Forecasting passenger movement for Brazilian airports network based on the segregation of primary and secondary demand applied to Brazilian civil aviation policies planning
Author
Abstract
Suggested Citation
DOI: 10.1016/j.tranpol.2019.02.003
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Hsu, Chaug-Ing & Wen, Yuh-Horng, 2000. "Application of Grey theory and multiobjective programming towards airline network design," European Journal of Operational Research, Elsevier, vol. 127(1), pages 44-68, November.
- Eric Kroes & Abigail Lierens & Marco Kouwenhoven, 2005. "The airport Network and Catchment area Competition Model - A comprehensive airport demand forecasting system using a partially observed database," ERSA conference papers ersa05p521, European Regional Science Association.
- Tsui, Wai Hong Kan & Ozer Balli, Hatice & Gilbey, Andrew & Gow, Hamish, 2014. "Forecasting of Hong Kong airport's passenger throughput," Tourism Management, Elsevier, vol. 42(C), pages 62-76.
- Xiao, Yi & Liu, John J. & Hu, Yi & Wang, Yingfeng & Lai, Kin Keung & Wang, Shouyang, 2014. "A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 1-11.
- Fernandes, Elton & Pacheco, Ricardo Rodrigues & Braga, Márcia Estrada, 2014. "Brazilian airport economics from a geographical perspective," Journal of Transport Geography, Elsevier, vol. 34(C), pages 71-77.
- Hess, Stephane & Polak, John W., 2005. "Mixed logit modelling of airport choice in multi-airport regions," Journal of Air Transport Management, Elsevier, vol. 11(2), pages 59-68.
- Jeffrey M Wooldridge, 2010.
"Econometric Analysis of Cross Section and Panel Data,"
MIT Press Books,
The MIT Press,
edition 2, volume 1, number 0262232588, April.
- Jeffrey M. Wooldridge, 2001. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262232197, April.
- J. D. Bermudez & J. V. Segura & E. Vercher, 2007. "Holt-Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1075-1090.
- Benedikt Mandel, 2014. "Contemporary Airport Demand Forecasting: Choice Models and Air Transport Forecasting," International Transport Forum Discussion Papers 2014/7, OECD Publishing.
- Abed, Seraj Y. & Ba-Fail, Abdullah O. & Jasimuddin, Sajjad M., 2001. "An econometric analysis of international air travel demand in Saudi Arabia," Journal of Air Transport Management, Elsevier, vol. 7(3), pages 143-148.
- World Bank, 2017. "World Development Indicators 2017," World Bank Publications - Books, The World Bank Group, number 26447.
- Pels, Eric & Njegovan, Nenad & Behrens, Christiaan, 2009. "Low-cost airlines and airport competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(2), pages 335-344, March.
- Grosche, Tobias & Rothlauf, Franz & Heinzl, Armin, 2007. "Gravity models for airline passenger volume estimation," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 175-183.
- Samagaio, António & Wolters, Mark, 2010. "Comparative analysis of government forecasts for the Lisbon Airport," Journal of Air Transport Management, Elsevier, vol. 16(4), pages 213-217.
- Pels, Eric & Nijkamp, Peter & Rietveld, Piet, 2000. "Airport and Airline Competition for Passengers Departing from a Large Metropolitan Area," Journal of Urban Economics, Elsevier, vol. 48(1), pages 29-45, July.
- Lian, Jon Inge & Rønnevik, Joachim, 2011. "Airport competition – Regional airports losing ground to main airports," Journal of Transport Geography, Elsevier, vol. 19(1), pages 85-92.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Jin, Feng & Li, Yongwu & Sun, Shaolong & Li, Hongtao, 2020. "Forecasting air passenger demand with a new hybrid ensemble approach," Journal of Air Transport Management, Elsevier, vol. 83(C).
- Sun, Shaolong & Lu, Hongxu & Tsui, Kwok-Leung & Wang, Shouyang, 2019. "Nonlinear vector auto-regression neural network for forecasting air passenger flow," Journal of Air Transport Management, Elsevier, vol. 78(C), pages 54-62.
