Lab to farm: Mapping knowledge transfer channels and determinants from researchers' perspective. A systematic literature review

Fa ah, Sa a Ben; Ama a, Nabil
A icle
Lab o a m: Mapping knowledge ans e channels and
de e minan s om esea che s' pe spec i e. A sys ema ic
li e a u e e iew
Jou nal o Inno a ion & Knowledge (JIK)
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Sugges ed Ci a ion: Fa ah, Sa a Ben; Ama a, Nabil (2025) : Lab o a m: Mapping knowledge ans e
channels and de e minan s om esea che s' pe spec i e. A sys ema ic li e a u e e iew, Jou nal o
Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 10, Iss. 1, pp. 1-27,
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Lab o a m: mapping knowledge ans e channels and de e minan s om
esea che s’pe spec i e –A sys ema ic li e a u e e iew
Sa a Ben Fa ah
*
, Nabil Ama a
Depa men o Managemen , Facul y o Business, La al Uni e si y, 2325 ue de l’Uni e si ´
e, Qu´
ebec Ci y, QC G1V 0A6, Canada
ARTICLE INFO
JEL classi ica ion:
O32
D83
O13
Keywo ds:
Knowledge ans e
Resea che s
Fa me s
De e minan s
Channels
Resea ch–p ac ice gap
Sys ema ic li e a u e e iew
ABSTRACT
The li e a u e on he esea ch–p ac ice gap in ag icul u e has e ol ed signi ican ly in ecen decades. Al hough
he e is a well-es ablished body o wo k on how a me s adop ag icul u al esea ch ou comes and he ac o s
ha in luence hei adop ion, esea ch on how esea che s pe cei e he p ocess o ans e ing hei esul s o
p ac ical applica ions, along wi h he ac o s ha acili a e o hinde his p ocess, emains inadequa e. This s udy
add esses his gap by conduc ing a sys ema ic li e a u e e iew o empi ical s udies on knowledge ans e and i s
de e minan s om he pe spec i e o ag icul u al esea che s, co e ing publica ions om 1960 o 2024. I o e s
wo key con ibu ions: i s , an o iginal axonomy o he channels h ough which ag icul u al esea ch is
ans e ed o a me s, and second, an in eg a i e concep ual amewo k ha links knowledge ans e o h ee
ca ego ies o in luen ial ac o s, ela ed o esea che s’indi idual cha ac e is ics, he o ganiza ional con ex
wi hin esea ch ins i u ions, and he ex e nal en i onmen . Based on he indings, a esea ch agenda has been
de eloped o se e as a ounda ion o u u e in es iga ions in o pe sis en gaps in he ield. The indings hold
alue o bo h academic and p ac i ione communi ies as hey p o ide deepe insigh s o imp o e he unde -
s anding and p ac ice o knowledge ans e in ag icul u e.
In oduc ion
The eme gence o he knowledge socie y e a in he 1990s
(Ly o chenko e al., 2022) has caused a ansi ion om ag a ian and
indus ial socie ies o a knowledge-based socie y p ima ily s emming
om he widesp ead a ailabili y and abundance o complex and massi e
da a, as well as e olu iona y ad ances in digi al and in o ma ion and
communica ion echnologies (ICTs) (Bilan e al., 2023). The ag icul u al
sec o has no been immune o hese changes, wi h ecen yea s wi -
nessing a wa e o mode niza ion d i en by he widesp ead adop ion o
nex -gene a ion digi al echnologies (NGDTs), such as a i icial in elli-
gence (AI), he in e ne o hings (IoT), big da a (BD), and nano ech-
nology (Pu nama &Seja i, 2023). Rapid scien i ic and echnological
ad ances in he ag icul u al sec o ha e gi en ise o a spec um o e ms
o cha ac e ize hese changes, a iously labeled as “ag icul u e 4.0
″
,
“digi al ag icul u al e olu ion,” “connec ed ag icul u e,” “digi al
a ming,”and “AgTech”(Jakku e al., 2023;Ma in &Schnebelin,
2023). Wi h au oma ed i iga ion sys ems, GPS-guided ac o s, ae ial
image y, soil senso s o AI-d i en c op moni o ing, and
nano ech-enhanced e ilize s, he possibili ies o inno a ion in
ag icul u e a e unlimi ed (Danai-Va sou e al., 2023;Nemade e al.,
2023). Consequen ly, a me s a e becoming da a-d i en decision--
make s (Rozens ein e al., 2024). The in eg a ion o ad anced p edic i e
analy ics, ueled by comp ehensi e and high-quali y da a, empowe s
a me s wi h he capabili y o access up- o-da e and ele an in o ma-
ion on a ious aspec s, such as wea he o ecas s, ma ke dynamics,
p icing o ag icul u al inpu s (e.g., seeds, e ilize s, and pes icides), and
ad anced a ming echniques (Fa ooqui e al., 2024;Ka una hilake
e al., 2023;Rozens ein e al., 2024). O e all, hese ad ances empowe
a me s o make mo e in o med decisions, e ec i ely manage on- a m
p oduc ion, and p oac i ely op imize a m e iciency.
Ag icul u al inno a ion begins in esea ch labo a o ies and in-
s i u ions, whe e inno a i e ideas and cu ing-edge echnologies a e
de eloped. Resea ch and de elopmen (R&D) in ag icul u e emains a
p io i y o di e se s akeholde s, including go e nmen bodies, public o
p i a e esea ch ins i u ions, and highe educa ion ins i u ions (HEIs).
(Anandajayaseke am, 2022;Yongabo &G¨
ok epe-Hul ´
en, 2021). In he
con ex o esea ch p omo ion, unde s a e ocused on bols e ing he
scien i ic p oduc i i y o esea che s and p omo ing esea ch excellence
among schola s and HEIs (A no e al., 2020). Howe e , despi e he
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (S.B. Fa ah).
Con en s lis s a ailable a ScienceDi ec
Jou nal o Inno a ion &Knowledge
jou nal homepage: www.else ie .com/loca e/jik
h ps://doi.o g/10.1016/j.jik.2025.100650
Recei ed 8 July 2024; Accep ed 1 Janua y 2025
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
2
in ol emen o nume ous esea che s in ad ancing knowledge, he
ag icul u al esea ch communi y o en encoun e s di icul ies in ans-
e ing i s esea ch esul s beyond he con ines o he ins i u ion (Ansa i
e al., 2016;Hoˇ
ce a &Is eniˇ
c, 2014;I eanyi-obi &Asuquo, 2023;
Theodo akopoulos e al., 2012;Yaakub e al., 2011). P ac ical applica-
ions o ag icul u al esea ch emain subop imal. Scien i ic esea ch
ou comes a e o en elega ed o o go en d awe s and a e unde u ilized
o e en dis ega ded al oge he in ag icul u al p ac ice (Kou sou is,
2012). Consequen ly, he ans e o e idence-based knowledge o
ac ionable ou comes in ag icul u e emains a complex and mul i ace ed
challenge (Chen &Li, 2022;McCown, 2001;Theodo akopoulos e al.,
2012).
Resea che s ace challenges in in eg a ing a me -cen ic needs
wi hin esea ch p ojec s, whe eas a me s pe cei e scien i ic esea ch as
dis an o i ele an o hei ag icul u al p ac ices (Bayissa, 2015a). The
di e gence o p io i ies be ween esea che s, d i en by a ques o
heo e ical knowledge and p og ess, and p ac i ione s gea ed owa ds
sol ing conc e e, eal-wo ld p oblems, hinde s he alignmen o scien-
i ic esul s wi h ield applica ions (Ama a e al., 2019;Caplan, 1979),
especially since he p ocess o gene a ing scien i ic knowledge is highly
ime-consuming and can span se e al yea s. Resea che s spend ime in
comp ehensi e s udies, whe eas p ac i ione s seek imely, p agma ic,
and angible solu ions o add ess immedia e issues (Ama a e al., 2019;
C uz e al., 2022;Tucke &Lowe, 2014). Consequen ly, an
e e -widening gap pe sis s be ween he scien i ic and ag icul u al
communi ies (Abe eijo, 2015;Ca ayannis e al., 2018;Du ´
eni e al.,
2016;Higgins, 1991;McCown, 2001;Roma´
nczyk e al., 2012). This
esea ch–p ac ice gap es ic s he e ec i e ans e o inno a i e solu-
ions om scien i ic knowledge o ac ionable p ac ices (Bansal e al.,
2012;B¨
ockel e al., 2021;Ca e , 2008;Neal e al., 2015;Tucke &
Lowe, 2014;Tucke &Pa ke , 2014), begging he impo an ques ion o
how o b idge he esea ch–p ac ice gap in ag icul u e o enhance he
e ec i e ans e o scien i ic indings among a me s. Al hough
esea ch p o ides signi ican insigh s in o how a me s adop new
ag icul u al p ac ices and wha ac o s in luence hei decisions, less is
known abou how esea che s pe cei e he p ocess o ans e ing hei
indings o p ac ical applica ions in ag icul u e (C uz e al., 2022). This
s udy sys ema ically e iews he s a e o knowledge ans e om e-
sea che s’pe spec i es, wi h a wo-p onged aim: i s , o de elop a
axonomy o knowledge ans e channels be ween ag icul u al esea ch
and a me s, and second, o iden i y, om he esea che s’pe spec i e,
he ac o s ha ei he acili a e o hinde his ans e . To his end, his
s udy explo ed h ee key esea ch ques ions.
1. How has he esea ch–p ac ice gap been concep ualized in ag icul-
u al li e a u e?
2. Wha o mal and in o mal channels do ag icul u al esea che s use o
ans e knowledge o a me s?
3. Wha ac o s se e as acili a o s o ba ie s o closing his gap?
To add ess hese esea ch ques ions, his s udy employs a igo ous
and comp ehensi e sys ema ic li e a u e e iew (SLR), analyzing a
co pus o a icles spanning >60 yea s. Based on he indings o his
ex ensi e analysis, i p oposes a esea ch agenda ha ou lines key ec-
ommenda ions and p omising u u e esea ch a enues.
The emainde o his pape is o ganized as ollows. Sec ion 1 p o-
ides an in-dep h o e iew o he me hodological p o ocols used in his
s udy, elabo a ing on he SLR me hod used o iden i y, selec , analyze,
and syn hesize he ele an li e a u e o he pas 64 yea s. Sec ion 2
p esen s he desc ip i e and analy ical indings, based on which an
in eg a i e concep ual amewo k o knowledge ans e and i s de-
e minan s wi hin he ag icul u al sec o a e de eloped. Finally, Sec ion
3 highligh s he key con ibu ions, ou lines he esea ch agenda o
u u e s udies, and add esses i s limi a ions.
Me hod
Ra ionale o using he sys ema ic li e a u e e iew
This s udy adop ed he SLR me hod o p o ide a s a e-o - he-a e-
iew o knowledge ans e in he ag icul u al sec o . Unlike o he ypes
o e iews (e.g., na a i e li e a u e e iews and scoping li e a u e e-
iews), he SLR is a igo ous, exhaus i e, eplicable, and anspa en
esea ch me hod ha in ol es a s uc u ed p ocess o iden i ying,
selec ing, analyzing, and summa izing exis ing esea ch on a speci ic
opic (Denye &T an ield, 2009;Saue &Seu ing, 2023).
Such an app oach is used o se e al easons. Knowledge ans e is a
mul idisciplina y ield o en subjec o a wide ange o esea ch con-
duc ed ac oss di e en disciplines and sca e ed ac oss di e se publi-
ca ions and jou nals. Many a icles on his opic ha e been published in
scien i ic jou nals ha do no specialize in ag icul u e. Second, se e al
s udies ha e ocused on he gap be ween ag icul u al esea che s and
a me s, hei esul s a e no linked o an in eg a i e concep ual
amewo k. Because cu en knowledge has been de eloped in silos, his
does no allow o he de elopmen o a holis ic iew o s a e-o - he-a
knowledge ans e om ag icul u al esea che s o a me s. Thi d,
esea ch on knowledge ans e be ween ag icul u al esea che s and
p ac i ione s in he ag icul u al milieu has expe ienced a su ge o in-
e es since he de elopmen o di usion models o ag icul u al inno-
a ion in he ea ly 1960s (Roge s, 1962). As a esul , he ex an
li e a u e on his opic has ailed o p o ide a comp ehensi e unde -
s anding o he gap be ween hese wo communi ies o p ac ice. An SLR
migh be an e icien me hod o o ganizing a s a e-o - he-a knowledge
ans e om ag icul u al esea che s o a me s, p o iding a comp e-
hensi e o e iew ha canno be ob ained h ough a single o ew s udies
and os e ing po en ial a enues owa ds no el b eak h oughs and ad-
ances in bo h heo y and p ac ice.
In 2016, a li e a u e e iew (no an SLR) was conduc ed by Elueze on
knowledge ansla ion in ag icul u e, which p ima ily in ended o
examine he knowledge ans e p ocess in ag icul u e ollowing he
La is knowledge ans e amewo k (La is, 2003). This amewo k is
based on i e co ne s ones: he message, a ge audience, messenge , KT
p ocess and suppo sys em, and e alua ion o he e ec o he knowl-
edge ans e ed. The indings o his s udy highligh ha ag icul u al
esea che s a e he main messenge s o knowledge ans e o a me s,
and ha , no wi hs anding a a ie y o po en ial use s o ag icul u al
knowledge, he mos popula a ge audience o esea che s is a me s.
