Pricing strategy of airline

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The complexity of price policy in the airline industry is a phenomenon that distinguishes this market from other forms of industries. A typical industry dynamic capacity pricing solution (or yield management) is a mechanism that allows companies to adapt ticket prices in response to increases in demand. This method is also used for restaurants, cruise lines, and car dealerships. They are all competitors in markets that share characteristics such as heterogeneous consumers, volatile demand, and little modifiable capability.

The essence of airline price policy and yield management, in general, is to strike a balance between two possibilities: to accept a booking request right now (lower price) or to refuse it and wait for tomorrow customer (higher price). In particular, for airline industry a yield management practice includes grouping of seats in special booking classes with attached fare combined with individual restrictions (valid travel days, stay restrictions, ticket refunding, and advance purchase restrictions) and then managing of two parameters – fares for classes and number of seats in each class. The procedure is supported by well-developed software and usually process automatically, however, in some outstanding moments like peak demand or dangerous rivals’ activities it may be handed to human professional for temporary management (alderighi).

Application of this method is important, as it allows number of companies stay on the market working with a minimal margin, and at the same time still to have profits and cover expenses in a long-term period. Only such strategy can provide long-term balance in the situation of unpredictable demand to limited supply, otherwise airline industry participants would be forced to take high risks of losses due to partial filling of their flights. For airline companies’ consumers it is also a profitable practice as they can save money by planning their regular trips, others with urgent and unpredictable need in flight still can get that good by higher price. Lack of yield management would lead to less supply and variance in opportunities for customers, worse conditions for them, less competition in industry, and finally higher risks and inconvenience for both sides. As an example of airline’s pricing strategy application for low-cost carriers in the Appendix A is shown price reduction across booking days.

Analysis

Next, I will provide a formal analysis of pricing strategy (yield management) in airline industry from the macroeconomic viewpoint. I include in the analysis identifying some aspects of the exchange process, factors affecting market outcomes in the time perspective, the welfare implications of the exchange outcome.

Main characteristics of airline industry market are limited capacity (planed in advance), limited length of time for good offering, uncertain aggregate demand, unpredictable mix of demand for business and leisure clients (bilotckach). Main agents on the airline market are airlines and passengers; however, professional associations (IATA) and government play an important role in first two agents’ behavior regulation.

The practice of yield management that carriers use has a goal of maximization of profits and load therefore it is providing the equilibrium on this market – predictable supply meets unpredictable demand by dynamically balancing price for particular sits. There are two main strategies of yield management – systematic and stochastic. By the first method is possible to predict accurately the high and low demand periods while with stochastic yield management is possible to operate in conditions of a priori unknown demand conditions.

In economy theory that methodology got representation in capacity-based and time-based theories of airline pricing. First ones focus on the relationship between the evolution of fares and a flight’s occupancy rate, it suppose that airline companies define that relationship in the beginning of the planning period and does not change it or change dynamically. In both cases the function describing and predicting fares is a non-strictly increasing function of the remaining capacity within the planning period (alderighi). Time-based theories in their turn focus on time factor, they suppose that industry players use inter-temporal price discrimination and that way affect heterogeneity of customers. Parameters for discrimination in this case are uncertainty about departure time and willingness-to-pay. Strategies available based on time factor are advance-purchase discount and clearance sale practices that have opposite profile in time – price is growing with time or it is declining (alderighi).

In the USA and other developed countries an airline industry development on its early stage (about first 60 years) been shaped mostly by government policy, market forces played minor role in those period. Market-based aviation industry starts in the USA since the Airline Deregulation Act of 1978 (nber).

the welfare implications

Conclusion

Significance of findings, limitations for models

Works Cited

Abdelghany, Ahmed, and Khaled Abdelghany. Modeling applications in the airline industry. Routledge, 2016.

Alderighi, Marco, Marcella Nicolini, and Claudio A. Piga. "Combined effects of capacity and time on fares: insights from the yield management of a low-cost airline." Review of Economics and Statistics 97.4 (2015): 900-915.

Bilotkach, Volodymyr, Alberto A. Gaggero, and Claudio A. Piga. "Airline pricing under different market conditions: Evidence from European Low-Cost Carriers." Tourism Management 47 (2015): 152-163.

Borenstein, Severin, and Nancy L. Rose. "How airline markets work… or do they? Regulatory reform in the airline industry." Economic Regulation and Its Reform: What Have We Learned?. University of Chicago Press, 2014. 63-135.

Homsombat, Winai, Zheng Lei, and Xiaowen Fu. "Competitive effects of the airlines-within-airlines strategy–Pricing and route entry patterns." Transportation Research Part E: Logistics and Transportation Review 63 (2014): 1-16.

Appendix A. Price reduction across companies and booking days (bilotkach)

November 09, 2022
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