Năs ase, Ma ian; C oi o u, Gab iel; Valen ina, Flo ea Nicole a; C is ache, Nicole a;
Lile, Ramona
A icle
The pe cep ions o employees om Romanian companies
on adop ion o a i icial in elligence in ec ui men and
selec ion p ocesses
Am i ea u Economic Jou nal
P o ided in Coope a ion wi h:
The Bucha es Uni e si y o Economic S udies
Sugges ed Ci a ion: Năs ase, Ma ian; C oi o u, Gab iel; Valen ina, Flo ea Nicole a; C is ache, Nicole a;
Lile, Ramona (2024) : The pe cep ions o employees om Romanian companies on adop ion o
a i icial in elligence in ec ui men and selec ion p ocesses, Am i ea u Economic Jou nal, ISSN
2247-9104, The Bucha es Uni e si y o Economic S udies, Bucha es , Vol. 26, Iss. 66, pp. 421-439,
h ps://doi.o g/10.24818/EA/2024/66/421
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Inno a i e Applica ion o AI in Business Impac ing Socio-Economic P og ess
AE
Vol. 26 • No. 66 • May 2024 421
THE PERCEPTIONS OF EMPLOYEES FROM ROMANIAN COMPANIES
ON ADOPTION OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT
AND SELECTION PROCESSES
Ma ian Năs ase1, Gab iel C oi o u2, Nicole a Valen ina Flo ea3,
Nicole a C is ache4 and Ramona Lile5
1) Bucha es Uni e si y o Economic S udies, Bucha es , Romania.
2)3) Valahia Uni e si y o Ta go is e, Ta go is e, Romania.
4) Duna ea de Jos Uni e si y o Gala i, Gala i, Romania.
5) Au el Vlaicu Uni e si y o A ad, A ad, Romania.
Please ci e his a icle as:
Năs ase, M., C oi o u, G., Flo ea, N.V., C is ache, N. and
Lile, R., 2024. The Pe cep ions o Employees om
Romanian Companies on Adop ion o A i icial
In elligence in Rec ui men and Selec ion P ocesses.
Am i ea u Economic, 26(66), pp. 421-439.
DOI: h ps://doi.o g/10.24818/EA/2024/66/421
A icle His o y
Recei ed: 28 Decembe 2023
Re ised: 27 Feb ua y 2024
Accep ed: 29 Ma ch 2024
Abs ac
Manage s inc easingly wan o imp o e he e iciency o human esou ces p ocesses, and a
solu ion wi h eal esul s is A i icial In elligence (AI), which p o ides eal esul s in a i ual
wo ld o human esou ces manage s, o companies, and also o candida es. The pu pose o
his a icle is o in es iga e he pe cep ion o employees in Romanian companies o adop and
use AI in ec ui men and selec ion p ocesses, analysing he ac o s ha in luence his accep ance
in en ion using Technology Accep ance Model (TAM). The s udy aimed o de e mine he
bene i s o AI adop ion in ec ui men and selec ion p ocesses, he pe cei ed use ulness o
adop ion, and he ease o use in hese p ocesses. The esul s ob ained showed ha almos all he
a iables p oposed o he model posi i ely in luenced he in en ion o accep and use AI in he
ec ui men and selec ion p ocess. Non-disc imina ion and he u ili y o using (PU) AI in
ec ui men and selec ion had li le in luence. The indings should con ibu e o unde s anding
he accep ance o a i icial in elligence in he wo p ocesses p oposed o analysis and obse e
i s impac on i s adop ion among employees in di e en ields.
Keywo ds: a i icial in elligence, human esou ces, Romanian companies, ec ui men ,
selec ion, e iciency.
JEL Classi ica ion: O15, P42, C52.
Co esponding au ho , Ma ian Năs ase – e-mail: [email p o ec ed]
This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons
A ibu ion License, which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in
any medium, p o ided he o iginal wo k is p ope ly ci ed. © 2023 The Au ho (s).
AE
The Pe cep ions o Employees om Romanian Companies on Adop ion
o A i icial In elligence in Rec ui men and Selec ion P ocesses
422 Am i ea u Economic
In oduc ion
Due o globalisa ion, he inc eased use o echnology, business complexi y, IT-based
echnologies, and a i icial in elligence (AI) is inc easingly used in a ious ields o ac i i y.
