The Adoption of Agricultural Technology - Food Security Group

I Chapter 1AdoptionStudiesWhy Study Adoption?There is no more distinctive feature of agriculture than its dynamism.Farming practices change continually. Farmers build on their ownexperience and that of their neighbors to refine the way they manage theircrops. Changes in natural conditions, resource availability, and marketdevelopment also present challenges and opportunities to which farmersrespond. In addition, farmers learn about new technologies from variousorganizations, programs, and projects dedicated to research, extension, orrural development. These organizations develop and promote newvarieties, inputs, and management practices. It is essential that suchorganizations be able to follow the results of their efforts and understandhow the technologies they promote fit into the complex pattern ofagricultural change in which all farmers participate.This manual is focused on one method for studying agricultural change. Itdescribes the design and management of farm surveys used to documentand explain farmers' adoption of agricultural technology. Too littleattention has been paid to this aspect of the process of agriculturaltechnology development. The aim of this manual is to help strengtheninstitutional capacity to carry out such adoption studies. This capacity isimportant for agricultural research organizations that develop innovationsfor farmers, extension institutions that promote new technology, varioustypes of rural development projects that introduce changes in agriculturaltechnology, and a range of non-governmental organizations (NGOs) andcommunity level efforts that are working to improve farming practices.There are several reasons to invest in studying the adoption of agriculturaltechnology. These include improving the effiCiency of technologygeneration, assessing the effectiveness of technology transfer,understanding the role of policy in the adoption of new technology, anddemonstrating the impact of investing in technology generation. Each ofthese is now discussed in more detail.MonitoringandfeedbackintechnologygenerationAny program that attempts to develop and promote improved farmingpractices should be able to assess progress and use that information tomake future actions more effective. One of the prinCipal incentives behindthe development of adaptive research methods such as farming systemsresearch (FSR) or on-farm research (OFR) was the criticism that muchagricultural research was being done on experiment stations, isolated fromthe fields, problems, and perspectives of client farmers. Many nationalagricultural research programs have now established location-specificadaptive research capacity that includes diagnostic surveys and on-farmexperimentation. But few of these organizations regularly monitor 1-

technology adoption to improve the efficiency of adaptive research. It isnot uncommon to find that a well-conceived program of agriculturalresearch and extension has been carried out for a number of years in agiven area but that none of the personnel involved can give any more thananecdotal evidence of changes that have taken place in farmers' practices,let alone the reasons for these changes. In many cases, the adaptiveresearch is in danger of straying far from farmers' needs unless researchershave a way of monitoring farmers' experience with the new technologiesbeing generated. For example, a new variety may have been tested onfarmers' fields and promoted by extension. But unless some sort ofmonitoring is carried out, researchers will not know the degree to whichthe variety is actually being used. In addition, it will be very helpful toknow what farmers see as the advantages of the new variety and what theyperceive as its drawbacks, in order to provide feedback to plant breedersfor refining their selection criteria.TheeffectivenessoftechnologytransferMost extension services are actively engaged in promoting newtechnologies with farmers. Resources are invested in various extensionactivities, such as field days or demonstrations, and the extension servicemay undergo considerable reorganization, such as with the training andvisit (T&V) system (Benor and Harrison 1977). But only infrequently areresources reserved for monitoring the outcome of these extension effortsand using the analysis to understand why some recommendations orextension techniques are more successful than others. For example, if theextension service is recommending a green manure crop, it will be veryuseful to know what proportion of farmers are using the new practice. Forthose farmers who have not adopted, do they find disadvantages with thenew practice, is the practice too far removed from farmers' knowledgebase, or has the extension methodology not been effective in acquaintingthese farmers with the new technique?Governments or donor agencies sponsor rural development projects inwhich the introduction of new agricultural technology plays an importantrole. Although these projects may represent a large investment of funds,the capacity to monitor progress is rarely a focus of project design. Forinstance, a development project may operate under certain assumptionsabout the possibility of improving tillage operations, and the effects thiswill have on yields and income. It is important to follow the degree towhich project participants are actually changing their tillage practices andidentifying any problems that have occurred.-2It is often difficult to draw a line between technology generation andtechnology transfer. An effective adaptive research effort should involveboth researchers and extension agents, for instance. There is growing

emphasis on participatory research as well, in which farmers assume moreresponsibility for the identification and dissemination of new technologies.One good example is the efforts of NGOs to improve agricultural practicesat the community level.Many of these projects are effective at identifying the priorities of farmersand enlisting widespread participation of community members toinvestigate and promote innovations. But these projects rarely go to thetrouble of documenting their results and assessing their progress to makefuture actions more effective. A project may generate considerableenthusiasm about the importance of improved crop storage, for instance,and several options may be available for farmers to try. But it is importantto follow up on the actual number of farmers who make a change, toanalyze which of the storage options they find most attractive, and tounderstand farmers' choices.Thus there is a widespread need to place additional emphasis onmonitoring the results of technology transfer and eliciting farmers'feedback. Organizations responsible for developing new technology needto know if the transfer process is functioning. Organizations responsible forpromoting technology need to know if their message is being heard. Andcommunity or regional development efforts need to judge to what extenttechnological change is contributing to their goals.The role of policy in technology adoptionMonitoring progress is necessary not only to improve the internal efficiency.of research and extension efforts, but also to improve the effectiveness ofinteractions with other institutions, partkularly those responsible forpolicy. Very often a research or extension effort falls well short of its goalsbecause of lack of coordination between institutions. Adoption studies mayshow the potential for technology diffusion by demonstrating progress inareas where institutional coordination is good, or may analyze theproblems in areas where technology diffusion has been slow.Adoption studies are also useful for illustrating the degree to whichacceptance of new technologies is limited by insufficient inputs, credit, ormarketing infrastructure. If it appears that farmers are unable to takeadvantage of a new technology because they lack inputs, this informationcan be presented to policymakers who have responsibility for theagricullural inputs that are available and the way they are distributed. If anadoption study shows that access to credit significantly influences the typeof technology that farmers use, then this information may be presented tothose responsible for designing and funding credit programs. Similarly,adoption studies may be used to highlight marketing bottlenecks that limitthe acceptability of new technologies.-3

Effective communication between researchers and policymakers is not verycommon. It will take more than a few adoption studies to establish goodlinks among researchers, extension personnel, national policymakers, andpublic interest groups. But the information from a well-conceived andeffectively presented adoption study can be very useful for improving thistype of communication._Measuringtheimpact oftechnologygenerationandtransferAnother important use of the information from adoption studies is to assessthe impact of agricultural ..esearch and extension and to measure thereturns to investments in these activities. Research and extensioninstitutions are often engaged in a battle to maintain their budgets, and thisimplies the necessity for demonstrating results. Adoption studies are animportant tool for measuring and assessing impact. They also prOVide datathat can be used to estimate the returns to investment in research orextension. Such an analysis may be used to justify further investment inthese sectors or to help identify the most productive opportunities forinvestment within research or extension.An important question on the minds of policymakers is who benefits fromnew technology. Adoption studies may be designed to document whatkinds of farmers and what areas of the country have profited most from thedevelopment of a particular technology.-4_The evaluation of impact and returns to investment is also a commonfeature of rural development projects, but these evaluations are often donewithout access to solid data on adoption. Even NGO projects need to spendmore time documenting progress and analyzing the effectiveness of theirinvestments. As more donor attention is directed to the option of NGOcontributions to agricultural change, these organizations will come underincreasing pressure to present wel\-documented evidence of theiraccomplishments.Contributingto theliterature onadoptionThere is a very large body of literature on the adoption of agriculturalinnovations (Rogers 1983; Feder, Just, and Zilberman 1985). The methodsdescribed in this manual can add to that literature, although their principalpurpose is to serve institutions involved in promoting agricultural changerather than to contribute to the theory of adoption. Many academic studieson adoption assume that the technology is appropriate and tend toconcentrate on identifying the characteristics of farmers who are likely toadopt. The kind of study described in this manual faces the more difficultchal\enge of not only describing patterns of adoption but alsounderstanding whether or not the technology and its institutionalenvironment are adequate to the needs and resources of farmers. This type

of adoption study must be done with an open mind; its purpose is not topromote a particular technology but rather to help research and extensionbe more effective in responding to farmers' needs.The follOWing chapters are concerned with adoption studies that helpdescribe, evaluate, and understand the process of technological change. Itis assumed that the principal audience for the studies will be staff ofresearch and extension institutions (public or private), and of otherinstitutions at the national level that are responsible for assessing or settingpolicies and allocating funds that determine the scope and direction ofagricultural development.Ways of Studying AdoptionThe process ofagricultural researchAlthough this manual focuses on the design and analysis of formaladoption surveys, it would be misleading to think of adoption assomething that is the subject of a Single study conducted at the end of aresearch effort. Monitoring changes in farming practices and assessing theadoption of new technology should be important elements of the entireresearch process.When a program of research or extension is being planned, it is essential toget a dear idea of what type of changes or technologies would beacceptable to farmers. Diagnostic surveys proVide information on farmers'current practices and concerns (Byerlee, Collinson, et al. 1980). To theextent that these surveys assess the distribution and rationale for farmers'present use of technology, they can be thought of as "adoption studies" forprevious technology generation efforts. Information from such surveys andfrom other sources needs to be carefully considered in planning a researchagenda (Tripp and Woolley 1989), and a growing number of techniques areavailable for imprOVing farmer and community participation in theplanning process (Farrington and Martin 1988).As research is carried out, and especially as experiments are planted infarmers' fields, it is essential to obtain continuous feedback from farmers. Itis a waste of resources to conduct several years of research on a technologyonly to discover that farmers find it unaq:eptable. There are several waysof monitoring on-farm experiments. One basic strategy is Simply to makesure that farmers are consulted when researchers or extension agents visitfield sites and that farmers' opinions are recorded and analyzed (Tripp1982). Other techniques are available for ensuring that farmers participatein the evaluation of technologies being tested. Guidelines have beendesigned to help elicit and utilize farmers' reactions to experimental-5

treatments (Ashby 1990) (see Box 1 at the end of this chapter). Farmergroups have also been helpful in planning and monitoring on-farmexperiments (Norman et al. 1988).MethodsforassessingadoptionAlthough constant monitoring of farmers' opinions and experience isessential during the design and testing of agricultural technology, it is alsonecessary to carry out some sort of assessment after a new technology hasbeen recommended or introduced. The type and the timing of theassessment will depend on the purposes of the study.This manual describes the design and analysis of formal surveyinstruments for assessing the adoption of agricultural technology. A formalsurvey of technology adoption is one of several kinds of studies that can bedone to assess adoption (Box 2). As mentioned in the previous section, it isimportant to have a continual interchange between farmers and researchersas technology is being developed and tested, and this interaction prOVidesthe first indication of whether or not a new technology is acceptable.Another way of assessing a technology's acceptability is by follOWing up onwhat farmers who have hosted experiments do the follOWing year.Once a technology has been released or an extension program has beeninitiated, it is possible to study a random sample of farmers to analyze thedegree of adoption. An informal survey (similar to the informal diagnosticsurveys used to help set priorities for a research program) is very useful forproViding researchers with preliminary feedback about the acceptability ofa technology. It can also prOVide information about policy-related problemsthat may imped~ the spread of a technology. An informal survey may besufficient for analyzing adoption patterns, but more often the type offormal survey described in this manual is necessary. Formal surveysgenerate quantitative information that is useful to decision makers and arebetter able to explore some of the complex issues in understandingvariability in adoption among farmers. But it is assumed that such a surveywill be carried out as part of a research or extension effort that has beenwell planned and executed and has included various opportunities forassessing farmers' opinions and practices along the way. It is also assumedthat the design of the questionnaire is preceded by a good informal surveythat helps researchers identify key issues to be pursued in thequestionnaire.-6The results of a formal adoption study can be combined with other data onchanges in farm production, farm incomes, or consumer gains to develop amore complete impact study. There are also other wa):'s of studying thespread of a new technology. Data from an agricultural census may proVide

-7some idea of the degree to which farmers use a particular technology. If anew technology involves purchased inputs, for instance, surveys of inputmerchants may be useful for assessing the spread of the technology.SummaryAll institutions that are involved in generating agricultural technologyshould have the capacity to carry out studies that document the degree ofadoption and help explain the rationale for farmers' decisions. Adoptionstudies can be useful for several purposes, and a decision about theaudience for the study must be taken before the study is designed.The information from an adoption study can be used to:1) provide feedback from farmers that is helpful in refining thetechnology generation effort;2) assess the effectiveness of a technology transfer strategy;:\)improve the flow of information between research and extension, onthe one hand, and policymakers, on the other; and4) document the impact of a technology generation or extension effort.This manual describes the design of formal surveys for studying adoption.A formal survey is a particularly useful method, but it must be seen as partof a wider range of activities that are used to make technology generationas efficient and as responsive to farmers' needs as possible.After defining the audience for an adoption study, the next step is tocarefully define what changes are going to be measured. The followingchapter describes various factors related to measuring adoption.

Box 1. Interview Form for Farmer Evalua on of E perlmental T eaCassavaVarieties Open EvaluationVariety G"'---....;.'7....;:8_6 _ Farmer __--=L:...::.U_/5=--B_[_TA_N-----'CO_U_R_T _Farmer's CommentsHAS HIGH 5TAR.CH, NOT "WATER'~ "DRY'~ IS "FLOURY". 7"J.lE "SKIN" IS WI-IITE, AND FLESI-I"CREAMY", A DISADVANTAGE BECAUSE PINK SK.IN IS GETTING A 8ETTER. MAJ

80 2. tudl Used to Assess Different Aspects of AdoptionsampleType of study nming slzea PurposeMonitoring farmers'opinions of technology;farmer participation inexperimental design-During experimentalprogram10-20Refine research objectivesto meet needs andconditions of farmersFollow-up on acceptabilitywith farmers whohave participated inexperiments (individualor group interviews)1-2 yearsafter experimentalprogram10-20See if farmers keep usingtechnology. Identify whetherthere are problems with itscontinued use.Informal survey oftechnology adoption2-4 years afterrelease of technologyand/or initiation ofextension program20-40Provide feedback to researcherson feasibility of technologyand feedback to policymakerson accessibility of technology.The study is a necessary stepfor designing a formal survey.Formal survey oftechnology adoption2-4 years afterrelease of technologyand/or initiation ofextension program6~120Provide feedback toresearchers, information forpolicymakers. Contribute toimpact assessment.Impact study2-5 years afterrelease of technologyand/or initiation ofextension program60-120Combine data on adoptionfrom formal survey withestimates of yield/incomegains and estimates of researchand/or extension program costs.Studies of technologyuse based on secondarydata (e.g., agriculturalcensuses)2-4 years afterrelease of technologyand/or initiation ofextension programn.a.Use secondary data (such asagricultural census) toassess spread of newtechnology.Interviews with inputsuppliers (e.g., seedsales agents)2-4 years afterrelease of technologyand/or initiation ofextension program5-20Estimate demand for technology.Detect bottlenecks in inputsupply system.Source: This table borrows from a similar one developed by W. Janssen for training courses at CIAT.a These sample sizes are only suggestive and may vary outside the ranges listed here, depending on thepurpose of the survey and the proposed analysis.n.a. = not applicable.9

Chapter 2MeasuringAdoptionDefining AdoptionOne of the most important issues in designing an adoption study is thedefinition of criteria for adoption. [f we are interested in the diffusion of anew variety, for instance, what constitutes adoption? Are farmers whoplant even a few rows of the new variety considered adopters, or do theyhave to plant a certain minim um proportion of their fields with the newvariety? If we are interested in the adoption of crop management pra tices,how closely does the farmer have to follow a recommendation b fore beingconsidered an adopter? Is any fertilizer use to be counted as adoption, forinstance, or does the rate and timing of application have to fall withincertain limits?Although these may seem to be definitions that can be decided after thesurvey is completed, they need to be discussed beforehand because theycan influence the sorts of questions asked to the farmer. An example ofdefinitions of adoption for a survey that examined changes in weed control,planting practices, and tillage is shown in Box 3 at the end of this chapter.In defining the criteria for adoption, it is also important to remember thatalthough recommendations may be presented to farmers as a package ofsev raj practices, some components of the package may be adopted first,others may be adopted later, and some may never find Widespreadacceptance. The adoption study should therefore ask specifically abouteach component of the package, bearing in mind that individualcomponents may be adopted at different times or under differentconditions.In many cases a survey will examine technologi al change in circumstanceswhere farmers have several options from which to choose. For instance, theobjective of an extension program may be to acquaint farmers with theprinCiples of erosion control. Farmers may be able to take advantage ofseveral appropriate crop management practices, and the survey shouldexplore which ones farmers are using and the rationale for their choices.Similarly, farmers may make their own modifications to a new technology(such as a storage technique or a piece of machinery), and an adoptionstudy needs to pay careful attention to this type of farmer innovation.-10The adoption of a new technology may have implications for the rest of thefarming system, and these attendant changes may be examined in anadoption study. Researchers will be pleased to see the Widespreadadoption of a new variety, for instance, but what effects does this changehave on the use of other varieties and the genetic diversity in farmers'fields? In other cases the adoption of a new' variety may bring aboutsignificant changes in other management practices. An example is shown inBox4.

