In the airline industry, the aim of O&D RM is to optimize network revenue by increasing seat availability for high-revenue connecting passengers while preventing connecting passengers from displacing high-yield local passengers to reduce displacement costs. Traditional O&D models rely heavily on complex historical data analysis. The outbreak of COVID-19 has led to an unprecedented disruption of the global airline industry. It has reset historical data, thereby reducing the reliability of the traditional forecasting and optimization results. This paper proposes Zero Displacement Cost (0DC) model as a simplified and flexible model for airlines to manage O&D in the post-COVID-19 world.
The development of Revenue Management (RM) in the airline industry started with overbooking in the 1960s and simple two-fare offerings in the 1970s. US airline deregulation in the 1970s and the resulting plethora of airfares in the 1980s led to further refinements in RM practices. These refinements included introducing multiple forecasting and optimization methods. By the 1990s, a few airlines had mastered leg-based RM.
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0DC model applies booking curve methodology to forecast the spoilage/spill. A flight booking curve reflects the booking pace by showing the number of bookings on each NDO (number of day out) on a flight level. It is represented graphically, NDO on the X-axis and LF on the Y-axis. It has been commonly used in airline industry to keep track of bookings and analyze booking patterns. Compared with traditional models, the needed data for generating booking curves have lower granularity, as they are in flight level, not ODF level. Even during COVID-19 time, analysts can utilize limited data and structured test-and-learn approach to build the booking curves (Fig. 1).
Industry data shows domestic routes and leg flights recover faster than international routes and connecting flights during COVID-19 recovery. Based on this assumption, 0DC model use leg flight performances as a foundation to build O&D fare recommendations. In the airline industry, a multiplier adjustment methodology is commonly used to quote O&D leg fares. Multipliers between 0.0 to 1.0 are multiplied by local leg fares to adjust O&D leg fares. 0DC model adopts this industry practice to provide recommendations for O&D leg fares. The values of multipliers are generated by calculating the ratios of how much current LF is above or below the full booking curve LF. Below is the formula for spoilage situations.
The Airline Group of the International Federation of Operations Research (AGIFORS) held a conference in October 2020 that included keynote addresses from KLM Royal Dutch Airlines and Airbus, as well as three panels that included representatives from 11 airlines throughout the world that focused on how COVID-19 is impacting and reshaping the airline industry. This paper presents key themes that emerged from these discussions, including the impact of border closures on airline operations and demand forecasts; the shift in development priorities within revenue management departments; and outlooks for how passenger preferences, booking curves, and fare product restrictions may change after the COVID-19 pandemic.
Never before has the airline industry seen such a dramatic and sustained decline in air passenger demand. Previous crises like SARSFootnote 1 in 2003 or the 9/11 terrorist attacks in 2001 have been more limited geographically or more limited in time and duration (Lange 2020). Therefore, it becomes more challenging to model exactly when airlines will be able to restart operations and when flight operations and customer demand will return to pre-COVID-19 levels. Current projections of when worldwide traffic will return to 2019 levels are between 2023 and 2025 (Lange 2020).
Given the influence that travel restrictions have on demand, combined with the predominance of local and national policies, which themselves are unstable and changing very rapidly, there remains a research need to determine a correlation between the propagation of health measures being taken in countries and the restrictions on the restart of airline operations (Lange 2020). Several airlines and professional organizations, such as the International Air Transport Association, have been conducting studies on the effectiveness of different travel restrictions related to testing and quarantines. Air Canada has been working with McMaster Labs to conduct voluntary screenings of passengers when they arrive, then one week later, and again two weeks later to help determine if the two-week quarantine restriction is effective or could be shortened (Meaney 2020). IATA released a study in October 2020 showing that since the start of 2020, there have been 44 cases recorded of flight-related transmission of COVID-19 among 1.2 billion travelers, or one case for every 27 million travelers (IATA 2020; as noted by Meaney 2020). Such studies add to the collective body of knowledge about COVID-19 while informing governments and regulatory agencies on best practices when it comes to restrictions that are so impactful to the airline industry.
The history of RM is recognized in the contribution from Ben Vinod of Sabre Technologies in the article Evolution of Yield Management in Travel. The article starts off with the recognition that Yield Management came into existence on a significant scale a few years after the deregulation of the US airline industry in 1978 under the administration of Jimmy Carter. The deregulation Act of 1978 was a dramatic event in US economic policy, and it dismantled a comprehensive system of government controls. Before deregulation, airlines operated in a tightly regulated environment; regulated by governments and self-regulated through organizations such as the Civil Aeronautics Board and the International Air Transport Association. The article is a comprehensive chronological account of RM right upto today.
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