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The de-bundling and re-bundling of service products offered by low cost carriers from service innovation have become 'à-la-carte' services and chargeable ancillary services to generate additional revenues in the airline industry. In this paper, we focus on the payable upgrade option in airlines to increase revenue when customers' demands are uncertain. This study is as an extension of planned upgrade, which guarantees the use of low-quality services at a low price, but requires customers to pay to use upgraded benefits. In this paper, we focus on the seat assignment problem with the payable upgrade option to maximize revenue. Also, we set the condition under which payable upgrade options can generate more revenue. Furthermore, applying Belobaba's EMSR approach, we suggest an effective seat assignment method for multiple fare classes with a payable upgrade option to increase the total revenue. With a simple numerical example, we find that introducing a payable upgrade option can increase the revenue. Our method for allocating seats for multiple fare classes with a payable upgrade option can contribute effectively to revenue increases in airlines' branded fare products, as well as in other service industries. [ABSTRACT FROM AUTHOR]

The k-means is one of the most popular clustering analysis algorithm and widely used in various fields. Nevertheless, it continues to have some shortcomings, for example, extremely sensitive to the initial center points selection and the special points such as noise or outliers. Therefore, this paper proposed initial center points' selection optimization and phased assignment optimization to improve the k-means algorithm. The experimental results on 15 real-world and 10 synthetic datasets show that the improved k-means outperforms its main competitor k-means + + and under the same setting conditions, namely, using the default parameters,its clustering performance is better than Affinity Propagation, Mean Shift, and DBSCAN. The proposed algorithm was applied to analyze the airline seat selection data to air passengers grouping. The clustering results, as well as absolute deviation rate analysis, realized customer grouping and found out suitable audience group for the recommendation of seat selection services. [ABSTRACT FROM AUTHOR]

Featured Application: The work focuses on analyzing airplane boarding methods used in normal times and evaluating them by applying lessons learned during the COVID-19 pandemic. As a result, the airplane boarding methods used in practice by the airlines are analyzed through a series of health risks indicators and an operational indicator—the boarding time. The COVID-19 pandemic has produced changes in the entire aviation industry, including adjustments by airlines to keep the middle seats of airplanes empty to reduce the risk of disease spread. In this context, the scientific literature has introduced new metrics related to passengers' health when comparing airplane boarding methods in addition to the previous objective of minimizing boarding time. As the pandemic concludes and the aviation industry returns to the pre-pandemic situation, we leverage what we learned during the pandemic to reduce the health risk to passengers when they are not social distancing. In this paper, we examine the performance of classical airplane boarding methods in normal times but while considering the health metrics established during the pandemic and new metrics related to passenger health in the absence of social distancing. In addition to being helpful in normal times, the analysis may be particularly helpful in situations when people think everything is normal but an epidemic has begun prior to being acknowledged by the medical scientific community. The reverse pyramid boarding method provides favorable values for most health metrics in this context while also minimizing the time to complete boarding of the airplane. [ABSTRACT FROM AUTHOR]

It is common for the airlines to sell a pool of identical seats at different prices according to different booking classes to improve revenues in a very competitive market. Under this practice, a complex yet very crucial problem is to determine whether a booking request for seats in a certain booking class occurring at some point in time during the booking period should be accepted or denied. This paper develops a discrete-time dynamic programming model for finding an optimal booking policy, which can be reduced to a set of critical values. Unlike many existing models, this model does not require any assumptions about the arrival pattern for the various booking classes. Furthermore, multiple seat bookings, which are a practical issue in airline seat inventory control, are also incorporated into the model. In this paper, the basic properties of the model are studied. Numerical examples are presented. Computational issues, including the computational efficiency of the model, are also discussed. [ABSTRACT FROM AUTHOR]