The au ho called o mo e s udies ocusing on knowledge ans e o
policymake s o be e e idence-based policy decisions, and a u he
explica ion o he ole played by lib a ies and in o ma ion science p o-
essionals in ag icul u e esea ch knowledge ans e . Howe e , Elueze
(2016) did no , like he p esen s udy, aim o iden i y he knowledge
ans e channels used by ag icul u al esea che s o each a me s no
build an in eg a i e concep ual amewo k linking knowledge ans e
om ag icul u al esea che s o a me s o i s de e minan s.
Resea ch ques ions
This SLR aimed o p o ide a comp ehensi e syn hesis o exis ing
esea ch ha sa is ies ou inclusion and exclusion c i e ia, o e ing a
de ailed unde s anding o how he esea ch–p ac ice gap is pe cei ed
and add essed wi hin he ag icul u al communi y. Speci ically, he
sys ema ic li e a u e e iew a emp s o answe he ollowing ques ions:
1) How has he gap be ween esea ch and p ac ice been concep ualized
in he ag icul u al li e a u e? (2) Wha a e he o mal and in o mal
means o knowledge ans e used by ag icul u al esea che s o each
a me s? 3) Wha a e he le e s and impedimen s, om he pe spec i e
o ag icul u al esea che s, ha may explain his gap?
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
3
Sea ch s a egy
The SLR was pe o med using he SALSA amewo k (Boo h e al.,
2013;G an &Boo h, 2009), which p o ides an explici , ans e able,
and ep oducible p ocedu e o conduc ing i (Ga cía-Holgado e al.,
2020;Mengis e al., 2020;Yeboah e al., 2023). I encompasses a
ou -s age p ocess—sea ch, app aisal, syn hesis, and analysis (SALSA)—
he i s o which is he “sea ch s age” ha aims o ga he a p elimina y
lis o publica ions o analyze. I deals wi h sea ch s a egy and deli e y,
no ably he de ini ion and cons uc ion o he keywo d chain and he
choice o ele an da abases o collec in o ma ion. Second, he
“app aisal s age”in ol es wo basic s eps: 1) iden i ying he ele an
a icles based on inclusion and exclusion c i e ia, and 2) assessing he
quali y o selec ed a icles. Thi d, he “syn hesis s age”consis s o bo h
ex ac ion and classi ica ion o ele an da a om selec ed pape s.
Finally, he “analysis s age”in ol ed assessing he syn hesized da a,
ex ac ing signi ican in o ma ion and d awing conclusions om he
selec ed a icles. He e, he SLR was analyzed agains he SALSA ame-
wo k desc ibed nex .
S age 1: sea ch
Boo h e al. (2013) ad ise ha any li e a u e sea ch isks missing
ele an i ems gi en he inclusion and exclusion c i e ia used o conduc
he sea ch. To add ess his p oblem, a sea ch was conduc ed using he
b oades possible e ms ela ed o he knowledge gap be ween ag icul-
u al esea che s and a me s. An expe lib a ian co obo a ed he
choice o he ele an da abases. The sea ch encompassed h ee mul i-
disciplina y elec onic da abases –Web o Science (Cla i a e Analy ics),
ABI/In o m Global (P oQues ), Business Sou ce P emie (EBSCO) –and
wo specialized elec onic da abases –CAB Abs ac s (OVID), E ic
(EBSCO). These da abases we e selec ed because hey p o ide a la ge
co e age o he ele an li e a u e. The ac ha he concep o he
knowledge gap be ween esea ch and p ac ice has been he subjec o
con ibu ions om a ious esea ch ields (e.g., Chi, 2021 –educa ion;
Newnam e al., 2020 –medicine; G eene, 2021 –psychology; I ano
e al., 2021 –managemen ) jus i ies he use o mul idisciplina y da a-
bases. The da abases we e accessed om he websi es o he au ho s’
uni e si y lib a ies. The expe lib a ian also pa icipa ed in building a
keywo d chain. The lis o keywo ds was ob ained by snowballing,
which included bibliog aphic e e encing, back- e e encing ( e iewing
he e e ences o included s udies), and ci a ion acking (Pe ic ew &
Robe s, 2006). The keywo d chain combined h ee key concep s. The
i s key concep e e ed o he heme o knowledge ans e , he second
included keywo ds ela ed o academic and scien i ic ields, and he
hi d included keywo ds ela ed o ag icul u e. These concep s and hei
synonyms we e used in a ious combina ions wi h Boolean ope a o s
“AND”( o ob ain esul s ha include all sea ch e ms simul aneously)
and “OR”( o include al e na i e e ms o synonyms). The ollowing
keywo ds we e used o iden i y ele an a icles.
T ans e * OR “knowledge ans e ”OR di us* OR “knowledge
di usion”OR dissemina * OR “knowledge dissemina ion”OR ansla *
OR “knowledge ansla ion”OR up ake* OR “knowledge up ake”OR
exchange OR “knowledge exchange”OR sha * OR “knowledge sha ing”
OR “knowledge ci cula ion”OR “knowledge sp ead”OR “know-how
ans e ”OR “knowledge ansmission”OR gap OR “knowledge gap”OR
“ esea ch–p ac ice”OR “ esea ch–p ac ice gap”OR implemen * OR
“knowledge implemen a ion”OR knowledge applica ion* AND
Resea ch* OR p o esso * OR scien* OR academic* OR “ag icul u al
esea che ”OR schola * OR “ag icul u al esea che s”OR “scien i ic
communi y”OR “scien i ic communi ies”OR acul y membe * OR ac-
ul * OR “ esea ch ins i u es”OR uni e si * OR highe educa ion ins i-
u ion* OR HEI* OR esea ch cen e * AND ag icul * OR a m* OR a m
wo ke * OR ag icul u al wo ke * OR u al sec o OR u al* OR ag i-
cul u al labo e * OR u al a m esiden * OR ag icul u al business OR
ag icul u al communi * OR ag icul u al p oduce * OR ag icul u al
agencie*
All a icles om each da abase we e indexed using Endno e so wa e.
Then, an examina ion o all iden i ied a icles was ca ied ou . A e
elimina ing 732 duplica e s udies, 5837 po en ially unique eligible a -
icles o his sys ema ic li e a u e e iew we e ob ained (Table 1).
S age 2: app aisal
This s age mainly in ol ed he applica ion o he exclusion and in-
clusion c i e ia es ablished wi h espec o he esea ch ques ions. These
c i e ia, along wi h a desc ip ion o he s udy a ionale, a e p esen ed in
Table 2.
Each a icle was sequen ially e alua ed based on hese c i e ia and
was excluded i any c i e ion was no me . The si ing p ocess had ou
s ages. All i les, keywo ds, and abs ac s we e e iewed o elimina e
publica ions ha did no ocus on he ans e o ag icul u al knowledge
om esea che s o a me s. This i s sc eening p ocedu e enabled he
exclusion o 4731 a icles ha did no mee all he c i e ia. Subse-
quen ly, a second, deepe shi ing based on a eading o he me hodol-
ogy and esul s o he s udy was pe o med on he 1106 a icles
emaining om he i s sc eening. This so ing elimina ed 1034 a icles.
The emaining 72 a icles we e examined in de ail. A de ailed analysis o
he ull ex s allowed he elimina ion o 45 pape s; hus, 27 a icles
emained. Finally, one-s ep backwa d snowballing (Jalali &Wohlin,
2012) was pe o med on he emaining 27 pape s. To achie e his, a
sys ema ic hand sea ch was conduc ed on he e e ence lis s o he inal
se o selec ed a icles o iden i y addi ional ele an a icles ha had
no been unco e ed h ough p e ious sea ch s a egies. This sea ch
allowed o he inco po a ion o h ee supplemen a y publica ions
(Pauno i´
c e al., 2022;Ra hod e al., 2018). Finally, he se o analyzed
pape s ha ma ched all he inclusion c i e ia amoun ed o 30 a icles
published in 26 di e en pee - e iewed jou nals. This numbe is com-
pa able o he numbe o selec ed a icles in se e al o he li e a u e
e iews in di e en esea ch ields (e.g., Elueze (2016): T ansla ion in
ag icul u e (27 a icles); Ra ajczak &Szu owski (2016): CSR and inno-
a ion (24 a icles); Clou ie &Ama a (2023): Inno a ion coope a ion
o manu ac u ing SMEs (29 a icles)). The low diag am in Fig. 1
summa izes he successi e elec onic and manual i e a ions, leading o
he inal selec ed se o a icles o analysis.
S ages 3 and 4: syn hesis and analysis
All 30 selec ed a icles we e managed using compu e -based
me hods ollowing he app oach ou lined by Pe ic ew (2006). Fo his
s udy, a Mic oso Excel da abase was de eloped o e ec i ely summa-
ize key in o ma ion om each a icle. This da abase included he de-
ails, such as he a icle’s e e ence, explici de ini ions o knowledge
ans e and i s de e minan s, channels used by esea che s o dissemi-
na e hei esea ch indings, uni o analysis conside ed, me hodological
app oach u ilized, analy ical echniques applied, geog aphical con ex
o he s udy, and o he ele an da a. The da abase se ed as a aluable
Table 1
Resul s o elec onic da abases sea ch.
DATABASE SCIENTIFIC
ARTICLES
IDENTIFIED
DUPLICATES UNIQUE ITEMS
MULTIDISCIPLINARY DATABASES
Web o science
(Cla i a e
Analy ics)
1437 289 1148
ABI/INFORM global
(P oQues )
1523 91 1432
Business Sou ce
P emie (EBSCO)
991 42 949
SPECIALIZED DATABASES
CAB (OVID) 2150 268 1882
E ic (EBSCO) 468 42 426
TOTAL 6569 732
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
4
ool o o ganizing and syn hesizing he collec ed in o ma ion, enabling
a comp ehensi e analysis o he indings om he selec ed a icles.
The esul s o he syn hesis and analysis o he esea ch ma e ial
co esponding o he las wo s eps o he SALSA me hod, a e desc ibed
in de ail in he Resul s sec ion. Fi s , he gene al ea u es o he included
s udies a e p esen ed. Subsequen ly, he analy ical indings om he
selec ed s udies a e discussed, enabling 1) edi ying an in eg a i e con-
cep ual amewo k linking ag icul u al knowledge ans e wi h i s le-
e s and ba ie s, and 2) p oposing a esea ch agenda ha highligh s he
mos p omising oppo uni ies o u u e esea ch.
Resul s
Gene al cha ac e is ics o he selec ed s udies
Dis ibu ion o he a icles by publica ion ou le
Table 3 shows he dis ibu ion o he 30 a icles selec ed om he 26
jou nals. The Jou nal o Ag icul u al Educa ion &Ex ension, Jou nal o
Ag icul u al &Food In o ma ion and he Ame ican Jou nal o Human
Ecology each ha e wo a icles. All he o he jou nals ha e only one
a icle each. The hi d o he a icles (10 ou o 30 a icles) we e pub-
lished in jou nals belonging o he i s and second qua iles (Q1 and
Q2), acco ding o he jou nal impac ac o anking o he Web o Sci-
ence Jou nal o Ci a ion Repo (e.g., Techno a ion; Biological Conse a-
ion; Ecological Economics; Technological Fo ecas ing &Social Change;
Jou nal o Ag icul u al Educa ion &Ex ension). The lis o jou nals iden-
i ied om he SLR e eals a di e se a ay o publica ions co e ing
se e al ields ele an o ou esea ch. This b oad disciplina y spec um
esul s in a agmen ed esea ch landscape as s udies span mul iple
domains, leading o a mo e dispe sed body o wo k.
Table 2
Exclusion and inclusion c i e ia.
CRITERIA
TYPE
CRITERIA RATIONALE
INCLUSION CRITERIA
Type o
documen
The selec ed documen s consis
o scien i ic pape s published
in pee - e iewed jou nals,
emphasizing he impo ance o
ensu ing he eliabili y o he
indings.
The a icles a e published in a
scien i ic pee - e iewed jou nal,
which no ably excludes books
(and book chap e s), essays,
mas e heses, doc o al heses,
esea ch no es, disse a ions,
and con e ence p oceedings, e c.
Addi ionally, o inclusion in he
e iew, he ull- ex e sion o
he a icles had o be accessible
o ensu e no b oken links o
limi a ions o accessing he
comple e con en .
Focus a ea The p ima y ocus o he
selec ed a icles is on he
knowledge ans e wi hin he
ag icul u al ield.
The a icles ha speci ically
discuss he concep o
knowledge ans e o he gap
be ween esea ch and p ac ice
in he ag icul u al con ex we e
chosen. Addi ionally, he
selec ed a icles had o o e
subs an ial in o ma ion o
acili a e a comp ehensi e
e iew o he ac o s in luencing
knowledge ans e in
ag icul u e. They we e o
speci ically a ge he esea ch
pe spec i e when examining he
in luen ial ac o s o knowledge
ans e om ag icul u al
esea che s o ag icul u al
communi y.
