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Journal articles on the topic 'Airline Schedule'

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Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

Massoud, Bazargan, and Xiaoxu Chen. "Airline Hangars Balanced Manpower Utilization." International Journal of Aviation Systems, Operations and Training 3, no. 1 (January 2016): 49–58. http://dx.doi.org/10.4018/ijasot.2016010104.

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Airlines on average spend 10%-15% of their total operating cost on aircraft maintenance. Most of the airlines conduct their light maintenance checks in-house. These light checks have a major impact on flight schedules, delay rates and cost. A chronic challenge with airlines is assigning light maintenance checks to the hangars while achieving a balanced utilization of the manpower. This study considers airline's daily flight schedule, manpower needed for each check, the availability of manpower and expertise at each hangar, capitalizes on flexibility of performing aircraft light maintenance checks among potential hangars aiming at balancing manpower utilization. The results are very encouraging compared with existing practices. The model not only identifies which maintenance checks to be performed at different hangars but provides recommendations in terms of increasing/decreasing manpower needs. An airline application reveals that the model can help airlines with their strategic manpower planning strategies to achieve a high and balanced utilization of their maintenance manpower.

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2

Zagrajek, Paweł, and Adam Hoszman. "Impact of Ground Handling on Air Traffic Volatility." Journal of Management and Financial Sciences, no. 33 (July 27, 2019): 147–55. http://dx.doi.org/10.33119/jmfs.2018.33.8.

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Ground handling services constitute an important element of airline operations and significantly affect traffic stability and punctuality. In this article, the existing and potential impact of airline handling on air traffic volatility is reviewed from the point of view of airlines and ground operations. The issues of airline expectations towards ground handling agents (including handling rates, turnaround time, passenger services, and ramp services) are explored. In addition, the impact of an airline’s schedule and the volatility of its operations on the performance and operational requirements of handling agents is discussed, including actions required by handling agents in response to the above challenges. The mechanism of how the volatility of an airline’s schedule and its operations may impact the volatility of ground operations (directly and indirectly) is considered. The statistics of airline delays caused by ground operations are presented and discussed. The issue of the correctness of air traffic delays reporting by airlines is investigated.Furthermore, this article investigates internal factors of ground handling agents and their impact on air traffic volatility. The existing and potential considerations discussed include staff management issues (in particular, employee rotation resulting in staff shortages and service quality, including punctuality), resources management, the ground service support equipment (including new developments aiming at limiting ground safety incidents), and their impact on performance.

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3

Yimga, Jules. "Competition and Schedule Padding in the US Airline Industry." Review of Network Economics 20, no. 1 (March 1, 2021): 1–33. http://dx.doi.org/10.1515/rne-2021-0016.

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Abstract Disclosure programs can help consumers with limited information about product quality make better purchase decisions. A quality disclosure mandate such as the On-Time Disclosure Rule in the U.S. that requires airlines to provide information on the quality of their products can be beneficial, but can also be counterproductive if it encourages airlines to act deceptively by “gaming” the system. If airlines care about public perceptions of their on-time record, they have an incentive to improve their on-time performance ranking by resorting to unscrupulous means such as padding their schedules beyond normal time required to absorb scheduling stochastic fluctuations. This study investigates the impact of competition on airline schedule padding. We construct a measure for schedule padding under different optimal flight time choices. Using different measures of market structure, we find that more competitive (concentrated) markets are subject to less (more) schedule padding.

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Munoz, Claudia, Henry Laniado, and Jorge Córdoba. "Airline choice model for an international round-trip flight considering outbound and return flight schedules." Archives of Transport 54, no. 2 (June 30, 2020): 75–93. http://dx.doi.org/10.5604/01.3001.0014.2969.

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This paper quantified the impact of outbound and return flight schedule preferences on airline choice for international trips. Several studies have used airline choice data to identify preferences and trade-offs of different air carrier service attributes, such as travel time, fare and flight schedule. However, estimation of the effect return flight schedules have on airline choice for an international round-trip flight has not yet been studied in detail. Therefore, this study introduces attributes related to return flight characteristics and round-trip flight schedule interaction into the airline choice models, which have not previously been reported in the literature. We developed a stated preference survey that includes round-trip fares based on flight schedule combinations and the number of days prior to departure fares was purchased. We applied modelling techniques using a set of stated preference data. A mixed logit model was tested for the presence of heterogeneity in passengers' preferences. Our results indicated that models with attributes related to return flight and its interaction with outbound flight attributes have a superior fit compared with models only based on attributes reported in the literature review. The model found shows that airfare, travel time, arrival preference schedule in the outward journey, departure preference in the return journey and the schedule combination of round-trip flight are significantly affecting passenger choice behaviour in international round-trip flights. Sensitivity analysis of airline service characteristics and their marketing implications are conducted. The analysis reports seven policies with the greatest impact on each airline choice probabilities. It shows that by reducing travel time and airfare and by adopting an afternoon and night schedule preference for outbound and return flight, respectively, the highest probability on airline choice would be reached. This research contributes to the current literature by enhancing the understanding of how passengers choose airlines, considering both outbound and inbound journey characteristics. Thus, this study provides an analytical tool designed to provide a better understanding of international round-trip flight demand determinants and support carrier decisions.

