The impact of digitalization and intelligentization on air transportation system
Abstract
This study aims to provide insights into the impact levels of digitalization and intelligentization on air transport system (ATS) in Australia, China, the US, and India. Air transport system is one of the most efficient transport systems which contains three elements: air traffic control, airport, and airlines. In modern society, the importance of digitalization and intelligentization in ATS is attached to by publics. In this study, firstly, comparative analysis is used to analyze the different states of digitalization and intelligentization level and air transport system in sample countries. Then, correlation analysis is used to study the correlation of the different impact factors with the ATS in different countries. The third one is regression analysis, it is used to analyze the relationship between ATS and the development of digitalization and intelligentization in four sample countries. At last, forecasting analysis is used to predict the future trend of digitalization and intelligentization’s impact on ATS in the sample countries in the next few years. Then, the most significant impact factors for ATS will be obtained. Also, the future development trends of ATS under digitalization and intelligentization’s impact could be forecasted by using econometric models.
Keyword : Air Transport System (ATS), digitalization, intelligentization, econometric models, digital impact, digital technology, safety
How to Cite
La, J., & Heiets, I. (2021). The impact of digitalization and intelligentization on air transportation system. Aviation, 25(3), 159-170. https://doi.org/10.3846/aviation.2021.15336
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Jones, D. R., Quach, C. C., & Young, S. D. (2001). Runway incursion prevention system-demonstration and testing at the dallas/fort worth international airport. In 20th Digital Avionics Systems Conference, 1(Autumn), 2.D.2–1–11. https://doi.org/10.1109/DASC.2001.963333
Jarach, D. (2002). The digitalisation of market relationships in the airline business: the impact and prospects of e-business. Journal of Air Transport Management, 8(2), 115–120. https://doi.org/10.1016/S0969-6997(01)00039-4
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Liu, Y., & Law, R. (2013). The adoption of smartphone applications by airlines. In Information and Communication Technologies in Tourism 2013 (pp. 47–57). Springer. https://doi.org/10.1007/978-3-642-36309-2_5
National Research Council. (1985). The Competitive status of the U.S. civil aviation manufacturing industry: a study of the influences of technology in determining international industrial competitive advantage. The National Academies Press.
Pandey, G., Chaudhary, P., Gupta, R., & Pal, S. (2020). SEIR and Regression Model based COVID-19 outbreak predictions in India. In arXiv preprint arXiv:2004.00958. Cornell University. https://doi.org/10.2196/preprints.19406
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Riedl, R., Benlian, A., Hess, T., Stelzer, D., & Sikora, H. (2017). On the relationship between information management and digitalization. Business & Information Systems Engineering, 59(6), 475–482. https://doi.org/10.1007/s12599-017-0498-9
Rajapaksha, A., & Jayasuriya, N. (2020). Smart airport: a review on future of the airport operation. Global Journal of Management and Business Research, 20(3). https://doi.org/10.34257/GJMBRAVOL20IS3PG25
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Sankaranarayanan, H. B., & Lalchandani, J. (2017). Conversational bots with workflow services architecture for smart travel systems. In International Conference on Smart Trends for Information Technology and Computer Communications (pp. 37–43). Springer. https://doi.org/10.1007/978-981-13-1423-0_5
SkaiBlu. (2018). Skaiblu 2018 Digital Airline Score (Das) Benchmark Report: An Assessment of Airline Digital Capabilities. SkaiBlu DAS Benchmark Report 2018.
Shirk, S. L. (2007). China: fragile superpower. Oxford University Press.
Tang, Y., Xiong, Y. H., Yu, W., Tian, C. Y., & Bao, Z. D. (2018). Research on the development of intelligent transportation based on smart city. In 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018). Atlantis Highlights in Intelligent Systems (AHIS), Vol. 1 (pp. 92–95). Atlantis press. https://doi.org/10.2991/caai-18.2018.22
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Vaidyanathan, G. (2008). Technology parks in a developing country: the case of India. The Journal of Technology Transfer, 33(3), 285–299. https://doi.org/10.1007/s10961-007-9041-3
Weiss, R. M., & Mehrotra, A. K. (2001). Online dynamic pricing: Efficiency, equity and the future of e-commerce. Virginia Journal of Law and Technology, 6(11), 1–10.
Wayman, J. L., Jain, A. K., Maltoni, D., & Maio, D. (Eds.). (2005). Biometric systems: Technology, design and performance evaluation. Springer Science & Business Media. https://doi.org/10.1007/b138151
World Bank. (2020). World Bank Open Data. World Bank. https://data.worldbank.org
Yin, J., Wang, D., Yang, L., Wei, H., Dong, P., Ke, L., Wang, G., Zhu, H., & Zeng, X. (2020). Correlation between forming quality and spatter dynamics in laser powder bed fusion. Additive Manufacturing, 31, 100958. https://doi.org/10.1016/j.addma.2019.100958
Zhou, J. (2013). Digitalization and intelligentization of manufacturing industry. Advances in Manufacturing, 1(1), 1–7. https://doi.org/10.1007/s40436-013-0006-5
Zhang, W., & Zhang, X. (2007). A forecast analysis on fertilizers consumption worldwide. Environmental Monitoring and Assessment, 133(1–3), 427–434. https://doi.org/10.1007/s10661-006-9597-7
Zanin, M., & Lillo, F. (2013). Modelling the air transport with complex networks: A short review. The European Physical Journal Special Topics, 215(1), 5–21. https://doi.org/10.1140/epjst/e2013-01711-9