199

calculated as the weighted average of two sub-dimensions at the level of EU-28
countries (2016):
• E-government (55.5% of 67%): E-government users; Pre-filled forms; Online
service completion; Open data.
As the online platforms play a central role, the European Commission intends to
reinforce the trust and security in digital services and in handling of the personaldata, through new EU Data protection rules (European Commission 2017).
3 ICT Sector Influence on EU-28 Economic Growth
Information, Communication and Technology Sector has an important role inEuropean economic growth. The percentage of EU ’s ICT sector in GDP was
4.10% in 2010 (Graphic 2). According to several authors, “ it is expected that
60% of the EU economic growth is due to ICT contribution ” (Cruz-Jesus et al.
2016 ).
In our analysis, we used the cross-sectional approach on 28 European Union
countries, focusing on ICT and GDP indicators, based on correlation function. Wealso introduced two moderating variables (national corruption and lifelong learn-ing) assumed by economists and sociologists to influence the connection betweenICT and GDP (Table 1).
According to the results from the Table 1, the effects of the development of the
ICT industry (ICT demand and ICT supply) are very close linked to the EuropeanUnion countries ’economic growth (Pearson coefficient, Sig.). The digital economy
Graphic 2 Percentage of the ICT sector on GDP (2010) (Source: authors ’compilation after
Eurostat, 2016)200 T. Burger-Helmchen and G.-M. Meghisan-Toma

and society follows two directions: production of digital technologies anduptake
and usage of digital technologies by businesses and individuals (Eurostat 2016).
Based on the obtained results, some recommendations should be made:
•There is a strong connection between economic development (GDP) and ICT
supply (Level of internet access-households, Households with broadbandaccess, Enterprises with broadband access) (Table 1). More than half of the
European Union ’s households have Internet access (80%) and broadband access
(78%). The lowest values of Internet access-households and Households withbroadband access were registered in Bulgaria, while the highest levels were inLuxembourg. The EU-28 average for Enterprises with broadband access is 95%(2015), while full broadband access can be explored in countries such asNetherlands, Finland and Lithuania (Table 2).
EU-28 is on its way to reach 100% Internet access and broadband access for
households and enterprises till 2020. European Union countries should be ready torespond to the future demand and offer next generation communication networks(Mobile Communications Journal 2016).
•There is a strong connection between economic development (GDP) and Inter-
net use by individuals (Pearson coefficient 0.695; sig. 0.000 <0.01). The lowest
values of Internet use by individuals was registered in Bulgaria (60%) andRomania (62%), while the EU-28 average of internet use had an ascendanttrend, from 60% (2007) up to 81% (2015) (Graphic 3).
•Lifelong learning is closely linked to Economic growth (Pearson coefficient
0.649; sig. 0.000 <0.01). A percentage of 45% of Europeans do not have digital
skills (Mobile Communications Journal 2016) .Romania is the country with theTable 1 Correlation between ICT variables and economic growth in European Union-28
countries
VariablesGDP (Pearson
coefficient)
Moderating
variablesCorruption Transparency Index 0.649a(sig 0.000)
Lifelong learning (%) 0.514a(sig 0.005)
ICT demand Internet use by individuals (%) 0.695a(sig 0.000)
Enterprises having purchased online (at least
1%)0.456b(sig 0.015)
ICT supply Level of Internet access-households (%) 0.722a(sig 0.000)
Households with broadband access (%) 0.710a(sig 0.000)
Enterprises with broadband access (%) 0.434b(sig 0.021)
Observations (no.) 28
aCorrelation is significant at the 0.01 level (2-tailed)
bCorrelation is significant at the 0.05 level (2-tailed)
Source: Data analysed with SPSS 20.0 software for WindowsEU Policy for Digital Society 201

