Industrial Innovations

Industrial Innovations

Maximizing Airline Revenue through Uncertain Dynamic Pricing: Integrating Carbon Tax and Green Tickets within the Liu Theory Framework

Document Type : Original Article

Authors
Maryam Almasi
Mehri Bagherian
Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
10.61882/jii.3.4.18
Abstract
Environmental and policy pressures have forced airlines to reconsider their traditional pricing strategies. This study proposes a dynamic pricing model for airline tickets in an uncertain environment, where demand uncertainty, inflation, seasonal fluctuations, and carbon costs are considered simultaneously. The proposed framework is developed based on Liu’s uncertainty theory and incorporates carbon cost into the objective function as an uncertain parameter derived from expert judgment. The objective of the model is to maximize the expected revenue of the airline while considering environmental sustainability requirements. The results of a case study for a domestic airline show that including carbon costs can significantly change the optimal price structure, redistribute demand between flight classes, and create a balance between economic profitability and environmental responsibility. The model also provides a practical tool for designing sustainable pricing policies in situations where historical data are limited.
Keywords
Liu&rsquo
s Uncertainty Theory
Carbon Tax
Pricing
[1] Doganis R. Flying off course: The economics of international airlines. London: Routledge; 2013. 
[2] International Air Transport Association. IATA review. Montreal: IATA; 2019.
[3] Talluri KV. The theory and practice of revenue management. Vol. 1. Boston: Kluwer Academic Publishers; 2004. 
[4] Maglaras C. Dynamic pricing strategies for multiproduct revenue management problems. Manuf Serv Oper Manag. 2006;8:136–148. 
[5] Kavacık MZ. Sustainable development in aviation industry and the case of Turkish Airlines. In: Proceedings of the 3rd International Symposium on Sustainable Development; 2012; Sarajevo, Bosnia and Herzegovina.
[6] Almasi M, Bagerian M. Airline pricing: an uncertain programming approach. OPSEARCH. 2025;62(1):123–145. doi:10.1007/s12597-025-00998-8..
[7] Littlewood K. Forecasting and control of passenger bookings. The Airline Group of the International Federation of Operational Research Societies. 1972;12:95–117.
 [8] Smith BC, Leimkuhler JF, Darrow RM. Yield management at American Airlines. Vol. 1. 1992. 
[9] Weatherford LA. A taxonomy and research overview of perishable-asset revenue management: yield management, overbooking, and pricing. Oper Res. 1992;40(5):831–844. doi:10.1287/opre.40.5.831.
[10] Yao K. Uncertain regression analysis: an approach for imprecise observations. Soft Comput. 2018;22:5579–5582. doi:10.1007/s00500-017-2521-y. 
[11] Yu JC. A novel fuzzy multi-objective programming model for airline dynamic seat. J Comput Appl Math. 2017;312:71–84. 
[12] Zhang Y. The impacts of pro-environmental values and knowledge on aviation voluntary carbon offsetting: a Mainland China study. J China Tour Res. 2022;18(3):495–509. doi:10.1080/19388160.2020.1868368. 
[13] Raghavan S. Metrics for sustainable aviation finance. J Int Finance Econ. 2023;23(1):129–141. doi:10.18374/JIFE-23-1.9. 
[14] Koç E. Green marketing strategies and climate change awareness in sustainable transportation: the case of airline companies. Mar Sci Technol Bull. 2023;12(4):459–472. doi:10.33714/masteb.1375842. 
[15] Kyrylenko OM. Intellectualization of logistics and supply chain management. Intellect Logist Supply Chain Manag. 2023;20:38–45. doi:10.46783/smart-scm/2023-20-4.
 [16] Cui Q. The online pricing strategy of low-cost carriers when carbon tax and competition are considered. Transp Res Part A Policy Pract. 2019;121:420–432. doi:10.1016/j.tra.2019.02.002. 
[17] Grimme W. Measuring the long-term sustainability of air transport – an assessment of the global airline fleet and its CO2-emissions up to the year 2050. Cologne: German Aerospace Center (DLR), Air Transport and Airport Research; 2024. 
[18] Fahimi B. Customer willingness to pay for carbon offsetting in aviation: a theory of planned behavior approach. Padua: University of Padua, Department of Economics and Business; 2025.
[19] International Air Transport Association. Access to SAF Europe brief [Internet]. Montreal: IATA; 2025 [cited 2026 Feb 25]. Available from: https://www.iata.org/en/programs/sustainability/reports/access-to-saf-europe-brief/
[20] Liu B. Uncertainty theory. In: Uncertainty Theory. Berlin: Springer; 2007. 
[21] Liu B. Some research problems in uncertainty theory. J Uncertain Syst. 2009;3(1):3–10. 
[22] Liu B. Theory and practice of uncertain programming. Vol. 239. Berlin: Springer; 2009.
[23] Wang XS, G Z. Delphi method for estimating uncertainty distributions. Inf: An Int Interdiscip J. 2012;15(2):449–460.
 [24] Liu B. Uncertainty Theory. Berlin: Springer; 2015. doi:10.1007/978-3-662-44354-5.
Industrial Innovations
Volume 3, Issue 4 - Serial Number 12
in press
Autumn 2025
Pages 18-36

  • Receive Date 06 January 2026
  • Revise Date 18 February 2026
  • Accept Date 22 February 2026