Review by: Sérgio de Andrade
A new study conducted by Ana Gomes (Portuguese Air Force Academy) and José G. Dias (BRU, ISCTE-IUL) reveals that despite the increased access to the internet across the European Union (reducing first-level digital inequalities), a deep digital divide persists in terms of internet usage frequency, types of internet use, and digital literacy (second-level digital inequalities), both within and between nation-states.
In 2010, the European Commission introduced the Europe 2020 Strategy and the Digital Agenda for Europe 2010-2020 (later extended to 2020-2030), aiming to ensure universal internet adoption among EU citizens by facilitating accessibility and digital literacy initiatives. However, the majority of these measures have yet to be fully implemented. There remain not only geographic disparities in internet access (Internet World Stats, 2021) but also socioeconomic inequalities, which are correlated with financial literacy and the types of internet use. Considering this, the article suggests that geographical differences, even when accounting for socioeconomic diversity within territories, demonstrate that internet use is a social phenomenon influenced by contextual factors (cultural norms, social infrastructure, etc.) and the social networks individuals are embedded in. These networks can either facilitate (family or friends who regularly use the internet encourage its use) or hinder (if those around an individual do not use the internet, there is no social normalisation of its use) internet adoption. Additionally, individuals’ confidence in online interactions, i.e., their perceived cybersecurity within a given territory, directly influences their willingness to engage in more “advanced” internet use.
A methodological note on how the study was conducted is pertinent. The authors utilised data from the European Commission’s Eurobarometer 87.4 (2017), which aimed to understand European citizens’ attitudes towards internet use. The data were collected through face-to-face recorded interviews across the then 28 EU member states, using multi-stage probabilistic (random) sampling. First, different EU countries were selected, followed by regional selection within these countries, and finally, individuals within these regions were chosen for interviews. The study’s sample comprised 27,812 individuals, resulting in a low margin of error (<1% with a 95% confidence interval). The authors also applied weighting factors to explanatory variables (e.g., nationality, education level, etc.) to ensure the results were representative of the European population, avoiding over- or under-representation of certain groups and allowing for more precise inferences. More details on this Eurobarometer can be found here.
The study identifies the individual characteristics and resources associated with lower internet use: income, formal education, and gender are among the most significant. To examine how these factors relate to internet usage patterns, the authors applied statistical clustering techniques to develop a typology consisting of six user profiles:
- Non-Users, Group 1: Representing 21% of the sample, these individuals lack internet access and are predominantly found in impoverished southern European countries (Portugal, Romania, etc.), where lower higher-education completion rates, reduced purchasing power, and higher ageing indices are common. Notably, in more technologically developed countries, the gap between individuals in Group 1 and the more affluent Group 6 is smaller. This group has the highest percentage of unemployed and economically inactive individuals (87%) and the highest proportion of widowed persons (26.4%).
- Basic Users, Group 2: The smallest cluster (7.9% of the sample), comprising individuals who access the internet two to three times a week, do not use it for work, and access it exclusively via computers and mobile phones, mainly for reading emails and news. This group typically has lower-secondary or upper-secondary education (52.9%), with the dominant age cohort between 45 and 54 years old. It is most prevalent in Italy (16.3%) and Poland (13.1%).
- Information Exchangers, Group 3: These users primarily access the internet at home on a daily basis but rarely at work. Almost all use computers, with email and news consumption being the preferred activities. Some 85.5% of this group is over 45 years old, with most having completed lower-secondary or higher education (50.8%). Latvia, the Czech Republic, France, Germany, and Italy have a high concentration of individuals in this profile.
- Instrumental Users, Group 4: These individuals use the internet daily at home and at work, utilising computers or mobile phones for tasks such as emailing, online banking, and shopping. Their age range is similar to that of Group 3 (>45 years), but 42.9% hold a higher-education degree. This group is most prevalent in Austria, Belgium, Germany, France, and Luxembourg.
- Socializers/Entertainers, Group 5: These users access the internet daily at home and at work, primarily via mobile phones, and spend most of their time on social media. This is the youngest group (42.5% aged 15-24) and has the highest student proportion (34.4%). They are mostly found in Southern Europe, the Balkans, and Northern Ireland.
- Advanced Users, Group 6: The most active users of the internet at home and work, with the highest use of mobile devices (smartphones and tablets) and the broadest engagement in online activities, especially email and shopping. This group consists mainly of individuals aged 25-44 (53.0%) with higher education (53.7%) and the highest urban residency rate (30.8%). It is most represented in Northern European countries, particularly Sweden, the Netherlands, and Denmark.
The analysis of statistics pertaining to these groups matters because it highlights a clear digital divide between Northern European countries (which have more Group 6 users, typically possessing higher economic and cultural capital) and Southern European countries (which have more Group 1 users, who tend to be economically disadvantaged with lower educational attainment). Another critical factor is that in more developed Northern European countries (such as Sweden), sociodemographic differences between Group 1 and Group 6 are less pronounced. This finding not only confirms the existence of a digital divide between countries but also indicates that this divide has a lesser impact within wealthier nations. Moreover, socioeconomic inequalities continue to exacerbate digital disparities, which the EU has long attempted, unsuccessfully, to address. These disparities contribute to weaker social integration (especially post-COVID) among basic and non-users and reinforce significant opportunity inequalities affecting an already vulnerable population (particularly non-users).
The authors conclude that achieving an inclusive and equitable “digital transformation” in Europe—one that mitigates digital inequalities—requires public policy measures targeted at the most vulnerable user groups (especially Groups 1 and 2) and addressing regional disparities across Europe. This should involve increased investment in formal education (which correlates with more frequent internet use), improved wealth redistribution (as income directly affects internet usage), and continuous research on digital divides to diagnose and combat them effectively.
