FinTech Services and Factors Determining the Expected Benefits of Users: Evidence in Romania for Millennials and Generation Z

101 2, XXIV, 2021 Finance 10.15240/ ul/001/2021-2-007 FINTECH SERVICES AND FACTORS DETERMINING THE EXPECTED BENEFITS OF USERS: EVIDENCE IN ROMANIA FOR MILLENNIALS AND GENERATION Z Oc a ian Dospinescu1, Nicole a Dospinescu2, Daniela-Ta iana Agheo ghiesei3 1 Alexand u Ioan Cuza Uni e si y, Facul y o Economics and Business Adminis a ion, Depa men o Business In o ma ion Sys ems, Romania, ORCID: 0000-0002-5403-8050, [email p o ec ed]; 2 Alexand u Ioan Cuza Uni e si y, Facul y o Economics and Business Adminis a ion, Depa men o Managemen and Ma ke ing, Romania, ORCID: 0000-0002-7097-7365, [email p o ec ed]; 3 Alexand u Ioan Cuza Uni e si y, Facul y o Economics and Business Adminis a ion, Depa men o Managemen and Ma ke ing, Romania, [email p o ec ed]. Abs ac : The pu pose o his esea ch is o de ine he le el o signi icance o a ious indica o s ha in luence he deg ee o consume sa is ac ion ega ding he use o FinTech echnologies and se ices. The mos impo an ac o s ha in luence he le el o sa is ac ion when using FinTech se ices we e conside ed: com o and ease o use, legal egula ions, ease o accoun opening, mobile paymen s ea u es, c owd unding op ions, in e na ional money ans e s ea u es, educed cos s associa ed wi h ansac ions, pee - o-pee lending, insu ances op ions, online b oke age, c yp ocoins op ions and exchange op ions. The s udy was conduc ed on a sample o 162 esponden s, pe sons belonging o he Millennials and Gene a ion Z gene a ions. The alues o he indica o s o di e en ca ego ies o use s o FinTech se ices and di e en ca ego ies o gene a ions can be de e mined based on he s a is ical es s pe o med and he esul s ob ained om he eg ession analysis. The alues o he indica o s a e he basic elemen s o de e mining he eg ession model ha will help he FinTech se ice endo s o make pe sonalized decisions o each ca ego y o use s so ha he le el o cus ome sa is ac ion is maximized. The s udy ca ied ou wi hin he p esen a icle is he i s o i s kind o Romania, because up o his momen in he specialized li e a u e he e a e no such s udies o Eas e n Eu ope. The esea ch we conduc ed aims o ill he gap exis ing in he li e a u e and esponds o he expec a ions and needs o s akeholde s in he FinTechs’ business a ea. The esul s o he a icle a e ele an o bo h s akeholde s and he scien i ic communi y ha is conce ned abou he impac o FinTech echnologies. Keywo ds: FinTech, Millennials, Gene a ion Z, FinTech cus ome s sa is ac ion. JEL Classi ica ion: M31, M37. APA S yle Ci a ion: Dospinescu, O., Dospinescu, N., & Agheo ghiesei, D.-T. (2021). FinTech Se ices and Fac o s De e mining he Expec ed Bene i s o Use s: E idence in Romania o Millennials and Gene a ion Z. E&M Economics and Managemen , 24(2), 101–118. h ps://doi. o g/10.15240/ ul/001/2021-2-007 In oduc ion The pu pose o his a icle is o iden i y he ac o s ha ha e a decisi e in luence on he le el o sa is ac ion o use s o FinTech se ices in Romania. To explain he a iables ha ha e an e ec , we conduc ed his s udy bo h in he en i e popula ion o FinTech use s, as well as di e en ia ed in o wo dis inc gene a ions: Millennials and Gene a ion Z. F om he poin o iew o age anges, consume s in he EM_2_2021.indd 101 31.5.2021 10:33:29 102 2021, XXIV, 2 Finance Millennials ca ego y a e also known in he special y li e a u e (Aichne & Shal oni, 2019) as Gene a ion Y, ha a e people bo n be ween he 1980s and he mid-1990s. Acco ding o Buco e chi e al. (2019), Gene a ion Z is he demog aphic coho ollowing Millennials and is made up o hose bo n be ween he second hal o he 1990s and ea ly 2000s. These wo gene a ions ha e di e en beha io s, p io i ies and p e e ences when i comes o he use o in o ma ion echnologies. FinTech is an eme ging end ha combines in o ma ion echnology wi h inancial se ices (Lee & Jae Shin, 2018), wi h he main ea u e being s ong inno a ion in he inancial indus y. Specialized s udies (Ryu, 2018) conside ha FinTech does no de ine a single sec o o ac i i y, bu co e s he en i e a ea o inancial p oduc s and se ices ha we e adi ionally o e ed by banking ins i u ions. A ne e al. (2015) de ine FinTech as a ange o p oduc s and se ices o e ed by non-banking ins i u ions ha use echnology dis up i ely. O he same opinion a e Gombe e al. (2018) who ha e come o he conclusion ha he classic banks a e unde a eal assaul om he inno a ions ealized by he newly c ea ed companies ha gene a e he concep o “FinTech Re olu ion”, pu ing in he ocus o end consume s and he desi e o con inuously imp o e hei expe iences. Cus ome s a e al eady in e ac ing wi h inancial obo s ha a e capable o sa is ying complex demands and making he igh decisions depending on he si ua ions in he clien ’s po olio. Acco ding o Zhang and Kedmey (2018), so wa e obo s can de ec audulen beha io s, help es ablish c i e ia and alues o insu ances, make beha io al p edic ions o help consume s o inancial se ices. The FinTech e e escence