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
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.
Figures & Tables
📖 Papers frequently viewed together
6 Citations
8 Citations
#1G. Tomas M. Hult (MSU: Michigan State University)H-Index: 84
#2Forrest V. MorgesonH-Index: 16
Last. Claes FornellH-Index: 50
view all 5 authors...
The ability of a firm’s managers to understand how its customers view the firm’s offerings and the drivers of those customer perceptions is fundamental in determining the success of marketing efforts. We investigate the extent to which managers’ perceptions of the levels and drivers of their customers’ satisfaction and loyalty align with that of their actual customers (along with customers’ expectations, quality, value, and complaints). From 70,000 American Customer Satisfaction Index (ACSI) cus...
101 CitationsSource
#1Michel Wedel (UMD: University of Maryland, College Park)H-Index: 82
#2P.K. Kannan (UMD: University of Maryland, College Park)H-Index: 41
AbstractThe authors provide a critical examination of marketing analytics methods by tracing their historical development, examining their applications to structured and unstructured data generated within or external to a firm, and reviewing their potential to support marketing decisions. The authors identify directions for new analytical research methods, addressing (1) analytics for optimizing marketing-mix spending in a data-rich environment, (2) analytics for personalization, and (3) analyti...
311 CitationsSource
#1Joshua E. Blumenstock (UW: University of Washington)H-Index: 19
#2Nathan Eagle (SFI: Santa Fe Institute)H-Index: 39
Last. Marcel Fafchamps (Stanford University)H-Index: 77
view all 3 authors...
We provide empirical evidence that Rwandans use the mobile phone network to transfer airtime to those affected by unexpected shocks. Using an extensive dataset on mobile phone activity in Rwanda and exploiting the quasi-random timing and location of natural disasters, we show that individuals make transfers and calls to people affected by disasters. The magnitude of these transfers is small in absolute terms, but statistically significant; in response to the Lake Kivu earthquake of 2008, we esti...
58 CitationsSource
#1K. Sudhir (Yale University)H-Index: 26
Marketing Science is in a very healthy state as the premier journal for quantitative research in marketing. Since its inception, it has led the way in bringing novel and innovative methodologies and expanding into new substantive areas of inquiry. The journal is now at the cusp of its next stage of creativity and innovation. I outline new research possibilities due to big data, behavioral field studies, and managerial interest in substantive areas such as health, sustainability, emerging markets...
22 CitationsSource
#1Joshua E. Blumenstock (UW: University of Washington)H-Index: 19
#2Gabriel Cadamuro (UW: University of Washington)H-Index: 4
Last. Robert On (University of California, Berkeley)H-Index: 1
view all 3 authors...
Accurate and timely estimates of population characteristics are a critical input to social and economic research and policy. In industrialized economies, novel sources of data are enabling new approaches to demographic profiling, but in developing countries, fewer sources of big data exist. We show that an individual’s past history of mobile phone use can be used to infer his or her socioeconomic status. Furthermore, we demonstrate that the predicted attributes of millions of individuals can, in...
306 CitationsSource
#1Ans Kolk (UvA: University of Amsterdam)H-Index: 74
#2François Lenfant (UvA: University of Amsterdam)H-Index: 8
The authors aim to contribute to the literature on subsistence marketplaces and the marketing field in general by exploring social innovation partnerships in a fragile country characterized by institutional gaps—specifically, by considering the role of cross-sector collaboration in conflict-affected areas. The empirical setting consists of coffee partnerships in the Democratic Republic of the Congo, where the authors collected data from and about companies, nongovernmental organizations, and coo...
53 CitationsSource
#1Neeraj Bharadwaj (UT: University of Tennessee)H-Index: 12
#2Charles H. Noble (UT: University of Tennessee)H-Index: 18
17 CitationsSource
#1Liran Einav (Stanford University)H-Index: 49
#2Jonathan Levin (Stanford University)H-Index: 50
Background Economic science has evolved over several decades toward greater emphasis on empirical work. The data revolution of the past decade is likely to have a further and profound effect on economic research. Increasingly, economists make use of newly available large-scale administrative data or private sector data that often are obtained through collaborations with private firms, giving rise to new opportunities and challenges. The rising use of non–publicly available data in economic resea...
240 CitationsSource
Computers are now involved in many economic transactions and can capture data associated with these transactions, which can then be manipulated and analyzed. Conventional statistical and econometric techniques such as regression often work well, but there are issues unique to big datasets that may require different tools. First, the sheer size of the data involved may require more powerful data manipulation tools. Second, we may have more potential predictors than appropriate for estimation, so ...
