Analysis of modern scientific approaches to calculating the number of passengers on air transport




passenger flow, air transport, modelling, passenger transport systems


The article reveals the state of modern scientific opinion on the issue of calculating the number of passengers on air transport. The research is of a review nature, the task of which is to define and evaluate methods for solving transport problems. To achieve the task, scientific publications included in the Scopus scientometrics database were used. Relevant scientific approaches to determining the parameters of passenger flow on air transport are studied in the section of the selection and use of methods for calculating the relevant parameters. The author's opinion on the issue of justification of the choice of the method used by the authors and the assessment of the adequacy of the methods proposed by the authors are highlighted. In the work, the method of system analysis was used in solving the task of conducting a study of the state of modern scientific opinion on the selection of methods for calculating passenger traffic on the aviation mode of transport.


Chi, J., & Baek, J. (2012). A dynamic demand analysis of the united states air-passenger service. Transportation Research Part E: Logistics and Transportation Review, 48(4), 755-761. doi:10.1016/j.tre.2011.12.005

Cooper, M. R., Boltwood, C. E., & Wherry, R. J. (1974). A factor analysis of air passenger reactions to skyjacking and airport security measures as related to personal characteristics and alternatives to flying. Journal of Applied Psychology, 59(3), 365-368. doi:10.1037/h0036609

Cheng, S., Mu, Q., Zhang, H., & Zhang, Y. (2014). A fuzzy decision tree model for airport terminal departure passenger traffic forecasting. Paper presented at the CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems - Proceedings of the 14th COTA International Conference of Transportation Professionals, 11-17. doi:10.1061/9780784413623.002

Xiong, H., Fan, C., Chen, H., Yang, Y., ANTWI, C. O., & Fan, X. (2022). A novel approach to air passenger index prediction: Based on mutual information principle and support vector regression blended model. SAGE Open, 12(1) doi:10.1177/21582440211071102

Wang, Y., Wang, J. -., Dang, Y. -., & Wang, Z. -. (2011). A prediction model of china's air passenger demand. Paper presented at the Proceedings of 2011 IEEE International Conference on Grey Systems and Intelligent Services, GSIS'11 - Joint with the 15th WOSC International Congress on Cybernetics and Systems, 347-350. doi:10.1109/GSIS.2011.6044120

Huang, F., Xiong, X., Peng, J., Guo, B., & Tong, B. (2018). RCA: A route city attraction model for air passengers. Physica A: Statistical Mechanics and its Applications, 491, 887-897. doi:10.1016/j.physa.2017.08.081

Ahmad Shafie, N. E., Mohamed Kamar, H., & Kamsah, N. (2015). A CFD simulation of PM1 and CO air contaminants in a bus passenger compartment. Jurnal Teknologi, 77(30), 35-39. doi:10.11113/jt.v77.6863

Álvarez-Albelo, C. D., Hernández-Martín, R., & Padrón-Fumero, N. (2017). Air passenger duties as strategic tourism taxation. Tourism Management, 60, 442-453. doi:10.1016/j.tourman.2016.12.002

Seetaram, N., Song, H., & Page, S. J. (2014). Air passenger duty and outbound tourism demand from the united kingdom. Journal of Travel Research, 53(4), 476-487. doi:10.1177/0047287513500389

Erjongmanee, S., & Kongsamutr, N. (2018). Air passenger estimation using gravity model and learning approaches: Case study of thailand. Paper presented at the ICAICTA 2018 - 5th International Conference on Advanced Informatics: Concepts Theory and Applications, 36-41. doi:10.1109/ICAICTA.2018.8541335

Li Long, C., Guleria, Y., & Alam, S. (2021). Air passenger forecasting using neural granger causal google trend queries. Journal of Air Transport Management, 95 doi:10.1016/j.jairtraman.2021.102083

Xiong, H. -., Zhu, R. -., Ji, H., Fan, C. -., & Xu, P. (2021). Air passenger index prediction method based on MI-SVR mode. [基于MI-SVR模型的航空旅客出行指数预测方法研究] Kongzhi Yu Juece/Control and Decision, 36(7), 1619-1626. doi:10.13195/j.kzyjc.2019.1446

Chang, Y. -., & Liao, M. -. (2008). Air passenger perceptions on exit row seating and flight safety education. Safety Science, 46(10), 1459-1468. doi:10.1016/j.ssci.2007.11.006