Another issue in measuring adoption is the fact that farmers often haveseveral fields that may be subject to different management practices.Researchers need to decide whether to assess adoption on all fields or onlythe largest field, or on fields that have characteristics relevant to the newtechnology (e.g., examining soil conservation practices only on slopingfields). The answer to this question depends in part on whether it isnecessary to estimate the total area where a particular technology is in use.If, for instance, researchers wish to estimate the proportion of crop area in agiven region planted to improved varieties, then either all fields should beincluded in the survey, or fields rather than farmers should be randomlysampled. Asking farmers to estimate total area planted to differentvarieties is usually not difficult, but if the practice under investigation ismore complex, such as the rate and timing of fertilizer application, thenestimating the range and average for these practices will be more timeconsuming. If the average rate of input application is reported in thesurvey analysis, it should be clearly stated if the rates are only for thosefarmers who use the input, or are the average across users and non-users.Investigating practices by individual field also has other advantages. Oneof the important ways of explaining differences in adoption behaviorbetween farmers is to look at related aspects of crop management. It maybe hypothesized that a particular weed control practice is used only inintercropped fields, for instance. This hypothesis on adoption can be testedonly with field-specific information.Sometimes there is more than one agricultural season per year. In this case,adoption may be assessed for only the most important season or for allseasons (Box 5).'In summary, the adoption of a new technology can be defined in severalways. In all cases, the definition of "adoption" needs to be agreed upon.Sometimes it may be sufficient Simply to report on the proportion offarmers using the technology (at some defined level). In other cases, theactual proportion of fields or crop area under the new technology will needto be estimated. An example of several ways of reporting these results issho\Yn in Box 6.Describing Adoption: The Logistic CurveMany adoption studies go beyond an analysis of current practices andattempt to document adoption history. lnformation about past seasonsrequires more time to obtain, but can be very useful. Ideally, informationon past practices and adoption history would come from baseline surveys,but such information is often not available.11

Not all adoption studies will want to analyze historical change, but suchanalysis can be useful for several purposes. It may help project futuredemand for inputs, determine whether extension needs to be strengthened,or quantify the change in the number or technology users over time toassess impact.It is useful to distinguish between adoption, which is measured at onepoint in time, and diffusion, which is the spread of a new technology acrossa population over time (Thirtle and Ruttan 19R7). Much of the literature ondiffusion assumes that the cumulative proportion of adoption follows anS-shaped curve in which there is slow initial growth in the use of the newtechnology, rollowed by a more rapid increase and then a slowing down asthe cumulative proportion of adoption approaches its maximum (whichmay be well below 100% of the farmers).The most common function used to portray the curve is the logisticfunction. For technology adoption, the y-axis represents the proportion offarmers or area adopting a technology and the x-axis represents time.KCumulativeadoptionTimeThis curve can be described mathematically:Yt = K / (I + e -s-bt),where:Y t= the cumulative percentage of adopters or area at atime t;K = the upper bound of adoption;b = a constant, related to the rate of adoption; anda = a constant, related to the time when adoption begins.12If we have sufficient observations on Y t, we can estimate the threeunknown parameters K, a, and b with a non-linear regression. For practicalpurposes, however, this very difficult technique can be replaced with anordinary least squares regression if we have at least three observations on

Yt and we can estimate K (the maximum adoption expected)independenlly. In this case, we note that the equation of the logistic curvecan be transformed to:Y tIn (--) =a + bt .K - Y tSimple ordinary least squares regression of the transformed variableIn [Y t/ (K - Y t)] on a constant and time wiII then yield estimates of a and b(Griliches 1957). This kind of calculation is easy to do with manyspreadsheet packages. One could also fit a curve without regression withonly two observations, although the information from only a fewobservations is likely to be limited (see below).There are several methods of estimating K. The first is simply to plot thedata and to choose the level that appears to be the upper bound ofadoption. A second method is to run the regression using different valuesof K and choose the one that maximizes R 2 • (This is also readilyaccomplished with most spreadsheets. It should be noted that in general, R 2and t-statistics from these regressions have no statistical meaning. Thistechnique only helps to choose K to get a fairly close fit to the data.) Toreduce the time spent selecting K, a combination of Simple plotting andexperimental regressions might be used.Although the logistic curve is the most common way of representingtechnology diffusion, it is well to remember that it is based on certainassumptions about diffusion, and that t~e fixed parameters estimated forthe curve imply that the relevant price ratios, infrastructure, and thetechnology itself have remained constant over the period when the curve isfitted. An example of a logistic curve is shown in Box 7.Time FrameIt is also important to remember that not only is the diffusion of a newpractice among farmers a gradual process, but that individual farmertesting of technology may follow the same type of curve. If possible, afarmer wiII test a new technology on a small part of the farm, and if theresults are positive wiII gradually increase the use of the technology. Box 8shows this process for a new variety.If an adoption study examines a number of different practices, whether ornot they have been presented to farmers as a technological package, it isimportant to consider the relationships among the adoption patterns. Insome cases, different elements may be adopted independently, while inother cases there may be a sequential adoption pattern, as shown in the13

example in Box 7. Sometimes certain elements wi1llikely be adoptedtogether, either because of biological complementarities between them orbecause farmers are provided incentives (e.g., a credit package).Although it is important to remember that actual diffusion patterns maynot follow the smooth theoretical curves, historical data on adoptionprovide valuable information about trends and prospects for a newtechnology. These data allow one to see when adoption began and to judgethe degree to which research or extension programs were in factresponsible for the introduction or spread of the technology. Thisinformation also allows for an estimate of the rate of adoption andpredictions about future progress.One problem with these estimates, however, is that they assumecumulative adoption - that is, once a farmer begins using the technology,he or she will keep using it. In some cases this is not correct, and manyfarmers may have one or more years of experience with the technologyonly to have subsequently abandoned it. One way of investigating thisphenomenon is to compare current use with past use (Box 9). It may be thata significant proportion of farmers has experience with the technology butvery few currently use it. If this is the case, it is worth trying to getinformation on why farmers have stopped using the technology. Thiscomparison between past and current use is relatively straightforward.More detailed information on historical patterns of adoption, use, anddisadoption requires questioning on year-by-year use of a technology,which is often quite difficult.Besides looking at past patterns of adoption, it is sometimes tempting to tryto assess future trends by asking farmers their plans for using a technologythe following year. Although it is often valuable to obtain farmers' opinionsabout the feasibility of using a technology and identifying what itsattractions and drawbacks might be, this information cannot be used toassess adoption. Statements about what a farmer would like to do, isinterested in, or hopes to do, are not substitutes for data on actualtechnology adoption.-14The adoption literature also refers to differences between early and lateadopters (Rogers 191B). In the case of technologies that depend onpurchased inputs, for instance, the first farmers to adopt a new technologymay be larger-scale farmers or those with more resources or capacity toexperiment with new practices. In some cases a technology may beappropriate only for this type of farmer and does not diffuse any further. Inother cases farmers who have fewer rc>sources also adopt the technology, orit may he that the technology is in fact more appropriate for these farmers.In any casc>, it may bl' important to draw a distinction between earliness ofadoption and the currc>nt degrc>e of adoption (Box 10).

Measuring ImpactEarlier sections discussed ways of estimating the degree of adoption of anew technology. These included measures of the proportion of farmers,cropped area, or harvest. If the adoption study has been done to helpprovide some measure of the impact or importance of the research orextension effort, it will be helpful to convert these figures so that the actualamount or value of the increased production (or other benefits) resultingfrom adoption can be estimated. This may require some additionalquestions on the survey, as well as complementary information.If the benefits of the new technology are largely expressed as increasedyield, the first step is to estimate yield changes due to adoption. There areseveral ways of doing this. The adoption survey itself may be a source ofyield data. Farmers may be asked to estimate their yields from particularfields, or crop cuts may be taken as part of the survey. Reliable yieldestimates, either by farmers' reports or by crop cuts, are not particularlyeasy to obtain, however, and the reader is referred to Poate and Casley(1985) for advice on appropriate methods. Even if good yield estimates areobtained from the survey, it will be difficult to find farmers who managecomparable fields in which the only difference is the adoption of thetechnology under study, or to find comparable farmers who use and do notuse the technology, to provide firm estimates of yield differences that canbe attributed to adoption. Year-to-year variations caused by climatic factorsmake it very dirficult to use data from the same farmer across several yearsto estimate yield changes due to technological change.A better way of obtaining data on yield differences that have occurredbecause of the new technology is through experimental data. If therecommendations have been derived from on-farm experiments, then yieldestimates should be available comparing farmers' practice with the newpractice. Caution must be exercised in using experimental data, however,to ensure that the yield estimates for the new technology were obtainedunder typical farmers' management, rather than researchers' management.Comparisons between new and traditional technology under researchers'management often give misleading results.Once the yield difference has been estimated, it is possible to assign a valueto the increased yield and calculate the total value of increased productionresulting from adoption in the study area. The simplpst approach is toassume that Widespread adoption has not affected prices, but when this isnot the case, price effects must be accounted for. If a diffusion curve hasbeen calculated, this can be used to estimate the strpam of belwfits OVNtime. This fir,ure will providp some idpa of the valup of the product of the-15

esearch effort. It may also be important to obtain an estimate of theincreased income for farmers who have adopted the new technology. Suchan estimate will require good data on the variable costs of the technology.Estimates of the benefits of a new technology should be balanced againstpOSSible costs implied by changes in other parts of the farming system (forexample, if a new technology leads to a change from intercropping tomonocropping). The long-term sustainability of a new practice may alsoneed to be examined when considering costs and benefits.If the research program has been planned carefully, with due attention todeveloping technologies appropriate for specific groups of farmers("recommendation domains"), then the adoption study may hold fewsurprises regarding the distribution of the technology. But oftenunexpected or unexplored factors influence the actual distribution of a newtechnology or of its benefits. Although the "average" impact in terms ofyield or income gains may be impressive, which farmers are able to takeadvantage of the change? Are many excluded from using the newtechnology? Answers to these questions may be sought by ensuring thatthe adoption survey covers a wide range of farmers, placing specialemphasis on the resources available to farmers. Thus the survey shouldseek to assess the experiences of larger- and smaller-scale farmers, thosewho have access to credit and those who do not, and so forth. These factorsare discussed in more detail in Chapter 3.More complex questions may also be asked about the distributionalimpacts of a new technology. Not only is it important to understand how anew technology is used by different types of farmers, it is also important tosee how the benefits of the technology are distributed among varioussectors of the population. Is it farmers or consumers who gain most? Tn thefarming sector, how is the extra income divided among landowners,tenants, and laborers? Do male farmers gain at the expense of femalefarmers? Does the technology increase or decrease the demand for labor,and how does that affect the incomes of the poorest sectors of thepopulation? An example of this kind of analysis is shown in Box 11. Theanswers to most of these questions go beyond the basic adoption studydescribed in this manual, but such adoption studies are a necessary part ofresearch on the distributional impacts of technological change. Furtherdiscussion of these issues can be found in Barker, Herdt, and Rose (1985,Chapter 10) and Lipton with Longhurst (1989).-16

-17The Role of Adoption Studies in Assessingthe Returns to Research and ExtensionOne of the reasons for doing an adoption study is to provide evidence ofthe returns to a research or extension effort. This analysis is done bycomparing the investment in the technology development effort to thevalue of the results, measured in terms of yield or income gains. Althoughthis manual does not pretend to provide guidance for this complex type ofstudy, it should be obvious that the results of a good adoption study are anessential element for a benefit-cost analysis of an agricultural technologygeneration program.If the adoption study is to be used for this purpose, it is quite likely thatadditional information, beyond the degree and distribution of adoption,will be needed. Tn particular, the survey will need to collect evidence thatallows the change in technology to be attributed clearly to the research orextension program under examination. The information required includesevidence of the similarity between the farmers' new practice and therecommended technology, assurance that farmer adoption took place afterthe recommendations became available, and evidence that the informationutilized by farmers had its origin in the research or extension program. Ifthe only change being examined is the adoption of a new crop variety, thenit is usually easy to collect this information and attribute the change to aparticular research program. But obtaining similar information for cropmanagement practices may be considerably more difficult (Box 12).In some cases it will be necessary to distinguish between returns toresearch and returns to extension. If a study is to estimate the returns toone or the other of these activities, particular care must be taken inseparating the two, and in examining to what extent research andextension are substitutes or complements. Assessing the returns toextension programs is quite challenging; a review of recent literature andadvice on the organization of such studies can be found in Birkhaeuser,Evenson, and Feder (1991).Once the extent and value of the technological change has beendocumented and it is possible to attribute a definite proportion of thischange to the research or extension program, the benefits of this change arecompared to the costs of that program. A standard reference for benefitcostanalysis is Gittinger (1982), and a review of methods for evaluating thereturns to agricultural research is presented by Norton and Davis (1981).