is con i med by he au ho s o he li e a u e (Kashyap e al., 2016) who es ima e ha by 2020 FinTech will each a ma ke sha e o 20% in he inancial se ices indus y. P essed by he compe i ion om FinTechs, banks a e hea ily in es ing in digi alisa ion in an a emp o e ain hei exis ing cus ome s. On he o he hand, Ash a and Bio -Paque o (2018) show ha FinTechs a e ying o ge cus ome s in wo ways: 1) by “ ec ui ing” he cus ome s o he classic banks and 2) by accessing he pe sons who we e no in he co e age a ea o banks (people who a e geog aphically dis an om bank b anches o pe sons who o a ious easons do no quali y o become a bank cus ome ). These dis up i e ac ions can lead o alliances be ween classic banks as well as be ween banks and FinTech challenge s in an a emp o p ese e hei cus ome base. The adop ion a es o FinTechs a y by coun y; hus, Zigu a (2019) shows ha he e a e coun ies wi h e y high adop ion a es (China – 69%, India – 52%, he Uni ed Kingdom – 42%, B azil – 40%) and coun ies wi h lowe adop ion a es (Belgium – 13%, Luxembou g – 13%, Japan – 14%, Canada – 18%). Behind hese adop ion a es o FinTech he e a e majo di e ences ega ding he a i ude o gene a ions o consume s. As a esul , in his esea ch we ocus on highligh ing he ac o s and a iables ha in luence he sa is ac ion and p e e ences o use s om he 2 echnologically ep esen a i e gene a ions: Millennials and Gene a ion Z. The a icle has he ollowing chap e s: In oduc ion, Li e a u e Re iew, Da a and Me hodology, Resul s, Discussion and Conclusions. 1. Li e a u e Re iew Assa zadeh and Abe oumand (2018) s a ed ha FinTech is a ph ase ha e e s o he combina ion o inancial se ices and in e ne - based echnologies, being an excellen example o inno a ion and indus ial in eg a ion. Specialized s udies (e.g. Wonglimpiya a , 2017) show ha a p esen , he banking landscape is cons an ly changing unde he in luence o in o ma ion echnologies. In his con ex , bo h banks and non-bank compe i o s a e adop ing FinTech wi h he e y clea pu pose o being close o cus ome s. This app oach alls wi hin he heo e ical amewo k de eloped by Da is (1989), ha is, in he TAM ( echnology accep ance model) model acco ding o which he main ac o s ha in luence he decision o adop he new echnologies a e: 1) pe cei ed ease o use and 2) pe cei ed use ulness. Ryu (2018) demons a ed ha end consume s’ in en ion o use FinTech depends on wo ca ego ies o ac o s: 1) pe cei ed bene i and 2) pe cei ed isk. Fac o s such as economic bene i , con enience and seamless ansac ion a e included in he pe cei ed bene i ca ego y. The pe cei ed isks all in o ou ca ego ies: inancial isk, legal isk, secu i y isk and ope a ional isk. In his app oach Hu e EM_2_2021.indd 102 31.5.2021 10:33:29 103 2, XXIV, 2021 Finance al. (2019) show ha he demand o he use s o he se ices o e ed by he FinTech companies depends e y much on he popula i y o he in e ne and he a ailabili y o sma mobile de ices. Also, go e nmen suppo can in luence he deg ee o accep ance o FinTech se ices by end consume s, while pe cei ed isk has a nega i e impac on us in adop ion and use. In e ms o ease o use, esea ch shows ha i has no signi ican in luence on he decision o adop FinTech se ices. In he same line o ideas, Dospinescu e al. (2019) show ha he decision o adop banking p oduc s and se ices di e s acco ding o he age gene a ion o which he inal consume s belong. F om an a chi ec u al poin o iew, Lee and Jae Shin (2018) conside ha he FinTech ecosys em is made up o i e majo componen s: (1) FinTech s a ups, (2) echnology de elope s, (3) go e nmen , (4) inancial cus ome s and (5) adi ional inancial ins i u ions. These componen s con ibu e symbio ically o he inno a i e p ocess, s imula e he economy, encou age compe i ion and gene a e he need o collabo a ion in he inancial indus y. Wi hin his complex ecosys em, FinTech s a ups ha e a cen al place because hey a e he mos en ep eneu ial componen , gene a ing inno a ions ha con inuously imp o e he inancial indus y. Schul e and Liu (2018) belie e ha adi ional banks a e no ye ully p epa ed o he challenges gene a ed by new in o ma ion echnologies in he con ex in which decisions will inc easingly be made by in elligen machines in a eas such as c edi isk analysis, da a managemen and insu ance. Since he 2000s, he inancial-banking sys em has di e si ied s ongly and clea unc ionali ies ha e been in oduced unde he FinTech end (Wonglimpiya a , 2017; Kim e al., 2016): in e ne ca d, online banking, digi al paymen s sys ems, digi al money (such as PayPal, Google Walle , Apple Pay, AliPay, LINE Pay, WePay, M-PESA Mobile money), pee - o-pee paymen s ia mobile banking. Many o hese new ea u es ha e been p omo ed especially by non-banking companies, in an a emp o di e en ia e hemsel es om he adi ional banks. The FinTech end causes ce ain sys emic cha ac e is ics o change o e ime and unde he in luence o ma ke size; as he ma ke g ows h ough collabo a ion be ween FinTech pa ne s, he cha ac e is ics o he inno a ion p ocess change subs an ially. Acco