Uni o
analysis
The uni o analysis o his
s udy encompasses indi idual
esea che s, uni e si ies,
esea ch ins i u ions, and o he
o ganiza ions in ol ed in
p oducing scien i ic esea ch
wi hin he ag icul u al ield.
The uni o analysis o his
s udy was selec ed s a egically.
This decision was guided by ou
speci ic ocus on iden i ying he
ba ie s and acili a o s ha
ope a e ups eam in he
knowledge ans e p ocess,
pa icula ly a he le el o
knowledge p oduce s
( esea che s).
Language The selec ed a icles a e
published in English.
Only a icles w i en in he
English language we e
conside ed o inclusion in he
SLR. This decision was aken
because a signi ican p opo ion
o in luen ial scien i ic
publica ions in schola ly
jou nals a e published in
English. By limi ing he e iew
o English-language a icles, he
s udy aimed o encompass a
subs an ial body o ele an and
impac ul esea ch in he ield o
ag icul u al knowledge ans e
(Duszak &Lewkowicz, 2008;
Henshall, 2018).
Tempo ali y The selec ed pape s we e
published be ween Janua y
1960 and June 2024
inclusi ely.
The a ionale behind selec ing
1960 as he e e ence poin o
ou sea ch is o ace he
de elopmen o li e a u e on
knowledge and inno a ion
di usion wi hin he ag icul u al
domain, s a ing om he
seminal wo k o Roge s (1962).
The choice o 2024 as he
concluding yea was because i
was he mos ecen yea .
Consequen ly, his ime ame
was expec ed o encompass he
g ea majo i y o publica ions
Table 2 (con inued)
CRITERIA
TYPE
CRITERIA RATIONALE
ela ed o he subjec ma e
unde e iew.
Me hod All ypes o empi ical pape s,
including quan i a i e,
quali a i e, and mixed-
me hods s udies, we e
included.
By ocusing on empi ical
s udies, his SLR aimed o
iden i y he de e minan s o
knowledge ans e conside ed
ac oss a ious con ex s and
se ings and highligh he mos
ecu en p edic o s o
knowledge ans e in
ag icul u e.
EXCLUSION CRITERIA
Type o
documen
All published s udies o he
han a icles published in
scien i ic jou nals, a e
excluded om he SLR, namely
books (books and book
chap e s), essays, esea ch
no es, con e ence p oceedings,
le e s, sho s o ies,
disse a ions, doc o al heses,
g ey li e a u e, including non-
pee - e iewed a icles, e c.
A icles no a ailable in ull
ex we e also excluded.
The exclusion o hese ypes o
documen s was ca ied ou
based on he consensus among
se e al au ho s ha impo an
scien i ic con ibu ions a e
p ima ily published in
in e na ional pee - e iewed
jou nals, which end o ha e
high impac on he ield (
Elsbach &Van Knippenbe g,
2020;Pos e al., 2020).
The e o e, o uphold he quali y
o he s udy, only pee - e iewed
a icles om schola ly jou nals
we e included in he e iew.
Focus a ea A icles ha do no p ima ily add ess knowledge ans e wi hin he
ag icul u al ield we e excluded
Uni o
analysis
A icles ha add ess uni s o analysis no di ec ly in ol ed in he
p oduc ion o scien i ic esea ch wi hin he ag icul u al ield (such
as a me s, p oduce unions, e c.) we e excluded.
Language A icles published in languages o he han English we e excluded.
Tempo ali y Pape s published ou side he speci ied ime ame (be o e Janua y
1960 and a e June 2024) we e excluded.
Me hod Non-empi ical s udies (all o he me hods (e.g., heo e ical/
concep ual)) we e excluded.
S.B. Fa ah and N. Ama a

Jou nal o Inno a ion & Knowledge 10 (2025) 100650
5
Publica ion end and coun ies s udied
O e all, he end shows a g owing in e es in ans e ing ag icul-
u al esea ch o a me s o e he pas ew decades, wi h a no able in-
c ease in ecen yea s (Fig. 2). The indings showed ha he numbe o
publica ions ela ed o he ans e o ag icul u al esea ch o a me s
inc eased signi ican ly be ween 2013 and 2024. In 2013, he e was a
sligh inc ease wi h h ee publica ions, ollowed by a signi ican inc ease
in 2015, wi h i e publica ions. Be ween 2016 and 2018, he numbe o
publica ions s abilized sligh ly, wi h wo publica ions each yea , sug-
ges ing sus ained in e es bu a a mode a e pace. Be ween 2016 and
2021, publica ions con inued a a s eady pace, wi h wo publica ions
each yea om 2016 o 2018, and one publica ion each yea om 2019
o 2021. The e was a ma ked inc ease be ween 2022 and 2023, wi h ou
publica ions in 2022 and wo in 2023. Publica ions we e spo adic om
1995 o 2012, wi h only one publica ion each in six yea s o his pe iod,
indica ing pe haps a educ ion in p io i y o he opic o ans e ing
ag icul u al esea ch o a me s. Howe e , mos o he a icles (24 o 30)
we e published in he las decade, sugges ing a clea gain in p ominence
o he opic in ag icul u al science esea ch, pa icula ly a e 2012.
The dis ibu ion o a icles by con y e lec s he coun y being
s udied in he a icle a he han he au ho (s)’coun y o o igin. This
dis ibu ion shows ha almos all (28) used da a collec ed om only one
coun y. The only wo excep ions a e Maas e al. (2021), which ocused
on Ge many and Aus ia, and Da id e al. (2010), which examined India
and E hiopia. The mos s udied coun y is Nige ia, wi h 5 o he 30 a -
icles, ep esen ing 16.67 % o he o al (Fabo odee &Ajayi, 2015;
I eanyi-obi &Asuquo, 2023;I eanyieze e al., 2017;Mgbenka e al.,
2013;Okocha, 1995). E hiopia and I an ollowed wi h ou (13.33 %)
a icles each (E hiopia –Ayalew &Abebe, 2018;Bayissa, 2015a,2015b,
2015c; I an –Ahmadinejad, 2020;Ansa i e al., 2016;Ka amidehko di,
2013;Tahe i e al., 2022). The Uni ed S a es ollows wi h h ee,
accoun ing o 10 % o he o al (Du am &La son, 2001;Ge son e al.,
2022;La son &Du am, 2000). Twel e coun ies, Spain, Sou h A ica,
Colombia, India, Russia, Aus alia, Bulga ia, Indonesia, Mozambique,
Slo enia, Slo akia, and S i Lanka, we e ep esen ed by one a icle each.
When conside ing he dis ibu ion o selec ed s udies in majo wo ld
egions, A ica had he highes p opo ion (37 %). Asia ollowed wi h 23
%, Eu ope 16.67 %, No h Ame ica (USA) 10 %, Sou h Ame ica 3.33 %,
and o he con inen s, 3.33 %. S udies in ol ing mul iple con inen s
accoun ed o 6.67 % o he o al (see Fig. A.1 in Appendix A).
Publica ion ends by uni o analysis and ields s udied
The dis ibu ion o a icles acco ding o he uni o analysis shows a
ocus on mul i-uni s udies, encompassing ag icul u al esea che s and
o he s akeholde s ( e e o Fig. A.2 in Appendix A). These s udies
ep esen 46 %, o 14 o 30 a icles (e.g., Ansa i e al., 2016;Ka -
amidehko di, 2013;Simbe, 2022;Tahe i e al., 2022;Wheele , 2008).
Following closely a e s udies ocusing speci ically on ag icul u al e-
sea che s, wi h 40 %, o 12 o 30 a icles (e.g., I eanyi-obi &Asuquo,
2023;La son &Du am, 2000;Maas e al., 2021). Uni e si ies, esea ch
cen e s, and esea ch ins i u es each accoun o 7 %, o 2 o 30 a icles
each (e.g., Di imano a &Rade , 2017;Theodo akopoulos e al., 2012;
Thu ne &Zaichenko, 2018).
The dis ibu ion o a icles in he ield o applica ion indica es ha
gene al ag icul u e is by a he mos s udied ield, accoun ing o 67 %
o he a icles (20 o 30) (e.g., Ahmadinejad, 2020;Ansa i e al., 2016;
Okocha, 1995). This was ollowed by sus ainable ag icul u e, ep e-
sen ing 13 % (4) (e.g., La son &Du am, 2000;Maas e al., 2021). Less
equen ly co e ed ields include ag icul u al inno a ion and he com-
bina ion o ish a ming and co ee p oduc ion, each accoun ing o 7 %,
o wo a icles (e.g., Theodo akopoulos e al., 2012), and u al and
o ganic ag icul u e, ep esen ed by one each (e.g., Wheele , 2008) ( e e
Fig. 1. The sys ema ic li e a u e e iew low diag am.
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
6
o Fig. A.3 in Appendix A).
Dis ibu ion o a icles by me hodological app oach and da a collec ion
echnique
The mos used me hodology is quan i a i e, appea ing in 47 % o he
a icles (14) (e.g., C uz e al., 2022;Ge son e al., 2022). This is ollowed
by quali a i e me hodology, used in 13 a icles, o 43 % (e.g., Ansa i
e al., 2016;Fongwa &Ma ais, 2016;Hoˇ
ce a &Is eniˇ
c, 2014;Ka -
amidehko di, 2013). This dis ibu ion e eals a nea ly spli be ween he
quan i a i e and quali a i e me hodologies, indica ing ha bo h ypes o
analysis we e alued almos equally. Mixed me hods, which combine
bo h quan i a i e and quali a i e app oaches, we e used in he
emaining h ee (10 %) (e.g., I eanyi-obi &Asuquo, 2023) ( e e o
Fig. A.4 in Appendix A).
Table 4 de ails he a ious analy ical echniques u ilized in he
selec ed a icles. Con en analysis is he mos p e alen , ea u ing in 30
% o he a icles (e.g., Ansa i e al., 2016;Fongwa &Ma ais, 2016;
Hoˇ
ce a &Is eniˇ
c, 2014). Mul i a ia e eg ession echniques accoun
o 16.7 % o he a icles, wi h speci ic echniques unde his ca ego y
including s uc u al equa ion modeling (Ahmadinejad, 2020;Tahe i
e al., 2022), logis ic eg ession (Thu ne &Zaichenko, 2018), and o -
de ed p obi eg ession (Wheele , 2008). Mul i-quan i a i e me hods (e.
g., Du am &La son, 2001;Maas e al., 2021) and in e en ial s a is ics (e.
g., Kau &Kau , 2013;Mgbenka e al., 2013) each we e used in 13.3 %
o he a icles. Quali a i e-quan i a i e me hods appea in 10 % o he
a icles (e.g., Okocha, 1995). Case s udies (e.g., Ka amidehko di, 2013),
ac ion esea ch (e.g., Theodo akopoulos e al., 2012), mul i-quali a i e
me hods (e.g., Dha mawan e al., 2023), and P incipal Componen
Analysis (PCA) (C uz e al., 2022) we e less commonly used.
Table 5 p esen s he dis ibu ion o a icles based on da a collec ion
me hods. Fou een a icles (46.67 %) used su eys (e.g., Ayalew &
Abebe, 2018;Maas e al., 2021;Tahe i e al., 2022;Wije a hna e al.,
2015), ollowed by mul iple da a collec ion me hods (6 o 20 %,) (e.g.,
I eanyi-Obi &Asuquo, 2023;Ka amidehko di, 2013). In e iews (e.g.,
Ansa i e al., 2016;Bayissa, 2015a;Dha mawan e al., 2023) we e used
in eigh (26.67 %), whe eas documen a ion me hods (e.g., Ja ´
abko ´
a,
2019) and wo kshops and aining (e.g., Theodo akopoulos e al., 2012)
we e he leas common, each accoun ing o 3.33 % (one a icle).
Analy ical indings
Pu ing he knowledge ans e in ag icul u e unde he mic oscope: cu en
de ini ions
Th ough he syn hesis o 30 a icles in he SLR, a ious de ini ions
associa ed wi h he concep o knowledge ans e in he ag icul u al
ield we e disce ned (Table 6), which can be app oached om h ee
pe spec i es. 1) De ini ions ha pe cei e knowledge ans e as a
sequen ial p ocess: his pe spec i e iews knowledge ans e as a p o-
cess ha enables knowledge p oduc ion by scien i ic esea che s and i s
subsequen applica ion in he ag icul u al sec o and is closely aligned
wi h he knowledge-d i en model, also known as he “science push
model”(Dilling &Lemos, 2011;Land y e al., 2001;Weiss, 1979). These
de ini ions unde sco e he impo ance o ensu ing ha esea ch ou -
comes each a me s and ag icul u al p ac i ione s. 2) De ini ions ha
highligh he in e ac i e aspec s o he knowledge ans e p ocess: om
his pe spec i e, knowledge ans e is an in e ac i e p ocess in ol ing
mul iple s akeholde s, including esea che s, a me s, ex ension
wo ke s, policymake s, and o he ele an ac o s wi hin he ag icul u al
ecosys em. I aligns wi h he “in e ac i e model,”which ecognizes he
non-linea , collabo a i e and dynamic na u e o knowledge ans e
p ocess (Land y e al., 2001). 3) De ini ions ha conside knowledge
ans e as a p oblem-sol ing mechanism o p ac ical solu ions and
eal-wo ld bene i s: his pe spec i e conside s knowledge ans e as a
mechanism o add essing speci ic challenges in he ag icul u al sec o
and ensu ing ha scien i ic ad ancemen s ansla e in o angible so-
cioeconomic bene i s. This aligns wi h he “p oblem-sol ing model,”
also known as he “demand-pull model”(Land y e al., 2001;Weiss,
1979;Yin &Moo e, 1988). The ans e o ag icul u al esea ch is
guided by he iden i ica ion and p io i iza ion o p oblem-o ien ed
esea ch ha di ec ly esponds o he needs and p oblems aced by he
ag icul u al communi y.
