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Waikato Regional Council Technical Report 2017/05
Towards predicting rates of adoption and compliance in farming: motivation, complexity and stickiness www.waikatoregion.govt.nz ISSN 2230‐4355 (Print) ISSN 2230‐4363 (Online)
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Prepared by: Dr Geoff Kaine and Dr Vic Wright Geoff Kaine Research For: Waikato Regional Council Private Bag 3038 Waikato Mail Centre HAMILTON 3240 August 2015 Document #: 9834604
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Doc # 9834604
Peer reviewed by: Date June 2016 Blair Keenan
Approved for release by: Date February 2017 Ruth Buckingham
Disclaimer
This technical report has been prepared for the use of Waikato Regional Council as a reference document and as such does not constitute Council’s policy. Council requests that if excerpts or inferences are drawn from this document for further use by individuals or organisations, due care should be taken to ensure that the appropriate context has been preserved, and is accurately reflected and referenced in any subsequent spoken or written communication. While Waikato Regional Council has exercised all reasonable skill and care in controlling the contents of this report, Council accepts no liability in contract, tort or otherwise, for any loss, damage, injury or expense (whether direct, indirect or consequential) arising out of the provision of this information or its use by you or any other party.
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Doc #9834604
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Towardspredictingratesofadoptionandcompliancein
farming:motivation,complexityandstickiness
DrGeoffKaineandDrVicWright
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AuthorsDrGeoffKaineandDrVicWrightGeoffKaineResearchHamilton,NewZealandAugust2015AcknowledgementsWewouldliketothankJustineYoungandhercolleaguesatWaikatoRegionalCouncilfortheirsupport,adviceandassistance. OurthanksalsogotoBlairKeenanatWaikatoRegionalCouncilforreviewingthispaper.Imagecourtesyofxedos4atFreeDigitalPhotos.netDisclaimer:Theauthorhaspreparedthisreportforthesoleuseoftheclientsandfortheintendedpurposesstatedbetweenbothparties.Othersmaynotrelyuponthisreportwithoutthewrittenagreementoftheauthorandtheclients.Nopartofthisreportmaybecopiedorduplicatedwithouttheexpresspermissionoftheauthorortheclients.Theauthorhasexerciseddueandcustomarycareinconductingthisresearch.Nootherwarranty,expressorimpliedismadeinrelationtotheconductoftheauthorsorthecontentofthisreport.Thereforetheauthordoesnotassumeanyliabilityforanylossresultingfromerrors,omissionsormisrepresentationsmadebyothers.Anyrecommendationsoropinionsorfindingsstatedinthisreportarebasedonthecircumstancesandfactsatthetimetheresearchwasconducted.Anychangesinthecircumstancesandfactsonwhichthereportisbasedmayaffectthefindingsandrecommendationspresented.
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Towardspredictingratesofadoptionandcompliancein
farming:motivation,complexityandstickiness
Introduction
Predictingtheextentandrateofadoptionbyfarmersofagriculturalinnovations
iscentraltoassessingthebenefitstobehadfromresearch,marketingand
extensionprogrammes.Itisalsocrucialtoassessingiffarmersmayresist
policiescompellingtheadoption,orabandonment,ofparticularagricultural
technologiesandpractices.
Predictingratesofadoption,orcompliance,andhowtheymightbeinfluenced,
requiresanin‐depth,detailedunderstandingoftheadoptionprocess.After
reviewingtheliteraturesonconsumerandorganisationalpurchasing,Wright
(2011)arguedthataprudentapproachtomodellingadoptiondecisionsby
farmerswouldbetoassumethefulloperationofthemostextensiveofconsumer
decision‐makingmodelsand,therefore,thedual‐processmodelofconsumer
decisionmakingproposedbyBagozzi(2006a,b)wouldbemostsuitable.
Wright(2011)alsoobservedthattheadoptionofmorecomplexinnovations
mightbeexpectedtoinvolvegreatereffortandrisk.Thereforethefactorsthat
mightinfluencethemotivationtoconsideradoptingagriculturalinnovations
mightvarydependingonthecomplexityoftheinnovation.Thesamecouldbe
saidinregardtochangingfarmpracticesandtechnologiesgenerally.This
observation,then,suggestedthataclassificationofagriculturalinnovations,or
changesinfarmpracticesandtechnologies,intotypesrangingfromsimple
throughcomplexwouldbeusefultotheextentthatthesetypesinfluencethe
intensityofmotivationrequiredtotakeaction.
Inthispaperwedescribeanapproachtopredictingratesofadoptionand
compliancewithrespecttotheagriculturaltechnologiesandpractices.The
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approachdrawsonthedual‐processmodelofconsumerdecision‐makinganda
methodforclassifyinginnovationsinfarmsystems.