ding o Lee and Jae Shin (2018), FinTechs a e going h ough a a o able e a in e ms o legal egula ions as many go e nmen s a e ying o suppo hei de elopmen so ha he na ional inancial indus ies do no lag behind he global ones. I is expec ed, howe e , ha i FinTechs a ec adi ional inancial ma ke s, go e nmen s will impose mo e s ingen ules. Jag iani and John (2018) show ha au ho i ies a ound he wo ld a e ocusing on consume in e es and s i ing o p o ec hem, ying o s ike a balance be ween inancial s abili y and he need o suppo c ea ion o an en i onmen conduci e o FinTech inno a ions. F om he pe spec i e o he secu i y and con iden iali y o ansac ions, many consume s a e conce ned abou he legal egula ions subjec o he ac i i ies o he FinTechs. Resea ch conduc ed by Buchak e al. (2018) shows ha FinTechs all in o he shadow-banking ca ego y due o he ac ha hey ake o e he asks ela ed o lending ac i i ies; o mo gage lending, he quan i a i e model highligh ed ha egula ion ep esen s abou 60% o shadow-banks g ow h, and he echnological componen con ibu es abou 30%. Wo ldwide, he s a is ics on in es men s in FinTechs show imp essi e amoun s a he Region Amoun o in es men s ($ billion) Numbe o deals Global 111.8 2,196 Ame icas 54.5 1,245 US 52.5 1,061 Eu ope 34.2 536 Asia 22.7 372 Sou ce: own, da a p ocessed om KPMG (2019) Tab. 1: In es men s in FinTechs (2018) EM_2_2021.indd 103 31.5.2021 10:33:29 104 2021, XXIV, 2 Finance le el o 2018, acco ding o o icial epo s (KPMG, 2019), acco ding o he da a in Tab. 1. F om he da a in Tab. 1 we can see ha he amoun in es ed globally is conside able (mo e han $111 billion), and he Uni ed S a es has a sha e o abou 50% in his in es men sec o . Also, i can be no ed ha globally he e a e app oxima ely 2,200 FinTech deals, which leads us o hink abou a e y wide di e si y o inno a i e inancial ini ia i es. The same epo (KPMG, 2019) shows ha in he las 6 yea s, each egion has had an upwa d end in e ms o he alues o he in es men s made. Acco ding o E ns & Young (2019), one o he main dis up i e aspec s o FinTechs is he i s con ac wi h he cus ome ; he ease wi h which new cus ome s can open a inancial accoun encou ages mo e and mo e use s o adop his ype o echnology. A he p esen ime i has come o he si ua ion whe e he ac i i y o opening a new ope a ional accoun has a du a ion o he o de o minu es, and he alida ion o he use s is done h ough a i icial in elligence echnologies, which leads o an inc ease in p oduc i i y and a signi ican educ ion o he cos s o en olling new clien s. Rega ding how FinTech echnologies a e implemen ed, a s udy has been ca ied ou by Du (2018), which has esul ed in he ac ha in he con ex o he p oli e a ion o mobile paymen s, hese echnologies a e o in e es no only o he big banks, bu also o he c edi unions. Thus, c edi ins i u ions ha ha e highe -le el IT capabili ies bu a e acing lowe pe o mance and s ong ins i u ional p essu es a e mo e likely o adop mobile paymen s se ices. Among he ad an ages o e ed in he case o mobile paymen s, Kang (2018) shows ha , unlike he exis ing bank paymen se ices, he paymen se ice o e ed by FinTech allows cus ome s using a adi ional bank o use an independen and pe sonalized paymen se ice which does no depend on he bank sys em. An ob ious inno a ion o FinTechs is being discussed by Magnuson (2018), who shows ha hese companies ha e aken o ano he le el how o dis ibu e capi al on he ma ke , h ough c owd unding pla o ms. Acco ding o Cumming and Ho nu (2018), he concep o c owd unding e e s o he phenomenon whe e companies in ea ly s ages o de elopmen (usually s a ups) seek o ob ain inancing om la ge g oups o people h ough In e ne - based echnologies (mos o en h ough social ne wo ks o i al ma ke ing campaigns). Abu Amuna e al. (2019) show ha he ole o FinTechs and c owd unding pla o ms is an impo an one in suppo ing and accele a ing he de elopmen o new businesses. Bes e al. (2013) es ima e ha he c owd unding indus y will each $96 billion by 2025. Gimpel e al. (2018) show ha in e na ional money ans e s a e a success ul componen o FinTech s a ups, because hey allow much cheape mul i-cu ency ans e s (see Die z e al., 2016) han h ough SWIFT o SEPA banking sys ems. Also, hese in e na ional ans e s made h ough FinTechs a e much as e . Issues ela ed o ading cos s a e also add essed by Coe zee (2018), who shows ha cus ome s a e e y sensi i e o his aspec , being willing o easily mig a e om a mo e expensi e adi ional inancial se ices p o ide o an al e na i e FinTech p o ide who o e s se ices a lowe cos s. Cos educ ion is a di ec esul o he ac ha FinTechs do no ope a e h ough subsidia ies and physical o ices as adi ional banks do. On he o he hand, Ozili (2018) conduc ed a scien i ic esea ch which showed ha in he case o de eloped o de eloping economies, people wi h a iable o low incomes a e willing o pay a highe cos o he se ices o e ed by FinTech p o ide s; his op ion is due o he con enience and ease o use in e ms o FinTech se ices. Gombe e al. (2018) show ha a ea u e ha is eally in