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5

Brueckner, Jan K., and Ricardo Flores-Fillol. "Airline Schedule Competition." Review of Industrial Organization 30, no. 3 (August 18, 2007): 161–77. http://dx.doi.org/10.1007/s11151-007-9140-1.

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6

Law, Colin. "The study of customer relationship management in Thai airline industry: A case of Thai travelers in Thailand." Journal of Airline and Airport Management 7, no. 1 (February 17, 2017): 13. http://dx.doi.org/10.3926/jairm.86.

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Purpose: This paper offer marketing strategy suggestion to the airlines operating within the Thai aviation market. It identifies the recommended motivational factors that influence the airline customers’ decision to their airline choices. Airlines use different customer relationship management programs to attract returning customers. This paper suggested the most attractive motivation factors for Thailand's air travel market.Design/methodology/approach: This research paper is an attempt to study and identify the factors, including loyalty program, distribution channel, customer services, promotions and other influence causes that affected the customer preference in the airline ticket purchasing behavior in Thailand.A questionnaire survey was conducted with the sample identified through unrestricted non probability sampling technique at four major airports in Thailand. The data collected are analyzed to identify the favorable drivers that lead to customer decision on airline choice.Findings: The result from the study has demonstrated that price, and promotion has a significant impact on customer preference and positively leads to repurchase intention for their future travel. Moreover, flight schedules are also a main factor influencing the travelers’ final decision on airline choice. However, when the promotional strategies and schedule are comparable between airlines, customers are attracted by the airline amenities and services. Loyalty program (frequent-flier program flier program) is showing a less attractive motivator while distribution channel demonstrates the least important affecting the travelers’ choice of airline.Originality/value: The paper begins with an overview of previous research in the area of airlines customer relationship management and then moves on to what is currently being implemented by the airlines. The authors then propose several customer relationship strategies and identify the most attractive one that motivates the Thai consumers.

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7

Cadarsoa, Luis, and Ángel Marín. "Integrated Robust Airline Schedule Development." Procedia - Social and Behavioral Sciences 20 (2011): 1041–50. http://dx.doi.org/10.1016/j.sbspro.2011.08.113.

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8

Mhlanga, Oswald, Jacobus Steyn, and John Spencer. "The airline industry in South Africa: drivers of operational efficiency and impacts." Tourism Review 73, no. 3 (August 20, 2018): 389–400. http://dx.doi.org/10.1108/tr-07-2017-0111.

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Purpose The airline industry is structurally challenged by its very nature, because of high overhead and capital costs. This is further exacerbated by macro-predictability and micro-uncertainty, thereby making it difficult for airlines in South Africa to attain operational efficiency. The purpose of this study is to identify drivers of operational efficiency and their impacts on airline performances in South Africa. Design/methodology/approach An extensive data collection using primary and secondary sources enabled the researchers to gather data on all the airlines operating in South Africa, for the period of 2012-2016, on a variety of parameters. A two-stage empirical analysis was carried out, which involved estimation of operational efficiencies during the first stage by using data envelopment analysis (DEA) and determination of performance drivers during the second stage by using a two-way random-effects generalised least squares regression and also a Tobit model. Findings From the study, it is clear that two structural drivers, namely, “aircraft size” and “seat load factor”, and two executional drivers, namely, “low cost business model” and “revenue hours per aircraft”, significantly impacted (p < 0.05) positively on airline efficiencies in South Africa. To improve efficiency, management should first concentrate on the drivers that can be changed in the short-term (executional drivers) and later focus on the drivers that require long-term planning (structural drivers). However, among the structural drivers, only “aircraft families” had a negative impact on airline efficiencies, whilst among executional drivers, only “block hours” negatively impacted on airline efficiencies. Research limitations/implications Despite the importance of this study, it is not free of limitations. Firstly, because of the small size of the industry, fewer airlines and lack of detailed data, the study could not consider other important factors such as optimal routing and network structure. Secondly, although non-aeronautical revenues have become increasingly important in airline management, they were not included in this study. Further studies may investigate the impact of these factors on airline efficiency. Practical implications The results have potential policy implications. Firstly, as the domestic airline market in South Africa is too small to operate with a smaller aircraft efficiently, airlines that intend to make use of smaller aircraft should first identify niche markets where they can have a route monopoly, such as SA Airlink. Secondly, as block time negatively affected airline efficiency, airlines can undertake schedule adjustments to reduce block time and thus improve technical efficiency. Originality/value This paper is a first attempt to identify drivers of operational efficiency in the airline industry in South Africa. The results indicate that DEA is a useful tool to identify factors impacting airline efficiency and could improve airline performances in South Africa.