Inthenextsectionthedual‐processmodelofconsumerdecision‐making
proposedbyBagozzi(2006a)isdescribed.Thisisfollowedbyadescriptionof
theclassificationofinnovationsproposedbyHendersonandClark(1990).More
detaileddescriptionsmaybefoundinWright(2011)andKaineetal.(2008),
respectively.TheadaptationoftheHendersonandClark(1990)classificationto
changingfarmpracticesandtechnologiesisthenexplained.Thewayinwhich
thetypesofinnovationsthatthesechangesrepresentinfluencefarmers’
motivationtochangepracticesandtechnologiesisthenconsidered.Asmall,
pilotapplicationoftheapproachisbrieflyreported.
Theimplicationsoftheapproachforpredictingratesofadoptionofinnovations,
andtheroleofincentivesandextensionininfluencingthoserates,arediscussed
usingtheeconomicconceptofstickiness(BallandMankiw1994;Szulanski
1996;Ogawa1998;Sims1998;BilsandKlenow2004;MankiwandReis2006).
Theimplicationsoftheapproachforpredictingratesofcompliancewithpolicies
compellingtheuse,orabandonment,offarmpracticesandtechnologiesarealso
considered.Particularattentionispaidtotheimplicationswithrespecttothe
intensityofoppositiontosuchpoliciesandtheroleofincentivesandextension
ininfluencingthatopposition,againusingtheeconomicconceptofstickiness.
Inthefollowingtheterm‘adoption’maybetakentoincludecommencingtheuse
ofanypracticeortechnology(innovativeorotherwise)and,implicitly,the
abandonmentofapracticeortechnology.
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TheDual‐Processmodelofadoption1
Adoptioninvolvesbothadecisiontoadopt,whichisintention,andthe
translationofthatintentionintobehaviour,whichmaynotoccur(Bagozziand
Lee1999).Theconceptof'goalstriving'wasdevelopedtolinkintentionwith
behaviour(Bagozzi2007;BagozziandDholakia1999;BagozziandLee1999).
Consequently,thedual‐processmodelofconsumerresponsetoinnovations
proposedbyBagozzi(2006a)hastwocomponents:goalsettingandgoalstriving.
Goalsettingdescribestheprocessofdecidingtoadopt;goalstrivingdescribes
theprocessofadopting.
Thegoalsettingprocessprovidesafoundationforidentifyingwhenmotivation,
andthefactorsthatinfluencemotivation,delayadoption.Thisprocessclarifies
thepotentialfortheadoptionofapparentlybeneficialinnovationstobedelayed
byalackofmotivation.Thegoalstrivingprocessprovidesafoundationfor
identifyingwhenitisimplementationofthedecisiontoadoptthatdelays
adoption.
Goalsetting
Thedual‐processmodelisshowninidealisedforminFigure1.Inthemodelthe
firstprocesstriggeredbyawarenessofanopportunitytoachieveagoalisa
sequenceofreflective,deliberativeprocesses:consider‐imagine‐appraise‐decide
(Bagozzi2006a).Thisprocessdeterminesthedegreeofinterestthedecision‐
makerhasinachievingagoal,thatis,goaldesire.Insufficientinteresthaltsany
movetotheconsciousformationanduseofattitudesandnorms.Thegreaterthe
timeandeffortenvisagedinadoptinganinnovation,thegreatergoaldesiremust
betoprovokemovementbeyondgoaldesiretogoalintention.Goaldesire
determineswhetheragoalacceptedasworthyofpossiblepursuit.
1ThematerialinthissectionisdrawnfromWright(2011),Kaineetal.(2012).
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FigureOne:KeyvariablesandprocessesinConsumerAction
Source:Bagozzi(2006a:15)
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Bagozzi(2006a)proposesfiveelementsintheconsider‐imagine‐appraise‐
decideprocess.Twooftheseelementsaretheemotionsthatresultfrom
imaginingsuccessandfailureandtheassociatedpersonalemotional
consequencesinachievingtherelevantgoal.Thesearetermedpositiveand
negativeanticipatedemotions,respectively.Theseemotionscouldinclude
happiness,excitementandprideordisappointment,angerandsadness.So,for
example,successfuladoptionofanewtechnologymaybeassociatedwith
happinessandexcitement.Conversely,theforcedabandonmentofavaluedfarm
practicemaybeassociatedwithfrustrationandanger.Thelikelihoodofsuccess
orfailureisnotconsideredwithanticipatedemotions.