Based on two strands of theoretical research, this paper provides new evidence on how fares are jointly affected by in-flight seat availability and purchasing date. As capacity-based theories predict, it emerges that fares monotonically and substantially increase with flight occupancy. After controlling for capacity utilization, our analysis also supports time-based theories, indicating a U-shaped temporal profile over a two-month booking period, as well as a sharp increase in fares in the two weeks prior to departure. [ABSTRACT FROM AUTHOR]

This paper reports the results of an investigation into changes in body shape anthropometry over the past several decades and discusses the impact of those changes on seating in transport, especially airliners. Changes in some body shape dimensions were confirmed in a sample of students at TU Delft; several of the changes, e.g. hip breadth, seated, are relevant to the ongoing design of seating. No change in buttock knee length was observed. The fit between current user anthropometry and current airline seat design, especially regarding seat width, was investigated. A comparison of the average current seat breadth with global anthropometric data suggests that accommodation may be problematic, with less than optimal width for passengers' shoulder and elbow widths. [ABSTRACT FROM AUTHOR]

As airlines have moved toward more concentrated "hub-and-spoke" schedules, connecting passengers have become an increasingly important part of their loads and revenues. Yet, many optimization approaches to such airline planning problems as revenue management and aircraft assignment have ignored the "cross-leg" effects of seating capacity on connecting traffic and the associated revenue. This paper presents a simple approach for calculating consistent on-board itinerary flows and the corresponding loads, revenues and marginal seat values given a set of underlying demands and an assignment of seating capacities to legs. An application of this approach to a large-scale airline network is presented and the implication of the results for decision-making discussed. Although the approach is presented in the context of airline planning, it is applicable to any transportation system in which connecting traffic plays a significant part as well as to hotel and automobile rentals. [ABSTRACT FROM AUTHOR]

Revenue management has started on the capacity control by booking classes for available seats and has been recognized as a powerful tool to maximize the total revenue. Among various RM techniques, pricing and seat controls have played key roles in airlines. Since pricing and seat control problems are highly correlated in RM problem. These two decision problems need to be considered jointly. However, due to the complex interaction between them, a few researches focus on the joint pricing and seat control problem. In this paper we consider a comprehensive problem including a cancellation in booking processes and a mark-up policy in pricing strategy under uncertain demands. To manage the demand uncertainty efficiently, we applied a linear approximation technique and proposed a new approximation model, a simple mixed Integer Programming model. From the computational experiments with randomly generated data, we can find our model makes good performance for deciding pricing and seat controls simultaneously. [ABSTRACT FROM AUTHOR]

The novel coronavirus (SARS-CoV-2) has imposed the need for a series of social distancing restrictions worldwide to mitigate the scourge of the COVID-19 pandemic. This applies to many domains, including airplane boarding and seat assignments. As airlines are considering their passengers' safety during the pandemic, boarding methods should be evaluated both in terms of social distancing norms and the resulting efficiency for the airlines. The present paper analyzes the impact of a series of restrictions that have been imposed or mooted worldwide on the boarding methods used by the airlines, featuring the use of jet-bridges and one-door boarding. To compare the efficacy of classical airplane boarding methods with respect to new social distancing norms, five metrics were used to evaluate their performance. One metric is the time to complete the boarding of the airplane. The other four metrics concern passenger health and reflect the potential exposure to the virus from other passengers through the air and surfaces (e.g., headrests and luggage) touched by passengers. We use the simulation platform in NetLogo to test six common boarding methods under various conditions. The back-to-front by row boarding method results in the longest time to complete boarding but has the advantage of providing the lowest health risk for two metrics. Those two metrics are based on passengers potentially infecting those passengers previously seated in the rows they traverse. Interestingly, those two risks are reduced for most boarding methods when the social distance between adjacent passengers advancing down the aisle is increased, thus indicating an unanticipated benefit stemming from this form of social distancing. The modified reverse pyramid by half zone method provides the shortest time to the completing boarding of the airplane and—along with the WilMA boarding method—provides the lowest health risk stemming from potential infection resulting from seat interferences. Airlines have the difficult task of making tradeoffs between economic productivity and the resulting impact on various health risks. [ABSTRACT FROM AUTHOR]

