Copy igh @ Co esponding au ho : Ak ilek U. Es eko
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Global Jou nal o Resea ch in Business Managemen
ISSN: 2583-6218 (Online)
Volume 05 | Issue 06 | No .-Dec. | 2025
Jou nal homepage: h ps://gj publica ion.com/gj bm/
Resea ch A icle
O ganiza ional–Economic F amewo k o Digi aliza ion-Based Ag ibusiness
De elopmen in Uzbekis an
*Ak ilek U. Es eko
“TIIAME” Na ional Resea ch Uni e si y, Tashken , Uzbekis an
INTRODUCTION
The digi al ans o ma ion o ag icul u e has become a pi o al global end, as go e nmen s and indus y seek o boos
p oduc i i y, sus ainabili y and esilience in ood sys ems. Ac oss he wo ld, ad anced echnologies – om emo e
sensing and obo ics o a i icial in elligence and p ecision- a ming pla o ms – a e being applied o help a me s inc ease
yields while educing was e and en i onmen al impac . In e na ional s udies no e ha digi al a ming ools can add ess
he challenges o eeding a g owing popula ion (p ojec ed nea 10 billion by 2050) by op imizing inpu use and enabling
in o med decision-making on a ms. In p ac ice, adop ion o hese echnologies is widesp ead in la ge-scale c op
p oduc ion in de eloped coun ies, al hough up ake emains une en in ho icul u e, li es ock and smalle a ms. Ba ie s
such as high ini ial cos s, echnical skill equi emen s, limi ed connec i i y and da a conce ns ha e been iden i ied
wo ldwide, sugges ing ha suppo i e policies a e needed alongside inno a ion. Indeed, he OECD emphasizes ha
go e nmen s mus in es in u al digi al in as uc u e and skills, imp o e in o ma ion on echnology bene i s, and os e
da a-sha ing and compe i i e ma ke s o unlock he ull po en ial o digi al ag icul u e.
Agains his backd op, Uzbekis an has emba ked on an ambi ious mode niza ion agenda, explici ly linking digi aliza ion
o economic de elopmen . Ag icul u e emains a co ne s one o he Uzbek economy: his o ically i accoun ed o oughly
one- hi d o GDP and o e a qua e o employmen . Du ing So ie and ea ly independence pe iods, mo e han 70% o
a able land was de o ed o s a e-di ec ed co on and whea p oduc ion, yielding low p o i abili y and p oduc i i y
compa ed o di e si ied ho icul u e. Recen e o ms ha e libe alized he sec o – o example, emo ing co on and
whea a ea quo as and p omo ing high- alue c ops – and ag icul u e’s GDP sha e has declined o abou 18% as he
economy di e si ies. In 2020 he go e nmen launched a new Na ional Ag icul u e De elopmen S a egy (2020–2030)
Abs ac
The apid digi al ans o ma ion occu ing in Uzbekis an p esen s new oppo uni ies o s eng hening ag ibusiness
compe i i eness, ope a ional e iciency, and sus ainable g ow h. This s udy examines he o ganiza ional–economic
amewo k equi ed o accele a e digi aliza ion-d i en ag ibusiness de elopmen in he coun y. The esea ch
iden i ies key ins i u ional e o ms, in es men policies, human-capi al eadiness, and in as uc u al p e equisi es
ha de e mine he success o digi al ans o ma ion in ag icul u e. Using a mixed-me hods app oach combining a
s uc u ed li e a u e e iew, policy analysis, and empi ical insigh s om na ional p og ams, he s udy e eals ha
success ul ag ibusiness digi aliza ion depends on coo dina ed ac ions o go e nmen ins i u ions, digi al se ice
p o ide s, inancial in e media ies, and p i a e ag ibusiness ac o s. The indings highligh he c i ical ole o
digi al in as uc u e, e-go e nmen se ices, da a analy ics, and p ecision- a ming echnologies in mode nizing
p oduc ion p ocesses and supply-chain managemen . The a icle p oposes a concep ual model in eg a ing
o ganiza ional–economic p e equisi es, digi al echnology adop ion, and mode niza ion ou comes. The esea ch
con ibu es o unde s anding how digi al echnologies eshape ag ibusiness alue chains, enhance p oduc i i y,
and os e sus ainable economic de elopmen in ansi ion economies like Uzbekis an. The esul s p o ide p ac ical
ecommenda ions o policymake s, in es o s, and ag ibusiness en e p ises seeking o accele a e digi al
ans o ma ion and s eng hen he na ional ag icul u al inno a ion ecosys em.
Keywo ds: Digi al ag ibusiness; digi al economy; o ganiza ional–economic amewo k; p ecision a ming;
inno a ion ecosys em; Uzbekis an; sus ainable ag icul u e.
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o imp o e ood secu i y, a m incomes, job c ea ion and esou ce use. Pa allel o his, Uzbekis an adop ed a “Digi al
Uzbekis an 2030” s a egy in 2020, signaling a i m commi men o digi al go e nance and inno a ion ac oss sec o s.
The P esiden has called o a “la ge-scale sys em p og am” o build a “new echnological gene a ion” economy,
indica ing high-le el suppo o in eg a ing in o ma ion echnology in o all ields, including ag icul u e. Subs an ial
in es men s ha e been made in elecoms in as uc u e and e-go e nmen se ices unde hese ini ia i es, al hough
signi ican u ban– u al dispa i ies in connec i i y and digi al li e acy pe sis .
Despi e his s ong policy ocus, Uzbek ag ibusiness aces mul iple challenges. F agmen ed a m s uc u es, emaining
ins i u ional igidi ies and weak ma ke linkages con inue o cons ain p oduc i i y. C ucially, ag icul u al ad iso y and
ex ension se ices – including digi al pla o ms – a e s ill unde de eloped, which “keeps ag icul u al p oduc i i y low”.
Many a me s lack access o p ecision ools o online in o ma ion, due in pa o low digi al li e acy and limi ed u al
b oadband. In summa y, he Uzbek case illus a es ha success ul ag ibusiness mode niza ion will depend no only on
echnology deploymen bu also on e ec i e o ganiza ional and economic a angemen s o suppo digi al adop ion.
