Abstract

The study is aimed at analysing how social and economic development indicators, global and regional economic indices are influencing low-cost carriers (LCC), AirAsia Group Berhad (AAGB) in particular. It is crucial not only to define the impact-factors, but to embed them in management framework for further decision-making. Passenger traffic is the main indicator of LCC performance, unlike the Full-Service Network Carriers (FNSC) that taking advantages on both passengers and freights. However, both categories depend on the macroenvironment and business environment dynamics, and KPIs should be reconsidered to face the current global challenges. The global GDP, GDP per capita are commonly used to access the economic and social development trends, the passenger numbers per annum, unemployment rate and else are used to understand the status of operations in LLC performance management. This study deals with several overlapped categories of research, such as low-cost carriers business model, impact-factors of air transport development, global trends in several industries. The research methodology is combination of comparative analysis, correlation analysis, regression analysis and forecasting, using secondary data from annual reports and quaternary financial reports. The comparative analysis gave us the understanding of the general performance trend of the group and subsidiaries. One of the study components is the correlation analysis that revealed the most correlated factors for the economic development of AAGB, such as global GDP, regional GDP, regional GDP per capita, population growth. The global and regional dimensions were presented in the research to reveal what affects the airline performance the most. Global GDP is the most correlated indicator for the global and regional development within AAGB, and the regional GDP per capita comes the second by its significance. The population size has a great influence on performance indicators (globally and regionally), and if this indicator is taken into account for forecasting the potential growth is expected in the next five years. These findings enable to design the business-model of LLC more accurate in accordance to the forecast analysis towards innovative costs decisions. 

Keywords: business model, management, KPI, performance management, Low-Cost Carrier, airline, AirAsia group, passenger traffic.

JEL Classification: D2, Q33, M31.

Cite as: Wu, C.-Y., Heiets, I., & Shvindina, H. (2020). Business model management of low-cost carriers: in a search for the impact-factors of performance (case of Airasia group Airlines). Marketing and Management of Innovations, 2, 354-367. https://doi.org/10.21272/mmi.2020.2-26

This work is licensed under a Creative Commons Attribution 4.0 International License

