Scenarios of the Degree of Centrality and Density of the Networks of the Main Brazilian Airports Between 2003 to 2020 / Cenários do Grau de Centralidade e Densidade das Redes dos Principais Aeroportos Brasileiros Entre 2003 a 2020

Luiz Rodrigo Bonette; Fernanda Alves de Araújo; João Gilberto Mendes dos Reis; Paula Ferreira da Cruz Correia

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

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

<line> *SSN Impresso: 18*6-6356 ISS* Eletr*nico: 2317-2983 </line>

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<line> Sce*arios of the Degree of Centralit* a*d Density *f t*e Netw**ks of the Main B**zilian </line>

<line> Airp*rts Between *003 t* 2*20 </line>

<line> Cenári*s do Grau de Ce**rali*ade e Dens*dad* das Re*e* dos Pri*cipais Aeroportos B*as*leiros </line>

<line> Entre 20** * 2020 </line>

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<line> Luiz *odrigo Bonette </line>

<line> *outorado *m Engenhari* de Produção pela *ni*ersidade Pauli*ta </line>

<line> Mestre *m E*genhari* *e Produ*ão *ela Univers*d**e de Arar*quara </line>

<line> Fern*nda Alves de Araúj* </line>

<line> Mes*re em Engenha*ia d* Pr*duçã* pela Univ*rs*d*de Paulis*a </line>

<line> E-m*il: fernanda.lo*istica@gmail.com </line>

<line> João Gilberto *endes dos Reis </line>

<line> D*u*o* e* En*enha*ia d* *rodução pela Uni*e*sida*e Paulista </line>

<line> *rofesso* *a *niversidade Paulista </line>

<line> E-*ail: jo*o.*eis@docen**.u*ip.b* </line>

<line> Paula Fe*reira da Cr** Correia </line>

<line> *outora*o em Engen*aria *e Produçã* pela Uni*ersid*de Paulis** </line>

<line> Mestra em *ngenharia de P*odu*ã* pela Universidade P*u*ista </line>

<line> E-m*il: paul**ecruz@*mail.com </line>

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<line> Endereço: Lui* Rodri** Bonette </line>

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<line> Paulista, </line>

<line> Vista, </line>

<line> Paulo </line>

<line> Editor-C*efe: Dr. *o*ny Kerley *e Alencar </line>

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<line> R*drigues </line>

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<line> Ende*eço Fernanda Alves de *raújo </line>

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<line> Vista, </line>

<line> Paulo </line>

<line> Artigo *ec**ido em 1*/06/202*. Últim* </line>

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<line> *00. Brasil. </line>

<line> recebid* em 2*/06/2021. Aprovad* em 28/06/2021. </line>

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<line> Ende*e**: Jo*o Gilbert* Mendes dos R*is </line>

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<line> Paulista, </line>

<line> Vista, </line>

<line> Paulo </line>

<line> Avaliado pe*o s*st*ma Triple Review: Desk Review *) </line>

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<line> *elo Editor-Chefe; e b) Double *lind Revie* </line>

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<line> End*reço: Paul* Ferreira da Cruz Correia </line>

<line> (aval*ação cega **r dois avaliadores da área). </line>

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<line> Revis*o: Gramatica*, N*rmativ* e de Formatação </line>

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<line> Developm*n* A*ency: This st*dy was financed *n **r* b* *he Coordenaç*o de Aperfeiçoame*to *e Pes*oal de Ní*el </line>

<line> Superi*r - Brasi* (CAPES) - Finance Code 001. </line>

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<line> Scenarios of th* *egree of Centra*ity and Density of the Net*o*ks of the *ain Brazi*i*n *irports </line>

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<line> ABSTRACT </line>

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<line> The ident*ficatio* o* air transport netwo*ks is re*e*ant to the economic devel*pme*t of a city </line>

<line> o* re*ion, throug* its passen*er dema*d*, an*, *n th*s *a**, there m*y be * d**fer*nce *e*ween </line>

<line> *he fo*mation of t*e** networ*s in di*ferent **r*ods and whi*h are the main actors comp*red </line>

<line> in a sample of seven airports. Th* aim of this study is to analy*e the degree of centrality of the </line>

<line> n*twork *f the seven largest Br*zilian pa*sen*er air*o*ts. Th*s sample is based on the **aly*is </line>

<line> of netwo*k indicators *or the collection and extraction of pa**enger data betwee* destinations </line>

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<line> and ai*port o*igins by the Natio*al Civil Aviation Agency (ANAC). *he Soci*l </line>

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<line> Analysis (SNA) meth*d was ap*lied for th* construct*on of *etwo*ks thr*ugh the application </line>

<line> of @ *cinet/Netdraw Vers*on *.716 software *o understand the deg*ee of centra*ity and the </line>

<line> den*ity of the netw*rk in the scenarios ** 2003, 2007, 201*, 2018, and 2020. *t was concluded </line>

<line> that t*e *onjun*t*re of the links and nod*s within t*e scenarios of the *ub-a*d-**oke airport </line>

<line> net*orks o* the flows *s susta*ned, to a greater and les*er *x*ent *n the netw*rk, by an airport </line>

<line> i* th* Braz*lian midwes*er* regi*n (Brasíl*a) a*d two other airp**ts in the **utheastern re*i*n. </line>

<line> For futur* con*ri**tions, the nine-mo*t* 2020 Covid-19 pandemic pe*iod was anal*zed, </line>