Theo e ical ancho age o he selec ed s udies
The SLR e ealed ha a majo i y o he a icles (20, o 66.66 %) did
no explici ly d aw upon heo e ical ounda ions o s udy knowledge
ans e in he ag icul u al sec o . The lack o a uni ied amewo k has
likely led o a agmen ed app oach o he s udy o knowledge ans e ,
esul ing in a ple ho a o pe spec i es ha s uggle o p o ide a
comp ehensi e unde s anding o he p ocess wi hin he ag icul u al
con ex . Table 7 p o ides a comp ehensi e o e iew o he dis inc
Table 3
Dis ibu ion o he e ained a icles acco ding o he jou nals (edi o ial end).
NAME OF THE JOURNAL NUMBER OF
ARTICLES
CATEGORY
1. JOURNAL OF AGRICULTURAL
EDUCATION &EXTENSION
2•Educa ion &
Educa ional esea ch
2. JOURNAL OF AGRICULTURAL &
FOOD INFORMATION
2•Ag onomy
3. AMERICAN JOURNAL OF HUMAN
ECOLOGY
2•Human ecology
4. AFRICAN JOURNAL OF
AGRICULTURAL RESEARCH
2•Ag icul u e
5. AFRICA EDUCATION REVIEW 1 •Educa ion &
Educa ional esea ch
6. BIOLOGICAL CONSERVATION 1 •En i onmen al
sciences
7. ECOLOGICAL ECONOMICS 1 •Ecology
8. INTERNATIONAL JOURNAL OF
TECHNOLOGY
1•Enginee ing,
mul idisciplina y
9. JOURNAL OF AGRICULTURAL
EXTENSION
1•Ag icul u e
10. JOURNAL OF NATURAL
RESOURCES AND
ENVIRONMENTAL MANAGEMENT
1•En i onmen al
managemen
11. AMERICAN JOURNAL OF
INTEGRATIVE AGRICULTURE
1•Ag icul u e,
mul idisciplina y
12. PLOS ONE 1 •Mul idisciplina y
sciences
13. PROFESSIONAL GEOGRAPHER 1 •Geog aphy
14. SCIENCE AND PUBLIC POLICY 1 •En i onmen al
s udies
•Managemen
15. TECHNOLOGICAL FORECASTING
AND SOCIAL CHANGE
1•Regional &U ban
planning
16. TECHNOVATION 1 •Enginee ing
indus ial
17. AMERICAN JOURNAL OF
BUSINESS AND MANAGEMENT
1•Business &
Managemen
18. BULGARIAN JOURNAL OF
AGRICULTURAL SCIENCE
1•En i onmen al
science
19. SCIENTIFIC JOURNAL OF
APPLIED SOCIAL AND CLINICAL
SCIENCE
1•Social sciences
20. ANTHROPOLOGICAL
NOTEBOOKS
1•An h opology
21. INTERNATIONAL JOURNAL OF
AGRICULTURAL MANAGEMENT
AND DEVELOPMENT
1•Ag icul u e
22. INDIAN JOURNAL OF
EXTENSION EDUCATION
1•Educa ion &T aining
23. INTERNATIONAL JOURNAL OF
ADVANCED RESEARCH
1•Mul idisciplina y
24. TROPICAL AGRICULTURAL
RESEARCH
1•Ag icul u e
25. THE INTERNATIONAL
INFORMATION &LIBRARY
REVIEW
1•Lib a y science
26. QUALITY INNOVATION
PROSPERITY
1•Managemen
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
7
heo e ical pe spec i es iden i ied in his SLR and co esponding a i-
cles. These heo ies include he di usion o inno a ion (DOI) heo y,
in o ma ion beha io heo y, echnology accep ance model (TAM),
heo y o planned beha io (TPB), si ua ed lea ning o communi ies o
p ac ice (CoPs) heo y, he adop ion-di usion model o inno a ion,
Nonaka’s knowledge c ea ion heo y, and he model o public
engagemen .
F om he o e iew o he main heo ies u ilized, one no ices ha
some impo an heo ies in knowledge ans e and up ake li e a u e
ha e no been conside ed. To add ess his gap, h ee addi ional heo-
e ical amewo ks a e sugges ed: esou ce-based iew heo y (RBV),
neoins i u ional heo y, and mo i a ion heo y. These heo e ical
amewo ks, widely used o add ess knowledge ans e in o he
esea ch ields (heal h, business, social sciences, enginee ing, e c.), a e
pa icula ly ele an o add essing he pe sis en gap be ween he sci-
en i ic esea ch and ag icul u al communi ies. Table 8 highligh s he
heo e ical ounda ions, main con ibu ions, and analy ical le els o
hese h ee heo ies.
Towa ds a axonomy o knowledge ans e channels om ag icul u al
esea che s o a me s
The SLR o he 30 selec ed a icles iden i ied 19 di e en channels o
knowledge ans e u ilized by ag icul u al esea che s o each a me s.
Howe e , no concep ual ca ego iza ion o hese channels has been done.
Following Jbilou (2010), he channels o knowledge ans e iden i ied
in his SLR a e classi ied in o wo dimensions: he ype o medium o he
ans e and he o m o he ans e . The o me can be in e ac i e o al,
ex -based, elec onic, o s uc u al media. The la e could be didac ic
(Es ab ooks e al., 2008;Madsen, 2009), dialogic (Beech e al., 2010;
Jones, 2000;Schmid &S ade mann, 2023), ac ical (Blumen hal &
Thie , 2003;Liew e al., 2012;New on e al., 2007), p ac ical (Oe mann
e al., 2008), hema ic (Es ab ooks e al., 2008), elec onic (Mai s e al.,
2013), o s a egic (Liew e al., 2012;Pe kmann &Walsh, 2008). As
ad oca ed by Jbilou (2010, p. 94), he didac ic o m in ol es an in e -
ac i e o al medium based on he demons a ion o how o e ec i ely use
esea ch indings, as well as a discussion wi h use s o he implica ions o
using hese indings. The esea ch esul s a e hus p esen ed in he
con ex o eaching hanks o p ac ical aining cou ses, wo kshops,
semina s, and con e ences a ge ing p ac i ione s. Simila ly, he dialogic
o m also in ol es an in e ac i e o al medium based on discussion and
mu ual exchange o he p ac ical implica ions o he esea ch indings
and he condi ions o hei implemen a ion. “Du ing his exchange, bo h
he esea che and he use a e expe s. One is an expe on he esea ch
esul and i s use, he o he is an expe on he implemen a ion en i-
onmen and i s con ingencies”(Jbilou, 2010, p. 95, ansla ed by au-
ho s). This o m o ans e channel includes discussion g oups,
pa ne ship pla o ms, exchange isi s, and join -on ield esea ch.
Knowledge ans e channels can also use w i en media in h ee
di e en o ms: ac ical, p ac ical, and hema ic. These o ms can be
conside ed as s a egies designed o achie e a speci ic objec i e: he use
o esea ch esul s. Speci ically, he ac ical o m is based on he d a ing
Fig. 2. Dis ibu ion o he numbe o a icles pe yea (publica ion end).
Table 4
Dis ibu ion o analy ical echniques in he selec ed a icles.
ANALYSIS TECHNIQUE NUMBER OF
ARTICLES
PROPORTION OF
ARTICLES
Con en analysis 9 30 %
Mul i a ia e eg ession 4 16.7 %
•S uc u al Equa ion
Modeling (SEM)
2 50 %
•Logis ic eg ession 1 25 %
•O de ed p obi eg ession 1 25 %
Mul i-quan i a i e me hods 5 13.3 %
Quali a i e-quan i a i e
me hods
3 10 %
In e en ial s a is ics 4 13.3 %
Case s udies 2 6.7 %
Resea ch ac ion 1 3.3 %
Mul i-quali a i e me hods 1 3.3 %
P incipal Componen Analysis
(PCA)
1 3.3 %
To al 30 100 %
Table 5
Dis ibu ion o a icles by da a collec ion echnique.
DATA COLLECTION METHODS NUMBER OF
ARTICLES
PROPORTION OF
ARTICLES
Su ey 14 46.67 %
In e iew 8 26.67 %
Documen a ion 1 3.33 %
Wo kshop and aining 1 3.33 %
Mul i-da a collec ion me hods 6 20 %
•Focus g oup and su ey and
in e iews
1 25 %
•Documen a ion and
in e iews
1 25 %
•Su ey and in e iews 2 50 %
To al 30 100
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
8
Table 6
Concep ual de ini ions o knowledge ans e wi hin he selec ed s udies.
CONCEPTUAL DEFINITION
OF KNOWLEDGE
TRANSFER IN AGRICULTURE
AUTHORS FROM
SELECTED ARTICLES
PURPOSE
DEFINITIONS THAT PERCEIVE KNOWLEDGE TRANSFER AS A SEQUENTIAL
PROCESS
Resea ch up ake ac i i ies
in ol e all ac i i ies aimed
a communica ing esea ch
indings o he a ge
audience o ensu e ha he
a ge audience u ilizes he
esea ch ou comes.
I eanyi-obi and
Asuquo (2023, p. 16).
De ini ions ha
pe cei e knowledge
ans e as a p ocess
enabling he
p oduc ion o
knowledge by scien i ic
esea che s and i s
applica ion wi hin he
ag icul u e.
Technology ans e is he
main componen o
echnology de elopmen .
This is because, o he
de eloped echnology o be
applied e ec i ely, i needs
o each he end use s o he
echnology wi h i s ull
package. The eedback needs
o each he de elope o he
echnology as well o in ol e
all ac o s in he decision-
making.
Ayalew &Abebe
(2018, p. 683).
Technology ans e is a
c i ical p ocess in
ans o ming ag icul u al
esea ch inno a ions in o
applica ions o end use s. I
helps o imp o e economic
g ow h, ans o m li es and
boos ou pu s.
I eanyieze e al. (2017,
p. 2064).
Resea ch up ake includes all
ac ions ha aid and
con ibu e o he use o
esea ch e idence by
policymake s, p ac i ione s
and o he de elopmen
ac o s. I is aimed a
s imula ing end use s o
ag icul u al esea ch
indings, including
policymake s, ag icul u al
p ac i ione s, esea che s,
and/o implemen e s, in o
g owing awa e o and
accessing and applying
esea ch knowledge/
indings/ou pu in
ag icul u al policy and
p ac ice.
I eanyi-obi &Asuquo
(2023, p. 16).
Comme cializa ion o
knowledge is a p ocess ha
ans o ms he knowledge
gene a ed in o ma ke able
p oduc s (Yadollahi Fa si
and Kala haie, 2012). I
begins when a business is
c ea ed as a way o use
mode n scien i ic and
echnological
ad ancemen s, wi h he aim
o esponding o ma ke
demands h ough design,
de elopmen ,
manu ac u ing, ma ke ing,
and subsequen e o s o
imp o e he p oduc (Meh a,
2008).
Ahmadinejad (2020,
p. 150).
Da enpo and P usak (1998)
a gue ha knowledge
ans e in ol es wo
ac ions, namely,
ansmission ( he p ocess o
Fongwa &Ma ais
(2016, p. 193).
Table 6 (con inued)
CONCEPTUAL DEFINITION
OF KNOWLEDGE
TRANSFER IN AGRICULTURE
AUTHORS FROM
SELECTED ARTICLES
PURPOSE
sending knowledge o a
po en ial ecipien ) and
abso p ion (by he ecipien
–pe son/ ins i u ion).
Technology ans e includes
di ec o indi ec
ansmission o scien i ic
knowledge o eal li e
(B ennen aed s, Bekke s and
Ve spagen, 2006).
Ja ´
abko ´
a e al.
(2019, p. 138).
Technology ans e e e s o
delibe a e, goal-o ien ed
ela ionship be ween wo o
mo e pe sons, g oups, o
o ganiza ions who exchange
echnological knowledge
(Au io and Laamanen,
1995).
I eanyieze e al. (2017,
p. 2064).
Technology ans e e e s o
mo emen o ideas,
in en ions and p o o ypes
wi hin companies, om
esea ch p oduce s o a wide
g oup o use s including
go e nmen depa men s,
non-p o i s, indus ies and
uni e si ies (Ha man and
Ha man, 2004).
I eanyieze e al. (2017,
p. 2064).
