Forum: "Using ICT to enable Agricultural Innovation Systems for smallholders" September, 2012
Question 4 (opens 26 Sept.)
11/09/2012
What evidence exists of smallholders using and/or benefiting from ICT-based advisory services?
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As pointed out in question 3, the private sector can point to user payment for a service as evidence that smallholders are using and/or benefiting from ICT-based advisory services.
What other types of evidence exist in your experience?
What factors most contribute to the effectiveness of such services?
What are the limitations and challenges?
Let us know what you think. Thank you in advance for sharing your ideas with us all!
Hi All,
Payment for ICT-enabled extension/advisory services can be an evidence for smallholders benefitting from the service. But we still need to investigate the nature of the payment for the service. How sustainable is the payment by the same group of farmers? Do one group of farmers pay this year and stop the following year? Do the service provider jump from one geographic area to another to demonstrate evidence for payment? Is the service provider using different models in a bid to keep payment record on paper? More of the so-called success stories that we have today are doing things of this sort.
But to add to the payment issue, I also think that scaling in terms of increased demand for service by farmers may be an evidence. This may apply to public-funded services that are free for users.
Ben
In response to: What factors other than fee payment indicate farmers benefit from ICT-based advisory services? Su Kahumbu of iCow sent this input via Twitter:
retention rates, feed back, user growth, growth across features
See the Twitter conversation here: https://twitter.com/SuKahumbu/status/250965582873255937
"Retention Rate" is the term I was describing in my post. Let's hear other factors from those implementing "sustainable" projects on the ground.
Ben
I'm not sure it's accurate to use retention rate as a reflection of impact especially if fees are subsidized as part of a non-profit model.
I'm not sure it's accurate to use retention rate as a reflection of impact especially if fees are subsidized as part of a non-profit model.
Farmers are enabled and well versed over technological inputs. They don’t have the magic power of fixing price for the harvested produce. Indian Government is providing minimum support price for the Non-perishable commodities like cereals, pulses, oil seeds, cotton and sugarcane.
The Tamil Nadu Agricultural University and The Centre for Development of Advanced Computing (C-DAC), Hyderabad initiated a project which provides real time price data on perishables covering Thirteen major markets in South India with 150 + commodities in an understandable manner through webpage (Daily price updation @ 1.00 pm) and through mobile phones to overcome the barrier of last mile connectivity (for information log in to www.tnau.ac.in and click dynamic market information).
On experimentation nearly 45151 farmers and 286 scientists are receiving the Mobile based text SMS on Market Wholesale Price Information in Free of Cost.
An on-line study was conducted among the farmers who are availing the SMS, it is inferred that most of the farmers are ready pay the nominal cost for market information. Further, they needs additional services like weather based crop advisories, pest and disease alert, voice SMS on new events and alters. It is also suggested that multimedia based mobile platform for instant and access by the smart phone users.
The problem here is the linguistic and many of the low end models are not supported by font and voice receiving facility.
As IKSL, Nokia Life tools, RML, m-Krishi are providing the demanded based farm information with charges both for pre-paid and post-paid format. Hence, a toll free mobile phone based agro advisory services with 24 x7 may offered with charge. This can be done by Agricultural Universities than Department of Agriculture of any state.
Gathering evidence and monitoring impact is very costly and difficult to do. How can you prove that an increase in revenues has come directly from market information and not from other factors or influences? It is very hard to prove definitely, as certainly other things will come into play. You also want to make sure that an impact study is done by an outside third party, so that the results are objective.
To that end, I wanted to share some results from a study of the French National Institute for National Research (INRA) released in December 2011. INRA found that smallholder farmers in Northern Ghana saw a 10% revenue increase receiving and then utilizing Esoko SMS market prices—the first study if its kind to prove impact.
Julie Subervie, the lead of the project, announced these findings in a presentation at the Market Information Systems Conference in Bamako. In the study, 600 smallholder farmers were comprehensively surveyed on their trading behaviors over the harvest cycles of 2008 and 2009. Half of those surveyed had been receiving market prices via SMS (with the going prices in wholesale markets across the country delivered weekly to their mobile) and half had not (as a control group), so the groups could be compared. This 10% increase comes from statistics around the selling prices of three commodities—maize, groundnut and cassava.
Traditionally, isolated rural farmers simply don’t know what their goods are worth in major markets, which allows traders to come in and offer incredibly low prices to buy their harvests. Armed with price information on their mobile phones, farmers could negotiate a better deal with confidence. In some cases, farmers were timing their goods to market better, and in some limited cases larger farmers were even paying for transport to send their goods to larger markets for sale where they could make more profit.
The impact of data delivered from mobile services on the trading patterns and behaviors of smallholder farmers has not been studied widely to date, but New York University is currently conducting another evaluation to assess the impact on farmers' livelohoods in Ghana. Updates to come in the next year . . .
I will do some more research to find other impact assessments I have read from India and other places to share with the forum.
Just to stay objective and present all the facts . . .
Unlike the study on Esoko in Ghana, this study by the University of Oxford Department of Economics estimates the benefits that Indian farmers derive from market and weather information delivered over SMS to their mobile phone by Reuters Market Light (RML), a commercial service. They conducted a controlled randomized experiment in 100 villages of Maharashtra. While some farmers who received information on their mobiles associated RML information with a number of decisions they have made, and there was some evidence that the information received affected spatial arbitrage and crop grading, the magnitude of these effects was small. The study showed there was no statistically significant average effect of the service on the price received by farmers, crop value added, crop losses resulting from rainstorms, or the likelihood of changing crop varieties and cultivation practices. In other words, this is the exact opposite of what was found in the study done on Esoko in Ghana. Check out this link to read the study: http://www.economics.ox.ac.uk/members/marcel.fafchamps/homepage/rml.pdfHi Laura,
Thanks for sharing the findings from the INRA study. I have a question about the control group- how did the study address the issue that those who received the market prices via SMS may have shared the information with others in the control group?