- Tascón, Diana C. & DÃaz Olariaga, Oscar, 2021. "Air traffic forecast and its impact on runway capacity. A System Dynamics approach," Journal of Air Transport Management, Elsevier, vol. 90(C).
- Xiao, Yi & Liu, John J. & Hu, Yi & Wang, Yingfeng & Lai, Kin Keung & Wang, Shouyang, 2014. "A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 1-11.
- Nieto, MarÃa Rosa & Carmona-BenÃtez, Rafael Bernardo, 2018. "ARIMA + GARCH + Bootstrap forecasting method applied to the airline industry," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 1-8.
- Wang, Sen & Gao, Yi, 2021. "A literature review and citation analyses of air travel demand studies published between 2010 and 2020," Journal of Air Transport Management, Elsevier, vol. 97(C).
- Mohammadian, Iman & Abareshi, Ahmad & Abbasi, Babak & Goh, Mark, 2019. "Airline capacity decisions under supply-demand equilibrium of Australia’s domestic aviation market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 108-121.
- Teixeira, Filipe Marques & Derudder, Ben, 2021. "Spatio-temporal dynamics in airport catchment areas: The case of the New York Multi Airport Region," Journal of Transport Geography, Elsevier, vol. 90(C).
- Hopfe, David H. & Lee, Kiljae & Yu, Chunyan, 2024. "Short-term forecasting airport passenger flow during periods of volatility: Comparative investigation of time series vs. neural network models," Journal of Air Transport Management, Elsevier, vol. 115(C).
- Sismanidou, Athina & Tarradellas, Joan & Bel, Germà & Fageda, Xavier, 2013. "Estimating potential long-haul air passenger traffic in national networks containing two or more dominant cities," Journal of Transport Geography, Elsevier, vol. 26(C), pages 108-116.
- Morimoto, Yu, 2020. "Do citizens of a city that owns a local public airport have attachment to the airport and use it?," MPRA Paper 103442, University Library of Munich, Germany.
- Yang, Chih-Wen & Lu, Jin-Long & Hsu, Chun-Yen, 2014. "Modeling joint airport and route choice behavior for international and metropolitan airports," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 89-95.
- Ari, Didem & Mizrak Ozfirat, Pinar, 2024. "Comparison of artificial neural networks and regression analysis for airway passenger estimation," Journal of Air Transport Management, Elsevier, vol. 115(C).
- Christidis, Panayotis, 2016. "Four shades of Open Skies: European Union and four main external partners," Journal of Transport Geography, Elsevier, vol. 50(C), pages 105-114.
- Cheung, Tommy King-Yin & Wong, Wai-hung & Zhang, Anming & Wu, Yangming, 2020. "Spatial panel model for examining airport relationships within multi-airport regions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 148-163.
- Lieshout, Rogier, 2012. "Measuring the size of an airport’s catchment area," Journal of Transport Geography, Elsevier, vol. 25(C), pages 27-34.
- Dey Tirtha, Sudipta & Bhowmik, Tanmoy & Eluru, Naveen, 2022. "An airport level framework for examining the impact of COVID-19 on airline demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 169-181.
- de Luca, Stefano, 2012. "Modelling airport choice behaviour for direct flights, connecting flights and different travel plans," Journal of Transport Geography, Elsevier, vol. 22(C), pages 148-163.
- Escobari, Diego, 2017.
"Airport, airline and departure time choice and substitution patterns: An empirical analysis,"
Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 198-210.
- Escobari, Diego, 2017. "Airport, airline and departure time choice and substitution patterns: An empirical analysis," MPRA Paper 79857, University Library of Munich, Germany.
- Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
More about this item
Keywords
Passenger movement forecast; Primary demand; Secondary demand; Gravitational model;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:trapol:v:77:y:2019:i:c:p:23-29. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.