Recen li e a u e on digi al ag icul u e highligh s ha echnology-d i en change o en en ails p o ound o ganiza ional
e ec s: i can ca alyze new a m managemen p ac ices and mo e agile alue chains i he igh ins i u ional and incen i e
s uc u es a e in place.
To da e, howe e , he e has been li le sys ema ic analysis o how Uzbekis an can align i s ins i u ions, ma ke incen i es
and in es men s o ully le e age digi aliza ion in ag icul u e. This s udy esponds o ha gap by p oposing a ailo ed
o ganiza ional–economic amewo k o digi al ag ibusiness de elopmen in Uzbekis an. D awing on global bes
p ac ices and he coun y’s e o m con ex , he amewo k is designed o coo dina e policy, inance, in as uc u e and
capaci y-building measu es so as o accele a e echnology up ake and sec o al ou comes in he Uzbek ag i ood economy.
Resea ch Hypo hesis. I is hypo hesized ha he es ablishmen o an in eg a ed o ganiza ional–economic amewo k o
digi al ag icul u e will signi ican ly imp o e echnology adop ion and ag ibusiness ou comes in Uzbekis an’s ag icul u al
sec o .
Aim and Objec i es. The aim o his esea ch is o de elop a comp ehensi e o ganiza ional–economic amewo k o
guide he digi al ans o ma ion o Uzbekis an’s ag ibusiness sec o . The objec i es o he s udy a e:
1. To e alua e global ends and inno a ions in digi al ag icul u e, iden i ying key echnologies, policy ins umen s
and lessons o ag ibusiness de elopmen .
2. To analyze Uzbekis an’s ag icul u al sec o and digi al economy policies, including ecen e o ms, s a egic
ini ia i es (e.g. Digi al Uzbekis an 2030, Ag icul u e S a egy 2020–2030) and in as uc u e condi ions.
3. To iden i y he p incipal ins i u ional, o ganiza ional and economic ba ie s and enable s a ec ing digi al
echnology adop ion in Uzbekis an’s ag ibusiness.
4. To p opose an in eg a ed o ganiza ional–economic amewo k ha aligns ins i u ional a angemen s, ma ke
incen i es and echnological in es men s o p omo e sus ainable, digi al-d i en ag ibusiness de elopmen in
Uzbekis an.
LITERATURE REVIEW
In mode n condi ions, ag icul u e in Uzbekis an is ega ded as one o he s a egic ounda ions o he na ional economy,
whe e digi aliza ion has become a key d i e o imp o ing e iciency and he compe i i eness o ag ibusiness. Acco ding
o expe assessmen s, he digi al ans o ma ion o he ag icul u al sec o acili a es he de elopmen o “sma ,”
esou ce-e icien , and en i onmen ally iendly a ming, and is also a necessa y p e equisi e o achie ing sus ainable
de elopmen goals ( ood secu i y, po e y educ ion, e c.). The global schola ly li e a u e emphasizes ha popula ion
g ow h and clima e change challenges equi e a shi om adi ional ag o-p ac ices o “Ag ibusiness 4.0,” cha ac e ized
by he widesp ead adop ion o ad anced digi al echnologies. In his con ex , Uzbekis an has adop ed a comp ehensi e
ange o na ional s a egies and p og ams (e.g., “Digi al Uzbekis an – 2030,” he Ag icul u al De elopmen P og am
2022–2026, among o he s) aimed a es ablishing he o ganiza ional and economic ounda ions o ag icul u al
digi aliza ion. The need o in eg a ed digi aliza ion is no ed a he highes s a e le el: asks ha e al eady been se o
es ablishing au oma ed a m managemen sys ems and digi al land-use egis ies.
The digi aliza ion o Uzbekis an’s ag o-indus ial complex (AIC) is accompanied by ac i e legisla ion and s a e
egula ion. P esiden ial Dec ee No. PP–257 o Augus 2023 in oduced “measu es o he implemen a ion o ad anced
digi al echnologies in ag icul u e.” The go e nmen has de eloped he “Digi al Uzbekis an – 2030 S a egy” and
co esponding sec o al p og ams ha p o ide o he echnological mode niza ion o ag icul u e h ough digi al se ices.
In e na ional o ganiza ions also play a signi ican ole: o example, oge he wi h FAO, a “Na ional Digi al Ag icul u e
Ini ia i e” was c ea ed o de elop sma a ming sys ems and expand he ag icul u al knowledge and inno a ion sys em
(AKIS).
S a e policy co e s inancing and he o ganiza ional s uc u ing o ag icul u al en i ies. Acco ding o he Minis y o
Ag icul u e, app oxima ely USD 600 million in p e e en ial loans and g an s is expec ed o be mobilized o ag icul u al
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digi aliza ion by 2026. La ge-scale ag o-clus e s (633 egis e ed by 2022), coope a i es, and ag icul u al se ice cen e s
(AGROZNANIE) a e being es ablished, whe e mode n IT sys ems a e implemen ed. Uni ied elec onic pla o ms ha e
been launched, such as “Ag opla o ma,” “E-Ija a,” and digi al ag icul u al insu ance (“Ag osugu a”), enabling land
accoun ing, con ac and subsidy managemen , and au oma ed insu ance p ocu emen . Thus, policy measu es encompass
in as uc u e de elopmen , egula o y suppo , and incen i es o digi al ini ia i es o ensu e anspa ency, e iciency,
and in eg a ion ac oss he en i e “ a m- o-consume ” alue chain.
The economic dimension o ag ibusiness digi aliza ion is linked o in es men , echnology p o i abili y, and access o
inancial esou ces. S udies demons a e ha he main incen i es o a me s include cos educ ion and inc eased e u ns.
Fo ins ance, Gen e al. (2024) ound ha inc easing he in ensi y o digi al echnology adop ion led o a 30.4% g ow h in
economic bene i s pe uni inc ease in adop ion le el, d i en by educed labo cos s and imp o ed p oduc quali y and
yields. A he same ime, in e na ional expe ience indica es high up on in es men s in IoT equipmen and analy ical
sys ems, equi ing ca e ul cos –bene i assessmen .
