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Walking into the Digital Era: Comparison of the European Union Countries in the Last Decade

This study allows us to understand how European Union countries are more or less prepared for confronting the digital era. In particular, we aim to understand whether the least developed countries are close or fairly distant from the others. For this study, data for some variables associated with digital skills, digital economy and digital society have been collected from the Eurostat database during the period 2010-2020. To analyze the data, we applied a double principal component analysis.

These results allow us to identify the differences and similarities between countries and indicators from 2010-2020, and, more precisely, to study the countries' evolution trends and the evolution of the relations between the different indicators.

1.1. Introduction

This study allows us to understand how the countries in the European Union are more or less prepared for confronting the digital era. People and societies have to deal with these new challenges not only to gain knowledge but also to promote growth, development and opportunities for everyone. In particular, it is interesting to see whether the least developed countries are close or relatively distant from the others in this route, in order to develop new strategies and to overcome detected fragilities.

Table 1.1. Variables considered in the study grouped by topic

G1: Activity and employment status of individuals
V1 - % employed persons in the universe of active persons with ICT education
V2 - % males in the universe of employed persons with ICT education
V3 - % persons with tertiary education among employed persons with ICT education
V4 - % persons aged 15-34 among the employed persons with ICT education G2: Internet at households with population aged 16-74 years
V5 - % households with Internet access
V6 - % households with broadband Internet connection G3: Internet use by individuals
V7 - % individuals with daily Internet access in the last three months before the survey
V8 - % individuals with Internet use in the last three months before the survey
V9 - % individuals with Internet use in the last 12 months before the survey
V10 - % individuals with Internet use more than a year ago before the survey
V11 - % individuals who have never used Internet before the survey G4: Online purchase by individuals
V12 - % individuals with last online purchase in the last three months before the survey
V13 - % individuals with last online purchase in the last 12 months before the survey G5: Reasons of the individuals for using Internet
V14 - % individuals using Internet for finding information about goods and services
V15 - % individuals using Internet for looking for a job or sending a job application
V16 - % individuals using Internet for selling goods and services G6: Enterprises use for selling (having e-commerce)
V17 - % enterprises with e-commerce sales of at least 1% turnover G7: Enterprises that provided training to develop/upgrade
ICT skills, excluding enterprises of the financial sector
V18 - % small enterprises provided training to ICT/IT specialists
V19 - % medium enterprises provided training to ICT/IT specialists
V20 - % SMEs provided training to ICT/IT specialists
V21 - % large enterprises provided training to ICT/IT specialists
V22 - % small enterprises provided training to other employed persons
V23 - % medium enterprises provided training to other employed persons
V24 - % SMEs provided training to other employed persons
V25 - % large enterprises provided training to other employed persons
V26 - % small enterprises provided training to their personnel
V27 - % medium enterprises provided training to their personnel
V28 - % SMEs provided training to their personnel
V29 - % large enterprises provided training to their personnel

1.1.1. The dataset

For this study, a large number of indicators associated with digital skills, digital economy and digital society (29 variables) have been considered, as well as all European countries for which we have data available (30 individuals). The data for these indicators were collected from the Eurostat database during the period 2010-2020.

The variables are grouped by topic (groups G1-G7), and are listed in Table 1.1. When we refer to ICT (Information and Communication Technology) Education, in the general sense, it means providing users with a diverse set of technological tools, definitions and resources to create, store, communicate, manage and optimize information. The database aggregates the ICT education levels into two categories: upper-secondary and post-secondary non-tertiary (levels 3 and 4), and tertiary (levels 5-8). Concerning employed persons with ICT education, they are divided by two classes of age: 15-34 and 35-74. The enterprises are classified accordingly to the number of employees and self-employed persons as follows: small (10-49), medium (50-249), SMEs (10-249) and large (250 or more).

Of course, it would be interesting to include other indicators such as the percentage of the ICT sector in GPD, the R&D personnel in the ICT sector as a percentage of total R&D personnel or the business expenditure on R&D in the ICT sector as a percentage of total R&D expenditure, for instance. However, we do not have information for all countries and years during the period.

The countries (individuals) considered in this study are presented in Table 1.2. We also further analyzed six data tables, corresponding to the years 2010, 2012, 2014, 2016, 2018 and 2020, each one with the same countries and variables. As the United Kingdom was not part of the EU in 2020, we considered the values obtained in 2019, instead of 2020, so we could still include it in the analysis.

Table 1.2. Countries considered in the study

Countries Countries Countries EU27 - European Union 27 FR - France AT - Austria BE - Belgium HR - Croatia PL - Poland BG - Bulgaria IT - Italy PT - Portugal CZ - Czechia CY - Cyprus RO - Romania DK - Denmark LV - Latvia SI - Slovenia DE - Germany LT - Lithuania SK - Slovakia EE - Estonia LU - Luxembourg FI - Finland IE - Ireland HU - Hungary SE - Sweden GR - Greece MT - Malta UK - United Kingdom ES - Spain NL - Netherlands NO - Norway

1.1.2. Preliminary analysis of the data

Before proceeding with a multivariate data analysis, we carried out an exploratory analysis in order to gain insight into the data. In particular, we represented the boxplots by year and for all of the variables (not presented here) and among other conclusions, it is worth mentioning here the huge number of outliers observed in the data, and reported in Table 1.3. The countries with an * are severe outliers. Some countries appear as outliers with respect to some variables during several years of the period 2010-2020, such as GR, RO and BG: GR is a severe lower outlier in variable V1 (the percentage of employed persons in the universe of active persons with ICT education is small comparatively to the corresponding percentage in the other countries); RO and BG are lower outliers in variables V21, V25 and V29 (the percentage of large enterprises providing training in ICT skills to their personnel, specialists or other employed persons is small when compared to what happens in other countries). We also mention, for instance, DK and FI, who appear during some years of the period as upper outliers in variable V15 (with a large percentage of individuals using the Internet to look for a job or sending a job application compared to other countries), and countries such as BE and FI, who in 2020 were upper outliers in variables V19, V23 and V27 (i.e. they have a large percentage of medium enterprises providing ICT training when compared with other countries). Other details can be found in Table 1.3.

Table 1.3....