Relevant bibliographies by topics / Airline Network

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Airline Network'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Airline Network"

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Hogendorn, Christiaan. "Niche Networks for New Entrants." Transportation Research Record: Journal of the Transportation Research Board 1567, no. 1 (1997): 17–25. http://dx.doi.org/10.3141/1567-03.

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How new entrant carriers may use returns to airline networks in competition is discussed. In addition to overall returns to scope and density, there are more localized returns that are based on network shape. A network shape index, which is a measure of airline network concentration based on the Herfindahl-Hirschman index, is described. Airlines have chosen many different shapes as measured by the network shape index, and new entrants tend to be shaped differently from major airlines. A model of new entrant profitability relative to the major airlines is developed. New entrants whose network shape indices are substantially different from the major airlines have niche networks, and the model indicates that niche networks are associated with higher profitability.
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Lu, Jin-Long, and Pei-Ya Siao. "Determining the antecedents and consequences of the airline brand personality." Journal of Airline and Airport Management 9, no. 1 (2019): 1. http://dx.doi.org/10.3926/jairm.121.

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Purpose: This study investigates air passengers’ perceptions of the brand personalities of airlines and explores the relationships between the brand personality and its antecedent factor, the country-of-origin of the airlines, and the consequent factor which is the purchase intentions to the corresponding airlines.Design/methodology/approach: The study uses a questionnaire survey containing air passengers’ trip characteristics and demographics and three main scales: country-of-origin, brand personality, and purchase intentions to collect the data of 490 respondents flying from Kaohsiung to Macao. The passengers are from three types of airlines: an international airline with a global network, a regional airline, and a low-cost carrier. The analysis of variance (ANOVA) was conducted to investigate the differences in the perceptions of brand personalities of airlines and several models were developed to determine the antecedent and the consequent factors of airline brand personality.Findings: The air passengers’ perceptions regarding the brand personalities of different types of airlines were significantly different. The country-of-origin of airlines was proved as a significant factor for the brand personality. The brand personality also significantly influenced passengers’ loyalty to the corresponding airlines. Moreover, some demographic and trip characteristics such as personal monthly income, memberships in the airline’s frequent flyer program, and experiences with the airlines were also determined as the significant variables to impact passengers’ loyalties.Originality/value: The concept of brand personality has been explored by various researches but few related to airline management and identified as a key element to brand marketing. Particularly, low-cost carriers always implement different marketing strategies to create a distinctive position in their target customers’ mind and legacy airlines are also doing different things to retain their customers. Therefore, investigating passengers’ perceptions of airlines from the perspective of brand personality is also an important issue for airline management. Not only does this study prove the differences in passengers’ cognitions of brand personalities of a global network airline, a regional network airline, and a low-cost airline but conclude the determinants and influences of the brand personality.
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Xu, Shun Zhi, Jin Fu Zhu, and Jing Du. "The Influence of Airline Network Passenger Flow, Fares on Airline Network Profit." Applied Mechanics and Materials 496-500 (January 2014): 2963–66. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2963.

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To airlines, the network profit is the fundamental and the only goal pursuit. When airlines operates the airline network, it is the most direct means to ensure passenger flow on every route, in addition to use large models, increase the frequency, developing competitive airline fares will also attract more passengers. As for the hub and spoke network, there are direct flights and the transit flights, each side of the flow varies with the fares and the number of network nodes, in order to highlight the scale economic benefit of hub and spoke network, research on the influence of network edge flow, fares on route network the profit is very important.
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Wu, Weiwei, Haoyu Zhang, Shengrun Zhang, and Frank Witlox. "Community Detection in Airline Networks: An Empirical Analysis of American vs. Southwest Airlines." Journal of Advanced Transportation 2019 (December 31, 2019): 1–11. http://dx.doi.org/10.1155/2019/3032015.

