BIG DATA AND COMPETITIVE ADVANTAGE: SOME DIRECTIONS AND USES

Eduardo Luis Casarotto; Erlaine Binotto; Guilherme Cunha Malafaia; Marta Pagán Martínez

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<line> Centro Unv*rsitário Santo Agostinho </line>

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<line> www*.fsanet.com.*r/revista </line>

<line> I*SN Impresso: 180*-6356 ISSN *letrô*ico: 2317-2983 </line>

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<line> Big *ata and Competitive Advantage: S*m* Directio*s a*d Uses </line>

<line> **g Data e Vantag** Competitiv*: Algumas Dir*ções * U*os </line>

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<line> Eduard* Luis Casarot** </line>

<line> Dout*r em Admin*str*ção pe*a *nivers*dade Federal de Mato *ro*so do Sul </line>

<line> Profes*** na Faculd*de de Administr*ção, Ciênc*a Contábeis * Economia FACE/UF*D. </line>

<line> E-*ail: eduardocas*rotto@ufg*.ed*.br </line>

<line> Erlai** Binott* </line>

<line> Do*tora em Agro*e**cios pel* Universidade Fe*e*al do Rio G*ande do Sul </line>

<line> P*ofessora na Facul*ade *e Administra*ão, C*ên*ia Co*tábeis e E*on*m*a FACE/UFG*. </line>

<line> E-ma*l: erlainebino*to@ufgd.edu.br </line>

<line> Guilherme Cunha M*lafaia </line>

<line> Doutor e* A*r*n*gó*ios p*la U**versidade Feder*l *o Rio *rande do Su* </line>

<line> Pesquis**o* na Empresa Brasileira d* Pesqu*s* Agropecu**i* - EMB*APA </line>

<line> E-mai*: gcmalafai*@*mail.com </line>

<line> *arta Pa*án Martín*z </line>

<line> Dou*ora em Téc*icas e Mé*odos A*uais em In**rmação e D*cumentação co* Sob*e*aliente "Cum Laude"/ Un*v*rsidad* de </line>

<line> Profe*sora Visitante na Pró-*eitor** de Pós-Graduação da Unive*sidade F*deral de São Carlos </line>

<line> E-mail: *agan.m*r*a@gmail.co* </line>

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<line> Endereço: *dua*d* Lui* Casarotto </line>

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<line> Un*versidade </line>

<line> Federal da </line>

<line> *rande </line>

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<line> Dourados-Itahum, </line>

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<line> Postal *22, D*urados-MS. Brasi*. </line>

<line> Rodrigues </line>

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<line> Ender*ç*: </line>

<line> *rl*ine Binot*o </line>

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<line> Universid*de </line>

<line> F*deral da </line>

<line> Dourado* </line>

<line> Artigo recebido em 11/10/*02*. Úl*ima versão </line>

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<line> Rodovia </line>

<line> Dourados-*tahum, </line>

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<line> Postal 322, Dourados-MS. Bras*l. </line>

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<line> Endereç*: </line>

<line> *uilherme Cunha Malafaia </line>

<line> Aval*a** pe*o sistem* *rip*e R*v**w: a) Desk Re*iew </line>

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<line> E*dereço: </line>

<line> *arta Pagán Martínez </line>

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<line> UFSCar - Pró-Reitor** de Pós-Graduaçã*. Rodovia </line>

<line> Revisão: Gramati*a*, Normati*a e de Form*t*ç*o </line>

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<line> Washington Luis, km 235, 13565-*05, São Ca*l*s-SP. </line>

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<line> Brasil. </line>

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<line> ABSTRACT </line>

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<line> *. L. Casar*t*o, E. Binotto, G. C. Malafaia, M. P. *art*nez </line>

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<line> The co*pe*itive </line>

<line> in gl*bal market *equire* a *on**nuo*s *r**sforma*ion *n **for*ati*n </line>

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<line> *echn*logy *ontents, ma*n** by the i*serti*n of new **o*s and techn*ques that rapidly evolve </line>

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<line> *nd are absorbed by members of the or*anizations. This advanced </line>

<line> o* new technologies in </line>

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<line> organizatio*s scen*rio brought challeng*s address*d to *eed to *o*lect, *tore, process and </line>

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<line> trans**rm t*eir data in*o relevant in*ormation to </line>

<line> create competitive advan**ge. In highly </line>

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<line> dynam*c business environm*nts, th* possibility of ge*erating information pushes c*mpanie* </line>

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<line> to u*e efficiently a huge vo*ume of d*ta, in </line>

<line> both r*sources an* capa*itie* appro*ches. This </line>

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<line> paper aimed </line>

<line> t* analyze the relati*n </line>

<line> b*tween Big Dat* and competitive adv*ntage using *he </line>

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<line> resource-ba*ed view and the *ynamic capabiliti**. Three intern*tional datab*ses were used </line>

<line> and anal*z*d 29 ar*i*les. Results indicate* that both *he resource-based *iew *n* *he dynamic </line>

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<line> capa*iliti*s </line>

<line> approac* </line>

<line> are use* to analyze Big Data as c*mp*t*tiv* advantag* creator. Two </line>

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<line> aspe*ts *ere e*idenced: the *om*ined *pproach*s c*n result in more **nsisten* *nalyses; and </line>

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<line> robu*t th*or**ical framework f*r *ig Data analysis is evide*ced by the </line>

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<line> pr*dominance of *escript*ve article* an* pra*tical *eports. </line>

<line> Keywo*ds: Inn*vation. Technology. *nfor*at*on M*nagement. Co*petiti*enes*. </line>

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<line> compe*i*iv*d*de no *ercado gl*bal exige *ma tran*formação *ontínua nos conteúdos </line>

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<line> tecnolog*a </line>

<line> da info*mação, principalmente **la inserção </line>

<line> *e novas f*rramentas e técnicas que </line>

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<line> evoluem ra*idamente e *ão abs**vi*as pelos membr*s das or***izaçõ*s. Este ce*ário de </line>

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<line> avanço de </line>

<line> n*vas t*c*ologia* n*s o*gan*zaçõ*s *rouxe </line>

<line> desafios enfrentados pel* necessidade </line>

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<line> d* *oletar, armazena*, processar e *ran*forma* *e*s dados em i*formaçõe* relevantes par* </line>

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<line> c*iação de vantagem competi*iva. *m ambie*tes de negóc*os altamen** dinâmi*os, </line>

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<line> poss*bilid*de de geração </line>

<line> de informações im*ulsio** as empresas * utili*a*** </line>

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<line> e*i*iente *m grande vol*me d* da**s, tanto em r*cursos quanto em capacidades. E*te *rt*go </line>

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<line> teve como objetivo </line>

<line> analis*r a relação e*tre Big Data e vantage* c*mp*tit*va utiliza*do </line>

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<line> vis*o **seada em recur*o* as capacidades dinâ*icas. Três bases de da*os *n*ernaci*nai* e </line>

<line> foram ut**iz*d*s e analisa*o* 29 artigos. Os resu*tad** ***icaram *ue tanto a visão basead* </line>

<line> em recursos quanto a abordagem de recu**os dinâmic** s*o usado* para ana*is*r Bi* D**a </line>

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<line> como *r*ador de **ntagem com*etitiva. Dois aspecto* foram evid**ci*d*s: as </line>

<line> *bordagens </line>

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<line> combin*das podem *esul*ar em anális** mais consis*entes; e a fal*a de um refe*enc*al *e*ri*o </line>

<line> robusto para a **á*ise de Big Data * e**dencia*a pel* pre*ominân*ia de **t*gos descri**vos e </line>

<line> r**atórios práticos. </line>

<line> Pa*avras-c*av*: Inovação. *ecnologia. Gest*o da Inform*ção. Competi*i*id*de. </line>

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<line> ww*4.fsanet.com.br/rev*sta </line>

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<line> Bi* Dat* and Compet*tive A*v*nt**e: Som* Directions and Uses </line>

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<line> * INT*ODUCTION </line>

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<line> The c*m*eti*ive l**dscape of </line>

<line> g*obal m**ket e**ironmen*s *eq*i*es </line>

<line> continuous </line>

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<line> tran*formation in inf**m*tion *ec*nol*gy (*T) contents, m*in*y b* the in*ert*** of new to*ls </line>