e es ing o many FinTech use s is pee - o-pee (P2P) lending, which con en ional banks a e no willing o o e . This ype o loan e e s o he possibili y o making di ec loans be ween he lende and he deb o , he FinTech sys em being an in e media y dealing wi h issues such as: iden i ying he bo owe s, iden i ying he c edi o s, nego ia ing he di ec loan ag eemen , highligh ing he paymen s o debi and in e es , he insu ance loan con ac , eco e y o ou s anding amoun s. Lee and Jae Shin (2018) and Williams-G u (2016) no e ha an impo an aspec o his business model is he ac ha FinTechs a e no di ec ly in ol ed in lending (as wi h adi ional banks), bu only in “connec ing” he c edi o wi h he deb o . FinTechs now end o in eg a e in one way o ano he wi h es ablished mic o inance pla o ms, pla o ms ha ha e been analyzed by Bollinge and Yao (2018). Acco ding o Jag iani and Lemieux (2018), op ions ega ding P2P loans we e pa icula ly success ul in a eas EM_2_2021.indd 104 31.5.2021 10:33:30 105 2, XXIV, 2021 Finance ha we e weake se ed by adi ional banks, which means ha a new ca ego y o clien s has been included in he inancial se ices sphe e. In his way, FinTechs mani es hemsel es as a ac o o inancial inclusion o a ious ca ego ies o popula ion, which usually would no ha e access o speci ic banking se ices. In andem wi h he P2P lending op ion, Die z e al. (2016) show ha some FinTechs also o e he possibili y o make sa ings simila o bank deposi s. Along he same lines, he p o ision o online b oke age se ices by FinTechs o hei clien s is also close , hus b inging he s ock exchange o small in es o s close . FinTechs ha e gained an inc easingly signi ican ma ke sha e e en among adi ional clien s o adi ional banks. As o Bi coin c yp ocoins, i seems ha he le el o accep ance by end use s is s ill qui e low and somewha below he le el o media impac i has had o e he las 3 yea s. Acco ding o Wonglimpiya a (2017), among he ac o s ha inhibi he widesp ead adop ion o his elec onic cu ency a e he ac ha i is nei he ecognized no suppo ed by any go e nmen al au ho i y, and legal egula ions lack o p ohibi he use o his means o paymen . Gi en he esea ch elemen s so a in he li e a u e, a summa y o FinTechs’ ea u es is p esen ed in Tab. 2. FinTech ea u e Desc ip ion Au ho s Digi al money PayPal, Google Walle , Apple Pay, AliPay, LINE Pay, WePay, M-PESA Mobile money Wonglimpiya a , 2017; Lee & Jae Shin, 2018; Du, 2018; Kang, 2018 Online-b oke age Managemen o s ock-exchange asse s Gombe e al., 2018; Kashyap e al., 2016 Financial obo s Au oma ic messages and answe s, in elligen inancial decisions, aud de ec ion Zhang & Kedmey, 2018; Gombe e al., 2018 Pee - o-pee paymen s ia mobile banking Ins an money ans e s Wonglimpiya a , 2017; Kim e al., 2016 Pee - o-pee (P2P) lending Cus omized lends Gombe e al., 2018; Magnuson, 2018 C yp o-cu encies Bi coin and assimila ed c yp o-coins Wonglimpiya a , 2017; I win & Tu ne , 2018; Teckla, 2019 Online in e na ional money ans e T ans e s wi hin FinTech use s o be ween FinTech use s and banks Gimpel e al., 2018; Kashyap e al., 2016 Sa ings Deposi s Gulamhuseinwala e al., 2015; Die z e al., 2016 Ease o se ing up an accoun Accoun opening E ns & Young, 2019 Insu ance T a el insu ance, ca ds insu ance, los -documen s insu ance, loan insu ance Dany e al., 2016; Gombe e al., 2018 Reduced cos s Signi ican educed cos pe ansac ion Die z e al., 2016; Coe zee, 2018; E ns & Young, 2019 Exchange Mul i-cu ency exchanges Oma o a, 2019; Haddad & Ho nu , 2019 Secu i y & p i acy Sa e ansac ions, his o y o ansac ions Gai e al., 2018; Lee & Jae Shin, 2018 C owd unding Dona ions, ewa ds Fellände e al., 2018; Magnuson, 2018; Bes e al., 2013 Sou ce: own Tab. 2: FinTech ea u e EM_2_2021.indd 105 31.5.2021 10:33:30 106 2021, XXIV, 2 Finance Among he challenges ha FinTechs ace, Lee and Jae Shin (2018) iden i y he ollowing main issues: in es men managemen , cus ome managemen , egula ion, echnology in eg a ion, secu i y and p i acy, and isk managemen . Zalan and Tou aily (2017) show ha ano he challenge is due o he ac ha adi ional banks and FinTechs ha e been o ced o wo k oge he , which will lead o a diminishing dis up i e e ec ha he FinTech inno a ions ha e on hem a his momen . As a esul , a majo challenge will be o FinTechs o be able o main ain he accele a ed pace o inno a ion in he con ex o collabo a ion wi h Hypo hesis numbe Hypo hesis desc ip ion P e ious esea ch H1a Com o and ease o use ha e a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Dospinescu e al., 2019; Da is, 1989; E ns & Young, 2019 H1b The exis ence o legal egula ions on FinTechs ha e a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Lee & Jae Shin, 2018; Jag iani & John, 2018; Van Loo, 2018; Buchak e al., 2018 H1c The ease wi h which a new inancial accoun is opened has a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. E ns & Young, 2019 H1d The exis ence o mobile paymen s op ions has a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Du, 2018; Kang, 2018; Wonglimpiya a , 2017 H1e The exis ence o c owd unding op ions ha e a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Fellände e al., 2018; Magnuson, 2018; Bes e al., 2013 H1 The in e na ional money ans e s op ion has a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Die z e al., 2016; Gimpel e al., 2018; Kashyap e al., 2016 H1g The educed ope a ion cos s ha e a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Ozili, 2018; E ns & Young, 2019; Coe zee, 2018 H1h The exis ence o pee - o-pee , (P2P) lending op ions has a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Gombe e al., 2018; Magnuson, 2018 H1i The insu ances included in he sys em ha e a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Dany e al., 2016; Gombe e al., 2018 H1j The online-b oke age op ions ha e a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Gombe e al., 2018; Kashyap e al., 2016 H1k The exis ence o c yp ocoins op ion has a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Wonglimpiya a , 2017; I win & Tu ne , 2018; Teckla, 2019 H1l The exchange op ion has a posi i e impac on he ul illmen o he bene i s expec ed by he cus ome s om he use o FinTech se ices. Oma o a, 2019; Haddad & Ho nu , 2019 Sou ce: own Tab. 3: Resea ch hypo heses – indica o s EM_2_2021.indd 106 31.5.2021 10:33:30 107 2, XXIV, 2021 Finance banks. Ozili (2018) conside s ha a u u e di ec ion in esea ching he challenges ela ed o FinTechs is he s udy o he ela ionship be ween economic c ises and digi al inance, in he ligh o how digi al inance can con ibu e o imp o e he inancial con agion in he e en o a c isis. 2. Da a and Me hodology 2.1 Aim and Hypo heses The pu pose o his scien i ic esea ch is o de ine he in luence and con ibu ion o he ollowing 12 indica o s: 1) com o and ease o use, 2) he exis ence o legal egula ions on FinTechs, 3) he ease wi h which a new inancial accoun is opened, 4) mobile paymen s, 5) exis ence o c owd unding op ions, 6) in e na ional money ans e s, 7) ope a ing cos s, 8) pee - o-pee (P2P) lending, 9) insu ances included in he sys em, 10) online-b oke age, 11) c yp ocoins, 12) exchange. The ini ial hypo hesis is ha he a o emen ioned ac o s ha e a signi ican in luence on he decision o adop FinTech se ices by cus ome s in Romania. In addi ion, in his esea ch we will es he dependence o hese indica o s on he socio-demog aphic a iables, such as: educa ion le el, age, mon hly income le el, gende , use o igin ( u al s. u ban). As we p esen ed in he li e a u e e iew chap e , mos p e ious s udies ha e analyzed hese ac o s indi idually o in small g oups o indi idual ac o s. The majo con ibu ion o ou esea ch lies in he ac ha we a e ying o p o ide a b oade pic u e o he numbe o ac o s ha in luence he decision o adop FinTech se ices and echnologies. Each o he 12 selec ed indica o s will be e alua ed by a sepa a e hypo hesis, acco ding o Tab. 3. In addi ion o he abo e, he cha ac e is ics ela ed o he le el o inancial educa ion, he deg ee o banking de elopmen , he pu chasing powe as well as he demog aphic cha ac e is ics, may cause di e en decisions om he cus ome s depending on he segmen s o which hey a e pa . Taking in o accoun he di e ences be ween he obse ed cha ac e is ics, he esea ch will ocus on iden i ying he di e ences be ween consume s ha a e di e en in e ms o socio-demog aphic a iables: educa ion le el, age, mon hly income le el, gende , cus ome ’s o igin ( u al s. u ban). As a esul , we p opose he ollowing se o esea ch hypo heses, acco ding o Tab. 4. 2.2 Measu emen Va iables and Ins umen The esea ch is based on a se o a iables ha allow he con i ma ion o ejec ion o he esea ch hypo heses. The independen a iables a e he ollowing indica o s: com o and ease o use, he exis ence o legal egula ions on FinTechs, he ease wi h which a new inancial accoun is opened, mobile paymen s, exis ence o c owd unding op ions, in e na ional money ans e s, ope a ing cos s, pee - o-pee (P2P) lending, insu ances included in he sys em, online-b oke age, c yp ocoins, exchange. The g ouping a iables a e: educa ion le el, age, Hypo hesis numbe Hypo hesis desc ip ion H2a Bene i s expec ed by cus ome s h ough he use o FinTech se ices di e acco ding o age. H2b Bene i s expec ed by cus ome s h ough he use o FinTech se ices di e acco ding o educa ion le el. H2c Bene i s expec ed by cus ome s h ough he use o FinTech se ices di e acco ding o income le el. H2d Bene i s expec ed by cus ome s h ough he use o FinTech se ices di e acco ding o gende . H2e Bene i s expec ed by cus ome s h ough he use o FinTech se ices di e acco ding o cus ome ’s o igin ( u al s. u ban). Sou ce: own Tab. 4: Resea ch hypo heses – demog aphic ac o s EM_2_2021.indd 107 31.5.2021 10:33:30 108 2021, XXIV, 2 Finance mon hly income le el, gende , cus ome ’s o igin ( u al s. u ban). The decision o adop FinTech se ices was analyzed h ough a ques ionnai e con aining 17 ques ions: 5 ques ions e e o he demog aphic cha ac e is ics o he g oup and 12 ques ions e e o he independen a iables. Responden s we e asked o assess o wha ex en each indica o is impo an in he expec ed bene i s o using FinTech se ices and echnologies; he ques ions we e cons uc ed on he Like scale, whe e he alue 1 means ha he measu ed a iable has no impo ance in he decision o adop FinTechs, while he alue 5 means ha he a iable has an inc eased impo ance in his decision. The ques ions allowed esponden s o choose a alue om 1 o 5 o each esponse associa ed wi h he a iable: 1) How impo an a e he com o and ease o use in he decision o adop FinTech? 