Personalization in airline revenue management – Heuristics for real-time adjustment of availability and fares

Wittman, Michael D.; Belobaba, Peter

doi:10.1057/s41272-016-0002-z

Cited by 21 publications

(10 citation statements)

References 21 publications

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“…Since the late 1980s, various aspects of RM, from the development of optimization and overbooking solutions for the RM problem, to the study of consumer reaction to RM practices and performance metrics, have been studied predominantly in the context of traditional RM applications (see, e.g., Baker & Collier, 1999; Dolasinski et al, 2019; Kimes, 1994; Lindenmeier & Tscheulin, 2008; Pekgün et al, 2013; Wittman & Belobaba, 2017). While researchers have advocated for the application of RM in nontraditional tourism settings, the potential impact of the unique characteristics associated with these nontraditional settings on RM practice and performance has been underresearched.…”

Section: Discussionmentioning

confidence: 99%

“…Prior research in the domain of RM has been dominated by a focus on traditional RM applications (i.e., airlines, hotels, and car rental) in terms of systems development, performance measurement, and consumers’ responses to RM practices (see, e.g., Dolasinski, Roberts, & Zheng, 2019; Karande & Magnini, 2011; Lindenmeier & Tscheulin, 2008; Noone & Lee, 2011; Pekgün et al, 2013; Schwartz & Chen, 2012; Tanford, Erdem, & Baloglu, 2011; Wittman & Belobaba, 2017). However, there has been a growing interest in the application of RM across a variety of tourism-related settings, including restaurants, theme parks, golf courses, spas, cruise lines, and entertainment venues (e.g., Li et al, 2014; Noone, Enz, & Glassmire, 2017; Noone et al, 2009).…”

Section: Literature Reviewmentioning

confidence: 99%

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The Uniqueness of Revenue Management Approaches in Nontraditional Settings: The Case of the Golf Industry

Noone

Enz²,

Canina

2019

Journal of Hospitality & Tourism Research

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This study focuses on two demand and supply characteristics that may affect the transferability of revenue management (RM) practices from traditional (e.g., hotels) to nontraditional (e.g., golf, restaurants, entertainment venues) RM settings. Consumption within many nontraditional RM settings is largely discretionary in nature, with the potential to affect how demand and price should be managed across the booking horizon. Equally, operators are often challenged with a high degree of time-based inventory complexity, which may require that price and inventoried demand are managed at a greater level of granularity than traditional RM applications dictate. Using longitudinal golf reservations data, we found that superior revenue performance was associated with capturing a higher proportion of demand early in the booking horizon, rather than protecting inventory at higher prices for late bookers. Competitive price positioning in which price was higher than the competition during within-day peak-demand tee times also shaped revenue gains. Similarly, conversion management was found to be most critical during within-day peak demand periods. These findings suggest that traditional RM strategies may not apply in nontraditional RM settings where one or both of the demand and supply characteristics of interest is present. The implications of these findings for practitioners are explored.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

The Uniqueness of Revenue Management Approaches in Nontraditional Settings: The Case of the Golf Industry

Noone

Enz²,

Canina

2019

Journal of Hospitality & Tourism Research

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“…Hu et al applyed dynamic programming methods to analyze the dynamic pricing problem, and the positive impact of passenger psychology on airline fare and revenue is analyzed (Hu, Li & Ran, 2015). Wittman, Michael, Belobaba, Peter discussed how to predict the willingness to pay for passengers and provide personalized services and discounts for the passengers based on the dynamic dynamic income management of the airline (Wittman & Belobaba, 2017). On the related issues of refund, Zhong Nin and Tian Peng used the expected marginal value difference of ticket at the time of ticket sales and refunds to determine the refund fee.…”

Section: Research Statusmentioning

confidence: 99%

A study on the dynamic refund fee model of air tickets based on win-to-win mechanism

Zhao¹,

Deng²

2019

J. airl. airpt. manag.

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Purpose: To achieve the balancing of interests between airlines and passengers, the dynamic refund fee model is designed, which meets the interests of both airlines and passengers.Design/methodology/approach: In the study, the expectation utility function is constructed respectively for passengers and airlines, and the equilibrium point of the two is chosen to solve the passenger refund fee. Then, a dynamic refund fee model based on refund time and real-time sales revenue is proposed according to the actual operating conditions of the flight.Findings:The results show that refund fee is negatively related to three variables, the ticket price, the probability of ticket sales and the probability of refund. Besides, The maximum payment limit is the airline single seat cost or the actual fare paid below it, and the lowest can be exempt.Originality/value: A better standard of the rufund is proposed. The refund mode breaks the traditional static charging mode, and charges different refund fees to passengers for different refund time and the real time income of flights. Comparing with the current refund policy, the new charge of refund fee could best meets the interests of both parties.a refund fee standard.

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“…Yet research indicates that consumers perceive PDP as less fair than price differentiation that depends on time of purchase (Grewal et al 2004), purchase quantity (Lii and Sy 2009), an active price-setting mechanism (Haws and Bearden 2006), or seller choice (Garbarino and Maxwell 2010). With regard to the profitability of PDP, Wittman and Belobaba (2017) are able to demonstrate that implementing heuristics that enable personalized fare offers have a positive impact on the revenue of an airline in the context of revenue management. In addition, research has discussed legal and ethical concerns of consumers (Turow et al 2015) and the fear of eroding data privacy (Borgesius and Poort 2017).…”

Section: Introductionmentioning

confidence: 99%

A special price just for you: effects of personalized dynamic pricing on consumer fairness perceptions

Priester

Robbert

Roth

2020

J Revenue Pricing Manag

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Personalized dynamic pricing (PDP) involves dynamically setting individual-consumer prices for the same product or service according to consumer-identifying information. Despite its profitability, this pricing provokes strong negative fairness perceptions, explaining why managers are reluctant to implement it. This research provides important insights into the effect of two PDP dimensions (price individualization level and segmentation base) on fairness perceptions and the moderating role of privacy concerns. The results of two experimental studies indicate that consumers perceive individual prices as less fair than segment prices. They also evaluate location-based pricing as less fair than purchase history-based pricing. Consumer privacy concerns moderate these effects.

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Personalization in airline revenue management – Heuristics for real-time adjustment of availability and fares

Cited by 21 publications

References 21 publications

The Uniqueness of Revenue Management Approaches in Nontraditional Settings: The Case of the Golf Industry

The Uniqueness of Revenue Management Approaches in Nontraditional Settings: The Case of the Golf Industry

A study on the dynamic refund fee model of air tickets based on win-to-win mechanism

A special price just for you: effects of personalized dynamic pricing on consumer fairness perceptions

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