Clustered airline flight scheduling: Evidence from airline deregulation in Korea

This paper explores the impacts of competition level on airline scheduling in the Korean domestic short-haul routes where a hub-and-spoke system is not the optimal air transport network strategy. The empirical findings using the Korean airline panel data for the period 2006–2010 suggest that competition leads to less differentiated departure flight times as expected from spatial competition theory. Unlike the previous study on the U.S airline industry, the degree of this tendency for less differentiation differs across the type of routes: the Jeju island routes (leisure type) and the inland routes (business type), in the deregulated period. Following the May 2008 Deregulation Act we find an increasingly clustered pattern of airline scheduling in the Jeju island routes where there have been competitive pressures associated with new low cost entrants. This recent evidence would imply that airline carriers strategically schedule departure flight times and allocate flights between routes as competition increases in the deregulated period.     

Airport curfew and scheduling differentiation: Domestic versus international competition

This study investigates the strategic flight departure scheduling on domestic and short-haul international routes from regional airports in Korea. Airport-level data were constructed for non-stop routes from 2010 to 2018. This study examines the effects of changes in scheduling constraints induced by airport night curfews on domestic and international routes through competition intensity. The empirical findings suggest that competition leads to less differentiated flight departure times on domestic routes from the two regional airports. However, competition leads to more differentiated flight departure times on international routes from Daegu airport, which has a new night curfew, while a clustered departure pattern is found for international routes from Cheongju airport. An obvious pattern of differentiated departure times is found after the easing of night curfews in 2014, along with the expansion in LCCs.     

Dynamic routing of time-sensitive air cargo using real-time information

The route planning of time-sensitive air-cargo is becoming more important with the growing air-network congestion and delays. We consider a freight forwarder’s routing of a time-sensitive air-cargo in the presence of real-time and historical information regarding flight availability, departure delays and travel times. A departure delay estimation model is developed to account for real-time information inaccuracy. A novel Markov decision model is formulated and solved with online backward induction. Through synthetic experiments and case studies, we demonstrate that dynamic routing with real-time information can improve delivery reliability and reduce expected cost.     

Using causal machine learning for predicting the risk of flight delays in air transportation

Delays in air transportation are a major concern that has negative impacts on the airline industry and the economy. Given the complexity of the National Air Space system, predicting the risk of flight delays and identifying significant predictors is vital to risk mitigation. The purpose of this paper is to perform data mining using causal machine learning algorithms in the USELEI process (Understanding, Sampling, Exploring, Learning, Evaluating, and Inferring) to predict the probability of flight delays in air transportation using data collected from different sources. The findings indicated significant effects of predictors, including reported arrivals and departures, arrival and departure demands, capacity, efficiency, and traffic volume at the origin and destination airports on the risk of flight delays. More importantly, causal interrelationships among variables in a fully structural network are presented to how these predictors interact with one another and how these interactions lead to delay incidents. Finally, sensitivity analysis and causal inference can be performed to evaluate various what-if scenarios and form effective strategies to mitigate the risk of delays.     

An Exploratory analysis of flight delay propagation in China

Delay propagation is the flight departure delay caused by the arrival delay of pre-segment flight. Chinese airline market has suffered very poor on-time performance (OTP) in recent years. It is, however, unclear whether delay propagation prevails as one major source for such problem. This study first aims to empirically quantify delay propagation in the Chinese airline market. Specifically, we shed light on heterogenous levels of delay propagations across different airports and airlines. Then, the distinct delay propagation patterns in China are also discussed and compared with other developed airline markets (e.g., the US and Europe). Our estimation is based on OTP data for over 12 million Chinese flights covering the 2015–2017 period. Specifically, it is found that 10 min arrival delay of pre-segment flight within 1 hr before the departure lead to an average of 7.49 mins delay propagation for subsequent departure flight. Arrival delay of earlier pre-segments (1–2 and 2–3 hr before the departure) leads to much less delay propagation, due to longer ground buffer. Chinese airlines arrange longer ground and flight buffer than that of the US airlines to prevent the delay propagation from accumulating along the subsequent flights in a day. Thus, unlike the US market, delay propagation is not the major reason for poor OTP in China. In addition, delay propagation is less prevailing at the Chinese hub airport. This is because China has relied on point-to-point network, which does not require sophisticated schedule coordination. And the local passengers at these Chinese hub airports have higher time value such that the Chinese airlines also try to improve OTP at these hub airports to better serve these lucrative but time-sensitive local passengers. Unlike the European LCCs, Spring Airlines, the largest low-cost carrier (LCC) in China, outperforms major full-service carriers (FSCs) in controlling delay propagation. This finding may also apply to other Northeast Asian LCCs sharing common operational characteristics as Spring Airlines. Last, we find that airlines purposely tolerate moderate departure delays of up to 15 min, which is the threshold that defines delays, no matter whether the pre-segment flight arrives late or on-time. The relevant policy and managerial implications are also discussed.     