2) How impo an is he exis ence o legal egula ions on FinTechs o you in he decision o adop FinTech? 3) How impo an is he ease wi h which a new inancial accoun is opened in he decision o adop FinTech? 4) How impo an is he mobile paymen s op ion in he decision o adop FinTech? 5) How impo an is he op ion ega ding in e na ional money ans e s in he decision o adop FinTech se ices? To e i y he eliabili y o he ques ionnai e, we applied he C onbach’s Alpha es . The es e i ies he in e nal consis ency om he poin o iew o he indi idual sco es and he agg ega e sco e. The alues o C onbach’s Alpha es is 0.610 and acco ding o Ta akol and Dennick (2011), his alue con i ms ha ou i ems a e accep able. 2.3 Resea ch Popula ion, Sampling Me hod and Sample The esea ch popula ion is ep esen ed by use s o FinTech echnologies and se ices, who a e membe s o Millennials and Gene a ion Z. The sampling me hod used was he Pu posi e Sampling. The esea che s conside ed he speci ic cha ac e is ics, quali ies, knowledge and expe ience o he esponden s he ele an c i e ia o he esea ch (E ikan e al., 2016). This esea ch was based on he esponses o 162 esponden s. The numbe o esponden s is highe han he minimum numbe (139) sugges ed by Raoso (2019) o a con idence le el o 95%. The dis ibu ion o esponden s shows a no mal dis ibu ion, e lec ing he p ope ies o he en i e popula ion in he analyzed segmen . In e ms o gende , he sample consis s o 45.7% male esponden s and 54.3% emale esponden s. F om he poin o iew o he income le el, 8.6% o he esponden s ha e below a e age incomes, 69.2% ha e a e age incomes and 22.2% ha e abo e a e age incomes. F om he poin o iew o he o igin ( u al s. u ban), 77.8% o he esponden s come om he u ban en i onmen and 22.2% om he u al a ea. Mos esponden s ha e a uni e si y deg ee (63.6%), and 31.5% o hem ha e comple ed hei mas e s s udies, while 1.2% ha e high school and 3.7% doc o al s udies. In e ms o age, 48.8% a e om he Gene a ion Z ca ego y, while 51.2% a e om he Millennials ca ego y. 2.4 P ocedu e and S a is ical Analysis o Da a The ques ionnai e was applied in July, Augus and Sep embe 2019 in Romania. The da a collec ed om he esponden s we e p ocessed wi h IBM SPSS S a is ics e sion 21. The answe s ob ained om he esponden s we e analyzed by he desc ip i e s a is ics me hod, being p esen ed a e age alues as well as de ia ion o each a iable. The accu acy o he se o hypo heses is analyzed using a ious s a is ical es s: Pea son co ela ion, mul i a ia e analysis o a iance and mul iple eg ession analysis and modeling. 3. Resul s The alues o he desc ip i e s a is ics o he dependen a iable ( he sa is ac ion le el ega ding he use o FinTech se ices) and he speci ic indica o s a e p esen ed in Tab. 5. As i can be seen, he esponden s conside ha he le el o sa is ac ion wi h he use o FinTech se ices depends la gely on educed cos s (M = 4.59), mobile paymen s (M = 4.53), a ached insu ances (M = 4.43), ease o opening a new inancial accoun (M = 4.15) and in e na ional money ans e op ions (M = 4.23). In he same con ex , low sa is ac ion is associa ed wi h c owd unding op ions (M = 1.53), c yp ocoins op ions (M = 1.56), online b oke age (M = 1.81), and pee - o-pee lending op ions (M = 2.40). These alues ob ained om ou esea ch con i m some p e ious pa ial esea ch on educed cos s (Coe zee, 2018; Die z e al., 2016), a ached insu ances (Dany e al., 2016; Gombe e al., 2018) and in e na ional money EM_2_2021.indd 108 31.5.2021 10:33:30 109 2, XXIV, 2021 Finance ans e op ions (Gimpel e al., 2018; Kashyap e al., 2016). To es hypo heses H1a – H 1l, mul iple linea eg ession analysis was used o y o p edic he dependen a iable (sa is ac ion le el in using FinTech se ices) based on a se o independen a iables: com o and ease o use, legal egula ions, ease o Indica o s Minimum Maximum Mean S d. de ia ion Com o AndEaseO Use 1.00 5.00 3.7963 1.0224 LegalRegula ions 1.75 5.00 3.8426 0.7032 EaseAccoun Open 1.75 5.00 4.1543 0.6219 MobilePaymen s 2.00 5.00 4.5309 0.6419 C owd unding 1.00 5.00 1.5340 0.8522 In e na ionalMoneyT ans e s 1.00 5.00 4.2346 0.7765 ReducedCos s 2.75 5.00 4.5941 0.6716 P2PLending 1.00 5.00 2.4074 1.2538 Insu ances 2.00 5.00 4.4321 0.5963 OnlineB oke age 1.00 5.00 1.8148 1.0469 C yp ocoinsOp ion 1.00 5.00 1.5617 0.9119 ExchangeOp ion 1.00 5.00 4.1790 0.8626 Sa is ac ionLe elFinTech 3.00 5.00 4.2654 0.6185 Sou ce: own Tab. 5: Values o desc ip i e s a is ics o dependen a iable and indica o s Model S anda dized coe icien s TSig. Be a Com o AndEaseO Use −0.107* −2.024 0.045 LegalRegula ions 0.141* 2.163 0.032 EaseAccoun Open −0.013 −0.241 0.810 MobilePaymen s 0.136* 2.117 0.036 C owd unding 0.055 1.077 0.283 In e na ionalMoneyT ans e s 0.128* 2.370 0.019 ReducedCos s 0.460** 8.003 0.000 P2PLending 0.052 0.973 0.332 Insu ances 0.177** 3.179 0.002 OnlineB oke age 0.080 1.514 0.132 C yp ocoinsOp ion 0.009 0.171 0.865 ExchangeOp ion 0.106* 2.059 0.041 Sou ce: own No e: * signi ican a he le el 5%; ** signi ican a he le el 1%. Tab. 6: Con ibu ion o independen a iables o dependen a iable desc ip ion EM_2_2021.indd 109 31.5.2021 10:33:30 116 2021, XXIV, 2 Finance Pos -C isis Pa adigm? SSRN Elec onic Jou nal, 47(4), 1271–1319. h ps://doi. o g/10.2139/ss n.2676553 Ash a, A., & Bio -Paque o , G. (2018). FinTech e olu ion: S a egic alue managemen issues in a as changing indus y. S agegic Change. B ie ings in En ep eneu ial Finance, 27(4), 301–311. h ps://doi.o g/10.1002/jsc.2203 Assa zadeh, A. H., & Abe oumand, S. (2018). FinTech in Wes e n Asia: Case o I an. Jou nal o Indus ial In eg a ion and Managemen , 3(3). h ps://doi.o g/10.1142/S2424862218500069 Bes , J., Neiss, S., Swa , R., Lambkin, A., & Raymond, S. (2013). C owd unding’s po en ial o he de eloping wo ld (Wo king Pape No. 84000). Washing on, DC: Wo ld Bank G oup. Re ie ed om h p://documen s. wo ldbank.o g/cu a ed/en/409841468327411701/ C owd undings-po en ial- o - he-de eloping-wo ld Bollinge , B., & Yao, S. (2018). Risk ans e e sus cos educ ion on wo-sided mic o inance pla o ms. Quan i a i e Ma ke ing and Economics, 16(3), 251–287. h ps://doi. o g/10.1007/s11129-018-9198-0 Buchak, G., Ma os, G., Pisko ski, T., & Se u, A. (2018). Fin ech, egula o y a bi age, and he ise o shadow banks. Jou nal o Financial Economics, 130(3), 453–483. h ps://doi.o g/10.1016/j.j ineco.2018.03.011 Buco e chi, O., Slusa iuc, G., & Činčalo á, S. (2019). Gene a ion Z – Key ac o o o ganiza ional inno a ion. Quali y – Access o Success, 20(3), 25–30. Coe zee, J. (2018). S a egic implica ions o Fin ech on Sou h A ican e ail banks. Sou h A ican Jou nal o Economic and Managemen Sciences, 21(1), 1–11. h p://dx.doi.o g/10.4102/sajems. 21i1.2455 Cumming, D., & Ho nu , L. (2018). The Economics o C owd unding. S a ups, Po als and In es o Beha io . London: Palg a e Macmillan. h ps://doi.o g/10.1007/978-3-319-66119-3 Dany, O., Goyal, R., Schwa z, J., Van den Be g, P., Sco ecci, A., & o Baben, S. (2016). Fin echs may be co po a e banks’ bes “F enemies”. Bos on, MA: Bos on Consul ing G oup. Re ie ed July 24, 2019, om h ps:// www.bcg.com/publica ions/2016/ inancial- ins i u ions- echnology-digi al-FinTechs-may- be-co po a e-banks-bes - enemies.aspx Da is, F. (1989). Pe cei ed use ulness, pe cei ed ease o use, and use accep ance o in o ma ion echnology. MIS Qua e ly, 13(3), 319–340. h ps://doi.o g/10.2307/249008 Die z, M., Olan ewaju, T., Khanna, S., & Rajgopal, K. (2016). Cu ing h ough he noise a ound inancial echnology. New Yo k, NY: McKinsey & Company. Re ie ed om h ps://www.mckinsey.com/indus ies/ inancial- se ices/ou -insigh s/cu ing- h ough- he-noise- a ound- inancial- echnology Dospinescu, O., Anas asiei, B., & Dospinescu, N. (2019). Key Fac o s De e mining he Expec ed Bene i o Cus ome s When Using Bank Ca ds: An Analysis on Millennials and Gene a ion Z in Romania. Symme y, 11(12), 1449. h ps://doi.o g/10.3390/sym11121449 Du, K. (2018). Complacency, capabili ies, and ins i u ional p essu e: unde s anding inancial ins i u ions’ pa icipa ion in he nascen mobile paymen s ecosys em. Elec onic Ma ke s, 28(3), 307–319. h ps://doi. o g/10.1007/s12525-017-0267-0 E ns & Young. (2019). Global FinTech Adop ion Index 2019. London: E ns & Young. Re ie ed om h ps://asse s.ey.com/ con en /dam/ey-si es/ey-com/en_gl/ opics/ banking-and-capi al-ma ke s/ey-global- in ech- adop ion-index.pd E ikan, I., Musa, S. A., & Alkassim, R. S. (2016). Compa ison o Con enience Sampling and Pu posi e Sampling. Ame ican Jou nal o Theo e ical and Applied S a is ics, 5(1), 1–4. h ps://doi.o g/10.11648/j.aj as.20160501.11 Fellände , A., Si i, S., & Teigland, R. (2018). The h ee phases o FinTech. In R. Teigland, S. Si i, A. La sson, A. Mo eno Pue as, & C. Ing am Bogusz (Eds.), The Rise and De elopmen o FinTech. Accoun s o Dis up ion om Sweden and Beyond (pp. 154–167). London: Rou ledge. Gai, K., Qiu, M., & Sun, X. (2018). A su ey on FinTech. Jou nal o Ne wo k and Compu e Applica ions, 103, 262–273. h ps://doi. o g/10.1016/j.jnca.2017.10.011 Gimpel, H., Rau, D., & Röglinge , M. (2018). Unde s anding FinTech s a -ups – a axonomy o consume -o ien ed se ice o e ings. Elec onic Ma ke s, 28(3), 245–264. h ps://doi. o g/10.1007/s12525-017-0275-0 Gombe , P., Kau man, R. J., Pa ke , C., & Webe , B. W. (2018). On he Fin ech e olu ion: In e p e ing he o ces o inno a ion, dis up ion and ans o ma ion in inancial se ices. Jou nal o Managemen In o ma ion Sys ems, 35(1), 220–265. h ps://doi.o g/10.1080/07421222.20 18.1440766 Gulamhuseinwala, I., Bull, T., & Lewis, S. (2015). FinTech is gaining ac ion