Özcan, I. Ç. (2013). Air passenger traffic and local employment: Evidence from turkey. European Journal of Transport and Infrastructure Research, 13(4), 336-356. doi:10.18757/ejtir.2013.13.4.3008

Profillidis, V., & Botzoris, G. (2015). Air passenger transport and economic activity. Journal of Air Transport Management, 49, 23-27. doi:10.1016/j.jairtraman.2015.07.002

Van de Vijver, E., Derudder, B., & Witlox, F. (2016). Air passenger transport and regional development: Cause and effect in europe. Promet - Traffic - Traffico, 28(2), 143-154. doi:10.7307/ptt.v28i2.1756

Wang, J., Liu, X., & Ding, J. (2019). Air passenger travel forecasting model based on both dynamical individual behavior and social influence force. Journal of Algorithms and Computational Technology, 13 doi:10.1177/1748302619881392

Lee, C. -., Wang, S. W., Hsu, M. K., & Jan, S. -. (2018). Air passenger's perception toward pre-flight safety briefing videos: Does it matter? Journal of Air Transport Management, 72, 20-31. doi:10.1016/j.jairtraman.2018.07.004

Majid, M. A. A., Pardi, F., Amer, A., Kamdari, N. A. M., & Selamat, S. M. (2019). Air passengers vertex curve theorem - evidence from asean countries. Asian Economic and Financial Review, 9(3), 329-338. doi:10.18488/journal.aefr.2019.93.329.338

Zhang, Y., & Findlay, C. (2014). Air transport policy and its impacts on passenger traffic and tourist flows. Journal of Air Transport Management, 34, 42-48. doi:10.1016/j.jairtraman.2013.07.010

Wei, W., & Hansen, M. (2006). An aggregate demand model for air passenger traffic in the hub-and-spoke network. Transportation Research Part A: Policy and Practice, 40(10), 841-851. doi:10.1016/j.tra.2005.12.012

Van De Vijver, E., Derudder, B., & Witlox, F. (2014). An assessment of the causal relationship between air passenger traffic and trade in asia-pacific doi:10.1108/S2212-160920140000004008

Liang, X., Qiao, H., Wang, S., & Zhang, X. (2017). An integrated forecasting model for air passenger traffic in china based on singular spectrum analysis. Xitong Gongcheng Lilun Yu Shijian/System Engineering Theory and Practice, 37(6), 1479-1488. doi:10.12011/1000-6788(2017)06-1479-10

Bacena, A. L. B., Bihasa, A. M. B., Cadayong, L. J. A., Romulo, P. M. A., & De Guzman, A. B. (2020). An intergenerational investigation of air passengers’ emotions during tarmac delay. Anatolia, 31(1), 19-30. doi:10.1080/13032917.2019.1684960

Tsui, W. H. K., & Fung, M. K. Y. (2016). Analysing passenger network changes: The case of hong kong. Journal of Air Transport Management, 50, 1-11. doi:10.1016/j.jairtraman.2015.09.001

Blinova, T. O. (2007). Analysis of possibility of using neural network to forecast passenger traffic flows in russia. Aviation, 11(1), 28-34. doi:10.1080/16487788.2007.9635952

Kalakou, S., & Moura, F. (2021). Analyzing passenger behavior in airport terminals based on activity preferences. Journal of Air Transport Management, 96 doi:10.1016/j.jairtraman.2021.102110

Hoyos, D. T., & Olariaga, O. D. (2020). Behavior of air passenger demand in a liberalized market. Transport and Telecommunication, 21(1), 1-14. doi:10.2478/ttj-2020-0001

Carmona-Benítez, R. B., & Nieto-Delfín, M. R. (2015). Bootstrap estimation intervals using bias corrected accelerated method to forecast air passenger demand doi:10.1007/978-3-319-24264-4_22

Iyer, K. C., & Jain, S. (2020). Breakeven passenger traffic for regional indian airports. Paper presented at the Transportation Research Procedia, , 48 1805-1814. doi:10.1016/j.trpro.2020.08.215

Qiu, R., Xu, J., & Zeng, Z. (2017). Carbon emission allowance allocation with a mixed mechanism in air passenger transport. Journal of Environmental Management, 200, 204-216. doi:10.1016/j.jenvman.2017.05.036

Xu, J., Qiu, R., & Lv, C. (2016). Carbon emission allowance allocation with cap and trade mechanism in air passenger transport. Journal of Cleaner Production, 131, 308-320. doi:10.1016/j.jclepro.2016.05.029