652 CitationsSource
#1Rajesh Chandy (LBS: London Business School)H-Index: 26
#2Kamalini Ramdas (LBS: London Business School)H-Index: 15
What next? Rajesh Chandy and Kamalini Ramdas look to the future role of mobile phones in changing the world and provide a blueprint for what needs to change to make this a reality.
2 CitationsSource
Cited By20
1 CitationsSource
#1Shahriar Akter (UOW: University of Wollongong)H-Index: 28
#2Grace McCarthy (UOW: University of Wollongong)H-Index: 14
Last. K.N. Shen (United Arab Emirates University)
view all 7 authors...
Abstract null null Data-driven innovation (DDI) gains its prominence due to its potential to transform innovation in the age of AI. Digital giants Amazon, Alibaba, Google, Apple, and Facebook, enjoy sustainable competitive advantages from DDI. However, little is known about algorithmic biases that may present in the DDI process, and result in unjust, unfair, or prejudicial data product developments. Thus, this guest editorial aims to explore the sources of algorithmic biases across the DDI proce...
5 CitationsSource
#1Shahriar AkterH-Index: 28
#2Afnan HossainH-Index: 5
Last. S. M. Riad ShamsH-Index: 12
view all 4 authors...
1 CitationsSource
Through recent leaps in application, artificial intelligence (AI) has become one of the most promising digital technologies, attracting significant attention from scholars and practitioners alike. Prior innovation research has mainly focused on the opportunities for and challenges to infusing digital technologies into the innovation process. However, understanding the general effects of digital technologies is insufficient as their specific fields of application differ. AI is distinct from other...
1 CitationsSource
#1Sergej von Janda (UMA: University of Mannheim)H-Index: 2
#2Sabine Kuester (UMA: University of Mannheim)H-Index: 12
Last. Monika C. Schuhmacher (University of Giessen)H-Index: 8
view all 3 authors...
Marketing capabilities are a major driver of competitive advantage across different business contexts. One of these capabilities is the ability to sense consumer needs and to develop innovations to...
#1Gema del Río Castro (UPM: Technical University of Madrid)H-Index: 1
#2María Camino González Fernández (UPM: Technical University of Madrid)H-Index: 1
Last. Ángel Uruburu Colsa (UPM: Technical University of Madrid)H-Index: 4
view all 3 authors...
Abstract The Sustainable Development Goals (SDGs) within the United Nations 2030 Agenda emerged in 2015, becoming an unprecedented global compass for navigating extant sustainability challenges. Nevertheless, it still represents a nascent field enduring uncertainties and complexities. In this regard, the interplay between digitalization and sustainability unfolds bright opportunities for shaping a greener economy and society, paving the way towards the SDGs. However, little evidence exists so fa...
17 CitationsSource
#1Anke JoubertH-Index: 3
#2Matthias MurawskiH-Index: 3
Last. Markus BickH-Index: 15
view all 3 authors...
The use of big data promises to drive economic growth and development and can therefore be a value-adding factor, but compared to private or public organisations, the country level is rarely investigated, and that is even more evident for developing countries. Another topic hardly ever considered in the big data research field is ‘big data readiness’, which means the level of preparation and willingness to exploit big data. We address these shortcomings in the literature and focus on the big dat...
2 CitationsSource
#1Francesco Paolo Appio (Skema Business School)H-Index: 11
#2Federico Frattini (Polytechnic University of Milan)H-Index: 38
Last. Paolo Neirotti (Polytechnic University of Turin)H-Index: 14
view all 4 authors...
6 CitationsSource
#1Venkatesh Shankar (A&M: Texas A&M University)H-Index: 58
#2Unnati Narang (A&M: Texas A&M University)H-Index: 3
Growth in emerging markets is critical as it leads global economic growth. Emerging market innovations, which we define as innovations created in an emerging market for use by consumers or customers in that market and possibly other markets, form the engine for such growth and continue to rise in importance for various stakeholders. These innovations fundamentally differ from developed market innovations, and impact consumers, firms, governments, and the society at large. Conceptual research on ...
9 CitationsSource
While extant literature showed a positive relationship between big data and firms’ competitive performance, there is still a general lack of understanding concerning the mechanisms through which bi...
1 CitationsSource