SummaryIn designing an adoption study, care must be taken to define preciselywhat technologies are being considered. It is likely that changes in farmers'practices will represent a combination of farmer adaptations to newtechnology, farmer innovation, as well as other changes external to thetechnology generation effort.Decisions must also be taken regarding how to measure adoption. Is theobjective to see if farmers are using a practice on any part of their farms, oris it necessary to quantify the area planted or to measure the proportion ofyield produced with the new practice?What time frame is of interest? Is the objective to assess adoption in thecurrent year, to try to establish a history of first use, to explore thediffusion process, or to examine patterns of continued use or abandonmentof technology?If the objective is to help assess impact, the study needs to be able todemonstrate a connection between changes in farmers' practices and theresearch, extension, or community development effort. The survey shoulddevelop information that establishes a causal link. The survey may alsoneed to proVide evidence regarding the adoption of the technology amongdifferent classes of farmers, in order to further analyze impact. The surveymay also prOVide an opportunity to develop some of the additionalinformation necessary for assessing impact, such as yield or incomechanges, as well, as evidence of other changes attendant on the newtechnology, such as changes in labor patterns or land use.Besides clearly defining and documenting the degree to which farmershave changed their practices, an adoption study is also useful forunderstanding the rationale behind these changes. The follOWing chapterexamines some of the factors that help us to understand adoption patterns.-18

Bo 3. Variable and Criteria __'_."Con Plantln ~actlces~For each of three technological alternatives in a maize on-farm research program in Panama, a series ofacceptance criteria were defined. These criteria allow for a range of definitions of adoption (e.g., it ispossIble to distinguish those farmers that have adopted the herbicide only from those that use theherbIcide at the recommended time and rate).Technological DlscrI....lnant AcceptancealternativevariablesChemical 1. Chemical weed control 1. If the farmer uses chemicalweed controlweed control2. Type of product 2. If the farmer usesGesaprim or Gramoxone3. Application time 3. i) Gesaprim: 0-5 daysafter plantingii) Gramoxone: 0-35 daysafter planting4. Application rate 4. i) Gesaprim 1-3 kg/haii) Gramoxone 1-3 It/haSpacing 1. Planting arrangement 1. If planting is done in rowsarrangementand density2. Density 2. 45,000 - 60,000 plants/haZero tillage 1. Tillage system 1. If the farmer does not usemechanical tillage2. Application of herbicides 2. If the farmer appliesherbicides prior to plantingSource: Martinez and Sain (1983).-19

In some cases, the adoption of a new technology leads to other changes in the farming system. If thesechanges are of interest to researchers, they can be analyzed in an adoption study. The example belowshows that many farmers in Peru who adopted a new bean variety also changed some of theirmanagement practices because of the new variety's characteristics.Percentage of farmers who changed their crop management after adopting the bean variety"Gloriabamba," PerucPlant seed less deeply 24 o 30Reduce planting distance 16 o oIncrease fungicide use 2 6 24Increase fertilizer use 7 6 24Change from broadcast to row planting 1 36 18Plant beans closer to maize in intercrop 6 36 oChange to monocrop beans o 3 6Source: Adapted from Table 15, Ruiz de Londono and Janssen (1990).-20

Farmers in Bumbogo, Rwanda grow beans during two seasons. Researchers were interested in assessingthe degree to which farmers had switched from bush beans to climbing beans. The data below show thatthe relative importance of improved climbing beans is considerably higher in the long rainy season,where they account for one-quarter of the bean area and half of the bean production.Adoption of different bean types in the short and long rainy seasons, RwandaInyseuon Long Y88880nBeen~tIoUIIhOld) (%)(k8f(%)(f)IIhoIiIehoTd) (%)(kgfhOUIibold) (%)Local bush beans .28Improved climbing beans .05Local climbing beans .05(74)(13)(14)1667752(56) .07(26) .03(18) .03(54)(25)(21 )23 (27)42 (49)21 (25)Total .38 (100) 295 (100) .13 (100) 86 (100)Source: Sperling et al. (1992).21

A survey in three regions of Malawi examined the adoption of hybrid maize. Questions were askedabout varietal use on each field that the farmer managed.It was possible to calculate several estimates of hybrid adoption. Not only does adoption vary by region,but the different estimates provide a complex picture of hybrid adoption. Only 12% of total maize area isin hybrids, although 27% of farmers grow some hybrid maize. But despite these relatively low figures,35% of total maize production comes from hybrid maize.Adoption of different maize types by farmers in three areas of MalawiPercent farmers growingLocal maizeHybrid maizeOther maize97148993311973814982710Percent aggregate maize areaLocal maizeHybrid maizeOther maize9162841337422485123Percent aggregate maize outputHybrid maize 18 44 47 35Source: Smale et al. (1991).-22

-23The following graph shows the actual adoption history and fitted logistic curvesfor three technologies (variety, fertilizer, and weed control) that were presented tobarley farmers in Mexico as a package but had independent adoption patterns.Farmers tended to adopt the variety first, then improved weed control, and finallyfertilizer.10080W0'>-0~wc­wa.0 0.... -060 ­Wella.w cn.....;::>W Eell .... 40-ell~-E­~o()200 I1956 60 64 68 72 76 80Logistic curves for the adoption of three technological components in thewet zone, Central Mexico.Source: Byerlee and Hesse de Polanco (1986).

A survey in Peru that examined the adoption of a new bean variety asked farmershow much of their farms they planted to the new variety in the first year that theyused it and in subsequent years. The results show a gradual increase in the use ofthe variety as farmers gain confidence.Use of bean variety Gloriabamba. by province, PeruFirst season 0.11 0.28 0.13Second season 0.24 0.40 0.40Third season 0.43 0.57 0.50Fourth season 0.43 1.06 0.83Source: Ruiz de Londono and Janssen (1990).-24

-25One valuable contribution to assessing adoption patterns is to compare theproportion of farmers who have ever USE'd a technology with the proportioncurrently using it. If the latter is much lower than the former, there is an indicationthat although farmers have tried the technology they have encountered difficultieswith it.The following example comes from Nepal and shows that different types offarmers have very different experiences with respect to improved maize varieties.The majority of large commercial farmers have tried these varieties and continueto use them. Almost half of small commercial farmers have also tried thesevarieties, but only a small proportion continue to use them. Some part-time andsubsistence farmers have also tried the varieties, but almost none currently usethem.Current and past use of improved maize varieties by type of farm, NepalLarge commercial 54 60Small commercial 13 45Part time 4 21Subsistence 3 26Source: Ashby (1982).

nee beitwe4m Ea Iy d ptlo andThe farmers who adopt a technology first are not always the ones who find It mostuseful. The following example from Nepal shows that although larger farmerswere the first to adopt improved (high yielding) vaneties (HYVs) of rice, it is thesmaller farmers who have the highest current usage.Adoption of improved rice varieties (HYVs) by farm type, NepalAverage years Percent ofalnceflrstrice land sownFarm type use of HYV rice toHYVrioeLarge commercial 8.3 31Small commercial 7.6 60Part-time 5.1 72Subsistence 5.8 66Source: Ashby (1982).-26

80 1A study of mechanical wheat harvesting in Pakistan examined the advantages of the new harvestingmethod for farm owners in terms of time saved, ability to plant the following crop earlier, and yields.Although mechanical harvesting was not a practice recommended by the research service, it wasspreading, and researchers wished to study the implications. The following figures show substantialadvantages for farmers.Farmers' estimates of differences in supervision time, harvest duration, and yields for harvestingby hand and with a combine, Pakistan ah8t'Y88llng methodItem Un CombineSupervision (mean) h/day 10.4 2.7Harvest duration (mean) days 23.0 2.4Time available to preparefor next crop (mean) days 9.1 29.4Yield (grain recovery) (mean) Vacre 2.5 2.8Source: Smale (1987).a Holding Input levels, vanety, and harvested area constant.However, an accompanying study showed the Importance of the wheat harvest as a source of income forlandless laborers. The follOWing data show how a shift to mechanical harvesting could affect the Incomesof the poor.Percentage distribution of laborers by most important income source, rabi and kharifseasons,Pakistan, 1986-87Percent of I8borer8MostImportantIncome source Rsb18 KhBrltbWheat harvesting 82.7Rice harvesting 62.7Rice transplanting 2.7Farming 1.3 6.7Livestock rearing 2.7 4.0All agricultural income 86.7 76.0All non-agricultural income 13.3 24.0Total 100.0 100.0Source: Smale (1987).a Rabl IS the period from wheat sowing to wheat harvesting.b Kharif IS the period after wheat harvesting through nee harvesting.These contrasting sets of data are valuahle to res

The following data come from a study of wheat technology adoption in northern Mexico (Traxler andByerlee 1992). Surveys were carried out in several different years (results from 1981 and 1989 only areshown here). There is evidence of change in several crop management practices. An analysiS was alsodone on changes in recommendations and evidence of causality between the recommendations andfarmers' new practices. It can be seen that although there is evidence of change in four practices, onlytwo of those changes can be attributed to research and extension.Evidence of causality between changes in recommendations and farmers' practices, northernMexicoPr8ctlceLand Percent farmerspreparation subsoiling 32 23 No MinorPlanting date Median date 5 Dec. 6 Dec. No MinorNitrogen Kg/ha 176 230 • Yes Minor NoPhosphorusPercent farmersapplying 59 78 • Yes Significant NoPlanting Percent farmersmethod ridging 8 33 • Yes Significant YesInsect Percent farmerscontrol applying insecticide 82 56 • Yes Significant YesSource: Traxler and Byerlee (1992) .• = difference significant at 1%.The recommendations for nitrogen use changed only slightly between 1981 and 1989, but farmerssignificantly increased the amount of nitrogen they applied, mostly in response to economic factors. Theproportion of farmers using phosphorus increased significantly as well, but there is little evidence thatthey responded to a recommendation for soil testing for phosphorus. On the other hand, ridge plantingwas developed by the research service and the survey showed that adopting farmers learned of thetechnique through demonstrations and field days. Similarly, the survey showed that the farmers who nolonger use insecticide now take advantage of the information prOVided by an integrated pestmanagement program developed by local research and extension personnel. It is these latter changeswhose contribution to increased wheat yields needs to be examined in an investigation of returns toresearch investment. The costs of the entire investment in crop management research over the period,including research in components not adopted by farmers, must be compared to the benefits of those-elements that have actually been adopted.28

Chapter 3UnderstandingAdoptionThe Factors That Influence Farmers' DecisionsBesides documenting the degree and scope of adoption of a technology,many adoption studies also try to understand the patterns of adoption thatare observed. Chapter 1 emphasized that this type of analysis can be usefulfor helping to refine the objectives of a technology generation program, aswell as for improving interactions between technology generation andvarious aspects of national agricultural policy. Our task in analyZingadoption patterns is to see what is acceptable and useful to farmers,identify what is not, and suggest ways for improving thesituation.The introduction mentioned that there is a large literature of technologyadoption studies, many of which pay little attention to the technology itselfbut rather concentrate on characteristics of the farmer. In some cases it isthe attitude or personality of the farmer that is analyzed, with adoptersbeing considered more "progressive" or "modern." In other cases,socioeconomic characteristics, such as wealth, landholding, or education,are used to explain the differences between those who adopt and thosewho do not.Although such approaches may be interesting, the type of analysisproposed in this manual requires a more careful examination of theinteraction between the characteristics of the technology and thecharacteristics of the farmers and farming systems that might accommodatethe technology. This analysis of adoption patterns should be a logicalcontinuation of the research planning process. When technologies are beingplanned and tested, priorities are set on the basis of potential benefits forfarmers (including a consideration of profitability and risks) and the easewith which farmers may be able to adopt the technology (includingcompatibility with their farming system, the pOSSibility that they can testthe new technology themselves, and the availability of institutionalsupport) (Tripp and Woolley 1989).An adoption study can be seen as another phase of the technologygeneration process and an opportunity to look in more detail at howresearchers help adapt technology to farmers' needs, and how farmersadapt their practices and conditions to take advantage of new technology.This chapter will examine several sets of factors that influence adoptionpatterns, including: the degree to which the technology is appropriate forfarmers' conditions; the compatibility of the technology with the localfarming system; how the technology is supported by markets; and how it ispresented by extension and other information systems.The list of factors that may influence adoption is long. Researchers willwant to review this list before planning an adoption study and decide-29

which factors should be included in their analysis. Researchers will uset~eir knowledge of the types of farmers potentially affected, a comparisonof the characteristics of the new technology with farmers' traditionalpractices, and an understanding of the technology diffusion process, todecide which factors deserve attention in a particular adoption study.Farm Resource and Farmer CharacteristicsThe first set of factors that we will explore are those characteristics of thefarmer and farm resources that can be used as explanatory variables inunderstanding adoption patterns. These include factors such as educationor wealth that may prediSpose a farmer to take an interest in a newtechnology, and resources such as amount of land or access to credit thatmay make it easier or more profitable for a farmer to change practices.Such farmer and farm resource characteristics occupy a major part of theliterature on adoption. Analysis of this kind of factor can be directed ateither of two audiences. H can be used for an assessment of the impact anddistributional consequences of adoption; is the new technology restricted tocertain sectors of the farming population? As well, an analysis of farm andfarmer characteristics may prOVide feedback to research itself for refiningthe technology; is it only appropriate for farmers with certain resource orskill levels, and what can be done to make the technology more Widelyavailable?_Characteristics ofthe farmerMuch of the literature on adoption assumes that new technology isnecessarily "good" and concentrates on analyZing those characteristics ofindividual farmers that make them more receptive to these innovations.For the purposes of a technology generation program, however, it is muchbetter to examine the correspondence between the recommendation andfarmers' conditions, without assuming that the technology is perfectlyappropriate or that those farmers who adopt ought to be called"progreSSive." Our purpose is rather to identify specific conditions thatmake a technology more, or less, acceptable to farmers and that can beaddressed through research, extension, or agricultural policy to maketechnology generation more efficient.-30Education. Many adoption studies examine the relation between a farmer'sformal education and adoption behavior. Education may make a farmermore receptive to advice from an extension agency or more able to dealwith technical recommendations that require a certain level of numeracy orliteracy. These skills are of course not necessarily perfectly correlated withyears of S('hooling, and some adoption studies go so far as to include a

small test of farmers' skills (for example, of the mathematics necessary tocalculate a dosage of herbicide). Informal education may be important aswell, and in certain cases adoption studies enquire about such things asattendance at short courses organized by the extension service (see thesection on "Information," p. 41). It may also be interesting to ask about thefarmer's own history of innovation and of trying new ideas.Many (but certainly not all) adoption studies show some relationshipbetween technology adoption and the educational level of the farmer. Themore complex the technology, the more likely it is that education will playa role. Thus the diffusion of a new variety among farmers may not dependat all on their education level, while the diffusion of a chemical input maybe more rapid among farmers who have at least some minimum amount ofschooling. The important point is that if such a relation is demonstrated,we must then ask how strong that relationship is and what the practicalimplications might be. If a particular technology finds its waypredominantly to farmers with a certain level of education, then severaloptions should be considered. One is to try to simplify the technology (ordevelop alternatives) so that it is more accessible. Another option is toconcentrate extension resources on farmers with less education and to trainthem in the use of the new practice. And a third option is to use this resultin making a case for more investment in extension services, training, orrural schools to accelerate the use of agricultural technology-which isbecoming ever more complex.Age. Another farmer characteristic that is often examined in adoptionstudies is age. A farmer's age may influence adoption in one of severalways. Older farmers may have more experience, resources, or authoritythat would allow them more pOSSibilities for trying a new technology.Experience in a particular farming area or with a given crop may not bestrictly correlated with age, however, and it may be worth asking morespecifically about experience. On the other hand, it may be that youngerfarmers are more likely to adopt a new technology, because they have hadmore schooling than the older generation or perhaps have been exposed tonew ideas as migrant laborers.In either case, it is unlikely that the demonstration of a relation betweenage and adoption per se will be of immediate utility. It is more important tosee if the relationship is due to farmers' experience or education or if theassociation with age is more la reflection of characteristics of the farmhousehold, including the distribution of authority, labor availability, orsources of income. An example of this type of analysis is shown in Box Bat the end of this chapter.-31

Gender. Women farmers are often forgotten in official agriculturalstatistics. Because women playa key role in most agricultural systems, it isimportant that adoption studies consider the degree to which a newtechnology reaches women farmers. This requires careful planning of thesurvey. Tn the first place, researchers should have a good idea of the crops,cropping systems, or farm operations that are important for womenfarmers and should make sure that the survey is designed to obtain therelevant information. Perhaps more important, the survey sampling andinterviewing strategies should be planned so that women are interviewedwhere they are the decision makers or have considerable knowledge abouta particular subject.If the survey results show a significant difference in adoption ratesbetween men and women farmers, there are at least two hypotheses to beexplored. The first relates to the type of farming system managed bywomen. It may be that the recommendations being examined are lessappropriate for the crops grown or crop management practiced by women,and decisions would have to be taken regarding a reorientation of theresearch program. The second hypothesis related to differential adoptionbetween men and women farmers is that women farmers are less likely tocommand the resources (such as land, credit, or information) to take fulladvantage of the technology. In such cases the conclusion might be to placemore emphasis on technology development that is appropriate to theresources available to women, or to address policy changes that mightmake services such as credit or extension more available to womenfarmers. Box 14 provides a few examples of how gender analysis maycontribute to an ~doption study.-32Ethnic, religious, and community factors. Tn many cases a technology isintroduced to an area that includes farmers of different customs andtraditions. These differences may be most notable between communities orbetween members of several groups liVing in the same community. It willnot be surprising to find that adoption patterns may differ among thesegroups. Although these differences may be easy to demonstrate, again weneed to ask whether this information can be used to make the research orextension program more effective. In many cases, differences amonggroups arise from differences in the resources they manage (for example,one group may have access to more or better land than another) or todifferences in farming systems or practices among the groups. In thesecases, it is a question of tailoring the recommendations for the conditions ofthe different groups. Another possible explanation for such differences isthat one group may have better access to government services. If this is thecase, the conclusion may be one of reorienting government policy,