AI is used in human esou ces (HR) p ocesses such as: ec ui men (Ho odyski, 2023) and
acquisi ion o new alen (Madeline Lau ano, Co- ounde & Chie Resea ch O ice), selec ion
and in e iewing (Ghee a and Bhanu S ee Reddy, 2018), p ocesses employmen (Kelan,
2023), aining and communica ion (O e and Sposa o, 2021), imp o ing he wo k clima e
(De Obesso A ias, Pé ez Ri e o and Ca e o Má quez, 2023), b inging a ious bene i s
(Yada and Kapoo , 2023).
Almos 30% o companies use AI o he ec ui men p ocess o educe ime and b ing he
igh employee wi h he igh alen o he igh place a he igh cos : educe ime-consuming
ac i i ies, au oma e CV e alua ion, ma ch candida e skills o job equi emen s, elimina e
pauses be ween p ocesses, make decisions much easie using big da a, p edic u u e esul s,
easily connec candida es wi h specialis s, easily manage candida e iles o quickly ex ac
key in o ma ion abou candida es. Many companies ha e al eady implemen ed AI in hese
p ocesses and a e measu ing i s accep ance among hei u u e employees (Vedap adha,
Ha iha an and Shi akami, 2019). AI is abou hinking quickly and logically based on a lo o
knowledge a i s disposal (Gee ha and Bhanu S ee Reddy, 2018), educing ime and cos in
mee ing he igh candida e wi h he acancy.
In he pandemic and pos -pandemic pe iod, AI in ec ui men and selec ion inc eased in
u ili y o indi iduals and also o specialis s who wan a mo e compe i i e p o ile o he
candida e (Anghel, 2023). Machines ha e al eady changed many con en s o jobs, bu now a
human- echnology coope a ion is being es ablished based on na u al language p ocessing
(NLP), oice ecogni ion (VR), machine lea ning p ocess, deep lea ning, neu al ne wo ks
(Eu banks, 2018), p oblem sol ing, au oma ion o ec ui men and selec ion (O e and
Sposa o, 2021). All hese bene i s a e making AI a ac i e o o ganisa ions who look o
alen ed mul i-skills employees.
AI was used o he i s ime in 1956 by he a he o AI, John McCa hy, and now AI has
o e ed he oppo uni y o use ec ui men and selec ion unc ions as being conduc ed in sma
ways (O e and Sposa o, 2021), b inging new oppo uni ies and challenges, and achie ing
impo an objec i es. Howe e , e en i en e p ises use AI in many p ocesses, he human
elemen will emain a i al componen o he p ocess.
The s udy is s uc u ed as ollows: in Sec ion 1 is he li e a u e e iew is p esen ed, along
wi h some impo an ad an ages o ec ui men and selec ion p ocesses based on using AI.
Mo eo e , he esea ch hypo hesis and he concep ual model o he analysis also a e
es ablished. In Sec ion 2 he esea ch me hodology is p esen ed, wi h a ocus on esea ch
design and con ex , consis ing in he p ocess o da a collec ion and analysis. The esul s and
esea ch discussion a e p esen ed in Sec ion 3, which con ains, in he inal pa , he heo e ical
and manage ial con ibu ions o he a icle; he limi a ions and u u e esea ch p oposals a e
also p esen ed.
Inno a i e Applica ion o AI in Business Impac ing Socio-Economic P og ess
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Vol. 26 • No. 66 • May 2024 423
1. Li e a u e e iew and esea ch hypo hesis
1.1. AI and ec ui men p ocess
Acco ding o Upadhyay and Khandelwal (2018), he applica ion o AI in HR managemen
has been one o he mos no able ends among ec ui men p o essionals. The e a e many
ad an ages o using AI in he ec ui men p ocess, so we men ion only a ew, based on which
some esea ch hypo heses ha e been es ablished.
These ad an ages mainly e e o he educed ime, whe e he so wa e used in oday's
ec ui men ma ke s uses AI o scan he bes possible candida es in a sho ime (Collins, 2018),
p o iding a sho lis and a anking o he mos p omising candida es (Fe nández and Fe nández,
2019). Ano he ad an age would be he low cos and easy anking o he candida es. The e a e
many applica ions o inding a job, bu using AI companies can easily ank candida es o
sho en he hi ing p ocess (Faliagka e al., 2012), anking candida es and ecognising candida es
wi h he bes sco es and educing en i onmen al impac (Lep i e al., 2018).