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<line> and tech*iqu*s that rapidly </line>

<line> evolve and are absorbed by membe*s of t*e organizations. </line>

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<line> Innovation* in telecommunicatio*s, multimedia channel* and new </line>

<line> h*rdware and </line>

<line> softwa*e </line>

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<line> r**ources *l*ow the *enerat*on and ca*tu*e *f *ata f*r the gen*rat*o* of in*ormation and the </line>

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<line> *roduction of k*owle**e (Lau**n*o et **., 2001). Th* t*chnolo*ical developmen* al*ows </line>

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<line> la*ge ge*er*tion and availability of data th*t ca* </line>

<line> *e *bserved and tra*s*ormed int* </line>

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<line> *nformation for d*cision-maki*g. This technolo**cal evo*ut*o* is in*reasin*ly *r*sent in </line>

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<line> social and econ*mic sci**ces, as w**l as i* the daily l*f* of indiv*duals and o*ganizati*ns. </line>

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<line> *rom inacc*ssible s*urce* a*d *nder the *ontrol of a *ew pe*ple in the past, data </line>

<line> nowadays a*e gaining vo*um* and *vai*ability. T*is lar*e vol*me of data called "Big Data" </line>

<line> offers en*l*ss condition* of treatment and *se. Alt**ugh t*ere is no consen*us o* Big Da**'s </line>

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<line> conceptualizat*on, f*om a bus**ess point of *iew this ca* be </line>

<line> defined as </line>

<line> "d*t*sets whose </line>

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<line> s*ruc*u** and size *o beyond the capac*ty of captu*ing, s*or*ng, m*naging and an*lyz**g th*t </line>

<line> common softwa*e holds, *nd wh*ch are *r**sformed into information" (Trevisan & Brito, </line>

<line> 2*15, p. 25). Acc*rding to *hen, M*o, and Liu (2*1*) dat* sets cann*t be per*ei*ed, </line>

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<line> managed and *roce*se* *n a tim*l* manner by *ra*itional software or hardware </line>

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<line> Seeking a **m*etitive a*v*ntag* in increasingly dy*amic markets *s a co*t*nuo** </line>

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<line> c*allenge in busi**ss. *irms </line>

<line> dire** t*ei* o*jective* to </line>

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<line> Neto, & Añez, 2014) and *his may explai* various *evels of busi*ess perfo*mance, as *ell as </line>

<line> t** success or fail*re o* corporati*ns. </line>

<line> Competitive a*vantage occ*rs whe* * firm is more successful than its current or </line>

<line> potential c**peti*ors. *he s*perior performance of a firm *ithin *he competitive environment </line>

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<line> is an em*iri*al *nd c*mmo* indicat*r </line>

<line> of competitive **vant*** (Côrte-R*al, Oliveira, & </line>

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<line> Associa*ing Big Data *ith the generat*on of competiti*e advantag* in th* business </line>

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<line> envi*onment </line>

<line> ha* rel*vance as Big *ata quickl* establishes it*elf in se*era* activities with </line>

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<line> la*ge volu*e o* *in*ncial s*pp*rt (Melo, 2016). </line>

<line> P*evi*us studies on compe**tive advantage asso*ia*ed with Big Data are impo*tant d*e </line>

<line> to the e*ol*tion of IT, whic* is *ommonly applied to the creation *f comp*tit*v* adva**age. In </line>

<line> *d*it*on, Big Data a**lysis is a latent issu* in *cademic and business *p*eres. With a holistic </line>

<line> R**. F*A, *eresina P*, *. 18, n. 01, *rt. 1, p. 3-24, jan. 20*1 w*w4.fsane*.com.br/revi*ta </line>

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<line> E. L. *asarotto, E. Binotto, G. C. Malafaia, M. P. Martínez </line>

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<line> approach f*r d*ta ma*ageme*t, *rocessi*g a*d analysis, Big Dat* enable **lue creation, </line>

<line> per*o*mance *easurement, a*d competit*ve adv*ntage co*struction (Wamba e* al., 2*1*). </line>

<line> Fi*ally, innova*i*g and gai*ing a competitive adv*ntage by using Big Data g*es *ar </line>

<line> b*yo*d data coll*ction and *trat*gy configuration bas*d on *hese data. Only that *ou*d be </line>

<line> insuf*ic*ent for a company to get the *xpect*d advantage (Prescott, 2016). For an or*anization </line>

<line> cre*t*s a *rue competitive *dv*ntage, int*rn*l capabilitie* and r**o**ces must be analyzed to </line>

<line> iden*ify the drivers *f differentiation and innovat*on. </line>

<line> * new envi*onment for business emerges, wit* challe*ges *nd unce**ain*ies to </line>

<line> ov*r*ome, add*es*ing *umerous of *ossibi*i*ie* bot* in academia and i* business. This p*per </line>

<line> aimed to analyze the re*a*ion *etween *ig D*ta an* competi*ive adva*t*ge using the resource- </line>

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<line> based </line>

<line> view *nd *h* dyn*mic capabiliti*s. The expecta*io* i* to *ont*ibu** to *he theore*ica* </line>

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<line> development of the *se of Big Data as a genera**r of compe*itive advanta*e, wi** *pplicat*on* </line>

<line> in business. The fol*owing q*estions we*e in*est*ga*ed: Do th* arti*les jointly addre*s the </line>

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<line> terms Big Data a*d compe*itive *dvantage? The </line>

<line> authors *ist Big Data </line>

<line> as a generator of </line>

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<line> *ompetiti*e advantage? Do the *uthors class*fy B*g Da*a in *he context ** the resource-b*sed </line>

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<line> view, dynamic capabi*ities or bo**? Wha* kind of a*proach did *he *uthors *se to </line>

<line> co*sider </line>

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<line> Big Data as a ge*erator of compe*itive *d**nt*ge? </line>

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<line> 2 *HEOR**ICAL BACKGROUND </line>

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<line> Big Data can be defined as "dataset*, which could not be c*ptured, mana*ed, and </line>

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<line> proc*ssed by gener*l *omputers *ithi* *n </line>

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<line> p.173). *i* D*** *lso d*fined as a new archi*ecture *om*osed of techniques *nd te*h*ologies </line>

<line> that allow the di*co*ery of hi*de* *alu*s in large databases, req*irin* n*w formats for the </line>

<line> larg*-scale *nteg*ation of dat* s*ts **at ar* hig*ly complex and highly diverse (Hashem e* al. </line>

<line> Big Data's fi*lds of *ction are vast, **co*passing new, ra*idly growing se*ments of </line>

<line> data such as media a*d ent**tainment, healthcare, and sur*e*lla*ce. Soc*al networking </line>

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<line> solution* like Face*ook, Foursquare and **itter </line>

<line> are n*w data sources where consumers </line>

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<line> provi*e </line>

<line> almost continuous data f*ows about themselves. Th*s type of </line>

<line> generation an* data </line>

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<line> c*pture, due to t*e *e***rk e*fec*, expands *t high speeds (Gantz & Reinsel, 2011). </line>

<line> From the manager*al *erspective is importa*t t* note that Big Data encompass** much </line>

<line> Re*. ***, T*resin*, v. *8, n. 0*, art. 1, p. 3-24, jan. **21 www4.fs*net.com.*r/revis*a </line>

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<line> B*g Data and Comp*titive Advantage: Some D*recti*ns *nd Uses </line>

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<line> just a lo* o* data, p*ovides managem*nt information to support decision-m*king </line>

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<line> (*onka, *014). Th* pro*ise and valu* of Big Da*a g* beyond what is known, *imited only by </line>

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<line> human capa*ili**es, then orga*iza*ions </line>

<line> *us* p*y *tte*t*on to the impl*cations and f**lures *o </line>

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<line> re**h the full po*ential of *ig Data (Chibba & C*voukia*, 2015). </line>

<line> T*e Big Data features can be su*m**ized as 4V*: volum*, variety, *eloc*t*, and value </line>

<line> (Hashem et al., 2015). Vo*um* **fers to the amount of *ata generated (all ty*e*) from </line>

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<line> dif*erent s*urces *n* *ro* a </line>