Wealth. Wealthier farmers may be the first to try a new technology,especially if it involves purchased inputs. This may be because wealthierfarmers are more able to take risks or have better access to extensioninformation or to credit, or they may be able to use their own cashresources to experiment with a new technique. Whether or not this patternpersists, and wealthier farmers are the ones that are the major adopters andusers of a new technology, may be an important issue for an adoptionsurvey. The targeting and organization of the original research is also animportant factor, especially the degree to which the research was aimed atresource-poor farmers.A survey might use any of several methods for estimating a farmer'swealth, and the method chosen will depend primarily on the hypothesesthat researchers wish to explore. Many times it is farmers with moreresources (land, labor, capital) who are able to take advantage of a newtechnology. These factors are discussed in the follOWing section. In othercases a farmer's wealth may be a proxy for education (discussed above) orconnections with extension (discussed below in the section on"Information," p. 40). Or in some cases farmers with a more commercialorientation, who sell a large proportion of their harvest, are the ones whoadopt particular technologies (see "Post-Harvest Utilization and Markets,"p. 38). Wealth per se is a difficult parameter to measure on a survey,although it is sometimes a useful concept in explaining adoption. A methodof "wealth ranking," in which knowledgeable members of a community areasked to divide households into groups according to locally recognizedwealth standards, is described in Grandin (1988).FarmresourcesFarm size. Farm size is a common variable examined in adoption studiesand is often a good proxy for wealth. It is often assumed that larger-scalefarmers will be more likely to adopt a technology, espeCially if theinnovation requires an extra cash investment. It may be that a certainthreshold farm size is necessary before the investment in a technology isworthwhile. Or it may be that on larger farms different managementpractices (e.g., mechanization) are used, making a recommendation moreappropriate for them. On the other hand, certain technologies are moreappropriate for the intensive management characteristic of smaller farms(or at least of farms with a higher ratio of labor to land). Finally, farm sizemay be related to access to information or credit that would facilitate theadoption of a recommendation. The distribution of a new technologyamong smaller and larger farms is valuable information for assessingimpact, but in order to refine a technology and ensure that it is appropriatefor a range of farm sizes, more specific information about the relation offarm size to farm management is usually required (Box 15).-33

Labor. Technologies have different labor characteristics; some reduce theamount of labor required for growing a crop, while others significantlyincrease it. Tn planning an adoption study, researchers need to identify thelabor implications of each technology being examined. Are changes in laborrequired, and if so, how great are they, and at what time of the crop seasondo they occur? How does the technology change the division of laborbetween men and women? Tf the new technology requires a Significantamount of extra labor, it may be necessary to develop a rough labor profilefor the farm household (see the next section, ''The Farming System"). Howmany laborers are available? When are the peak labor periods during theyear? Do some household members work off of the farm and, if so, duringwhat periods? In addition, the survey may need to obtain information onthe availability of hired labor during the period relevant to therecommended technology. An example of how labor availability affectstechnology adoption is shown in Box 16.Credit. Credit may be an important factor in determining adoption. If arecommendation implies a Significant cash investment for farmers, itsadoption may be facilitated by an efficient credit program. Tf the majority ofadopters use credit to acquire the technology, this is of course a strongindication of credit's role in diffusing the technology. Similarly, manyfarmers who do not adopt may complain of a lack of cash or credit as theprincipal factor limiting their adoption. But the interpretation of this data isaided by a knowledge of the sources of credit available to farmers. Whatare the rules and regulations associated with official credit programs in theresearch area? What pr?Cedures do farmers have to go through to obtain aloan? Is the cred!t provided in cash or as inputs? The workings of the localinformal credit market should also be investigated. Such informationshould be analyzed before the questionnaire is designed so that the surveycan distinguish accurately between farmers who mayor may not haveaccess to credit.Rather than facilitating access to new technology, credit programs aresometimes responsible for obligating farmers to use a particulartechnology. The credit may be offered as a package that provides a set ofinputs to farmers. Parts of the package may be "adopted" simply because ofthis obligation, although farmers may feel that they are inappropriate orunprofitable. If this is the case, the adoption study can proVide valuabledata for refining and making more efficient both the recommendedpackage and the credit program.-34Equipment and machinery. Farmers' ownership of equipment ormachinery may infiuence their ability to adopt technology. Farmers whoown draft animals or tractors can be more Ilexible in changing their tillagepractices than farmers who must rent or borrow equipment (Box 17). If arecommendation involves a new type of equipment or machinery, the

degree of adoption may depend on the number of farmers who are able toacquire the equipment and whether or not an effective rental marketdevelops. An adoption study that examines technology related toequipment and machinery may need to ask how and where farmers rentthe necessary equipment.Land tenure. An issue that is much debated in the adoption literature is thedegree to which land tenure affects a farmer's ability to adopt. This issue isof practical interest for an adoption study if it helps us understand thedegree to which all farmers are able to take advantage of a new technology,and whether different technologies are required for farmers without secureaccess to their land.Researchers will need to be acquainted with the specific details of rental orsharecropping arrangements. In the case of sharecropping, how areobligations divided between sharecropper and owner, and how is theharvest divided? Different arrangements may make a technology more orless attractive for the sharecropper.Another important element of the land tenure issue is the fact that in manycases renters or sharecroppers will be less interested in technologies thathave long-term effects, such as soil fertility maintenance or enhancement,because they have no guaranteed access to the land. Tn other cases, rental orsharecropping may go beyond a Simple economic contract between ownerand tenant and involve particular obligations that restrict the tenant fromusing a new technology, such as when a tenant is required to plant varietiesthat proVide crop residues for the owner's animals to graze after harvest.The Farming SystemOne of the basic principles of on-farm research is that technologies must becompatible with the farming system if they are to find acceptance. For thisreason, a good part of the diagnostic and planning phases of on-farm.research is devoted to examining the pOSSible interactions between aproposed technology and the management of the crops and animals thatconstitute the farming system. Experience has shown that many times atechnology that appears as a reasonable innovation is rejected by farmersnot because of any intrinsic quality of the technology itself, but because itconflicts with other elements of the farming system. An adoption studyshould examine the degree to· which that technology is consistent with therest of the farming system.The principal audience for this aspect of an adoption study is researchersthemselves. The idea is to take this opportunity to monitor the35

compatibility of the technology with the farming system and, if anyproblems are detected, to use this information to refine the technology.We will consider below some of the parameters associated with an analysisof farming systems: the allocation of labor among various enterprises in thesystem, the management of other crops planted in the same field or inrotation, the biological conditions of the field, the soil conditions, andclimatic factors. In addition, we will examine the concept of risk. Much ofthis type of analysis is useful only if it is done with reference to a specificfield, so it is important that the survey be organized to collect thisinformation on particular fields and for particular years.Laborinthefanning systemA basic element of farming systems diagnosis is the development of a laborcalendar that gives an idea of how farm household labor is allocated overthe year. It is essential to know if the labor demands of a new technologyconOict with a particularly busy time of the year for farmers or rather takeadvantage of a period when labor is available. It is important to rememberthat this labor profile is determined not only by operations on the targetcrop but also by demands from various other enterprises in the farmingsystem. Thus it may seem that farmers should be able to do an additionalweeding on the target crop, for instance, but actually at that time they arebusy planting another crop.An adoption study is not the place to develop a complete labor profile. Thisshould have been done previously, in the earlier stages of research. Butquestions can be ,asked about the availability of labor and/or competingactivities during those periods of peak labor demand for the technologybeing promoted. Simply asking the farmers their perceptions of the laborrequirements of the new technology also can be useful (Box 18).Othercrops inthe systemlntercropping and relay cropping are common practices in many farmingsystems. New varieties or practices for one crop may thus have to becompatible with the presence and management of other crops. This mayaffect the choice of variety (e.g., does the new maize variety support theintercropped climbing beans?) or management practice (is the new weedcontrol method compatible with the intercrop?). In some cases, whatappear to be "weeds" are actually volunteer or sown species that may beused as food or fodder. The adoption study should pay attention to thedegree to which recommended practices are being used for the target cropin various intercropping systems. Significant differences may Signal thenecessity to target the recommendations better.-36Crop rotations are also an important part of farming systems, and theacceptance of the recommended technology may be affected by practices or

conditions of the preceding or following crop. A rotation pattern may affectthe timing of operations in the following crop (see Box 19). Carryovereffects from fertilizers or herbicides may also affect the management of thefollowing crop. Cropping history itself is important, and the practicesappropriate for newly cleared fields may be quite different from practicessuitable for fields with a longer cropping history. Again, the study ofrotation patterns is part of farming systems diagnosis, but the adoptionstudy should pay careful attention to the relative use of recommendedpractices as part of various rotation patterns.BiologicalcircumstancesThe adoption of technology may be affected by the weeds, diseases, andinsect pests prevalent in the area or in speCific fields. Weed controltechniques will be more or less appropriate depending on the weedpopulations or the presence of particular problem weeds in the field. Newvarieties may be more or less susceptible to diseases or insect pests, andcertain management practices (such as planting time) may reflect farmers'attempts to avoid these problems. The examination of the interaction ofthese factors with technology acceptance will require that researchers arefamiliar with local names for the weeds, diseases, or insects.SoilsLand quality and soil type may be important factors inJluencing theacceptance of a new technology. The selection of sites for on-farmexperiments needs to take account of variations in soil type or land type inthe research area. Researchers sh9uld have a good idea of the response andappropriateness of the new technology under the major soil conditions ofthe area. Not only may management practices differ by type of soil, butother conditions, such as slope or moisture retention capacity, are oftenimportant as well. To examine the influence of these factors on theacceptance of technology in an adoption study, researchers should befamiliar with local terms for variations in soil or land type.OimateClimatic factors play an obvious role in the management of farmingsystems. Rainfall patterns limit the crops that can be grown and regulateplanting and harvesting schedules. The pOSSibility of drought or Jloodingmakes farmers wary about investing in some technologies (see nextsection). Seasonal temperature changes also regulate cropping patterns, aswhen frosts at the end of the growing season dictate early planting and/oruse of early maturing varieties. By the time an adoption study is carriedout, the researchers should have analyzed available secondary data onclimatic variables and have a clear idea of how they may interact with thenew technology. Climatic factors in one area may set limits on theacceptability of a technology, and farmers may be asked their opinions and 37

experiences in this matter. Or adoption patterns may differ significantlybetween two research areas, based in part on differences in climate (Box20). Researchers should also be aware of any climatic abnormalities duringthe year of the adoption survey and understand how these may affecteither the short-term or long-term use of the technology.RiskThe failure of a new technology to be accepted is sometimes attributed torisk aversion on the part of farmers, but this is a difficult parameter toassess, especially in an adoption study. One important element of risk iscertainly the compatibility of the technology with climatic circumstancesdescribed above. If secondary data show that there is a high probability ofmid-season drought at the end of June, it is not surprising that farmerswould find a maize variety that flowers in late June to be unacceptable.Farmers would be able to articulate this reasoning in response to a questionon a survey.There is also the perception that some farmers are more willing to takerisks than others. Besides the obvious fact that wealthier farmers willalmost certainly be more Willing to invest in testing a new technology, thereis little in the literature that gives us a firm grounding for comparing riskattitudes to adoption behavior. Certainly in many cases resource-poorfarmers have come to adopt practices, such as growing high value cashcrops, that entail considerable risk.Another element related to risk is the variability in prices. Farmers'experience may be that input or product prices are so variable that theadoption of a particular technology presents unacceptable risks.In adoption studies that seek to explore the influence of risk on theacceptance of a technology, it is best to either use what is known aboutclimatic factors from secondary data or ask farmers specifically to give theirperceptions of the advantages and disadvantages, including risks, of thenew technology.Post-Harvest Utilization and Markets-38The adoption of a new technology can be hindered or enhanced dependingon whether it is in accord with the system of post-harvest utilization andmarketing and the organization of input markets. A technology may lead Losignificant increases in crop production, but if the inputs needed are notavailable or if the extra production cannot be utilized effectively, then thetechnology may be rejected. An examination of these issues may be helpfulfor two potential audiences. The first is research itself; if a technology isin(omratible with post-harvest conditions, or if farmers cannot obtain the

equired inputs, then the technology may have to be adjusted to theseconditions. But if the technology is underutilized because of problems withinput or product markets, then the results of an adoption study may beused to demonstrate to policymakers the advantages of improving thesemarkets._Post-harvestutilizationand outputmarketsThe introduction of new crop varieties to resource-poor farmers requiresan understanding of their food consumption patterns and preferences. If anew variety is to be used for home consumption, it will have to beacceptable for local processing and cooking practices. This issue needs tobe explored from the early stages of research, so as not to waste time onvarieties tha.t are incompatible. Farmer participation in the research isessential, and simple taste tests or panels may be devised to sort out whichvarietal characteristics are crucial for achieving farmer acceptance.One difficulty, however, is that farmers' tastes are subject to change as well,and a variety that is not ideal for certain purposes may have agronomic orother characteristics that offset the disadvantages. Thus at times a period oftesting is necessary, when farmers get better acquainted with the varietyand see to what degree it can be used. An adoption survey offers a chanceto monitor farmers' experience with a variety that has been released and toproVide feedback to plant breeders regarding acceptable and unacceptablecharacteristics (Box 21).If farmers market a considerable proportion of their harvest, then theacceptability of the new variety on the market needs to be investigated aswell. The characteristics required for market acceptance may beconsiderably different from those that determine acceptability in thehousehold. Researchers will want to talk to both farmers and merchants toidentify the principal characteristics that regulate the market price of a cropvariety. The survey can get more information about how and wherefarmers sell particular varieties, and can explore differences in price amongvarieties.A more general look at crop marketing may also be called for. Not only domarkets affect the acceptability of a new crop variety, they may alsoinfluence farmers' interest in any technology that promises higher yields. Ifmarkets are inefficient, there may be little incentive to invest in improvedtechnology. In addition, characteristics such as seasonal variation in marketprices may affect the acceptability of technologies that change the timing ofharvest (e.g., a technique that allows earlier planting).Storage practices may also deserve attention in a varietal adoption survey.Indeed, new storage techniques may be one of the subjects of such asurvey. In addition, crop storagf' practices may affect the acceptability of39