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In this paper, we develop a route-traffic-based method for detecting community structures in airline networks. Our model is both an application and an extension of the Clauset-Newman-Moore (CNM) modularity maximization algorithm, in that we apply the CNM algorithm to large airline networks, and take both route distance and passenger volumes into account. Therefore, the relationships between airports are defined not only based on the topological structure of the network but also by a traffic-driven indicator. To illustrate our model, two case studies are presented: American Airlines and Southwest Airlines. Results show that the model is effective in exploring the characteristics of the network connections, including the detection of the most influential nodes and communities on the formation of different network structures. This information is important from an airline operation pattern perspective to identify the vulnerability of networks.
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Chan, Chun-Hsiang, Tzu-How Chu, Jiun-Huei Proty Wu, and Tzai-Hung Wen. "Spatially Characterizing Major Airline Alliances: A Network Analysis." ISPRS International Journal of Geo-Information 10, no. 1 (2021): 37. http://dx.doi.org/10.3390/ijgi10010037.

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An airline alliance is a group of member airlines that seek to achieve the same goals through routes and airports. Hence, airports’ connectivity plays an essential role in understanding the linkage between different markets, especially the impact of neighboring airports on focal airports. An airline alliance airport network (AAAN) comprises airports as nodes and routes as edges. It could reflect a clear collaborative proportion within AAAN and competitive routes between AAANs. Recent studies adopted an airport- or route-centric perspective to evaluate the relationship between airline alliances and their member airlines; meanwhile, they mentioned that an airport community could provide valuable air transportation information because it considers the entire network structure, including the impacts of the direct and indirect routes. The objectives are to identify spatial patterns of market region in an airline alliance and characterize the differences among airline alliances (Oneworld, Star Alliance, and SkyTeam), including regions of collaboration, competition, and dominance. Our results show that Star Alliance has the highest collaboration and international market dominance among three airline alliances. The most competitive regions are Asia-Pacific, West Asia, Europe, and North and Central America. The network approach we proposed identifies market characteristics, highlights the region of market advantages in the airline alliance, and also provides more insights for airline and airline alliances to extend their market share or service areas.
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Doyme, Khan, Lynnette Dray, Aidan O’Sullivan, and Andreas Schäfer. "Simulating Airline Behavior: Application for the Australian Domestic Market." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 2 (2019): 104–12. http://dx.doi.org/10.1177/0361198119826533.

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This paper demonstrates the ability of a model, which simulates competition between airlines in a domestic aviation market, to accurately reproduce real-world behavior. The Australian market was chosen as a test case as it is a geographically isolated region with significant demand and complexity, including one of the busiest routes in the world, where connecting international passengers do not significantly skew the market. The model is based on an n-player noncooperative game, in which each airline represents a player within the game. The primary assumption is that each airline attempts to maximize profits by adjusting the decision variables of airfares, flight frequency, and choice of aircraft on routes within its network. The approach works iteratively, allowing each airline to respond to the decisions made by other airlines during each successive optimization. The model is said to reach convergence when there is no significant change in any airline’s profit from one iteration to the next. Once this occurs, the predictions of each airline’s decision variables can be compared with real data. The model gives highly detailed predictions of airline specific airfares, flight frequencies on segments, passenger flows, and airline market share, which strongly correlate with observed values.
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Wu, Weiwei, Haoyu Zhang, Siqi Lin, and Frank Witlox. "Evolution of Air Transport Networks under Different Airline Business Models: The Case of Three Chinese Airlines." E3S Web of Conferences 235 (2021): 03051. http://dx.doi.org/10.1051/e3sconf/202123503051.

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This study was conducted to compare the evolution process of air transport networks (ATNs) under different airline business models, and empirically analyzed the causes of evolution differences combining with airline market behaviors. Three representative Chinese airlines (China Southern Airlines, Spring Airlines, and Lucky Air) that belong to three business models (full-service, low-cost, and regional) were examined. Based on mathematical statistics and complex network theory, from spatial pattern, topological feature and central city, the result showed that the airlines have their own unique evolution characteristics of ATNs driven by different business models. China southern airlines as state-owned full-service network carrier, its ATN is easily affected by national policy. Spring Airlines has more flexible and diverse choice in choosing target markets and the ATN had a transformation from a mono-centric divergence network to a two-centric regional one. Lucky Air as a regional feeder carrier, whether navigable airports or navigable routes increasingly concentrated within the southwest of China. This information is important for government to improve the national ATN by developing targeted airlines.
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Jin, Ying, Ye Wei, Chunliang Xiu, Wei Song, and Kaixian Yang. "Study on Structural Characteristics of China’s Passenger Airline Network Based on Network Motifs Analysis." Sustainability 11, no. 9 (2019): 2484. http://dx.doi.org/10.3390/su11092484.