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9

Tao, Mei, Lan Ma, and Yiming Ma. "Flight schedule adjustment for hub airports using multi-objective optimization." Journal of Intelligent Systems 30, no. 1 (January 1, 2021): 931–46. http://dx.doi.org/10.1515/jisys-2020-0114.

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Abstract Based on the concept of “passengers self-help hubbing,” we build a flight schedule optimization model where maximizing the number of feasible flight connections, indicating transfer opportunities, as one objective and minimizing total slot displacements as the other objective. At the same time, the “Demand Smoothing Model” is introduced into the flight schedule optimization model to reduce the queuing delays for arrival and departure flights. We take into account all aircraft itineraries, the difficulty level of schedule coordination, and the maximum displacement of any single flight acceptable to airlines when optimizing flight schedule. Given an original schedule, the model produces a feasible modified schedule that obeys the slot limits specified for an airport without canceling any flights, increases transfer opportunities, and improves on-time performance for hub airports while reducing interference with airline scheduling preferences. The model was verified with the operating data of the Urumqi international airport, and the results show that minor adjustments to flight schedules can increase the transfer opportunities of the airport and significantly reduce flight queuing delays.

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Lagos, Carlos, Felipe Delgado, and Mathias A. Klapp. "Dynamic Optimization for Airline Maintenance Operations." Transportation Science 54, no. 4 (July 2020): 998–1015. http://dx.doi.org/10.1287/trsc.2020.0984.

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The occurrence of unexpected aircraft maintenance tasks can produce expensive changes in an airline’s operation. When it comes to critical tasks, it might even cancel programmed flights. Despite this, the challenge of scheduling aircraft maintenance operations under uncertainty has received limited attention in the scientific literature. We study a dynamic airline maintenance scheduling problem, which daily decides the set of aircraft to maintain and the set of pending tasks to execute in each aircraft. The objective is to minimize the expected costs of expired maintenance tasks over the operating horizon. To increase flexibility and reduce costs, we integrate maintenance scheduling with tail assignment decisions. We formulate our problem as a Markov decision process and design dynamic policies based on approximate dynamic programming, including value function approximation, rolling horizon techniques, and a hybrid policy between the latter two that delivers the best results. In a case study based on LATAM airline, we show the value of dynamic optimization by testing our best policies against a simple airline decision rule and a deterministic relaxation with perfect future information. We suggest to schedule tasks requiring less resources first to increase utilization of residual maintenance capacity. Finally, we observe strong economies of scale when sharing maintenance resources between multiple airlines.

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11

Jayam, Harika, and Linda K. Nozick. "Understanding the Trade-Off Between Maximum Passenger Throughput and Airline Equity in Allocating Capacity Under Severe Weather Conditions." Transportation Research Record: Journal of the Transportation Research Board 2626, no. 1 (January 2017): 18–24. http://dx.doi.org/10.3141/2626-03.

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When the capacity at an airport is reduced because of weather conditions, a ground delay program (GDP) is implemented to resolve the discrepancy between demand for arrival slots and the available arrival slots on a given day. GDPs currently ration the available arrival slots via the proportion of arrivals that exist in the schedule by airline (this practice is termed ration by schedule) with an emphasis on equity among the airlines. Existing rationing schemes do not explicitly consider the number of passengers delayed. This study examined the passenger impacts of a focus on seat throughput in reduced capacity conditions for a GDP at a single airport with consideration for airline equity. An optimization model was developed by using the number of seats available in an aircraft as a proxy for number of passengers and an equity term to estimate airline equity implications. A comparison of the current GDP rationing scheme with one focused on seat delay showed that with no change in the total flight delay time periods, passenger throughput could be improved with a threshold placed on equity. The trade-off between airline equity and passenger throughput and the implications of these results are discussed.

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12

Teodorović, Dušan, and Goran Stojković. "Model to Reduce Airline Schedule Disturbances." Journal of Transportation Engineering 121, no. 4 (July 1995): 324–31. http://dx.doi.org/10.1061/(asce)0733-947x(1995)121:4(324).

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13

Barnhart, Cynthia, and Amy Cohn. "Airline Schedule Planning: Accomplishments and Opportunities." Manufacturing & Service Operations Management 6, no. 1 (January 2004): 3–22. http://dx.doi.org/10.1287/msom.1030.0018.