Modeling air travelers’ choice of flight departure and return dates on long holiday weekends

Air travel demand is typically high on long holidays. Understanding factors that influence the choice of air travelers with respect to their departure and return dates on long holidays can help airlines make effective decisions on pricing, ticket sales, and scheduling. We conduct a stated preference survey to examine the preferences of low-cost airline travelers on a particular holiday weekend. A temporally correlated logit model is developed to account for the temporal correlation of day-of-the-week alternatives. The results indicate that airfare is the key variable affecting air travel date choices. The utility of day alternatives decreases when more leave days are required before the holiday begins. Departure dates before the beginning of the holiday weekend and return dates after the end of the holiday are highly substitutable. The low-fare strategy comprising early departures and late returns can effectively increase the load factor of off-peak flights on long holiday weekends.     

Making the connections between transport disadvantage and the social exclusion of low income populations in the Tshwane Region of South Africa

To date, the majority of studies which consider transport from a social exclusion perspective have been conducted in the context of the developed world where both income poverty and lack of transport are relative rather absolute states. In a unique departure from these previous studies, this paper explores the relationship between transport and social disadvantage in the development context, the key difference being that income poverty is absolute and where there is much lower access to both private and public transportation generally. Thus, it seeks to explore whether the concept of social exclusion remains valid, when it is the majority of the population that is experiencing transport and income poverty compared with the minority who do so in advanced economies.The paper is based on a scoping study for the Republic of South Africa Department of Transport (RSA DOT), which primarily involved focus group discussions with a range of socially deprived urban and peri-urban population groups living in the Tshwane region of South Africa. In a second departure from previous studies which consider transport and social disadvantage in the development context, the study takes a primarily urban focus. The rationale for this is that theoretically low income urban settlements do not suffer from the lack of transport infrastructure and motorised transport services in the way that more remote rural areas do. The policy issue is therefore less a question of addressing a deficit in supply and more one of addressing particular aspects of public transit service failure, which are more readily amenable to relatively low cost, manageable, small-scale national and local policy interventions.A primary aim for the study was to reinvigorate cross-government debate of these issues in the hope of breaking South African government’s long-standing and persistent policy inertia in the delivery of equitable and socially sustainable urban transport systems.     

Determinants of flight delays at East Asian airports from an airport,route and network perspective

Previous studies on determinants of flight delays have been limited to the attributes of departure and arrival airports and routes and experiences in North America and Europe. This research extends the existing discussions by considering a network perspective to explore East Asian airports. A total of 4611 routes among 318 airports in the second half of 2017 are analyzed using panel data regressions. Results show that the attributes of airports and routes linked with the departure and arrival airports of a flight are the essential determinants of flight delays in East Asia. However, the congestion internalization and hubness effect of departure and arrival airports suggested in previous research are not observed in this region. The associations of slot control levels and route attributes with delays are varying between airports inside and outside China and domestic and international routes. This research supplements a new perspective to understand the determinants of flight delays in existing literature and provides a rarely observed knowledge to encourage East Asian airport operators and carriers developing management strategies for minimizing flight delays.     

A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling,with consideration of fleet assignment problem

One of the most important airline's products is to determine the aircraft routing and scheduling and fleet assignment. The key input data of this problem is the traffic forecasting and allocation that forecasts traffic on each flight leg. The complexity of this problem is to define the connecting flights when passengers should change the aircraft to reach the final destination. Moreover, as there exists various types of uncertainties during the flights, finding a solution which is able to absorb these uncertainties is invaluable. In this paper, a new robust mixed integer mathematical model for the integrated aircraft routing and scheduling, with consideration of fleet assignment problem is proposed. Then to find good solutions for large-scale problems in a rational amount of time, a heuristic algorithm based on the Simulated Annealing (SA) is introduced. In addition, some examples are randomly generated and the proposed heuristic algorithm is validated by comparing the results with the optimum solutions. The effects of robust vs non-robust solutions are examined, and finally, a hybrid algorithm is generated which results in more effective solution in comparison with SA, and Particle Swarm Optimization (PSO).     

Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We demonstrate our approach for strategic flight schedules in the period 2013–2018 at London Heathrow Airport. Together with the development of dedicated strategic flight schedule optimization models, our proposed approach supports an integrated strategic flight schedule assessment, where schedules are evaluated with respect to flight delays and cancellations.     

A push to cycling—exploring the e-bike's role in overcoming barriers to bicycle use with a survey and an intervention study

In Norway, as in many countries, there is a political goal to increase bicycle use. The electric bicycle (e-bike) is a promising tool for achieving this goal, given the hilliness of the country. However, little is yet known about the deterrents of cycling in Norway in general, and in particular how the purchase of an e-bike could be stimulated.