S ock and Ta ikonda (2000)
desc ibed echnology
ans e as he ac o
con eying and u ilizing
echnological inno a ion by
he ecipien o achie e se
objec i es, wi hin cos and
ime a ge s. Technology
ans e is, he e o e, he
mo emen o ele an
specialized knowledge o
inno a ions om esea ch
ins i u es o a me s o
adop ion wi h he help o
ex ension agen s and
p o iding eedback o
esea che s o achie e he
in ended objec i es.
I eanyieze e al. (2017,
p. 2064).
DEFINITIONS THAT HIGHLIGHT THE INTERACTIVE ASPECT OF THE
KNOWLEDGE TRANSFER PROCESS
REFILS (Resea ch-Ex ension-
Fa me -Inpu Linkage
Sys em) p o ides a means o
sha ing in o ma ion a he
poin o o e lapping
be ween i s di e en ac o s
h ough he use o a ious
ac i i ies.
Fabo ode &Ajay
(2015, p. 82).
De ini ions ha
highligh he
in e ac i e aspec o
knowledge ans e .
Fo e ec i e ans e o
echnology, s ong in e -
o ganiza ional linkage is
i al because o he
in ol emen o a ious
o ganiza ions in he p ocess
(Sen, 1984).
Kau &Kau (2013, p.
699).
Technology ans e equi es
esea ch s a ions o
dissemina e in o ma ion
h ough ex ension agen s
and o he s o ensu e ha
a ge audience ecei e he
inno a ion h ough media
and o he means.
I eanyieze e al. (2017,
p. 2064).
The a e a which echnology
ans e is accep ed o
I eanyieze e al. (2017,
p. 2064).
(con inued on nex page)
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
15
(Wheele , 2008), os e ing mo e ele an knowledge ans e ac i i ies,
which esea che s a e mo e inclined o adjus o mee a me s’speci ic
needs and condi ions. Mo eo e , he esea che s’senio i y o academic
ank signi ican ly in luences he in ensi y and e ec i eness o his
knowledge ans e . Mo ing up he academic ladde , hey gain g ea e
expe ience and esou ces, which enhances hei capaci y o e ec i e
knowledge ans e (Du am &La son, 2001).
Resea che s’in e disciplina i y
Scien i ic discipline in luences he na u e o he knowledge being
ans e ed, he eby shaping he p ocess o ans e ing ag icul u al
esea ch (e.g., Du am &La son, 2001;Maas e al., 2021). Fu he mo e,
he ag icul u al sec o aces challenges ha equi e insigh s om a wide
ange o disciplines. In e disciplina i y plays a c ucial ole in acili a ing
knowledge ans e om esea che s o a me s (Maas e al., 2021).
Resea che s om di e en disciplines in he ag icul u al ield ha e a
di e se ange o pe spec i es, allowing hem o app oach complex
challenges om mul iple angles. In ag icul u e, whe e he challenges a e
mul i ace ed, his mul idisciplina y app oach no only enhances
p oblem-sol ing abili ies, bu also p omo es a mo e e icien app oach o
add essing hese issues.
a. Resea che a i udes and mo i a ions
Resea che s’a i udes, cul u es and pe cep ions
The SLR inds ha he di e gen pe spec i es, cul u es, and in e es s
o esea che s and a me s can signi ican ly exace ba e challenges in he
knowledge ans e p ocess (Ansa i e al., 2016;Bayissa, 2015b;Maas
e al., 2021). Resea che s who o en p io i ize heo e ical amewo ks
and pu sue new scien i ic esul s may ind hemsel es a odds wi h
a me s who a e mo e conce ned abou p ac ical and expe ience-based
solu ions. Mo eo e , esea che s’a i udes owa ds a me s’knowl-
edge play a c ucial ole in he knowledge ans e p ocess (C uz e al.,
2022). Some esea che s commonly iew a me s’knowledge as in e io
o less aluable han scien i ic knowledge (C uz e al., 2022). These
p ejudices and pe cep ions o in e io i y can lead esea che s o un-
de alue a me s’p ac ical insigh s g ounded in yea s o expe ience and
a deep unde s anding o speci ic ag icul u al con ex s (C uz e al., 2022).
Resea che s’in en ions and mo i a ions
Resea che s’in en ions and eadiness o ans e hei esea ch e-
sul s o a me s a e essen ial componen s ha in luence he knowledge
ans e p ocess (Bayissa, 2015b;Tahe i e al., 2022). As ad oca ed by
many s udies in he SLR, esea che mo i a ion is a c i ical de e minan
o he success o knowledge ans e ac i i ies (e.g., Ahmadinejad, 2020;
Bayissa, 2015b;Fabo ode &Ajayi, 2015;Helen e al., 2010;I eanyi-obi
&Asuquo, 2023;Ka amidehko di, 2013;Wije a hna e al., 2015). Spe-
ci ically, when esea che s a e no adequa ely mo i a ed by hei in-
s i u ions (whe he h ough inancial ewa ds, oppo uni ies o ca ee
ad ancemen , ma e ial gains, public ecogni ion, o hono s), hey a e
less inclined o dedica e he necessa y ime, esou ces, and e o o
engaging wi h a me s and o he po en ial ag icul u al use s o hei
esea ch (I eanyi-obi &Asuquo, 2023;Okocha, 1995). This challenge is
compounded by he me i oc a ic s uc u e p e alen in uni e si ies
(Anzi ino &Canni o, 2024;Soysal e al., 2024), which o en p io i izes
speci ic measu able ou pu s such as publica ions, ci a ions, and he
acquisi ion o esea ch g an s (Hoˇ
ce a &Is eniˇ
c, 2014).
In addi ion, subjec i e no ms shaped by he pe cep ion o app o al
om colleagues o supe io s wi hin an ins i u ion can signi ican ly in-
luence a esea che ’s decision o pa icipa e in knowledge- ans e ac-
i i ies (Wije a hna e al., 2015). When esea che s belie e ha hei
pee s and he academic ins i u ions alue and suppo hei engagemen
in knowledge ans e ac i i ies, hey a e mo e likely o eel mo i a ed o
p io i ize such ac i i ies (Ahmadinejad, 2020;Bayissa, 2015b). Pe sonal
sa is ac ion is a key d i e mo i a ing academics o engage in knowledge
ans e (Wije a hna e al., 2015). When esea che s expe ience a p o-
ound sense o ul illmen om seeing hei esea ch ou pu , hey a e no
only mo e likely o pa icipa e in hese ac i i ies bu also mo e
commi ed o sus aining hei in ol emen o e ime. Simila ly, e-
sea che s who app oach ou each ac i i ies posi i ely and iew hem as
enjoyable and inhe en ly aluable a e signi ican ly mo e likely o
pa icipa e ac i ely (Wije a hna e al., 2015). By pe cei ing hese ac-
i i ies as oppo uni ies o connec wi h he p ac ical side, add ess
eal-wo ld challenges, and con ibu e o he ad ancemen o ag icul u e,
his pa icipa ion is ueled by genuine en husiasm a he han ex e nal
p essu e.
The indings align wi h a subs an ial body o li e a u e highligh ing
he dual na u e o mo i a ion, encompassing bo h in insic and ex insic
ac o s, in in luencing esea che engagemen in knowledge ans e . Fo
ins ance, Lam’s (2011) amewo k p o ides aluable insigh s in o how
di e en mo i a ional d i e s a ec a esea che ’s pa icipa ion in hese
ac i i ies. Acco ding o Lam (2011), esea che s’mo i a ions can be
di ided in o h ee dis inc ca ego ies: in insic sa is ac ion, de i ed om
in ellec ual cu iosi y (puzzle); inancial incen i es and economic e-
wa ds (gold); and he pu sui o p o essional ecogni ion, epu a ion
enhancemen , and ca ee p og ession ( ibbon). The puzzle mo i a ion is
linked o in insic mo i a o s, while he gold and ibbon mo i a ions a e
associa ed wi h ex insic mo i a o s.
a. Resea che engagemen and ou pu
Resea che s’ ime alloca ion
Acco ding o se e al s udies, he alloca ion o ime ac oss eaching,
esea ch, and dissemina ion ac i i ies plays a pi o al ole in de e mining
he e ec i eness o knowledge ans e wi hin he ag icul u al sec o
(Fabo ode, 2015;Ge son e al., 2022;La son &Du am, 2000;Wije -
a hna e al., 2015). Resea che s’abili y o e ec i ely ans e knowledge
o a me s hinges no only on hei expe ise bu also on he a ailabili y
o su icien ime o meaning ully engage in hese ac i i ies (La son &
Du am, 2000). Hea y wo kloads o esea che s, including eaching,
esea ch, and adminis a i e du ies, may c ea e signi ican ime con-
s ain s (La son &Du am, 2000). The cons an p essu e o ul ill he
expec a ions associa ed wi h hese mul iple oles o en esul s in he
de-p io i iza ion o ac i i ies ha do no yield immedia e academic
ou pu s.
Resea ch ype
The e ec i eness o knowledge ans e o a me s is signi ican ly
in luenced by he ype o esea ch conduc ed by ag icul u al esea che s
(e.g., Ahmadinejad, 2020;Bayissa, 2015a;Mgbenka e al., 2013;Simbe,
2022). Con empo a y ag icul u al esea ch aces a signi ican discon-
nec be ween he p ac ical needs o a me s and he esea ch p io i ies o
academic ins i u ions (Bayissa, 2015a). This gap a ises la gely om he
ype o esea ch, which o en ends o be heo e ical and disconnec ed
om eal-wo ld ag icul u al challenges (Bayissa, 2015a).
Resea che s, d i en by a combina ion o in insic mo i a ions and
ex e nal incen i es, end o ocus on p oducing high-impac publica ions
ha o en emphasize scien i ic igo and no el y o e p ac ical ele-
ance (Hoˇ
ce a &Is eniˇ
c, 2014). This ocus on heo e ical con ibu ions,
while aluable in ad ancing scien i ic unde s anding, o en esul s in
esea ch ou pu s oo abs ac o be o immedia e use in add essing
a me s’challenges (Bayissa, 2015a;Hoˇ
ce a &Is eniˇ
c, 2014). Unlike
basic esea ch, applied esea ch is explici ly designed o add ess p ac-
ical p oblems and p o ide solu ions ha can be implemen ed in
eal-wo ld con ex s. Howe e , despi e i s impo ance, applied esea ch
is equen ly unde alued in academia and lacks he ecogni ion and
suppo i dese es (Hoˇ
ce a &Is eniˇ
c, 2014). Applied esea ch p ojec s,
which may yield immedia e and angible bene i s o a me s, a e o en
judged by he same c i e ia as basic esea ch, despi e hei di e en
objec i es (Hoˇ
ce a &Is eniˇ
c, 2014).
Resea che s’p oduc i i y
The au ho s ound ha esea che s’p oduc i i y, o en measu ed by
academic publica ions and ci a ions, is a c i ical ac o in he
knowledge- ans e p ocess (e.g., Fongwa &Ma ais, 2016;I eanyi-obi &
Asuquo, 2023). Acco ding o Fongwa and Ma ais (2016), e ec i e
S.B. Fa ah and N. Ama a

Jou nal o Inno a ion & Knowledge 10 (2025) 100650
16
knowledge ans e elies hea ily on he esea che s’capaci y o p o-
duce high-quali y esea ch. I eanyi-obi &Asuquo (2023) highligh he
impo ance o publishing a icles as a majo ac i i y in he ans e o
ag icul u al esea ch.
a. Resea che eam and ne wo king
Resea ch eam
The size o he esea ch eam signi ican ly in luences he knowledge
ans e p ocess. Fo ins ance, Thu ne &Zaichenko (2018) highligh he
c ucial ole o s a numbe s, pa icula ly wi hin Resea ch and ech-
nology o ganiza ions, and explain how s a expansions o educ ions
di ec ly impac he e ec i eness o echnology ans e ac i i ies. When
a esea ch eam has a la ge numbe o membe s, i bene i s om a
di e se ange o skills, expe ise, and backg ounds. A la ge eam also
allows a mo e e icien dis ibu ion o wo kload, ensu ing ha he e-
sponsibili ies associa ed wi h knowledge ans e a e managed
e ec i ely.
Resea che s’social capi al and ne wo king
Nume ous s udies unde sco e he pi o al ole o esea che s’social
capi al in acili a ing knowledge ans e wi hin he ag icul u al sec o
(e.g., Ahmadinejad, 2020;Bayissa, 2015b,2015c;C uz e al., 2022;
Di imano a &Rade , 2017;Fabo ode &Ajayi, 2015;Fongwa &Ma ais,
2016;I eanyi-obi &Asuquo, 2023;Kau &Kau , 2013;La son &Du am,
2000). S ong social capi al accele a es he ans e o in o ma ion om
ag icul u al esea che s o a me s. When esea che s o ge s ong
connec ions wi h ag icul u al ex ensionis s, a me s, policymake s, and
o he s akeholde s, dissemina ion o scien i ic indings becomes mo e
e icien (Fongwa &Ma ais, 2016;I eanyi-obi &Asuquo, 2023;
Mgbenka e al., 2013). By con as , poo coo dina ion o limi ed in e -
ac ion and communica ion be ween esea che s and o he ag icul u al
s akeholde s can be de imen al o he ans e and adop ion o esea ch
(Bayissa, 2015b;C uz e al., 2022;Fabo ode &Ajayi, 2015;Fongwa &
Ma ais, 2016;Mgbenka e al., 2013).