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14

Abdelghany, Ahmed, Khaled Abdelghany, and Farshid Azadian. "Airline flight schedule planning under competition." Computers & Operations Research 87 (November 2017): 20–39. http://dx.doi.org/10.1016/j.cor.2017.05.013.

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15

Pavlovic, Danica. "Sensitivity analysis of airline schedule optimization (ASO) advanced model." Journal of Air Transport Studies 1, no. 2 (July 1, 2010): 1–26. http://dx.doi.org/10.38008/jats.v1i2.107.

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The ASO model provides a proposal for a new flight schedule, in situations when a carrier’s flight scheduled is disrupted, and which would minimize the negative effects of the disruption. The objective function of the model is a mathematical formulation of the company’s goals and preferences, where all assumptions and operational constraints must be satisfied. The disruption costs are given in weighted coefficients which present the penalties that can be changed by the dispatcher. One of the goals was to test to what degree the generated solutions are sensitive to changes in penalty values.

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Gönsch, Jochen. "Airline Schedule Planning - Grundlagen und aktuelle Entwicklungen." WiSt - Wirtschaftswissenschaftliches Studium 39, no. 5 (2010): 230–35. http://dx.doi.org/10.15358/0340-1650-2010-5-230.

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17

Schaefer, Andrew J., and George L. Nemhauser. "Improving airline operational performance through schedule perturbation." Annals of Operations Research 144, no. 1 (April 2006): 3–16. http://dx.doi.org/10.1007/s10479-006-0003-1.

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18

Kim, Daeki, and Cynthia Barnhart. "Flight schedule design for a charter airline." Computers & Operations Research 34, no. 6 (June 2007): 1516–31. http://dx.doi.org/10.1016/j.cor.2005.07.010.

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19

Yimga, Jules, and Javad Gorjidooz. "Airline schedule padding and consumer choice behavior." Journal of Air Transport Management 78 (July 2019): 71–79. http://dx.doi.org/10.1016/j.jairtraman.2019.05.001.

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Shiau, Jiun-Yan, Ming-Kung Huang, and Chu-Yi Huang. "A Hybrid Personnel Scheduling Model for Staff Rostering Problems." Mathematics 8, no. 10 (October 3, 2020): 1702. http://dx.doi.org/10.3390/math8101702.

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The problem of staff scheduling in the airline industry is extensively investigated in operational research studies because efficient staff employment can drastically reduce the operational costs of airline companies. Considering the flight schedule of an airline company, staff scheduling is the process of assigning all necessary staff members in such a way that the airline can operate all its flights and construct a roster line for each employee while minimizing the corresponding overall costs for the personnel. This research uses a rostering case study of the ground staff in the aviation industry as an example to illustrate the application of integrating monthly and daily schedules. The ground staff in the aviation industry case is a rostering problem that includes three different types of personnel scheduling results: fluctuation-centered, mobility-centered, and project-centered planning. This paper presents an integrated mixed integer programming (MIP) model for determining the manpower requirements and related personnel shift designs for the ground staff at the airline to minimize manpower costs. The aim of this study is to complete the planning of the monthly and daily schedules simultaneously. A case study based on real-life data shows that this model is useful for the manpower planning of ground services at the airline and that the integrated approach is superior to the traditional two-stage approach.

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Li, Li Sha. "Research on Airline Operational Control Model Based on Analytic Hierarchy Process." Applied Mechanics and Materials 496-500 (January 2014): 1365–68. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1365.

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With expansion of airlines fleet capacity in China, airlines pay more attention to airline profit, service evaluation, etc., besides flight safety. Therefore it is important to study on operational control approaches that can promote operational efficiency, guarantee flight on-schedule rate and reduce operational cost. In this paper, an Analytic Hierarchy Process is employed to build a related-factor model mainly influencing dispatchers making decision in the operational control process of airlines. This process makes the complicated decision-making system hierarchic and analyzes the importance of all related factors by comprising their importance in a hierarchical way. Through an algorithmic example and data analysis, the operational control decision-making model of an assisting nature based on hierarchic analysis in this paper can provide quantitative basis for final decision making.

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Babić, Obrad, Milica Kalić, Goran Pavković, Slavica Dožić, and Mirjana Čangalović. "Heuristic approach to the airline schedule disturbances problem." Transportation Planning and Technology 33, no. 3 (April 2010): 257–80. http://dx.doi.org/10.1080/03081061003732318.

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23

Eltoukhy, Abdelrahman E. E., Felix T. S. Chan, and S. H. Chung. "Airline schedule planning: a review and future directions." Industrial Management & Data Systems 117, no. 6 (July 10, 2017): 1201–43. http://dx.doi.org/10.1108/imds-09-2016-0358.

