Measuring Social Networks' Effects on Agricultural Technology Adoption

By A. Maertens, Christopher B. Barrett. 2013

405 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Agricultural and Biological Sciences, Plant Science

View Paper: https://www.semanticscholar.org/paper/2e6696874a23a910c67343362242d004dfeb98c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Camilla Andersson
2. C. Chege
3. J. Bijman
4. G. Abebe
5. A. Royer
6. Y. Nakano
7. Takeshi Aida
8. Valerien Pede

In General Agricultural and Biological Sciences

1. M. Qaim
2. Camilla Andersson
3. C. Chege
4. J. Bijman
5. G. Abebe
6. A. Royer
7. Y. Nakano
8. Takeshi Aida

In Plant Science

1. G. Abebe
2. J. Bijman
3. M. Qaim
4. Camilla Andersson
5. A. Royer
6. Glenn Stone
7. Arjunan Subramanian
8. Elaine M. Liu

Citations in the corpus

• Are middlemen facilitators or barriers to improve smallholders' welfare in rural economies? Empirical evidence from Ethiopia (2016, background): “Middlemenmay solve market imperfections which are ubiquitous in developing countries (e.g. Maertens and Barrett, 2013), but theymay also take a relatively large share of the profit margin in the value chain and they may constrain upgrading opportunities for smallholder farmers (e.g. Lee et al.,…”
• Understanding the role of social capital in adoption decisions: An application to irrigation technology (2017, neutral): “Networks are positively related to irrigation technology adoption and adoption of scheduling (Maertens and Barrett, 2013; Venkatesh et al., 2012).”
• Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania (2018, background): “Maertens and Barrett (2012) also point out that ordinary farmers receive information from progressive farmers.”
• Leveling with friends: Social networks and Indian farmers' demand for a technology with heterogeneous benefits (2015, neutral): “While using the village as the relevant social network captures many if not all of a farmer's contacts, it also captures many that are not in the farmer's network (Babcock and Hartman, 2010; Maertens and Barrett, 2012).”
• Impacts of supermarkets on farm household nutrition in Kenya (2015, background): “On the other hand, previous research has shown that farmers observe what others are doing and are influenced by their social network when making innovation adoption decisions (Maertens and Barrett, 2013).”