Imp o ed speed using AI makes ec ui men as e (Collins, 2018), becoming a ac i e and
mo e cos -e ec i e and pe o med a high speed ( an Esch and Black, 2019) and e icien ly
(Lamikan a and Oba e ni-Ajayi, 2023). The "anywhe e any ime" p inciple and he websi e
can p o ide di e en in o ma ion, any ime i can be accessed om anywhe e, and c ea e he
abili y o a ac and e ain he igh people (Cohen, 2001), p o iding 24/7/365 accessibili y
based on jus -in- ime sys ems o a ac new candida es (Nawaz and Gomes, 2019) conside ed
an asse in oday's " alen wa " (Leich -Deobald e al., 2019). Using AI in R&D p o ides
equal oppo uni ies and non-disc imina ion. Using AI, esumes a e sc eened ai ly, gi ing
equal chances o all candida es (Upadhyay and Khandelwal, 2018). Thus, non-disc imina ion
is educed (Kelan, 2023) and e hics-based ision inc eases (Tambe, Cappelli and
Yakubo ich, 2019). Wo k di e si y and eliabili y a e o he pe ks ha alen ed employees
wan . Non-judgmen al is he bigges ad an age (Ho odisky, 2023), AI igno es he
backg ound o candida es and helps o ind he igh alen , be e e alua ions, di e si y he
employee po olio and a g ea e di e si y o candida es (Lewis, 2018), o an inclusion mo e
e ec i e socio-economic o u u e employees. Focusing on skills and ex ac ing in o ma ion
makes he p ocess o scanning da a on skills and knowledge a bene icial p ocess, and by
de ec ing and collec ing hem (S ua and No ig, 2016), hey lead o an e ec i e ec ui men
p ocess. CV upda ing using AI p o ides he possibili y o check he skills o he employees
and also p o ides he possibili y o upda e he da a o o he jobs (Ghee a and Bhanu S ee
Reddy, 2018). Thus, we can de elop he ollowing esea ch hypo heses:
H1- Rec ui men p ocess based on AI has a posi i e e ec on In en ion o adop AI in R&S
p ocesses and also o he hypo hesis as:
H1a-H1j- Time sa ing/ cos sa ing/ speed/ anywhe e/ any ime/ equal chances/ non-
disc imina ion/ wo k di e si y/ ocus on compe ency/ con inuous CV upda ing ha e a
posi i e impac on In en ion o adop AI in ec ui men p ocesses.
1.2. AI and selec ion p ocess
The li e a u e on AI and he selec ion p ocess has al eady been analysed since he ea ly 2000s,
and he pe cep ions o he use o new echnologies in he selec ion p ocess and he job
in e iew ha e o e ed nume ous ad an ages. Reducing he cos s o in e iewing using AI is
a eal bene i : he amoun o manual wo k dec eases and he ime o ocus on he igh
candida es inc eases (Guchai e al., 2014), ec ui e s can ins an ly ela e o alen ed
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The Pe cep ions o Employees om Romanian Companies on Adop ion
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424 Am i ea u Economic
candida es (Leong, 2018), using in e iews a dis ance ha a e e y e ec i e in helping o
achie e speci ic goals h ough lexible adap a ion. Da a p i acy becomes e y impo an , and
da a mining mus be done based on AI egula ions, and da a p o ec ion mus be pe cei ed as
an e hical issue (Oswald e al., 2020), acco ding o he Eu opean Gene al Da a P o ec ion
Regula ion (GDPR).
Using da a mining and AI, p edic ions can be made and decisions can be made (Hmoud and
Laszlo, 2019), o in o ma ion can be ex ac ed based on CV scanning, bu based on da a
con iden iali y. Da a secu i y, using AI p o ides a sa e en i onmen (Tilmes, 2022), whe e
candida es can, o example, ha e di e en ques ions and answe s in a secu e pla o m,
ega ding bene i co e age, aca ion lea e, o pay le el e alua ion. AI handles all ypes o
que y using cha box, email o m, o a i ual con e sa ion in a mee ing oom (Ghee a and
Bhanu S ee Reddy, 2018). Quick eedback leads o a quick esponse o candida es because
au oma ed emails a e used, so he ela ionship wi h he candida e is quick and he esponse
is ime and cos e icien (Ghee a and Bhanu S ee Reddy, 2018).
AI enables apid eedback abou a candida e's ejec ion, his aining p og ammes, knowledge
and skills ha an employee can de elop in he u u e (Upadhyay and Khandelwal, 2018).