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Purpose The purpose of this paper is twofold: first to carry out a comprehensive literature review for state of the art regarding airline schedule planning and second to identify some new research directions that might help academic researchers and practitioners. Design/methodology/approach The authors mainly focus on the research work appeared in the last three decades. The search process was conducted in database searches using four keywords: “Flight scheduling,” “Fleet assignment,” “Aircraft maintenance routing” (AMR), and “Crew scheduling”. Moreover, the combination of the keywords was used to find the integrated models. Any duplications due to database variety and the articles that were written in non-English language were discarded. Findings The authors studied 106 research papers and categorized them into five categories. In addition, according to the model features, subcategories were further identified. Moreover, after discussing up-to-date research work, the authors suggested some future directions in order to contribute to the existing literature. Research limitations/implications The presented categories and subcategories were based on the model characteristics rather than the model formulation and solution methodology that are commonly used in the literature. One advantage of this classification is that it might help scholars to deeply understand the main variation between the models. On the other hand, identifying future research opportunities should help academic researchers and practitioners to develop new models and improve the performance of the existing models. Practical implications This study proposed some considerations in order to enhance the efficiency of the schedule planning process practically, for example, using the dynamic Stackelberg game strategy for market competition in flight scheduling, considering re-fleeting mechanism under heterogeneous fleet for fleet assignment, and considering the stochastic departure and arrival times for AMR. Originality/value In the literature, all the review papers focused only on one category of the five categories. Then, this category was classified according to the model formulation and solution methodology. However, in this work, the authors attempted to propose a comprehensive review for all categories for the first time and develop new classifications for each category. The proposed classifications are hence novel and significant.

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Graf, Vojtech, Dusan Teichmann, Jiri Horinka, and Michal Dorda. "Dynamic Model for Scheduling Crew Shifts." Mathematical Problems in Engineering 2020 (May 30, 2020): 1–12. http://dx.doi.org/10.1155/2020/5372567.

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In regular as well as nonscheduled air transport, extraordinary situations occasionally occur, which may fundamentally disrupt the flight schedule. Fundamental disruptions of flight schedules affect not only passengers but also the airline. One of the areas that are negatively affected by the disruption is the crew plan. Due to extraordinary events, it happens that a flight is delayed, and the crew will not be at the destination airport at the prescribed time and the airline will not be able to assign it on further flights according to the original plan. Such situations can be resolved either by deploying any other available crew or by delaying the flight appropriately until the previously planned crew is available. Assigning a new crew entails additional costs for the airline, as it has to assign more flight staff than had been originally planned. Furthermore, delayed flights lead to paying passengers financial compensation, incurring additional costs for airlines. Therefore, it is important that the airline is able to resolve any irregularity situations so that the additional costs incurred to deal with the irregularity situations are kept at a minimum. The paper presents one possible approach, a mathematical model that can be used to solve such a situation. The presented mathematical model may be the basis for the decision support system of the operations center worker who is responsible for the operational management of flight crews. The model will primarily aim at smaller airlines that cannot afford expensive software and often rely on manual solutions. However, a manual solution may not always be the best, as the operator, who plans the processes, may not consider all the constraints. Another important factor that makes the decision processes more difficult is that it is usually necessary to decide in a short period of time. The solution proposed in this paper will allow the operator to make a quick decision that will also be the most advantageous for the airline. This is because the proposed method is an exact approach, which guarantees finding the optimum solution. In this article, we are only dealing with pilot crews.

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Özkır, Vildan, and Mahmud Sami Özgür. "Two-Phase Heuristic Algorithm for Integrated Airline Fleet Assignment and Routing Problem." Energies 14, no. 11 (June 5, 2021): 3327. http://dx.doi.org/10.3390/en14113327.

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High profitability and high costs have stiffened competition in the airline industry. The main purpose of the study is to propose a computationally efficient algorithm for integrated fleet assignments and aircraft routing problems for a real-case hub and spoke airline planning problem. The economic concerns of airline operations have led to the need for minimising costs and increasing the ability to meet rising demands. Since fleets are the most limited and valuable assets of airline carriers, the allocation of aircraft to scheduled flights directly affects profitability/market share. The airline fleet assignment problem (AFAP) addresses the assignment of aircraft, each with a different capacity, capability, availability, and requirement, to a given flight schedule. This study proposes a mathematical model and heuristic method for solving a real-life airline fleet assignment and aircraft routing problem. We generate a set of problem instances based on real data and conduct a computational experiment to assess the performance of the proposed algorithm. The numerical study and experimental results indicate that the heuristic algorithm provides optimal solutions for the integrated fleet assignment and aircraft routing problem. Furthermore, a computational study reveals that compared with the heuristic method, solving the mathematical model takes significantly longer to execute.

