Airline Fares Research Articles

A Multi-Aspect Informed GRU: A Hybrid Model of Flight Fare Forecasting with Sentiment Analysis

This paper presents an advanced method for forecasting flight fares that combines aspect-based sentiment analysis (ABSA) with deep learning techniques, particularly the gated recurrent unit (GRU) model. This approach leverages historical airline ticket transaction data and customer reviews to better understand airline fare dynamics and the impact of customer sentiments on pricing. The aspect analysis extracts key service aspects from customer feedback and provides insightful correlations with airfare. These were further categorized into nine groups for sensitivity analysis, which offered a deeper understanding of how each group influences customers’ attitudes. This ABSA-driven forecasting method marks a departure from traditional models by utilizing sentiment data alongside airline transaction data to improve the predictive accuracy. Its effectiveness is demonstrated through metrics including a root mean square error (RMSE) of 0.0071, a mean absolute error (MAE) of 0.0137, and a coefficient of determination (R2) of 0.9899. Additionally, this model shows strong prediction performance in both short- and long-term fare predictions. It not only advances airfare forecasting methods but provides valuable insights for decision makers of airline industry to refine the pricing strategies or make improvements when it is indicated some services require further attention.

A Machine Learning Chronicle in Airfares for Pricing the Clouds

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs. The price of a plane ticket is influenced by the length of the trip, the location, the schedule, and several other factors, like holidays or vacations. Therefore, many people will surely save time and effort by having a basic awareness of airline expenses prior to making trip arrangements. The performance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analysed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used to build a system that can predict how much a flight will cost.

Flight Price Prediction Using Machine Learning

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs.The price of a plane ticket is influenced by the length of the trip, the location , the schedule, and anumber of other factors, like holidays or vacations. Therefore, many people will surely save timeand effort by having a basic awareness of airline expenses prior to making trip arrangements. Theperformance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analyzed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used tobuild a system that can predict how much a flight will cost.

An econometric study of the effects of airport privatization on airfares in Brazil

This paper develops empirical models to test the impact of airport privatization on airline fares. We employ a difference-in-difference approach combined with an endogenous switching regression model to account for the selection of airports to be privatized. The results suggest that prices for tickets on routes with at least one privatized airport at an endpoint are about 3–3.5% higher than on routes between two publicly managed airports. By testing moderating effects, we find evidence that market dominance enforces the privatization impact on airfares. The main conclusions are consistent using various control group classifications.

Civil airline fare prediction with a multi-attribute dual-stage attention mechanism

Airfare price prediction is one of the core facilities of the decision support system in civil aviation, which includes departure time, days of purchase in advance and flight airline. The traditional airfare price prediction system is limited by the nonlinear interrelationship of multiple factors and fails to deal with the impact of different time steps, resulting in low prediction accuracy. To address these challenges, this paper proposes a novel civil airline fare prediction system with a Multi-Attribute Dual-stage Attention (MADA) mechanism integrating different types of data extracted from the same dimension. In this method, the Seq2Seq model is used to add attention mechanisms to both the encoder and the decoder. The encoder attention mechanism extracts multi-attribute data from time series, which are optimized and filtered by the temporal attention mechanism in the decoder to capture the complex time dependence of the ticket price sequence. Extensive experiments with actual civil aviation data sets were performed, and the results suggested that MADA outperforms airfare prediction models based on the Auto-Regressive Integrated Moving Average (ARIMA), random forest, or deep learning models in MSE, RMSE, and MAE indicators. And from the results of a large amount of experimental data, it is proven that the prediction results of the MADA model proposed in this paper on different routes are at least 2.3% better than the other compared models.

On the Benefits of Being Alone: Scheduling Changes, Intensity of Competition and Dynamic Airline Pricing

We empirically test the hypothesis that the discounts offered by firms to consumers who purchase tickets in advance increase with the intensity of competition. We develop a new measure of competition for which we use the proximity (in departure time) of a given flight to its competitors to infer the intensity of competition and estimate the impact of competition on advance purchase discounts (APDs) and the dynamic pricing of airlines by exploiting plausibly exogenous changes in the flight schedules of airlines that occur during the booking period. We find strong support for the theoretical prediction that APDs are larger when the intensity of competition is higher using a sample of airline fare quotes. Our results also suggest that airline price dispersion increases with the intensity of competition.

Optimizing airline fare structures

Optimizing an airline’s fare structure has always been reliant on the expertise and market awareness of its Pricing professionals. Whether in the traditional airline world—with restrictions aiming to “fence” high-yield customer segments from the leisure ones, in the low-cost carrier competitive world with more simplified fare structures, or in the new world of dynamic offer generation and continuous pricing, how to establish the entry level price and all other prices, as well as the appropriate conditions associated to a price remains a challenge for any airline Pricing department. In this article we explore some of the common airline practices for determining fare levels and fare rules, as well as what the future holds for this field in the context of IATA New Distribution Capability, where offers will be generated dynamically, pricing could be continuous and traditional booking classes might not exist.