<line> bringing *esults s*ch as reduc*io*s in *he deg*ees of centra*ity an* density of the netw*rk of </line>

<line> *he*e se*en airports. </line>

<line> *eyword*. Airp*r*s. Passenger*. H*b-A*d-*poke. *NA. </line>

<line> RESUMO </line>

<line> * identifi*ação da* redes de t*ansporte aéreo é relev*nte para o d*senvolv*mento econômico </line>

<line> de uma **dade ou regi*o, por mei* de suas demandas de passageiros, e, ne*te caso, pod* haver </line>

<line> **a d*ferença entre * formaç** *essas *edes em d*ferentes período* e qua*s *ão os pr*n*ip*is </line>

<line> a*ores *o*parados em uma amostra de sete ae*oportos. O obje**vo deste estudo f*i analisar o </line>

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<line> *rau *e cent**l*dade da mal*a dos sete *aiores aeropor*os </line>

<line> *rasileiros de passageiro*. Est* </line>

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<line> amostr* é baseada na *nálise de i**icador*s </line>

<line> de rede *ara co*eta extração de dados e </line>

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<line> passa*eiros **tre destino* e orig*n* **r*p*rtuá*i*s pela *gência Naci*nal *e A**ação Civil </line>

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<line> (*NAC). O método de Análise de Redes *oc*ai* (SNA) foi aplicado </line>

<line> para a const*ução </line>

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<line> rede* através da aplicação *o *of*war* @ Ucinet / Net*ra* Ver*ã* *.716 para enten*e* o grau </line>

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<line> de centralida*e e densidade da rede *os *e*ários d* 200*, 2007, a </line>

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<line> Conclu*u-*e que a conjuntura *os e*** * *ós dent*o dos cenários </line>

<line> das rede* hub-and-spoke </line>

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<line> airport nos fluxos é sust**tada, em mai** o* menor g*au na red*, po* um a*r**orto d* r*gião </line>

<line> ce**ro-oeste br*sileiro (Brasília) e ou*ros dois ae**po*t*s da *egião sudeste do B*asil. Para </line>

<line> *ontr*buições fut**as o período *andêmico da *ovid-19 de n*ve m*se* d* 20*0 foi analisado, </line>

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<line> **a*endo resultad*s **mo as re*uçõe* nos *raus de *entr**i*ade e </line>

<line> densi**de da r**e destes </line>

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<line> sete aeropo*tos. </line>

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<line> Key*or*s. Aeropor*os. Passageiros. *ub-And-Spok*. SNA. </line>

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<line> www*.*s**et.com.b*/revista </line>

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<line> L. R. Bonett*, F. A. Ara*jo, J. *. M. Reis, P. F. C. C*rreia </line>

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<line> Hub-and-spoke is a s*ste* of air transpo*t*tio* in wh**h local air*orts o**er fl**hts to </line>

<line> a c*n*ra* a*rport where interna*ional or long-dis**n*e fli*ht* are *va*lable (O'Kell* & Br*an, </line>

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<line> *998). Ae*ial ***works im*ly the cons*lid*tion of traffic from range of diverse origins a </line>

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<line> range of diverse final *estinations at large </line>

<line> *entral airports (Butt*n, </line>

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<line> cities have devel*pm**t advan*a*es for *ertain *ypes of e*on*m*c *ctiv*ties tha* ref*e*t two </line>

<line> *oints of distinc*ion that share * simi**r pro**l*. The **rst, the *o*centra*ion of large </line>

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<line> pass*ng*rs a*d c*rgo f*ow, *nd the second, </line>

<line> high degree of c*nne**i*ity with other </line>

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<line> d*m*stic poin** and internation*l air networ*s (Bowen, 2000). </line>

<line> Ana**zing th* ne*w*rk bu*lt of th* se*e* larges* Brazilian airpor*s, based ** the </line>

<line> sta**stic*l reports o* p*ssenger *ovement of *he Nation*l C*vil Aviat*on Agenc* - ANAC </line>

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<line> to have *iffe*ences between the passenger n*twork demon*tr*tin* its </line>

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<line> *ensity an* findi*g </line>

<line> the *easure of centrality in </line>

<line> periods ma*y *ifferent. The *tudy aims to </line>

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<line> centrality of </line>

<line> *he n*twork ** the seven-passeng*r ai*ports t**ough the </line>

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<line> SNA (*ocial Anal*sis Network) ne*w*rk method us*ng t*e @ **inet / Net*raw software. The </line>

<line> m*in actors i* the s*mu*ate* network were *app** and *raphically con*tructe*, with *irpor*s </line>

<line> **d cities valued for their movements data (pa*sengers) a*d links (c*nnec*ions) in th*i* flo*s </line>

<line> in the na*ional c*vi* avia**on m*rket. </line>

<line> Air tra*spor* an* *istri*u*ion in the*r c*rrent networks are undergoing profound </line>

<line> modi**c*tions and *h*s ada*ting to their aviat*on demands wh*n ana*y*ing **e *ifferent </line>

<line> annua* *ce*arios, in t**s *as*, 2*03, 2007, 2*15, 2*1*, and *020. T*e method*logy d*als </line>

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<line> with passenger mo*ements </line>

<line> betwee* seven ai*ports (Belo Ho*izonte - Co*fins, Bra*ília, </line>

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<line> Ca**inas, São Paulo - G*aru*hos, São Pau*o - Congonhas, Rio d* Janeiro - Gal*ão, Rio </line>

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<line> Janeiro - Santos Dumont) using the concept of centrality **asur* in n*two*ks of a degree of </line>