<line> contin*ous exp*nsion that ca* resu** *n the cr*ation </line>

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<line> informati*n and obs*rvable pattern* throu*h **ta analysis. </line>

<line> Vari*ty ref*r* to the differen* types o* data coll*cted, including vi*eo, image, text, </line>

<line> audio and nume*ical data records in a struc*ured or unstruc*ured fo*mat. Vel*cit* refers to </line>

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<line> how f*st da*a *ransfer *ccurs as content chan*e* consta*tly d*e t* </line>

<line> the introductio* </line>

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<line> complementary d*ta, arc*ived or t*an*mitted from multiple s*urces. Th* impo*t*nt aspec* of </line>

<line> Big *ata *efers to the process of *i*co*ering hid*en va*ues of *ata sets with various typ*s a*d </line>

<line> rapid gene*a*ion (H*shem et *l., 2*15). </line>

<line> T*e big challenges of *ig Data are relate* to the acquisi*ion, storage, mana*ement, </line>

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<line> and anal*s*s, since traditi*nal systems *f ma*agement, an* anal**is are based on </line>

<line> relationa* </line>

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<line> database m*nagem**t sys*ems (RDBMS). This *ype of system h*s a high cost and is </line>

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<line> applicabl* to structured d*ta. Therefore, a more viable alternative to the **fra**ructure </line>

<line> requirements *or **g Dat* is the Cloud Computing (Chen, Mao & Liu, 2014). </line>

<line> Some possible solutions for *to*i*g an* managing larg*-s*ale disor*ere* datasets are </line>

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<line> distributed file sy*tems (Howard et al., </line>

<line> 1988) and NoSQ* datab*s*s (*attell, 201*) th*t can </line>

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<line> be used to proc*ss tasks in c**sters, su*h *s web pages *or ex**ple. </line>

<line> Other challenge* t* developing the use of Big *ata *re observed by Chaudhuri, D*yal, </line>

<line> a*d Naras*yya (201*), Labrinidis and Jagadish (2012) and Agrawal et al. (2011) and include: </line>

<line> data r*presentation; redu*dancy; d*ta *ifecy*l* *an*gem*nt; analysis mechanisms; </line>

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<line> confiden*iali*y of data; en*rgy *an*g*ment; dispensability </line>

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<line> *ompani*s can str*te*icall* stand out in the market *s**g Big Data resour*es </line>

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<line> c*mbined wit* </line>

<line> a service-oriented manuf*ct*ri*g model. Mastering adva*ced techn*logy </line>

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<line> combi*ed with a service-oriented mode* can e*fecti*ely *ncrease the c**petitiv* adv*ntage of </line>

<line> compa*ies (Zhang et al., 2*17a) </line>

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<line> 2.2 Compet*tive Ad*antage </line>

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<par>

<line> R**. FSA, Teres*na PI, v. 18, n. 01, art. 1, p. 3-2*, jan. 2*21 </line>

<line> *w*4.fsa*et.*om.br/revista </line>

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</page>

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<line> E. L. Ca*arotto, *. *inot*o, G. C. Mal**aia, M. P. Martínez </line>

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<par>

<line> Co*pet*ti*e adv*nta*e is *n advanta*e th*t the firm has i* a ma*ket, which </line>

<line> diff*re*tiates it from i*s competi*ors, through a*t*ibutes that it *olds and is offered *o its </line>

<line> c*stomers (Porter, *986). These advantage* *rise fr*m fir**, which base* on a g*ven </line>

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<line> *errit*ry, generat* det*rmi*ants of </line>

<line> their compet*t*ven*ss a** of th* te*rit*ry in which *hey </line>

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<line> *perat*. *ompet*tive </line>

<line> advant*ge det*rmin*d ** decisive charac***isti*s is </line>

<line> that a**ow firms to </line>

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<line> *reate and maintain *ompet*ti*e*ess (Cou*i**o et al., 200*). </line>

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<line> Accordin* to Vasconc*los and Cyrino (2000), there are *wo the*retical </line>

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<line> *he competitive adv*ntag*. Firs*ly, the compet*ti*e advantage is exp*ained by external **ctors </line>

</par>

<par>

<line> such as marke* process*s (Aust*ian Schoo* - Hayek </line>

<line> and Schum*eter) and indust** structure </line>

</par>

<par>

<line> (Str*ctur*-C**duc*-P*r**rma*ce M***l - Scherer and Ros* and Positioning Analys** </line>

</par>

<par>

<line> Porter). Second a*is, the compet*tive </line>

<line> adva*tage is *xplained by *he internal factors, spec*fic </line>

</par>

<par>

<line> of the fir*, *uch as resources and co*petencies: Resource-Base* Vie* (*BV); and d*namic </line>

<line> capabilities (*C) (Vasconcelos & Cyrino, 20*0). </line>

<line> This study foc*sed *n the se*ond axis, since i*n**ating in IT t* create a competitive </line>

<line> *dvantage using Big Data depends on specific reso*r*es and internal *apabilities ** e*ch *irm </line>

<line> t* *enerate, store, proces* an* manage information. </line>

<line> Effici*n* management of resources crea*es *onditions fo* co*p*nies gene*ating </line>

</par>

<par>

<line> compet**ive ad**n*ages on marke*s in which they </line>

<line> operate. Ac*o*din* </line>

</par>

<par>

<line> companies can different*ate *hroug* thei* resou**e* and not every resource </line>

<line> can generate </line>

</par>

<par>

<line> c*m*etitive a*vanta*e. *or this o*c*r, four req*irements sh*uld be met: *) resource *ust be </line>

</par>

<par>

<line> valuable </line>

<line> to exp*oit ****rtuniti*s </line>

<line> and/or mitig*te t*re*ts </line>

<line> in the business env*ronme**; b) </line>

</par>

<par>

<line> resource must be rare among </line>

<line> *urrent and potential </line>

<line> com**titors; *) resour** m*s* be </line>

</par>

<par>

<line> imperfect*y imitab*e (diff*c*lt *o *mitate); d) **ere must be no eq*iv*lent sub*titutes for this </line>

</par>

<par>

<line> resource, wh*ch a*e valu*b*e, b*t not </line>

<line> rare or impe*f*ctly imita*le (Barney, 199*). *hus, </line>

</par>

<par>

<line> res*urces ca* **nerate compe*i**ve d**fer*ntials accordin* to *heir availa*ility, specifi*ity and </line>

<line> ability to add valu* *o final *r*duc*s. </line>

<line> T*e concept of resource-based v*sion shows a competitive hetero*e*eity betw*en </line>

</par>

<par>

<line> compani*s. Each company *as its </line>

<line> own ch**acteristics, in*mitable and inta*gi*le, re*ources </line>

</par>

<par>

<line> that allow </line>

<line> a different*a*ed and superior </line>

<line> performance that allo* oppor*unities for </line>

</par>

<par>

<line> g**eration of com*et*tive a**a*tage (Habb*rshon & Wi*liams, 1999). </line>

<line> *ev. FSA, T**esi*a, *. 18, n. 01, art. 1, p. 3-*4, ja*. 20*1 www4.fsanet.com.br/**vista </line>

</par>

</page>

<page>

<par>

<line> Big Data and *ompetitive Adva*tage: Some Dir*ctions *nd *ses </line>

</par>

<par>

<line> A firm i* uniq*e in its strategi* </line>

<line> re*ources. Heterogeneous chara*terist*cs </line>

</par>

<par>

<line> potentially create advantages over co*pe*it*rs since every firm can hold exclusive reso*rces </line>

<line> that a*e not pe**ectly movable to others. It *ll*ws firms maint*i*ing a *om*etitive a*vantag* </line>

<line> for long peri*d* (Almarri & G**dine*, 2014). The th*ory examin*s *elati*ns b*tween internal </line>

<line> c*aracteris*ics and proc*sse* of a firm, as well as its performance. Compe*iti*e heterogeneity </line>

<line> arises from the premise tha* the close*t *ompetit*r* differ i* resources an* capacitie* *n an </line>

<line> impo*t*nt an* lasting way (H*lfat & Peteraf, *003). </line>

<line> The r*source-based view has been i*creasingly used b* sch*la*s and strategists wi*hin </line>

<line> org*ni*at*on* to identify management phen*m*na *nd the di*cussions is proposed b* sev*ral </line>