Thus, AI acili a es apid communica ion as he Web, social media, o mobile
communica ions a e used (Upadhyay and Khandelwal, 2018). By educing a ou i ism using
AI in he selec ion p ocess, many ad an ages can be achie ed: less nepo ism and a ou i ism
(Lange e al., 2019; Lange , König and Papa hanasiou, 2019; Lange , König and Hemsing,
2020; Suen, Chen and Lu, 2019), highly quali ied candida es (Pe sson, 2016), p ocess
co ec ness and p ecision due o p edic ion algo i hms (Polli, 2019) and a iables ha do no
need o be p ede ined by RU specialis s (Polli, 2019).
By sc eening candida es, companies can easily check candida e skills and knowledge
(Fo bes, June, 2018), and using he cha box, hey can in e ac wi h candida es by helping
answe ques ions o p o iding eedback and eques ed in o ma ion (Ghee a and Bhanu S ee
Reddy, 2018). Cha bo s, as AI ools, help in sc eening and upda ing he candida e base using
cha , email, o ex messages (Upadhyay and Khandelwal, 2018). Job skill ma ching leads o
an e icien AI-based selec ion p ocess and is when a sui able candida e is ound based on
he ma ching p inciple and less pape is used (Dickson and Nusai , 2010). A apid assessmen
using AI o he candida e is based on he da a pos ed on social media, so he selec ion
specialis s ha e access o hei alues, a i udes, and pe sonali y ai s (Upadhyay and
Khandelwal, 2018).
The ideo in e iew is e y popula , uses a sho se o p ede e mined ques ions, and can
analyse he candida e's compe ences, skills, bu also non- e bal communica ion, such as body
language, acial exp essions, o oice (in lec ion, one, hy hm, speed) (Tambe, Cappelli and
Yakubo ich, 2019; an Esch and Black, 2019). The applica ion compa es each in e iewed
candida e wi h he mos alen ed employees in he company, and hen he bes one is
sugges ed (Hi eVue, 2018). Rapid assessmen o he igh candida e consis s o p e-sc eening
and so ing CVs and hen ma ching hem o acancies. The manage s' ask is now o ind
quali ied candida es based on inc eased speed and e iciency (Dickson and Nusai , 2010). A
apid assessmen o hei skills and knowledge is used based on AI (Faliagka e al. 2012).
When we alk abou alen managemen , we a e alking abou a sys em ha can suppo he
o ganisa ion's objec i es and ha acili a es he de elopmen o a sys em o con ol and
measu emen o esul s and ha e eals he s ong co ela ions be ween e o s and
pe o mances (Si niko , Mihalcea and Romanescu, 2023). By mining da a, he sys em may
Inno a i e Applica ion o AI in Business Impac ing Socio-Economic P og ess
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Vol. 26 • No. 66 • May 2024 425
ga he in o ma ion ela ed o a ailabili y, con ac in o ma ion, skills, knowledge, a i udes,
aining p og ammes, and expe iences, esidency o ne sala y expec a ions. Thus, AI can
p o ide he abili y o book a mee ing, schedule one, o o de ood wi hou he in ol emen
o a ec ui men specialis (Ghee a and Bhanu S ee Reddy, 2018). Thus, he ollowing
hypo heses we e de eloped:
H2- Selec ion p ocess based on AI has a posi i e e ec on In en ion o adop AI in R&S
p ocesses and also:
H2a-H2j- Reduced cos s/ p i acy/ secu i y/ ins an eedback/ lack o a ou i ism/ apid
sc eening/ ma ch skills and job/ e icien ideo in e iewing/ quick e alua ion/ da a
ex ac ion ha e a posi i e impac on in en ion o adop AI in selec ion p ocesses.
1.3. Technology Accep ance Model (TAM)
The echnology accep ance model (TAM) p oposed by Da is is explaining he impac ac o s
necessa y o adop ion o new echnologies (Da is, 1989) and is e y used in in o ma ion
sys ems esea ch. The TAM elies on wo ac o s: pe cei ed use ulness (PU) and pe cei ed
ease o use (PEU). PU e e s o he inc ease in pe o mance based on he use o new
echnologies and PEU o he accep ance o new echnologies wi hou much e o (Na e al.,
2022).