References

1. Abed, S. Y., Ba-Fail, A. O., & Jasimuddin, S. M. (2001). An econometric analysis of international air travel demand in Saudi Arabia. Journal of air transport management, 7(3), 143-148. [Google Scholar] [CrossRef]
2. Ahmad, K., & Khan, M. M. (2011). A comparative analysis of productivity of airline industry: Evidence from selected Asian airlines. International Journal of Business and Social Science, 2(15), 224-230. [Google Scholar]
3. Ahmad, R., & Neal, M. (2006). AirAsia: The Sky’s the Limit. Asian Journal of Management Cases, 3(1), 25-50. [Google Scholar] [CrossRef]
4. AirAsia. (2011). Annual report 2010. Retrieved from https://ir.airasia.com/misc/ar2010.pdf
5. AirAsia. (2012). Annual report 2011. Retrieved from https://ir.airasia.com/misc/ar2011.pdf
6. AirAsia. (2013). Annual report 2012. Retrieved from https://ir.airasia.com/misc/ar2012.pdf
7. AirAsia. (2014). Annual report 2013. Retrieved from https://ir.airasia.com/misc/ar2013.pdf
8. AirAsia. (2015). Annual report 2014. Retrieved from https://ir.airasia.com/misc/ar2014.pdf
9. AirAsia. (2016). Annual report 2015. Retrieved from https://ir.airasia.com/misc/ar2015.pdf
10. AirAsia. (2017). Annual report 2016. Retrieved from https://ir.airasia.com/misc/ar2016.pdf
11. AirAsia. (2018). Annual report 2017. Retrieved from https://ir.airasia.com/misc/ar2017.pdf
12. Albers, S., Baum, H., Auerbach, S., & Delfmann, W. (Eds.). (2017). Strategic management in the aviation industry. Taylor & Francis. [Google Scholar]
13. Alekseev, K. P. G., & Seixas, J. M. (2002, November). Forecasting the air transport demand for passengers with neural modelling. In VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings. (pp. 86-91). IEEE. [Google Scholar] [CrossRef]
14. Asuero, A. G., Sayago, A., & Gonzalez, A. G. (2006). The correlation coefficient: An overview. Critical reviews in analytical chemistry, 36(1), 41-59. [Google Scholar] [CrossRef]
15. Benítez, R. B. C., Paredes, R. B. C., Lodewijks, G., & Nabais, J. L. (2013). Damp trend Grey Model forecasting method for airline industry. Expert Systems with Applications, 40(12), 4915-4921. [Google Scholar] [CrossRef]
16. Bishara, A. J., & Hittner, J. B. (2012). Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches. Psychological methods, 17(3), 399. [Google Scholar] [CrossRef]
17. Carmona Benitez, R. B., & Lodewijks, G. (2008). Literature review of the passenger airline business models: Full service carrier, low-cost carrier and charter airlines. In 10th TRAIL Congress: TRAIL in Perspective. Transport, Infrastructure and Logistics (TRAIL). [Google Scholar]
18. Chi, J., & Baek, J. (2013). Dynamic relationship between air transport demand and economic growth in the United States: A new look. Transport Policy, 29, 257-260. [Google Scholar] [CrossRef]
19. Chin, A. T., & Tay, J. H. (2001). Developments in air transport: implications on investment decisions, profitability and survival of Asian airlines. Journal of Air Transport Management, 7(5), 319-330. [Google Scholar] [CrossRef]
20. Daft, J., & Albers, S. (2012). A profitability analysis of low-cost long-haul flight operations. Journal of Air Transport Management, 19, 49-54. [Google Scholar] [CrossRef]
21. Daft, J., & Albers, S. (2013). A conceptual framework for measuring airline business model convergence. Journal of Air Transport Management, 28, 47-54. [Google Scholar] [CrossRef]
22. de Wit, J. G., & Zuidberg, J. (2012). The growth limits of the low cost carrier model. Journal of Air Transport Management, 21, 17-23. [Google Scholar] [CrossRef]
23. Demydyuk, G. (2011). Choosing financial key performance indicators: the airline industry case. In Winter Global Conference on Business and Finance (GCBF) (p. 2). [Google Scholar]
24. Dobruszkes, F. (2006). An analysis of European low-cost airlines and their networks. Journal of Transport Geography, 14(4), 249-264. [Google Scholar] [CrossRef]
25. Fageda, X., Suau-Sanchez, P., & Mason, K. J. (2015). The evolving low-cost business model: Network implications of fare bundling and connecting flights in Europe. Journal of Air Transport Management, 42, 289-296. [Google Scholar] [CrossRef]
26. Fedosova, A. (2016). Comparison between Low-cost and Traditional Airlines. Case study: easyJet and British Airways. [Google Scholar]
27. Fehrm, B. (2018). Is Long-Haul LCC viable?. Leeham News and Analysis, March 28. Retrieved from https://leehamnews.com/2018/03/28/is-long-haul-lcc-viable/
28. Ghobbar, A. A., & Friend, C. H. (2003). Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model. Computers & Operations Research, 30(14), 2097-2114. [Google Scholar] [CrossRef]