Anothertwoelementsintheconsider‐imagine‐appraise‐decideprocessare
termedanticipatoryemotions.Theseemotionscanalsobepositiveornegative
andareemotionalresponsestotheprospectofafutureevent.Theemotions
involvedarehopeandfearanddependinpartontheperceivedprobabilityofan
event,thatis,successorfailure,occurring(Wright2011).Inourcontext
anticipatedemotionsconcernfeelingsabouttheconsequencesthatwouldflow
fromsuccessfullychangingfarmtechnologyorpractice(orfailingto),
anticipatoryemotionsconcernfeelingsaboutthechancesofsuccess(orfailure).
Thefinalelementintheconsider‐imagine‐appraise‐decideprocessisaffect
towardsthemeansofstrivingforthegoal.Thisisthepersonalemotionalappeal
ofthemethods,processes,actionsandsoonrequiredtopursuethegoal(Bagozzi
2006a).Thesemaybefavourable,orunfavourable,dependingoncircumstances.
Theconsider‐imagine‐appraise‐decideprocessleadstoacceptanceorrejection
ofthegoalasabasisforactingornot.
Anumberofpersonalitytraitsmayinfluencegoaldesireincluding:self‐efficacy,
responseefficacy,andcausalandresponsibilityattributionprocesses(Bandura
1997).Self‐efficacyandresponseefficacywillimpactonanticipatoryemotions
whileresponsibilityattributionwillimpactonanticipatedemotions(Wright
2011).
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Movingthoughthemodel,goaldesiremustbeconvertedintosomegoal
intention,acommitmenttoacttoachievethegoal.Thishappensthroughthe
interactionofgoaldesirewithself‐regulatoryprocesses,thatis,theinteraction
ofgoaldesirewiththedecision‐makersevaluativeandmoralstandardsthat
governwhotheyareorwanttobe(Bagozzi2006a).Theinteractionofthese
standardswithgoaldesirescanleadtoanintentiontopursuethegoal,
cancellationofthegoal,orpostponementofgoalimplementation(Wright2011).
Thiscommitmentorintentionmustthenbetranslatedintoasetofspecific
behavioursoractionstobeimplemented.Thisistermedbehaviouraldesire.The
factorsthatmoderatethetranslationofgoalintentionintoasetofactionsthe
decision‐makerismotivatedtoperformareattitudetowardstheact,socialand
subjectivenormsandperceivedbehaviouralcontrol(FishbeinandAjzen1975;
Ajzen2001;2002).
Justasgoaldesiremustbetranslatedintoagoalintention,behaviouraldesire
mustbetranslatedintospecificbehaviouralintentions.Aswasthecasewiththe
translationofgoaldesireintogoalintention,thetransformationofbehavioural
desireintobehaviouralintentionismoderatedbyself‐regulation,thatis,the
decision‐maker’sevaluativeandmoralstandardsthatgovernwhotheyareor
wanttobe(Bagozzi2006a).Thetranslationofbehaviouraldesireinto
behaviouralintentionmayalsobemoderatedbyperceptionsofbehavioural
controlsuchasself‐efficacy.
Finally,theprocessofgoalsettinghasthepotentialtobecomplexanditerative,
whichmeanstheprocesscantakesometime.Actionwillnotproceeduntilthe
processofdecidinghasrunitscourse(Wright2011).
Goalstriving
Typically,thepredictionsfrommodelsofconsumerbehaviourhavebeenlimited
topredictingbehaviouralintention.Thislimitationisbasedontheexpectation
thatactualandintendedbehaviourarehighlycorrelated(BagozziandLee1999).
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Unfortunately,thisisnotalwaysthecase.Inthedual‐processmodelthefactors
thatinfluencethelinkbetweenintendedandactualbehaviourareconsidered
explicitlyinthegoalstrivingcomponentofthemodel.Explicitconsiderationof
thesefactorsisparticularlyimportant,notonlyinforecastingratesofadoption
butalsoinhighlightingwhatopportunities,ifany,theremaybetoinfluencethis
rate.
Thefirststageingoalstrivingisthechoiceofhowthebehaviouralintentionwill
befulfilled.Alternativemeansbywhichthismaybedoneareevaluatedinterms
ofself‐efficacy,outcomeexpectancyandaffect,whichislikeordislikeofameans
(Wright2011).
Thesecondstageisactionplanning.This‘involvesdecisionsastowhen,where,
howandhowlongtoact.Inthisstagesituationalcuesforthetimingofspecific
actionsarecontemplated’(Wright2011:18).Thethirdstageingoalstrivingis
trying,thatis,theimplementationoftheplan,whichisthecommencementof
actioninpursuitofthegoal.