Qiu, R., Xu, J., Xie, H., Zeng, Z., & Lv, C. (2020). Carbon tax incentive policy towards air passenger transport carbon emissions reduction. Transportation Research Part D: Transport and Environment, 85 doi:10.1016/j.trd.2020.102441

Wang, J. E., & Jin, F. J. (2007). China's air passenger transport: An analysis of recent trends. Eurasian Geography and Economics, 48(4), 469-480. doi:10.2747/1538-7216.48.4.469

Meng, J., & Yang, Z. (2006). Civil aviation passenger traffic volume forecasting based on fuzzy diagonal regression neural networks. Paper presented at the IMACS Multiconference on "Computational Engineering in Systems Applications", CESA, 1771-1775. doi:10.1109/CESA.2006.313600

Dang, Y. -., & Li, W. -. (2011). Comparative analysis on weighted network structure of air passenger flow of china and US. Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 11(3), 156-162. doi:10.1016/s1570-6672(10)60127-4

Carmona-Benítez, R. B., & Nieto, M. R. (2017). Comparison of bootstrap estimation intervals to forecast arithmetic mean and median air passenger demand. Journal of Applied Statistics, 44(7), 1211-1224. doi:10.1080/02664763.2016.1201794

Shirai Reyna, O. S., & De La Mota, I. F. (2020). Complex networks of the air passenger traffic in monterreýs airport. Paper presented at the Transportation Research Procedia, , 48 23-31. doi:10.1016/j.trpro.2020.08.003

Drake, S. (2020). Delays, cancellations and compensation: Why are air passengers still finding it difficult to enforce their EU rights under regulation 261/2004? Maastricht Journal of European and Comparative Law, 27(2), 230-249. doi:10.1177/1023263X20904235

Leandro, F., Andrade, A. R., & Kalakou, S. (2021). Designing aviation networks under public service obligations (PSO): A case study in greece. Journal of Air Transport Management, 93 doi:10.1016/j.jairtraman.2021.102042

Kovynyov, I., & Mikut, R. (2019). Digital technologies in airport ground operations. NETNOMICS: Economic Research and Electronic Networking, doi:10.1007/s11066-019-09132-5

Zhou, H., Xia, J., Norman, R., Hughes, B., Nikolova, G., Kelobonye, K., . . . Falkmer, T. (2019). Do air passengers behave differently to other regional travellers?: A travel mode choice model investigation. Journal of Air Transport Management, 79 doi:10.1016/j.jairtraman.2019.101682

Hu, Y., Xiao, J., Deng, Y., Xiao, Y., & Wang, S. (2015). Domestic air passenger traffic and economic growth in china: Evidence from heterogeneous panel models. Journal of Air Transport Management, 42, 95-100. doi:10.1016/j.jairtraman.2014.09.003

Amaliah, B., Zeinita, A., & Suryani, E. (2017). Dynamics simulation of air passenger forecasting and passenger terminal capacity expansion scenario in yogyakarta airport. Paper presented at the Proceedings of 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016, 187-192. doi:10.1109/ICTS.2016.7910296

Shafie, N. E. A., Kamar, H. M., & Kamsah, N. (2016). Effects of air supply diffusers and air return grilles layout on contaminants concentration in bus passenger compartment. International Journal of Automotive Technology, 17(5), 751-762. doi:10.1007/s12239-016-0074-1

Ahmad Shafie, N. E., Mohamed Kamar, H., & Kamsah, N. (2015). Effects of ventilation setups on air flow velocity and temperature fields in bus passenger compartment. Jurnal Teknologi, 77(30), 49-53. doi:10.11113/jt.v77.6867

Suresh, S., Balachandran, T. G., & Sendilvelan, S. (2017). Empirical investigation of airline service quality and passenger satisfaction in india. International Journal of Performability Engineering, 13(2), 109-118.