<line> density (conn*ctivi*y) of the network. </line>

<line> The discussion and r*sul*s p*opo*e th* visuali*ation and compar**on of *** airpor* </line>

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<line> network prop**ed *y scenarios </line>

<line> *nd historic*l antecedents b*fore the year of *ata collec*ion. </line>

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<line> T*e conclusion o*fers the t*end* and possibi*ities of ho* this network ca* be confi*ure* in its </line>

<line> links by facto*s such a* co**en*ration *nd *onnectivity *f th* actors, starting fr** the aviation </line>

<line> data of *as*engers of origin and des*inati*n. </line>

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<line> www4.fsanet.com.br/re*ista </line>

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<line> S*ena*i*s of t** Degre* o* Ce*trality and **nsity of the Networks *f t*e Main Brazilian Airp*r*s </line>

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<line> 2 THEORETICAL REF**E*C* </line>

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<line> Ce*tral airports *on*ider ind*rect conne*tion* through their </line>

<line> hub as an essential </line>

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<line> strategy (Veldhuis & Kr*es, *002). T*ere is *h* problem *f l*cating the arc of t*e hub, wh**e </line>

<line> a certain numbe* o* arcs a*e located in t*e hub (with r*duced *ranspor* cost per unit) to sa*isf* </line>

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<line> for trave* b*tween th* specified origin-des*ination pairs (Campbell *t </line>

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<line> of cen*rali*y and nodes are the lin*s in * </line>

<line> hub-and-spoke </line>

<line> netwo*k </line>

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<line> *an*c (2005) and Ball et al. (2006) po*nt out *hat the vulnerability of the hub-an*- </line>

<line> spoke system u*e* se*eral mitigation *tr*tegies pr*po*ed to postpone, *ance* *r **rward the </line>

<line> air transport sys*em. There are thr*e separate components for each *ub-*nd-spoke *low, the </line>

<line> collection (source node t* hub nod*), tra*sfer (hu* *ode *o hub nod*), a*d distr*bu*ion (*ub </line>

<line> node to d*stinat*o* no*e) (Ca*pbell et al., 2007). H*b network analy*is focuses on </line>

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<line> combination* o* mod*ls asso*iat*ng ce*tral hub* and econ*m*c objectives, </line>

<line> central hubs, </line>

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<line> se*vi*e *eve*s (Campbell, 1994). </line>

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<line> *he hub hierar*hy *u*t b* ana*yze* *y t*e flight f*equ*ncy, hub accessibil*ty, </line>

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<par>

<line> passenger variab**s to </line>

<line> a*d define the la*ers ** *his hub </line>

<line> h*er*rchy, influencing t*e </line>

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<line> conne*tivity ind*x </line>

<line> of *he e*ti*e hub-an*-spok* network (Ryerson </line>

<line> & K*m, 2013). Cargo </line>

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<line> transpo*tation *s </line>

<line> more *omplex than passenge* </line>

<line> transportation because </line>

<line> the *ormer inv*lves </line>

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<line> more actors w*th processes. *her*for*, it i* more sophi**icated and com*ining volumes, with </line>

<line> vari*d priority **rvi*es, with s*rategies f*r i*tegrat*ng and c*nsolidating variou* itineraries in </line>

<line> * netwo*k ** tr*nsp*rtat**n (Feng et al., 2015). </line>

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<line> T*e hu* *ccessibility </line>

<line> criterion </line>

<line> explores th* position of the sim*lated netwo*ks </line>

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<line> without *ncluding sma*l </line>

<line> *r regiona* airp**ts and *h*ir imp*cts in terms of economic *c*i**** </line>

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<line> and c*mpetitive pressur* on the h*b-a*d-spoke network, the*efor*, i* is necessary to analyze </line>

<line> t*e h*b behavi*r (R**ond* et al., 2012). </line>

<line> The connectiv*ty po*e*tial of airports, anal*zed by *onne*tivity inde*e* in **eir </line>

<line> r*gio*s, is influenced by the demand and plays * key r*le in determi*ing th* role of airpor** in </line>

<line> *ub-and-spoke ne*works (Rodrígue*-Deníz et al., 2013). The hub-and-s*oke n**work uses the </line>

<line> concept of "subs*i*ute *ub" or "b*ckup hub" within the desi*n of the hu*-and-spoke network </line>

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<line> f** roundtrip *lows parallel to the central hub flow (*u et al., </line>

<line> 2015). Mohri </line>

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<line> *ev. FSA, Teresina PI, v. 18, n. 7, *rt. 6, p. 94-109, jul. 2021 </line>

<line> www*.fsane*.com.br/revist* </line>

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<line> L. *. B***tte, *. A. Ar*újo, J. G. M. R*is, P. F. C. Correia </line>

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<line> consider the possibility of a di*ec* conflict between no-hu*s, t*gether with the problem of </line>

<line> de**rminin* *** c*pacit* o* the *odes of a hub w**h a multip*e netwo*k alloc*ti*n model. </line>

<line> All pos*ible allocation strate*ies, su*h a* the extension fo* each all*c*tion s*rategy, </line>

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<line> make it p*ssible </line>

<line> to model cases in which direct *onne*tion* betwe*n no-*ub nodes are </line>

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<line> *llowed, i* th*s case, testing and ev*luating the performance *f th* *roposed mod*ls </line>

<line> 2.2 Hub-and-spo*e network com**sitio* </line>

<line> Rou** systems, by t*eir natur* and geographic *cope, ar* based *n route level data, </line>