Thefourthstageconsistsofthecontrolprocessesexercisedovertheplanned
actionssuchastrackingprogress,identifyingopportunitiesandhindrancesand
revisingplansaccordingly,maintainingcommitmentandreconsideringgoals,
means,plansandactionsinthelightofexperience.Appraisalsofprogresswill
leadtoaffectiveresponses.Forexample,positiveaffectwillevokeanintentionto
staythecourse.Anegativeaffectmayevokegreatereffort.Alternatively,itmay
resultinchangesingoals,aredefinitionofsuccessorfailureorabandonmentof
goalstriving(Bagozzi2006b).
Thefinalstageistheoutcome:adoption,trialorfailuretoadopt,whichwill
generateemotions.Astheyareexperienced,outcomeswillfeedbacktoinfluence
goalsettingforsubsequentinnovations.
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Typesofagriculturalinnovations2
Theeffortandtimeinvolvedinadoptingcomplexagriculturalinnovationswillbe
greaterthanforlesscomplexinnovations.Consequently,theintensityofthe
motivationneededtoadoptcomplexinnovationscanbeexpectedtobegreater
thanthatneededforsimplerinnovations.Animportantstep,then,inusingthe
dual‐processmodeltopredicttherateofadoptionofagriculturalinnovationsor
non‐compliance,wouldbetolinkdifferencesinthestrengthofanticipated
emotions,anticipatoryemotionsandaffecttowardsmeanswiththecomplexity
ofagriculturalinnovations.Suchalinkrequiresarigorousmethodfor
characterizingthecomplexityofinnovations.Thereareavarietyofmethodsfor
doingso.
Wright(2011)suggestedHendersonandClark’s(1990)frameworkfor
classifyingproductchangesintotypesofinnovations,whichwasadaptedfor
innovationstoagriculturalsystemsbyKaineetal.(2008),wasthemostsuitable
inthiscontext.TheusefulnessoftheclassificationdevelopedbyHendersonand
Clark(1990)iswhatitrevealsaboutthemagnitudeoftheimpactofadoption(or
abandonment)ofatechnologyorpracticeintermsofdisruptiontosystem
activity,thedestructionofcompetencies,andtheneedfornewskillsand
knowledge.SeeKaineetal.(2008)formoredetail.
Inthissectionwebrieflydescribetheframeworkforclassifyinginnovationsinto
fourgenerictypesandsummarisetheadaptationoftheframeworktoclassifying
innovationsinagriculturalsystems.
Classificationofinnovations
HendersonandClark(1990)proposedthataproductcouldbeconceivedofasa
system–acollectionofcomponentsthatarelinkedtogether.Theydefinedthe
componentsofaproductasthephysicallydistinctpartsofaproduct.Howthe
componentsarelinkedtogethertoenabletheproducttofunctionisthe
architectureoftheproduct.Consequently,productinnovationcanbe
2ThematerialinthissectionisdrawnfromKaineetal.(2008;2012).
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conceptualisedaschangestocomponents,thelinkagesbetweenthem,orboth.
Theythensuggestedthatinnovationscouldbecategorisedintofourtypesof
increasingcomplexity:incremental,modular,architecturalorradical,depending
onthedegreeofchangeintroducedintothecomponentsandthelinkages
betweenthem(seeFigure2).
Incrementalinnovationsintroducerelativelymodestchangestothecomponents
ofaproductleavingthelinksbetweencomponents,thatis,theproduct
architecture,largelyunchanged(HendersonandClark1990).Incremental
innovationsexploitthepotentialofanestablisheddesignandtendtobuildon
existingskillsandknowledge.
Modularinnovationsintroducerelativelysubstantialchangestothecomponents
ofaproductinthatatleastsomeexistingcomponentsbecomeobsoletebecause
thenewcomponentsarebasedonnewdesignconcepts(HendersonandClark
1990).Generallyspeaking,thearchitecturelinkingthecomponentstogether
remainslargelyunchangedwithmodularinnovation.
Newskills,competencies,andprocessesmayberequiredtomanufactureand
installthenewcomponents.Consequentlymodularinnovationsmayenhanceor
destroycompetencedependingonthehistoryofthespecificorganisation
(Gatignonetal.2002).
HendersonandClark(1990)defineanarchitecturalinnovationaschangingthe
waythecomponentsinasystemlinktogether.Generallyspeaking,architectural
innovationsentailrelativelyminorchangesinthecomponents.Knowledgeabout
thewaycomponentslinktogetherbecomesembeddedintheorganisational
procedures,processesandstructuresovertime(HendersonandClark1990).