technologies that increase the harvest or change its timing. New varietiesmay have quite different storage characteristics, and this may be a limitingfactor for acceptance. An adoption survey can explore the degree to whichsuch storage problems are best addressed through plant breeding orthrough improved storage techniques.Crop production may not only be important for human consumption, butmay also be important for animal production as well. The place of animalsin the farming system needs to be explored in relation to new technologies.New varieties may have less acceptable forage qualities, for instance. Newcrop management techniques related to plant populations, weeding, orharvest may increase grain yield but affect the production of byproductsdestined for animals. The sale of crop byproducts may be an importantsource of income. The use of damaged or spoiled grain or tubers for onfarmanimal feed may diminish farmers' interest in certain crop protectiontechnologies._Input marketsIf a recommendation involves the use of purchased inputs, the adoptionstudy can check to see if farmers are able to acquire them. Preliminaryinvestigation should develop information on points of sale, availablesupplies, and form of sale, and the survey can then compare this to farmers'experience. Do farmers know where the inputs are sold? Are theredifficulties in getting to the location? Are the inputs always available whenthey are needed (Box 22)? What price does the farmer have to pay? Is inputquality reliable?The use of new crop varieties and seeds requires particular attention to thesource of the input. Seed is frequently saved from year to year, exchangedamong farmers, or purchased at a local market, besides being acquiredfrom official sources. Not only is it important to ask the source of seed, butalso the number of years since the farmer first obtained seed from thatsource.This type of information can be valuable for developing communicationwith policymakers and demonstrating ways in which relatively minorchanges in input policy may significantly affect the use of new technology(Heisey 1990).Information-40For farmers to adopt a technology they must first know about it. Theinformation may come from several sources. It is important to explore thedegree to which farmers have received the necessary information. This will

help in analyzing the degree to which low adoption may not be a functionof the technology itself, but rather of the information that is available. Thisanalysis is useful for improving extension policies and programs.In order to explore these issues on a survey, researchers need to be familiarwith existing extension programs and other media for providinginformation to farmers. They need to know whether field days,demonstrations, farm visits, or other methods are used by the extensionservice, and which terms farmers use to refer to them. Radio, television,newspapers, or magazines may be important sources of information insome places.One Simple way of addressing this question is to estimate the degree ofcontact that each farmer has had with extension activities and to comparethis with adoption behavior, in order to see if the extension contact has hadan inOuence. Another strategy is to ask farmers where they learned about atechnology (Box 2:\), although farmers' memories often are not perfect onthis subject.It also must be borne in mind that much information comes from otherfarmers. This makes studying the effect of extension difficult, because theinformation may well have originated with an extension agent but passedto the respondent through another farmer. This kind of problem ledBirkhauser, Evenson, and Feder (1991) to suggest that a study designed tomeasure the actual impact or effectiveness of an extension program is bestorganized by comparing communities that have had access to an extensionprogram with those that have had no co!'lact, rather than trying to makecomparisons between individual farmers in one community.Farmers can be asked about specific production problems to see if they arefamiliar with recommendations (Box 24). Finally, it is worth rememberingthat knowledge and use are two different things. An adoption study canexamine the distribution of farmers who don't know about a technology,those who know about it and don't (or no longer) use it, and those whoknow about it and use it. This contrast will proVide a clear indication of thedegree to which knowledge is a factor in explaining adoption patterns.SummaryThe following is a checklist of factors that help explain adoption patterns.No adoption study will include all of these factors, and it is important todecide which ones to focus on. This decision will depend to a large extenton the purpose of the study. Because an adoption study can have severalpotential audiences, it is important that the audience be clearly definedbefore the survey is designed.41

-42.....pI'OIIl'8Ift~=A checklist of factors that are important for understanding adoption-... err IdapUan IlUdV JF8ctDr ....,.......1orIUMJ-'I~hpoIlOY........ ImpIIctEducation Measure years 01 schooling, Types 01 training availableparticipation in other to larmers. oJ ..j oJtraining.Age Age 01 decision maker. ..; ..j(Effect may be related toexperience, education,household characteristics.)Gender (Effect may be related to Sampling strategy to oJ ..jtype ollarming system or include women larmers.access to resources such What crops, systems,as credit, extension, etc.) operations do women haveresponsibility lor?Ethnic (Effect may be related to What are the different groups oJgroup, type 01 farming system or in the research area? Howetc. access to resources.) do they reler to themselves?Wealth Can be estimated by land ..j oJholding, income, or otherlactors. (Effect may berelated to specificresources.)Farm size (Ellect may be related Local measures 01 area. oJ ..jto larming system orresources.)""..joJ ..;"..j" "Labor Amount 01 labor available LaQor requirements 01 ..j oJlorce in household; hiring the technology.practices.Credit Participation in credit What credit programs exist oJ oJprograms; source of loans lor farmers? What arelor farming.their requirements? Whois eligible?Equipment Ownership of equipment; Equipment and machinery oJ oJand experience with rental. requirements 01 themachinerytechnology. Rental marketsin the area.Land Decision makers' access What are local customs and oJ ..j ..jtenure to specific field. vocabulary lor renting,borrowing, sharecropping?Labor in Amount 01 labor available Timing and amount 01 labor oJ oJfarming in household; hiring required by new technology.system practices; other labor Cropping calendar.demands in system.Other Intercropping and relay Local practices lor oJ ..jcrops in cropping in specilic intercropping, relaysystem field. Rotation history cropping, rotation.of specilic field.(continued...)

Checklist (cont'd.).....FactorBiologicalfactorsHow to IncludeIn surveyCharacteristics of specificfield, by season.Other InformationRefiningneeded for--survey designLocal vocabulary for weeds,pests, diseases. Susceptibilityof new technology.......­researchprogram.,JPurpose of adoption studyInteractingwtthInput cr8d1tor marketpoRcymprovlng Asse88tng~xt.n.lon ImpactSoils,land typeSoil type, slope, othercharacteristics ofspecific field.Local vocabulary for landtypes. Experimentalevidence of differentresponses of technology.-JClimateRiskFarmers' opinions aboutliming of technology,climatic interactions.Farmers' opinions of riskof technology. Otherindicators of farmers'attitude to risk.Secondary data on climate. -JSecondary data on climate. -JHomeconsumptionOpinions on acceptabilityof new variety. Changesin food preparation.Local food preparation,types, and methods.-J .,JOutputmarketingFarm crop sales; amounts,timing.How and where are cropsmarketed in area? How doprices vary by season?-J .,J -JStorageHow do farmers store thecrop? Opinions oncharacteristics of newtechnology related to typeor timing of storage.Local storage techniques..,JFodderneedsTiming of fodderrequirements. Types offodder.Importance of animals andfodder in farming system..,J -JInputmarketsWhere farmers obtainspecific inputs. Knowledgeof input type, source.Local sources of inputs;availability. Localvocabulary for inputs.-J -JInformationContacts with extensionactivities. Knowledgeof technology. Source ofknowledge. Time of firstuse of technology.Types of extensionactivity in the research area.-JOnce the purpose and audience for an adoption study have been defined, the definition andmeasurement criteria for changes in farmers' practices have been identified, and hypotheses have beenlisted regarding reasons for differences in adoption patterns, the adoption study can be designed. Thenext chapter discusses issues related to choosing a sample, designing questions, and implementing thesurvey.-43

Box 13. Household Development Cycle and AdoptionAlthough the age of the household head or decision-maker may influence adoption patterns, otherhousehold characteristics may play an even more important role. Anthropologists use the term"household development cycle" to describe the way households evolve over time, often growing largerand more complex and then declining. This is not merely a function of household size, but also reflectschanges in access to resources (for example, a son may gradually acquire rights to his father's land),changing sources of income (younger households may earn more money from off-farm labor), andvarious kinship obligations.The table below compares the adoption of hybrid maize in Swaziland for three types of household. Itwas found that hybrid adopters were no more likely to sell maize than non-adopters, and the questionwas then asked why some farmers would grow hybrids for subsistence and others would not. Theargument made here is that younger households (type 1) have higher consumer/worker ratios andrequire more efficient technology for producing maize. More mature households (type 2) have lowerconsumer/ worker ratios but have significant cash earnings to support the improved technology.Households that are in decline (type 3) have the lowest consumer/worker ratios and thus the least needfor more productive technology. In addition, their wage earners earn less than those from otherhousehold types because they tend to be older and less educated. It can be seen that this classification byhousehold type is more successful at explaining adoption than a simple analysis by age of householdhead.Adoption of hybrid maize by household type.......Type 1 Type 3(establishment Type 2 (fission andand expansion) (consolidation) decline)Percent adoptinghybrid maize 57 64 37Average age ofhousehold head 40.3 56.7 59.7Consumer/workerratio 2.2 1.9 1.7Number ofwage earners 1.0 2.21.4Source: Calculated from Tables 7.17, 7.19, 8.12 in Low (1986).44

Box 14. Gender Analysis and AdoptionThe adoption of technology by women farmers may be quite different from that by men. The planning ofan adoption survey may need to include a careful examination of how responsibilities for differentagricultural activities are divided between men and women. The following data from Nepal show thatwomen participate in most agricultural decisions, and in cases related to choice of variety they are theprimary decision-makers.Farm management decisions in Nepal (%)Type of decision Male Female Joint TotalWhat crop to plant 18.0 30.2 51.8 100.0What seed to use 20.7 60.4 18.9 100.0Amount and kind of fertilizer 32.5 39.7 27.8 100.0Source: Acharya and Bennett (1982).One of the reasons that women farmers may adopt technology at a lower rate than male farmers is thatoften women are not as well served by extension services as men are. The following data from Malawishow the strong tendency for extension to have less contact with women farmers.Type of extension contact for male household heads (MHH), wives, and female household heads(FHH), Malawi (percentages of total in category)LilongweNgabuType of contactMHH(n=147)Wives(n=35)FHH(n=35)FHH(n=31)Personal visitGroup meetingDemonstrationField visit4166131328446923496628435151212154802Source: Spring (1985).Women farmers may also have different farming systems. In a project in The Gambia, the provision ofnew pump-irrigated rice technology benefited men more than women farmers.Women's participation in different rice technologies in The GambiaProject Project Traditionalpump-irrigated improved rainfed ricetechnology technology technologyFields under women's control (%) 10.0 77.0 91.0Yields per hectare 5.9 2.5 1.3Input cost (US$/ha) 294.0 154.0 20.0Labor input by women (in %of unpaid family labor) 29.0 60.0 77.0Source: von Braun and Webb (1989).-45

Box 15. Farm Size and AdoptionA study in Eastern Province, Zambia, showed that adoption of new technology was related to farm size,but the relationship depended on the technology. The adoption of hybrid maize, a cash crop, is verydependent on farm size. Ox cultivation varies as well with farm size, partly because farmers who havemore land are more likely to own oxen. Fertilizer use, on the other hand, is only weakly related to farmsize, and fertilizer rates do not vary across different farm size classes.Size of farms and adoption of technology in the Plateau Zone of Eastern Province, ZambiaLess than 1·2 2·3 3-4 More thanIndicator 1 ha ha ha ha 5ha1Farm sizeHouseholds (%) 23.6 31.7 15.4 18.7 10.6Average size (ha) 0.6 1.5 2.4 3.8 8.0Hybrid maizeFarmers using hybrids (%) 6.9 30.8 42.1 52.2 96.1Maize area under hybrids (%) 3.1 15.1 17.6 24.2 49.2Cultivation with oxenFarmers using oxen (%) 25.9 56.4 65.8 87.0 96.2Farmers owning oxen (%) 17.2 17.9 36.8 58.7 76.9FertilizerFarmers using fertilizer(percent) 51.7 67.9 65.8 67.3 100.0Crop area fertilized(percent) 45.5 49.8 52.3 43.5 72.3Average rate ofapplication (kg of plantnutrients per fertilizedhectare) 102.5 92.2 94.6 104.5 93.9Source: Jha et al. (1991).-46

Box 16. Labor Availability and AdoptionA study of the adoption of dry-seeded rice (D5R) in the Philippines examined a number of factors. Oneof the most important was labor availability in the household, because the dry-seeding technologydemands more labor for weeding. Farmers who adopt dry-seeding must either use more householdlabor or hire labor.A logH regression showed that labor availability, knowledge, and farm area had significant associationswith the adoption of dry-seeding. The first table shows the output of the logit regression. (For moreinformation on logit regressions, see pp. 76-81.)Logit regression analysis for adoption of DSR in Iloilo, Philippines, 1982Explanatory Asymptotic Significancevariable Coefficient error t-value levelb o Constant -1.0154 1.1258 -0.902 n.s. aX 1 Farmer's age -0.0143 0.0160 -0.895 n.s.X:2 Education -0.0623 0.0539 -1.156 n.s.X 3 Labor index 0.3132 0.1545 2.027 5%X 4 Draft index -0.2643 0.2331 -1.134 n.s.Xs Extension visits 0.00373 0.00829 0.451 n.s.~ Knowledge 0.4922 0.1109 4.437 0.1%X 7 Credit -0.4662 0.4190 -1.113 n.s.X s Tenancy 0.000130 0.00417 0.031 n.s.Xg Rainfed lowland area 0.0000558 0.0000227 2.455 5%Log likelihood ratio statistic [-2(log La - log L max )]44.6 (9 d.!.)Cases predicted correctly 70.5Sample size 173Source: Denning (1991).a n.s. = not significant.The second table looks more specifically at the independent effects of the three factors on the adoption ofthe D5R technology. It uses the results of the logit regression to calculate the probability of adoption fordifferent types of farmers. With respect to labor availability, it shows that the higher the labor index, themore likely farmers are to adopt DSR, independent of the effects of know ledge or farm area.Predicted probabilities of DSR adoption for an average farmer, for different sizes of rainfedlowland area being farmed and different levels of labor availability and farmer knowledge, Iloilo,PhilippinesSmall raInfed Medium ralnfed Large rainfedlowland area lowland area lowland area(1 ha) (2ha) (3 ha)L:aJ:)Or Index Labor Index Labor Index1 2 4 2 1 2Mean knowledge level 0.45 0.53 0.69 0.59 0.66 0.79 0.72 0.78 0.87-High knowledge level 0.59 0.66 0.79 0.71 0.77 0.86 0.81 0.86 0.92 47Source: Denning (1991).

Box 17. Access to Machinery and EquipmentThe availability of machinery or equipment may affect farmers' ability to follow recommendations. Thefollowing data from Kenya show that machinery owners (who tend to be larger farmers) are able toprepare their land for wheat closer to the recommended time than those who must rent machinery.Relationship between wheat planting date and machinery ownership, KenyaLand preparationDate Percent within Percentpreparation recommended using ownFarm SiZ9 begins date machineSmall (n = 24) March (1)a 0 8Medium (n = 18) February (1 ) 16 28Large (n = 17) December (4) 52 94Source: Hassan, Mwangi, and Karanja (1992).a Numbers in brackets refer to the week (e.g., first, second, -fourth) of the month.-48

80 1 te Trade-offsFarmers must often make trade-offs in the management of their resources, and labor often presents aparticular challenge. Farmers in western Ethiopia were encouraged to switch from broadcasting maize torow planting. About half of the farmers changed to row planting, but a survey that included questions onfarmers' opinions of the recommendations showed that the greatest limitation to further adoption wasthe extra labor required by row planting.Farmers' opinions on row planting, western Ethiopia (n = 64)Row planting Broadcastinglabetter labetter Ssme~ptnlon (0/0) (0/0) (0/0)Labor saving 7.8 92.2 0.0Seed saving 98.4 1.6 0.0Convenience for oxen-cultivation 90.6 4.7 3.1Reduce lodging 96.9 0.0 3.1Yield 93.8 3.1 1.6Source: Beyene Seboka et al. (1991).49

Box 19. Crop RotationsAdoption of technology for one crop may be affected by interactions with another crop in the rotation. Inthe example below, wheat that is planted after fallow in the Punjab of Pakistan is much more likely to beplanted at the recommended (early) date than wheat that follows cotton, since the cotton harvest canextend into the time for preparing land for wheat. Other practices, such as number of plowings andfertilizer use, tend to differ somewhat between the two systems as well.Major differences in production practices in two cropping patterns in cotton-wheat areas,Pakistan, 1985Wheat after Wheat after SignificancePractice cotton fallow level}Percent planted before 30 Nov.551Percent planted during 1-15 Dec.2731.00Percent planted after 15 Dec.6818Number of piowings and plankings 6.9 8.0 .09Average fertilizer use (kg/ha)Nitrogen 98 86 .09Phosphorus 50 40 .08Number of irrigations 6.0 5.9 .69Average wheat yield (kg/ha) 2,178 2,401 .04Source: Akhtar et al. (1986).50

-51The adoption of technology is influenced by climatic circumstances. In an adoption study in CentralMexico, it was found that barley farmers in a higher rainfall area were more likely to adoptrecommendations than those in a lower rainfall area. In addition, the technological components wereadopted differently in each area. The majority of farmers in both areas adopted improved barleyvarieties, but the use of herbicide and fertilizer was much higher in the higher rainfall area, whereresponse to these inputs was greater. In addition, farmers in the wet zone tended to adopt herbicidebefore fertilizer, while those in the dry zone, where weeds were less of a problem, tended to adoptfertilizer first.Adoption of three technological components in two zones of Central Mexico, 1975 and 1980PiiCiiit Of hlrmerazonetcomponentU8ectln1875~U8ed1n1980Ever used In1980Wet zoneImproved varietiesHerbicideFertilizer767746917462968265Dry zoneImproved varietiesHerbicideFertilizer291114611326611730Source: Byerlee and Hesse de Polanco (1986).