TAM is a model ha measu es he deg ee o accep ance and use o echnology in human-
compu e in e ac ion (G ani and Ma anguni, 2019) and is conside ed a e y impo an model
used o de e mine he deg ee o adop ion o i s use in a ious ields o inno a i e ac i i y
(Lai, 2017). The main idea o his model is o analyse he use 's cu en ela ionships,
beha iou , in en ions, a i udes, belie s, and no ms. In 1993 i was e hough o unde s and
i s u ili y and accep ance o IT sys ems used in ce ain p ocesses (Chen e al., 2016). Many
esea che s use TAM, adding a ious o he a iables such as gende , educa ional le el, o
pa icipa ion in a ious aining p og ams (Ma ono e al., 2020); he e o e, in addi ion o
esea che s who used i in ec ui men and selec ion p ocesses, i was also used in his s udy
p ecisely o highligh he ole, impo ance, and bene i s b ough by he use o AI in he
ec ui men and selec ion p ocesses among employees in Romanian companies.
The model s a es ha a pe son's a i ude owa ds using echnology in ce ain p ocesses is
in luenced by hei pe cep ion o he ease and use ulness o using echnology (Byun, 2018).
Pe cei ed use ulness (PU). S udies de e mined ha AI is used in ec ui men because i is
iendly and un and is used o a ac he in en ion o job seeke s (B ahmana and B ahmana,
2013) and o e con ol (Lin, 2010). PU and a i ude ully media e he ela ionship be ween
e-WOM om e- ec ui men and he beha iou al in en ions o job seeke s (Kau and Kau ,
2023). The e o e, he ollowing hypo hesis was p oposed.
H3- PU has a posi i e e ec on in en ion o adop AI in R&S p ocesses.
Pe cei ed ease o use (PEU). PEU has a di ec impac on a i ude o use e- ec ui men ;
esul s indica ed ha job seeke s adop e- ec ui men when i is use - iendly and when help
hem o accomplish hei asks easily and e icien ly (Kau and Kau , 2023), when websi e is
in e es ing, when e- ec ui men is c ea ing he desi e o choose he company as a po en ial
employe o when is c ea ing he desi e o p omp ly apply o a job, when websi e is play ul,
o e e- us o c ea e a posi i e ela ionship (P iyada shini, S eejesh and Anus ee, 2017), o
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The Pe cep ions o Employees om Romanian Companies on Adop ion
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426 Am i ea u Economic
o e s con ol o job seeke (Lin, 2010). The e o e, he ollowing esea ch hypo hesis was
de eloped.
H4- PEU has a posi i e e ec on he in en ion o adop AI in R&S p ocesses.
Based on he li e a u e e iew and TAM, we de eloped he concep ual model (Figu e no. 1),
whe e AI used in ec ui men and selec ion p ocesses (Pa ikh, Pa el and Jaiswal, 2021) has
an impo an impac on he in en ion o adop AI in hese p ocesses, and PU (Lin, 2010;
B ahmana and B ahmana, 2013) and PEU (Lin, 2010; P iyada shini, S eejesh and Anus ee,
2017; Kau and Kau , 2023) ha e an in luence on he in en ion o adop AI in R&S p ocesses.
Figu e no. 1. S uc u al model
Sou ce: au ho s' p ocessing
2. Resea ch Me hodology
The goal o his pape is o in es iga e he impac o ec ui men and selec ion p ocesses
based on AI on he in en ion o adop AI in hese p ocesses, and also he in luence o PU and
PEU on he in en ion o use AI in hese analysed p ocesses. In ou s udy, TAM was used,
Inno a i e Applica ion o AI in Business Impac ing Socio-Economic P og ess
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Vol. 26 • No. 66 • May 2024 427
which p o ides a clea amewo k ha helps o ganisa ions o e alua e hei beha iou al
in en ion o adop echnology in R&S p ocesses.
O he esea ch objec i es would be o de e mine he bene i s o using AI in he ec ui men
and selec ion p ocesses ha each candida e enjoyed, he pe cei ed use ulness o adop ing AI
in he ec ui men and selec ion p ocesses, he pe cei ed ease o use o AI in hese p ocesses,
and he deg ee o adop ion in he u u e pe iod o AI wi hin hese p ocesses.