Consequently,architecturalinnovationshavebeenshowntocreateserious
disruptionstoorganisationsbecausetheyrequirechangesintheoperating
procedures,processesandstructuresoftheorganisations,aswellasthe
acquisitionofnewskillsandcompetencies.
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FigureTwo:Idealisedmapofthefourtypesofinnovations
Source:HendersonandClark(1990)
MajorArchitecturalChange
MinorArchitecturalChange
MajorComponentChange
MinorComponentChange
MODULAR INCREMENTAL
RADICAL ARCHITECTURAL
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Finally,radicalinnovationsinvolveanewsetofdesignconceptsthatare
embodiedinnewcomponentsthatarelinkedtogetherusinganewarchitecture
(HendersonandClark1990).Radicalinnovationsarebasedoncompletely
differentscientificandengineeringprinciplestotheprinciplesthatwereusedin
theproductstheysupersede.Withradicalinnovationsmanyareasof
organisationalknowledgeandcompetencearerenderedirrelevant,
consequentlyanorganisationmayhavetoconsidernewwaysofthinkingto
adoptaradicalproductinnovation(Smith2000).
Classificationofagriculturalinnovations
Kaineetal.(2008)adaptedthesystemsapproachofHendersonandClark(1990)
toclassifydifferentkindsofinnovationsinagriculturalsystems.Theychose
innovationstoafarmsub‐systemastheunitofanalysis.Afarmsub‐systemisa
setofcomponentsthatlinktogetherinaspecificwaytoperformafunction
(Kaineetal.2008).Thecomponentsofafarmsub‐systemarethephysically
distinctelementsofthesub‐system.Thecomponentsofafarmsub‐systemmay
includetechnology,techniquesandpractices.Thearchitectureofthesub‐system
describeshowthecomponentsarearrangedorlinkedtogethertoenablethe
sub‐systemtofunction.
Differentfarmsub‐systemsaredesignedtoperformfundamentallydifferent
functions.Forexample,apressureirrigationsystemisagenericdescriptionofa
sub‐systemthatdistributeswatertoplantsusingmechanicalenergy.Integrated
pestmanagementisagenericdescriptionofasub‐systemformanagingpests
anddiseasesbasedontheuseofbeneficialinsectsandspecies‐specific
chemicals.Othersub‐systemsincludeanimalhealth,feedmanagementand
breedingmanagement.
Differentsub‐systemconceptshavedifferentarchitecturesandsoare
underpinnedbydifferentarchitecturalprinciples.Forexample,theprinciplethat
watermovesdownhillundertheinfluenceofgravityunderpinsthearrangement
ofcomponentsinafloodirrigationsub‐system.Incontrast,theprinciplethat
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watermovesfromanareaofhightolowpressureunderpinsthearrangementof
thecomponentsinasprinklerirrigationsub‐system.
Theextentofchangetothecomponentsandarchitectureofafarmsub‐system
provideabasisforclassifyinginnovationsinfarmsub‐systemintothefourtypes
ofinnovation:incremental,modular,architecturalandradical.
Crouch(1981)observedthatfarmsconsistofhierarchiesofinter‐relatedsub‐
systems.Thedifferenttypesofinnovationcanbeexpectedtohavedifferent
effectsontheinteractionsbetweensub‐systems,witharchitecturalandradical
innovationshavinggreatereffectsthanincrementalormodular.Consequently,
dependingonthetypeofinnovation,incorporatingnewtechnologiesor
practicesintoafarmsub‐systemwillrequireknowledgeaboutthesub‐systemto
bechanged,andknowledgeabouthowtorealignothersub‐systemsto
accommodatethatchange.
Kaineetal.(2008)proposedthattheadoptionofeachtypeofinnovationcould
beexpectedtomeanthatdifferentskillsandcompetencieswillbeneededwith
respectto(i)thesub‐systemitself,(ii)theinteractionsbetweensub‐systems
and,(iii)planningtheimplementationoftheinnovation.Thismeansthat
qualitativedifferencescanbeexpectedinthetimeandeffortinvolvedin
implementingthefourdifferenttypesofinnovations,andthattherewillbe
differencesintherateofadoption(orabandonment)ofthedifferenttypesasa
result.