<line> relating *i**ines and a*rport* to route *truc*u*e, costs, and carrier performa*ce (***ia et al., </line>

<line> 1998). Six fact*rs shape the design o* i*tegrati*g netwo*ks, suc* a* *he *iberali*ation o* the </line>

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<line> airline i*dust**, </line>

<line> *he cent*ality of the market </line>

<line> *nd inter*ediation, the gr*und tr*n**ortation </line>

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<line> networ*s, comp*t*tion among comp*ementa*y aerial n*tworks, the growth *f transport </line>

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<line> networks, and th* characteristics </line>

<line> of aircra*t (Bowen, 2012). The *ub-and-s*oke net*ork </line>

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<line> formed in bui*ding *l*cks of th* quality approach by w*i*hting c*nnec*io* levels, such as: th* </line>

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<line> connection identi*icati*n </line>

<line> level, t*e c*nnection quality leve* and the d*stin*t*on level </line>

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<line> (*urgho*wt & W*t, 2005; Allroggen et al., 2*1*). </line>

<line> Ta*le 1 - Conge*tion *onsid*rations </line>

<line> Author Factors t*at *ffect Hub co*g*stio* </line>

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<par>

<row> (Fageda & *lo*es-F*llol, </row>

<row> (Brueckne* & Lin, 2016) </row>

<row> (Lin & Yimin, *017) </row>

<row> (Mohri et al., *018) </row>

<row> (Alkaabenh et *l., 2019) </row>

<row> Source: A*t*ors (2020). </row>

<row> 3 METHO*OLOGY </row>

</column>

<row> Airli*e ne*works, netw*rk ef**ciency and airport conge*tion. </row>

<row> Conce*trati** of fl*ghts, airlines, *ub congestion, *owntime cost, </row>

<row> hub-and-spoke networ*, downtime cost. </row>

<row> P*ice of hub congestion at the airport, investme** in i** capacity, use </row>

<row> of a simpl* hu*-*nd-sp*ke model with an emphasis on the hub airport </row>

<row> as a profit maximizer. </row>

<row> Hub *oc*t*on p*oblem, congest*o*, hub capac*ty. </row>

<row> H*b-and-Spoke design network, Conges*ion, Economy of scale and </row>

</column>

</par>

<par>

<line> For the app*ic*bility of this rese*rch, the Soci** Network *n*lysis (SNA) m*thod </line>

<line> **s used through the te*h*iques of centrality and d*nsi*y measurements with the @ </line>

<line> Uc*net/N*tdraw s*ftware (*orgatti, 2002; Borgatti et al., 2002). </line>

<line> Rev. FSA, Teresina, v. 18, n. 7, art. 6, p. 94-109, ju*. 2021 www4.fsanet.co*.br/revi*ta </line>

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<page>

<par>

<line> *cenar*o* *f t*e De*ree of Centrality and Density of t*e Net*orks of the *ain *ra*i*ian Airports </line>

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<par>

<line> We sought to e*plo*e *he *ata f**m A*AC (2019) stati*tica* *eports *ith the a*nu*l </line>

<line> data*ases in the periods of 2*0*, *007, 2015, 2018, and *ine *onths of th* COVID19 </line>

<line> pandemic period *n 2*20, *esulting in the sample *f seven ai*ports anal*zed (Belo Horizonte - </line>

<line> Confins, Bra*ília, *ampin*s, Sã* Paulo - Guarul**s, São Pau*o - Co*gonhas, Rio de J*neiro - </line>

<line> Galeão, Ri* de Janeiro - Sa*tos Dum*nt). </line>

<line> The me**odologic*l process had the fol*owin* st*g*s: (1) th* tr*atment of data by </line>

<line> e*ectron** spre*dsheet* *nd the construc*io* of t*e r*lati*nal *atr*x of numer*cal *alances and </line>

</par>

<par>

<line> y*ar, (2) the applic*ti*n of the SNA meth*d with </line>

<line> the *eneration of *h* graph </line>

</par>

<par>

<line> diag*am and (3) the simulat*ons of *he measurement *ables of the degree o* *entral*ty an* </line>

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<par>

<line> *ensity to a*sess </line>

<line> *he b*havio* of the SNA i* thi* net*ork (Hanneman, 2001; Ha*n*man & </line>

</par>

<par>

<line> *idd**, 2005; *co*t, 20*0; Wasserma* & Fau*t, 1994). </line>

<line> **ble 2 - T*e coding of a*rport *cron*m* *y the Internatio*** Civi* Aviation </line>

<line> **ganizatio*. (ICAO) </line>

</par>

<par>

<line> Airpor* </line>

<line> Local*za*ã* </line>

</par>

<par>

<line> I*t**national *irport of *rasília (Pr*sidente Juscelino Kubitsch*k) </line>

</par>

<par>

<line> **terna*io*al Airport of Belo H*rizo*te-Co*fins (Tancred* Ne*es) </line>

<line> Confins </line>

</par>

<par>

<line> Internationa* *irport of Rio de Jan*iro (Tom J*bim/Ae*oporto do *aleão) </line>

<line> Janeiro </line>

</par>

<par>

<line> Internatio**l Airport of Sã* Paul*/G**rul*o* (A**ré F*anc* **ntoro) </line>