Table 2 Descriptive statistics of ICT supply indicators (2015)
Level_of_internet_access_households (%) Households_with_broadband_access (%) Enterprises_with_broadband_access (%)
N Valid 28 28 28
Missing 0 0 0
Mean 80.2857 78.2143 94.7857Minimum 59.00 59.00 76.00Maximum 97.00 95.00 100.00
Source: Data analysed with SPSS 20.0 software for Windows202 T. Burger-Helmchen and G.-M. Meghisan-Toma

lowest percentage regarding Lifelong learning with only 1.3%, compared to the
average of EU-28 of 10.7% (Graphic 4).
European Commission should focus more on training and competences ’devel-
opment for a digital economy and society.
•Online commerce represents an opportunity for European Union ’s enterprises,
even though only 16% of SMEs sell online (Eurostat 2016), despite the fact that
the costs associated with the staff “is the third most significant expenditure for aretailer” (Dabija et al. 2011 ). In this case, the efforts of the enterprises should be
“primarily targeted to ensure high returns for equity providers (shareholders), inorder to increase their wealth” (Cı ˆrciumaru et al. 2010 ; Bus ¸e et al. 2007 ).
However, the companies are encouraged to use forecasting, as a “tool o strategicmanagement” (Constangioara et al. 2009 ). The EU-28 average percentage of the
enterprises having purchased online was 24% (2015) (Graphic 5).
Graphic 3 EU-28 Internet use by individuals-% (2007–2015) (Source: authors ’compilation after
Eurostat, 2016)
Graphic 4 EU-28 Lifelong learning-% (2015) (Source: authors ’compilation after Eurostat,
2016)EU Policy for Digital Society 203

Countries like Greece (5%) or Bulgaria (6%) are expected to register progress,
due to new legislation that the European Commission proposes regarding the onlinecommerce (European Commission, A Digital Single Market Strategy forEurope, 2015).
The next step in our research consists in using ANOVA analysis to estimate the
level of influence of the independent variables on the dependent variable.
Within the current research, the dependent variable is Level of Internet access-
households , while the independent variables are represented by: Internet use by
individuals, Households with broadband access.
The two dependent variables explain the Level of Internet access-households in
a percentage of 98.3% (R square) (Table 3).
The ANOVA table confirms that the two models are significant (Significa-
tion¼0.000) (Table 4).
Graphic 5 Enterprises having purchased online % (2015) (Source: authors ’compilation after
Eurostat database, 2016)
Table 3 ANOVA analysis-model summary
Model R R square Adjusted R square Std. error of the estimate
1 .983a.967 .964 1.78561
aPredictors: (Constant), Internet_use_by_individuals, Households_with_broadband_access
Source: Data analysed with SPSS 20.0 software for Windows
Table 4 ANOVAaanalysis
Model Sum of squares df Mean square F Sig.
Regression 2302,004 2 1151,002 360,997 .000b
1 Residual 79,710 25 3188
Total 2381,714 27
aDependent variable: Level_of_internet_access_households
bPredictors: (Constant), Internet_use_by_individuals, Households_with_broadband_access
Source: Data analysed with SPSS 20.0 software for Windows204 T. Burger-Helmchen and G.-M. Meghisan-Toma

Internet use by individuals has a significant and positive effect on the Level of
Internet access-households (t¼4.289, p <0.01). Also, the variable Households
with broadband access has a significant and positive effect on the Level of Internetaccess-households (t¼7.499, p <0.01) (Table 5).
We created a model of significant and positive effects of the independent vari-
ables (Internet use by individuals, Households with broadband access) and the
dependent variable (Level of Internet access).
4 EU-28 Digital Divide
Following the analysis made before, we developed a model, adding more digital
divide variables to the ones previously approached: Internet use, Connection to theInternet and computer use, E-government, E-commerce. The units of the analysisfocus on the EU-28 countries (Table 6).
The correlation matrix reveals that all the elements are correlated, underlying
the fact that they are measuring the same phenomenon: the adoption of ICT
services. However, we can observe that some pairs of variables register very high
values of correlation levels (Pearson coefficient >0.9). The percentage of Individ-
uals regularly using Internet (1) has a correlation of 0.929 with the percentage of
Individuals using Internet for finding information about goods and services (4), a
correlation of 0.909 with the percentage of Individuals using Internet for Internet
banking (5), a correlation of 0.968 with the percentage of Individuals using internet
for sending/receiving e-mails (13) and a correlation of 0.954 with the percentage of
Individuals using Internet for ordering goods or services (16) (Table 7).
Factor analysis will define the correlations ’structure between variables, by
determining the common factors. The KMO value is 0.903, representing acceptable
factor solutions (Table 8).
This last one-dimensional solution allows us to explain 86,428% of the variance
(Table 9).
We can observe that out of the 17 variables, eight of them are highly correlated
(correlation more than 0.900) (Table 10).Table 5 ANOVA analysis-coefficients
ModelUnstandardized
coefficientsStandardized
coefficients
t Sig. BStd.
error Beta
1 (Constant) 1.335 3.062 .436 .667
Households_with_broadband_access .677 .090 .640 7.499 .000Internet_use_by_individuals .324 .075 .366 4.289 .000
aDependent Variable: Level_of_internet_access_households
Source: Data analysed with SPSS 20.0 software for WindowsEU Policy for Digital Society 205

