Big Data for Good: Insights from Emerging Markets*

Published on Sep 1, 2017in Journal of Product Innovation Management5
· DOI :10.1111/JPIM.12406
Rajesh Chandy26
Estimated H-index: 26
(LBS: London Business School),
Magda Hassan2
Estimated H-index: 2
,
Prokriti Mukherji3
Estimated H-index: 3
Sources
Abstract
This paper examines how innovations involving big data are helping to solve some of the greatest challenges facing the world today. Focusing primarily on the developing world, this paper explores how the large volumes of digital information, increasingly available in these contexts, can help decision-makers better address problems as big as poverty, illness, conflict, migration, corruption, natural disasters, climate change, and pollution, among other areas. This paper argues that the information vacuum that still exists in many developing countries makes the potential for impact from big data much greater in these contexts. Through a series of case studies, the authors demonstrate how big data can be used to address pressing social and environmental challenges in developing countries. The authors present research questions that could not have been addressed in the absence of dramatic recent increases in data volume, variety, and velocity. They then extrapolate from these questions, and discuss the nature of the technological changes that now allow decision-makers in developing countries to leapfrog from data poverty to big data, and permit innovative solutions to the aforementioned challenges. The authors emphasize the importance of looking beyond the current focus, in the literature, on storing, analyzing, and creating commercial value from big data. Instead, they point to the importance of innovativeness in identifying, integrating, disseminating, and applying new sources of data to execute actions that in turn generate product, service, process, and business model innovations that are impactful due to big data. The authors argue that academic researchers have an important role to play in helping the world harness the potential for big data innovations, through validation, visualization, and verification of such data.
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