and young, EM_2_2021.indd 116 31.5.2021 10:33:32 117 2, XXIV, 2021 Finance high-income use s a e he ea ly adop e s. The Jou nal o Financial Pe spec i es, 3(3), 1–17. Haddad, C., & Ho nu , L. (2019). The eme gence o he global FinTech ma ke : economic and echnological de e minan s. Small Business Economics, 53(1), 81–105. h ps://doi.o g/10.1007/s11187-018-9991-x Hai , J. F., Black, W. C., Babin, B. J., & Ande son, R. E. (2013). Mul i a ia e Da a Analysis. London: Pea son. Hu, Z., Ding, S., Li, S., Chen, L., & Yang, S. (2019). Adop ion In en ion o Fin ech Se ices o Bank Use s: An Empi ical Examina ion wi h an Ex ended Technology Accep ance Model. Symme y, 11(3), 340. h ps://doi.o g/10.3390/ sym11030340 I win, A. S. M., & Tu ne , A. B. (2018). Illici Bi coin ansac ions: challenges in ge ing o he who, wha , when and whe e. Jou nal o Money Launde ing Con ol, 21(3), 297–313. h ps://doi. o g/10.1108/JMLC-07-2017-0031 Jag iani, J., & John, K. (2018). Fin ech: The Impac on Consume s and Regula o y Responses. Jou nal o Economics and Business, 100, 1–6. h ps://doi.o g/10.1016/j. jeconbus.2018.11.002 Jag iani, J., & Lemieux, C. (2018). Do in ech lende s pene a e a eas ha a e unde se ed by adi ional banks? Jou nal o Economics and Business, 100, 43–54. h ps://doi.o g/10.1016/j. jeconbus.2018.03.001 Kang, J. (2018). Mobile paymen in Fin ech en i onmen : ends, secu i y challenges, and se ices. Human-cen ic Compu ing and In o ma ion Sciences, 8(1), 32. h ps://doi. o g/10.1186/s13673-018-0155-4 Kashyap, M., Ga inkel, H., Shipman, J., Da ies, S., & Nicolacakis, D. (2016). Blu ed lines: How FinTech is shaping Financial Se ices. London: P iceWa e houseCoope s. Re ie ed Ma ch 22, 2019, om h ps://www. pwc.de/de/ inanzdiens leis ungen/asse s/pwc- in ech-global- epo .pd Kim, Y., Choi, J., Pa k, Y., & Yeon, J. (2016). The adop ion o mobile paymen se ices o “FinTech”. In e na ional Jou nal o Applied Enginee ing Resea ch, 11(2), 1058–1061. KPMG. (2019). The Pulse o Fin ech 2018. Biannual global analysis o in es men in Fin ech. Ams el een: KPMG. Re ie ed June 22, 2019, om h ps://asse s.kpmg/con en /dam/kpmg/xx/ pd /2019/02/ he-pulse-o - in ech-2018.pd Lee, I., & Jae Shin, Y. (2018). Fin ech: Ecosys em, business models, in es men decisions, and challenges. Business Ho izons, 61(1), 35–46. h ps://doi.o g/10.1016/j. busho .2017.09.003 Magnuson, W. (2018). Regula ing Fin ech (71 Vande bil Law Re iew 1167). Fo Wo h, TX: Texas A&M Uni e si y School o Law. Re ie ed Oc obe 18, 2019, om h ps:// schola ship.law. amu.edu/cgi/ iewcon en . cgi?a icle=2243&con ex = acschola Oma o a, S. T. (2019). New Tech . New Deal: Fin ech as a Sys emic Phenomenon. Yale Jou nal o Regula ion, 36(2), 735–793. h p://dx.doi.o g/10.2139/ss n.3224393 Ozili, P. K. (2018). Impac o digi al inance on inancial inclusion and s abili y. Bo sa Is anbul Re iew, 18(4), 329–340. h ps://doi. o g/10.1016/j.bi .2017.12.003 Raoso . (2019). Sample Size Calcula o by Raoso . Re ie ed No embe 12, 2019, om h p://www. aoso .com/samplesize.h ml Ryu, H.-S. (2018). Wha makes use s willing o hesi an o use Fin ech?: he mode a ing e ec o use ype. Indus ial Managemen & Da a Sys ems, 118(3), 541–569. h ps://doi. o g/10.1108/IMDS-07-2017-0325 Schul e, P., & Liu, G. (2018). FinTech Is Me ging wi h IoT and AI o Challenge Banks: How En enched In e es s Can P epa e. The Jou nal o Al e na i e In es men s, 20(3), 41–57. h ps://doi.o g/10.3905/jai.2018.20.3.041 Ta akol, M., & Dennick, R. (2011). Making Sense o C onbach’s Alpha. In e na ional Jou nal o Medical Educa ion, 2, 53–55. h ps://doi.o g/10.5116/ijme.4d b.8d d Teckla. (2019). Re olu C yp ocu ency – Re iew 2019. Finso . Re ie ed om h ps:// inso .ne / e olu -c yp ocu ency- e iew-2019 Van Loo, R. (2018). Making Inno a ion Mo e Compe i i e: The Case o Fin ech (65 UCLA Law Re iew, pp. 232–279). Bos on, MA: Bos on Uni e si y, School o Law. Re ie ed om h ps:// schola ship.law.bu.edu/ acul y_schola ship/50/ Williams-G u , O. (2016). Deloi e jus ashed he hype a ound a $180 billion in ech ma ke . Business Inside . Re ie ed om h ps://www.businessinside .com/deloi e- epo -ma ke place-lending-no -signi ican - playe s-pee - o-pee -2016-5 Wonglimpiya a , J. (2017). FinTech banking indus y: a sys emic app oach. Fo esigh , 19(6), 590–603. h ps://doi.o g/10.1108/FS-07-2017- 0026 Zalan, T., & Tou aily, E. (2017). The P omise o Fin ech in Eme ging Ma ke s: No EM_2_2021.indd 117 31.5.2021 10:33:32 118 2021, XXIV, 2 Finance as Dis up i e. Con empo a y Economics, 11(4), 415–430. h ps://doi.o g/10.5709/ce.1897- 9254.253 Zhang, X.-P., & Kedmey, D. (2018). A Budding Romance: Finance and AI. IEEE Mul imedia, 79–83. Re ie ed om h ps://www. ee. ye son.ca/~xzhang/publica ions/mmmag2018- 25n4-Zhang-Kedmey-A%20Budding%20 Romance%20Finance%20and%20AI.pd Zigu a . (2019). E olu ion o Fin ech. Ba celona: Zigu a Inno a ion & Technology Business School. Re ie ed Oc obe 5, 2019, om h ps://www.e-zigu a .com/inno a ion- school/blog/e olu ion-o - in ech/ EM_2_2021.indd 118 31.5.2021 10:33:32