<line> Guarulhos </line>

</par>

<par>

<line> International Air**rt of Campinas (V*racopos-Camp*nas) </line>

<line> Campi*as </line>

</par>

<par>

<line> Inter*ational Airport of Rio de *aneiro (Santo* *umont) </line>

<line> Janeiro </line>

</par>

<par>

<line> In*ernational Airport of Sã* Pau**/Congon*as (Deputado Freitas *obre) </line>

<line> São Paulo </line>

</par>

<par>

<line> Source: IC*O (2020) </line>

<line> 4 RESULT A*D DI*CUSSIO* </line>

<line> The networks of *h* *even airpor*s analyzed by the SNA m*thod in the periods of </line>

<line> 2003, 2007, 2015, 2018, and 2020 *r* of the types of c*aracterized **t*or*s and **assified as </line>

<line> distribu*ed *nd symmetrical, being from *he di*ection of no*es to th* b*directional links </line>

</par>

<par>

<line> structure* in *elational ma*ri*. I* takes int* account the f**lowin* *i*torical back*round a </line>

<line> necessary for ext*a*tin* ANAC's **atistical reports between the *ear* 2003, 2*07, 20*5, 2018, </line>

</par>

<par>

<line> Rev. FSA, Teresina PI, v. 18, n. 7, art. 6, p. 94-1*9, *ul. 2021 </line>

</par>

</page>

<page>

<par>

<line> L. R. Bonet*e, F. A. Araújo, J. *. M. Reis, P. F. C. *orreia </line>

</par>

<par>

<line> Table 3 - The historica* bac****und of th* periods rela*ed t* th* analysis of the five </line>

<line> n*twork*. </line>

<line> *ear Historical background </line>

</par>

<par>

</column>

<row> In 2**2 there *as the t**r* p*ase of the der*gulatio* plan f*r *he *r*zilian a**line industry. </row>

<row> I* 20*6 there w*s the phenomenon of "Air Black*ut". </row>

<row> I* 2014, t*e "*ol*tical Crisis in B*a*il" begins, w*ich negative** affect* the coun***'s </row>

<row> economic in*i**tor*. </row>

<row> *con*mic Recession ex*en*s from 2014 t* 2018 associat*d with the country's electi** year. </row>

<row> CO*I*-19 P*nd*mic Period </row>

</column>

</par>

<par>

<line> Source: Authors (20*0). </line>

<line> The analysis criteria of the SN* m*thod refe* to the foll*wing aspects f*r the next </line>

</par>

<par>

<line> Ou*degree (nOutdeg): O*tp*t deg*ee (origin/destination). </line>

</par>

<par>

<line> Indegr*e (*Indeg): Input degree (destination/origi*). </line>

</par>

<par>

<line> Centr*lization: It is * s**cial conditio* in *hich a* *c*or plays a *entral r*le by being </line>

<line> *onnect** to a*l *odes, which ne*d to *as* through the centra* *ode to connect, whi*h </line>

<line> can be Centrali*ation Outdeg*ee (Out-C*) or *entralizat*on In*egree (In- Ce). </line>

</par>

<par>

<line> Densi*y: S*ows whether the network has h*gh or lo* connectivity between the number </line>

<line> of existing *el*ti*nships with the possible relationships. </line>

</par>

<par>

<line> Kc*re: Possibi*ity of s**networks supported by act*rs *ho mediate the*e *onne*ti*ns. </line>

<line> Table 4 - *he 2003 *irport datab*s* </line>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

<line> Sou*ce: Autho*s (2020). </line>

</par>

<par>

<line> Rev. FSA, Teresina, v. 18, n. *, art. 6, p. 94-109, jul. 20*1 </line>

<line> ww*4.f*anet.com.br/revista </line>

</par>

</page>

<page>

<par>

<line> S*enario* of *he *eg*ee of Centrality and Density *f *he *etworks *f the Main Brazilian Ai*por*s </line>

</par>

<par>

<line> F*gure 1 - The net*or* scenari* in 2003 **ter the t*i*d phase of th* deregulation plan </line>

<line> fo* *he Brazilia* airline indus*ry in 2*02 </line>

</par>

<par>

<line> S*urce: Authors (2020). </line>

<line> The netw*r* simul*tio* revealed the f*llo*ing behavior *f the s**en a*r***ts fo* the </line>

<line> *0*3 sce*ario: SBSP airport* have 2*.50%, and SBRJ has 24.10% of nOutdeg, whereas in </line>

<line> nIn*eg SB*P h*s 24.10% and SBRJ h*s 21.20 % d*monstr*tin* th*t they are dominant </line>

</par>

<par>

<line> a*rport* in this network and </line>

<line> 2003's scenario. Taki*g into account that SBBR is an </line>

</par>

<par>

<line> in*erme**ary in the dominance of origins *nd destinations with 13.60% nOutdeg and 12.60% </line>

<line> nIndeg. T*e other four ai*ports *ave *ower **ad*s in **e analys*s scale, su*h as SBGR </line>

<line> (nOutdeg of 5.10% and nIndeg of 5.40%), SBGL (nOutdeg of 3.9*% and nIndeg of *.*0%), </line>

</par>

<par>

<line> SBK* (nOutdeg of 1.70% *nd nIndeg of 1.70%); SBCF (nOutdeg of 1.2*% and nI**eg of </line>

</par>

<par>

<line> 1.10%). On *he ce*trali**tion *egree as a basis on t*e central axi* of the network, 16.75% of </line>

<line> **garding the network Densi*y, *here i* a 95.20% de*re* of connections to the li*ks </line>

<line> of all possible interactions, d*monstrat*ng hi** network connec*ivity in 2003. </line>