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The air passenger transport network system is an important agent of social and economic connections between cities. Studying on the airline network structure and providing optimization strategies can improve the airline industry sustainability evolution. As basic building blocks of broad networks, the concept of network motifs is cited in this paper to apply to the structural characteristic analysis of the passenger airline network. The ENUMERATE SUBGRAPHS (G, k) algorithm is used to identify the motifs and anti-motifs of the passenger airline network in China. A total of 37 airline companies are subjected to motif identification and exploring the structural and functional characteristics of the airline networks corresponding to different motifs. These 37 airline companies are classified according to the motif concentration curves into three development stages, which include mono-centric divergence companies at the low-level development stage, transitional companies at the intermediate development stage, and multi-centric and hierarchical companies at the advanced development stage. Finally, we found that adjusting the number of proper network motifs is useful to optimize the overall structure of airline networks, which is profitable for air transport sustainable development.
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Low, Joyce, and Kum Khiong Yang. "Understanding the operating landscape of the global airline industry: A DEA integrated alternating conditional expectation approach." Journal of Airline and Airport Management 9, no. 2 (2019): 27. http://dx.doi.org/10.3926/jairm.126.

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Purpose: This study investigates the relationships between service efficiency in 5 major cost centres (namely, business orientation, network coverage, physical resources, maintenance, repair and overhaul (MRO), and human resources) and profitability in the global airline industry.Design/methodology/approach: The study integrates the Slack-based Model (SBM) of Data Envelopment Analysis (DEA) with the Alternating Conditional Expectation (ACE) regression to understand the relationships between an airline’s profitability and its efficiencies in 5 identified operations areas.Findings: Based on the observational data obtained from 75 international airlines, the relationships between operational performances and profitability are found to be curvilinear and contingent on an airline’s operating model.Research limitations/implications: The omission of non-IATA airlines and many low cost carriers may hinder a holistic view of the airline industry.Practical implications: Management can influence the profitability of an airline through its strategic operations decisions that affect an airline’s cost, service quality, and financial structure after the influences of location and size have set the stage. Airlines pursuing cost leadership should seek to increase productivity especially in MRO, human resources and physical resources; whereas airlines pursuing service differentiation may choose to provide quality service at lower efficiencies or pursue an approach to improve quality and efficiencies simultaneously.Originality/value: Identifying operations practices that are consistent with a firm’s competitive priorities is important in the multifaceted service environment today. An integrated SBM-ACE regression model, which permits different input-output mix, variable return to scale and non-linear relationship, is proposed and applied to analyze the profit impact of service efficiencies in the five key operations areas.
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Mhlanga, Oswald, Jacobus Steyn, and John Spencer. "The airline industry in South Africa: drivers of operational efficiency and impacts." Tourism Review 73, no. 3 (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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Dissertations / Theses on the topic "Airline Network"

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Lordan, Oriol. "Airline route networks : a complex network approach." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/144526.

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Communication via air routes is an important issue in a world organized around a web-like city network. In this context, the robustness of network infrastructures, e.g. air transport networks, are a central issue in transport geography. Disruption of communication links by intentional causes (e.g., terrorist attack on an airport) or unintentional (e.g., weather inclemency) could be a serious drawback for countries, regions and airlines. Policymakers and the management of airlines and alliances should be able to reduce the effects of such interruptions in order to ensure good communication through air transport (i.e., maximize the robustness of their network at a reasonable cost). The literature review of the study of air transport route networks through an analysis of complex networks has highlighted a lack of contributions to the study of the topology and the robustness of such networks, which contrasts with advances undertaken for other transport networks or communication systems. The literatura survey suggests areas in which research should be undertaken, based on the existing literature in other areas and from three different perspectives: global route networks, airline alliances and airlines. The aim of this research is to develop a better understanding of air traffic and, in particular, to be able to assess the potential damage of any airport being inoperative for a continent, country or airline.
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Pearson, James. "The competitive strength of Asian network airlines in competing with low-cost carriers and the use of low-cost subsidiaries." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/21847.