29. Goossens, Y., Mäkipää, A., Schepelmann, P., Van de Sand, I., Kuhndt, M., & Herrndorf, M. (2007). Alternative progress indicators to Gross Domestic Product (GDP) as a means towards sustainable development. Beyond GDP, 305. [Google Scholar]
30. Henriksen, L. F., & Ponte, S. (2018). Public orchestration, social networks, and transnational environmental governance: Lessons from the aviation industry. Regulation & governance, 12(1), 23-45. [Google Scholar] [CrossRef]
31. https://www.iata.org/publications/economics/Pages/index.aspx/
32. 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. [Google Scholar] [CrossRef]
33. IATA Economics. (2018). Air cargo improved in May, but a full recovery will take time. Retrieved from 
34. IATA. (2017). Economic performance of the airline industry.  Retrieved from https://www.iata.org/en/iata-repository/publications/economic-reports/airline-industry-economic-performance—2017-mid-year—report/
35. ICAO. (2006). Manuel on Air Traffic Forecasting. Retrieved from https://www.icao.int/MID/Documents/2014/Aviation%20Data%20Analyses%20Seminar/8991_Forecasting_en.pdf
36. Ismail, N. A., & Jenatabadi, H. S. (2014). The influence of firm age on the relationships of airline performance, economic situation and internal operation. Transportation Research Part A: Policy and Practice, 67, 212-224. [Google Scholar] [CrossRef]
37. Jenatabadi, H. S., & Ismail, N. A. (2007). The determination of load factors in the airline industry. International Review of Business Research Papers, 3(4), 125-133. [Google Scholar]
38. Jiang, H. (2013). Service quality of low-cost long-haul airlines–The case of Jetstar Airways and AirAsia X. Journal of Air Transport Management, 26, 20-24. [Google Scholar] [CrossRef]
39. Jifri, M. H., Hassan, E. E., & Miswan, N. H. (2017, October). Forecasting performance of time series and regression in modeling electricity load demand. In 2017 7th IEEE International Conference on System Engineering and Technology (ICSET) (pp. 12-16). IEEE. [Google Scholar] [CrossRef]
40. Jones, D. (2002). Cutting costs in Asia. Air finance Journal, 38(250), 31-33.
41. Khakpour, A. (2013). Methodology of comparative studies in education. Contemporary Educational Researches Journal, 2(1), 20-26. [Google Scholar]
42. Kua, J., & Baum, T. (2004). Perspectives on the development of low-cost airlines in South-east Asia. Current Issues in Tourism, 7(3), 262-276. [Google Scholar] [CrossRef]
43. Lawton, T. C., & Solomko, S. (2005). When being the lowest cost is not enough: Building a successful low-fare airline business model in Asia. Journal of Air Transport Management, 11(6), 355-362. [Google Scholar] [CrossRef]
44. Lin, C. K. E. (2010). Low cost carrier-airport relationship development in Southeast Asia (Doctoral dissertation, The Hong Kong Polytechnic University). [Google Scholar]
45. Liu, A. M., Yi, S., & Yuan, S. S. (2018, April). The Developing Model of Aviation Economy to Support the Destination as a Hub City. In 2018 International Conference on Education Reform and Management Science (ERMS 2018). Atlantis Press. [Google Scholar] [CrossRef]
46. Malighetti, P., Paleari, S., & Redondi, R. (2009). Pricing strategies of low-cost airlines: The Ryanair case study. Journal of Air Transport Management, 15(4), 195-203. [Google Scholar] [CroosRef]
47. Marazzo, M., Scherre, R., & Fernandes, E. (2010). Air transport demand and economic growth in Brazil: A time series analysis. Transportation Research Part E: Logistics and Transportation Review, 46(2), 261-269. [Google Scholar] [CrossRef]
48. Mehmood, B., Shahid, A., & Ilyas, S. (2015). Co-integration analysis of aviation demand and economic growth in Philippines. International Journal of Economics and Empirical Research (IJEER), 3(6), 271-277. [Google Scholar]
49. Mukaka, M. M. (2012). A guide to appropriate use of correlation coefficient in medical research. Malawi medical journal, 24(3), 69-71. [Google Scholar]
50. Nam, K., & Schaefer, T. (1995). Forecasting international airline passenger traffic using neural networks. The Logistics and Transportation Review, 31(3), 239-252. [Google Scholar]
51. OECD. (2019) Economic Outlook for Southeast Asia, China and India; Towards Smart Urban Transportation. Retrieved from https://www.oecd-ilibrary.org/development/economic-outlook-for-southeast-asia-china-and-india-2019_saeo-2019-en
52. Oum, T. H., & Yu, C. (1995). A productivity comparison of the world’s major airlines. Journal of Air Transport Management, 2(3-4), 181-195. [Google Scholar] [CrossRef]
53. Pender, L., & Baum, T. (2000). Have the frills really left the European airline industry?. International Journal of Tourism Research, 2(6), 423-436. [Google Scholar] [CrossRef]