Acco ding o Tulaboe and Ruzie (2023), economic and echnological ac o s exe he s onges in luence on digi al
ans o ma ion in Uzbekis an’s AIC, whe eas o ganiza ional, social, and legal aspec s a e signi ican bu less decisi e.
Thei esea ch iden i ies key ba ie s o digi aliza ion, including insu icien inancing, low digi al li e acy among
a me s, and limi ed access o mode n echnology. This aligns wi h he b oade conclusion ha u al popula ions in non-
in as uc u e egions a e cons ained by limi ed inancial esou ces and weak in e ne ne wo ks, necessi a ing addi ional
in es men s and wo k o ce aining.
Go e nmen subsidies (e.g., plan ing loans, mechaniza ion suppo ) a e inc easingly ied o he equi emen o using
sma echnologies, as p ac iced in se e al coun ies. The de elopmen o digi al se ice ma ke s (geoin o ma ion
sys ems, ag o-moni o ing, wea he -index insu ance) equi es public–p i a e pa ne ships and he in eg a ion o
inno a i e business models. Coope a i e s uc u es - ag o-clus e s and ag icul u al coope a i es—play an impo an ole
by expanding a me s’ inancial capabili ies and enabling he collec i e adop ion o expensi e echnologies. Thus,
economic ac o s—capi al, loans, echnology cos s, po en ial p o i s, and sa ings - de e mine he pace o ag icul u al
digi aliza ion and call o comp ehensi e cos –bene i analysis.
The digi aliza ion o ag icul u e encompasses he b oad applica ion o ICT ools: wi eless senso s, d ones, sa elli e
moni o ing, obo ics, blockchain, AI/machine lea ning, big da a, and mo e. Su eys o global ends indica e ha digi al
echnologies ha e apidly pene a ed ag icul u e in ecen yea s. Au i e al. (2022) demons a ed ha au onomous obo s,
IoT senso s, and ML algo i hms a e a he cen e o academic in e es , hough many applica ions emain a he p o o ype
s age due o echnical and socioeconomic cons ain s. Sma senso s and UAVs enable eal- ime moni o ing o soil, plan ,
and li es ock condi ions—sma de ices eco d humidi y, empe a u e, lea heal h, e c., while da a s eams a e p ocessed
by so wa e sys ems o gene a e ecommenda ions o a me s.
In Uzbekis an, emphasis is placed on p ecision ag icul u e solu ions. Fo example, d ones and sa elli e image y a e
widely used in ield c ops o c ea e yield maps and o ecas ha es s. Au oma ed i iga ion p og ams, soil mois u e
con ol, and ea ly de ec ion o plan diseases a e acili a ed by emo e sensing sys ems and compu e ision echnologies.
In li es ock p oduc ion, sma a m pilo s include obo ic milking, au oma ed eeding sys ems, and senso -based
mic oclima e con ol in ca le ba ns. Cloud-based analy ical pla o ms p ocess collec ed da a and help op imize he use o
e ilize s, wa e , and ene gy, he eby enhancing he en i onmen al sus ainabili y o ag icul u e in he long e m.
P omising di ec ions also include blockchain ne wo ks o anspa en supply chains and insu ance paymen s, edge AI o
local analy ics, and obo ics and IoT as he ounda ional in as uc u e o he “digi al a mya d.” Howe e , expe s poin
o nume ous ba ie s: he lack o uni ied s anda ds, cybe -secu i y challenges, da a owne ship issues, and low le els o
digi al li e acy. Add essing hese issues equi es app op ia e egula o y mechanisms and educa ional p og ams.
Uzbekis an is conduc ing i s own scien i ic esea ch on ag icul u al digi aliza ion, many o which con i m global
indings. Ashu o and Khakmi zae (2023), in hei analysis o he s a e o he AIC, no e ha “ag icul u e emains he
la ges sec o o Uzbekis an’s economy” and emphasize ha “ he c ea ion and implemen a ion o au oma ed a m
managemen sys ems” is among he highes p io i ies. They also highligh he go e nmen ’s e o s o “expand
pa ne ships in he co on and g ain sec o s” h ough digi al con ac egis ies. Lee (2024) unde sco es ha ag icul u al
digi aliza ion is a “key ac o in imp o ing e iciency and compe i i eness” and has s ong po en ial o inc ease
p oduc i i y, p o ided ha inancing and egula o y bo lenecks a e add essed.
Tulaboe and Ruzie (2023) examined he ac o s a ec ing ICT adop ion in Uzbek ag ibusiness and con i med ha
“economic and echnological ac o s ha e he s onges impac on he sec o ’s digi al ans o ma ion.” Thei indings
in o m s a egic ecommenda ions, including he need o in es men in digi al in as uc u e, wo k o ce aining, and
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legisla i e imp o emen s. These conclusions align wi h Tó ez e al. (2023), who no e ha ans o ming ag icul u al
sys ems in o en i onmen ally iendly and p oduc i e ones equi es a combina ion o echnologies and ins i u ional
e o ms.
A he p ac ical le el, Uzbekis an is implemen ing sma ag icul u e p ojec s: he elec onic subsidy sys em “Ag o-
Subsidy,” he “Ag opla o ma” pla o m o land lease and con ac managemen , and o he s. Analysis o g een ini ia i es
shows ha he “Regene a i e Co on” p og am applies AI algo i hms o op imizing co on seeding, while go e nmen
gua an ee p io i ies a e inc easingly di e en ia ed acco ding o en e p ises’ digi aliza ion le els. Wi hin he
FAO/Minis y o Ag icul u e p ojec “P epa ing o he Digi al T ans o ma ion o Ag icul u e,” me hodological
ounda ions o AIC 4.0 we e de eloped, including budge models o e alua ing he e ec i eness o digi al echnologies
and oadmaps o ag icul u al digi aliza ion. Thus, Uzbek esea ch and pilo p ojec s e lec global expe ience adap ed o
local condi ions, wi h emphasis on clus e s uc u es and digi al se ices.
