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Digital platforms for development: Foundations and research agenda
Open accessAbstract
Digital platforms hold a central position in today's world economy and are said to offer a great potential for the economies and societies in the global South. Yet, to date, the scholarly literature on digital platforms has largely concentrated on business while their developmental implications remain understudied. In part, this is because digital platforms are a challenging research object due to their lack of conceptual definition, their spread across different regions and industries, and their intertwined nature with institutions, actors and digital technologies. The purpose of this article is to contribute to the ongoing debate in information systems and ICT4D research to understand what digital platforms mean for development. To do so, we first define what digital platforms are and differentiate between transaction and innovation platforms, and explain their key characteristics in terms of purpose, research foundations, material properties and business models. We add the socio‐technical context digital platforms operate and the linkages to developmental outcomes. We then conduct an extensive review to explore what current areas, developmental goals, tensions and issues emerge in the literature on platforms and development and identify relevant gaps in our knowledge. We later elaborate on six research questions to advance the studies on digital platforms for development: on indigenous innovation, digital platforms and institutions, on exacerbation of inequalities, on alternative forms of value, on the dark side of platforms and on the applicability of the platform typology for development.
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“What remains a gap, however, is an understanding within the policy space of how transaction and innovation platforms interact to address development and humanitarian goals (Bonina et al., 2021).”
From Digital identity as a platform for improving refugee management (2021) · cites this paper as Bonina et al., 2021
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Metadata
- Authors
- Bonina, C., Koskinen, K., Eaton, B., & Gawer, A.
- Affiliations
- University of Surrey (GB)
- Aalto University (FI)
- Copenhagen Business School (DK)
- Corresponding author
- Bonina, Carla
- Venue
- Information Systems Journal
- Publisher
- Wiley
- Published
- 2021-01-28
- Volume
- 31
- Issue
- 6
- Pages
- 869-902
- ISSN
- 1350-1917 (ISSN-L)
- 1365-2575
- OpenAlex
- W3127663722
- Cited by
- 512
- References
- 127
- Citations by year
- 2026: 108 · 2025: 113 · 2024: 120 · 2023: 96 · 2022: 56 · 2021: 19
- FWCI
- 64.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Information Systems Journal (publishedVersion, cc-by)
- Aaltodoc (Aalto University) (submittedVersion, cc-by)
- CBS Research Portal (Copenhagen Business School) (submittedVersion, cc-by)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Funders
- Economic and Social Research Council
- Royal Holloway, University of London
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Keywords
- digital platforms, development, ICT4D, transaction platforms, innovation platforms, business models, independent innovation, institutions, inequality, platform typology, Global South
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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