B 2 .It is often useful to ask farmers their opinions on various characteristics of a new variety. Rarely will anew variety be judged superior to a local one on all counts, but farmers are able to balance theadvantages and disadvantages of a new variety in making adoption decisions.The data below show that a new maize variety in Ghana is judged to have a number of superioragronomic traits, but is found to be deficient in both storage and cooking quality. These deficiencies didnot keep the variety from being widely adopted, but more attention to storing and cooking qualities inbreeding future maize varieties would certainly lead to even higher acceptance of new varieties.Farmers' opinions on local and new maize varietiesHumber of v~farmei'asameCharacterl 0 o,anlon l%) ('HI)Yield without fertilizer 66 22.7 74.2 3.0Yield with fertilizer 63 4.8 93.7 1.6Lodging resistance 60 28.3 70.0 1.7Germination 61 3.3 60.7 36.1Storage quality 72 77.8 13.9 8.3Cooking quality 55 72.7 23.6 3.6Source: Tripp et al. (1987).-52

-53Box 22. Source of Purchased InputsIn order to understand the input distribution system it is useful to ask farmers where they acquired theirinputs. In a study on wheat varietal adoption in Pakistan, researchers found that very few farmers wereusing government seed depots or merchants as sources of seed.Sources of wheat seed of new varieties and other popular varieties, Mardan, PakistanPercentage of fields sown to:Source of seed P8k-81 Blue Sliver SA-42 ''Mnfpal('Own 35 53 56 81Other farmers 35 35 37 19Seed depot 15 12Research/extension 15Shopkeeper/grain merchant 7Total 100 100 100 100Source: Heisey (1990).When asked about the location of the seed depots, only about half of the farmers could say where thesewere located. These data provided evidence to show that seed was not being distributed from seeddepots in the way that policymakers believed.Percentage of farmers who knew seed depot location and had visited a depot, PakistanAlcezone Cotton zone Msrd8nKnew correct location 51 46 52Stated other location 14 11 38Did not know location 35 44 10Visited depo~ 38 36 21Source: Heisey (1990).a Includes only farmers with correct knowledge of depot location.

Box 23. Source of InformationKnowing where farmers get information about new technologies may be important. If one of thepurposes of a particular adoption study is to evaluate information transfer, this sort of data is essential.The table below shows farmers' answers to a question on how they learned about a new maize variety,row planting, fertilizer, and fertilizer application methods. Although extension is the most importantsource of information, the degree to which farmers also obtain information from other farmers,especially in the case of new varieties, is noteworthy.How farmers first learned of technology (Ghana, 1990)Row-FertilizerVariety planting Fertilizer applicationHowleamed (n =241) (n = 199) (n = 158) (n =149)Demonstration byextension (%) 17 30 22 30Visit by extension (%) 29 24 41 35Other extension method (%) 3 3 5 2(Total extension) (%) (49) (57) (68) (67)From another farmer (%) 48 36 29 27Other or don't know (%) 4 8 4 6Source: Ghana Grains Development Project (1991).-54

Box 24. Knowledge of RecommendationsIt may be useful to ask about farmers' knowledge of specific recommendations. The data below arefrom a study that examined the effectiveness of a training and visit extension program in India. Anumber of questions were asked regarding technologies presented by the extension program, and theanswers of contact farmers were compared to those of non-contact farmers. In some cases contactfarmers were more aware of the recommendations than other farmers, while in other cases there was nodifference.Farmers' knowledge and adoption of selected extension recommendations on groundnut inDhenkanal District, Orissa, India (recommended practices indicated by an asterisk)Question""'-­AnswerNon-contact Ifarmers(%)(n =66) IContactfarmers (0/0)(n =73)1. What can be doneto control the attackof termites ingroundnut?Seed treatment"Soil treatment"FertilizerSeed and soil treatment"Soil treatment and fertilizerAshesDo not know6.125.822.71.510.64.528.811.034.216.44.19.61.423.3n.s.2. What can be doneto control the Tikkadisease ingroundnut?Seed treatment"Spraying"Seed treatment and spray"Do not know1.727.30.071.20.057.51.441.4.0013. What kind of seedtreatment should begiven to groundnut?No answerRhizobium culture"Chemical treatment"Do not know0.00.045.554.51.41.464.432.9.044. Do you practice theseed treatment ofgroundnut?Yes"No22.777.341.158.2 .035. What is the bestrow-to-row spacingin groundnut (erect.semi-erect type)?Correct (17 < X $ 25cm)Not correctDo not know22.765.212.115.175.39.6n.s.(+ 20 em)Source: Hoeper (1988).-55

Chapter4SurveyOrganizationIntroductionChapter 1 emphasized that the study of adoption is an integral part of thetechnology generation process. Most of the factors that affect the potentialacceptability of a new technology must be identified and monitored whileagricultural research is being planned and carried out. The study ofadoption is not something that can be left until the last minute.Although a number of methods can be used to assess adoption once atechnology has been released (see Box 2, p. 9), this manual focuses on themanagement of formal farmer surveys. There is an ample literature onsurvey techniques and design, and this chapter will emphasize only thosefactors that are of particular relevance to adoption surveys.Before approaching the adoption survey design, researchers need toaddress several issues. First, researchers must carefully define the nature ofthe technology change they hope to analyze. What types of changes infarmers' practices do they propose to study? Second, they need to identifythe audience for their study. Is the purpose to provide feedback fromfarmers to the research or extension program to make it more effective? Isthe audience another institution that helps determine the policyenvironment in which the technology generation process operates? Is thepurpose to document the impact of a research or extension effort? Andthird, a decision on the purpose of the study will determine whether thestudy will emphasize documenting the degree of adoption (Chapter 2) orwhether it will also explore the reasons for the observed pattern ofadoption (Chapter ~).Sampling-56ObjectivityThe adoption studies described in this manual are aimed at proVidinginformation to improve the efficiency of research and extension activities.This information can also be used to assess the effectiveness of particularinvestments in research or extension. Although donor developmentprojects or other special investments are often subject to outside evaluation,in the majority of cases studies of agricultural technology adoption will becarried out by the institutions that developed the technology. This places aspecial responsibility for objectivity on those doing the study. It must beremembered that the study is done to assess and to understand, rather thanto "prove" success. The sampling for the study must be undertaken withspeCial care, aVOiding biases that may show the institution in anunreasonably favorable light and making sure not to ignore issues thatshould be addressed. For instance, if the adoption of a new technology maybe more rapid with farmers who have better access to roads, extension

services, or markets, it is important that the sampling for a study be carriedout.so as to avoid favoring such farmers and giving the impression thatadoption is more widespread than it really is.- SamplingframeTechniques for drawing samples for surveys are described elsewhere andwill not be discussed here in detail (see Casley and Kumar 1988, Scott1985). It is assumed that the adoption study will look at a relatively smallnumber of technological changes in a well-defined area of a country.It is important to define the population to be sampled. Ts it, for instance, allthe farmers in a specified region? All the rice farmers? All farmers whogrow at least a half hectare of rice? All rice farmers who have participatedin a special extension program? The answers to these questions will dependon the purpose of the study, but a clear definition of the population isessential. Once this decision has been taken, the next step is to decide whatunits will be sampled. This may prove more difficult than it sounds. Ifhouseholds are the units, how do we define a household? Tn some cases itmay consist of members of an extended family who share certainagricultural resources and responsibilities but who also manage otheragricultural enterprises independently. Are the interviews to be conductedwith the head of the household? Tn many cases the household head may bea male, but females may take key decisions or have significantresponSibilities for crop management. Tn other cases, certain fields or cropsmay be the responSibility of particular household members. Preliminaryinvestigation will be necessary to decide how respondents are to be chosenand who will be the subject of the interviews.Once the study population has been defined, it is necessary to identify asampling frame. The sampling frame is constructed so that randomsampling can be carried out (in other words, so that - theoretically ­every unit in the population has a known chance of being chosen for thesurvey). In many of the procedures described here, the probabilities ofselection for each farmer will be equal. The sampling frame is, ideally, a listof all the units that could be sampled. Tn many cases, however, such acomplete list will not exist and may be impossible to assemble. Tn thesecases, alternative procedures can be defined that still allow for randomselection. One alternative is to draw a map of the households in the studyarea. Another possibility is to devise rules for sampling; for instance, anumber of randomly selected points on a map may be chosen andenumerators are instructed to take the first (or nth) unit in a randomlyselected direction.A common strategy when complete sampling frames are not available is todo two-stage sampling. If the study area consists of a large number ofvillages, for instance, the first stage of sampling would be a random-57

selection of a certain proportion of those villages. The second stage wouldbe to assemble complete lists of farmers or households in the selectedvillages and then draw samples from those lists. Special care must be takenin assembling the lists to ensure that all farmers (e.g., including all womenfarmers) are represented. Two-stage sampling may be the only feasiblealternative in areas where complete population or residence lists areunavailable. It requires careful planning, especially if the first-stage units(e.g., villages) are very different sizes. Scott (1985) discusses twoapproaches to this problem. One is to recombine the first-stage units sothey are of roughly equivalent size. The second is to select the units with aprobability approximately equivalent to their size, and then to choose equalnumbers of farmers from each sampled unit.The size of the sample will depend to some extent on the nature of thestudy and the resources available. The appropriate sample size is alsodetermined by the amount of variability in the population. If the study areafarmers are very heterogeneous in their practices or adoption behavior, alarger sample will be required. One way of reducing some of the samplingerror related to this variability is to stratify the sample. If part of thevariability in the sample results from differences between, let's say, farmerswho have access to irrigation and those who do not, it will be more efficientto stratify the sample by access to irrigation, rather than to rely on purelyrandom sampling to provide sufficient numbers of each class of farmer forthe analysis. When a stratified sample is used, however, researchers needto be able to estimate the proportion of each category in the generalpopulation so that they can assign weights to each subsample whenestimating important parameters, such as adoption rates, for the entirepopulation. The adoption studies described in this manual may be carriedout with as few as 50-60 respondents, but the complexity of the adoptionprocess is such that 80-120 respondents will be a more usual sample size.At times the existence of previous studies may help determine the nature ofthe sampling frame. If a formal survey was conducted in the area severalyears earlier as part of the diagnosis for the research program or to providebaseline data, an adoption study carried out using similar samplingprocedures will provide valuable comparative data. Tn some cases, anadoption study with the same sample used earlier may be useful. In somecases a "panel" of farmers is visited every few years to follow technologicalchange. There are both advantages and disadvantages to repeatedlysurveying the same farmers (see Scott, 1985). Although this is at times anattractive option, in most cases the sample for an adoption study will bedrawn without benefit of previous surveys.-58

- SamplingforcomparisonsTn many instances an adoption study attempts to answer questions aboutdifferences in the rate of adoption between groups of farmers. Have largerorsmaller-scale farmers tended to adopt the technology? Are participantsin extension programs more likely to adopt? Does distance from marketsmake a difference in adoption behavior? These and similar questions maybe addressed in two possible ways. Tn the majority of cases it is likely thatthese characteristics will appear with sufficient frequency in a randomlydrawn sample that the appropriate comparisons can be made. But if aparticular comparison is important enough for the purposes of the study,and if it is not certain whether a randomly drawn sample will proVide asufficient number of each category, then the sampling may be done in apurposive manner. For instance, if it is important to judge whether theparticipants in an extension program have reacted differently to a newtechnology than non-participants, then part of the sample may be drawnfrom a list of program participants and part may be drawn from thegeneral population. ]n this example the sampling is fairly straightforwardbecause a list of program participants exists. But in other cases (such aslarge-scale versus small-scale farmers) it may take considerably more effortto develop appropriate samples, and researchers will have to decide if thisis worthwhile. As with stratified sampling, for each purposively chosengroup, researchers need to know the proportion of farmers in order toknow what weight to assign each subsample to assess overall adoptionrates._SamplingfieldsBesides deciding on an appropriate sampling frame for farmers, it may alsobe necessary to define a sampling procedure for fields. If farmers in thestudy area have several fields, researchers will have to decide whether theyare going to assess adoption of the technology on all of the farmer's fields,on fields with certain characteristics, or only on the largest field. Thisdecision will depend partly on the definition of adoption selected for thestudy and the purpose of the study. If the purpose is to inventory the use ofa particular technology, then all fields may have to be sampled. If thepurpose is more to understand the context in which a technology is used,then a subsample of fields may be sufficient, or the farmers themselves maybe the only sampling unit and be classified as adopters or non-adopters.Timing of the SurveyTn most cases the best time to do an adoption study will be shortly after theharvest, when farmers may have more time to answer questions and whenthey will be able to report on their experience during the season. If morethan one season per year is being studied, the timing question is more59

complex. The timing may also depend on the specific purpose of thesurvey. For certain surveys it may be useful to include field observations inthe study (to observe the effectiveness of a weed control technology, forinstance), in which case the survey will be done during the crop season. Orit may be that storage or marketing issues are important, and researchersmay wait until some time after harvest and then survey farmers about theirmarketing experience. The timing of the survey may be affected by naturalcircumstances. Although it is often impossible to carry out a survey in theproverbial "normal" year, unusual conditions such as a severe drought maymean that conditions are not appropriate for assessing farmers' experiencewith a particular technology, and the survey might have to be postponedor at least redeSigned. In certain areas where the performance of atechnology is chronically variable (because of uncertain rainfall, forexample), it may be necessary to assess adoption and technologyperformance over several years.Survey DesignThis manual discusses the development and analysis of short, well-focusedquestionnaires for studies of adoption. Such questionnaires can be used todocument and quantify the degree of adoption of particular technologiesand to collect information that helps explain the patterns and extent ofadoption. It is very important that the purpose of the survey be identifiedclearly so that the questionnaire is an efficient instrument for collectingpriority information, not a device for exploring a wide range of issues.The section on sampling discussed the importance of an objective approachto assessing adoption. The same advice is relevant when desiening thequestionnaire. The questions should be presented to the farmer in asneutral a manner as possible. The best way to do this is simply todocument the relevant practices that the farmer is using, much as would bedone in a diagnostic survey of farming practices. The interviewers shouldexplain to the farmers that they are interested in farming practices andproblems, not that they are trying to see if farmers are follOWingrecommendations. Thus questions on varietal use should not begin with,"Do you use new variety X?"/ but rather with more general questions thatask farmers to list the varieties that they grow. It is very important that noleading questions are asked and that the farmers do not feel they are being testedwith regard to their knowledge or use of recommendations.-60The survey questions will be determined by the objectives of the study. Indocumenting adoption, for instance, the goal may simply be to estimate theproportion of farmers using a practice, or it may be to estimate theproportion of area or production associated with the practice. The goal

chosen for the survey will determine the type of question to be asked.Similarly, if one goal is to understand why some farmers have adopted apractice and others have not, researchers will need to form specifichypotheses to guide the types of questions that are asked. Thesehypotheses may be pursued directly, by asking farmers' opinions, orindirectly, by statistical comparisons between adoption behavior andspecific characteristics of the farmers' circumstances (Chapter 5).There are a number of good sources available on survey design, and onlygeneral gUidelines will be offered here. The reader is referred to Byerlee,Collinson, et a!. (1980), Casley and Kumar (1988), Bernsten (1980), Alreckand Settle (1985), and Murphy and Sprey (1982) for more detail.1. Open versus closed questionsQuestions may either be precoded so that the farmer's response shouldcorrespond to one of a limited number of choices, or the space for theresponse on the questionnaire may be open and the interviewer recordswhatever the farmer says. There are advantages and disadvantages foreach of these types of questions, but for an adoption study it is to beexpected that the vast majority of questions will be closed. This is notonly more efficient for analysis, but also reOects the fact that theadoption study will be quite well focused; will be carried out in an areawhere researchers should have a good idea of local practices,vocabulary, and so forth; and will be designed after a good informalsurvey.2. Leading questionsNo survey should contain leading questions, but this is particularlyimportant for an adoption study. There should be no "hints" orencouragement that might lead a farmer to respond positively aboutparticular practices. For instance,.farmers should not be told what is"correct" and then be asked if they follow that practice. Similarly,farmers should be allowed to give the names of varieties or purchasedinputs that they use and should not be proVided these namesbeforehand. If farmers cannot remember the name of the input, this factshould be recorded on the questionnaire.3. SpecificityQuestions about adoption should be as specific as possible. "Do you usefertilizer?" is rarely a sufficiently precise question, for instance. Thefertilizer use should be specified by season and field. If input rates arerequired for the study, questions should be asked about specific fieldsand the interviewers will have to be familiar with local units of measurefor both inputs and field size.61