The success o knowledge ans e in ag icul u e hinges on he
es ablishmen o e ec i e communica ion channels ha os e in-
e ac ions be ween esea che s and a me s (Du am &La son, 2001;
La son &Du am, 2000;Simbe, 2022). Communica ion in ag icul u al
esea ch should be adap ed o i he a me s’con ex , ensu ing i is
unde s andable, unambiguous, con ex ually ele an , and di ec ly
applicable o hei needs (Theodo akopoulos e al., 2012). T us in
collabo a i e ne wo ks is a undamen al pilla o success (e.g., Ahma-
dinejad, 2020;Ansa i e al., 2016;Fongwa &Ma ais, 2016;Ja ´
abko ´
a
e al., 2019;Theodo akopoulos e al., 2012). Fo e ec i e knowledge
ans e , a me s mus know ha esea che s and hei a ilia ed in-
s i u ions a e commi ed o anspa ency and he pu sui o sha ed
bene i s.
De e minan s ela ed o he o ganiza ional con ex in uni e si ies/ esea ch
cen e s. The SLR helped iden i y ou de e minan subca ego ies ela ed
o he o ganiza ional con ex p e ailing in uni e si ies and esea ch
cen e s: 1) uni e si y/ esea ch cen e size, 2) uni e si y cul u e, 3)
uni e si y unding and in as uc u e, and 4) uni e si y esea ch
ne wo ks.
Uni e si y/Resea ch cen e size
The impac o uni e si y size on ag icul u al knowledge ans e was
highligh ed as a signi ican ac o in some s udies. The size o an ins i-
u ion, o en quan i ied by he numbe o esea ch s a membe s o he
p esence o a dedica ed knowledge and echnology ans e o ice, can
subs an ially in luence he e ec i eness o knowledge ans e ac i i ies
(Thu ne &Zaichenko, 2018). La ge uni e si ies and esea ch in-
s i u ions end o possess mo e ex ensi e expe ise, specialized suppo
s uc u es, g ea e esou ces, and a b oade knowledge base. These a -
ibu es collec i ely enhance a uni e si y’s capaci y o e ec i ely
dissemina e ag icul u al esea ch indings and echnologies o he
ag icul u al communi y.
Uni e si y cul u e
Uni e si ies’cul u e and s a egic o ien a ion signi ican ly in luence
how esea ch is ans e ed and applied in p ac ical con ex s (Fongwa &
Ma ais, 2016;Wije a hna e al., 2015). A uni e si y’s academic cul u e,
shaped by i s alues and no ms, can acili a e o hinde knowledge
ans e o he ag icul u al communi y. When a uni e si y does no
alloca e su icien esou ces o lacks a clea policy ha p omo es and
suppo s knowledge ans e ac i i ies, i e lec s a cul u al o ien a ion
ha may no ully ecognize he impo ance o engagemen beyond
academic ci cles (Fongwa &Ma ais, 2016).
O en, wi hin uni e si ies, he c i e ia used o acul ies’p omo ions
ypically emphasize me ics such as publica ion achie emen s and
ci a ion coun s, wi h a less ecogni ion gi en o ac i i ies like ans-
e ing esea ch o wo king wi h non-academic s akeholde s (Hoˇ
ce a &
Is eniˇ
c, 2014). The “publish o pe ish”cul u e in uni e si ies means ha
ac i i ies ha a e seen as pe iphe al o publica ion, such as engaging
wi h non-academic s akeholde s o ocusing on knowledge ans e ,
pa icula ly in he ag icul u al sec o , a e o en dep io i ized (Hoˇ
ce a &
Is eniˇ
c, 2014).
Uni e si y unding and in as uc u e
A key ac o in luencing he e ec i eness o knowledge ans e in
ag icul u e is he le el o in es men in inancial and ma e ial esou ces
(Ahmadinejad, 2020;Ansa i e al., 2016;Du am &La son, 2001;
Fabo ode &Ajayi, 2015;Fongwa &Ma ais, 2016;I eanyi-obi &Asuquo,
2023;I eanyieze e al., 2017;La son &Du am, 2000). Resea ch in-
s i u ions ely on unding om a ious public and p i a e sou ces,
including ounda ions, go e nmen councils and agencies, nonp o i
o ganiza ions, and p i a e en i ies. Compe i i e unding mechanisms
d i e ins i u ions o p io i ize applied esea ch wi h angible pa hways
o comme cializa ion (Thu ne &Zaichenko, 2018). By con as , in-
s i u ions ha ecei e a la ge sha e o hei budge om public unds
may lean owa ds basic esea ch (Du am &La son, 2001;Thu ne &
Zaichenko, 2018). Sho - e m unding limi s esea che s’abili y o
adap ag icul u al esea ch o he di e se and e ol ing needs o di e en
egions (Du am &La son, 2001). Insu icien unding leads o challenges
in p o iding he ma e ial, echnical, and logis ical esou ces equi ed o
acili a e success ul echnology ans e (Fabo ode &Ajayi, 2015). In
addi ion o inancial cons ain s, inadequa e in as uc u e such as poo
anspo a ion o limi ed in o ma ion and communica ion echnology
(ICT) esou ces p esen s a signi ican ba ie o knowledge ans e in
ag icul u e (Ahmadinejad, 2020;Ansa i e al., 2016;Fongwa &Ma ais,
2016;Helen e al., 2010;I eanyi-obi &Asuquo, 2023;I eanyieze e al.,
2017;La son &Du am, 2000;Wije a hna e al., 2015). E ec i e
communica ion and in e ac ion wi h a me s o en equi e obus
in as uc u e, including e icien and eliable anspo a ion sys ems,
ad anced ICTs, and well-equipped esea ch acili ies.
Uni e si y esea ch ne wo ks
Uni e si y ne wo ks a e an impo an de e minan o he success o
knowledge ans e ini ia i es o he ag icul u al sec o (Ayalew &
Abebe, 2018;Hoˇ
ce a &Is eniˇ
c, 2014;La son &Du am, 2000). Uni-
e si ies o en engage wi h a di e se ange o ex e nal s akeholde s such
as a me s, ag icul u al ex ension se ices, go e nmen agencies, and
o he ele an s akeholde s. Howe e , he e ec i eness o hese ne -
wo ks is o en impai ed by limi ed in e ins i u ional collabo a ion
(Hoˇ
ce a &Is eniˇ
c, 2014;I eanyi-obi &Asuquo, 2023). The absence o
well-coo dina ed collabo a ions ac oss di e en ins i u ions c ea es
ba ie s o e ec i e knowledge ans e (Hoˇ
ce a &Is eniˇ
c, 2014). This
lack o coo dina ion hampe s he exchange o c ucial insigh s and leads
o a op-down linea app oach ha o en ails o add ess he complex
and e ol ing needs o ag icul u al communi ies.
De e minan s ela ed o he ex e nal en i onmen . The e ec i eness o he
knowledge ans e p ocess is in luenced by a ange o con ex ual de-
e minan s (e.g., Dha mawan e al., 2023;Fongwa &Ma ais, 2016;
S.B. Fa ah and N. Ama a
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17
Helen e al., 2010), which can be di ided in o socio-cul u al and ins i-
u ional/poli ical de e minan s. P e ious SLRs ha e a gued ha one o
he c i ical de e minan s o e ec i e knowledge ans e is he abili y o
adap ac i i ies o he unique cul u al and socioeconomic condi ions o
di e en egions (C uz e al., 2022; Ge son e al., 2012; Simbe, 2022).
This is pa icula ly impo an because knowledge ans e is highly
con ex -dependen ; a one-size- i s-all app oach is unlikely o e ec i ely
add ess di e se con ex s and needs. Consequen ly, he e ec i eness o
knowledge ans e ac i i ies is closely linked o hei alignmen wi h
he cha ac e is ics o he ag icul u al communi y and a ge ed egions
(C uz e al., 2022). Wi hou his con ex ual sensi i i y, e en he mos
inno a i e and well-in en ioned knowledge ans e ini ia i es isk
ailing o esona e wi h local popula ions, diminishing hei po en ial
impac . Cul u al ba ie s a ising om di e ences in cul u al and social
backg ounds may se e ely hinde he ans e o knowledge o a me s
om a ious g oups o cul u al backg ounds (Fongwa &Ma ais, 2016).
These ba ie s also in ensi y social and e i o ial inequali ies (Fais ,
2010). E ec i e knowledge ans e depends, among o he ac o s, on
add essing cul u al ba ie s (such as by de eloping pa icipa o y
communica ion pla o ms (Dha mawan e al., 2023) and building us
and collabo a i e ies be ween esea che s and a me s (Fongwa &
Ma ais, 2016;Ja ´
abko ´
a, 2019;Theodo akopoulos e al., 2012)).
Ins i u ional and poli ical de e minan s, along wi h sociocul u al
de e minan s, play a key ole in he ans e o scien i ic ag icul u al
esea ch (Ansa i e al., 2016;Bayissa, 2015b;Ge son e al., 2022;Helen
e al., 2010;I eanyi-obi &Asuquo, 2023;Mgbenka e al., 2013). In-
s i u ions cha ac e ized by igid s uc u es and complex adminis a i e
p ocesses o en c ea e signi ican ba ie s o he e icien ans e o
esea ch indings (Fabo ode &Ajayi, 2015;I eanyi-obi &Asuquo,
2023). Go e nmen in es men has also eme ged as a de e mining ac o
Fig. 3. In eg a i e concep ual amewo k o ag icul u al knowledge ans e and i s de e minan s.
S.B. Fa ah and N. Ama a
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18
in success ul ans e s (Du am &La son, 2001). Poli ical ba ie s ha
a e mul i ace ed and include ideological biases (Ge son e al., 2022),
policy apa hy (I eanyi-obi &Asuquo, 2023), misaligned s a egies, and
inconsis en suppo (Ansa i e al., 2016) add ano he laye o
complexi y.
The ans e o scien i ic ag icul u al esea ch can also be signi i-
can ly in luenced by policymake s’poli ical belie s and a ilia ions
(Ge son e al., 2022). Poli ical ideologies in luence he alloca ion o
esou ces, dic a ing which esea ch a eas and knowledge ans e ini-
ia i es ecei e p io i y (Ge son e al., 2022). Ano he signi ican
impedimen is he lack o en husiasm o ac i e disin e es among poli-
cymake s (Bayissa, 2015b;I eanyi-obi &Asuquo, 2023). When policy-
make s neglec o in eg a e esea ch indings in o policy amewo ks,
he en i e p ocess o knowledge ans e is hampe ed, esul ing in missed
oppo uni ies o inno a ion and angible imp o emen . The apa hy o
policymake s c ea es a gap be ween esea ch and p ac ical imple-
men a ion, leading o s agna ion in policy de elopmen ha could
o he wise op imize he knowledge- ans e p ocess. Finally, he absence
o a clea and well-de ined ision coupled wi h he absence o p ope
policies, laws, and egula ions o he implemen a ion o inapp op ia e
policies and p og ams also ac s as a ba ie o e ec i e knowledge
ans e (Ansa i e al., 2016;Bayissa, 2015b;Ge son e al., 2022;Helen
e al., 2010;Mgbenka e al., 2013).
An in eg a i e concep ual amewo k o e ec i e knowledge ans e in
ag icul u e
To consolida e he main indings o he SLR on he de e minan s o
knowledge ans e om ag icul u al esea che s o a me s, an in e-
g a i e concep ual amewo k was de eloped. The esul ing amewo k,
illus a ed in Fig. 3, iden i ies he p incipal de e minan s ha signi i-
can ly explain he knowledge- ans e p ocess om he pe spec i e o
ag icul u al esea che s. These we e ca ego ized in o indi idual, o ga-
niza ional, and en i onmen al de e minan s. In indi idual de-
e minan s, he SLR iden i ied 11 subca ego ies ela ed o he
cha ac e is ics o ag icul u al esea che s. These encompass key a i-
bu es, such as compe encies, in e disciplina i y, expe ience, and ime
alloca ion. Addi ionally, ac o s such as he ype o esea ch conduc ed,
size o he esea ch eam, educa ional backg ound and senio i y,
esea ch p oduc i i y, social capi al, and ne wo king, along wi h he
esea che s’a i udes, pe cep ions, in en ions, and mo i a ions, all play
signi ican oles in explaining knowledge ans e wi hin he ag icul u al
sec o . In o ganiza ional de e minan s, we iden i ied ou key sub-
ca ego ies ha in luence knowledge ans e wi hin uni e si ies and
esea ch cen e s. The size o he ins i u ion, p e ailing o ganiza ional
cul u e, a ailabili y o unding and in as uc u e, and s eng h o
esea ch ne wo ks a e all signi ican de e minan s. Las ly, en i on-
men al de e minan s, encompassing ins i u ional, poli ical, and socio-
cul u al ac o s, con ibu e o explaining he e ec i eness o knowledge
ans e ac i i ies wi hin he ag icul u al sec o .
