Abstract
Mobile phones are the most accessible information and communication technology today, and they serve as the gateway to high-speed internet for large populations in developing economies. However, despite the progress, there remains a persistent disparity in mobile phone usage among users, and between users and non-users, in developing countries. However, the literature on the digital divide has paid limited attention to the multi-level nature of this gap in mobile phone adoption and use, particularly in developing countries. This research paper provides a comparative analysis of this divide in mobile phone usage in eight developing nations from Africa and Asia. Broadly, the study categorises individuals into three groups: mobile phone non-users, mobile phone users who do not use internet applications and mobile phone users who use applications that need internet access. The disparity between these users was analysed using micro-level survey data from each country. The study results show that the nature of the divide varies across countries and that the influence of socio-demographic factors is not consistent. Further, we find that there is a larger digital divide in terms of mobile phone usage in Asian countries when compared to African countries. The study recommends that policymakers and international agencies exercise caution while developing one-size-fits-all cross-country policies to address the multi-level digital divide.
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Notes
Though Wei et al. (2011) extend the two levels and add a third level, known as the digital outcome divide, for the purpose of this study, we restrict our analysis to only the first two levels.
Please note that selection of these countries was not random. These are countries for which latest micro-level data was available from Intermedia while we wrote this paper. More details on the data is provided in the methodology section.
The dataset is a secondary data available publicly on request. The dataset can be accessed here: http://finclusion.org/data_fiinder/. The primary objective of the survey was to measure changes in trends and market developments in digital financial services.
R is an open-source statistical software for data analysis.
Lin et al. (2013): Effect size is the sensitivity of the dependent variable to changes in the independent variable. In logistic regression, the effect size can be interpreted by considering the factor (β) by which the odds of Y = 1 at X = 1 are higher than at X = 0.
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Vimalkumar, M., Singh, J.B. & Sharma, S.K. Exploring the Multi-Level Digital Divide in Mobile Phone Adoption: A Comparison of Developing Nations. Inf Syst Front 23, 1057–1076 (2021). https://doi.org/10.1007/s10796-020-10032-5
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DOI: https://doi.org/10.1007/s10796-020-10032-5