In ou esea ch, a quan i a i e s udy was used, based on he de e mina ion o he ela ionships
de eloped and as esea ch hypo heses. A ace- o- ace and online ques ionnai e was used,
de eloped, and applied in No embe 2023. A o al o 250 ques ionnai es we e dis ibu ed o
esponden s who we e ec ui ed and selec ed using AI. These we e ob ained om con ac
wo ke s in Romania, who we e ec ui ed and selec ed using AI be o e being hi ed. O he
o al, 56% o he esponden s a e male, 68% o he esponden s a e om u ban a eas, almos
38% ha e mas e 's and doc o a e deg ees, and 27% a e om he 36-45 age g oup, and 74%
hold an execu i e posi ion. A pe cen age o 43.2% we e in manu ac u ing, 34% in educa ion,
27% in IT, 22% in inance and banking and 8% in heal h. Rela ed o he wo a iables
analysed, ega ding he use o AI in ec ui men , 13.6% used ec ui men agency po als, 38%
he company websi e, 35.6 LinkedIn, and 12.8% o he media si es; and in he selec ion,
69.2% we e subjec ed o an online in e iew, 26.8% o online es s, and 10% o a ideo
in e iew. The demog aphics o he esponden s a e shown below (Table 1).
Table no. 1. Demog aphic cha ac e is ics o he esponden s
Cha ac e is ic
N
%
Cha ac e is ic
N
%
Cha ac e is ic
N
%
Gende
Male
Female
Residence
U ban
Ru al
Field o
ac i i y
P oduc ion
Educa ion
Finance and
Banking
IT/Technology
Heal h
140
110
170
80
108
85
22
27
8
56
44
68
32
43.2
34
8.8
10.8
3.2
Educa ion
College
Bachelo ’s
deg ee
Mas e ’s
deg ee
Doc o a e
Func ions
Managemen
Execu ion
Selec ion
using AI
Online
in e iew
Online es s
The ideo
in e iew
32
82
94
42
65
185
173
67
10
12.8
32.8
37.6
16.8
26
74
69.2
26.8
4
Age
< 25 yea s
26-35 yea s
36-45 yea s
46-54 yea s
> 55 yea s
Rec ui men
using AI
Agency po als
Company
websi e
LinkedIn
O he media
si es
30
60
68
65
27
34
95
89
32
12
24
27.2
26
10.8
13.6
38
35.6
12.8
Sou ce: au ho s' p ocessing
3. Resul s and discussions
The ques ionnai e (Table no. 2) was de eloped using a i e-poin Like scale (1- s ongly
disag ee and 5- s ongly ag ee).
AE
The Pe cep ions o Employees om Romanian Companies on Adop ion
o A i icial In elligence in Rec ui men and Selec ion P ocesses
428 Am i ea u Economic
The s uc u al model examined esponden s' pe cep ions o he in en ion o adop R&D
p ocesses based on he use o AI. Focusses on ac o s such as ec ui men , selec ion,
pe cei ed ease o use, pe cei ed use ulness, and ac ual use o echnology.
Table no. 2. Con i ma o y Fac o Analysis and Desc ip i e s a is ics
Cons uc
I em
Measu e
Mean
VIF
Loading
(S .Es .)
Ch o
alpha
AVE
CR
1. AI and R&S p ocesses
1.1. AI and ec ui men p ocess
AIR01
Time sa ing
4.70
3.026
0.873
0.842
0.682
0.792
AIR02
Cos sa ing
4.38
3.296
0.807
AIR03
Inc eased speed
4.31
1.954
0.702
AIR04
Apply om
anywhe e
4.20
3.397
0.744
AIR05
Apply any
momen
4.30
1.240
0.798
AIR06
Equal chances o
candida es
3.90
2.239
0.740
AIR07
Disc imina ion is
elimina ed
3.70
1.127
0.853
AIR08
A mo e di e se
wo k o ce
3.80
1.392
0.926
AIR09
Focus is on
compe ency
4.00
2.370
0.876
AIR10
Imp o e
con inuous and
upda e CVs
4.20
1.275
0.750
1.2. AI and selec ion p ocess
AIS01
Reduced cos s
4.60
2.682
0.800
0.796
0.676
0.847
AIS02
O e p i acy
3.80
1.279
0.888
AIS03
O e secu i y
3.40
1.021
0.740
AIS04
O e ins an
eedback
4.20
2.341
0.709
AIS05
Reduce
a ou i ism
3.80
1.642
0.830
AIS06
E icien and
apid sc eening
4.49
2.265
0.783
AIS07
Ma ch be ween
employees skills
and job acancy
4.44
2.089
0.867
AIS08
Video
in e iewing
allows o de ec
non- e bal
language
4.64
2.352
0.728
AIS09
O e quick
e alua ion
esponses
4.60
1.785
0.750
AIS10
Use in o ma ion
ex ac ion o
candida es skills
4.30
2.580
0.734
Inno a i e Applica ion o AI in Business Impac ing Socio-Economic P og ess
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Vol. 26 • No. 66 • May 2024 435
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