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Dorneich, Michael C., Stephen D. Whitlow, Christopher A. Miller, and John A. Allen. "A Superior Tool for Airline Operations." Ergonomics in Design: The Quarterly of Human Factors Applications 12, no. 2 (April 2004): 18–23. http://dx.doi.org/10.1177/106480460401200205.

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Lohatepanont, Manoj, and Cynthia Barnhart. "Airline Schedule Planning: Integrated Models and Algorithms for Schedule Design and Fleet Assignment." Transportation Science 38, no. 1 (February 2004): 19–32. http://dx.doi.org/10.1287/trsc.1030.0026.

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Sudjono, Idjon. "Dampak Penghentian Operasi PT. Mandala Airlines di Bandara Ahmad Yani Semarang." WARTA ARDHIA 37, no. 3 (September 30, 2011): 200–210. http://dx.doi.org/10.25104/wa.v37i3.167.200-210.

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The impact of ceasing temporary operation PT. Mandala Arilines in Achmad Yani Airport at Semarang on January 13th 2011 will effect toward the decreasing air of transport capacity of Semarang—Jakarta routes and Semarang-Banjarmasin routes. In hence, the route Semarang-Banjarmasin flown by Mandala airlines seven times in a week, and route Semarang-Jakarta twelve times per week. By using load factor comparative method, from the result of the research was obtained the increasing of load factor to all routes of airline schedule flow by mandala.

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Williams, J. E. D. "Anderson Memorial Lecture: On the Navigation of London Taxis and Certain Flying Machines." Journal of Navigation 39, no. 3 (September 1986): 394–400. http://dx.doi.org/10.1017/s0373463300000862.

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Whereas the proper object of all commercial transportation is profit-making, the navigational objectives of taxis and of airliners differ remarkably. In airlines navigation only affects product quality and operating costs but in taxis the revenue (the fare on the meter) is a function of the navigation. Regularity of service is meaningless to taxis whereas regularity of schedule keeping is an imperative of airline navigation because it is only possible to offer air fares a full order lower than taxi fares on aeroplanes costing up to $200,000 a seat by achieving high equipment utilization. Many taxi drivers hire their cabs at a weekly rate which includes maintenance and repair but not fuel. They therefore have a direct interest in the cost of fuel but not in wear and tear of machinery. Finally, taxi drivers are self-employed businessman whose income depends entirely on their navigational skills.

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Babic, Obrad, Milica Kalic, Danica Babic, and Slavica Dozic. "The airline schedule optimization model: validation and sensitivity analysis." Procedia - Social and Behavioral Sciences 20 (2011): 1029–40. http://dx.doi.org/10.1016/j.sbspro.2011.08.112.

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Şafak, Özge, Alper Atamtürk, and M. Selim Aktürk. "Accommodating new flights into an existing airline flight schedule." Transportation Research Part C: Emerging Technologies 104 (July 2019): 265–86. http://dx.doi.org/10.1016/j.trc.2019.05.010.

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Jiang, Hai, and Cynthia Barnhart. "Robust airline schedule design in a dynamic scheduling environment." Computers & Operations Research 40, no. 3 (March 2013): 831–40. http://dx.doi.org/10.1016/j.cor.2011.06.018.

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Brueckner, Jan K., Achim I. Czerny, and Alberto A. Gaggero. "Airline schedule buffers and flight delays: A discrete model." Economics of Transportation 26-27 (June 2021): 100218. http://dx.doi.org/10.1016/j.ecotra.2021.100218.

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Dennis, Nigel, and David Pitfield. "A Tale of Two Cities: The Impact of Airline Mergers and Consolidation at London and New York." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 23 (August 15, 2018): 1–7. http://dx.doi.org/10.1177/0361198118758336.

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This paper considers the changes to airline networks, service patterns, and competition that have taken place as a result of recent airline mergers on both sides of the North Atlantic as well as through transatlantic alliances. Capacity, frequency and the competitive position are studied at London and New York with the use of schedule data within different markets in which measures of market concentration are evaluated. International Civil Aviation Organization data is employed to examine load factors on international routes, and UK Civil Aviation Authority data to consider the distribution of traffic between airports in London. It is shown that the effectiveness of the hubs has increased, with enhanced efficiency for surviving airlines, through fewer competitors, an enlarged network and greater control of capacity. Potential concerns are identified however, regarding passenger choice, pricing, and service options that suggest the industry is moving toward an oligopoly. Smaller cities are also seen to be the losers from consolidation with slot divestments favoring increased service in the dense markets, with many regional links being axed altogether. The paper supplements the literature on airline consolidation, with a particular focus on the two biggest markets in the world—London and New York—which demonstrate some similar but also some different issues. Both airline network impacts and choice, and service for local consumers are considered.