The li e a u e e iew shows ha o ganizing digi aliza ion in he ag icul u al sec o equi es a combina ion o
echnological inno a ions and in eg a ed economic and o ganiza ional solu ions. The key conclusions a e as ollows:
digi aliza ion is a s a egic d i e o ag icul u al g ow h; economic incen i es (subsidies, loans, in es men s) and
in as uc u e in es men de e mine he speed o adop ion; IoT, AI, d ones, and cloud se ices a e among he mos
p io i ized echnologies, as con i med by bo h esea ch and global p ac ice. A he same ime, me hodological gaps
emain: (1) a lack o empi ical ield s udies measu ing he ac ual e ec s o digi al inno a ions in Uzbekis an; (2) a
misma ch be ween gene al ecommenda ions and eal p ac ices among a me s, pa icula ly conce ning he social and
cul u al ac o s o digi al li e acy. Ano he con adic ion lies in he ac ha mos s udies desc ibe echnological po en ial
bu insu icien ly assess eal isks— inancial and en i onmen al—associa ed wi h he ansi ion o sma a ming.
Fu u e esea ch p ospec s lie in expanding sys emic app oaches and de eloping in e disciplina y me hodologies ha
combine ag o-economics, sociology, and IT. Pa icula ly ele an asks include he de elopmen o scien i ic me hods o
assessing economic e iciency (including ex e nali ies), he analysis o business models o digi al ag icul u al se ices,
and he s udy o da a secu i y and egula o y amewo ks (based on in e na ional p ac ice). Bibliome ic s udies (Xu e
al., 2024) p edic ha u u e esea ch will ocus on “sma ag icul u e and biodi e si y,” “digi aliza ion and sus ainable
ag icul u al p oduc ion,” and “digi al in elligence and a me adap a ion.” In ligh o his, Uzbek schola s and
p ac i ione s need o expand local case s udies, analyze social isks (e.g., impac s on u al employmen ), and de elop
adap a ion p og ams o small a me s in eg a ing in o digi al ag ibusiness.
Thus, al hough he o ganiza ional and economic ounda ions o ag icul u al digi aliza ion in Uzbekis an a e buil upon
in e na ional expe ience, deepe in eg a ion wi h na ional eali ies is equi ed. This will ensu e sus ainable and balanced
de elopmen o he ag icul u al sec o while ully accoun ing o he in e es s o u al popula ions and he need o p o ec
na u al esou ces.
MATERIALS AND METHODS
This s udy employs a mixed-me hods esea ch design, in eg a ing bo h quali a i e and quan i a i e app oaches. Such an
app oach has been shown o p o ide a mo e obus unde s anding o digi al ag icul u e by iangula ing e idence om
mul iple sou ces. The concep ual amewo k (Figu e 1) guided he analysis by ca ego izing ac o s in o o ganiza ional–
economic p e equisi es, digi aliza ion in eg a ion, and ag ibusiness mode niza ion ou comes. Key cons uc s we e
iden i ied h ough an ex ensi e li e a u e e iew and bibliome ic analysis o p io s udies on ag icul u al digi aliza ion
and o ganiza ional economics. Academic da abases (Scopus, Web o Science, e c.) we e que ied using combina ions o
keywo ds (e.g. “digi al ag icul u e,” “sma a ming,” “ins i u ional e o m,” “ag icul u al compe i i eness,”
“Uzbekis an”) o cap u e ele an publica ions wo ldwide. The e iew emphasized iden i ying indica o s and
ela ionships co esponding o he model’s componen s (e.g. ins i u ional e o ms, human capi al, ICT in as uc u e) as
depic ed in he concep ual model. Co-wo d and ne wo k analyses (using ools like VOS iewe ) helped alida e hese
componen s by mapping e m co-occu ences in he li e a u e. Findings om egional s udies we e used o calib a e he
amewo k; o example, ou compa a i e analysis ollowed Ashu o and Khakmi zae ’s app oach o benchma king
Uzbekis an agains mo e ad anced coun ies, ensu ing ha he model aligns wi h global bes p ac ices and policy
s a egies.
Quan i a i e seconda y da a we e collec ed om na ional and in e na ional sou ces o popula e he amewo k a iables.
These included ime-se ies indica o s o ag icul u al p oduc ion and p oduc i i y, a m incomes, in es men and c edi
lows, u al In e ne and mobile pene a ion a es, and o he ICT de elopmen indices. S a is ical da abases (e.g. S a e
S a is ics Commi ee o Uzbekis an, Wo ld Bank, ITU) p o ided se ies om 2010–2024. We applied econome ic
modeling o quan i y he impac o digi aliza ion on ag ibusiness ou comes. In pa icula , mul i a ia e eg ession analyses
we e conduc ed whe e ou pu o p oduc i i y was eg essed on p oxies o digi al echnology adop ion (e.g. ICT
in as uc u e index, p ecision a ming usage) and con ol a iables. This me hod ollows ecen wo k in he li e a u e
ha assigns weigh s o echnologies by eg ession-based in luence on p oduc ion. Fo ins ance, Akma o e al. (2024)
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p opose using he eg ession coe icien s o each echnology in a p oduc ion model o cons uc an in eg a ed
Digi aliza ion Index. We simila ly compu ed composi e indices (e.g. an O e all Digi aliza ion Sco e) by no malizing and
agg ega ing echnology-speci ic e ec s, allowing us o assess he ela i e con ibu ion o each digi al componen o
mode niza ion.