In the current study, 5500 respondents from a convenience sample among car owners were asked about their perceptions of bicycling in general, and of e-bikes in particular as well as their willingness to pay (WTP) for an e-bike. Randomly selected participants (N = 66) were given access to an e-bike for a limited time (2 or 4 weeks). A second questionnaire captured the same perceptions and WTP post-intervention. The results were compared with a control group (N = 214).

The results showed that those who cycle the least were most interested in buying an e-bike and that prior knowledge of the e-bike corresponded with a higher desire to buy one. Pro-environmental values did not predict interest in e-bikes, neither did norms and attitudes toward cycling. The WTP for an e-bike increased after having experienced the benefits for those who used an e-bike compared to those who did not. Price reduction of the e-bike (e.g. VAT exemption), spread of knowledge among the wider population, and actions to offer an e-bike experience may therefore be effective strategies for further expansion of the e-bike in the transport system and thereby to increase bicycle use in Norway.     

The benefits of tankering considering cost index flying and optional refuelling stops

This work presents the application of a fuel tankering strategy to an airline considering cost index flying and the possibility of using intermediate optional refuelling stops. The tankering solution was based on integer linear programming algorithm using a network modelling strategy. Two methodologies have been used to calculate mission performance according to the aircraft cost index, the first is the complete method where every flight phase (climb, cruise and descent) are optimized according to the cost index. This methodology has the disadvantage of being a slow process as the optimization of every flight leg is time consuming. The second approach is a simplified method, which is based on the Breguet equation and has the advantage of being a quick solution for an initial tankering assessment analysis. A comparison is made between these two methodologies on a simulated multi-stage flight mission demonstrating the validity of this simplified approach. The benefits of a tankering flight using cost index and refuelling stops are illustrated by a study case of a network linking six airports and seventeen optional refuelling stops with different fuel costs. The results from the optimized flight route show a 3% cost reduction at the specific multi stage mission example when compared to a more traditional dispatch approach without the use of the fuel tankering strategy.     

An investigation of fatigue issues on different flight operations

The influence of various kinds of flight operations on pilot fatigue remains a chronic problem which has a bearing on flight safety. In this study we sampled flight crews from six airlines in Taiwan, asking them to report on their perceptions of both physical and mental fatigue, before and after flight duty. The data were then analyzed with paired t-test and ANOVA. Our research results confirm findings obtained in other studies, namely, that perceived fatigue levels increase after flight duty, with that of oceanic crews being greater than that of crews serving either regional or short-haul operations. A majority of the pilots surveyed reported feeling fatigued or even nodding-off during long-distance flights, and consequently were in favor of a program of scheduled cockpit napping. While these findings are preliminary, they offer valuable information to aviation regulators and airlines regarding the assigning of consecutively scheduled flights to the same aircrews.     

Aircraft routing for on-demand air transportation with service upgrade and maintenance events: Compact model and case study

This paper addresses a problem faced by airline companies that offer on-demand flight services. Given a list of flight requests, the company has to assign its aircraft to these requests while minimizing operational costs. The main issue in this planning process involves the positioning of aircraft when they are not available at the airports of customer departure. The cost of this positioning should be as low as possible, as the customers’ expenditures are proportional to the requested flight hours only. We propose a compact optimization model to support decision making in this situation. It takes into account the mandatory aircraft maintenance events and the possibility of flight upgrades according to the their impact on the operational costs. One important and novel feature of this model is that it allows the anticipation or postponement of the beginning of flights and maintenance events within a given tolerance, giving more freedom to the decision making process. This research is motivated by a case study carried out with a fractional management airline company that operates in European and Asian countries. Computational experiments using real-life data collected from the company show that the proposed model can be solved quickly using general-purpose optimization software, including open-source alternatives. The results indicate that the obtained solutions lead to significant reductions in the operational costs and hence can be used in practice for effective decision making.     

The Relative Importance of Social and Personal Norms in Explaining Intentions to Choose Eco‐Friendly Travel Options

Changes in current travel patterns are important in order to move towards a more sustainable future of tourism. This paper reports findings from a study (N = 762) investigating the relative importance of social and personal norms in explaining intentions to choose eco‐friendly travel options. Personal norms showed the strongest association with behavioural intentions and further mediated the link between injunctive social norms and behavioural intentions. Overall findings indicate that social and personal norms seem both related to travel choices but that a particular emphasis should be given to the role of personal norms. Further implications of these findings are discussed. © 2015 The Authors. International Journal of Tourism Research Published by John Wiley & Sons Ltd.     

