Forthcoming

Elasticity-Driven Fare Optimization in U.S. Air Travel Segments

Authors

Keywords:

demand elasticity, market segmentation, distance-based pricing, revenue management, dynamic pricing, U.S. air travel market

Abstract

Purpose. This study investigates the variation in price elasticity of demand across U.S. domestic air travel markets, with a particular focus on how different distance-based market segments respond to airfare changes. Design / Method / Approach. The analysis presents air travel markets in the distance categories of very short, short-haul, medium-haul, and long-haul to analyze the heterogeneous nature of price responses. Findings. The results indicate substantial differences in elasticity across directions. In the short-haul markets, the negative price elasticity demonstrates strong awareness of fare increases (ε=-0.344). Conversely, long-haul markets demonstrate price elasticity in a positive direction (ε = +1.840), indicating perceptions of value-added (i.e., direct services quality or even network effects). Medium-haul distances suggest nearly neutral responses, and the very short routes produce statistically insignificant elasticity coefficients. Theoretical Implications. The research expands transportation economics and marketing analytics literature through the analytic demonstration that distance travelled does impact demand elasticity in the case of airline routes. The study provides additional evidence for segmentation theories and distance-based price models. Practical Implications. The results provide airline revenue managers with data-based evidence that depicts the opportunity to develop fare structures that align closer to consumer behaviors and may provide opportunities for enhanced profits by utilizing distance and type of flight configurations. Originality / Value. This study employs an entirely unique segmentation-based approach to enable an elasticity analysis of city-pair air travel market distances by utilizing a wealth of longitudinal data to provide evidence-based recommendations for both academics as well as practitioners. Research Limitations / Future Research. Limitations include the exclusion of international routes and ancillary pricing factors. Future research may explore dynamic pricing strategies in real-time or investigate elasticity in the context of loyalty programs and airline alliances. Article Type. Research article. 

PURL: https://purl.org/cims/4.316

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References

Abrahams, M. (1983). A service quality model of air travel demand: An empirical study. Transportation Research Part a General, 17(5), 385. https://doi.org/10.1016/0191-2607(83)90007-9

Aryal, G., Murry, C., & Williams, J. W. (2023). Price Discrimination in International Airline Markets. The Review of Economic Studies, 91(2), 641. https://doi.org/10.1093/restud/rdad037

Barnhart, C., & Cohn, A. M. (2004). Airline Schedule Planning: Accomplishments and Opportunities. Manufacturing & Service Operations Management, 6(1), 3. https://doi.org/10.1287/msom.1030.0018

Bhuvaneswaran, R., Venkatasamy, R., & Ramarajan, R. (2018). Service Quality towards Customer Satisfaction in Low Cost Airline Industries. International Journal of Management Studies (IJMS), 5(4(4), 125–129. https://researchersworld.com/index.php/ijms/article/view/2005

Bijmolt, T. H. A., Heerde, H. J. van, & Pieters, R. (2005). New Empirical Generalizations on the Determinants of Price Elasticity. Journal of Marketing Research, 42(2), 141. https://doi.org/10.1509/jmkr.42.2.141.62296

Bose, R. K., & Shukla, M. (1999). Elasticities of electricity demand in India. Energy Policy, 27(3), 137. https://doi.org/10.1016/s0301-4215(99)00011-7

Castiglioni, M., Gallego, Á., & González, J. L. G. (2017). The virtualization of the airline industry: A strategic process. Journal of Air Transport Management, 67, 134. https://doi.org/10.1016/j.jairtraman.2017.12.001

Daft, J., & Albers, S. (2013). A conceptual framework for measuring airline business model convergence. Journal of Air Transport Management, 28, 47. https://doi.org/10.1016/j.jairtraman.2012.12.010

Daramola, A., & Fagbemi, T. (2019). Air Travel and Airline Operations in Nigeria: Market Potentials and Challenges. In Aviation and Its Management - Global Challenges and Opportunities. https://doi.org/10.5772/intechopen.80646

Fan, S., & Hyndman, R. (2011). The price elasticity of electricity demand in South Australia. Energy Policy, 39(6), 3709. https://doi.org/10.1016/j.enpol.2011.03.080

Franke, M. (2007). Innovation: The winning formula to regain profitability in aviation? Journal of Air Transport Management, 13(1), 23. https://doi.org/10.1016/j.jairtraman.2006.11.003

Gillen, D. (2006). Airline Business Models and Networks: Regulation, Competition and Evolution in Aviation Markets. Review of Network Economics, 5(4). https://doi.org/10.2202/1446-9022.1103

Gössling, S. (2011). Carbon Management in Tourism: Mitigating the Impacts on Climate Change. Routledge. https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-10866

Gupta, S. (2024). Advanced AI-Driven Dynamic Pricing Models in Marketing: Real-World Applications. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4958529

Kandikanti, N., Zare, Z., & Karatas, M. (2025). Urban air mobility: Key innovations and optimization approaches. In The 2025 International Conference on the Leadership and Management of Projects in the digital age (ICLAMP2025). Wright State University.

