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Cited by 19ICT Impact and PoliciesGender and Technology in EducationInformation Society and Technology Trends

A spatial analysis of the digital gender gap in South Africa: Are there any fundamental differences?

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Shiferaw, Yegnanew A.·2024·Technological Forecasting and Social Change
DOI 10.1016/j.techfore.2024.123443
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Abstract

This research paper explores the gender disparities in accessing and using information and communication technologies (ICT) in various local municipalities in South Africa. A statistical technique called small area estimation (SAE) is utilized to improve the accuracy of the estimates. It involves using both the 2016 Community Survey (CS2016) and the Population Census 2011 (PC2011) and applying methods such as the log-transformed spatial Fay-Herriot (FH) and the hierarchical Bayes spatial FH models. According to the results, the digital statistics estimates generated by the SAE methods at the local municipality level are more precise and efficient than the direct design-based estimates. In other words, combining the CS2016 and PC2011 datasets with the spatial information resulted in more precise estimates. The results also indicate a digital divide between men and women. Specifically, South African men tend to use the internet more than women. However, disparities in cell phone ownership have diminished at the national level, and the gap in some local municipalities, such as Kheis, Midvaal, Kgatelopele, Thabazimbi, and Karoo Hoogland, is >30 %. The results provide evidence of the digital gender divide within South African households at the local municipality level. Indeed, as the Fourth Industrial Revolution is now underway, the analysis of digital statistics can provide policymakers with a clear picture of South Africa's readiness level to welcome this revolution.

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  • Practical disciplinary trends include attaching AI-generated logs and prompts as supplemental materials.

    “Practical disciplinary trends include attaching AI-generated logs and prompts as supplemental materials (e.g., Butson & Spronken-Smith, 2024;Shiferaw, 2024).”

    From A university framework for the responsible use of generative AI in research (2026) · cites this paper as Shiferaw, 2024

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Authors
Shiferaw, Y. A.
Affiliations
University of Johannesburg (ZA)
Corresponding author
Shiferaw, Yegnanew A.
ORCID
Shiferaw, Yegnanew A.
Venue
Technological Forecasting and Social Change
Publisher
Elsevier BV
Published
2024-07
Volume
204
Pages
123443
ISSN
0040-1625 (ISSN-L)
DOI
10.1016/j.techfore.2024.123443
OpenAlex
W4396986157
Cited by
14
References
77
Citations by year
2026: 6 · 2025: 7 · 2024: 1
FWCI
2.32
Type
journal article
Language
en
Open access
Licence
Locations
  • Technological Forecasting and Social Change (publishedVersion, cc-by-nc)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Engineering › Media Technology › ICT Impact and Policies
  • Social Sciences › Gender Studies › Gender and Technology in Education
  • Social Sciences › General Social Sciences › Information Society and Technology Trends
Keywords
gender digital divide, digital divide, ICT access, internet use, mobile phone ownership, small area estimation, Bayesian hierarchical model, municipalities, South Africa, household technology use, Fourth Industrial Revolution

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