Big Data and Smallholder Farmers: Big Data Applications in the Agri-Food Supply Chain in Developing Countries

The potential of big data (BD) applications in agriculture is attracting a growing interest from food and agribusiness industry players, researchers, and policy makers. Possible gains in agricultural productivity and supply chain efficiency from BD-based solutions can help address the challenge of doubling the food supply by 2050. Most of the research in this area evolves around commercial agricultural production in developed countries with relatively limited attention to BD-based solutions focused on smallholder farms in developing countries. This paper provides an overview of the existing and emerging technologies that can potentially enhance the big data application in the agribusiness value chain in developing countries, and presents a discussion of four successful cases of big data applications targeting smallholder producers. This paper also highlights drivers and barriers for smallholder-oriented applications in the agri-food supply chain in developing countries and discusses related implications for policy makers, private industry, and NGOs.


Editor(s):
IFAMR, IFAMA
Issue Date:
Jun 15 2016
Publication Type:
Journal Article
DOI and Other Identifiers:
(ISSN #: 1559-2448) (Other)
PURL Identifier:
http://purl.umn.edu/240705
Published in:
International Food and Agribusiness Management Review, Volume 19, Special Issue A
Page range:
173-190
Total Pages:
18
JEL Codes:
Q13; Q19
Note:
The IFAMR is published quarterly my IFAMA. For more information visit: www.ifama.org.
Series Statement:
Volume 19
Issue A




 Record created 2017-04-01, last modified 2017-08-19

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