The Impact of Terrorism on European Tourism

This paper estimates the influence of terrorist attacks on European tourism through the short-term post-hoc response of the airline industry and passengers. We use a seasonally-adjusted ARMA-GARCH methodology on unique datasets that examine changes in tourism as measured by ASKs, seats filled and changes in both fares and revenues. Traffic flows are found to fall despite significant fare reductions; however, this response varies substantially based on the flight origin and ticket-type purchased. We found that business travel slows substantially due to duty of care legislation for corporate transport. While we found evidence indicating substantial airline fare reductions, in the majority of investigated cases this response was unable to mitigate substantial reductions in passenger demand and flows across varying ticket types.

The impact of terrorism on European tourism

This paper estimates the influence of terrorist attacks on European tourism through the short-term post hoc response of the airline industry and passengers. We use a seasonally-adjusted ARMA-GARCH methodology on unique datasets that examine changes in tourism as measured by ASKs, seats filled and changes in both fares and revenues. Traffic flows are found to fall despite significant fare reductions; however, this response varies substantially based on the flight origin and ticket-type purchased. We found that business travel slows substantially due to duty of care legislation for corporate transport. While we found evidence indicating substantial airline fare reductions, in the majority of investigated cases this response was unable to mitigate substantial reductions in passenger demand and flows across varying ticket types.

Do jet fuel price movements help forecast airline fares and the demand for air travel?

ABSTRACTThe paper studies the predictive content of jet fuel prices for the U.S. aviation industry through in-sample and out-of-sample forecasting exercises. Our results suggest the possibility of limited improvements in the predictions of airline fares, and little evidence of predictability from jet fuel prices to measures of air travel demand.

Mixed logit analysis of trade-off effects between international airline fares and fences: a revenue management perspective

As transportation is essential for tourism development, effectively utilizing its perishable resources has become an important issue. This study aims to analyse the relationship between airline fares and using conditions from the perspective of millennial tourists and taking the Taipei–Tokyo market as an example. The study attempts to show a revenue management practice in the manipulation of homogeneous seat service and give millennial tourists a better understanding of their preferences for ticket choices. We categorize availability of flight, advance booking, ticket validity, and changing conditions as main attributes and develop a stated-preference questionnaire with multiple hypothetical scenarios for respondents to select in the experiment. We effectively collect 390 valid samples for a mixed logit analysis and the results show that all applied attributes are statistically significant. Ticket validity is revealed to be the most important fence with the largest willingness-to-pay value and followed by availability of flight, advanced booking, and changing conditions.

Customized dynamic pricing of airline fare products

Firms practice dynamic pricing when they charge different customers different prices for the same products, as a function of an observable state of nature. In the airline industry, dynamic pricing has historically been limited by the capabilities of distribution systems, which require filing a finite set of fare products with fixed prices. However, advancements in airline distribution technology will soon allow the generation of “customized offers,” which could include a dynamically generated price. In this paper, we propose a heuristic for customized dynamic pricing of airfares when the observable state of nature includes an observation of passenger characteristics. We first introduce a general model for decoupling the customized offer generation problem from the well-studied airline revenue management problem. After generating a baseline assortment of fare products and observing the characteristics of a passenger’s request, an airline can choose to customize that passenger’s offer by dynamically incrementing or discounting the prices that would ordinarily be offered. The methodology could be applied with existing airline revenue management methods, and would be compatible with IATA’s New Distribution Capability (NDC). For implementation, we propose a straightforward heuristic approach based on simple estimates of passenger willingness-to-pay distributions. The heuristics are simulated in the Passenger Origin–Destination Simulator, a complex airline revenue management simulation environment that takes into account passenger choice and competition. The results show that the heuristics can lead to revenue gains of up to 3–4% when practiced by one airline. Furthermore, the heuristics remain revenue positive in competitive environments.

Effects of Mergers and Divestitures on Airline Fares

U.S. antitrust authorities have increasingly forced merging companies to divest assets as a condition for merger approval, with the goal of creating a more competitive postmerger environment. This study examined the effectiveness of this government strategy in the context of the airline industry, in which forced divestitures have occurred in recent consolidations. The study used unique data on assets critical to airport facilities that were involved in the divestitures to document the reallocation of those assets to low-cost carriers. Estimates of the impact of the divestitures on airfares were then calculated. The results show that, at the affected airports, fares for merging carriers fell by 3% and fares for nonmerging carriers fell by 1% relative to airports at which no divestiture occurred. These results provide evidence that the divestiture strategy used by antitrust authorities is effective in this setting in mitigating market power.

Network carriers' strategic decisions: does low cost carrier entry matter?