</par>

<par>

<line> *u*hors (Jang, 201*). Th*y mentio* that </line>

<line> co**orate re*o*rces play a k*y role in </line>

<line> explaining </line>

</par>

<par>

<line> p**nomena such *s: the strategi* manag*men* of the organization (Barne*, 2*01a, Ba*ney, </line>

<line> *001b), strategi* all*ances (Eisenh*rdt & Sc**onh*v**, *996, W*ssm*r & *ussa*ge, 2012), </line>

<line> business d*versi*ication (Silverman, 1999), new product develop*ent (H*na*d & McFadyen, </line>

</par>

<par>

<line> 2012, *erona, 1*99), coop*rat*on </line>

<line> *etween firms </line>

<line> (Combs & K*tchen *r., 1999), marketing </line>

</par>

<par>

<line> (Srivastava, Fahey & Chri*tensen, </line>

<line> 2001), international sma*l bus**ess management </line>

</par>

<par>

<line> (Westhead, Wrigh* & Ucbasaran, 2001), entrepreneurship (Zahra, Hayton & Sal*ato, 2004) </line>

<line> In su*mary, the resource-based view highlight that some firms sh*w better </line>

<line> comp**itiv* performance b* differentiating their capabili*ies an* *esources. T*is ap*roach </line>

</par>

<par>

<line> **itia*ly focuses on </line>

<line> the in*ernal relati*nships of firms and points tha* **e resources **d </line>

</par>

<par>

<line> capacities that generat* c*mpeti*ive adva*ta*e should be protected wi*hin the firms. However, </line>

<line> the resourc*-based vie* reco**izes, in a more cu*rent approach, that value genera*ion may </line>

</par>

<par>

<line> als* result from combin*tions </line>

<line> of intern*l r**ources with ex*sting resources beyo*d the </line>

</par>

<par>

</par>

<par>

<line> This advance is e*i*enced by the focus on t*e formation of competitive ad*an*age </line>

</par>

<par>

<line> initial*y from t*e internal </line>

<line> resource* to ** overall v*ew, *onsiderin* the im*ortance of </line>

</par>

<par>

<line> relational res*u*ce* and th* in*titutional *nvironment in whi** fir*s *xist (Viana, *eto, </line>

</par>

<par>

</par>

<par>

<line> 2.4 D*namic capabilities </line>

</par>

<par>

<line> C*mpa*ies that pres*nt adv*n*ages in a global marke* can *apidly respond with </line>

</par>

<par>

<line> product i*nova*io* and </line>

<line> flex*bility. They *lso can manage, *oo*din*te and esta*li*h </line>

</par>

<par>

<line> *ompe*ences, in internal and extern*l e*vir*nmen*s (*eece & Pi*ano, 1994). </line>

<line> Rev. *SA, Teresi*a PI, v. 18, n. *1, *rt. 1, p. 3-24, ja*. *021 www4.fsane*.com.br/revista </line>

</par>

</page>

<page>

<par>

<line> E. L. Ca*arotto, E. Bi*ott*, *. C. Malafaia, M. P. Martínez </line>

</par>

<par>

<line> *ynamic c**abilitie* i* de*ined as *h* int*lligence of a co*pany to integrate, develop </line>

</par>

<par>

<line> or redesign *ts </line>

<line> i*ternal and external co***ten*es to *ompete in envir*n*en*s that change </line>

</par>

<par>

<line> quickly (Teece, Pisano & Shuen, 1997). *t *eflects the firm\s ability t* develop inn*vati*e </line>

<line> wa*s of obtaining competiti*e adva*tage *s well as *nviro*mental con*iti**s in t*e marke* i* </line>

<line> Dynamic capabiliti** as a so*r*e of competit*ve advan*age, "dynamic*" is the chan*es </line>

<line> of environmental chara*terist*cs r*sulting *rom th* ne*d for stra*egic responses *n a market in </line>

</par>

<par>

<line> which tim*-to-ma*ket (per*od of analysis a*d product launching </line>

<line> in th* market) **d tim*ng </line>

</par>

<par>

<line> (r*sponse the right **me) are crucial. "Capability" the s*rateg*c *anagement, adequacy, </line>

</par>

<par>

</par>

<par>

<line> *nd adaptatio* of organizational abilities in internal a*d external **vironments, as *el* *s the </line>

<line> management *f resources an* c*mp*te**ie* to ch*nge *uch *nviron*ents (**ece & Pisan* </line>

</par>

<par>

<line> *eirelles and C*ma*go (2*14) highlight*d that studies on dynamic *apabilitie* </line>

</par>

<par>

<line> ra*idly evolve* f*r diver*e areas of knowled*e, *ainly in dynamic mar*e*s with c*ntinuous </line>

<line> *echnolog*cal c**nge*. Th*s he*p* *o maintain a compe*itive advantage. T*e same occurs *n </line>

</par>

<par>

<line> compl*x environm**ts where strategic resour*es an* inte*nal co*pete*cies, </line>

<line> by themselves, </line>

</par>

<par>

<line> *r* not enough. </line>

</par>

<par>

<line> Wi**er (2003), app*oa*hed dynamic c*pab*l*tie* *ith a m*re comprehensive concept, </line>

</par>

<par>

<line> based *n the organiz*tiona* r*u*ine: an </line>

<line> organiza*ion** ca*ability is a high-level routine </line>

</par>

<par>

<line> b*havior that is le*rned, highly sta**ardiz*d, repetitiv* </line>

<line> or *uasi-repetiti*e, in p*rt base* </line>

</par>

<par>

<line> tacit knowled*e - w*ich gives the m*nage**nt a *et of dec*sion opti*ns to **odu*e significant </line>

<line> r*sults. </line>

<line> Accordi** to Eisenha*dt and Martin (2000, p. 1105), "dynam*c capa*il*ties *re a set of </line>

<line> s*eci*ic and ident*fiable proc*sses such as produ*t develo*ment, s*ra**gic decision-mak*ng, </line>

</par>

<par>

<line> **d all*ancing". Dynami* *apabilities *ontain idiosyncrati* featu*es in the*r </line>

<line> details </line>

</par>

<par>

<line> emerge fr*m </line>

<line> past sit*ations (path *epen*en*e). How*ver, the*e ar* *oin*s *f s*gnifican* </line>

</par>

<par>

<line> con*ergence betw*en firms and, from the managerial sphere; s*ch po*nts are </line>

<line> called "best </line>

</par>

<par>

<line> practices". </line>

</par>

<par>

<line> *las***ication for d*namic capabilities is divided into two views (Meirelles, & </line>

</par>

<par>

<line> *ompr*s*s a *et of behavior*, organizat*onal a**litie* </line>

</par>

<par>

<line> ca*abil*ties and the second, proces*es an* routine* *f organizations. The e*iste*ce of dynam*c </line>

</par>

<par>

<line> c*pabilities </line>

<line> in the con*inuous accum*lat*on of *xperiences and kn*w*edge base of an </line>

</par>

<par>

<line> organi*atio* is consider*d. The authors **oposed a more comprehensi** def*nition bas*d on </line>

</par>

<par>

<line> *ehavior* </line>

<line> and abilit*es; routines an* </line>

<line> p*ocesse*; an* mechanisms of </line>

<line> g*vernance </line>

</par>

<par>

<line> www4.fsanet.com.br/revista </line>

</par>

</page>

<page>

<par>

<line> Big *at* *nd C*m*etitive Advanta*e: Some Dir*ctions *nd Uses </line>

</par>

<par>

<line> of the knowledge. </line>

</par>

<par>

<line> 3 METHODS </line>

</par>

<par>

<line> To answe* the four questions *roposed in this pa*er the syst*m*tic *i*erature review </line>

</par>

<par>

<line> **th t*e a*pro*ch proposed b* Fin* (2013) wa* *sed, com**i*ed seven steps: 1) raising </line>

</par>

<par>

<line> research question; 2) </line>

<line> databa** selection; *) choo*ing res*arch issues; 4) a*plicatio* of *he </line>

</par>

<par>

<line> p**ctical s*lection **iteria; 5) application of the m*thodical selecti*n criteria; 6) review; 7) </line>

<line> *ynt*e*is of res*lts. Suess-Reyes and Fuetsch (20**), T*onema*n and **humann (20*8), </line>