<line> Table 5 - The 2007 air*ort databa*e </line>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

<line> Source: *uthors (2020). </line>

</par>

<par>

<line> www4.fsanet.com.br/rev*sta </line>

</par>

</page>

<page>

<par>

<line> *. R. Bonette, F. A. A*aújo, J. *. M. *eis, P. F. C. Correia </line>

</par>

<par>

<line> Fi*ure * - The network scenario in 2007, a*ter t*e A*r Blacko*t phenomeno*, in 2006 </line>

</par>

<par>

<line> Source: *ut*ors (*020). </line>

<line> The net*or* s*mula*ion revealed the following b*ha*ior *f the *e*en airp*rts for the </line>

<line> 2*07 scenar*o: the SBS* a*rport had 3*.*0% nOutdeg, whil* in nIndeg SBSP it ha* 31.10% </line>

<line> demon*tra**ng that it was a dominant a*rport in **is networ* a*d 2*07's sce*a*io. T*king into </line>

<line> accou*t a group of four intermediate airport* in d*minance of origins and ***tin*tion*, </line>

<line> namely SBBR (nOu*d*g o* 20.70% and nIndeg of 21.30%), SBGL (nOutdeg of 19.30% an* </line>

</par>

<par>

<line> n*ndeg of 16.60%), SBRJ (nOutdeg </line>

<line> *6.80% and nInd*g of 1*.70%), S*CF (nOutdeg of </line>

</par>

<par>

<line> 16.30% and nIn*eg of 1*.30%). Th* other tw* airpo*ts have low*r gr**es in *he anal*s*s </line>

<line> s*a*e, such *s SBG* (nOut*eg of 10.01% and nIndeg of **.60%), SBK* (n*utdeg of 3.50% </line>

<line> a*d nIndeg *f 3.50%). Regard*ng the degr*e of centralization as a ba*is in th* cen*ral axis *f </line>

</par>

<par>

<line> the n*tw*rk, there w*s 19.02% of Out-Ce a*d In-Ce 17.48%, which incr*ased *ompare* to </line>

</par>

<par>

<line> 2003's scenar*o. </line>

</par>

<par>

<line> Regarding the network D*nsity, 8*.*0% of c*nne*tions were made t* *he links of all </line>

<line> possible intera*tions, *h*wing high network conne**ivity in 2007. *owever, there was a drop </line>

<line> compared to 2003's sc*nario. </line>

<line> Tabl* * - The 2015 airpo*t d**abase </line>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

<line> Rev. F*A, Teresin*, v. 18, n. *, *rt. 6, *. 94-*09, j*l. **21 </line>

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

</par>

</page>

<page>

<par>

<line> Scenari*s of the Degre* of Cent*ality and D**sity of the Networks of the *ain B*azil*an Air*orts </line>

</par>

<par>

</par>

<par>

</par>

<par>

<line> Source: Authors (2020). </line>

<line> Figur* 3 - The 2015 net*ork sc*n*r*o a year after th* pol**ic*l crisis in 2014 </line>

</par>

<par>

<line> Source: Authors (2*20). </line>

<line> The network si*ulation reveal** the fo*lowing beha*io* of the seven ai*port* for the </line>

<line> *015 scenario. The *BS* airport had 36.*0% nOu**eg, w*ereas in *Indeg, SBS* it ha* </line>

<line> *6.10% *emonstrating t*at it was a domi**nt airport *n this network and 2015's scena*io. </line>

</par>

<par>

<line> Tak*ng *nto a*count a gro*p </line>

<line> of *ive interme*iate airpor*s in dominance </line>

<line> of o*igins an* </line>

</par>

<par>

<line> desti*at**ns, being SBRJ (nOu*de* *f 28.9*% and nIndeg of 2*.*0%), SBBR (nOutde* of </line>

</par>

<par>

<line> nIndeg </line>

<line> of 2*.80%), SBC* (nOutdeg *f 18.60% and nI*deg of 15.4*%), SBGR </line>

</par>

<par>

</par>

<par>

<line> 15.*0%). On*y one airport *as a lower grade on the analysis scale, bei*g SBK* (nOutdeg of </line>

<line> 5.10% and nIndeg of 3.2*%). </line>

<line> Reg***ing the degre* of centralization as a base in the central axis of the networ*, </line>

</par>

<par>

<line> there was 18.*0% of O*t-Ce a*d *n-C* 18.13%, </line>

<line> which inc*eased comp*red to **e 2003'* </line>

</par>

<par>

<line> scena*io. </line>

</par>

<par>

<line> Re*arding the network Densit*, the d*gree of 9*.*0% of connections to th* link* of </line>

<line> all poss*bl* interactions was dem*nstrated, sho*ing *igh n*twork connectivi*y *n 2007. This </line>

<line> value of th* netw*rk Density r*turns to leve** close to the 2003 scenario. </line>

</par>

<par>

<line> **v. FS*, Teresina P*, v. 18, *. 7, art. 6, p. 9*-109, jul. 202* </line>

<line> www4.fsanet.co*.b*/revist* </line>

</par>

</page>

<page>

<par>

<line> L. R. *onette, F. A. Araú*o, J. G. *. Re*s, *. F. C. *orreia </line>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

<line> Source: A*thors (202*). </line>

<line> Fi*ure * - *he 2018 n*twork sc**ario with Economic Recessio* and Elections </line>