This model has an acceptable internal coherence (alpha ¼0.960). There is not
possible to improve alpha by eliminating other items (Table 11).
According to the research made, the main drivers of digital divide across Eu-28
countries are (Table 12):
• The frequency of Internet usage (with variations from 52% to 97% usage rate at
the level of EU-28);
• Use of Internet for finding information about goods and services (with variations
from 26% to 84% at the level of EU-28);Table 6 Digital divide variables
Variables Code
Internet use Individuals regularly using Internet E_use (1)
Individuals using the Internet for looking for
information about education, training orcourse offersE_education (2)
Individuals seeking health-related information E_health (3)
Individuals using Internet for finding informa-
tion about goods and servicesE_info_goods (4)
Individuals using Internet for Internet banking E_banking (5)
Individuals taking part in online consultations
or votingE_voting (6)
Individuals using the internet for doing an
online courseE_course (7)
Individuals using internet for looking for a job
or sending a job applicationE_job (8)
Individuals using internet for selling goods or
serviceE_sell (9)
Individuals using internet for uploading self-
related contentE_upload (10)
Individuals using internet for downloading
softwareE_software (11)
Individuals using internet for participating in
social networksE_social (12)
Individuals using internet for sending/receiv-
ing e-mailsE_mail (13)
Connection to the
Internet and computeruseIndividuals using mobile devices to access
internet on the moveM_internet (14)
E-government Individuals using the Internet for interaction
with public authoritiesE_governance (15)
E-commerce Individuals using Internet for ordering goods
or servicesE_commerce (16)
Individuals using Internet for ordering goods
or services from other EU countriesE_commerce_EU (17)
Source: Data analysed with SPSS 20.0 software for Windows206 T. Burger-Helmchen and G.-M. Meghisan-Toma

Table 7 Pearson correlation coefficient
1 2 3 4 5 6 7 8 9 1 01 11 21 31 41 51 61 7
1 1 .569a.794a.929a.909a.657a.664a.723a.577a.549a.721a.704a.968a.882a.881a.954a.700a
2 1 .677a.504a.452b.801a.575a.694a.465b.598a.808a.559a.477b.615a.583a.566a.630a
3 1 .831a.697a.731a.580a.740a.597a.606a.862a.674a.751a.753a.779a.729a.599a
4 1 .855a.618a.558a.690a.657a.502a.686a.612a.923a.814a.856a.894a.557a
5 1 .585a.621a.712a.569a.465b.643a.608a.894a.727a.897a.848a.572a
6 1 .681a.699a.550a.484a.850a.475b.608a.605a.635a.675a.634a
7 1 .692a.281 .456b.592a.541a.613a.668a.634a.627a.492a
8 1 .655a.645a.813a.687a.621a.757a.788a.736a.496a
9 1 .266 .639a.353 .558a.557a.520a.659a.258
10 1 .670a.603a.460b.577a.525a.456b.438b
11 1 .626a.623a.702a.738a.669a.645a
12 1 .656a.746a.585a.632a.587a
13 1 .810a.833a.930a.639a
14 1 .769a.863a.701a
15 1 .834a.624a
16 1 .634a
17 1
Observations 28
aCorrelation is significant at the 0.01 level (2-tailed)
bCorrelation is significant at the 0.05 level (2-tailed)
Source: Data analysed with SPSS 20.0 software for WindowsEU Policy for Digital Society 207