<line> Bar*h and Rieckmann (***6) a*d Osagi* et *l. (2016) *lso adopted th*s pro**dure. </line>

<line> Aft*r raising the r*sea**h qu*s*ion*, three databases widely used in re*ear*h o* ar*as </line>

</par>

<par>

<line> of ad**n**t*ation were selec*ed: Web of Science; *c***c* D*rect; an* Scopus. *he </line>

<line> database </line>

</par>

<par>

<row> Scopus *ere used as a g*ug* of the results for the other two d*tabases since it com*rehends </row>

<row> inform*t*on *ot included i* the other databas*s. The reason *or cho*sing thes* *atabases was: </row>

<row> a) *u*ntit* and *uality of t** i*formation p*ovided; b) fa*ili*r*ty *ith the us*; *) availa*ility </row>

<row> an* ac*essibility v*a CAPES j*urn*ls s*stem. </row>

<row> The *erms "competitive advant*ge" and "Big D*ta" were searc*ed *nd thei* respective </row>

<row> re*ults a*e pres*nt*d i* Table *, divided **to bases *nd selectio* steps. </row>

<row> Table 1 - Search and *el*ction pr*cedur*s </row>

</column>

<par>

</par>

<par>

</par>

<par>

<line> Science Direct ("Co*p*titive A**antag*" AND "Bi* *ata") </line>

</par>

<par>

<line> Scopus ("Co*petitive A*vantage" AN* "Big Data") </line>

</par>

<par>

</par>

<row> Source: prepared by author*. </row>

<row> Al* *cientific jour*als we*e analyz*d investiga*ed regardless of their im**c* factor, </row>

</column>

</par>

<par>

<line> fo*lowing the sa*e reasoning li*e </line>

<line> prop*sed by Suess-Reyes an* Fuetsc* (2*17). W*rk </line>

</par>

<par>

<line> papers, symposium and *onf*renc* publica*ions, *s we*l as m*nuals and book ch*pters were </line>

<line> *n step 1, a wide *e*rch *f documents i* th* three database* was do** u**ng </line>

<line> competitive adv*ntage and Big Data *erms. *he se*rch for the terms were t*tle, a*stract and </line>

<line> keywords. Th* search criteria *o* selecting *nd i*cludi*g ar*icles we*e: full art*cles and open </line>

<line> Rev. F*A, Teresina PI, v. 18, n. 01, art. *, p. 3-24, *an. 2021 www4.fsan*t.com.br/revista </line>

</par>

</page>

<page>

<par>

<line> E. L. Ca*arotto, E. Bin*t*o, G. C. Mal*faia, *. P. Martín*z </line>

</par>

<par>

<line> ac*ess in the Por*al Peri*dicos CA*ES; scientific </line>

<line> pap*r fro* journ*ls with peer revi*wer </line>

</par>

<par>

<line> classifie* *n Quartil 1 (Q1) or Qu*rtil 2 (Q2) according wit* JCR I*dex; *ublished in English </line>

<line> between January 2010 to December 2017; Admini*tratio*, Economi*s, *ccounting, Finance, </line>

<line> Comp*ti*g, Engin*ering a*d IT ar*a* were co**idered. Journ*ls from Co*p*ting, </line>

<line> Eng*neering and IT *reas were included sin** th*t t*e Administrat**n area was at th* scope. </line>

<line> T*e se*rch res*lted in 144 articles. </line>

<line> In st*p 2, d*plic*t* arti*l*s, p*blications in n*n-English language, docum**ts *ot </line>

<line> availa*le in f*ll v*rsion and othe* kind o* docume*ts, w*th ju*t two terms a*d t*ey were no* </line>

</par>

<par>

<line> they n*t cl*ssif*e*. Tittles and abstracts were </line>

</par>

<par>

<line> exa*ined and eliminated 1*7 do*uments, 78 dupl*cated, and 29 for not addres*in* the </line>

<line> research approac*es in this part of th* paper. </line>

<line> In step 3, all *r*icles were re*d a*d eight artic*es *ere excluded *u* to *he f*l**wi*g </line>

</par>

<par>

<line> reaso*s: una*ailability; non-English publi*at*on; </line>

<line> not add*es*ing the research ap***a**; and </line>

</par>

<par>

<line> n*n-*cademi*al *ublic*tion (*anual). Finall*, *9 a*ti**es *omposed the d*taba*e f*r anal*sis. </line>

<line> 4 FINDINGS AND DI*CUSSION </line>

<line> T* analyze the re*ults, the previous*y introd*ced *ese*rch questions will be taken up: </line>

<line> 1. Do the a*ticles jointly address the term* Big D*t* and competi*ive adv*ntage? </line>

</par>

<par>

<line> *he an*lysis was </line>

<line> p**formed on articles se*rched on datab*ses from *010 to 2017. </line>

</par>

<par>

<line> Figure 1 *hows the evolution of the sci*ntific p*b*i*ations and *he n*mber *f authors ov*r the </line>

<line> rese*r*hed period, consid*ring only tho*e 29 se*ected articles: </line>

</par>

<par>

<line> *igure * - Ev*l*ti*n of **e **mber of publica*ions and author* </line>

<line> Rev. FSA, *eresina, *. 1*, *. 01, art. 1, p. 3-24, jan. 2021 www4.*sanet.com.br/revista </line>

</par>

</page>

<page>

<par>

<line> Big *ata an* Co*petitive Advantage: Some Directions and Uses </line>

</par>

<par>

<line> Source: pr*p*red by aut*ors *ase* in res*a*ch *ata. </line>

<line> The*e were no publications t*at j*intl* *ddressed B*g Dat* and *omp*titive advant*ge </line>

</par>

<par>

<line> between the year* 2*10 and </line>

<line> 2013. The number of pub*ications an* authors *a** gradu*lly </line>

</par>

<par>

<line> i*creased from 2013. T*e aut**rship ev***tion, four fr*m th* 86 listed au*hors stand out with </line>

<line> *he publications: Liu, Y. (201*a, 2017b); Carayannis, *. G. (*013, 2017); Ren, S. (2017a, </line>

<line> 2017b); * Zhang, Y. (2017a, 20*7b). </line>

<line> Th* art*cles we*e published in 2* different journals. The Jo**n*l *f *leaner Prod*ctio* </line>

<line> **d the *ournal o* Knowle*ge Man*geme*t wit* t*ree *rti*les each one, followed by </line>

<line> Californi* *anagement Review, Inform**ion & Management, International Journal of </line>

</par>

<par>

<line> Production Econ*m*cs a*d Journal of Intelligence Stu*ies in Busin*ss, wi*h two a*ti**es </line>

</par>

<par>

<line> th* issue of *his *tud*. </line>

</par>

<par>

<line> 2. The autho*s l*st Big Data as a **nerator of comp*titive advantage? </line>

</par>

<par>

<line> Some authors\ s*gned rela*ing Big Data to the gene*atio* o* **mpetitive advanta*e as </line>

<line> well *s techni*ues and me*ho*s used to *reat* the advantages. *f the 29 selected articl*s, 17 </line>

<line> st*dies ad*re*se* Big Da*a as a *enera*or of competitiv* advantage *u*h as: Alharthi, Kroto* </line>

<line> *nd Bowman (2017); Carayannis et al. (2017); C**ura*ia and Rosi* (20**): Côrte-Real, </line>

<line> Ol*veira a** Ruivo (2017); Grover and Kar (2*1*); *han and Vo*ley (2017); M*tthias et a*. </line>

</par>

<par>

<line> Byrd (2017); Zhang et al. (2017a); N*durupati, Tebboune and Ha*dman </line>

</par>

<par>

<line> Geo*ge (2016); He et al. (2015); Opresnik *nd Tai*ch (2015); Tan et </line>

</par>

<par>

<line> (2015); Fawcett and Wal*er (2014); Kabir and Cara*annis (20**); and Ribarsky, Wang an* </line>