Con ibu ions o his s udy
Theo e ical con ibu ions
To he bes o ou knowledge, a comp ehensi e mapping e iew o
help consolida e and syn hesize he exis ing body o knowledge on
ans e o ag icul u al esea ch has been lacking. This SLR on ans e o
ag icul u al esea ch knowledge o a me s and i s le e s and obs acles
enabled he iden i ica ion o pa e ns, ends, and gaps in li e a u e.
Second, he e is s ill a limi ed unde s anding o how ag icul u al e-
sea che s ans e hei esea ch esul s o p ac i ione s in he ag icul-
u al milieu. This s udy p oposes an o iginal axonomy o knowledge
ans e channels based on wo dimensions: he ype o ans e medium
(in e ac i e o al o ex ual suppo ) and he o m o ans e (didac ic,
dialogic, ac ical, p ac ical, hema ic, elec onic, o s a egic). Thi d, his
s udy de eloped an in eg a i e, e idence-based amewo k based on he
ele an s udies o imp o e ou unde s anding o he le e s and ba ie s
ha may explain di e ences in ag icul u al esea che s’engagemen in
knowledge ans e . This amewo k ca ego izes he de e minan s in o
h ee signi ican ca ego ies ela ed o he: 1) indi idual cha ac e is ics o
ag icul u al esea che s, 2) p e ailing o ganiza ional con ex o esea ch
ins i u ions, and 3) ex e nal en i onmen . This in eg a i e concep ual
amewo k, de i ed om he i s SLR on he ans e o ag icul u al
esea ch o p oduce s, ep esen s a subs an ial concep ual con ibu ion.
Finally, o ag icul u al esea che s, his s udy p o ides a esea ch
agenda ha iden i ies unde explo ed lines o esea ch and may se e as
a ounda ion o u u e esea ch,
P ac ical con ibu ions
Beyond he heo e ical ealm, he esul s o his s udy will illumina e
ag icul u al p ac i ione s and decision-make s ega ding key de-
e minan s ha can be a ge ed o enhance he knowledge ans e
p ocess. The esul s will gene a e ac ionable insigh s ele an no only o
uni e si ies, esea che s, and knowledge and echnology ans e o ga-
niza ions (KTTOs) bu also o a ious s akeholde s wi hin he ag icul-
u al sec o . This encompasses ex ension and ag icul u al ad iso y
agencies, ag icul u al unions, go e nmen o ganiza ions, and agencies
in ol ed in p omo ing ag icul u al p ac ices ha alue cu ing-edge
esea ch and inno a ion. A comp ehensi e unde s anding o he le e s
and ba ie s ha may encou age o discou age b idging he gap be ween
esea che s and a me s will guide s akeholde s in e ec i ely os e ing
p ac ice-o ien ed esea ch ans e among a me s, designing impac ul
knowledge- ans e p og ams, and ine- uning policies.
Towa ds a esea ch agenda o he u u e
O e all, he p oposed esea ch agenda p o ides a s a ing poin o
u he analysis o add ess se e al sho comings in li e a u e and opens
he oppo uni y o mo e high-quali y s udies o educe o close he gap
be ween academics and a me s. Speci ically, ou e iew and analysis
iden i y se e al gaps and sho comings ha dese e u he in es iga-
ion. Six o hese a e o pa icula in e es and may p o ide p omising
esea ch oppo uni ies.
•Disen angling esea ch p oduc ion om esea ch ans e
Wi hou excep ion, he e iewed a icles ailed o di e en ia e be-
ween knowledge p oduc ion and knowledge ans e p ocesses. Se e al
signi ican con ibu ions o he opic o knowledge ans e om
esea ch p oduce s o po en ial use s in he p ac ice milieu ha e high-
ligh ed he impo ance o disen angling he p oblems and issues ela ed
o each p ocess ega ding he knowledge ans e gap. Fo ins ance,
Shapi o e al. (2007) used he me apho s o “los in ansla ion”and “los
be o e ansla ion” o e e , espec i ely, o knowledge p oduc ion
p oblems and knowledge ans e p oblems. Ama a e al. (2019) d ew on
S oke’s model (1997) o cons uc ou p o iles o esea che s by
c ossing wo a iables e lec ing he esea che s’o ien a ion owa ds
he p oduc ion o knowledge o he basic unde s anding o p oblems o
owa ds p ac ical use s’needs. Consequen ly, an in e es ing con ibu-
ion o he ad ancemen o knowledge on ag icul u al knowledge
ans e will be o disen angle he ac o s impai ing he b idging o he
gap be ween ag icul u al esea che s and a me s acco ding o he
knowledge p oduc ion and ans e p ocesses.
•G ounding he de e minan s o knowledge ans e in a concep ual
amewo k
S udies ha ha e a emp ed o iden i y he de e minan s o knowl-
edge ans e om ag icul u al esea che s o a me s su e om an
unde de elopmen o heo e ical g ounding (e.g., Ansa i e al., 2016;
Kau &Kau , 2013;Maas e al., 2021;Thu ne &Zaichenko, 2018). A
S.B. Fa ah and N. Ama a
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19
majo i y o he selec ed pape s (20 a icles, o 66.66 %) did no
explici ly e e o models o heo e ical app oaches. This lack o a sound
heo e ical backg ound hinde s he ull exploi a ion o he ela ionship
be ween knowledge ans e and i s de e minan s. As a heo e ical
con ibu ion o he ad ancemen o knowledge, an in eg a i e concep-
ual amewo k is p oposed ha ca ego izes he de e minan s o ag i-
cul u al knowledge ans e iden i ied h ough he da a ex ac ion
p ocedu e o he sys ema ic li e a u e e iew in o meaning ul ca e-
go ies. Addi ionally, he need o be e ancho he selec ion o he de-
e minan s o ag icul u al knowledge ans e wi hin heo e ical
amewo ks is emphasized, along wi h he impo ance o es ing hy-
po heses based on he p edic ions o hese heo ies.
•P oposing a axonomy o knowledge ans e channels
In he a icles s udied, we ound no classi ica ion o g ouping o he
knowledge ans e channels used by ag icul u al esea che s o each
a me s. To add ess his gap, an o iginal axonomy o knowledge
ans e channels is p oposed, inspi ed by Jbilou (2010) and based on
wo dimensions: ype o medium and o m o ans e . Howe e , his
axonomy wa an s empi ical es ing.
•Re ining he knowledge ans e and i s de e minan s’measu es
Fo a icles ad oca ing quan i a i e app oaches, he SLR ound an
unde u iliza ion o widely ecognized and alida ed cons uc s and in-
dica o s o measu e knowledge ans e and i s de e minan s. Li e a u e
appea s o be less ecep i e o me hodologies de eloped in o he disci-
plines. Fo ins ance, se e al well-known cons uc s de eloped by e-
sea che s om a ious ields o measu ing knowledge ans e om
esea che s o p ac i ione s ha e been iden i ied (e.g., A za &Ca a oli,
2017;Land y e al., 2001;Lawson e al., 2019;P ado-Gasc´
o e al., 2020,
e c.). The e is an u gen need o ake ad an age o exis ing empi ical
ma e ial om o he esea ch ields o de elop cons uc s and indica o s
ha conside he peculia i ies o knowledge ans e in ag icul u e.
•Taking in o accoun he peculia i ies o esea ch ields and disciplines
O e all, empi ical s udies on knowledge ans e ha e shown ha
disciplines ma e and ha esea che s in ol ed in ce ain disciplines
a e mo e likely o engage in knowledge ans e and o he esea ch ac-
i i ies, such as publica ion in schola ly jou nals, pa en ing, and spin-o
c ea ion han hei coun e pa s om o he disciplines (Land y e al.,
2007;Leydesdo &Shin, 2011;Mugabushaka e al., 2016;Radicchi &
Cas ellano, 2012;Rhaiem &Ama a, 2020). Fu u e esea ch should
conside he peculia i ies and publica ion con en ions o di e en dis-
ciplines. Many ields a e d i en by adi ional sys ems ha ewa d
publica ions in p es igious jou nals and high bibliome ic me ics
(Ama a e al., 2015). This sys em has implica ions o o he esea ch
ac i i ies, including he ans e o knowledge o p ac ical applica ions.
•Consolida ing he pool o empi ical s udies
Wi h a ew excep ions (e.g., Ansa i e al., 2016;I eanyi-obi &Asu-
quo, 2023;Okocha, 1995), he iden i ica ion o he de e minan s o
knowledge ans e was a ely he main objec i e o he a icles
analyzed. The e o e, mo e empi ical s udies will be needed o explain
knowledge ans e in ag icul u e. One can di e si y analy ical me hods
by inco po a ing asymme ical me hods such as quali a i e compa a i e
analysis (QCA) (Ragin, 2006,2009). Unlike co ela ional me hods, such
as eg ession, QCA o e s he ad an age o iden i ying mul iple con ig-
u a ions o necessa y and su icien condi ions ha lead o he same
ou come—in his case, ans e o knowledge o p ac ical applica ions.
This al e na i e me hod is being inc easingly u ilized ac oss a ious
disciplines (e.g., heal h, managemen , and he en i onmen ).
Limi a ions and concluding ema ks
The indings o he SLR should be conside ed in ligh o some limi-
a ions. The i s is he he e ogenei y ac oss s udies and he isk o da a
emo al om speci ic con ex s. This he e ogenei y can mani es in
a ious aspec s, including di e ences in he me hodologies used, s udy
designs, epo ed ou comes, and con en . This could lead o incomple e
in e p e a ions and a po en ial loss o o e all pe spec i e when syn-
hesizing da a om di e se con ex s. The second s ems om p ede ined
inclusion and exclusion c i e ia. Al hough English is he p edominan
language used in he scien i ic domain, he decision o exclude con i-
bu ions in o he languages led o he omission o a subs an ial co pus o
ele an a icles no w i en in English. The hi d limi a ion is he
exclusion o g ey li e a u e in he o m o books (and book chap e s),
essays, mas e ’s heses, doc o al heses, esea ch no es, disse a ions,
and con e ence p oceedings. The ocus was speci ically on pee -
e iewed pape s, which led o he omission o po en ially aluable
indings published in al e na i e scien i ic ou le s. This decision may
ha e led o he o e looking o ele an documen s ha could ha e
p o ided u he con ibu ions. Addi ionally, he exclusion o concep-
ual s udies is ano he signi ican limi a ion. Concep ual o heo e ical
s udies, i included, could p o ide a solid heo e ical ounda ion and
b oade pe spec i e, he eby augmen ing he dep h and ichness o ou
analysis.
No wi hs anding hese limi a ions, his SLR is he i s o comp e-
hensi ely analyze he s a e-o - he-a esea ch on knowledge ans e
om ag icul u al esea ch o a me s. The indings o e a p omising
ou look o u he esea ch.
CRediT au ho ship con ibu ion s a emen
Sa a Ben Fa ah: W i ing –o iginal d a , Valida ion, Me hodology,
Fo mal analysis, Da a cu a ion, Concep ualiza ion. Nabil Ama a: Vali-
da ion, Supe ision, Resou ces, P ojec adminis a ion, Me hodology.
Appendix A
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20
Fig. A.1. Dis ibu ion o selec ed a icles by majo egions.
Fig. A.2. Dis ibu ion o selec ed a icles by uni o analysis.
Fig. A.3. Dis ibu ion o selec ed a icles by ield o applica ion.
S.B. Fa ah and N. Ama a

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21
Fig. A.4. Dis ibu ion o selec ed a icles by ype o me hodological app oach (empi ical end).
Appendix B
Table B.1
Classi ica ion o he de e minan s o knowledge ans e om ag icul u al esea che s o a me s.
DETERMINANTS FACTORS SUB-FACTORS DESCRIPTION EXAMPLES OF
AUTHORS FROM THE
SLR
De e minan s ela ed o he indi idual cha ac e is ics o ag icul u al esea che s
De e minan s ela ed o he
indi idual cha ac e is ics
o ag icul u al
esea che s
Resea che s’compe encies T aining T aining esea che s is c ucial o enhancing
he ans e o knowledge o a me s.
Ahmadinejad (2020)
Ansa i e al. (2016)
Ge son e al. (2022)
Helen e al. (2010)
I eanyi-obi and Asuquo
(2023)
Ka amidehko di
(2013)
  Skills Resea che s wi h subs an ial skills and
expe ise play a pi o al ole in he e ec i e
comme cializa ion o esea ch indings.
Ansa i e al. (2016)
Bayissa (2015a)
Resea che s’in e disciplina i y Mul idisciplina y app oaches/
T ansdisciplina y app oaches
Mul idisciplina y app oaches o e b ead h
and in eg a ion, leading o mo e holis ic and
impac ul solu ions.
Du am and La son
(2001)
Maas e al. (2021)
Resea che s’expe ience Resea che s’p io engagemen
in knowledge ans e ac i i ies
Resea che s who ha e p e ious posi i e
expe ience in knowledge ans e ac i i ies a e
mo e likely o engage in simila u u e
ac i i ies.
Bayissa (2015a)
Helen e al. (2010)
Wheele (2008)
Wije a hna e al.
(2015)
Resea che s’ ime alloca ion Time cons ain s in conduc ing
knowledge ans e ac i i ies
Resea che s o en ace hea y wo kloads ha
encompass eaching esponsibili ies, ongoing
esea ch p ojec s, and adminis a i e du ies.