Kaviti, S., & Venigalla, M. (2019). Assessing service and price sensitivities, and pivot elasticities of public bikeshare system users through monadic design and ordered logit regression. Transportation Research Interdisciplinary Perspectives, 1, 100015. https://doi.org/10.1016/j.trip.2019.100015

Mantin, B., & Rubin, E. (2018). Price volatility and market performance measures: The case of revenue managed goods. Transportation Research Part E Logistics and Transportation Review, 120, 35. https://doi.org/10.1016/j.tre.2018.10.005

Moreno‐Izquierdo, L., Rodríguez, A. B. R., & Perles‐Ribes, J. F. (2015). The impact of the internet on the pricing strategies of the European low-cost airlines. European Journal of Operational Research, 246(2), 651. https://doi.org/10.1016/j.ejor.2015.05.013

Morris, M. H., & Joyce, M. L. (1988). How marketers evaluate price sensitivity. Industrial Marketing Management, 17(2), 169. https://doi.org/10.1016/0019-8501(88)90019-3

Neubert, M. (2022). A Systematic Literature Review of Dynamic Pricing Strategies. International Business Research, 15(4), 1. https://doi.org/10.5539/ibr.v15n4p1

Nowak, M., & Pawłowska-Nowak, M. (2024). Dynamic Pricing Method in the E-Commerce Industry Using Machine Learning. Applied Sciences, 14(24), 11668. https://doi.org/10.3390/app142411668

Oyewole, P., & Choudhury, P. K. (2006). Purchase Situations and the Level of Importance that Consumers Attach to Services in the Airline Industry. Services Marketing Quarterly, 28(1), 19. https://doi.org/10.1300/j396v28n01_02

Park, E., Jang, Y., Kim, J., Jeong, N. J., Bae, K., & Pobil, Á. P. del. (2019). Determinants of customer satisfaction with airline services: An analysis of customer feedback big data. Journal of Retailing and Consumer Services, 51, 186. https://doi.org/10.1016/j.jretconser.2019.06.009

Pereira, F. C., Costa, J. M., Ramos, R. F., & Raimundo, A. (2023). The impact of the COVID-19 pandemic on airlines’ passenger satisfaction. Journal of Air Transport Management, 112, 102441. https://doi.org/10.1016/j.jairtraman.2023.102441

Price, I., Fowkes, J., & Hopman, D. (2017). Gaussian processes for demand unconstraining. arXiv preprint arXiv:1711.10910. https://doi.org/10.48550/arxiv.1711.10910

Qu, X., Hui, H., Yang, S., Li, Y., & Ding, Y. (2018, February). Price elasticity matrix of demand in power system considering demand response programs. In IOP Conference Series: Earth and Environmental Science (Vol. 121, No. 5, p. 052081). IOP Publishing. https://doi.org/10.1088/1755-1315/121/5/052081

Razak, F. A., Abd Ghadas, Z. A., Suhaimi, F. A., & Udin, N. M. (2021). Unfair contract terms in online contracts: special reference to online booking of flight tickets. Psychology and education, 58(2), 1618-1623. https://doi.org/10.17762/pae.v58i2.2317

Richard, D. B. (2009). The Changing Price Elasticity of Demand for Domestic Airline Travel. In 50th Annual Transportation Research Forum. https://doi.org/10.22004/ag.econ.207597

Sengpoh, L. (2015). The Competitive Pricing Behaviour of Low-Cost Airlines in the Perspective of Sun Tzu Art of War. Procedia - Social and Behavioral Sciences, 172, 741. https://doi.org/10.1016/j.sbspro.2015.01.427

Setiawan, E. B., Valdhavessa, D., Bambang, H., Marina, S., Desa, L., Bilqis, F. R., & Sidjabat, S. (2021). How to build customer loyalty: Through customer experience, perceived price, and customer satisfaction. Turkish Journal of Computer and Mathematics Education, 12(4), 1546-1554. https://doi.org/10.17762/turcomat.v12i4.1410

Siqueira, J. R., Bendixen, M., Reinoso‐Carvalho, F., & Campo, R. (2023). Key drivers of brand trust in a Latin American airline: the impact of Colombia’s Avianca customer experience. Journal of Marketing Analytics, 11(2), 186. https://doi.org/10.1057/s41270-023-00208-8

Sun, X., Zheng, C., Wandelt, S., & Zhang, A. (2024). Airline competition: A comprehensive review of recent research. Journal of the Air Transport Research Society, 2, 100013. https://doi.org/10.1016/j.jatrs.2024.100013

Toh, R. S., Kelly, M. K., & Hu, M. Y. (1986). An Approach to the Determination of Optimal Airline Fares: Some Useful Insights on Price Elasticities, Monopoly Power and Competitive Factors in the Airline Industry. Journal of Travel Research, 25(1), 26. https://doi.org/10.1177/004728758602500105

Vojdani, K., & Lloyd, J. (2022). Assessing the Impact of Technological Advancements on the Consumer Experience in Commercial Aviation. Journal of Student Research, 11(3). https://doi.org/10.47611/jsrhs.v11i3.3071

Wensveen, J. G., & Leick, R. (2009). The long-haul low-cost carrier: A unique business model. Journal of Air Transport Management, 15(3), 127. https://doi.org/10.1016/j.jairtraman.2008.11.012

Wittman, M. D. (2018). Dynamic pricing mechanisms for airline revenue management: Theory, heuristics, and implications [Doctoral Theses, Massachusetts Institute of Technology]. DSpace@MIT. https://dspace.mit.edu/handle/1721.1/122707

Zhang, Y., Lee, S.-Y., & Gu, Y. (2023). A review of air transport service quality studies: current status and future research agenda. Journal of the Air Transport Research Society, 1(1), 9. https://doi.org/10.59521/ef52bb6324bd7035

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Published

2025-06-16

How to Cite

Sifat, A. I., & Elahi, M. A. (2025). Elasticity-Driven Fare Optimization in U.S. Air Travel Segments. Challenges and Issues of Modern Science. https://cims.fti.dp.ua/j/article/view/316

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