</par>

<par>

<line> Re*. FS*, Teresina PI, v. 18, n. 01, art. 1, p. 3-24, jan. 2021 </line>

<line> w*w*.*sanet.co*.br/revi*t* </line>

</par>

</page>

<page>

<par>

<line> *. L. Ca*arotto, E. Bi*otto, *. C. Malafaia, M. P. Martínez </line>

</par>

<par>

<line> In t*e other 1* ar**cl*s, the r*lationship presented was </line>

<line> in*irect. The e**cu*ion of </line>

</par>

<par>

<line> pr*cesses that in*luded *ig *ata can re*u*t in the ge*e*a*ion of comp*titive advantage. In th* </line>

<line> *ajo*ity, the competitive adv*nt*ge is menti**e* in a **n*ric w*y. </line>

<line> 3. D* the au*h*rs classify Big Data in *he context *f th* r*source-ba*ed vi*w, dynamic </line>

<line> ca*abilitie* or both? </line>

<line> Few a*th*rs make Big Data classifica*ion expl**it within the r*s*urce-based view and </line>

<line> dyn*mic capa**lities. Only Nud*rupati, Tebboune, and Hardman (2016) c*assified *ig Dat* </line>

<line> *s a compa*y resou*ce an* a**roach it by the re*ourc*-bas*d vi*w. Carayanni* e* a*. (2017); </line>

</par>

<par>

<line> Côrte-Real, Oli*eira </line>

<line> and Kabir and Carayannis </line>

</par>

<par>

<line> (*013) approa*hed *ig Data by the dy*a*ic c**ab*l*ties o* a firm. </line>

<line> On the other hand, Gup*a and George (2016), Opresnik and T*isch (2*15) used bo*h </line>

</par>

<par>

<line> **p*oa*h*s *o justify Big Data as </line>

<line> ge**rat*r of co*petitiv* advantage*. The las* autho*s </line>

</par>

<par>

<line> considered r*sources as a source of com*etitive *dvant*ge; however, resour*es cannot per*ist </line>

</par>

<par>

<line> therefor*, cannot be a s*stainable *dvantage. To </line>

<line> avoid th*s, </line>

</par>

<par>

<line> capabi*ities sh*uld result in supe*ior performance. The con*tru*tion of dynam*c cap*bilities *s </line>

<line> c*uc*al *or "constant pursuit of the r*newal, r*configura*ion and r*-creation of *esources an* </line>

<line> capabilities to addre*s the environme*tal c*ange [...] the \ul*imate\ organi*ation*l cap*bilities </line>

<line> t**t are c*nducive to *ong-term *er**rmance" (*presnik & *aisch, 201*, p. 182). </line>

</par>

<par>

<line> ** approach did the </line>

<line> aut**rs use to consider </line>

</par>

<par>

<line> com*etitive *dvanta*e? </line>

</par>

<par>

<line> A**ordin* to the answer* f*r t*e </line>

<line> q**stion two, 17 studies a*dr*ssed Big *ata as </line>

</par>

<par>

<line> g*nerator o* competit*ve advantage in a diversity of </line>

<line> approaches *uch as kn**ledge </line>

</par>

<par>

<line> management; *er*ormance ma*agement; *arketi*g str*tegy; productio* </line>

</par>

<par>

<line> *akin*; *rganizational proce**es; and resources and ca*acities (T*ble 2). </line>

</par>

<par>

<line> **ble 2 - *ig Data **lat*onship with Competitive A**antage approach </line>

</par>

<par>

</par>

<par>

<line> Knowledge management </line>

<line> Khan and Vo*ley (2017); Ca**yannis et al. (*017); Cô**e-R*al, ***veira and R*ivo (*017); Kabir and Caray*n*is (2013). </line>

</par>

<par>

<line> Performance **nag*ment </line>

<line> **durup*ti, Tebb*u*e and Hardman (2016); Fawcett a** Wal*er (2014). </line>

</par>

<par>

<line> Marketing strategy </line>

</par>

<par>

<line> Product*on *tra*egy </line>

<line> Zh*ng *t al. (2017a); *p*esnik *nd Ta*sch (2015). </line>

</par>

<par>

<line> Rev. FS*, *eresina, v. *8, n. 01, art. 1, p. *-24, jan. 2021 </line>

<line> *ww4.fsanet.co*.br/revi*ta </line>

</par>

</page>

<page>

<par>

<line> Big Data and *om*eti*ive Advantage: Some Dir*ctions and U**s </line>

</par>

<par>

<line> Organizat***al processes </line>

<line> Matth*as et al. (2*17); Chaurasia a** Rosin (201*). </line>

</par>

<par>

<line> *ang and *y*d (2017); *lhar*hi, Krotov and Bowm*n (20**); Tan et *l. (2015). </line>

</par>

<par>

<line> Organi*ational resources </line>

<line> Grover and *ar (2017); Gupta and George (*01*) </line>

</par>

<par>

<line> Source: Web of Scienc*, Science **rect **d Scopus (2017). </line>

<line> *ll articl*s an*lyzed i* this phase ad*res*ed Bi* *a*a as a gen*rat*r of c*mpetitive </line>

<line> adv*ntage by different approach*s. Th*se ap*roache* have in common t*e generat*on, </line>

<line> acq*isition, an* storage of **ta *s *ell a* the conce*n *ith *roce*sing the* t* extra*t </line>

<line> in*ormation useful for th* creatio* of competitive adv*ntage. </line>

<line> Kno*l*dge management w** ind*cat*d by Khan an* Vor*ey (201*) as a key factor in </line>

<line> *fficient business processes a*d competitive adv*ntage. The authors designated the Big Data </line>

<line> textua* anal*sis as a *nowledge man*ge*ent facilitator. Ac*ordin* to the authors, generat**g </line>

<line> qua*ity knowledge t*rough Big Data *n*lysis i* of fundamental im*ort*nce for the </line>

<line> develo*ment of *ompetitive advantages. </line>

<line> Competiti*e advantages ***ult from k*owl*dge managem*nt and decision-maki*g ** </line>

</par>

<par>

<line> the org*nizat**nal inte*ligence c*ntex*. *eci*ion-makin* re**ires </line>

<line> understanding a*d </line>

</par>

<par>

<line> dim*nsioning of </line>

<line> the Big Da*a exploi*ation p*oce*ses, in which the most **po*tant aspect is </line>

</par>

<par>

<line> the proactive analysis, targeted to improve both t*e </line>

<line> individual a*d the team performance* </line>

</par>

<par>

<line> within org*nizations (Cara*ann*s e* al., 2017). </line>

</par>

<par>

<line> The a*option of Big Data analysis allows effective k*owledge management (both </line>

<line> internal **d external) tha* *elp* *o i*crease *he firm\s agility *hr*ugh t** id*ntificati*n of </line>

</par>

<par>

<line> thre**s and *ppo*t*n*tie*, us* of opp*rt*n*ties a*d attainment of competitive adva*tage </line>

</par>

<par>

<line> adju*ting th* technologi*al enviro*ment (Côrte-Real, Oliveira & Rui*o, 2*17). </line>

</par>

<par>

<line> Efficient B*g Da*a ma*a*em**t can pro*uc* sources </line>

<line> o* compet*tive adv*ntages. </line>

</par>

<par>

<line> Howev*r, there i* a need fo* c*mbining staf*, tools, and data, t*gethe* *ith the dev*lopmen* </line>

</par>

<par>

<line> of a data-oriented culture. *a*a *reated </line>

<line> *uring ope*ating processes an* *ct*vitie*, as*o*iated </line>

</par>

<par>

<line> with the de*el*pment ** staf*\s a*ilitie*, can be a grea* pot**tial for developi*g a competiti*e </line>

<line> adv*nta** (Kabir & Caray*nnis, 201*). </line>

</par>

<par>

<line> N*du*upati, Te*bo*n*, and Har*man (2016) </line>

<line> *pproac* Big *ata </line>

<line> by o*ganizational </line>

</par>

<par>

<line> performance manag*men*. Organizat*ons i*te*e*ted in t*c*no*ogic*l deve*opments such as </line>

</par>

<par>

<line> the Internet of Things (IoT) or social media mi*h* creat* new prod*cts and busi*ess mode*s. </line>

<line> Currently, data are easy to ob**in and h*ve a low *aintenanc* **s*, which i* a good reaso* to </line>

