The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve?

By M. Marra, D. Pannell, A. A. Ghadim. 2003

668 citations recorded by the source corpus.

Subfields: General Agricultural and Biological Sciences, Management Science and Operations Research, Soil Science

View Paper: https://www.semanticscholar.org/paper/c51c37f315fe43a6d6a4fb752143a018f0412bc2

How researchers see this paper

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

In General Agricultural and Biological Sciences

1. M. Qaim
2. R. Llewellyn
3. Elisabeth Fischer
4. David Zilberman
5. F. D'Emden
6. M. Burton
7. D. Pannell
8. Teresa Serra

In Management Science and Operations Research

1. L. Klerkx
2. A. Komarek
3. V. Smith
4. A. De Pinto
5. David Zilberman
6. Andrew Henley
7. L. Schechter
8. J. Gil

In Soil Science

1. M. Qaim
2. A. Komarek
3. V. Smith
4. A. De Pinto
5. A. Rose
6. Daniel Osgood
7. David Zilberman
8. B. Campbell

Citations in the corpus

• Linking Smallholders to Markets: Determinants and Impacts of Farmer Collective Action in Kenya (2012, background): “8 common approach to analyze innovation adoption under uncertainty (Feder et al. 1985; Marra et al. 2003).”
• Climate risk management and rural poverty reduction (2018, background): “These ex-ante, precautionary strategies include selection of less risky but less profitable crops and cultivars, shifting household labor to off-farm activities, and avoiding borrowing and investment in productive assets (including soil fertility) and improved production technology (Barrett et al., ”
• Factors influencing adoption of conservation tillage in Australian cropping regions (2008, background): “…are consistent with the role of information quality and learning in a framework of the role of risk, uncertainty and learning in adoption of agricultural technology outlined by Marra et al. (2003) and demonstrate the value of being able to observe use within the context of local farming systems.”
• Differential uncertainties and risk attitudes between conventional and organic producers: the case of Spanish arable crop farmers (2008, background): “The role of risk and risk aversion in the adoption and evaluation of innovations varies across technologies and has not been sufficiently ivestigated for some recent farming methods (Marra et al., 2003).”
• Facilitating Agricultural Technology Adoption Among the Poor: The Role of Service Delivery Through Mobile Phones (2012, neutral): “Wealthier farmers or those with off-farm income may be more willing to bear the financial risk in case the technology does not perform well (CIMMYT 1993; Kebede 1992 cited in Marra et al. 2003).”
• Information networks that generate economic value: a study on clusters of adopters of new or improved technologies and practices among oil palm growers in Mexico. (2015, background): “For future research, we thus suggest measuring the risk perception that the grower has in regards with his/her decision upon adopting or rejecting new or improved technologies or practices, especially in relation to how different clusters of growers may interpret the institutional environment as fav”
• Farm diversification, entrepreneurship and technology adoption : analysis of upland farmers in Wales (2017, background): “The capacity of farmers to capitalise on both farm diversi fi cation opportunities and grant-seeking activity may be supported or constrained by farmer attitudes, access, adoption costs, inertia and skills to use technology (Marra et al., 2003; Knowler and Bradshaw, 2007).”
• A review of types of risks in agriculture: What we know and what we need to know (2020, positive): “Our current study complements earlier reviews that have examined the theoretical models and empirical methods used to examine specific types of risk (Just, 2003; Just and Pope, 2003; Marra et al., 2003; Barrett et al., 2010; Chavas et al., 2010).”
• The Roles of Risk and Ambiguity in Technology Adoption (2014, methodology): “…utility model commonly used in technology adoption studies, farmers choose the technology that provides the highest expected utility conditional on their aversion to risk (Feder et al., 1985; Sunding and Zilberman, 2001; Isik and Khanna, 2003; Marra et al., 2003; Foster and Rosenzweig, 2010).”
• Impact of Bt cotton on pesticide poisoning in smallholder agriculture: A panel data analysis (2011, background): “Second, technology adoption is a learning process, so that farmers’ perceptions and behavior may also change, which is particularly true during the early stages of technological diffusion (Marra et al., 2003).”