Airlines Seat Pricing with Seat Upgrading

Li, Yihua; Mahmoudzadeh, Ahmadreza; Wang, Xiubin Bruce

doi:10.1016/j.multra.2022.100054

Cited by 3 publications

(5 citation statements)

References 33 publications

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“…Not only does this data change over time, but data limitations also render the determination of each class's capacity irrelevant. In the studies by [20] and [3], they transform the deterministic model in conventional Revenue Management into a stochastic model to model uncertainty. Based on numerical calculations, both obtain maximum revenue compared to conventional Revenue Management models like EMSR B and Littlewood.…”

Section: Quantity Decisionmentioning

confidence: 99%

“…Addressing industry challenges, RM in the airline sector aims to optimize total revenue through dynamically controllable ticket sales. At its core, RM involves managing seat allocations across different fare groups [3]. While airlines prioritize accommodating higher-fare customers, demand uncertainty prompts consideration for filling seats with lower-fare customers, aiming to mitigate opportunity costs related to unoccupied seats.…”

Section: Introductionmentioning

confidence: 99%

“…The philosophy is to sell tickets at the right time and offer appropriate fares to the right customers before departure [3].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Revenue Management Strategies in Airline Industry: A Literature Review

Manalu,

Demas Haryo Bismantoko,

Oktaviana Putri

et al. 2024

j.sist.teknik.industri.

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The airline industry has rapidly evolved, fostering intense competition among companies. This competition drives airlines to formulate strategies for revenue maximization, giving rise to Revenue Management. This literature review spans the past 13 years, examining the development of Airline Revenue Management methods. By analyzing 22 journals with at least Q2 and SINTA 2 indexing, three primary scopes emerge: Quantity Decision, Pricing Decision, and Structural Decision. Airlines predominantly employ dynamic pricing and programming to optimize revenue by adapting to ongoing changes. The development trend in Airline Revenue Management indicates a shift towards faster and more accurate processing through increased integration with simulation and algorithm programming. This paper identifies the three main scopes involved in revenue management strategies and explores the diverse approaches airlines take to optimize income. Notably, dynamic pricing and programming remain prevalent methods, adapting to changing decision variables. The evolving landscape emphasizes integration with advanced technology for efficient processing. The study utilizes numerical and case studies to exemplify the ongoing development of Airline Revenue Management methods within this dynamic industry.

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Section: Quantity Decisionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Revenue Management Strategies in Airline Industry: A Literature Review

Manalu,

Demas Haryo Bismantoko,

Oktaviana Putri

et al. 2024

j.sist.teknik.industri.

View full text Add to dashboard Cite

show abstract

“…At this point, we omit a literature survey on (free) upgrades and refer to Gönsch and Steinhardt (2015) who review the literature regarding upgrades extensively. Some papers also discuss pricing with considering upgrades in the pricing process, e.g., Li et al (2016Li et al ( , 2022. Upsells, in contrast to upgrades, are a relatively unexamined topic in revenue management.…”

Section: Fundamental Topicsmentioning

confidence: 99%

On the value of booking data for upsell decision-making in revenue management

Rauhaus,

Gönsch,

Steinhardt

2024

Flex Serv Manuf J

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In passenger aviation and many other areas of transportation, it is common practice to offer customers who have booked a ticket for a lower compartment free seats in higher compartments at a discount before departure, a practice known as upselling. For example, economy class customers are offered a seat in business class for a small surcharge a few days before take-off. Obviously, it matters to whom to offer an upsell and at what price. In this paper, we address this decision problem in a generic fashion for revenue management settings. We assume that the company has disaggregated booking data about the customer’s initial choice of a product from a provided offer set. This data contains information about individual customers’ preferences and may be leveraged to decide on upsell prices. To this end, we propose an optimization approach based on an expectation model, in which customers’ response probability is represented as a conditional probability formally consistent with their initial buying decision in a multinomial logit model. We present variants of the approach based on different levels of exploitable customer-specific booking data. In a numerical study, we investigate the value of this data usage and upselling in general to the company. Upselling in conjunction with knowledge of the customers’ original offer sets and customer segments, substantially increases revenues. Furthermore, the study demonstrates that the proposed approach can lead to larger revenue benefits than a naive benchmark approach which statistically decouples the customers’ upgrade acceptance decision from their original choice during the purchasing process.

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“…Civil aviation is a typical industry with heavy assets, high cost and low profits. Airline management consists of a variety of decision-making steps, such as fleet assignment, crew scheduling, aircraft routing, and pricing management, which affect the airline profitability [1][2][3]. Recently, governments are advocating for the green and sustainable development of the aviation industry [4,5].…”

Section: Introductionmentioning

confidence: 99%

Green Airline-Fleet Assignment with Uncertain Passenger Demand and Fuel Price

et al. 2023

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Although air transport contributes to globalization, airline emissions have attracted focus in green logistics. In this work, we investigate the airline-fleet assignment problem from a risk-averse perspective in which uncertain demand and fuel price are considered simultaneously. The objective is to maximise the total profit in a risk-averse fashion, i.e., the weighted sum of the expected profit and the conditional value at risk of profit. An appropriate assignment can reduce fuel use and carbon dioxide emissions. For the problem, a two-stage stochastic programming model is constructed. The first stage consists of assigning aircraft families to flight legs, while the second stage determines specific aircraft deployment with the realized information. To solve the problem, a sample average approximation (SAA) approach is firstly applied. An efficient string-based heuristic is, further, developed. Numerical experiments are conducted and sensitivity analysis is performed. The results show the efficiency of the proposed heuristic and managerial insights are drawn.

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Airlines Seat Pricing with Seat Upgrading

Cited by 3 publications

References 33 publications

Revenue Management Strategies in Airline Industry: A Literature Review

Revenue Management Strategies in Airline Industry: A Literature Review

On the value of booking data for upsell decision-making in revenue management

Green Airline-Fleet Assignment with Uncertain Passenger Demand and Fuel Price

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