<line> use *ig Data (Fawcet* & Waller, 20*4). </line>

</par>

<par>

<line> Rev. FSA, Teresina PI, v. *8, n. 01, art. 1, *. 3-*4, jan. 2021 </line>

<line> www4.fsanet.com.*r/revista </line>

</par>

</page>

<page>

<par>

<line> E. *. Casa*otto, E. Binotto, G. C. Malafai*, M. P. Ma*tín*z </line>

</par>

<par>

<line> He et al. (2015) developed a market analysis t*ol based ** ma*keting strategi*s </line>

<line> (comm*rcializat*on). Com*a*ies should develop *bili*ies of so*ial m*dia *ompetitive an**ysi* </line>

<line> to *rod*ce dif*eren*ia*s ov*r com*etitors and in an inno**tive approach to eval*ate, mo*itor </line>

<line> *nd compare **cial med*a da*a ** vari*us brands *n* c**panie*. </line>

<line> Moni**rin* mar*et actions throu*h Big Data *s impor*a*t becau*e Bi* Data ana*y*es </line>

</par>

<par>

<line> are linke* *o strateg*e* th*t, in *ertain circumstances, can </line>

</par>

<par>

<line> *edia such as Twit*er and Fa*ebook (Ri*arsky, Wang & Do*, 2013). </line>

<line> *ig *ata is also linke* to production str**egi*s of products and services. T*e </line>

<line> e**loit*tion of Big Data can be the *ext **ep for the value cr*ation after prod*ct actualizat*on </line>

<line> in a manu*actur*ng ser**ce ecosys*em (MSE). A manufac*uri*g company *an d**fer**tiate by </line>

</par>

<par>

<line> o* Big Dat* exp*oitatio* strat*g* and eff****nt Big Data use *n the ser*itiz*t*on </line>

</par>

<par>

<line> proc**s, thus *timulat*ng the most important of the "Vs" - Value (Opres*ik & Tais*h, 20*5). </line>

<line> Z**n* et al. (2017a) affirm t*a* companies can strategically differentiate in the market </line>

</par>

<par>

<line> by using Big *ata r*s*u*ces </line>

<line> com**n*d with a s*rv*ce-*r*e*ted manufa*turing model. The </line>

</par>

<par>

<line> mastery of advanced technology *ombine* w*th a service-oriented mo*el </line>

<line> can effect*vel* </line>

</par>

<par>

<line> *n*rease the c*mpe*itive advant**e of c*m*anies. </line>

</par>

<par>

<line> Efficient **n*g*ment *nd improvements i* the or*anizational *roc*sses are </line>

</par>

<par>

<line> *mporta*t to make </line>

<line> st*ategie* work. The *ig Data solutions </line>

<line> applied to t*ese </line>

<line> p*ocesses offe* </line>

</par>

<par>

<line> c**ditio*s for </line>

<line> organizati*ns exploitin* and making use of the tech*olo*y to create </line>

</par>

<par>

<line> compe*iti*e a*vantage*. Such applicati*n is highl*gh*ed s*nce socia*, te*hn*logical and human </line>

<line> dema*ds o*cur. C*nseque*t*y, these current demands mu*t be met a* th* long-*e*m real </line>

<line> advantag* is reache* (Matthias et al., *017). </line>

<line> O* the other hand, the us* of Big Data can *till be a com*lex org*nizational proc*ss, </line>

</par>

<par>

<line> an appro***ate platfor* for th* organi*ational </line>

</par>

<par>

<line> in*rastructure. The pro*ess o* deve**ping usab*lity *apabilities will also d*man* the atten*i*n </line>

<line> of ma*age*s. *hi* proce*s consolidated c*u*d generate compet*tive a*vantages for </line>

<line> organizat*ons (*haurasia & *osin, 2*17). </line>

</par>

<par>

<line> In ge*eral, manag*ment proc*sses are d*iven by decis*on-making, which should </line>

</par>

<par>

<line> ma*e with a b*si* on diverse in*ormation and s*tuations observed </line>

<line> from various sources. Big </line>

</par>

<par>

<line> Dat* appears as an important to*l and source of competiti*e advantage. </line>

</par>

<par>

<line> Conceptual m*dels in inform*t*on technolo*y </line>

<line> views of resou*ces and </line>

</par>

<par>

<line> c*pabilities can i*f*uen** the effe*tiv*ness of d*cision-making. Howe*er, this is an a*ea *hat </line>

<line> **eds *o *e *e***r explored to **come e*f*ctive (Wang & Byr*, 2017). </line>

<line> Re*. FSA, T*resina, v. 18, *. 0*, ar*. *, p. *-24, jan. 202* www4.fsan*t.*o*.br/re*ista </line>

</par>

</page>

<page>

<par>

<line> *ig *ata an* Compet*tive **van*age: Some Directio** a*d U**s </line>

</par>

<par>

<line> The pote*ti*l of **ow** is big; however, B*g Data can onl* g*ne*ate c*mp*tit*ve </line>

</par>

<par>

<line> advantage if *anag*rs use *e*h*iq*es that stru*ture and link various data se*s </line>

<line> to *reate a </line>

</par>

<par>

<line> cohere*t ima*e of a specific problem. Extracti*g impo*tant and *se*ul information for a be*te* </line>

</par>

<par>

<line> view of the problem i* </line>

<line> the key to obt*in a competitive advan*age in </line>

<line> d*n*mic business </line>

</par>

<par>

<line> enviro*ments (Tan et a*., 2*15). </line>

<line> Bi* Data and its ca*acity f** anal*zi*g and usin* co*plex *a*a se*s a*e increasingly </line>

</par>

<par>

</column>

<row> *s the most impo*tant sou*ce ** compet*tive a*vanta*e </row>

</column>

</column>

</column>

</par>

<par>

<line> century. The Big Data potential of increasing in*er*al a** *xtern*l efficiency and im*r**ing </line>

<line> t*e *r*fitabi*ity *nd compe*itiveness of organizati*n* i* ve*y big (Alhar*hi, Krotov & </line>

<line> Bowman, 2017). </line>

<line> **tho*g* not e*plic*tly, the *tudy o* Grover and Kar (2017) presen*e* Big Dat* and i*s </line>

<line> variable* as a* org*niz*tional resou*ce. *or t*e aforeme*tioned *ut*ors, the correc* choice </line>

<line> of tools *or a given foc**, allows to ide*tify problems and, consequently, to elaborate a set o* </line>

<line> *pproaches or means for the s*luti*n o* these. Thu*, Big Data and its *pplication* are tools for </line>

<line> *olving complex problems in v*rious or*aniz*tional environments (G*over & Kar, 2017). </line>

<line> H**ever, the B*g Da** potential **r competitive adva*tage should *e nec*ssar*ly </line>

</par>

<par>

<line> as*ociated with *h* r*sou*ces *nd capacities *f orga*izations, a* </line>

<line> previously m*ntione*. This </line>

</par>

<par>

<line> was previo*s </line>

<line> poin**d by Gupta and George (2016), t**t B*g Data c*n </line>

<line> g*nerat* competitive </line>

</par>

<par>

<line> advanta*e when used together wit* oth*r cap*cities *f the firm. </line>

<line> Finally, human a*il*t*e* and intangible resources are neces*ary. I* a*dition t* tech*ical </line>

<line> and managerial *vailab*lity, it is important f*r * co**any to ap*ly all the org*nizational </line>

<line> lear**ng and culture to e**a*ce the Big Data potential. According to *upta and Ge*rge </line>

<line> (2016), only t*e conjoint effe*t o* resources *ould cre*te a sp*cific ca*a**ty f*r the firm. By </line>

<line> itsel*, it i* not probable th** Big Data could represent a *our** *f comp*t*tive advantage sin*e </line>

<line> Big D*ta can *e accessed by many organizations. </line>

<line> 5 CONCLUSION </line>

<line> This paper provided a sy**ematic literatur* r*view on the *ig Data and comp*ti*ive </line>

<line> *dv*ntage issue*. In the res*lts of 29 a*ticles, ana*yzed *ig Data is appro*ched as a generator </line>

</par>

<par>

<line> of competitive advanta*e. H*wev*r, seven articles c*ass**ied *n the perspect*ve of </line>

</par>

<par>

<line> resource-bas*d view *r dynamic </line>

<line> capabilities, **ur ad*resse* to dynami* capa*ity, one </line>

</par>

<par>

<line> *esource-based view and t** other* addressed to both pe*specti*es. </line>