Atthispointitisworthnotingthereislikelytobesymmetryinthecomplexityof
practicesandtechnologieswhenitcomestocompulsorilyabandoningthem.A
technologyorpracticethatwas,forexample,anincrementalinnovationina
farmsub‐systemwhenadoptedwillmostlikelybeanincrementalinnovation
whenabandoned,providedthefarmerreturnstothetechnologiesorpractices
thatweresuperseded.Thefarmer’sfamiliaritywiththetechnologyorpractice
maymeantheycanabandonitrathermorequicklythantheyadoptedit.The
potentialforthiseffectincreaseswiththecomplexityofthetechnologyor
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practice.If,however,thefarmeradoptssomeothertechnologyorpracticein
preferencetothosethatweresupersededthenthetypeofinnovationtothefarm
sub‐systemthatabandonmententailsmayquitedifferenttothatentailedin
adoption.
Returningtothedual‐processmodel,anticipatedemotionswereidentifiedas
potentiallyimportantdeterminantsofgoaldesire.Itmaybethecasethatthereis
limitedemotionalcontentassociatedwithincrementalandmodularinnovations.
Ifso,goaldesireinrelationtoincrementalandmodularinnovationswould
dependmainlyonthefarmers’perceptionsofthetimepathandreliabilityofthe
costsandbenefitsofchangingfarmpracticeortechnology(Wright2011).
Incontrast,itmaybethecasethatimaginedgoalachievementandgoalfailure
havesignificantemotionalcontentwitharchitecturalandradicalinnovations.If
thisisthecase,thentherelativestrengthofpositiveandnegativeanticipated
emotionswillstronglyinfluencegoaldesire.Theanticipatoryemotionsofhope
andfear,andrelatedfactorssuchasperceivedbehaviouralcontroland
anticipateddifficultiesinstrivingarealsolikelytostronglyaffectgoaldesire
witharchitecturalandradicalinnovations.
Inshort,bothanticipatedandanticipatoryemotionsmayplayasubstantialrole
inchangingfarmpracticesandtechnologieswhenthesechangescanbe
characterisedasarchitecturalandradicalbecauseoftheircomplexity;notleast
becauseofthechallengestheymayposetofarmercompetence.Thesamemay
besaidforaffecttowardsthemeans.Thissuggeststhatthedivisionofchangesin
farmingsub‐systemsintoincremental,modular,architecturalandradical
innovationscouldbemostinformativeaboutratesofadoptionandcompliance.
Anapplication
Kaineetal.(2012)conductedasmallpilotstudyintothedual‐processmodeland
theclassificationofinnovationstocroppingsub‐systemsinnorthernVictoria.
Kaineetal.(2012)foundthatanticipatedemotions,anticipatoryemotionsand
affecttowardsmeanswerepresentintheadoptionprocessforbothsimple
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innovationssuchaschangingwheatvarietyandmorecomplexinnovationssuch
asstubbleretentionanddirectdrilling.Theyalsofoundtherelativestrengthof
theseemotionalfactorsincreasewiththecomplexityofinnovations.Thisis
consistentwiththepropositionthattheadoptionofmorecomplexinnovations
requirescorrespondinglygreaterlevelsofmotivationthanlesscomplex
innovations.
Theyalsofoundrelationshipsbetweenthetypeofinnovationandtheneedfor
newskillsanddecisioneffort.Theyalsofoundthatmorecomplexinnovations
wereevaluatedforasignificantlylongerperiodthansimplerinnovationsprior
toadoption.Alloftheseresultswereconsistentwiththeliteratureandhighlight
thattherateofadoptionofcomplexinnovationswillbeinherentlyslower,on
average,thantherateofadoptionofsimplerinnovations(Kaineetal.2012).
Kaineetal.(2012)foundthatcurrentskills,knowledgeandexperiencewere
usefulintheadoptionofcomplexaswellassimpleinnovationsinfarming.
Significantpositivecorrelationswerefoundbetweentheimpactofthe
innovationonthearchitectureofthefarmsystem,theusefulnessofcurrent
skills,currentknowledgeandexperience,anddecisioneffort.Thissuggeststhat
currentknowledgeandexperienceisvitalinthetaskofrealigningfarmsub‐
systemswhenintegratingmorecomplexinnovationsintoafarmsystem.
Thoughnotthefocusoftheirstudy,Kaineetal.(2012)classifiedavarietyof
innovationsthatfarmerscharacterisedassimpleorcomplexintoincremental,
modular,architecturalandradicalcategoriesbasedonfarmers’assessmentsof
thenoveltyofthepracticeortechnology,andtheirimpactonsystem
architecture(seeFigure3)3.Withoneexception,thereisapositiveassociation
betweenfarmer’sratingsofthenoveltyofinnovationsandtheircharacterisation
ofinnovationsassimpleorcomplex.However,theassociationbetweentheir
ratingsofthedegreeofchangeintherelationshipsbetweencomponentsand
theircharacterisationofinnovationsassimpleorcomplexwasweak.
