A Simulation Study of General Aviation Cargo Policy in China: A System Dynamics Perspective
DOI:
https://doi.org/10.71222/2g71ce08Keywords:
general aviation cargo, system elements, system dynamics, policyAbstract
Currently, addressing the imbalances in the development of domestic general air freight and public aviation freight formats, as well as the imperfections in policies, regulations, and sys-tems, is crucial. This study employs system dynamics theory as its research method to con-struct a dynamic model of China's general aviation freight system. By examining the supply side, demand side, and the general aviation freight industry chain, the study illustrates the feedback relationships within general aviation freight and establishes an indicator system. Using Ven sim PLE software, the research creates causal relationship diagrams of the main subsystems and an overall system flow diagram. The model is quantitatively specified through historical and sensitivity testing. The findings indicate that varying levels of financial in-vestment and tax preferential policies significantly enhance the economic benefits of navigation and freight in China. Additionally, increased investment in scientific research funding is expected to advance the technical level of navigation operations. Therefore, it is recommended to boost investment in general air freight, implement preferential tax policies for air-craft manufacturing enterprises, navigation operating enterprises, and infrastructure support units, increase investment in R&D for the general cargo transport industry, and focus on the training and incentivization of navigation professionals.
References
1. F. Kupfer, H. Meersman, E. Onghena, et al., "The underlying drivers and future development of air cargo," J. Air Transp. Manag., vol. 61, no. 6, pp. 6–14, 2016, doi: 10.1016/j.jairtraman.2016.07.002.
2. H.-C. Chu, "An exploration of adjusted flight operations affecting passenger load factors in the post-pandemic recovery," Res. Transp. Bus. Manag., vol. 55, p. 101144, 2024, doi: 10.1016/j.rtbm.2024.101144.
3. W. Wang, et al., "Green investing in China's air cargo industry: Opportunities and challenges for sustainable transportation," Heliyon, vol. 9, no. 8, 2023, doi: 10.1016/j.heliyon.2023.e19013.
4. Q. Gong, et al., "International trade drivers and freight network analysis—The case of the Chinese air cargo sector," J. Transp. Geogr., vol. 71, pp. 253–262, 2018, doi: 10.1016/j.jtrangeo.2017.02.009.
5. W. Wang, et al., "Green investing in China's air cargo industry: Opportunities and challenges for sustainable transportation," Heliyon, vol. 9, no. 8, 2023, doi: 10.1016/j.heliyon.2023.e19013.
6. K. Yamaguchi, "International trade and air cargo: Analysis of US export and air transport policy," Transp. Res. E Logist. Transp. Rev., vol. 44, no. 4, pp. 653–663, 2007, doi: 10.1016/j.tre.2007.05.006.
7. Y.-C. Hu, et al., "Improving the sustainable competitiveness of service quality within air cargo terminals," Sustainability, vol. 10, no. 7, p. 2319, 2018, doi: 10.3390/su10072319.
8. S. Domingues, et al., "An assessment of the regulation of air cargo security in Europe: A Belgian case study," J. Air Transp. Manag., vol. 34, pp. 131–139, 2014, doi: 10.1016/j.jairtraman.2013.10.001.
9. S. Liang, et al., "International freight forwarding services network in the Yangtze River Delta, 2005–2015: patterns and mech-anisms," China Geogr. Sci., vol. 29, pp. 112-126, 2019, doi: 10.1007/s11769-019-1018-2.
10. N. Wang, M. Wu, and K. F. Yuen, "Modelling and assessing long-term urban transportation system resilience based on system dynamics," Sustainable Cities Soc., vol. 109, p. 105548, 2024, doi: 10.1016/j.scs.2024.105548.
11. D. Rees, J. Stephenson, D. Hopkins, et al., "Exploring stability and change in transport systems: Combining Delphi and system dynamics approaches," Transp., vol. 44, no. 4, pp. 789–805, 2017, doi: 10.1007/s11116-016-9716-7.
12. D. I. Vega and S. Bautista-Rodriguez, "The impact of circular economy strategies on municipal waste management: A system dynamics approach," Cleaner Eng. Technol., vol. 21, p. 100761, 2024, doi: 10.1016/j.clet.2024.100761
13. V. Gavra and E.-J. van Kampen, "Evolutionary reinforcement learning: Hybrid approach for safety-informed fault-tolerant flight control," J. Guid. Control Dyn., vol. 47, no. 5, pp. 887-900, 2024, doi: 10.2514/1.G008112.
14. X. Sun et al., "A review on research regarding HSR interactions with air transport and outlook for future research challenges," Transport Policy, 2024, doi: 10.1016/j.tranpol.2024.08.008.
15. A. Ghadge, et al., "Impact of additive manufacturing on aircraft supply chain performance: A system dynamics approach," J. Manuf. Technol. Manag., vol. 29, no. 5, pp. 846–865, 2018, doi: 10.1108/JMTM-07-2017-0143.
16. B. Pratap, et al., "Factors affecting the market dynamics of lithium-ion battery for electric mobility: A system dynamics per-spective," J. Simul., vol. 3, pp. 428–445, 2024, doi: 10.1080/17477778.2022.2150578.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Qing Liu, Daling Wang (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