54. Pereira, B. A., & Caetano, M. (2015). A conceptual business model framework applied to air transport. Journal of Air Transport Management, 44, 70-76. [Google Scholar] [CrossRef]
55. Pereira, B. A., & Caetano, M. (2017). Business model innovation in airlines. International Journal of Innovation: IJI Journal, 5(2), 184-198. [Google Scholar] [CrossRef]
56. Profillidis, V., & Botzoris, G. (2015). Air passenger transport and economic activity. Journal of Air Transport Management, 49, 23-27. [Google Scholar] [CrossRef]
57. Pulina, M., & Cortés-Jiménez, I. (2010). Have low-cost carriers influenced tourism demand and supply? The case of Alghero, Italy. Tourism Analysis, 15(6), 617-635. [Google Scholar] [CrossRef]
58. Puth, M. T., Neuhäuser, M., & Ruxton, G. D. (2014). Effective use of Pearson’s product–moment correlation coefficient. Animal behaviour, 93, 183-189. [Google Scholar] [CrossRef]
59. Rahman, K., Azad, S., & Mostari, S. (2015). A Competitive Analysis of the Airline Industry: A Case Study on Biman Bangladesh Airlines. IOSR Journal of Business and Management, 17(4), 23-33.
60. Rengaraju, V. R., & Arasan, V. T. (1992). Modeling for air travel demand. Journal of Transportation Engineering, 118(3), 371-380. [Google Scholar]
61. Ricart, J. E., & Wang, D. (2005). Now everyone can fly: Air Asia. Asian Journal of Management Cases, 2(2), 231-255. [Google Scholar] [CrossRef]
62. Sengur, Y., & Sengur, F. K. (2017). Airlines define their business models: a content analysis. World Review of Intermodal Transportation Research, 6(2), 141-154. [CrossRef] [CrossRef]
63. Shuk-Ching Poon, T., & Waring, P. (2010). The lowest of low-cost carriers: the case of AirAsia. The International Journal of Human Resource Management, 21(2), 197-213. [Google Scholar][CrossRef]
64. Soyk, C., Ringbeck, J., & Spinler, S. (2018). Revenue characteristics of long-haul low cost carriers (LCCs) and differences to full-service network carriers (FSNCs). Transportation Research Part E: Logistics and Transportation Review, 112, 47-65. [Google Scholar] [CrossRef]
65. Srisaeng, P., Baxter, G. S., & Wild, G. (2014). The evolution of low cost carriers in Australia. Aviation, 18(4), 203-216. [Google Scholar] [CrossRef]
66. Srisaeng, P., Baxter, G. S., & Wild, G. (2015). Forecasting demand for low cost carriers in Australia using an artificial neural network approach. Aviation, 19(2), 90-103. [Google Scholar] [CrossRef]
67. Taylor, R. (1990). Interpretation of the correlation coefficient: a basic review. Journal of diagnostic medical sonography, 6(1), 35-39. [Google Scholar] [CrossRef]
68. Thomas, G. (2002). Asia’s absent revolution: no-frills airlines are flourishing across north america and europe but not in ASIA. ATW: Air Transport World. [Google Scholar]
69. Turner, J. R., & Thayer, J. (2001). Introduction to analysis of variance: design, analyis & interpretation. Sage Publications. [Google Scholar]
70. Wang, J., Bonilla, D., & Banister, D. (2016). Air deregulation in China and its impact on airline competition 1994–2012. Journal of Transport Geography, 50(C), 12-23. [Google Scholar] [CrossRef]
71. Wang, K., Zhang, A., & Zhang, Y. (2018). Key determinants of airline pricing and air travel demand in China and India: Policy, ownership, and LCC competition. Transport Policy, 63, 80-89. [Google Scholar] [CrossRef]
72. Wensveen, J. G., & Leick, R. (2009). The long-haul low-cost carrier: A unique business model. Journal of Air Transport Management, 15(3), 127-133. [Google Scholar] [CrossRef]
73. Williams, A. (2016). Contemporary Issues Shaping China’s Civil Aviation Policy: Balancing International with Domestic Priorities. Routledge. [Google Scholar]
74. World Bank Data. (2018). Global indicators world. Retrieved from https://data.worldbank.org/indicator/NY.GDP.MKTP.CD/
75. Xiao, C., Ye, J., Esteves, R. M., & Rong, C. (2016). Using Spearman’s correlation coefficients for exploratory data analysis on big dataset. Concurrency and Computation: Practice and Experience, 28(14), 3866-3878. [Google Scholar] [CrossRef]
76. Yadav, M., & Dhingra, T. (2018). Recent developments in’low cost carrier’research: a review. International Journal of Business Excellence, 16(4), 427-453. [Google Scholar] [CrossRef]
77. Yeung, S., Tsang, N., & Lee, Z. (2012). An importance–performance analysis of low cost carriers in asia. International journal of hospitality & tourism administration, 13(3), 173-194. [Google Scholar][CrossRef]
78. Zhang, A., Hanaoka, S., Inamura, H., & Ishikura, T. (2017). Low-cost carriers in Asia: Deregulation, regional liberalization and secondary airports. In Low Cost Carriers (pp. 55-69). Routledge.