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Oluwafisayo T., Ayo-Agunbiade, and Stephens Mobolaji S. "Causal Factors of Flight Delay in Nigerian Airport: A Case Study of Murtala Muhammed International Airport." Bangladesh Journal of Multidisciplinary Scientific Research 1, no. 2 (August 16, 2019): 54–59. http://dx.doi.org/10.46281/bjmsr.v1i2.381.

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Delay is a prominent event mostly experienced at the airport by both airline and passengers. Globally delay is permitted at 15mins later than the scheduled time. Assessing the level of delay in the airport is a major criterion for measuring airport performance. Aircraft not adhering to schedule flight results in increased airport congestion, cancellation flight and flight delay. This study made use of primary data through well-structured questionnaires to obtain information from selected NAMA Staff at the Murtala Muhammed International Airport (MMIA). Operational delay report for a month and Airlines flight were examined for two months under the MMA2 to know the deviation of scheduled flight time from actual flight time. Descriptive Analysis, Wilcoxon Rank test, Factor Analysis and Step Wise Regression were the statistical tools deployed for this research. Findings showed that on a monthly base, 63% of the domestic traffic flows are delayed. Some factors responsible for delay were considered: aircraft damage, bad weather, aircraft maintenance, VIP movement and fueling are the major factor responsible for delay of aircraft Movement.

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Rosenow, Judith, Philipp Michling, Michael Schultz, and Jörn Schönberger. "Evaluation of Strategies to Reduce the Cost Impacts of Flight Delays on Total Network Costs." Aerospace 7, no. 11 (November 18, 2020): 165. http://dx.doi.org/10.3390/aerospace7110165.

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Competitive price pressure and economic cost pressure constantly force airlines to improve their optimization strategies. Besides predictable operational costs, delay costs are a significant cost driver for airlines. Especially reactionary delay costs can endanger the profitability of such a company. These time-dependent costs depend on the number of sensitive transfer passengers. This cost component is represented by the number of missed flights and the connectivity of onward flights, i.e., the offer of alternative flight connections. The airline has several options to compensate for reactionary delays, for example, by increasing cruising speeds, shortening turnaround times, rebookings and cancellations. The effects of these options on the cost balance of airline total operating costs have been examined in detail, considering a flight-specific number of transfer passengers. The results have been applied to a 24-h rotation schedule of a large German hub airport. We found, that the fast turnaround and increasing cruise speed are the most effective strategies to compensate for passenger-specific delay costs. The results could be used in a multi-criteria trajectory optimization to find a balance between environmentally-driven and cost-index-driven detours and speed adjustments.

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Che Yahya, Norliza, Hanizatul Nadia Harun, and Azreen Roslan. "DETERMINANTS OF FINANCIAL LEVERAGE: THE CASE OF LARGEST AIRLINES IN ASIA." ADVANCES IN BUSINESS RESEARCH INTERNATIONAL JOURNAL 5, no. 2 (September 30, 2019): 127. http://dx.doi.org/10.24191/abrij.v5i2.10011.

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This study is developed to examine the determinants of financial leverage of capital structure of airlines industry in Asia for the period from 2012 to 2016. Airlines industry is selected as sample of this study as it reflects the highest energy intensive industry based on the largest amount of fuel consumption on the business (Bratlie, 2012). This study defined airline as an operation entity that provides services to carry people and freight by air with schedule routes provided. This study, using panel data analysis, reports that size and growth have a positive relationship to financial leverage. In contrast, profitability and age are negatively related. Regardless of the signs, all the explanatory variables in this study are strongly significant in determining financial leverage (measured by debt to equity ratio).

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Beatty, Roger, Rose Hsu, Lee Berry, and James Rome. "Preliminary Evaluation of Flight Delay Propagation through an Airline Schedule." Air Traffic Control Quarterly 7, no. 4 (October 1999): 259–70. http://dx.doi.org/10.2514/atcq.7.4.259.

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Raut, Sumit, Viswanath Kumar Ganesan, and J. K. Jha. "A novel constraint propagation approach for airline schedule design problem." International Journal of Mathematics in Operational Research 10, no. 4 (2017): 485. http://dx.doi.org/10.1504/ijmor.2017.084162.

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Teodorović, Dušan. "A model for designing the meteorologically most reliable airline schedule." European Journal of Operational Research 21, no. 2 (August 1985): 156–64. http://dx.doi.org/10.1016/0377-2217(85)90027-x.

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Kotas, Jakob. "A linear programming model for airline schedule recovery after disruption." International Journal of Operational Research 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijor.2020.10039384.

