Airport competition in Brazil’s northeast region
DOI:
https://doi.org/10.33448/rsd-v11i2.13454Keywords:
Airport; Choice; Passenger; Binomial logit.Abstract
Aviation growth is mainly due to the integration between national and world economies in the global era. The capital’s airports of the Brazilian Northeast were managed by a federal public company and are currently being granted to private companies, which have the premise of expanding the number of passengers. The increase in number of passengers drives competition between airports, since they must have adequate infrastructure to contain the demand. The choice by the user for an airport can be evaluated based on factors such as access mode, air fares, availability of flights and airport infrastructure. This paper aims at evaluating the choice of passengers between two airports in the Northeast of Brazil since 2014 and how this choice has been changing over the years. The binomial logit model was used to obtain the probability of choosing between airports and to evaluate the most relevant factors. The results of the study presented that availability for direct flights, preference for airlines, access time, air fares and general satisfaction of the airport fluctuated in the choice of the two airports during the study period. By evaluating the likelihood of choice, subsidies are provided to improve services considered indispensable by passengers.
References
Aena Brasil (2020). Characteristic of the airport. Website do Aerorporto Internacional de Recife - Guararapes - Gylberto Freire. https://www.aenabrasil.com.br/pt/aeroportos/aeroporto-internacional-do-recife-guararapes-gilberto-freyre/index.html.
ANAC (2019a). Historical and operational data of the airports. Website of Agência Nacional de Aviação Civil (ANAC). https://www.anac.gov.br/assuntos/paginas-tematicas/concessoes
ANAC (2019b). Air fares. Website of Agência Nacional de Aviação Civil (ANAC). https://www.anac.gov.br/assuntos/paginas-tematicas/concessoes.
Ashford, N. & Benchemam, M. (1987). Passengers’ Choice of Airport: an Application of the Multinomial Logit Model. Transp. Res. Rec., 1–5.
Bao, D., Hua, S. & Gu, J. (2016). Relevance of airport accessibility and airport competition. J. Air Transp. Manag., (55), 52–60.
Ben-Akiva, M. E. & Lerman, S. R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press.
Bettini, H.F.A.J. & Oliveira, A.V.M. (2016). Two-sided platforms in airport privatization. Transp. Res. Part E Logist. Transp. Rev., (93), 262–278.
Cheung, T.K.Y., Wong, W. hung, Zhang, A. & Wu, Y. (2020). Spatial panel model for examining airport relationships within multi-airport regions. Transp. Res. Part A Policy Pract., (133), pp. 148–163.
De Luca, S. (2012). Modelling airport choice behaviour for direct flights, connecting flights and different travel plans. J. Transp. Geogr., (22), 148–163.
EPL (2015). Relatório o Brasil que voa. www.aviacao.gov.br/obrasilquevoa.
Gatwick Airport (2010). Two-sided platforms and airports. https://www.gatwickairport.com/globalassets/publicationfiles/business_and_community/reg ulation/competition/doc29-galtwo-sidedplatformspaper.pdf.
Great Circle Mapper (2020). Global map. http://www.gcmap.com/mapui?DU=mi.
Gretl (2019). GNU Regression, econometric and time-series library (Gretl), Cottrell, A., Lucchetti, R. http://gretl.sourceforge.net/.
Harvey, G. (1987). Airport choice in a multiple airport region. Transp. Res. Part A Gen., (21), 439–449.
Hess, S. & Polak, J.W. (2005). Mixed logit modelling of airport choice in multi-airport regions. J. Air Transp. Manag., (11), 59–68.
ICAO (2018). Aviation trends. International Civil Organization. https://www.icao.int/annual-report-2018/Documents/Annual.Report.2018_Air%20Tr ansport%20Statistics.pdf.
Inframerica (2020). Historical data of NAT. https://www.natal.aero/br/.
Jarach, D. (2001). The evolution of airport management practices: towards a multi-point, multi-service, marketing-driven firm. Journal of Air Transport Management, (7), 119–125.
Jimenez, E. (2014). Airport strategic planning in the context of low-cost carriers ascendency: insights from the European experience. Doctoral Program in Transportation Systems, MIT Portugal Program.