This paper investigates the time to complete the boarding of a partially occupied two-door airplane when its passengers are transported from the airport terminal to the airplane using two apron buses. We propose a greedy method that assigns each passenger to a particular apron bus based on the passengers' airplane seat assignments. This greedy approach exploits the airplane's symmetry by providing essentially the same method for those boarding through the front door of the airplane as those boarding through the rear door of the airplane. The symmetrical properties of window, middle, and aisle seats of each row/side are considered in the proposed method as well. Computer simulation results indicate that, when using the greedy method, the boarding time can be reduced by up to 8.33% compared to the boarding time resulting from the best known practices in the literature, and with up to a 43.72% improvement in boarding time when compared to the boarding method commonly used in many airports. Furthermore, experimental results confirm our hypothesis that when the capacity of the apron buses exceeds the number of passengers to be transported to the airplane, the most time-efficient results of the proposed greedy method occur when an equal number of passengers are assigned to each of the two apron buses. [ABSTRACT FROM AUTHOR]

Aircraft can hold large numbers of persons in close proximity for long periods, which can increase the risk for transmission of infectious disease.* Current CDC guidelines recommend against travel for persons who have not been vaccinated against COVID-19, and a January 2021 CDC order requires masking for all persons while on airplanes.†,§ Research suggests that seating proximity on aircraft is associated with increased risk for infection with SARS-CoV-2, the virus that causes COVID-19 (1,2). However, studies quantifying the benefit of specific distancing strategies to prevent transmission, such as keeping aircraft cabin middle seats vacant, are limited. Using bacteriophage MS2 virus as a surrogate for airborne SARS-CoV-2, CDC and Kansas State University (KSU) modeled the relationship between SARS-CoV-2 exposure and aircraft seating proximity, including full occupancy and vacant middle seat occupancy scenarios. Compared with exposures in full occupancy scenarios, relative exposure in vacant middle seat scenarios was reduced by 23% to 57% depending upon the modeling approach. A 23% exposure reduction was observed for a single passenger who was in the same row and two seats away from the SARS-COV-2 source, rather than in an adjacent middle seat. When quantifying exposure reduction to a full 120-passenger cabin rather than to a single person, exposure reductions ranging from 35.0% to 39.4% were predicted. A 57% exposure reduction was observed under the vacant middle seat condition in a scenario involving a three-row section that contained a mix of SARS-CoV-2 sources and other passengers. Based on this laboratory model, a vacant middle seat reduces risk for exposure to SARS-CoV-2 from nearby passengers. These data suggest that increasing physical distance between passengers and lowering passenger density could help reduce potential COVID-19 exposures during air travel. Physical distancing of airplane passengers, including through policies such as middle seat vacancy, could provide additional reductions in SARS-CoV-2 exposure risk. [ABSTRACT FROM AUTHOR]

This paper examines the problem of allocating airline seats between two nested fare classes when the demands for the classes are stochastically dependent. The well known simple seat allotment formula of Littlewood which requires the assumption of statistical independence between demands is generalized to a formula which requires only a much weaker monotonic association assumption. The model employed here is also used to examine the problems of full fare passenger spillage and passenger upgrades from the discount class. [ABSTRACT FROM AUTHOR]

Previous research in the optimal allocation of airline seats has followed one of two themes: marginal seat revenue or mathematical programming. Both approaches capture important elements of the revenue management problem. The marginal seat revenue approach accounts for the "nesting" of fare classes in computer reservation systems, but can only control seat inventory by bookings on legs. The mathematical programming approach will handle realistically large problems and will account for multiple origin-destination itineraries and side constraints, but it does not account for fare class nesting in the reservation systems. This paper combines both approaches by developing equations to find the optimal allocation of seats when fare classes are nested on an origin-destination itinerary and the inventory is not shared among origin-destinations. These results are applicable to seat allocation in certain reservations systems, point-of-sale control, and acceptance of groups over their entire itinerary. A special case of the analysis produces the optimal booking limits for leg-based seat allocation with nested fare classes. [ABSTRACT FROM AUTHOR]