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While 3.3 billion people flew worldwide in 2014 a large number of these were from developed countries. It is emerging countries which offer the greatest potential for future air traffic growth, with forecasts suggesting that 7.3 billion people will fly by 2034. The greatest proportion of this traffic will be in the Asia-Pacific region where there is already high low-cost carrier penetration. Given increasing price-based competition within short-haul markets, there are many significant challenges in terms of how Asian network airlines respond to LCC competition, and a popular response is the use of low-cost subsidiaries. Thus, the aims of this research are to establish the sources of competitive advantage of Asian airlines generally, and to examine the competitive responses of Asian network airlines and the strategic capabilities of them in competing with low-cost carriers, with a particular focus upon the use of low-cost subsidiaries. This research is underpinned with competitive advantage theory, particularly the resource-based view which concerns the internal environment of firms where each firm possesses a collection of unique resources and capabilities that provide the foundation for competitive strategy. For this research, data were collected from 49 senior airline management personnel using questionnaire surveys, resource surveys, and semi-structured interviews. The data were then analysed using VRIN analysis, the importance and difficulty of 37 competitive responses, strategic capability analysis, and the product and organisational architecture model. The results found that both a strong strategy and stable leadership are crucial. The strategies of Asian network airlines must be flexible to respond appropriately to competitive threats as they materialise, with this responsiveness contributing to the attainment of competitive advantage. Out of an analysed 36 intangible resources, the top resources for competitive advantage and responding to competitive threats for Asian airlines generally are slots, brand, and product and service reputation, with the importance of these based more on being hard to copy than valuable. Each analysed airline business model has a relatively distinct core bundle of intangible resources which explains the internal sources of their competitive advantage. The need for Asian network airlines to strengthen their competitive advantage and their ability to compete is because low-cost carriers impact them in many ways, most notably through a reduction in market share and reduced yields given the key motivation of customers within short-haul markets and economy class is now price and value-for-money. Asian network airlines are most likely to respond to low-cost carriers if they focus upon their core markets, grow their market share, and target the core higher-yielding passengers on which network airlines rely. In such instances, Asian network airlines should respond by focusing more on their brands and meeting the needs of their core targeted market segments. There is a strong positive correlation between profit margin and the strategic capability to compete with low-cost carriers. Yet, Asian network airlines have relatively weak capabilities overall. While Vietnam Airlines, Malaysia Airlines, and Garuda Indonesia are reasonably well placed to compete, network airlines from Northeast Asia, in particular, must strengthen their capabilities especially as Japan, China, and Taiwan are witnessing fast low-cost carrier growth. However, the possession of a strong capability does not mean it is fully or properly leveraged. To compete more effectively with low-cost carriers, the most important competitive responses, based upon analysis of 37 responses, are the ability of management to quickly introduce changes, leveraging brand strength, and increasing aircraft utilisation. Based on the relationship between the importance and difficulty of responses, the most crucial responses for competitive advantage of Asian network airlines are reducing costs to within 30% of LCCs and increasing aircraft utilisation. If achieved, these should lead to meaningful sustained advantage. Low-cost subsidiaries are easier to implement than for network airlines to significantly reduce costs, change to one fleet, or reduce the use of direct distribution, which may explain their popularity within Asia and them being a borderline very essential competitive response. For network airlines, low-cost subsidiaries are a more effective way to compete with low-cost carriers, to participate in the growth of the budget segment, a means of operating uneconomic routes, and to remove unprofitable customers. Network airlines can then focus upon their core market segments and their core competencies. However, their creation is reactive and not proactive which undermines their effectiveness, likewise that low-cost subsidiaries suffer from poor profitability, higher costs, and much smaller size and scale than their key low-cost competitors. This research recommends that Asian network airlines strengthen their existing and primary sources of competitive advantage while pursuing new sources of advantage. While the strategic capabilities of Asian network airlines have strengthened over time, it is essential that they are further strengthened and fully acted upon given increasing competitiveness. The use of low-cost subsidiaries will continue, but it is crucial for themselves and their parent network airlines that they improve their ability to compete and thereby their performance.
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Bratu, Stephane (Stephane J.-C) 1970. "Network value concept in airline revenue management." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9939.