Detecting passengers' heterogeneity on airlines’ services using SP data

In this paper, the heterogeneity in passengers' perceptions of airlines' services has been investigated by using a Random Parameter Mixed logit model. To calibrate and validate the proposed model, data from a Stated Preferences choice experiments was used. The survey was conducted online and involved the whole population of the University of Calabria (Italy). The experiments were designed by considering the main service attributes characterizing air travellers’ experience in its entirety: before, during, and after the flight. Differently from the previous studies using Stated Preferences survey, two different groups of choice experiments were designed: the former referring to before/after the flight stages, and the last referring to during the flight experience. For each group, specific attributes were considered.Final findings remark that flyers' perceptions on airline's services vary among the different service aspects and among individuals. Specifically, we found that curtesy of cabin crew, space available, temperature, cleanliness, service on board and ticket cost are attributes referring to the during the flight stage of the travel that showed heterogeneity in passenger's perceptions. On the contrary, the attributes referring to the before/after the flight stages for which we detected heterogeneity in passengers' perceptions are waiting time at check-in, delay of flight departure, and ticket cost.     

Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion

Airport congestion mitigation requires reliable delay estimates. This paper presents an integrated model of airport congestion that combines a tactical model of capacity utilization into a strategic queuing model. The model quantifies the relationships between flight schedules, airport capacity and flight delays, while accounting for the way arrival and departure service rates can be controlled over the day to maximize operating efficiency. We show that the model estimates the average and variability of the delays observed at New York’s airports relatively well. Results suggest that delays can be extremely sensitive to even small changes in flight schedules or airport capacity.     

A border effect in airport choice: Evidence from Western Europe

Some commentators suggest that air travelers are reluctant to use a foreign airport as a point of departure for their journey. Such reluctance has implications for marketing and policy measures, especially in border regions and in smaller countries, such as the Netherlands and Belgium. In this study, we tested this supposed barrier effect of national borders with empirical data.Our research is based on a subsample (n = 4083) of a large-scale survey among German, Dutch and Belgian adults. Participants were asked about their most recent flight, preferences regarding long-distance travel, and general travel behavior. The survey information about the most recent trip was linked to the Official Airline Guide with data from 18 airports in the Western European region. On average, however, only 10 airports offered a direct connection to the destination of the respondents’ most recent flight. A conditional logit model with varying choice sets allowed us to model only the relevant airports per respondent, while accounting for other known determinants in airport choice, such as travel time, airline competition, and number of available flights.The model results confirmed our expectations: people strongly prefer a departure airport situated in their own country. The model predictions suggest that without the border effect the share of people in our sample departing abroad would rise from 7.7% to 18.7%. Experience (with multiple airports as a point of departure) mitigates the barrier effect of the border. The performance of our model is good: the median probabilitie for the chosen alternative is 68%. Our research stresses the importance of the barrier effect of borders in airport choice: even when traveling across borders in the European sky, national borders remain important.     

Offsite passenger service facilities: A viable option for airport access?

Offsite passenger service facilities transfer passengers from a common location to an airport and may provide additional services such as baggage handling and passenger check-in. Although they are conceptually promising, there is a lack of modern methods specifically tailored to forecast their demand. This paper reports on the development of two sequential models that forecast demand for an offsite facility. Models were calibrated based on data collected at six airports in California, Maryland, Massachusetts, and Virginia. The results showed that likely candidates for an offsite facility are airports that are not easily accessible, and departing air passengers with early morning flight departure times and high variability in ground travel times to the airport. A case study demonstrates the application of the models to Virginia’s Richmond International Airport.     

Airport and route classification by modelling flight delay propagation

Flight delay can be divided into the root and propagated delays for identification and analysis of airports/routes that have a great influence on actual flight delay using flight operations raw data (tower logs) for South Korean domestic flights. In addition, the presented concept of “generated delay” classifies airports as affecting other airport delays or affected by other airport delays. The generated delay refers to the delay time at a particular airport/route, and this delay thereafter actually propagates to other airports/routes. In this study, the generated and propagated delays were displayed on a two-dimensional graph, and the airports/routes were grouped according to delay characteristics. Group A represented airports with high generated and propagated delays, and group B represented airports that are highly affected by delays of preceding airports/routes. Group C represents airports where newly formed delays affect other airport delays, but these airports mitigate delays from other airports. Airports in group D have relatively low delays and propagation. Thus, we targeted airports belonging to groups A and C because of their delay propagation impact on other routes/airports, which must be reduced by decreasing the root delay from targeted routes/airports. Among the airports, Jeju international airport (CJU) had the highest average delay time and propagated flight delay time with similar averaged generated delay times. Among the routes, departure flights from various airports to CJU had significant propagation effects on the subsequent flights. CJU and related routes have a very large impact on domestic flight delays because South Korean domestic airline routes are concentrated on CJU. However, there has been no quantitative analysis, and it is meaningful that the quantitative analysis results were presented in this study. In addition, we suggest that other airports such as GMP (Gimpo), CJJ (Cheongju), WJU (Wonju), and KUV (Gunsan) have a significant impact on domestic flight delays.