It’s still a thing: digital inequalities and their evolution in the information society

Abstract

Internet diffusion has prompted research into differences in internet access, use and consequences. Exploiting the full potential of the ongoing digital transformation in all spheres of life-a proclaimed goal of governments and international organizations-requires ensuring equal opportunities and supporting disadvantaged individuals in their internet use. Using representative, population-level survey data from Switzerland spanning nearly a decade (2011-2019; Ntotal = 5,581), multiple multivariate regression analyses tested the effects of demographic and internet-use related variables on access (general and mobile), on internet skills and on different types of use (information, entertainment, commercial transactions and communication). Results indicated that despite high access rates (92% in 2019), considerable usage inequalities persist in the Swiss information society: in particular, we found an increasing marginalization of older individuals regarding the adoption of the internet and revealed the importance of internet skills, experience and mobile internet use for adopting differentiated types of use. The extreme differences between the highly connected majority and an increasingly marginalized minority raise concerns about the latter group’s opportunities for personal, social and economic benefits in an information society. This study provides unique results on current digital inequalities and their evolution which are crucial for assessing the success, suitability and legitimacy of digitization policies.

Conflicting Norms—How Norms of Disconnection and Availability Correlate With Digital Media Use Across Generations

“…However, as the study’s primary aim was to learn about differences in normative influences on digital disconnection across generational groups, this limitation does not concern the study’s main aim (as it may have affected generations comparably). In this context, we also note that the study was conducted in Switzerland, which is characterized by high levels of digital media uptake with well over 90% of the population using the Internet (Festic et al, 2021). Thus, generalizations of the findings to regions with different digital infrastructures and cultures should be done with careful consideration.…”

An Assessment of the Structural Validity and Measurement Invariance of the Web-Use Skills Scale for Aging Internet Users

“…56 As a next step, research focusing on the measurement invariance of the WUS could highlight other factors of digital inequality, such as occupation and income, 2 and investigate whether the WUS is also invariant in cross-country settings. 30 Moreover, it may be interesting to test the convergent validity of the WUS with other survey measures of internet skills. In particular, this scale could be compared with those based on multidimensional measurement models to assess which theoretical dimensions of internet skills besides web-use skills are captured by the WUS.…”

“…6,9,24,25 Indeed, there is a large difference between the lifestyles of those aged 50-64 years (largely employed) and those aged 65+ years (largely retired), leading to an increasing risk of social and digital exclusion in the older group. 21,[26][27][28] Differences in internet skills also relate to gender, with women reporting lower levels of internet skills 6,[29][30][31][32] and education; here, internet skills are shown to increase with level of education. 1,30,31…”

“…21,[26][27][28] Differences in internet skills also relate to gender, with women reporting lower levels of internet skills 6,[29][30][31][32] and education; here, internet skills are shown to increase with level of education. 1,30,31…”

What about the Less IT Literate? A Comparison of Different Postal Recruitment Strategies to an Online Panel of the General Population

“…In addition, research on digital inequality has shown that individual factors influence Internet use (e.g., Festic et al 2021) and that these individual factors translate into different levels of socioeconomic status and socioeconomic inequalities (see Scheerder et al 2017). (Social) inequality measures related to the socioeconomic situation of individuals especially might suffer from nonresponse bias in online panels that underrepresent individuals with low IT literacy.…”