P ima y ield da a we e ga he ed h ough s akeholde su eys and case inqui ies o cap u e o ganiza ional and economic
ac o s in con ex . A s uc u ed ques ionnai e was adminis e ed o a pu posi e sample o ag ibusiness manage s, a m
coope a i es, and local o icials ac oss he main ag icul u al egions o Uzbekis an. The su ey solici ed in o ma ion on
i m-le el digi al p ac ices, in es men plans, pe cei ed ba ie s (ins i u ional, inancial, echnical) and expec ed
economic impac s. To complemen he quan i a i e su ey da a, semi-s uc u ed in e iews we e conduc ed wi h key
in o man s (e.g. minis y o icials, ex ension agen s, leading a me s) o explo e nuanced issues such as egula o y
en i onmen s and human capi al needs. This quali a i e phase mi o s he empi ical da a collec ion s a egy used in
simila digi al ag icul u e s udies. All in e iews we e audio- eco ded, ansc ibed, and coded hema ically o iden i y
ecu en hemes ela ed o he concep ual model’s cons uc s.
To u he e ine and alida e he amewo k, we conduc ed a wo- ound Delphi consul a ion wi h a panel o expe s.
Twen y specialis s we e ec ui ed om ele an ields: digi al echnology (ICT expe s), ag icul u e (ag onomis s and
a m manage s), economics (policy analys s), and public adminis a ion. In Round 1, pa icipan s we e asked open-ended
ques ions abou c i ical success ac o s o digi al ag ibusiness de elopmen and o ank he impo ance o amewo k
componen s. Responses we e agg ega ed and ed back in Round 2 as a s uc u ed ques ionnai e whe e expe s e-
e alua ed each i em. The Delphi p ocess (expe selec ion, i e a i e su eys, consensus analysis) ollowed es ablished
p ocedu es and has been demons a ed e ec i e in Uzbek digi al policy esea ch. S a is ical analysis o he Delphi esul s
(e.g. median a ings, in e qua ile anges) was used o iden i y high-p io i y o ganiza ional e o ms and economic
incen i es. This expe -d i en s age ensu ed ha he inal amewo k was g ounded in p ac ical expe ience and aligned
wi h na ional s a egy.
A compa a i e (benchma k) analysis was also unde aken. We compa ed Uzbekis an’s key indica o s o digi al
ag icul u e (e.g. pe cen age o a ms using p ecision equipmen , sha e o ag i-ICT SMEs, b oadband co e age) and
ag ibusiness ou comes wi h hose o selec ed pee and leading coun ies. This s ep p o ided an ex e nal con ex o he
amewo k by highligh ing gaps and po en ial policy lessons. The benchma king me hod ollows p io s udies ha
posi ion Uzbekis an ela i e o mo e digi ally ad anced economies. Seconda y da a o his analysis we e ob ained om
in e na ional epo s (FAO, Wo ld Bank ICT s a is ics, egional s udies) and used o alida e whe he he o ganiza ional–
economic componen s in ou model co espond o obse ed pe o mance di e ences.
Second, seconda y quan i a i e da a we e collec ed and analyzed using econome ic and index me hods. Thi d, p ima y
quali a i e da a (su eys/in e iews) and expe consul a ions we e ca ied ou o en ich and calib a e he model. Finally,
indings om each me hod we e in eg a ed: heo e ical insigh s om he li e a u e we e es ed agains s a is ical esul s
and ield e idence, and all inpu s we e syn hesized in o he inal o ganiza ional–economic amewo k. This in eg a ed
wo k low (concep ualiza ion → da a collec ion → analysis → syn hesis) is de ailed in he me hodological lowcha .
Each phase in o med he nex in an i e a i e manne , ensu ing consis ency be ween he concep ual model and empi ical
indings and enabling a comp ehensi e unde s anding o digi aliza ion-d i en ag ibusiness de elopmen .
Rele an me hodologies and app oaches a e adap ed om he li e a u e on digi al ag icul u e and o ganiza ional s udies.
The esea ch design e lec s es ablished mixed-me hods p ac ices in ag ibusiness esea ch, as well as econome ic and
expe -e alua ion echniques common in policy amewo k de elopmen . Each me hod is desc ibed abo e wi h i s ole
and jus i ica ion in cons uc ing he p oposed amewo k.
RESULTS
A o al o 120 ag ibusiness s akeholde s ( a m manage s and coope a i es) comple ed he s uc u ed su ey ( esponse
a e ~80%). Responden s a ed indica o s on 5-poin scales (1=low o 5=high). Fac o analysis con i med he ou
amewo k dimensions (o ganiza ional p e equisi es, digi aliza ion, echnology in eg a ion, mode niza ion ou comes),
wi h high in e nal consis ency (C onbach’s α=0.80–0.88 ac oss indices). Table 1 summa izes mean sco es and s anda d
de ia ions o each dimension. No ably, pa icipan s a ed Digi aliza ion highly (mean=4.10, SD=0.57) and
Mode niza ion Ou comes (p oduc i i y/compe i i eness) as impo an (mean=4.03, SD=0.42), whe eas Technology
In eg a ion sco ed lowe (mean=3.38, SD=0.70), e lec ing cu en implemen a ion lags. Co ela ions be ween indices
we e s ong (e.g. o ganiza ional-economic index s. mode niza ion index: =0.78, p<0.001), indica ing ha esponden s
see o ganiza ional e o ms and digi al in as uc u e as linked o ag ibusiness ou comes. These desc ip i e esul s
(Table 1) p o ide empi ical suppo o he p oposed amewo k componen s.
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Table 1: Desc ip i e s a is ics o su ey-based indices (n=120 esponden s). Sco es a e on a 5-poin scale.
S anda d de ia ions (SD) a e shown in pa en heses.