Jimenez, E., Claro, J. & Sousa, J.P. (2014). The Airport Business in a Competitive Environment. Procedia - Soc. Behav. Sci., (111), 947–954.
Kalakou, S. & Macário, R. (2013). An innovative framework for the study and structure of airport business models. Case Stud. Transp. Policy, (1), 2–17.
Lieshout, R. (2012). Measuring the size of an airport’s catchment area. J. Transp. Geogr., (25), 27–34.
Loo, B. P. Y. (2008). Passengers’ airport choice within multi-airport regions (MARs): some insights from a stated preference survey at Hong Kong International Airport. J. Transp. Geogr., (16), 117–125.
Louviere, J. J., Hensher, D. A. & Swait, J. D. (2000). Stated choice methods. Cambridge University Press.
Medeiros, A. (2007). Turismo de eventos como estratégia no combate à sazonalidade: uma análise na hotelaria de Natal-RN. Master Program – Universidade Federal do Rio Grande do Norte.
Muñoz, C., Cordoba, J. & Sarmiento, I. (2017). Airport choice model in multiple airport regions. J. Airl. Airpt. Manag., (7), 1.
Murça, M. C. R. & Correia, A. R. (2013). Análise da modelagem da escolha aeroportuária em regiões de múltiplos aeroportos. Journal of Transport Literature, (4), pp. 130-146.
Negri, N.A.R., Borille, G.M.R. & Falcão, V.A. (2019). Acceptance of biometric technology in airport check-in. J. Air Transp. Manag., (81).
Pagliari, R. & Graham, A. (2019). Airport competition within the Scottish lowlands region. Res. Transp. Econ.
Paliska, D., Drobne, S., Borruso, G., Gardina, M. & Fabjan, D. (2016). Passengers’ airport choice and airports’ catchment area analysis in cross-border Upper Adriatic multi-airport region. J. Air Transp. Manag., (57), 143–154.
PAN (2019). Plano Aeroviário Nacional. https://infraestrutura.gov.br/conteudo/52-sistema-de-transportes/8110-plano-aeroviario-nacional.html.
Pels, E., Nijkamp, P. & Rietveld, P. (2001). Airport and airline choice in a multiple airport region: An emphirical analysis for the San Francisco bay area. Reg. Stud., (35), pp. 1–9.
Pereira, A.S., Shitsuka, D.M., Parreira, F.J. & Shitsuka, R. (2018). Metodologia da pesquisa científica. UFSM. https://repositorio.ufsm.br/bitstream/handle/1/15824/Lic_Computacao_Metodologia-Pesquisa-Cientifica.pdf?sequence=1.
Prentice, C. & Kadan, M. (2019). The role of airport service quality in airport and destination choice. J. Retail. Consum. Serv., (47), 40–48.
SAC (2020). Historical data. Secretaria de Aviação Civil. Website Hórus. Ministério dos Transportes, Portos e Aviação Civil. https://horus.labtrans.ufsc.br/gerencial/#Movimentacao/Ranking.
SIROS (2020). Historial data. Consulta de voos planejados – SIROS. https://sas.anac.gov.br/sas/siros/(S(vlc2bsso5ftnrtjohiv 2l3if))/view/registro/frmConsultaVoos.
Skinner, R. E. Jr. (1976). Airport choice: an empirical study. Transp. Engrg. J., ASCE, 102(4), 871-882.
Train, K. E. (2003). Discrete choice methods with simulation. Cambridge University Press.
Tretheway, M. & Kincaid, I. (2005). Competition between airports in the new Millennium: what works, what doesn’t work and why. 8th Hambg. Aviat. Conf., 1–18.
Website Hórus (2019a). Historical data. https://horus.labtrans.ufsc.br/gerencial/.
Website Hórus (2019b). Historical data. https://horus.labtrans.ufsc.br/gerencial/#DesempenhoOperacional/DadosCompletos.
Windle, R. & Dresner, M. (1995). Airport choice in multiple-airport regions. J. Transp. Eng., (121), 332–337.
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