4. Order of questionsThe questionnaire should follow a logical order. The introductoryquestions should be of a general nature. These would be followed byquestions about specific aspects of crop management. Sensitivequestions, such as those about use of credit, are best left until near theend. As well, if the study requires information on farmers' knowledge ofrecommended practices, this type of question should be left until afterthe farmer's actual practices have been recorded.Examples ofquestions for an adoptionstudyAppropriate questions for a questionnaire should be based on understandingdeveloped during an informal survey. No manual can proVide"standard" questions to be used on a survey. The following examples arepresented only to show some appropriate formats for questions.A. Many questions regarding the adoption of technology can be asked inthe context of an inventory of practices by field. Tt is almost alwayspreferable to ask about practices in speCific fields, rather than in general.If complete information on the area of adoption is required, the questioncan be repeated for all fields. In other cases, questions about the majorfield may suffice.The following table illustrates how questions about weeding practices incassava might be organized:Size of field (no. of acres)Date of planting cassava aName of cassava variety(ies)IntercropbDate of planting intercropaDate of 1st weeding aMethod of 1st weeding CDate of 2nd weeding aMethod of 2nd weeding C'. y. -'-., :_'" . ':-:-1 • 'I,~-., .:~""". -'- -'!"''': ~''''- ~_...-_'_ ..--.a Week and month, e.g" 2/4 = 2nd week of April.b 0 = monocrop, 1 = maize, 2 = sorghum, 3 = other.C 1 = machete, 2 = hoe, 3 = plow.62

B. Measurements for input use may be necessary if it is important toestimate exact dosages. This may require using local measures andvocabulary.In an area where farmers measured herbicides with small cans, thefollowing questions were asked:If you used herbicide to control weeds, can you tell us about yourpractice?Size of field: _______ "tareas" (local measure)Days before (-) orafter (+) plantingName of herbicideCans of commercialproduct per sprayer tankNumber of tanks perfieldC. Farmers' opinions on a new technology are often best assessed byasking about specific characteristics of the technology. The farmer maybe asked to compare two or more technologies (e.g., varieties) and beasked which is best or worst.The following is an example of questions to elicit farmers' opinions oncover crops:1. We have heard that the cover crop that farmers call "rertilizer bean"has some advantages. Which of the rollowing are important ror you?Improves soil fertili tyMakes land preparation easierHelps control weedsHelps conserve moistureControls erosion1 = Very important advantage 3 = Not important2 = Some advantages 4 = Don't know63

2. We have also heard that the "ferlilizer bean" has somedisadvantages. Which of the following are disadvantages?Planting the cover crop means losingone cycle of maizeBrings more insectsBrings more ratsCauses landslides on steep slopes1 = Very important advantage 3 = Not important2 = Some advantages 4 = Don't knowD. Studying varietal use may require careful questioning regarding thesource of the seed.1. Name of principal variety planted in this field: _2. Where did you obtain the seed that you planted this year?1. From last year's harvest2. Purchased from the seed depot~. Purchased from the market4. Purchased from another farmer5. Gift from another farmer6. Other _~. If the seed is from last year's harvest, in what year did you firstacquire this variety?4. How did you first acquire the seed?1. Purchased from the seed depot2. Purchased from the market~. Purchased from another farmer4. Gift from another farmer5. Other _E. Extension contact and source of knowledge.To be able to attribute a change in farmers' practice to an extensionprogram, questions need to elicit when the farmer first began using thepractice and the source of the materials and knowledge required tocarry out the practice.-641. If you are using leucaena for alley farming on part of your farm, inwhich year did you begin this practice?_

2. Where did you acquire the seed?1. Another farmer2. The farmer's club3. An extension agent4. Other _3. How did you learn how to plant the leucaena?1. From another farmer2. Attending a field day organized by farmer's club3. Attending a field day of extension service4. Visit from extension agent5. Reading extension bulletin6. Own experiments7. Other _4. How did you learn how to prune the leucaena?1. From another farmer2. Attending a field day organized by farmer's club3. Attending a field day of extension service4. Visit from extension agent5. Reading extension bulletin6. Own experiments7. Other _Survey ImplementationGuidance on survey implementation can be found in a number of sources(Byerlee, Collinson, et al. 1980; Casley and Lury 1981). Any questionnaireshould go through several drafts as it is reviewed by colleagues and pretestedwith farmers. It is difficult to overemphasize the importance ofcareful questionnaire testing. The fi~ld testing of the questionnaire shouldbe done by the people who will work as enumerators, so that they canparticipate in developing the final version and have a thoroughunderstanding of the questions. Besides participating in the field testing ofthe questionnaire, the enumerators should undergo additional training toensure that they are able to present and interpret the questions correctly.The logistics of carrying out the survey need to be carefully thought out.Enumerators are assigned specific portions of the sample, and are givenexplicit instructions regarding rules for replacing sample farmers who areunavailable. The enumerators may be deployed singly, or in teams of two,with one responsible for asking the questions and the other for recording.Completed questionnaires should be turned in to a supervisor everyevening, and they should be checked so that gaps or inconsistencies can be 65addressed immediately._

The coding and analysis should begin immediately after the completion o{the survey. For an adoption survey to be useful, a report should be writtenand distributed as soon as possible.SummaryThe choice o{ sample {or an adoption study will be determined in part bythe objectives of the study. The study area needs to be defined (politicalboundaries, ecology, etc.). Farmers may be selected at random {rom thestudy area, or the sample may include farmers with particularcharacteristics. The sample size will depend on the variability of the{arming population being studied and the resources available. Decisionswill also have to be made about sampling within the {arm: are all fields tobe studied, or only particular ones?The design of questions for an adoption study should follow the rules ofsurvey design in general, with attention to clarity, specificity, and logicalordering. In an adoption study, particular care must be given to ensuringthat the questions do not bias the farmer towards positive responsesregarding the technologies being studied.The survey should be implemented as efficiently as possible, and timelyanalysis and write-up are crucial. The following chapter provides somegUidelines for analyzing the results of an adoption survey.-66

Cha ter 5MethodsforAnalyzingAdoptionPatternsThe results of an adoption survey require careful analysis andpresentation. The form and focus of the final report will depend very muchon the purpose of the study. If the purpose is only to document the degreeof adoption, then thought must be given to the factors discussed in Chapter2 regarding the definition of adoption, the best way to present the degreeof present adoption, and the necessity of analyzing historical adoptionpatterns. This type of analysis is useful for considering the rate of progressof a technology generation effort and for helping to investigate the impactof such an effort.But very often we also wish to analyze the adoption patterns and to try toexplain why a technology may be reaching certain farmers and not others.Some of the pOSSible reasons for differences in adoption were outlined inChapter 3. Explaining adoption patterns requires additional analysis,which is the subject of the present chapter.There are two principal strategies for helping us understand why farmersaccept or reject a particular technology. One is to seek the opinions andobservations of the farmers, and the second is to do a statistical comparisonof adoption behavior with the characteristics of the farm, farmer, orinstitutional environment. Both of these are valid aspects of surveyanalysis. This chapter discusses the analysis and presentation of this typeof data.Farmers' OpinionsFarmers usually know what they like and what they do not like about anew technology and are able to express their opinions. These opinions willreflect their own experience. If the adoption study encourages farmers toproVide an honest assessment and does not make them feel that thequestioning represents a test of knowledge of "modern agricul ture" or"recommended practices," then very useful information will be obtained.Open questions, such as "Do you like variety X?" or "What problems doyou find with reduced tillage?" may not be effective, however. The formaladoption study will be based on the experience of an inrormal survey(where these open questions are more appropriate), and the questionnaireshould refer more to speCific characteristics or the technology that havebeen identified. Box 25 (at the end of this chapter) shows farmers' opinionson two technologies; in one case adopters were asked to explain thereasons for using a technology, while in the second case rarmers who didnot adopt were asked to explain their choice.Farmers' decisions regarding new technology can rarely be reduced to asimple set or opinions, however. Farmers use a range of criteria in decidingwhether to change their practices, and a number or models and theories-67

have been developed to try to explain farmer decision-making. Suchmethods are beyond the scope of this manual, but one of the mostcommonly used tools, "decision trees," is illustrated in Box 26.Statistical ComparisonsAlthough farmers are experts regarding their own fields and practices,they may not be able to provide much information on factors that affectother farmers. In addition, the factors that influence the adoption of atechnology may be so diverse or complex that it is unreasonable to ask afarmer to account for them or to try to explain the pattern of adoption.For that reason, an understanding of adoption also can benefit from astatistical comparison of the farmers' adoption behavior with variouscharacteristics of the farmers' environment. In most instances it is thefarmers themselves who will be asked to describe these characteristics,but they will not be asked to actually articulate the causal linkagebetween the characteristics and adoption. That is the task of theresearcher, and it may draw upon a wide range of tools in statisticalanalysis.Techniques of survey analysis are well described in a number of texts,including Casley and Kumar (1988), Alreck and Settle (1985), andNorusis (1991). The purpose here is only to review briefly a few of themost common methods that are relevant to the analysis of an adoptionstudy.In attempting to explain adoption patterns by statistical analysis, themost common approach is to compare the characteristics of farmers whohave adopted a technology with those who have not adopted, to see ifsome of these differences might offer insights into the rationale foradoption. Thus if the proportion of farmers who have access to irrigationis much higher among adopters, we would be led to explore thepOSSibility that the technology is more appropriate or accessible if afarmer has irrigation.-68Just because these differences can be found does not of course constituteproof of an association. The differences must be explored within thecontext of all of the data available from the survey. Simple methods ofpresenting these data and statistical tests help in making the case, butthe major responsibility in interpretation lies with the researcher, whomust proVide a consistent, coherent, and logical explanation for theadoption patterns that are observed.

One of the simplest and most useful ways of examining differences inadoption patterns is with contingency tables, in which the cells or the tablecompare the proportion of adopters and non-adopters with a particularcharacteristic. This is particularly appropriate if the characteristic of interestis a nominal one, that is, one that is represented by non-numericalcategories, such as access to irrigation (yes or no) or previous crop in therotation (potatoes, barley, or other). Even in cases where the variable is acontinuous one (such as farm size or number or days between land preparationand planting), it is sometimes useful to divide it into a few simplecategories (large vs. small; low, medium, high) and develop contingencytables. The relevant statistical test or this association is the chi-square test.In the example below, the adoption of row planting for maize is examinedin light or land preparation practices. It can be seen that there is a strongassociation. Farmers who use a tractor for land preparation are much morelikely to adopt row planting; 84% of these farmers adopt row planting,while only 29% of the farmers using manual land preparation adopt rowplanting. The chi-square test shows that it is improbable that thisassociation could occur by chance.Planting method by land preparation-- - - ~ ­.,. ­- "', ~ ',' - .!........~ '., . -'.' ,:.•• • • I !!=. ..:.- -.....:..~ •• '. ">--",_ .. ~Random 177 22 199(71%) (16%)Row 71 114 185(29%) (84%)Total 248 136 384(100%) (100%)X'?- =105.0 d.t. = 1 P < .0001The contingency table does not tell us why these two factors are related,however. It could be that tractor preparation makes row planting easier; inthis case tractor preparation is a cause of row planting. It is possible(although unlikely) that row planting "causes" tractor use, in the sense thata farmer who decides to row plant will rent a tractor for land preparation.The point is that we must go beyond presentation of the association andseek an explanation.69

If the variable is continuous, another option is to compare the means foradopters and non-adopters. An appropriate statistical test in this case is thet-test. The table below shows that fields where farmers apply fertilizer tendto be cropped continuously for a longer time than those fields wherefertilizer is not used.Fertilizer use by cropping historyWithout fertilizer (N = 50) 3.14With fertilizer (N = 58) 6.40t=3.51d.f.=106 p

For instance, a survey may show that the average farm size for adopters is4.7 ha, while the average farm size for non-adopters is 4.2 ha. Dependingon the variability in the sample and the sample size, this difference mightbe shown to be statistically significant. It is probably not surprising thatfarm size exerts some influence on a farmer's adoption decision, but it isdoubtful if we would want to give much emphasis in this case to the factthat adopters tend to operate farms that are about 10% larger than those ofnon-adopters. The information probably is not useful to researchers (forrefining their recommendations) or to policymakers (in understanding thespread or impact of new technology). If the adopters tended to have farmsthat were twice as large as those of the non-adopters, on the other hand, wewould have to begin thinking about better targeting or presentation of thetechnology.If two factors are associated, there are a number of ways of explaining theobserved association. Tn most cases, the analysis of adoption surveys willlook for factors that may cause or contribute to the adoption (or nonadoption)of a technology. There is no standard method for doing this typeof interpretation, and the researcher must be guided by his or herknowledge of the data and of the farming system. Further detail on thistype of survey analysis can be found in Rosenberg (1968).Someways ofinterpretingand refiningtherelationshipbetweentwo variables inan adoptionstudyJust because there is a relationship between two variables does not meanthat one causes the other. Tn studying adoption, we try to identify factorsthat influence a farmer's decision to use a technology. The analysis shouldprovide a clear and logical explanation for the contribution that a particularfactor makes to the adoption decision. This requires a careful analysis of therelationship between variables. The following examples show how therelationship between two variables (A and B) can be understood better byincluding a third variable (C) in the'analysis.1. Identifying specific components of the causal variableTn some cases a relationship may seem reasonable, but it is possible tofind a more specific explanation. For example, farm size (A) may berelated to the adoption of contour hedgerows for erosion control (B). Thesmaller the farm, the more likely the adoption. What is it about farm sizethat would influence the adoption of hedgerows? If we find that smallfarms have more family labor available per hectare (C), and that there isalso a strong relationship between labor availability and hedgerowadoption, it may be sensible to emphasize this factor in our analysis ofthe data.71