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Seshadri, Anand. "A Demand Driven Airline and Airport Evolution Study." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/29526.

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The events of September 11,2001 followed by the oil price hike and the economic crisis of 2008, have lead to a drop in the demand for air travel. Airlines have attempted to return to profitability by cutting service in certain unattractive routes and airports. Simultaneously, delays and excess demand at a few major hubs have lead to airline introducing service at reliever airports. This dissertation attempts to capture the changes in the airline network by utilizing a supply-demand framework.<br>Ph. D.
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Wei, Yuanyuan (Yuanyuan Julie). "Airline O-D control using network displacement concepts." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10525.

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Chi, Zhihang. "Airline yield management in a dynamic network environment." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11735.

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Heang, Rasmey. "APPLYING THE VALUE GRID MODEL IN AIRLINE INDUSTRY : A CASE STUDY OF SCANDINAVIAN AIRLINES (SAS)." Thesis, Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33507.

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The concept of a value chain has assumed a dominant position in the strategic analysis of industries. However, the concept of linear value chain has recently become unsuitable as a tool to analyze some industries and to uncover many sources of value. The value grid approach allows firms to identify opportunities and threats in a more explicit way than with the traditional value chain model. Until now, there are still not many researchers working on the concept of value grid. Therefore, the purpose of this research is to exemplify the value grid model in airline industry with a case study of Scandinavian Airlines (SAS) and to illustrate its application, the provision of airline industry and content is explored to identify potential strategic implications for Scandinavian Airlines (SAS).
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Lo, King Shuen. "Hub-and-spoke airline network analysis for mainland China /." access abstract and table of contents access full-text, 2006. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?mphil-ms-b21471435a.pdf.

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Thesis (M.Phil.)--City University of Hong Kong, 2006.<br>"Submitted to Department of Management Sciences in partial fulfillment of the requirements for the degree of Master of Philosophy" Includes bibliographical references (leaves 81-84)
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Martin, Shane L. "Merger analysis using a simulated annealing airline network model." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 128 p, 2009. http://proquest.umi.com/pqdweb?did=1833625921&sid=2&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Williamson, Elizabeth Louise. "Airline network seat inventory control : methodologies and revenue impacts." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/13174.

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Books on the topic "Airline Network"

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Abdelghany, Ahmed, and Khaled Abdelghany. Airline Network Planning and Scheduling. John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119275909.

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Bittlingmayer, George. The economics of a simple airline network. Wissenschaftszentrum Berlin für Sozialforschung, 1986.

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Airline network development in Europe and its implications for airport planning. Ashgate, 2007.

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Vincent, Richard C. When technology fails: The drama of airline crashes in network television news. Association for Education in Journalism and Mass Communication (AEJMC), 1989.

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Brueckner, Jan K. Fares and network 'feed': Estimating economies of traffic density in airline hub-and-spoke systems. University of Illinois at Urbana-Champaign, 1991.

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Rafiq, Saqib. A decision support system for route optimisation analysis and network cost calculations for an airline. Oxford Brookes University, 2003.

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Baughcum, Steven L. Aircraft emission inventories projected in year 2015 for a high speed civil transport (HSCT) universal airline network. Langley Research Center, 1995.

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Brueckner, Jan K. Competition and mergers in airline networks. College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1988.

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Brueckner, Jan K. Fare determination in airline hub-and-spoke networks. College of Commerce and Business Administration, University of Illinois Urbana-Champaign, 1990.

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Airline operations and delay management: Insights from airline economics, networks, and strategic schedule planning. Ashgate, 2010.

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Book chapters on the topic "Airline Network"

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Bruce, Peter J., and Chris Mulholland. "Multi-Engineering Scenario: Unserviceabilities in the Network." In Airline Operations Control. Routledge, 2020. http://dx.doi.org/10.4324/9781351136303-10.

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Reggiani, Aura, Peter Nijkamp, and Alessandro Cento. "Connectivity and Competition in Airline Networks." In The Network Experience. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85582-8_10.