<line> Re*. FSA, Ter*sina PI, v. 18, n. 01, art. 1, p. 3-24, jan. 2021 w*w4.fsanet.com.br/revist* </line>

</par>

</page>

<page>

<par>

<line> E. L. C*saro*to, E. Binott*, G. C. Mal*faia, M. P. Martínez </line>

</par>

<par>

<line> In *hese articles, se**ral ***roaches justify the generation, or ma*ntenance, of </line>

<line> co*petitive a*vant*ges by using Big Dat* resourc*s, either by *s*ng B*g Dat* analysis, or by </line>

<line> usi*g l*rge vo*umes of data in conjun*tion wi*h othe* to*ls. </line>

<line> Alt*ough the analys*s *f the a*ticles d*d not m*ke it explicit, *e believ* *hat *he best </line>

<line> way to analyze *nd describe Big D*ta as a gen**ator *f compe**tiv* adv*ntage is th**ugh its </line>

</par>

<par>

<line> *ntegrat**n with *he res**rce-based *iew based and *ynamic ca*abil**ies. Seem </line>

</par>

<par>

<line> as an enterpri*e asset, because re*ources are need*d to foster the generation, </line>

</par>

<par>

<line> storage, processi*g *f data, as well as financ*a* and human resources. </line>

<line> It still difficu*t to a*f**m th*t *i* Da*a c*n g*nerate a competitive *d*an*age o*ly from </line>

<line> a resource-based view, especial*y i* the long term. This is because resou*ces are a**ilable for </line>

</par>

<par>

<line> an* *rganizati*n. *herefo*e, peculiar *r ex*lusive info*mation, o*ce </line>

<line> ob**ined, would *e the </line>

</par>

<par>

<line> d*fferent*ator *o a*d val*e in a *roduct or s*rvice. Th* *iffer*ntial would *e a rar*t* because </line>

</par>

<par>

<line> the informa*io* </line>

<line> is not a*ailab*e to competit*r*; thus, difficult t* *mi*a*e and co*se*u*ntly </line>

</par>

<par>

<line> irr*placeable. </line>

</par>

<par>

<line> On the one h*nd, the resource-**s*d vi** c*n de*ine Bi* Data as **e generator of </line>

<line> competit*ve advantage, *ec*use organizations need sp*cific cap*bi*ities to ext*ac* val*able </line>

</par>

<par>

<line> in*ormat*on to create </line>

<line> competit*ve a*van*age in d*nami* and compet*tive **sines* </line>

</par>

<par>

<line> enviro*ments. *ynam*c </line>

<line> *apabilit*es *an comp*ement t*e resource-based view </line>

<line> analysis to </line>

</par>

<par>

<line> ex*l*in **w *ig Dat* can gen*rate a com*etitive advantage. </line>

<line> The lack of a robust t*eoretical f*a*e*ork *or Big Dat* analysi* *s evidenced by the </line>

</par>

<par>

<line> predominanc* of descri*ti*e article* and practical rep*rt*. H*nc*, more elemen*s </line>

</par>

<par>

<line> n*cessary to clas*ify Big Da*a as a gene*ator of </line>

<line> competitiv* a*vantage **ly i* the res*urce- </line>

</par>

<par>

<line> b*se* v**w. Yet, *ynamic capabilities sho**d co*plement Big Data whe* t*is *s classif*ed as </line>

<line> In practice, organizati*ns need *apid adaptations to create a compe*itive *dvantage by </line>

</par>

<par>

<line> using the va*t </line>

<line> *vai*ability of data *xisting under the *ost diver*e forms **d levels of </line>

</par>

<par>

<line> s*ruct*ri*g. For this, moder* equipment, up-to-dat* p*ocess*s, intelligent systems, a*d user </line>

<line> train*ng are indispens*b*e. </line>

</par>

<par>

<line> *his revi** contribute* to discussions </line>

<line> on the *tate-of-the-ar* of t*e theme* here </line>

</par>

<par>

<line> sug*ested: Big *ata; *omp*t*tive ad*an*age; resou*ce-based view; *nd d*namic capab*li*ies, </line>

<line> them*s *ha* are little *iscussed c*n*ointly in the searched li*eratu*e. </line>

<line> Th* majo* limitations of this st**y *ere the content of so*e *ub*ic*tions\ abstracts </line>

<line> tha* did *ot describe clearly or no* b*ing evidence ab*u* the us* of resource-based view and </line>

<line> dynamic ca*abilit*es i* its discussion, and the **a**ic*l bias of the most publi**tions *howi*g </line>

<line> Rev. FS*, Tere*ina, v. *8, n. 01, *rt. 1, p. 3-24, j*n. 2021 www4.fsa*et.com.br/revista </line>

</par>

</page>

<page>

<par>

<line> Big Data a*d *ompetitive Advant*ge: Some Directions a*d Uses </line>

</par>

<par>

<line> littl* theo*et*cal </line>

<line> disc*ss*o*s. The lack o* th*o*etical ba*k*r*und in the articles is </line>

<line> probabl* </line>

</par>

<par>

<line> becau** Big Data *s a new theme with u**n*wn facets, **t*ou*h much discussed. Howev*r, </line>

<line> t*is i* only an assum*t**n, *ithout the p**tensio* o* being confirmed by th*s research. </line>

<line> For future *es*ar*h, it is su*ge*ted *o deep*n *n other f*elds *f science that mig*t </line>

<line> benefi* fr*m Big Data, exp*or*ng all p*ssible al*ernati*es of us*. In t*e context of the applied </line>

</par>

<par>

<line> *ocial sci*nces, it is pr*posed more cover*ge for t*e **bject, </line>

<line> a*dressing not ***y t*e </line>

</par>

<par>

<line> c*mpetitive adv*nta*e b*t also the strategic b*siness management. </line>

</par>

<par>

<line> R*FERENCES </line>

</par>

<par>

<line> Agra*al, *., Bernstein, *., Bertino, E., Dav*dson, S., Dayal, U., *ra*klin, M., ... & Jagadis*, </line>

</par>

<par>

<line> and Opportunitie* with big *ata *0**-1. Retrieved from: </line>

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<line> https://docs.li*.pur*ue.*du/cctech/1/. *ccess: April/2018. </line>

<line> Al*arri, K. & Gardiner, P. (20*4). Application of resou*ce-based view to projec* </line>

<line> ma*age*ent research: supporters an* opponents. Procedia-Social a*d Behavioral </line>

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<line> A., Krotov, V. & Bowman, M. (2017). Addressi*g barriers to big *ata. Busines* </line>

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<line> *arney, *. B. (**91). Firm resou**e* an* *ustained competi*ive advantage. Jou*n*l of </line>

<line> *ana*e*ent, 1*(1), 99-120. https://doi.org/*0.*177%2*01*920*39101700*08 </line>

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<line> Barney, J. B. </line>

<line> (*001a). Resou*ce-based theories o* com*etitive ad*antage: * ten-year </line>

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<line> retr*spec*i*e on the resourc*-base* view. Journal of management, *7(*), 643-650. </line>

<line> https://doi.o*g/10.1016/S0149-206*(01)0011*-5 </line>

<line> Barney, *. *. (**01*). Is the **sour*e-based "*iew" a useful *erspective for *tr*t*gic </line>

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<line> ma*agement </line>

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<line> https://d*i.org/10.*465/AMR.2001.*011938 </line>

<line> Bart*, *. & R*eckm*nn, M. (2016). State *f t*e *rt in *esear** on higher e*ucation *or </line>

<line> *ustainable d*v*lo*m*nt. Matt*ias B*rt*, Gerd Mich*lsen, Marco Ri**k***n und I*n </line>

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<line> Thomas (*d*.): **utledge Handb*ok of Higher Edu*ation for </line>

<line> Sust*inab*e Deve*opment. </line>

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<line> *ondon: Rou*l*d*e, 10*-1*3. </line>

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<line> Car**annis, E. G., *rig*roudis, E., Del Gi**ice, M., Dell* Peruta, M. R. & Sindakis, S. </line>

<line> (2017). An explor*tion of contemporary organiza*i*nal artifacts and routi*es ** a sustainabl* </line>

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