</par>

<par>

<line> Sou*ce: Authors (2020). </line>

<line> The n*two*k *imulati*n revealed the following beha**o* of the *even **rports fo* the </line>

</par>

<par>

<line> 2*18 scenario. The ***P a*rport h*d 3*.70% of </line>

<line> n*utdeg, whereas, *n nIn**g, SBSP ha* </line>

</par>

<par>

<line> demonstr*tin* *hat *t *as a *ominant airport in this network a*d 20*8's *ce*ario. </line>

</par>

<par>

<line> Ta**n* *n*o account a group *f four intermedi*t* **r*o*ts in do*inance *f origins and </line>

</par>

<par>

<line> desti*ations, being *BR* (nOutdeg of 28.90% and nIndeg of 28.9*%), SBBR (nOutdeg </line>

</par>

<par>

<line> 26.70% *nd nIndeg of 26.5*%), S*CF (*Outdeg of 23.6*% </line>

<line> and nIndeg of 23.40%), *BGR </line>

</par>

<par>

<line> (nOutdeg *f 19.80% *nd nIndeg ** 20.00%). The other *w* airp*rts *ave lower d**r*es in the </line>

<line> ana*ysis scale, *uch *s *BG* (nOutdeg o* *3.90% and *Indeg of *3.9*%), SBKP (nOutdeg *f </line>

<line> Regar*ing the degree of central*zation as a *asis in the ce*tr*l axis o* the network, </line>

<line> th*re was *4.60% of *ut-*e a*d In-Ce *4.70%. A dec**ase if co*pared to the *cenarios of </line>

<line> Rev. FSA, *eresi*a, v. 18, n. *, art. *, p. 94-109, ju*. 202* www4.fsane*.com.*r/rev*s*a </line>

</par>

</page>

<page>

<par>

<line> Sc*n**io* of th* D**ree *f Central**y a*d Density of the Netw*r*s of the M**n Braz*lian A**ports </line>

</par>

<par>

<line> Concernin* the networ* Density, th* degree of 95.20% o* con**ctions to the links of </line>

<line> all possible i*te**ctions was demo*strat*ng high n*twork conne*tivity in 2018. </line>

<line> When simul**i*g Kcore in *003, 2007, 2015, *nd 2018 scenar*os, no s*bnet creation </line>

<line> was pr*venOn t*e *the* hand, a direct connectio* was *oint*d out to t*e 7 ai*por*s wit*out </line>

<line> intermediar*es in their rel*tion* of origins an* d*sti*ations. </line>

<line> 4.1 Con*ri*utions to the Pa*demic **r**d (Covid-19) </line>

<line> This subs*ction was created *ue to *he re*evance of the pandemic *erio*, in this part </line>

<line> of the rese*rch, the period of * m*nths of 202* was *pproa*hed *n contra*t to the pr*viously </line>

<line> analyzed *eriods of 2003, 2007, 2015, *nd 20*8 scenarios that *ere collected in 12 m*nths. </line>

</par>

<par>

<line> it* impac*s on the airpo*t secto*, the urge*cy of the </line>

</par>

<par>

<line> contribu*ions *akes t*e research to be a*proached in th** context, of the 202* scenario. </line>

<line> Table 8 - The 20*0 air*ort *atabase </line>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

<line> S*urce: Authors (20*0). </line>

<line> Figure 5 - The 2020\s netwo** sc*nario dur*ng a pe*iod *f 9 months of th* Covid-*9 </line>

<line> Pande*ic </line>

</par>

<par>

<line> S*urce: *uthors (2020). </line>

</par>

<par>

<line> *ev. *SA, Teresi*a P*, v. 18, n. 7, ar*. 6, p. 94-109, *ul. 202* </line>

<line> www*.fsanet.com.b*/rev*sta </line>

</par>

</page>

<page>

<par>

<line> L. *. B*nette, F. A. Araújo, J. G. M. Reis, P. F. C. Cor*eia </line>

</par>

<par>

<line> The network si*ula*ion revealed t*e following behavior of th* se*en airports for the </line>

</par>

<par>

<line> 20*0 scenario. Five air*orts divided the n*t*ork as main pl*ye*s in this scen*ri*, with </line>

</par>

<par>

<line> domin*n* ai*por*s, **me*y: SBRJ (n*utde* of 15.00% and nIndeg of 12, 00%), SBBR </line>

<line> (*Ou*deg of 12.5*% an* nIndeg of 13.20%), SBSP (***t**g of 1*.3*% and nIn*eg *f </line>

<line> 12.80%), *BCF (n*utdeg of 25.80% **d n*nd** of *0,70%), SBGR (nOut*eg of *.40% *nd </line>

<line> nIn*eg of 10.80%). In this sce*ario, ther* was no airport *ith an intermedia*e functi*n to *he </line>

<line> n*twork of origins and destinations. The *ther two airports have lower deg*ees i* t*e analysis </line>

<line> s*ale, suc* as SBK* (nOut*eg of 5.70% an* *Indeg of 20.40%) and SBGL (*Outdeg of </line>

<line> 5.30% a*d nIndeg *f 5.00%). </line>

<line> Table 9 - The net*ork performance based on the *roposed *c*n*rios </line>

</par>

<par>

<line> Scena*ios </line>

<line> D*nsity </line>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

</par>

<par>

<line> Source: Aut*ors (2020). </line>

<line> Regard*ng the d*gree of c*n**alization as a basis in th* central axis of the netw*rk, </line>

<line> the*e w*s 15.98% of Out-Ce and In-Ce 9.69%, a drop compared to the scenario* o* 2003, </line>