3Theangleoftheaxesisanartifactoftheprogrammeusedtomaptheinnovations,inprinciplethemapcanberotatedtoalignwiththeidealisedmapinfigure2.
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FigureThree:Classificationofcroppinginnovations(redsimple,bluecomplex)
Source:Kaineetal.(2012)
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ThecorrespondencebetweenthetypesofinnovationasmeasuredbyKaineetal.
(2012)andfarmers’characterisationswaspromisingenoughtosuggestthat
thereismeritindevelopingscalestomeasurecomponentandrelationship
changeinfarmsub‐systems.
Overall,Kaineetal.(2012)concludedthatthedual‐processmodelofBagozzi
(2006a),inconjunctionwiththeinnovationclassificationofHendersonand
Clark(1990),showedpromiseasameansforpredictingtherateofadoptionof
agriculturalinnovationsandforprovidingguidanceastohowratesmaybestbe
influenced.
Discussion
ThefindingsofKaineetal.(2012)supportthepropositionthattheadoptionof
morecomplexinnovationsrequiresgreaterdecision‐makermotivation,timeand
effortthansimpleinnovations.Theadoptionofmorecomplexinnovationstakes
longersimplybecausetheyareinherentlymoredifficulttounderstandandto
integrateintothefarmsystem.Thegreatertimeandeffortinvolvedinadopting
morecomplexinnovationsmeanstheiradoptionisalsomoresusceptibleto
delaybecauseofinsufficientmotivation.Inotherwords,complexinnovations
areintrinsically‘stickier’(BallandMankiw1994;Szulanski1996;Ogawa1998;
Sims1998;BilsandKlenow2004;MankiwandReis2006)thansimple
innovations;farmerswillbemoreresistanttoadopting(orbeingcompelledto
abandon)complexinnovationsthansimplerinnovations.
Thesefindingshaveimportantimplicationsforpoliciesintendedtopromote
changeinfarmingtechnologiesandpractices.Fromtheperspectiveofvoluntary
change,differencesinthe‘stickiness’ofinnovationstranslatesintodifferencesin
therateoftheiradoption,andthepotentialforincentivesandextensionto
influencethatrate(seeFigure4).
Forexample,simpleinnovationsrequireverylittlelearningtoimplement.By
definition,thefarmsystemisvirtuallyunchangedbysimpleinnovationsandthe
farmeralreadypossessestheknowledgeandskillsneededtoimplementthem.
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FigureFour:Stickinessintherateofadoptionofinnovations
Largeimprovementinrelativeadvantage
Smallimprovementinrelativeadvantage
ComplexinnovationSimpleinnovation
STALLED SYRUPY
SLUGGISH SWIFT
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Differencesintherateofadoptionofsimpleinnovationswillmostlikelyreflect
differencesintherelativeadvantagetheyoffer:thatis,theirsuperiorityover
currenttechnologyorpractice.Inthesecircumstancestheroleforextensionis
limitedtoraisingawarenessofthepractice.Therateofadoptionofsimple
innovationsislikelytobequitesensitivetotheprovisionofincentivesbecause
simpleinnovationsarerelativelyinexpensiveandlowrisk.Therateofadoption
ofsimpleinnovationswithalargerelativeadvantagewillbe‘swift’.Therateof
adoptionofsimpleinnovationswithasmallrelativeadvantagewillbeslower;
theyare‘syrupy’.
Theadoptionofcomplexinnovationsrequirestheacquisitionofnewknowledge
andskillsbythefarmerandentailsplanningandmakingsubstantialchangesto
thefarmsystem.Differencesintherateofadoptionofcomplexinnovationswill
reflectdifferencesinthetimeandeffortinvolved,aswellasdifferencesinthe
relativeadvantagetheyoffer.Complexinnovationswithalargerelative
advantageare‘sluggish’:theirrateofadoptionwillbeslow.Therateofadoption
ofcomplexinnovationswithasmallrelativeadvantagewillbeevenslower;they
mayevenbe‘stalled’permanently.
Theremaybeanimportantroleforextensioninreducingtheeffortfarmers
mustdevotetosearchingforinformationon,andtolearningabout,complex
innovations,andacquiringtheknowledgeandskillsneededtoimplementthem.
Extensionmayalsoincreasetherateofadoptionifitispossibletoincreasethe
motivationoffarmerstoconsideradoptingtheinnovation.Thiswouldrequire
knowledgeoftherootcauseofthelackofmotivation.Therateofadoptionof
complexinnovationsislikelytobequiteinsensitivetotheprovisionof
incentives,unlessthoseincentivescoveramajorproportionofthecostof
adoptingtheinnovation.