This paper addresses the airplane passengers' seat assignment problem while practicing social distancing among passengers. We proposed a mixed integer programming model to assign passengers to seats on an airplane in a manner that will respect two types of social distancing. One type of social distancing refers to passengers being seated far enough away from each other. The metric for this type of social distancing is how many passengers are seated so close to each other as to increase the risk of infection. The other type of social distancing refers to the distance between seat assignments and the aisle. That distance influences the health risk involved in passengers and crew members walking down the aisle. Corresponding metrics for both health risks are included in the objective function. To conduct simulation experiments, we define different scenarios distinguishing between the relative level of significance of each type of social distancing. The results suggest the seating assignments that best serve the intention of the scenarios. We also reformulate the initial model to determine seat assignments that maximize the number of passengers boarding an airplane while practicing social distancing among passengers. In the last part of this study, we compare the proposed scenarios with the recommended middle-seat blocking policy presently used by some airlines to keep social distancing among passengers. The results show that the proposed scenarios can provide social distancing among seated passengers similar to the middle-seat blocking policy, while reducing the number of passengers seated close to the aisle of an airplane. • A mixed integer programming (MIP) model to assign passengers to seats is formulated. • The model can be used to properly assign the passengers to their seats while effectively preserving the social distancing. • Two types of social distancing are considered in the model. • Two metrics are used for measuring the health risk and are included in the MIP model objective function. • Model parameters may be varied to generate efficient tradeoffs based on airline's relative preference for social distancing. [ABSTRACT FROM AUTHOR]

Article deals with creation of continuous simulation model of actual check-in process of selected airline based on identified decision points in passenger handling process. Case study covers actual passenger acceptance situations based on their fulfilment to ticket conditions, ticket fare, transported baggage and considering overbooking situations as planned part of airline revenue management strategy. The problem is related to the identification of bottlenecks in order to efficiently plan and use check-in counters and effectively utilize aircraft seating capacity. Case study shows importance of proper setting of check-in process, together with associated fees in case of not fulfilling ticket conditions, which helps airlines to move breakpoint to favourable percentage of load factor. Simulation models points to possibilities of restriction procedures that affects risk management and movement of breakpoint according to utilization of the aircraft and influence final revenue from the flight. The results of the computer simulation show that ticket prices range from 100.81 € to 398.14 €, the luggage weights ranges from 0.06 kg to 31.57 kg, the total revenue from ticket sales and baggage payments is 44125.8 €. [ABSTRACT FROM AUTHOR]

Prices for the same flight change substantially depending on the time of purchase. This article uses a unique data set with round‐the‐clock posted fares to document significant within‐day price variation. Labeling time‐variation as discriminatory is difficult because the cost of an unsold airline seat changes with inventory, days before departure, and aggregate demand expectations. After controlling for these factors and aggregating hourly fares to have a framework with two consumer types, we are able to identify a component that is largely consistent with dynamic price discrimination. We find higher prices during office hours (when business travelers are likely to buy) and lower prices in the evening (when leisure travelers are more likely to purchase). As the proportion of business travelers increases closer to departure, both price dispersion and price discrimination become larger. We provide an alternative explanation for the observed within‐day price differentials which is related to Edgeworth price cycles. [ABSTRACT FROM AUTHOR]