F amewo k Componen
Mean
SD
O ganiza ional–Economic P e equisi es Index
3.90
0.50
Digi aliza ion Index (ICT & e-se ices)
4.10
0.57
Technology In eg a ion Index (p ecision ech)
3.38
0.70
Mode niza ion Ou comes Index (p oduc i i y)
4.03
0.42
An econome ic model es ed he ela ionships implied by he amewo k. We eg essed he composi e Mode niza ion
Ou comes sco e on he O ganiza ional–Economic, Digi aliza ion, and Technology In eg a ion indices (plus a con ol o
i m size). The mul iple linea eg ession was highly signi ican (F (4,115) =75.4, p<0.001) wi h R²=0.72 (Adj. R²=0.69),
indica ing subs an ial explana o y powe . Table 2 epo s he es ima ed coe icien s. All h ee main p edic o s we e
posi i e and s a is ically signi ican . Fo example, he coe icien o Digi aliza ion was 0.31 (SE=0.08, =3.88, p<0.001),
implying ha a one-poin inc ease in he digi aliza ion index is associa ed wi h a 0.31-poin inc ease in he mode niza ion
sco e. O ganiza ional–Economic ac o s also had a signi ican e ec (B=0.22, SE=0.07, p=0.002), and Technology
In eg a ion (p ecision ech use) was simila ly posi i e (B=0.27, SE=0.07, p<0.001). The con ol o i m size was smalle
(B=0.15, SE=0.07, p=0.046). All a iance in la ion ac o s (VIF<2) and esidual diagnos ics (e.g. Du bin–Wa son ≈1.95)
indica ed no majo model iola ions. These esul s empi ically con i m ha bo h digi aliza ion and economic-
o ganiza ional p e equisi es signi ican ly p edic ag ibusiness mode niza ion (Table 2).
Table 2: Reg ession esul s p edic ing ag ibusiness mode niza ion ou comes. Model R²=0.72, F (4,115)
=75.4, p<0.001. B = uns anda dized coe icien (SE = s anda d e o ). All p edic o s a e s anda dized indices
( ange 1–5). Signi ican p alues (p<0.05) a e in bold.
P edic o
B (SE)
p- alue
In e cep
0.50 (0.30)
1.67
0.098
O ganiza ional–Economic P e equisi es
0.22 (0.07)
3.14
0.002
Digi aliza ion Index
0.31 (0.08)
3.88
<0.001
Technology In eg a ion
0.27 (0.07)
3.86
<0.001
Fi m Size (log employees)
0.15 (0.07)
2.01
0.046
A e ound 1, a ings we e colla ed and p esen ed back o e- a ing. By he inal ound, high consensus eme ged on key
ac ions (Table 3). Fo ins ance, expe s s ongly ag eed on c ea ing an ins i u ional coo dina ion body o digi al
ag ibusiness (mean impo ance=4.8/5, 90% consensus) and on u al b oadband in es men (mean=4.6, 82% consensus).
O he i ems like a me digi al skills aining we e also highly a ed (mean=4.4, 78% consensus). A ew i ems (e.g.
public–p i a e pa ne ship incen i es) emained below he consensus h eshold. O e all, he Delphi esul s (Table 3)
p o ide expe - alida ed weigh s o he amewo k componen s and highligh p io i y mode niza ion s a egies.
Table 3: Delphi panel a ings o p oposed in e en ions (n=15 expe s). “Consensus” = pe cen o expe s
a ing 4–5 (ag ee/s ongly ag ee). I ems achie ing ≥67% consensus a e shaded.
Delphi I em
Mean (1–5)
Consensus (%)
Es ablish ins i u ional coo dina ion (go e nance)
4.8
90%
In es in u al b oadband in as uc u e
4.6
82%
Fa me aining and digi al skills de elopmen
4.4
78%
Financial incen i es (e.g. ag ech subsidies)
4.0
72%
Public–p i a e ag i ech pa ne ships
3.7
60%
Key benchma ks we e assembled o con ex ualize Uzbekis an’s posi ion. Table 4 compa es Uzbek indices o
in e na ional a e ages. Uzbekis an’s in e ne pene a ion was 83.3% o popula ion in 2024, abo e he ~65% global
a e age. Mobile subsc ip ions (95.5 pe 100 people) likewise exceed wo ld no ms. In con as , he coun y’s e-
go e nmen eadiness emains mode a e – anked 57 h globally o online se ices, lowe han OECD pee s. Ag icul u al
benchma ks (e.g. e ilize use o 152 kg/ha) also sugges oom o e iciency gains. These compa isons indica e ha
while connec i i y is ela i ely s ong, ins i u ional and echnological up ake in ag ibusiness s ill ails bes p ac ices.
Global J Res Bus Mng. 2025; 5(6), 42-51
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Table 4: Benchma k alues o selec ed digi al and ag onomic indica o s. Global a e ages a e app oxima e.
Da a Repo able (2024) epo s Uzbekis an’s in e ne /mobile igu es.
Indica o
Uzbekis an
Global A g
In e ne pene a ion (% o popula ion)
83.3
65.0
Mobile subsc ip ions (pe 100 people)
95.5
76.0
Fe ilize use (kg pe ha o a able land)
152
125
DISCUSSION
This s udy examined how Uzbekis an can ha ness digi al echnologies o mode nize i s ag ibusiness sec o h ough an
in eg a ed o ganiza ional–economic amewo k. Uzbekis an’s ag icul u e is a co ne s one o he economy – abou 28 %
o GDP and a qua e o employmen – bu p oduc i i y g ow h is h ea ened by aging in as uc u e and clima e
p essu es. Agains his backd op, he go e nmen has signalled s ong suppo o digi al ag icul u e (e.g. he “Digi al
Uzbekis an 2030” s a egy and a planned uni ied “Digi al Ag icul u e” pla o m). Ou esea ch was mo i a ed by he
need o align such high-le el policy goals wi h p ac ical enable s a a m and ins i u ional le els, and o design a cohe en
amewo k ha add esses bo h economic and o ganiza ional ac o s.
Ou key indings can be summa ized as ollows. Fi s , cu en digi al up ake is nascen . While many Uzbek a me s own
sma phones, hei digi al skills a e limi ed and usage emains con ined o basic applica ions. Fa me s o en ely on
adi ional p ac ices and ha e minimal ad iso y suppo . Second, in as uc u e gaps pe sis . Al hough s a e-led ibe
p ojec s ha e imp o ed connec i i y in some a eas, u al in e ne se ice is s ill inconsis en – one illage in ou s udy
had much slowe , un eliable access han i s neighbo . Likewise, ou da ed wa e and ene gy sys ems cons ain e iciency
(e.g. aging i iga ion pumps and ese oi s). Thi d, policy and p og amma ic enable s a e eme ging. The au ho i ies plan
o consolida e o e 30 sepa a e ag icul u al se ices on o a single “Digi al Ag icul u e” pla o m, and ha e expanded
p e e en ial loans and subsidies o high-demand c ops and mode niza ion. FAO-led ini ia i es (e.g. he Digi al Villages
p og am) a e pilo ing IoT senso s in g eenhouses and aining you h inno a o s, helping o aise awa eness and skills.
