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Forecasting of Hong Kong airport's passenger throughput

Citations

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Cited by:

  1. Chen, Jieh-Haur & Wei, Hsi-Hsien & Chen, Chih-Lin & Wei, Hsin-Yi & Chen, Yi-Ping & Ye, Zhongnan, 2020. "A practical approach to determining critical macroeconomic factors in air-traffic volume based on K-means clustering and decision-tree classification," Journal of Air Transport Management, Elsevier, vol. 82(C).
  2. 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.
  3. Tsui, Wai Hong Kan & Fung, Michael Ka Yiu, 2016. "Causality between business travel and trade volumes: Empirical evidence from Hong Kong," Tourism Management, Elsevier, vol. 52(C), pages 395-404.
  4. 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).
  5. Jiao, Xiaoying & Chen, Jason Li & Li, Gang, 2021. "Forecasting tourism demand: Developing a general nesting spatiotemporal model," Annals of Tourism Research, Elsevier, vol. 90(C).
  6. Xu, Shuojiang & Chan, Hing Kai & Zhang, Tiantian, 2019. "Forecasting the demand of the aviation industry using hybrid time series SARIMA-SVR approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 169-180.
  7. Tuğba Dayioglu & Serdar Alnipak, 2023. "Dynamic effecting factors of air travel demand: an econometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3713-3727, August.
  8. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," IREA Working Papers 201805, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
  9. Elisa Jorge-González & Enrique González-Dávila & Raquel Martín-Rivero & Domingo Lorenzo-Díaz, 2020. "Univariate and multivariate forecasting of tourism demand using state-space models," Tourism Economics, , vol. 26(4), pages 598-621, June.
  10. Jun, Wang & Yuyan, Luo & Lingyu, Tang & Peng, Ge, 2018. "Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 136-147.
  11. de Paula, R.O. & Silva, L.R. & Vilela, M.L. & Cruz, R.O.M., 2019. "Forecasting passenger movement for Brazilian airports network based on the segregation of primary and secondary demand applied to Brazilian civil aviation policies planning," Transport Policy, Elsevier, vol. 77(C), pages 23-29.
  12. 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).
  13. Tascón, Diana C. & Díaz 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).
  14. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
  15. Gudmundsson, S.V. & Cattaneo, M. & Redondi, R., 2021. "Forecasting temporal world recovery in air transport markets in the presence of large economic shocks: The case of COVID-19," Journal of Air Transport Management, Elsevier, vol. 91(C).
  16. Aydın, Umut & Ülengin, Burç, 2022. "Analyzing air cargo flows of Turkish domestic routes: A comparative analysis of gravity models," Journal of Air Transport Management, Elsevier, vol. 102(C).
  17. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
  18. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
  19. Ioannis Sitzimis, 2021. "An Optimal Forecasting Method of Passenger Traffic in Greek Coastal Shipping," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 14(3), pages 72-87, December.
  20. 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.
  21. Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
  22. Wai Hong Kan Tsui & Faruk Balli, 2017. "International arrivals forecasting for Australian airports and the impact of tourism marketing expenditure," Tourism Economics, , vol. 23(2), pages 403-428, March.
  23. Wang, Zhanwei & Song, Woon-Kyung, 2020. "Sustainable airport development with performance evaluation forecasts: A case study of 12 Asian airports," Journal of Air Transport Management, Elsevier, vol. 89(C).
  24. Hu, Yi-Chung, 2023. "Air passenger flow forecasting using nonadditive forecast combination with grey prediction," Journal of Air Transport Management, Elsevier, vol. 112(C).
  25. Mingming Hu & Haiyan Song, 2020. "Data source combination for tourism demand forecasting," Tourism Economics, , vol. 26(7), pages 1248-1265, November.
  26. Fanyu Meng & Wenwu Gong & Jun Liang & Xian Li & Yiping Zeng & Lili Yang, 2021. "Impact of different control policies for COVID-19 outbreak on the air transportation industry: A comparison between China, the U.S. and Singapore," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-19, March.
  27. Balli, Hatice Ozer & Tsui, Wai Hong Kan & Balli, Faruk, 2019. "Modelling the volatility of international visitor arrivals to New Zealand," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 204-214.
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