Good decisions require that each decision-maker accurately predicts the strategic moves of the other parties. Dealing with prospective low-cost carrier (LCC) entrants is critical for global network airlines. This research focused on two main issues. First, it investigates competitive reaction by established US airlines when they face an LCC entrant in the less congested, small-sized US regional airports. Second, it examines which of the market indicators are most likely to influence airline fares out of small regional airports with the LCC entry. While the first stage of research demonstrated mixed results and did not discover any patterns in airline behaviour with LCC entry due to a large number of other variables influencing airline revenue management. The second stage confirmed that the stage length, number of passengers, number of competitors, number of stops and the oil price do have an impact on airfares.

Network carriers' strategic decisions: does low cost carrier entry matter?

Good decisions require that each decision-maker accurately predicts the strategic moves of the other parties. Dealing with prospective low-cost carrier (LCC) entrants is critical for global network airlines. This research focused on two main issues. First, it investigates competitive reaction by established US airlines when they face an LCC entrant in the less congested, small-sized US regional airports. Second, it examines which of the market indicators are most likely to influence airline fares out of small regional airports with the LCC entry. While the first stage of research demonstrated mixed results and did not discover any patterns in airline behaviour with LCC entry due to a large number of other variables influencing airline revenue management. The second stage confirmed that the stage length, number of passengers, number of competitors, number of stops and the oil price do have an impact on airfares.

The effect of rail travel time on airline fares: First evidence from the Italian passenger market

The empirical evidence shows that travel time is crucial for rail transport to be a competitor to air transport. However, there are no papers testing whether travel time has a direct effect on airline pricing. This paper is a step towards filling this gap. We test and quantify the effect of rail travel time on airline fares, using unique data at flight-level. We find that airlines design pricing strategies taking into consideration the travel time of competing rail transport service. Airlines are found to set, on average, higher fares as rail travel time increases. However, the competitive pressure induced by rail travel time is perceived by airlines only as the day of departure gets closer: from the 40th to the day before departure it increases while it gradually decreases as the departure date gets further away.

Homogeneous service with heterogeneous products: Relationships among airline ticket fares and purchase fences

A fare table derived from homogeneous service is essential for revenue management applications in the airline industry. Restrictions or so-called fences are usually regarded as a useful tool to differentiate homogeneous seat service. Nevertheless, the relationships among fares and fences are not yet clear. This study aims to investigate passengers’ preferences on the choice of ticket alternatives describing by fares and fences and using Taiwan domestic air travel as an example. Regarding the attributes that an airline ticket may be attached such as departure time, booking time, ticket validity, changing fee, refund and fare, stated preference questionnaires are developed with multiple hypothetical scenarios for respondents to select in the experiment. 398 valid samples are collected for the logit model analysis. With the use of mixed logit model to accommodate both passengers’ heterogeneity and also the issue of relevant alternatives in the experiment, the results show statistical significance of all applied attributes with correct signs. In addition, passengers possess different attitudes on the fence of booking time, ticket validity, changing fee, and fare. Willingness-to-pay of each fence is further calculated to ultimately generate a fare table based on the combination of fences for practice use.

From the Fringe to the Forefront: Low Cost Carriers and Airline Price Determination

Low-cost carriers (LCCs) have transformed the US airline industry. They are now much larger and have moved into more direct competition with legacy carriers. This paper re-examines airline fare determination in this transformed industry. It finds that LCCs have a much larger fare impact than do legacies, but that their fare-reducing effect diminishes as they become dominant on a route. It also finds that legacy carriers primarily affect each others’ prices, whereas LCCs have a significant impact on pricing by both other LCCs and legacies. These and other results suggest a new and more nuanced role for LCCs in the domestic airline industry.

An insight into airline dynamic pricing practices in emerging markets: Effects of low cost carriers' presence on routes from Belgrade 'Nikola Tesla' airport

Dynamic pricing and revenue management in airline industry have been the subject of research for more than twenty years now. Building upon that massive body of research, in this paper we investigate actual dynamic pricing patterns in new and emerging markets. We specifically focus on the impact that recent entry of low cost carriers on a number of routes from Belgrade Nikola Tesla Airport might have had on pricing practices of legacy incumbents. Unlike with most of previous contributions in the field, we analyse the market characterised by relatively low frequencies and predominantly short-to-medium haul flights. In this paper, we observe and analyse pricing dynamics on two types of routes: routes where only legacy carriers operate and routes where legacy carriers face competition from low cost carriers. The effects of route competition on offered airline fares are estimated and conclusions derived.

Product Unbundling in the Travel Industry: The Economics of Airline Bag Fees

This paper provides theory and evidence on airline bag fees, offering insights into a real‐world case of product unbundling. The theory predicts that an airline's fares should fall when it introduces a bag fee, but that the full‐trip price (the bag fee plus the new fare) could either rise or fall. The empirical evidence presented in the paper provides strong confirmation of the first prediction. The data also suggest that the average fare falls by less than the bag fee itself so that the full price of a trip rises for passengers who choose to check bags.