Optimally organizing passengers boarding/deboarding an airplane offers a potential way to reduce the airplane turn time. The main contribution of our work is that we evaluate seven boarding strategies and two structured deboarding strategies by using a surrogate experimental test. Instead of boarding a real or mocked airplane, we carried out the experiment by organizing 40 participants to board a school bus with ten rows of four seats, symmetrically distributed on a single, central aisle. Experimental results confirm that the optimized strategies, i.e., Steffen and Steffen-lug, are superior to the traditional ones, i.e., Back-to-front, Window-to-aisle, and Random in time-saving and stability. However, the two structured deboarding strategies failed to reduce the deboarding time, and this result strongly suggests the prerequisites of applying such strategies only when, on average, passengers have a large amount of luggage. Besides, we further carried out a questionnaire survey of participants' preferences on seat layout and discussed how those preferences influence the boarding time. [ABSTRACT FROM AUTHOR]

Airlines have launched various ancillary services to meet their passengers' requirements and to increase their revenue. Ancillary revenue from seat selection is an important source of revenue for airlines and is a common type of advertisement. However, advertisements are generally delivered to all customers, including a significant proportion of people who do not wish to pay for seat selection. Random advertisements may thus decrease the amount of profit generated since users will tire of useless advertising, leading to a decrease in user stickiness. To solve this problem, we propose a Bagging in Certain Ratio Light Gradient Boosting Machine (BCR-LightGBM) to predict the willingness of passengers to pay to choose their seats. The experimental results show that the proposed model outperforms all 12 comparison models in terms of the area under the receiver operating characteristic curve (ROC-AUC) and F1-score. Furthermore, we studied two typical samples to demonstrate the decision-making phase of a decision tree in BCR-LightGBM and applied the Shapley additive explanation (SHAP) model to analyse the important influencing factors to further enhance the interpretability. We conclude that the customer's values, the ticket fare, and the length of the trip are three factors that airlines should consider in their seat selection service. [ABSTRACT FROM AUTHOR]

Loading strategies for commercial passenger aircraft have been a subject of recent study among air transportation research analysts. A fundamental assumption in the majority of these studies is the fixed configuration of passenger seats. Previous studies have focused on analyzing different strategies in an effort to reduce passenger loading time. This study takes a more proactive approach to the passenger loading process by starting with the design of the aircraft seating layout itself. Simulation analysis results indicate that alternative designs can result in loading time reductions between approximately 9-44%. [ABSTRACT FROM AUTHOR]

In this note, we attempt to prove the equivalence of the optimality conditions from three well-known existing models that deal with the seat allocation problem for a single leg, multifare flight with independent fare class demands. [ABSTRACT FROM AUTHOR]

We formulate and analyze a Markov decision process (dynamic programming) model for airline seat allocation (yield management) on a single-leg flight with multiple fare classes. Unlike previous models, we allow cancellation, no-shows, and overbooking. Additionally, we make no assumptions on the arrival patterns for the various fare classes. Our model is also applicable to other problems of revenue management with perishable commodities, such as arise in the hotel and cruise industries. We show how to solve the problem exactly using dynamic programming. Under realistic conditions, we demonstrate that an optimal booking policy is characterized by state-and time-dependent booking limits for each fare class. Our approach exploits the equivalence to a problem in the optimal control of admission to a queueing system, which has been well studied in the queueing-control literature. Techniques for efficient implementation of the optimal policy and numerical examples are also given. In contrast to previous models, we show that 1) the booking limits need not be monotonic in the time remaining until departure; 2) it may be optimal to accept a lower-fare class and simultaneously reject a higher-fare class because of differing cancellation refunds, so that the optimal booking limits may not always be nested according to fare class; and 3) with the possibility of cancellations, an optimal policy depends on both the total capacity and the capacity remaining. Our numerical examples show that revenue gains of up to 9% are possible with our model, compared with an equivalent model omitting the effects of cancellations and no-shows. We also demonstrate the computational feasibility of our approach using data from a real-life airline application. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including freight movement forecasting, airline passenger seat allocation, and the 2012 International Association of Maritime Economists Conference (IAME).