<line> 2007, *015, *nd 2*18. Abo*t *he *etwork *ensity, there is a degree *f 90.*0% of c**nections </line>

</par>

<par>

<line> t* the l*nks *f al* possible inte*actions, demonstra*i*g high </line>

<line> network connectivit* in 2020, </line>

</par>

<par>

</par>

<par>

<line> 5 CON**USION </line>

</par>

<par>

<line> Th* **rports of Br*síl*a (SBBR), São Pa*lo (SBSP), and Rio de Ja*eiro (SBRJ) have </line>

<line> historica*ly supported the ne*w*rk, generating its high co*nectivity. Over *he pe*iod *f the 18 </line>

</par>

<par>

<line> *ears analyzed, B*asília airport has establ**h*d *t*elf as an act*r wit* **ntin*ous </line>

</par>

<par>

<line> e*pressi*e </line>

<line> t*ese n*t*ork*. The*e is a high degree of connectivity </line>

</par>

<par>

<line> competitiveness among t** largest Brazilian passenger airports in the scenarios of *0*3, 20*7, </line>

<line> a signif*ca*t drop in the de**ee of centralit* and density of the network. In thi* case, ther* was </line>

<line> a decentralizatio* of th* d***ity flow from one ai*port (200*, 2007, 201*, and 2018 s*en*rios) </line>

<line> to f*ve ai*ports in the 202* scenario to support the *etwor*. </line>

</par>

<par>

</par>

</page>

<page>

<par>

<line> Scenarios of the D**ree of Centrality and Density of the N**wor*s of the Mai* Br**ilian Airpor*s </line>

</par>

<par>

<line> Fo* *uture research, it is inter*s**ng to expl*re non-hub *etworks, re*e*ve hub </line>

<line> networks, and international car*o hubs as part of mitigati*g the *ffects o* **nges*ion hubs and </line>

<line> for mapping and c*eatin* contingency plans for the Brazilia* airport system. </line>

<line> REFER*NCES </line>

<line> Alk**bneh, F., Diabat, A., & Elhed*li. (2019). A La*ra*gian heuristic and GRASP for the </line>

</par>

<par>

<line> hub-an*-s**ke netwo*k syste* w**h ec*nomies-of-s*ale a*d congestion. </line>

<line> Transportatio* </line>

</par>

<par>

<line> Researc* Pa** C, 1*2, 249-2*3. </line>

</par>

<par>

<line> Allroggen, F., Wittman, M. D., & Mali*a, R. (2015). How **r t*ansport *onnects the wo*ld - </line>

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<par>

<line> A ne* me*ric of air *o*nectivit* a*d *ts evoluti*n </line>

<line> between 1990 and2012. </line>

<line> **ans*ortation </line>

</par>

<par>

<line> Research Part *, 80, *84-201. 2015. </line>

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<par>

<line> completa. D*dos </line>

</par>

<par>

<line> *s*atístico**. Base </line>

<line> *e dados subd*vida por a*o 2000, </line>

<line> *018. Passageiros </line>

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<line> (Origem/Des*ino), Aero**ves (Pousos/Dec*l*gens). </line>

<line> Ball, M., Barnhart, C., N*mhauser, *., & *doni, A. (2006). Air t*ansportation: irregular </line>

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<line> operatio*s and </line>

<line> cont*ol. In: H**dbooks o* Operat*ons R*s**rch and Manageme*t, Nor*h- </line>

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<line> Borgatti, S. P. (*0*2). *etDraw. Graph Visua*izati** S*ftware. Harvard: Analytic </line>

<line> Technologies. </line>

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<line> Borgatti, </line>

<line> S. P., *verett. M.G., & F*eem*n, L. C. (2002). Ucinet *o* Win**ws *o*tware *or </line>

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<line> Social Network Analysi*. </line>

<line> Brueckner, J. K., & Lin, M. H. (2016). Conven*ent fl*ght conne*t**n* vs. *i*p*rt congestion: </line>

<line> Modeling **e \ro*ling h*b\. Intern*tional Jou*nal of I*dustr*al Organizati*n, 48, 118-142. </line>

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<line> Burghouwt, G., & Wi*, J. (2005). Te*poral *onfigurations of *uropean Airl*ne. Jou*n*l of </line>

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<line> Ai* Tra***ort Managemen*, 11(3), 185-198. </line>

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<line> B*tton, K. (2002). "*ebunking some commo* myths ab*ut airpo*t hubs. "Journal of A*r </line>

<line> Transport Management, *(3), 17*- 202. </line>

<line> Campbell, *. F. (199*). Integer p*og*am*in* formulations of discrete h*b locat*on problem*. </line>

<line> Europea* Journal of O*erational R*search, 72, 387-405. </line>

<line> Campb*ll, F. J., Stiehr, G., Er*st, A. T., & *rishnamoo*thy, M. (2003). Sol*ing hu* arc </line>

<line> l*cation pro**ems on * cluster of *orkstat*on*. *aralle* Computi*g, 29, 555-55*. </line>

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<line> Campbell, A. M., Low*, *. J., & Zhang, L. (2007). The </line>

<line> p-hu* *enter allocation </line>

<line> problem. </line>

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<line> Europ*an Jo*rnal of *peratio*al Rese*rc*, *76, 819-*21, 834. </line>

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<par>

<line> Fageda, *., & F*or*s-F**lol, R. (2017). A note on opt*ma* airline *etworks *nder </line>

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