La son &Du am
(2000)
   Time cons ain s mani es as es ic ed
a ailabili y o esea che s o engage in
e ec i e communica ion and collabo a ion.
Fabo ode (2015)
Ge son e al. (2022)
Wije a hna e al.
(2015)
Resea ch ype Types o esea ch conduc ed
(basic o undamen al esea ch,
applied esea ch)
Basic esea ch can be oo abs ac and no
immedia ely use ul o sol ing p ac ical
ag icul u al issues. Basic esea ch equen ly
ails o mee a me s’needs because a me s
a e no su icien ly in ol ed in iden i ying
esea ch p oblems. Applied esea ch is o en
unde alued and lacks adequa e suppo o
p ac ical implemen a ion.
Bayissa (2015a)
Hoˇ
ce a &Is eniˇ
c
(2014)
  Quali y and ele ance o
esea ch
High-quali y and ele an esea ch, aligned
wi h a me s’p ac ical needs, is essen ial o
e ec i e knowledge ans e o a me s.
Resea ch mus add ess p ac ical and imely
Bayissa (2015c)
Dha mawan e al.
(2023)
Mgbenka e al. (2013)
(con inued on nex page)
S.B. Fa ah and N. Ama a
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22
Table B.1 (con inued)
DETERMINANTS FACTORS SUB-FACTORS DESCRIPTION EXAMPLES OF
AUTHORS FROM THE
SLR
issues aced by a me s o be conside ed
ele an .
  In eg a ion o scien i ic esea ch
in o policy and p ac ice
Fo scien i ic esea ch o ha e ac ionable
ou comes, i needs o be e ec i ely in eg a ed
in o ag icul u al policy and p ac ice.
Dha mawan e al.
(2023)
Resea ch eam Size o he esea ch eam La ge esea ch eams bene i om a b oade
ange o skills and expe ise, acili a ing mo e
e ec i e knowledge ans e .
Thu ne &Zaichenko
(2018)
Resea che s’educa ional
backg ound and senio i y
Educa ional backg ound Resea che s wi h ad anced educa ion end o
ha e a mo e analy ical and open-minded
app oach, enhancing he e ec i eness o
knowledge ans e .
C uz e al. (2022)
Wheele (2008)
  Senio i y As esea che s p og ess in hei academic
ca ee s, hey end o ha e g ea e expe ience
and esou ces, which can enhance hei
capaci y o e ec i e knowledge ans e .
Du am &La son
(2001)
Resea che s’p oduc i i y High esea ch p oduc i i y Resea che s’p oduc i i y, measu ed by
publica ions and ci a ions, is a c i ical ac o in
he knowledge ans e p ocess, hough i
should be pai ed wi h e ec i e dissemina ion.
Fongwa &Ma ais
(2016)
I eanyi-obi &Asuquo
(2023)
Resea che s’social capi al and
ne wo king
Coo dina ion among
s akeholde s
Syne gy/linkage be ween esea che s,
a me s, policymake s, ex ension wo ke s,
and o he s akeholde s is essen ial o
add essing ag icul u al challenges.
Du a ion o ela ionships: Es ablishing long-
e m ela ionships be ween a me s and
esea ch ins i u ions can enhance us and
acili a e ongoing collabo a ion.
In ol emen o he p i a e sec o can p o ide
addi ional esou ces.
Ahmadinejad (2020)
Ansa i e al. (2016)
Ayalew &Abebe
(2018)
Bayissa (2015a)
Bayissa (2015c)
Di imano a &Rade
(2017)
Du am &La son
(2001)
Fabo ode &Ajayi 92,
015)
Fongwa &Ma ais
(2016)
Helen e al. (2010)
I eanyi-obi &Asuquo
(2023)
I eanyieze e al. (2017)
Kau and Kau (2013)
La son &Du am
(2000)
Mgbenka e al. (2013)
Wije a hna e al.
(2015)
  E ec i e communica ion
channels and pla o ms
U iliza ion o e ec i e communica ion
me hods makes ag icul u al esea ch engaging
and maximizes i s each among a me s.
Ayalew &Abebe
(2018)
Dha mawan e al.
(2023)
Fongwa &Ma ais
(2016)
Ge son e al. (2022)
La son and Du am
(2000)
Maas e al. (2021)
Okocha (1995)
Theodo akopoulos
e al. (2012)
  T us be ween esea che s and
a me s
Ini ial mis us be ween esea che s and
a me s hinde s open dialogue.
Ahmadinejad (2020)
Di imano a &Rade
(2017)
Fongwa &Ma ais
(2016)
Ja ´
abko ´
a e al. (2019)
Theodo akopoulos
e al. (2012)
Resea che s’a i udes, alues and
pe cep ions
Di e ences in pe cep ions Resea che s’and a me s’di e ing p io i ies
and pe spec i es can exace ba e he
challenges in he knowledge ans e p ocess.
I eanyieze e al. (2017)
Bayissa (2015c)
Ja ´
abko ´
a e al. (2019)
Maas e al. (2021)
Simbe (2022)
  P ejudices and s e eo ypes
Pe cep ion o Knowledge:
Pe cep ion o in e io i y
Nega i e s e eo ypes abou a me s
signi ican ly impede he exchange o
knowledge.
Some esea che s pe cei e a me s’
C uz e al. (2022)
(con inued on nex page)
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
23
Table B.1 (con inued)
DETERMINANTS FACTORS SUB-FACTORS DESCRIPTION EXAMPLES OF
AUTHORS FROM THE
SLR
knowledge as in e io , which can hinde he
ecogni ion o aluable p ac ical insigh s.
Resea che s’in en ions and
mo i a ions
Resea che s’in en ions Readiness and willingness o ag icul u al
esea che s o dissemina e knowledge and
echnologies among a me s
Bayissa (2015b)
Tahe i e al. (2022)
  Resea che s’mo i a ions:
In insic and ex insic
mo i a ions
Incen i es ha d i e esea che s o conduc
knowledge ans e ac i i ies (sel -
de elopmen , pe sonal sa is ac ion,
ecogni ion om academic ins i u ions,
inancial mo i a ions, encou agemen om
pee s, e c.).
Ahmadinejad (2020)
Bayissa (2015b)
I eanyi-obi &Asuquo
(2023)
Fabo ode &Ajayi
(2015)
Ka amidehko di
(2013)
Helen e al. (2010)
Wije a hna e al.
(2015)
De e minan s ela ed o he
o ganiza ional con ex in
uni e si ies/ esea ch
cen e s
   
De e minan s ela ed o he
o ganiza ional con ex in
uni e si ies/ esea ch
cen e s
Uni e si y/Resea ch cen e size Numbe o esea ch s a
Exis ence o a echnology
ans e o ice (TTO)
La ge uni e si ies possess g ea e esou ces,
suppo s uc u es, and expe ise, enhancing
hei capaci y o e ec i e knowledge
ans e .
Thu ne &Zaichenko
(2018)
Uni e si y cul u e The uni e si y cul u e does no
p io i ize he p ac ical
applica ion and
comme cializa ion o esea ch
Limi ed suppo o comme cializa ion
ac i i ies uni e si y cul u e and no ms do no
suppo o p io i ize knowledge ans e
ac i i ies.
Hoˇ
ce a &Is eniˇ
c
(2014)
Wije a hna e al.
(2015)
   Unde alua ion o knowledge ans e e o s:
esea che s’e o s o ans e knowledge a e
unde alued compa ed o hei esea ch
ou pu s.
Absence o egula assessmen o he
knowledge ans e ac i i ies.

  The emphasis on esea ch
excellence
The emphasis on esea ch excellence and he
in ense p essu e om uni e si ies o publish
in p es igious in e na ional jou nals a ec
esea che s’e o s o ans e hei indings
in o p ac ical ag icul u al applica ions.
Resea che s, p ima ily e alua ed on hei
scien i ic ou pu , a e less incen i ized o
engage in knowledge ans e ac i i ies.

Ins i u ional policy Absence o a clea uni e si y
policy owa ds p omo ing and
suppo ing knowledge ans e
ac i i ies
Wi hou adequa e policies, laws, and
egula ions o suppo knowledge ans e , he
p ocess o mo ing esea ch in o p ac ical use
can be cumbe some and augh wi h
obs acles.
Bayissa (2015c)
Wije a hna e al.
(2015)
  Bu eauc a ic s uc u es The bu eauc a ic na u e o ag icul u al
ins i u ions, cha ac e ized by complex
adminis a i e p ocesses and igid
o ganiza ional s uc u es, can signi ican ly
hinde he e iciency o knowledge ans e
ac i i ies.
Ahmadinejad (2020)
Fabo ode &Ajayi
(2015)
I eanyi-obi &Asuquo
(2023)
Financial esea ch unding and
in as uc u e
  
Resea ch unding A ailabili y and alloca ion o
unding
 
Lack o unding and esou ces o
esea ch ini ia i es can limi he
scope and impac o knowledge
ans e e o s.
Ahmadinejad (2020)
Ansa i e al. (2016)
Bayissa (2015c)
Du am &La son (2001)
Fabo ode &Ajayi (2015)
Fongwa &Ma ais (2016)
Helen e al. (2010)
I eanyi-obi &Asuquo (2023)
I eanyieze e al. (2017)
Ja ´
abko ´
a e al. (2019)
La son &Du am (2000)
 
  Compe i i e unding
High dependence on public
unding
Ins i u ions ha ecei e compe i i e unding
a e mo e inclined o pa icipa e in knowledge
ans e ac i i ies.
Ins i u ions wi h a high sha e o hei budge s
coming om ede al unds ypically p io i ize
Thu ne &Zaichenko
(2018)
(con inued on nex page)
S.B. Fa ah and N. Ama a
Jou nal o Inno a ion & Knowledge 10 (2025) 100650
24
Table B.1 (con inued)
DETERMINANTS FACTORS SUB-FACTORS DESCRIPTION EXAMPLES OF
AUTHORS FROM THE
SLR
basic esea ch o e applied esea ch, limi ing
hei p ac ical impac on echnology ans e .
  Sho - e m unding  
Many g an s o e unding o
limi ed pe iods, which is
inadequa e o he long- e m
esea ch equi ed in ag icul u e.
Du am and La son (2001)  
In as uc u e In as uc u e Insu icien in as uc u e and sca ce
esou ces c ea e a ba ie o academics,
hinde ing hei abili y o pe o m e ec i e
knowledge ans e ac i i ies.
Ahmadinejad (2020)
Ansa i e al. (2016)
Fongwa &Ma ais
(2016)
Helen e al. (2010)
I eanyieze e al. (2017)
La son &Du am
(2000)
Wije a hna e al.
(2015)
Resea ch ne wo ks   
Resea ch ne wo ks Ins i u ional ne wo ks Lack o s ong ins i u ional linkage.
Lack o coo dina ed ne wo ks be ween
academic and non-academic ac o s es ic s
he low o knowledge.
Hoˇ
ce a &Is eniˇ
c
(2014)
De e minan s ela ed o he
ex e nal en i onmen
   
Socio-cul u al de e minan s Adap a ion o local con ex s Sensi i i y o egional socio-
economic and cul u al
condi ions
Alignmen wi h local
ag icul u al p ac ices
The e ec i eness o knowledge ans e
s a egies depends on adap a ion o he
speci ic cul u al and socio-economic
cha ac e is ics o di e en egions and he
pa icula cha ac e is ics o he ag icul u al
communi y.
C uz e al. (2022)
Simbe (2022)
  Cul u al con ex Cul u al ba ie s, a ising om di e ences in
cul u e and social backg ound, can se e ely
hinde he ans e o knowledge o a me s
om a ious g oups o di e en cul u al
backg ounds.
Fongwa &Ma ais
(2016)
Ins i u ional and poli ical
de e minan s
Ins i u ional de e minan s Bu eauc a ic p ocedu es Impac o igid s uc u es and adminis a i e
complexi y
I eanyi-obi &Asuquo
(2023)
  Go e nmen in es men s Role o unding in acili a ing knowledge
ans e
Du am &La son
(2001)
Poli ical de e minan s Policymake s’belie s and
a ilia ions
The ans e o scien i ic ag icul u al esea ch
can be in luenced by poli ical belie s and
a ilia ions.
Ge son e al. (2022)
  Nonchalan a i ude o
policymake s
Policymake s exhibi a disin e es o lack o
en husiasm owa ds inco po a ing esea ch
indings in o p ac ical applica ions.
I eanyi-obi and Asuquo
(2023)
  Inapp op ia e pe spec i es and
policy-making
Inconsis en policymaking
The absence o a clea ision, along wi h
inapp op ia e policies and p og ams,
cons i u es a majo ba ie o knowledge
ans e ac i i ies.
Fluc ua ing and inconsis en policies hinde
he e icien ans e o knowledge.
Ansa i e al. (2016)
Bayissa (2015b)
Ge son e al. (2022)
Helen e al. (2010)
Mgbenka e al. (2013)
  Policy, unds, and adminis a i e
suppo
 
Lack o p ope policy, adequa e
unds, and adminis a i e suppo
c ea es signi ican ba ie s o
e ec i e knowledge ans e .
  
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