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Evler, Jan, Ehsan Asadi, Henning Preis, and Hartmut Fricke. "Airline ground operations: Optimal schedule recovery with uncertain arrival times." Journal of Air Transport Management 92 (May 2021): 102021. http://dx.doi.org/10.1016/j.jairtraman.2021.102021.

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Evler, Jan, Ehsan Asadi, Henning Preis, and Hartmut Fricke. "Airline ground operations: Schedule recovery optimization approach with constrained resources." Transportation Research Part C: Emerging Technologies 128 (July 2021): 103129. http://dx.doi.org/10.1016/j.trc.2021.103129.

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Josephat, Peter, and Abbas Ismail. "A Logistic Regression Model of Customer Satisfaction of Airline." International Journal of Human Resource Studies 2, no. 4 (December 14, 2012): 255. http://dx.doi.org/10.5296/ijhrs.v2i4.2868.

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Evaluation of customer satisfaction differs from one study to another. Studies have been differing with their focus and coverage. Most of studies focused on evaluating factors influencing customer satisfaction or associate customer satisfaction and quality of services. This paper used logistic regression to develop customer satisfaction model for Precision Air. Five dimensions or variables have been considered: on time performance; aircraft safety; schedule integrity; on board services; and customer service. Data used in this paper were collected from four major regions with many flights. These include Dar es Salaam, Mwanza, Arusha and Kilimanjaro. A sample size of 272 passengers was selected. Convenience sampling was used to select the respondents. Primary data were collected in the field through questionnaire. Findings showed that out of the five independent variables only one variable is negatively related with satisfaction of airline passengers (customer services). In contrast, on time performance was satisfactory variable by most of passengers compared to the rest of explanatory variables. Airline safety, schedule integrity and on board services are positively related with passengers satisfaction. Relationship between customer services and satisfaction are negatively related which implies that, there is a need of finding strategies to improve customer services to customers. The paper recommends that the airline should maintain and improve on time performance as this is crucial variable for passenger’s satisfaction but other variables need more improvement. Keywords: Logistic, Logit, Dimension, On Time Performance, Aircraft Safety, Schedule Integrity, On Board Services, Customer Service

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Bazargan, Massoud. "Airline Hangars Balanced Manpower Utilization." International Journal of Aviation Systems, Operations and Training 3, no. 2 (July 2016): 36–49. http://dx.doi.org/10.4018/ijasot.2016070104.

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Airlines on average spend 10%-15% of their total operating cost on aircraft maintenance checks. Many airlines conduct their light checks in-house. These checks are inherently very labor intensive. This study offers a mathematical model to help airlines with scheduling their in-house light maintenance checks to achieve a high and even utilization of manpower among all hangars. The model attempts to minimize the utilization imbalances by assigning light maintenance checks, during their feasible time-windows, to available and certified hangars on daily, weekly and monthly. It incorporates daily flight schedule, maintenance requirements for each fleet type, certification and availability of manpower at each hangar. Furthermore, the model highlights the utilization imbalances and thus provides some guidelines in terms of increasing/decreasing manpower capacities at each hangar. The model is applied to 3 US and 2 European airlines with encouraging results.

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Dožić, Slavica, Milica Kalić, and Obrad Babić. "Heuristic Approach to the Airline Schedule Disturbances Problem: Single Fleet Case." Procedia - Social and Behavioral Sciences 54 (October 2012): 1232–41. http://dx.doi.org/10.1016/j.sbspro.2012.09.837.

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Rupp, Nicholas G., George M. Holmes, and Jeff DeSimone. "Airline Schedule Recovery after Airport Closures: Empirical Evidence since September 11." Southern Economic Journal 71, no. 4 (April 1, 2005): 800. http://dx.doi.org/10.2307/20062081.

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Yan, Shangyao, Chin-Hui Tang, and Chong-Lan Shieh. "A Simulation Framework for Evaluating Airline Temporary Schedule Adjustments Following Incidents." Transportation Planning and Technology 28, no. 3 (June 2005): 189–211. http://dx.doi.org/10.1080/03081060500120324.

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Ruppy, N. G., G. M. Holmes, and J. Desimone. "Airline Schedule Recovery After Airport Closures: Empirical Evidence Since September 11th." Revista Organizações em Contexto 3, no. 6 (December 31, 2007): 153–79. http://dx.doi.org/10.15603/1982-8756/roc.v3n6p153-179.

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Brueckner, Jan K., Achim I. Czerny, and Alberto A. Gaggero. "Airline mitigation of propagated delays via schedule buffers: Theory and empirics." Transportation Research Part E: Logistics and Transportation Review 150 (June 2021): 102333. http://dx.doi.org/10.1016/j.tre.2021.102333.

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