Finding a control group for impact evaluations of mobile services appears to be a challenging area when we consider the nature of mobile phones and how information can be shared so easily and quickly. Are methods such as Randomised Control Trials appropriate in this context?
Thanks, Victoria
Victoria,
Good question. I wish I could answer it, but the study was conducted by INRA, and I don't have access to how they performed their random sampling. However, I will be happy to provide you with a copy of the study and also to put you in touch with the project lead to give you more information.
From what I understand, the control group was in a different community from the group that was receiving market prices on their mobile phones, and members from the two groups do not know each other, nor were they part of the same association.
The important lesson that you highlight is if you are going to conduct an impact assessment, there should be certain rules established around sampling. Good points!
Feel free to follow up with me over email.
Laura
Laura ... Hallelujah! We train and supply farmers. Potentially they should be able to double to triple their yields but free will is a funny thing. A farmer has to implement what they have learned. And yes, where they choose to sell their final crop is also their decision. The same dynamics exist for mobile content. I know it may be irritating to hear but farming is done in the dirt so the simple transfer of knowledge to a farmer isn't enough to increase yields or income. If nothing else, we need to start teaching farmers gross margin models so that before they even prepare their fields they can manage not just production but the costs of production.
Completely agree that information and technology are just one piece of the pie . . . in any project ICTs compose approximately 5% of the solution, and the remaining 95% should be focused on deployment, in the dirt as you say.
Other than yield/income increase, user fee/ willingness to pay and scaling-up evidences...
are there any more evidences on ...
1. Time and Cost saving in availing advisory services
2. Farm Input(s) saving (eg. less pesticide usage...)
3. Socio-economic indicators etc.
Systematic and comprehensive impact studies/ evidences on ICTs for smallholder farmers are not available. Most of the sucees stories are anectodal.....however, some of the published documents indicated following.... -Digital Green project increased the adoption of certain agriculture practices SEVEN-FOLD over a classic extension approaches. Digital Green project was shown to be ten times more effective per dollar spent. Further, 85 per cent of adoption of improved technologies achieved as against 11 per cent of adoption by traditional extension methods. -e-Sagu project increased income of the farmers for the tune of INR. 3075 (63 USD) per ha and also reduced the pesticide usage. Further, their rudimentary estimate of economic advantage indicated that if the e-Sagu prototype used for 1000 farmers, overall net benefit with the proposed ICT based system is INR 100 Million (USD 204800). -e-Arik project report indicated the cost and time indicators comparing traditional extension system and e-Arik (e-agriculture) project, sixteen fold and three fold less time were required to the clientele availing and extension system delivering extension services, respectively. He further reported that 3.4 fold economic benefit as compared to the expenditure of deploying e-agriculture prototype. Interestingly, digital green also reported positive social side effects and other qualitative results of Digital Green project on participatory video for agricultural extension.
The information needs of small holders are quite different from large farmers. Most of the ICT-based advisory services are not taking care of their specific needs and hence unable to target and attract this segment of farmers. However, a few mobile based advisory services are found helping the small farmers to some extent.
Evidence from our ongoing research project “Dairy Extension Education and Services at Farmer’s Door through Mobile Extension Unit: An Action Research” at National Dairy Research Institute, Karnal, Haryana, India proves the extensive use of mobile phone technology to receive the problems and technology/service needs of dairy farmers and reach solutions to their doorstep using the Mobile Extension Unit. Moreover, the ICT facilities of the mobile unit are used to provide education at farmers’ doorstep.
We are receiving encouraging feedback on these ICT- based advisory services. As an outcome of the project, reduction in the intercalving interval of dairy animals by providing timely AI service on receiving the mobile call from farmers and improvement in productive and reproductive parameters could be achieved by reaching the unreached using ICTs.
There is a growing body of rigorous, quantitative, independent empirical research on the impact of various ICT-based advisory services on farmers’ welfare. While much of the early evidence was largely anecdotal, fortunately we are now in a world where there is some data detecting what works and what doesn’t. A few key studies, from across the globe, that immediately come to mind are:
From India: Rob Jensen has looked at the adoption of mobile phone by fishermen in south Indian state of Kerala (http://qje.oxfordjournals.org/content/122/3/879.abstract). I have looked at the impact of market information systems on prices received by soybean farmers in Madhya Pradesh (http://www.aeaweb.org/articles.php?doi=10.1257/app.2.3.22). Similarly, Fafchamps and Minten have looked at impact of SMS based market information systems on the choices that farmers make about where to buy and sell. There is evidence from Sub Saharan Africa: Muto and Yamano have looked at the impact of mobile phone usage by Ugandan farmers of maize and banana (http://ideas.repec.org/a/eee/wdevel/v37y2009i12p1887-1896.html), and Fafchamps and Aker have looked at mobile phone usage in Niger (http://www.economics.ox.ac.uk/members/marcel.fafchamps/homepage/mobiles). There is evidence emerging from Colombia and Peru as well (http://works.bepress.com/aparajita_goyal/23/).