Fromtheperspectiveofcompulsorychangevariationsinthe‘stickiness’of
practicesandtechnologiestranslateintodifferencesintherateofcompliance,
differencesinthelikelihoodandintensityofoppositiontothepolicy,differences
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inapparentcompliance,anddifferencesinthepotentialforincentivesand
extensiontoinfluencecompliance(seeFigure5).
Withregardtosimplepracticesandtechnologies,therateofcompliancewitha
policycompellingtheiruse(ortheirabandonment)islikelytobehighwhilethe
likelihoodandintensityofoppositiontothepolicyislikelytobelow.Thiswillbe
especiallysoiftherelativeadvantageofthechangeinpracticeortechnologyis
small.Inthesecircumstancestheroleforextensionislikelytobelimitedlargely
toraisingawarenessofthepolicy.
Compliancewithrespecttochangingsimplepracticesandtechnologieswitha
smalllossinrelativeadvantageislikelytobehighand‘swift’.Compliancewith
respecttochangingsimplepracticesandtechnologieswithalargerlossin
relativeadvantagemaybehigh,eventually,butcouldhappenmoreslowly,tobe
more‘syrupy’.Thegreaterthelossinrelativeadvantagethegreaterthe
motivationtodelaycompliance.Therateofcomplianceanddegreeofopposition
tothepolicyislikelytobequitesensitivetotheprovisionofincentives,
particularlywherethechangeinpracticeortechnologyentailsasubstantialloss
inrelativeadvantage.
Withregardtochangingcomplexpracticesandtechnologiestherateof
compliancewithapolicycompellingtheiruse(ortheirabandonment)islikelyto
belowerthanwithsimplepracticesandtechnologies.Furthermore,the
likelihoodandintensityofoppositiontothepolicyislikelytobehigh.Thiswill
beespeciallysoifthelossinrelativeadvantageofthechangeinpracticeor
technologyislarge.
Compliancewithrespecttochangingcomplexpracticesandtechnologieswitha
smalllossinrelativeadvantageislikelytobemoderatebut‘sluggish’.
Compliancewithrespecttochangingcomplexpracticesandtechnologieswitha
largelossinrelativeadvantagewillbelowand‘stalled’.
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FigureFive:Stickinessandcomplianceintheuseorabandonmentofpractices
andtechnologies
Largelossinrelativeadvantage
Smalllossinrelativeadvantage
ComplexinnovationSimpleinnovation
SLUGGISH SWIFT
STALLED SYRUPY
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Inthesecircumstancestheroleforextensionappearsproblematic.Wherethe
changeinpracticeortechnologyentailsasubstantialchangeinrelative
advantagetherateofnon‐complianceanddegreeofoppositiontothepolicyis
likelytobequiteinsensitivetotheprovisionofincentives.Thismaybethecase
evenwhereincentivesrepresentasubstantialproportionofthecostofchanging
practiceortechnology.Thereasonisthat,returningtothedual‐processmodel,
changingcomplextechnologiesorpracticesrequiresahighdegreeofmotivation;
thisentailsasubstantialemotionalinvestmentintermsofanticipatoryand
anticipatedemotions,andaffecttowardsmeans.
Thegreatertheemotionalinvestmentinadoptingacomplexinnovation,andthe
relativeadvantageitoffered,thecorrespondinglystrongertheresistanceto
abandoningtheinnovationwillbe,andthegreaterthelikelihoodofoutrage.
Relatedly,whereapolicycompelsadoptionofacomplexpracticeortechnology,
thegreatertheemotionalinvestmentinadoptingthatinnovation,andthe
smallertherelativeadvantageitoffers,thecorrespondinglystrongerthe
resistancetousingtheinnovationwillbe,andthegreaterthelikelihoodof
outrage.
Inthesecircumstancesfarmerswillseektoblockormodifythepolicy,ordelay
itsimplementation.Theywillseekwaysofcomplyingwiththeletterofthepolicy
whileavoidingcomplyingwithitsintent(KaineandHigson2006).Rigorous
enforcement,includingpunitivesanctions,maybetheonlymeansof
substantiallyimprovingcomplianceinthissituation.
Conclusion
Inthispaperanapproachtopredictingtherateofadoptionofagricultural
innovationshasbeendescribed.Theapproachappliesequallytopredictingrates
ofnon‐compliancewithpoliciesprescribingtheuse,orabandonment,of
particularagriculturalpracticesandtechnologies.Theapproachdrawsonthe
dual‐processmodelofconsumerdecision‐makingandamethodforclassifying
innovationsinfarmsystems.Apilotapplicationhasshownthattheapproach
hasmerit.
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