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Kawasaki, Akio. "The Basic Model of Airline Network." In New Frontiers in Regional Science: Asian Perspectives. Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-55294-9_8.

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Reynolds-Feighan, Aisling J. "Previous Studies on U.S. Airline Deregulation." In Advances in Spatial and Network Economics. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77061-6_2.

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Oliveira, Douglas, Marco Carvalho, and Ronaldo Menezes. "Using Network Sciences to Evaluate the Brazilian Airline Network." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38768-5_78.

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Schosser, Maximilian. "Big data opportunities for airline network planning." In Big Data to Improve Strategic Network Planning in Airlines. Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-27582-2_5.

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Yang, Yong, Kaijun Xu, and Jiayi Wu. "Empirical Structural Analysis on Chinese Airline Network." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3305-7_223.

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Helme, Marcia P. "A Selective Multicommodity Network Flow Algorithm for Air Traffic Control." In Operations Research in the Airline Industry. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5501-8_4.

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Bieger, Thomas, and Andreas Wittmer. "Airline Strategy: From Network Management to Business Models." In Aviation Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20080-9_5.

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Zhang, Weiyang, Yifei Wang, and Jianghao Wang. "Is China’s airline network similar to its long-distance mobility network?" In The Geography of Mobility, Wellbeing and Development in China. Routledge, 2020. http://dx.doi.org/10.4324/9781315112954-5.

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Conference papers on the topic "Airline Network"

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Siqueira, Lisandro, Vitor Loureiro, and Bento Mattos. "The Suited Airliner for an Existing Airline Network." In 50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-2206.

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Singh, Ajeet, and Rajkumar Pant. "Airline Network Optimization using Grey Theory." In 7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; followed by 2nd TEOS Forum. American Institute of Aeronautics and Astronautics, 2007. http://dx.doi.org/10.2514/6.2007-7757.

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Seghayati, Majid, Amirreza Nickkar, and Hasan Khaksar. "Airline Network Design by Mixed Integer Linear Programming: The Case of Small Size Airlines." In International Conference on Transportation and Development 2019. American Society of Civil Engineers, 2019. http://dx.doi.org/10.1061/9780784482582.011.

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Qin, Yi, Jinfu Zhu, and Wei Zhang. "Airline network design with variable hub number." In 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS). IEEE, 2009. http://dx.doi.org/10.1109/peits.2009.5406804.

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Zhou, Yi-Ye, Deng-Kai Yao, Qian-Rui Sun, and Qi-Ke Wu. "Optimization of Conflict-Free Airline Network Designing." In 2016 4th International Conference on Machinery, Materials and Information Technology Applications. Atlantis Press, 2016. http://dx.doi.org/10.2991/icmmita-16.2016.256.

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Zhou, Yi-Ye, Deng-Kai Yao, Qian-Rui Sun, and Qi-Ke Wu. "Maklink Graph in Conflict-Free Airline Network Designing." In 2016 4th International Conference on Machinery, Materials and Information Technology Applications. Atlantis Press, 2016. http://dx.doi.org/10.2991/icmmita-16.2016.180.

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Shao, Jiajia, Wendong Yang, and Hai Jiang. "Evaluation of Airline Alliance Route Network Efficiency Based on Complex Network." In 2019 4th International Conference on Electromechanical Control Technology and Transportation (ICECTT). IEEE, 2019. http://dx.doi.org/10.1109/icectt.2019.00077.

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Zhang Yan and Zhang Jun. "Dijkstra's algorithm based robust optimization to airline network planning." In 2010 International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2010. http://dx.doi.org/10.1109/mace.2010.5536824.

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Clemons, Emily, Richard Jordan, and Tom Reynolds. "Airline network and competition characterization using big data approaches." In 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC). IEEE, 2016. http://dx.doi.org/10.1109/dasc.2016.7777957.

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Qing, Qiankai, Zhixue Liu, Kunpeng Li, Chen Wang, and Jun Xiao. "Airline Network Design for Nanning Airport Facing to CAFTA." In 2009 International Conference on E-Business and Information System Security (EBISS). IEEE, 2009. http://dx.doi.org/10.1109/ebiss.2009.5137915.

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