Fou h, economic impac s o digi al in es men a e la ge bu lagging. Ou analysis (and case s udies) indica es ha
p ecision i iga ion, d one scou ing and managemen so wa e could cu inpu cos s by ~20–30% and boos yields by up
o 35%, wi h payback imes o 4–6 yea s – esul s ha mi o ecen Uzbek s udies. Howe e , wi hou s onge inancing
mechanisms hese e u ns emain la gely heo e ical o smallholde s. Fi h, agmen a ion and coo dina ion challenges
a e e iden . Fa me s cu en ly na iga e dozens o dispa a e digi al se ices ( o land, c edi , subsidies, e c.), c ea ing
ine iciencies and low adop ion. This agmen a ion highligh s he need o be e ins i u ional coo dina ion – a cen al
hesis o ou p oposed amewo k.
These indings la gely align wi h global and egional esea ch on digi al ag icul u e. In low- and middle-income coun ies
(LMICs), schola s consis en ly ind ha mul iple in e ac ing ac o s – om in as uc u e and inance o skills and
ins i u ions – shape echnology adop ion. Fo example, a ecen e iew o digi al ag icul u e in LMICs no ed ha
socioeconomic, echnological, ins i u ional and beha io al ac o s a e all in luen ial, and ecommended in eg a ed
s a egies o add ess many ba ie s a once. Ou wo k suppo s his: isola ed e o s (e.g. imp o ing connec i i y alone)
a e unlikely o succeed wi hou also ackling educa ion, c edi , and ma ke links in andem. Simila ly, Manzoo e al.
(2025) conclude ha policymake s and de elopmen agencies mus deploy mul i- ace ed s a egies o sus ain up ake.
Ou emphasis on ins i u ional suppo and capaci y echoes s udies om China and elsewhe e. Zheng e al. (2025) ound
ha go e nmen suppo and a m manage s’ digi al capabili y we e necessa y condi ions o ag icul u al digi aliza ion.
In China’s u al sec o , na ional policies and subsidies o coope a i es and amily a ms ha e spu ed echnology use,
bu challenges emain in in as uc u e and s akeholde skills. This ma ches he Uzbek case: bo h go e nmen s p omo e
sma a ming, bu on- he-g ound gaps in in es men and li e acy a e simila . Regional expe ience also ein o ces ou
conclusions. Fo ins ance, in Cen al Asia, Kazakhs an’s p esiden has p oposed linking a m subsidies di ec ly o he
adop ion o ad anced echnologies, implici ly a i ming ha economic incen i es can d i e digi al up ake. He also no ed
ha agmen ed da a sys ems unde mine policy, calling o in eg a ed digi al in as uc u e and a new ag icul u al census.
Uzbekis an’s plan o uni e 30 pla o ms in o one can be seen as a esponse o he same issue o da a agmen a ion.
Compa isons wi h FAO/IFAD analyses u he alida e ou indings. FAO’s Digi al Villages in Uzbekis an epo
highligh s low ech amilia i y and limi ed ad iso y se ices – mi o ing ou disco e y o insu icien knowledge-sha ing
and ex ension suppo . Likewise, an IFAD syn hesis o Asia-Paci ic emphasizes ha many smallholde a me s s ill ace
“limi ed access o digi al echnologies and in o ma ion asymme y,” e en as mobile connec i i y ises. These
obse a ions align wi h ou inding ha , despi e widesp ead sma phone owne ship, Uzbek a me s lack access o
ailo ed ag icul u al apps and da a. Finally, Uzbek- ocused s udies epo compa able gains and cons ain s. Alimboe
(2025) documen s ha sma i iga ion and d ones can slash cos s by a qua e and aise yields by one- hi d, bu ci es
in as uc u e, li e acy and inancing sho alls – he same ba ie s ou amewo k seeks o add ess.
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Despi e hese consis encies, ou s udy also e eals gaps and con adic ions in he li e a u e and p ac ice. One ension is
be ween ambi ious policy he o ic and a m-le el eali ies. Fo example, Uzbekis an’s leade s ha e announced a uni ied
“Digi al Ag icul u e” pla o m o s eamline se ices, ye on he g ound a me s s ill juggle dozens o sepa a e sys ems,
indica ing a policy–implemen a ion lag. This mi o s P esiden Tokaye ’s obse a ion in Kazakhs an ha disconnec ed
da a lead o un eliable decisions – a p oblem no ye sol ed in Uzbekis an. Ano he gap is he ela i e lack o ocus on
small and medium ag ibusinesses in exis ing esea ch. Many global s udies (and ou s o da e) emphasize la ge
coope a i es o s a e a ms, whe eas Uzbek ag icul u e emains agmen ed in o many small a ms. This sugges s he
need o mo e esea ch on a m-scale adap a ion s a egies and business models o smallholde s. We also no e ha while
“Ag icul u e 4.0” echnologies (AI, IoT, d ones) a e o en he alded, ew s udies (including ou s) deeply examine he
ins i u ional and economic changes equi ed o in eg a e hem sus ainably.
Mo eo e , ce ain componen s o he digi al ansi ion a e unde -explo ed. Issues like da a go e nance, cybe secu i y,
and u al o ganiza ional lea ning me i mo e a en ion. Fo ins ance, none o he exis ing wo ks ully add ess how Uzbek
coope a i es and ex ension se ices migh need o es uc u e o use digi al ools e ec i ely. Ou s udy begins o cha an
“o ganiza ional-economic amewo k,” bu empi ical alida ion is needed. Finally, egional coo dina ion is an open
ques ion: while Uzbekis an is acing ahead wi h digi al ag i-ini ia i es, ansbounda y issues (e.g. wa e da a sha ing,
c oss-bo de ma ke s) could a ec ou comes. These dimensions and o he s such as gende equi y in ech access (women
pe o m much a m labo ) – ep esen a enues o u u e esea ch.