Santos, C. (2014). Enhancing the decision making process through relevant legal information in consumer law disputes - A case study in air transport passenger rights. Paper presented at the CEUR Workshop Proceedings, , 1296

Chiang, W. -. (2011). Establishment and application of fuzzy decision rules: An empirical case of the air passenger market in taiwan. International Journal of Tourism Research, 13(5), 447-456. doi:10.1002/jtr.819

Iacus, S. M., Natale, F., Santamaria, C., Spyratos, S., & Vespe, M. (2020). Estimating and projecting air passenger traffic during the COVID-19 coronavirus outbreak and its socio-economic impact. Safety Science, 129 doi:10.1016/j.ssci.2020.104791

Seetaram, N., Song, H., Ye, S., & Page, S. (2018). Estimating willingness to pay air passenger duty. Annals of Tourism Research, 72, 85-97. doi:10.1016/j.annals.2018.07.001

Lv, Z. (2014). Evaluation the quality of air passenger services doi:10.4028/

Van De Vijver, E., Derudder, B., & Witlox, F. (2014). Exploring causality in trade and air passenger travel relationships: The case of asia-pacific, 1980-2010. Journal of Transport Geography, 34, 142-150. doi:10.1016/j.jtrangeo.2013.12.001

Lyu, Z., Zhu, Y., Li, J., Xu, Y., Li, Z., & Wang, X. (2020). Exploring spatiooral characteristics of air passenger flow in the beijing-tianjin-hebei region based on ticket data. Paper presented at the Proceedings of 2020 IEEE 2nd International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2020, 925-930. doi:10.1109/ICCASIT50869.2020.9368855

Lin, X. -., Chiang, C. -., Shih, T. -., Jiang, Y. -., & Chou, C. -. (2009). Foot-and-mouth disease entrance assessment model through air passenger violations. Risk Analysis, 29(4), 601-611. doi:10.1111/j.1539-6924.2008.01183.x

Do, Q. H., Lo, S. -., Chen, J. -., Le, C. -., & Anh, L. H. (2020). Forecasting air passenger demand: A comparison of LSTM and SARIMA. Journal of Computer Science, 16(7), 1063-1084. doi:10.3844/JCSSP.2020.1063.1084

Jin, F., Li, Y., Sun, S., & Li, H. (2020). Forecasting air passenger demand with a new hybrid ensemble approach. Journal of Air Transport Management, 83 doi:10.1016/j.jairtraman.2019.101744

Cakir, V., & Oguz, S. (2018). Forecasting air passenger demand with system dynamics under terrorism threat. Paper presented at the Proceedings of the International Conference on Industrial Engineering and Operations Management, , 2018(JUL) 2676-2677.

Gunter, U., & Zekan, B. (2021). Forecasting air passenger numbers with a GVAR model. Annals of Tourism Research, 89 doi:10.1016/j.annals.2021.103252

Wu, X., Xiang, Y., Mao, G., Du, M., Yang, X., & Zhou, X. (2021). Forecasting air passenger traffic flow based on the two-phase learning model. Journal of Supercomputing, 77(5), 4221-4243. doi:10.1007/s11227-020-03428-2

Tsui, W. H. K., Ozer Balli, H., Gilbey, A., & Gow, H. (2014). Forecasting of hong kong airport's passenger throughput. Tourism Management, 42, 62-76. doi:10.1016/j.tourman.2013.10.008

Kim, S., & Shin, D. H. (2016). Forecasting short-term air passenger demand using big data from search engine queries. Automation in Construction, 70, 98-108. doi:10.1016/j.autcon.2016.06.009

Nourzadeh, F., Ebrahimnejad, S., Khalili-Damghani, K., & Hafezalkotob, A. (2020). Forecasting the international air passengers of iran using an artificial neural network. International Journal of Industrial and Systems Engineering, 34(4), 562-581. doi:10.1504/IJISE.2020.106089

Janic, M. (2003). High-speed rail and air passenger transport: A comparison of the operational environmental performance. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 217(4), 259-269. doi:10.1243/095440903322712865

Sulistyowati, R., Suhartono, Kuswanto, H., Setiawan, & Astuti, E. T. (2018). Hybrid forecasting model to predict air passenger and cargo in indonesia. Paper presented at the 2018 International Conference on Information and Communications Technology, ICOIACT 2018, , 2018-January 442-447. doi:10.1109/ICOIACT.2018.8350816

Hsu, C. -., & Wen, Y. -. (1998). Improved grey prediction models for the trans-pacific air passenger market. Transportation Planning and Technology, 22(2), 87-107. doi:10.1080/03081069808717622

Chen, S. -., Kuo, S. -., Chang, K. -., & Wang, Y. -. (2012). Improving the forecasting accuracy of air passenger and air cargo demand: The application of back-propagation neural networks. Transportation Planning and Technology, 35(3), 373-392. doi:10.1080/03081060.2012.673272



How to Cite

Dolia, O. (2022). Analysis of modern scientific approaches to calculating the number of passengers on air transport. International Science Journal of Engineering & Agriculture, 1(3), 247–272.



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