Proposed relation: A 8Revised relation: A(C) 8ProposedFarm size (A) Adoption of hedgerows (8)Planthedgerows (n=22)Do not planthedgerows (n=29)Average farm size 1.2 ha 2.3 hat-test prob. < .05RevisedFarm size (A) is associatedwith labor availability (C) ----.. Adoptionof hedgerows (8)Planthedgerows (n=22)Do not planthedgerows (n=29)Family labor/ha 2.7 persons 1.2 personst-test prob. < .052. Looking for intervening variablesThere is another possibility, closely related to the previous one, where asearch for a more specific or useful explanatory factor leads tolengthening the causal chain. If it is found that oxen ownership (A) isrelated to the adoption of a new, late-maturing maize variety (8), weneed to ask what is the connection. We may find that farmers with oxenare able to prepare and plant their fields earlier (C) and are thereforeable to use the new variety without worrying about the relatively shortrainy season. The relationship between planting date (C) and varietyadoption (8) is more useful than the relationship between oxenownership (A) and variety adoption.Proposed relation: A 8Revised relation: [A___.... 8----__t 1 CProposedOxen ownership (A) Variety adoption (8)Adopt Do not adoptnew variety variety Total-72 XOwn oxen 28 (70%) 12 (30%) 40 (100%)Rent oxen 7 (24%) 22 (76%) 29 (100%)2 prob. < .01

-73Revised[Oxen ownership (A) --.t~1Early planting (C) ......... Variety adoption (8)Adoptnew varietyDo not adoptnew varietyMean planting date 14 April 2 May3. Eliminating an extraneous variableSometimes we find an association between two variables that we do notunderstand. This may be because the two are related only by chance, orperhaps because the two variables happen to be related to a third. Inone survey an association was found between tenancy (A) and varietyadoption (B); owners rather than sharecroppers were the ones whoadopted the variety. Researchers could give no clear explanation forthis relationship. It was then discovered that sharecroppers wereconcentrated in one region where the new variety had not beenpromoted. When the analysis was done controlling for region (C), therelationship between tenancy and variety adoption disappeared.?Proposed relationship A 8A Co C 1Revised relationship C A (no relationship) 8 A (no relationship) 8ProposedLand ownership (A) Variety adoption (8)AdoptDo not adoptnew variety new variety TotalOwner 159 (60%) 106 (40%) 265 (100%)Sharecropper 14 (26%) 39 (74%) 53 (100%)X 2 prob. < .01

RevisedThe association is tested controlling for the third factor:Region X (CO> Region Y (C 1)A (no relationship) BA (no relationship) BRegion XRegion YAdopt Do not adopt Adopt Do not adoptvariety variety Total variety variety TotalOwner 35 (30%) 81 (70%) 116 (100%) 124 (83%) 25 (17%) 149 (100%)Share­ 10 (21%) 37 (79%) 47 (100%) 4 (67%) 2 (33%) 6 (100%)cropper X 2 prob. =n.s. X 2 prob. = n.s.4. Finding a variable that suppresses a relationSometimes we expect to see an association between two variables, butwe find none exists. A third variable may suppress the relation by beingpositively correlated with the dependent variable and negativelycorrelated with the independent variable. Preliminary analysis of anadoption survey showed no relationship between farm size (A) andfertilizer use (B), although researchers expected to see such arelationship. A third variable, slope of field (C), suppressed therelationship. More fertilizer was used on hillside fields than on Oatfields, and most large farms were on Oat land. Hillside fields werepositively correlated with the dependant variable (fertilizer adoption)and negatively correlated with the independent variable (farm size).Proposed relation: A (no relation) 8Revised relation:(-)Ac ~8 A==-- 8ProposedFarm size (A) (no relation) Fertilizer use (8)Small farms (n=53)Large farms (n=38)Average fertilizer use (bags/ha) 4.6 4.9t-test prob = n.s.-74

RevisedThe association is tested controlling for the third factor:Farms on flat land (Co) Farms on hillsides (C 1)A B A BFarms on flat landFarms on hillsidesSmall farms Large farms Small farms Large farms(n=9) (n=33) (n=44) (n=5)Average fertilizeruse (bags/ha) 1.7 4.3Hest prob.

RevisedThe association is tested controlling for the third factor:Low rainfall zone (Co) High rainfall zone (C l)A B A (no relationship) BLow rainfall zoneHigh rainfall zonePlant before Plant after Plant before Plant after1 Nov. 15 Nov. 1 Nov. 15 Nov.Percent farmersplantingcover crop 34% 12% 48% 42%x 2 prob.

The following example is a simple logistic regression that examines theadoption of a new variety. The dependent variable is variety adoption andthe independent variables are the region of the country, land tenure,cropping practice, and rarmers' age. The variables are listed below:Variety adoption (VAR) o no yesRegion (REG) o forest savannaTenure (TEN) o sharecrop ownerMonocrop (MON) o intercrop monocropAge (AGE)(continLJClus variable)The results of the logistic regression show a highly significant associationwith region, no association with tenure, a significant association withmonocropping, and none with age.Constant -2.087 0.549 -3.803 0.000REG 2.332 0.325 7.169 0.000TEN 0.465 0.400 1.162 0.245MON 1.111 0.310 3.585 0.000AGE -0.012 0.010 -1.289 0.197Sample size 318Log of likelihood function -162.9Chi-square statistic for significance of equation 131.1Degrees of freedom for chi-square statistic 4Significance level for chi-square statistic 0.000Cases correctly predicted 79.0%This example draws on the same datu used in the example on page 73. Inthat example, there was a significant relationship between variety adoptionand tenure. But when we controlled for region, the relationshipdisappeared. The logistic regression does the same thing, and the resultssay that when we control for region (and cropping practice and age) thereis no association between land tenure and varietal a~option.If we were to run the logistic regression without in~luding region, wewould find that tenure appears to have a significant association withvariety adoption (see the follOWing table). The use of multivariatetechniques such as logit models is therefore no guarantee that we willidentify important relationships and discard unimportant ones. The-77

opposite strategy of throwing as many independent variables as possibleinto the equation is not advisable either. The use of such techniques will beefficient only if we have a clear understanding of the data with which weare working.CoeffIcIentProIMIbIIftyConstantTENMONAGE-1.3670.8931.868-0.0120.4810.3530.2660.009-2.8422.5317.016-1.4450.0050.0110.0000.148Sample sizeLog of likelihood function318-192.7Chi-square statistic for significance of equation 71.4Degrees of freedom for chi-square statistic 3Significance level for chi-square statistic 0.000Cases correctly predicted 72.4%One way of presenting information from probit or logit regressions is toshow how changing one independent variable alters the probability that agiven individual is an adopter. In ordinary least squares regression, acoefficient can be interpreted directly as the change in the vi.llue of thedependent variable associated with a change in one unit of the independentvariable associated with that coefficient. This is not true in probit or logitregressions; the change in probability of adoption given a change in one ofthe independent variables depends not only on the coefficient of thatvariable but also on the levels of all the other independent variables.As an example, the estimated probability of adoption in a logit model isgiven by:probability of adoption = F(b'x),where:F(b'x)1 + e-b'xis the cumulative logistic probability distribution. The expression b'x isdefined as:78

where b o is the constant, b}' b 2, •.• b kare the other estimated coefficients,and Xl' x 2' ..• X kare the values of the independent variables. Tn the firstmodel estimated above, the probability of new variety adoption for a forestzone farmer who is an owner, 41 years old, and planting an intercroppedfield is calculated as below:v.-.CoeffIcf8nt1)Value of Independentvartable(2)Constant -2.087 1 -2.087REG 2.332 0 0TEN 0.465 1 0.465MON 1.111 0 0AGE -0.012 41 -0.492Total (b'x) -2.114F(b'x) .111 + e-b'x 1+e 2 . 114Thus, the probability of such a farmer being an adopter is .11. A farmerwith identical characteristics except for planting a monocropped fieldwould have a probability of adopting a new variety given as follows:v (1Constant -2.087 1 -2.087REG 2.332 0 0TEN 0.465 1 0.465MON 1.111 1 1.111AGE -0.012 41 -0.492Total (b'x) -1.003F(b'x) .271 + e-b'x 1+ e 1 . oo3Similar calculations show that a 41-year-old owner in the savanna zone hasa predicted probability of adoption of .55 if he or she intercrops and .79 ifhe or she monocrops. In other words monocropping raises the predictedprobability of adoption for otherwise identical farmers in both the forestand the savanna zone, but the change in predicted probabilities is differentin the two different environments..7.9_.

Predicted adoption probabilities in the probit model are calculated inexactly the same way, except that F(b'x) in this case represents thecumulative standard normal probability distribution. The mathematicalform of the normal distribution is relatively complex, but values of F(b'x)can be found easily enough in standard probability tables.In some instances one might want to analyze not only adoption but also theextent or intensity of adoption. For example, one might want to estimateboth the probability that a farmer uses fertilizer and the rate of applicationas well. A commonly used model in this case is the tobit model. Tobit, likeprobit, is based on the normal distribution. As in probit or logit, coefficientsare estimated for the independent variables thought to be relevant. Tobitestimates also include the standard error of the regression s, which is anestimate of the standard deviation of the error term in the regressionmodel.Tn a tobit model, the predicted probability of adoption for a farmer withcharacteristics x is estimated by F(b'x/s), where b, x, and s are defined asabove, and F is the cumulative standard normal distribution function. Theexpected value of the application rate Y (or total amount used, dependingon the dependent variable used in the regression) is estimated byE(Y) = F(b'x/s)(b'x) + sf(b'x/s) ,where f is the probability density function for the standard normaldistribution.The expected value of Y, the application rate or total amount used, giventhat Y>O (Le., that the farmer is an adopter), is estimated byE(Y:Y>O) = b'x + Sf(b'x/ s)F(b'x!s)As with the cumulative standard normal distribution, the standard normaldensity function is also easily found in probability tables.-80Maddala (1983) is a good source of information on logit, probit, and tobitmodels. Multivariate analytical techniques are available in several softwarepackages for personal computers. It is thus quite easy to enter data on alarge number of variables and obtain long printouts and an impressive listof coefficients and related significance levels. But just as with the simpleranalytical techniques, the responsibility for interpreting the results restswith the researcher. A result that shows that certain variables areassociated with adoption says nothing about the causal links among those

variables. And a high significance level says nothing about the importanceof the relationship. This warning is especially relevant for multivariateanalyses, where computer technology makes it possible to examine dozensof variables. It must be remembered that a significance level of 10% meansthat the observed association has a one in ten chance of occurring atrandom. If we were to include 15 or 20 independent variables in anequation, we would expect that a couple of them would appear"significant" just by chance, especially if we ran several regressions withdifferent combinations of variables. (This warning is of course equallyvalid for the practice of analyzing 15 or 20 single-variable relationshipsuntil something appears that is "significant.") A summary of some of theseanalytical problems related to understanding the adoption of soilconservation is presented by Lockeretz (1990).Even sophisticated analytical techniques have severe limitations in theirability to disentangle complex relationships among a number of variables.The purpose of analyZing adoption patterns should be to identify a few keyrelationships or factors that not only can help us to understand theadoption process, but can help to make the research and extension effortmore efficient in the future. The emphasis should thus be on simpleanalyses and clear presentations (Casley and Kumar 1988). We should alsoremember that we are limited in our ability to understand adoption notonly by the statistical techniques at hand, but most of all by the skill withwhich we frame the questions in our adoption study and the quality of thedata that are generated.SummaryAdoption studies often attempt to analyze and understand the observedadoption patterns. In these cases, a~option survey analysis can includeboth an examination of farmers' opfnions and observations, and a statisticalcomparison of adoption measures with characteristics of the farmer or thefarming system. Farmers' decisions regarding a new technology are oftenquite complex, and the purpose of an analysis is to try to use a range ofstatistical procedures to identify the most important factors that influenceadoption. The analysis will be successful only if the information can beused to help improve the efficiency of subsequent technology generationand diffusion efforts.81

A.An adoption survey can ask farmers' opinions about a new technology. Farmers may be able to giveboth positive and negative characteristics of the technology.In the example below, farmers in Nigeria who had adopted alley farming were asked what they sawas its principal advantages.Alley farmers' perceptions and uses of alley farms,a NigeriaTrees used for:Cultivated tree species preferred by farmers:Mulch only 3 Leucaena 66Feed only 5 Gliricidia 2Mulch + feed 35 Both ---.2AMulch + feed + otherb ~ 9294Perceived benefits:Reason for preference for species planted:Better soil fertility 29 Liked by animals 75Better animal performance 41 Grows fast 5Better soil fertility and Other ~animal performance ~ 8593Source: Reynolds et al. (1991).a Based on 137 farmers. Percentages do not add to 100% because of missing data.b Includes stakes and firewood.B.It is equally important to ask farmers why they don't adopt. In the example below, farmers in Ghanawho did not use the recommended maize variety were asked why they did not plant it. The analysiswas divided between farmers who had used the variety in the past but stopped using it, and thosewho had never used the variety.Reasons for not using Improved varieties, Ghana, 1990Seed not available 62 64Lack of knowledge 29 0Storage problems 27 39Marketing problems 20 49Cooking quality 8 6Yield 2 6(Number of farmers) (98) (33)_82 Source: Ghana Grains Development Project (1991).Note: Percentage total is more than 100% because of multiple answers.

1Decision trees are a method of representing a farmer's choice about a new technology as a series ofdecisions, arranged in a hierarchy. The method is described in detail in Gladwin (1989).An example of a decision tree is shown below. It attempts to analyze farmers' decisions regarding theuse of an early-maturing maize variety ("Katumani") in Kenya. According to this analysis, the decision toplant this variety is based on farmers' need for early maize, the availability of other early varieties, andexperience with yields and dog damage.Good to have maize that is ready early?YESTried planting Katumani?YESHave another variety forearly maize which is betterthan Katumani?NONODo NOT PLANT3 casesReasons for not tryingYESI~TI1 caseNODogs destroymost of yourKatumani planting?YESJNOHave anothervariety forearly maize~3 casesDamage Yields Otherby dogs are toolowI=TI I=TI I~TI3 cases 4 cases 5 casesGetting early maize soimportant that youcontinue to plantKatumani?Katumani so low yieldingthat the benefits of earlinessare outweighed by thelow yield?YESNOYESi7 '[ I~TI l'~TICan you obtainseed for plantingby buying, borrowing,3 cases 5 cases 5 cases or storing own seed?NOn= 81 (6 cases not includeddue to inadequancy of data)NOYESI=TI49 cases 2 casesSource: Franzel (1984).-83

Chapter 6ConclusionsThere is an urgent need to develop more productive technology for farmersin developing countries. The resources available to public and privateinstitutions, and to the farmers themselves, are very limited, however.Thus it is imperative that the process of technology generation be made asefficient as possible. One way of improving the efficiency of agriculturaltechnology development is to doa better job of describing and analyzingtechnology adoption.There is no single method for studying technology adoption. Indeed,concerns with adoption and acceptability must form a part of thetechnology generation process from its early stages. Agricultural researchthat does not include a continual dialogue between farmers andresearchers will have little chance of success.As technology is developed and made available, there are several ways offollOWing its progress. This manual has described one important method,the formal survey. Its advantages include the ability to provide systematic,quantitative information to those who must take decisions about researchor extension efforts, and its ability to formally test hypotheses that explainadoption patterns.Formal adoption studies can proVide valuable information to research,extension, or rural development institutions that wish to assess theirprogress and take advantage of farmer experience. Adoption studies arealso valuable tools for improving the efficiency of communication betweeninstitutions responsible for research, extension, and agricultural policy.And finally, an adoption study can play an important role indemonstrating the impact of a research or extension effort and in justifyingcontinued or expanded support from funding sources.Properly managed, adoption studies can contribute to improving theefficiency of agricultural research, technology transfer, input provision,and agricultural policy formulation. Formal adoption studies should thusbe an important part of the methodology of institutions involved inagricultural development.-84

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