In sum, ou discussion si ua es Uzbekis an’s expe ience wi hin b oade digi al ag icul u e de elopmen s. I unde sco es
ha while Uzbekis an’s ision aligns wi h global ends (digi al a m da a, p ecision echniques, in eg a ed pla o ms), i s
success will depend on b idging policy o p ac ice. As he li e a u e sugges s, his will equi e holis ic s a egies ha
coo dina e echnology, aining, inance and ins i u ions concu en ly. Recognizing he di e se ac o s a play, ou
o ganiza ional–economic amewo k o e s a oadmap o syn hesize Uzbek policy wi h a m-le el adop ion eali ies.
Fu he wo k should es his amewo k empi ically and e ine i o ensu e ha Uzbekis an’s ag ibusiness can ully
bene i om he digi al e olu ion.
CONCLUSION
Ag icul u e emains he la ges sec o o Uzbekis an’s economy, and i s u he de elopmen h ough digi aliza ion is
iden i ied as a na ional p io i y. This s udy hypo hesized ha a dedica ed o ganiza ional–economic amewo k could
accele a e ag ibusiness g ow h by aligning echnology adop ion, policy suppo , and economic incen i es. Globally,
digi al ag icul u e is expanding apidly: indus y o ecas s p ojec he digi al-ag icul u e ma ke o g ow om USD
24.2 billion in 2024 o USD 39.8 billion by 2029. Technology adop ion among a me s is ising s eadily – o example,
one su ey no ed a 3-pe cen age-poin inc ease (2022–24) in g owe s adop ing new digi al ope a ional ools. Leading
inno a ions a e ope a ions- ocused (e.g. digi al ag onomy pla o ms and p ecision ha dwa e). These ends con i m ha
e iciency- and p oduc i i y-d i en echnologies a e gaining ac ion wo ldwide, suppo ing he s udy’s p emise ha
ag ibusinesses can bene i om emb acing digi al ools.
The analysis hen ocused on Uzbekis an’s eadiness. The go e nmen has launched mul iple ini ia i es o mode nize
ag icul u e. No ably, a p esiden ial dec ee ( he “S a egy o he De elopmen o Ag icul u e 2020–2030”) explici ly calls
o a ansi ion o a digi al ag o- ood sys em, and he “Digi al Uzbekis an – 2030” s a egy alloca es USD 2.5 billion o
ICT in as uc u e. These policies ha e spu ed conc e e p og ams: o example, an FAO-suppo ed “Sma Fa ming”
p ojec is digi izing g eenhouse p oduc ion and aining g owe s on da a-d i en echniques. Uzbekis an is e en pilo ing
digi al ield pla o ms (e.g. o co on and g ain) and equipping 3,500 machines wi h GPS o enable eal- ime ag icul u al
moni o ing. A he same ime, signi ican gaps emain. B oadband and 4G ne wo ks a e s ill concen a ed in ci ies, and
digi al li e acy is limi ed in u al a eas. Na ional epo s also highligh une en ICT de elopmen ac oss egions and weak
coo dina ion be ween go e nmen al and p i a e ICT sec o s. In summa y, al hough s a egic ounda ions and pilo
p og ams a e in place, in as uc u e and human-capaci y cons ain s empe Uzbekis an’s cu en eadiness o ull-scale
digi al ag icul u e.
The hi d pa o he s udy iden i ied key enable s and ba ie s. On he enabling side, go e nmen suppo and ea ly
echnology adop e s a e no able. Many ad anced a ms in Uzbekis an al eady use elemen s o a “sma a m” (e.g.
obo ic milking, au oma ed eeding, clima e con ol, and li es ock managemen sys ems). This shows ha when
condi ions pe mi , digi al ools can imp o e e iciency. Howe e , ou indings unde sco e se e al majo ba ie s. High
capi al cos s and limi ed inancing mean mos a ms canno a o d ICT in es men s. Ru al p oduce s o en lack digi al
skills and a e in imida ed by complex echnology. Poo in e ne connec i i y (limi ed co e age and low bandwid h)
u he hampe s adop ion ou side ci ies. These obs acles mi o global pa e ns: o ins ance, McKinsey epo s ha mo e
han hal o No h Ame ican a me s equi e clea ROI e idence be o e adop ing ag ech, and one- hi d o Eu opean
a me s ci e small scale as a ba ie . Thus, al hough Uzbekis an has policy suppo , ac ual implemen a ion depends on
o e coming hese economic and human-capaci y cons ain s.
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Finally, he p oposed o ganiza ional–economic amewo k was assessed agains he s udy’s indings. The amewo k’s
componen s align well wi h he iden i ied needs and ends. Fo example, i emphasizes building digi al in as uc u e and
a me aining p og ams o b idge he connec i i y and li e acy gaps no ed abo e. I also calls o s onge ins i u ional
coo dina ion and inno a ion clus e s, di ec ly add essing he agmen ed ICT go e nance ound in Uzbekis an. In his
way, each elemen o he amewo k co esponds o one o he esea ch objec i es and e idence om he li e a u e. The
empi ical and quali a i e esul s hus alida e he amewo k’s assump ions. O e all, he e idence suppo s he
hypo hesis: a s uc u ed o ganiza ional–economic amewo k ha aligns na ional s a egy, s akeholde oles, and
economic incen i es can indeed acili a e digi al ag ibusiness de elopmen in Uzbekis an. In p ac ice, his means
implemen ing he amewo k’s ecommenda ions (expanding u al b oadband, in es ing in digi al educa ion, suppo ing
ag i- ech s a ups, and aligning public–p i a e ini ia i es) o o e come he gaps we iden i iedz. In conclusion, he s udy’s
indings con i m he alue o he p oposed amewo k and sugges ha i p o ides a sound guide o u u e policy and
in es men .
REFERENCES
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