Tryout and (Dis)adoption of conservation agriculture. Evidence from Western Madagascar

Razafimahatratra, Hanitriniaina Mamy; Bignebat, Celine; David-Benz, Hélène; Bélières, Jean-François; Penot, Éric

doi:10.1016/j.landusepol.2020.104929

Cited by 20 publications

(7 citation statements)

References 43 publications

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“…Evidence-informed guidance on the strategies to stimulate independent and socially transmitted adoption is emerging (e.g., Jagadish et al, 2021). In contrast, there is little systematic understanding of the drivers of conservation abandonment (Cook et al, 2024), particularly compared to other fields such as sustainable agriculture (e.g., Pedzisa et al, 2015;Razafimahatratra et al, 2021). Future research on this subject could help guide approaches to manage dropout detected when using our modeling framework.…”

Section: Study Considerations Limitations and Future Workmentioning

confidence: 99%

Forecasting adoption trends for adaptive management of conservation scaling

Clark,

Pienkowski,

Jagadish

et al. 2024

Preprint

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Achieving global climate, development, and biodiversity goals will require bringing conservation interventions to scale in suitable contexts and with appropriate timing. Practitioners and policymakers have a range of actions available to influence where, when, and by whom an initiative is adopted. Yet, to make effective management decisions, they must have a clear view of the current trajectory towards scaling goals. The non-linearity and variability of scaling processes has, however, hindered forecasting of adoption trends and environmental outcomes. Here, we adapt models of disease transmission to present a simple and flexible modeling structure for forecasting the adoption of conservation initiatives. We tested this framework on empirical adoption data from 19 distinct initiatives. Specifically, we fit the shape of the adoption timeline during the first half of each initiative, estimating the rates of independent uptake and social transmission up to that point. Forecasting the latter 50% of the timeline of cumulative adoption using just these two parameters resulted in an out-of-sample average error of 15.9% across all observations, indicating that this simple formulation captures much of the data-generating process. In one case, we included data on conservation abandonment, extending the cumulative adoption model to estimate the dropout rate and predicting net adoption with an average error of 19.6%, also indicative that this model captures the empirical process reasonably well. We caution against using such models for long-term forecasts, as they are sensitive to multiple assumptions, but instead advocate for their use in adaptive management. Iterative comparisons of forecasts allow users to retrospectively evaluate the impact of decisions and investments. When combined with estimates of environmental outcomes, our framework may provide a comprehensive modeling strategy for identifying targeted management actions and forecasting the impact of conservation projects while considering dynamic social processes.

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Section: Study Considerations Limitations and Future Workmentioning

confidence: 99%

Forecasting adoption trends for adaptive management of conservation scaling

Clark,

Pienkowski,

Jagadish

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Thus, the economic competitiveness of an intervention is highly intertwined with its likelihood of being adopted. Economic competitiveness here could relate to the cost of applying the practice relative to the farmers capability to meet those costs (Grabowski et al, 2016;Razafimahatratra et al, 2021) or the opportunity cost of transition. The capacity to meet these costs is linked to performance in terms of yield, ability of the RA practice to reduce crop losses from erratic rain (Grabowski et al, 2016) or pest and diseases (Simtowe & Mausch, 2019) or any parameter most useful to the targeted farmer.…”

Section: Economic Competitiveness and Performancementioning

confidence: 99%

Reply on RC1

Emenyu

2024

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“…However, getting farmers to adopt technologies successfully is not a "once and for all" victory of extension and technology dissemination programs. As shown in the literature, farmers often dis-adopt technologies after beginning to use them, and their reasons for doing so are not well understood (Chinseu et al, 2019;Lwiza et al, 2017;Razafimahatratra et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Understanding dis-adoption of technologies by smallholder dairy farmers in Indonesia

Akzar,

Peralta,

Umberger

2024

Int. Food Agribus. Manag. Rev.

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Farmer cooperatives represent a vertical coordination strategy aimed at reducing transaction costs and facilitating the adoption of technologies among farmers. In their roles, cooperatives undertake internal coordination of activities which may include enforcement measures, provision of quality inputs, internal control, and negotiation of favourable terms of exchange with buyers. However, limited attention has been given to understanding how cooperatives’ performance in the internal coordination of activities either promotes or hinders the continued adoption of agricultural technologies among cooperative members. We conducted a case study of the dairy sector in West Java, Indonesia, and utilised a mixed-method approach combining insight from dairy cooperative board members and dairy farming households. Our results suggest that the dis-adoption of dairy technologies is rooted in weak or non-existent monitoring and enforcement mechanisms to ensure input and output quality, the absence of price incentives, and inadequate provision of extension services. Furthermore, the lack of tight monitoring and control mechanisms reduces the cooperatives’ bargaining power with input providers and milk buyers. Unless these issues within the cooperatives are addressed, continued adoption of recommended dairy farming practices by smallholder farmers will not be sustained.

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Tryout and (Dis)adoption of conservation agriculture. Evidence from Western Madagascar

Cited by 20 publications

References 43 publications

Forecasting adoption trends for adaptive management of conservation scaling

Forecasting adoption trends for adaptive management of conservation scaling

Reply on RC1

Understanding dis-adoption of technologies by smallholder dairy farmers in Indonesia

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