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Despite having high literacy rates and a robust digital infrastructure, the Middle East and North Africa (MENA) region still faces digital inequalities. This collection of articles explores the complexities of digital disparities within MENA, taking into account cultural, economic, and historical factors. Each article in this section examines the impact of digital inequality on society, the economy, and culture, emphasizing the need for context-specific approaches. The goal of this thematic issue is to encourage international study and address social challenges stemming from digital divides in MENA by critically discussing digital disparities and their effects. [ABSTRACT FROM AUTHOR]

This article investigates the interaction between digital capital and some offline components (economic, cultural, political, social and personal) that represent the background against which we access and use the Internet. Based on a stratified sample of the UK population (868), six indexes (one for each component) were generated through factor analysis and univariate analysis. We summarised them into a unique model by performing a multiple linear regression to evaluate the role-played by offline components in the development/reinforcement of digital capital. The interaction between these new indexes and the digital capital index shows that, with the exception of the political component, all offline backgrounds positively contribute to digital capital. Moreover, the multiple regression analysis shows that the economic and social components have the strongest influence on digital capital. [ABSTRACT FROM AUTHOR]

This paper explores Digital Poverty (DP) in England by adopting the DP Alliance's theoretical framework that includes both Individual Determinants (individual capability and motivation) and Circumstantial Determinants (conditions of action). Such a framework is interpreted as an expression of Strong Structuration Theory (SST), by situating the connection between social structure and human agency in an intertwined relationship. We focus on new potential vulnerabilities that are connected to DP in England by drawing on a survey conducted on a randomised stratified sample (n = 1988) of parents aged between 20–55 with children at school. Exploring parents' experience in the COVID-19 era, we identified economic factors and having children with disabilities as important predictors connected to Digital Poverty. Additional socio-demographic traits (such as age and education), parental status, lifestyles and digital behaviours also play a role in predicting some of the determinants linked to Digital Poverty. This paper adds to SST by empirically exploring how individuals use the Internet according to their metabolised embodiment of external determinants. [ABSTRACT FROM AUTHOR]

This article investigates the entanglement between socio-economic and technological factors in conditioning people's patterns of Internet use. We analysed the influence of sociodemographic and techno-social aspects in conditioning the distinctive digital practices developed by Internet users. By using a representative sample of UK users and different methods of analysis, such as factor analysis, K-means cluster analysis and logit analysis, this study shows how techno-social variables have a stronger effect than socio-economic variables in explaining the advanced use of the Internet. [ABSTRACT FROM AUTHOR]

This article theorizes fresh connections between Bourdieusian social theory, and the digital divide in five key areas: political, economic, cultural, social, and personal digital advantage. In so doing it makes new arguments about how digital resources result in benefits that accrue from the combination of both access to and use of ICTs. In this way, the findings shed additional light on the third level of the digital divide by focusing on the role played by digital capital in influencing the uneven distribution of benefits that derive from the use of the Internet. Based on a structured sample of the UK population, the article adopts the model of digital capital developed by Ragnedda, Ruiu and Addeo (2019). Findings show that varied levels of digital capital are related to engagement in activities that have political, social, economic, cultural, and personal valence. Thus, the study offers compelling evidence of the increasing importance of digital capital in everyday life. [ABSTRACT FROM AUTHOR]

The paper draws linkages between ethnic diversity of the eight federal districts of Russia and their technological development (access and use of ICTs, digital literacy, etc.). We show that although there is no universal correlation between ethnic composition of the regions and the level of their technological advancement, regions where Russians constitute the majority (i.e. Central and Northwestern) more often tend to be the country's leaders in terms of technological development. Following up on this, we use purposive sample of 398 Internet users based in Russia, showing how the level of digital capital of users varies depending on their ethnicity (here we will distinguish between two large groups – Russians and non-Russians, based on self-identification of survey participants) and their place of living. Results of the digital capital study, despite being indicative, show that those belonging to the ethnic majority (in our case Russians) and those living in big cities tend to have a higher level of digital capital. We argue that although ethnicity solely does not define the level of users' digital capital, it is still an important and understudied issue. This is particularly true for big multiethnic societies, such as the Russian society, where digital divide across various groups and regions remains a serious problem. [ABSTRACT FROM AUTHOR]

This article develops a Digital Capital Index by adopting the definition provided by Ragnedda, who defines Digital Capital as the accumulation of digital competencies and digital technologies, and the model for measuring it developed by Ragnedda and Ruiu. It aims to develop a measure that can be replicated for comparison in different contexts. This article contributes both theoretically and empirically to the literature by (a) consolidating the concept of Digital Capital as a specific capital and (b) empirically measuring it. A Digital Capital Index is developed through an exploratory factor analysis (EFA) and validated with a representative sample survey of 868 UK citizens. The validation procedure shows that the Digital Capital Index is associated with socioeconomic and sociodemographic patterns, such as age, income, educational level and place of residence, while it appears not to be related to gender. [ABSTRACT FROM AUTHOR]

• The research sheds light onto the gradual process of digital inclusion by creating a typology with three different types of people according to their level of digital inclusion, namely Advanced, Intermediate and Basic. • Our analysis shows the self-reinforcing effect of digital and social exclusion, by highlighting how, despite their access to the Internet, those people at risk of social exclusion are more likely to lack the digital experience necessary to fully exploit the possibilities the Internet can offer. • Those who tend to obtain more benefits from the use of the Internet are, on average, young, well-educated and with a higher income, thus reinforcing their already privileged social positions. • Socially vulnerable people have more difficulties in using digital technologies and gaining benefits from them, leading to further marginalisation of their position and deepening of inequalities. • By highlighting how different levels of digital inclusion are related to socioeconomic and sociodemographic features, this research contributes to reinforcing the idea that offline social structures and practices influence individuals' ability to use digital technologies as an empowering tool of social inclusion. Since an increasing number of daily activities are carried out online, an exclusion or limited access to the Internet prevent citizens from entering a world full of opportunities that cannot be accessed otherwise; in this sense, inclusion in the digital realm is strictly connected to social inclusion. Digital inclusion is not conceived as a mere dichotomy, access versus no access, but in terms of the degree to which e-inclusion improve wellbeing for individuals, community and society. Using a quantitative method based on a multivariate analysis, multiple correspondence analysis and cluster analysis, applied to a representative sample of UK citizens, this article sheds light onto the gradual process of digital inclusion, highlighting how social and digital inclusion are intertwined and how people who have one or more social or economic vulnerabilities are more likely to be in the group of those who are digitally excluded. [ABSTRACT FROM AUTHOR]