Table 8 KMO and Bartlett ’s test
Kaiser-Meyer-Olkin measure of sampling adequacy .903
Bartlett ’s test of sphericity Approx. Chi-square 333,966
df 28
Sig. .000
Source: Data analysed with SPSS 20.0 software for Windows
Table 9 Total variance explained
ComponentInitial eigenvalues Extraction sums of squared loadings
Total % of VarianceCumulative
% Total % of VarianceCumulative
%
1 6914 86,428 86,428 6914 86,428 86,428
2 .371 4635 91,064
3 .307 3837 94,9014 .186 2323 97,2245 .087 1089 98,313
6 .074 .924 99,237
7 .045 .565 99,8038 .016 .197 100,000Extraction Method: Principal Component Analysis
Source: Data analysed with SPSS 20.0 software for Windows
Table 10 Component matrix
Component
1
Individuals_regularly_using_internet .986
Individuals_using_internet_for_information_about_goods .956Individuals_seeking_health_related_information .849Individuals_using_internet_for_internet_banking .920
Individuals_using_mobile_devices_to_access_internet .890
Individuals_using_internet_for_interaction_with_public_authorities .921Individuals_using_internet_for_ordering_goods_or_services .951Individuals_using_Internet_for_email .958Extraction Method: Principal Component Analysis
a. 1 components extracted
Source: Data analysed with SPSS 20.0 software for Windows
Table 11 Reliability
statisticsCronbach ’s alpha N of items
.960 8
Source: Data analysed with SPSS 20.0 software for Windows208 T. Burger-Helmchen and G.-M. Meghisan-Toma

Table 12 Drivers of digital divide for EU-28 (2015)
N Minimum Maximum Mean Std. deviation
Individuals_regularly_using_internet 28 52.00 97.00 76.0714 11.62032
Individuals_using_internet_for_information_about_goods 28 26.00 84.00 61.3571 14.54804Individuals_seeking_health_related_ information 28 27.00 67.00 47.5000 11.35129
Individuals_using_internet_for_internet_banking 28 5.00 86.00 47.5000 23.41810
Individuals_using_mobile_devices_to_access_internet 28 26.00 80.00 57.4643 14.90832Individuals_using_internet_for_interaction_with_public_authorities 28 11.00 88.00 49.5000 19.14758Individuals_using_internet_for_ordering_goods_or_services 28 11.00 81.00 48.3571 19.90573
Individuals_using_Internet_for_email 28 43.00 91.00 67.9286 13.70841
Valid N (listwise) 28
Source: Data analysed with SPSS 20.0 software for WindowsEU Policy for Digital Society 209

• Use of Internet for seeking health-related information (with variations from 27%
to 67% at the level of EU-28);
• Use of Internet for Internet banking (with variations from 5% to 86% at the level
of EU-28);
• Use of mobile devices to access internet on the move (with variations from 26%
to 80% at the level of EU-28);
• Use of Internet for interaction with public authorities (with variations from 11%
to 88% at the level of EU-28);
• Use of Internet for ordering goods or services (with variations from 11% to 81%
at the level of EU-28);
• Use of Internet for sending/ receiving e-mails (with variations from 43% to 91%
at the level of EU-28).
5 Conclusions
In all stages of their life, people interact with digital technology: at work (e-mailing,
professional networking, telecommunications); as citizens (digital education, dig-
ital health systems, unique digital counter); as private individuals (interaction with
e-shops, e-banks), making use of digital devices. However, regardless of thisinteraction, there is still a digital gap between the countries of the European Union.
As a further development within the nearest future, the “ non market sectors such
as financial, health, education and even government services have become moreprone to the positive growth effects from ICT” (European Commission 2013).
Despite the diversity of cultural clusters, Europe should be seen “as a homog-
enous region” (Dima and Vasilache 2013 ), with the member countries being
“subject to the multilateral surveillance procedures” (Marcu 2008 ).
Questions and Activities
1. Define the term “digital single market”.
2. Explain the main influences of ICT sector on economic development.3. Which are the main elements that we can use in order to assess the evolution of
ICT sector of a country?
4. Which are the main measures to eliminate the digital gap between EU
countries?
5. Take one EU country and assess the digital gap.6. Take one driver of digital divide at the level of EU and find solutions for further
improvement.
7. Take one EU country and analyse the level of Internet access in rural and urban
areas. What solutions would you propose for increasing the level of Internetaccess in both areas?
8. What measures should be taken in order to determine the EU ’s enterprises to
use a wide variety of ICT services?210 T. Burger-Helmchen and G.-M. Meghisan-Toma

9. What measures should be taken in order to determine the EU ’s population to
use a wide variety of ICT services?
10. Propose concrete strategies for further adoption of EU digital society.
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