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Traffic Distribution in Low-cost and Full-service Carrier Networks in the US Air Transport Market
Abstract
After deregulation in the US in 1978, air carrier networks were increasingly focused around a small number of hubs. These ‘hub-and-spoke’ (HS) networks were the predominant form of network organisation of large carriers as well as smaller regional and commuter carriers. The passenger carrier networks typically consisted of between three and seven hubs, while the air freight carrier networks were typically focused around one or two hubs. A variety of measures of the traffic distribution in carriers’ networks have been presented in the economics and regional science literature. These measures are reviewed and compared for a sample of US major carriers for the period 1969–99. The HS network structure requires a concentration of traffic in both space and time. The summary measures presented focus on measuring the spatial concentration at discrete locations in the networks.The emergence of a new wave of low-cost airline entrants has been a significant component in the more recent development of the US air transport industry. Southwest Airlines began its operations in the early 1970s and has been copied in the US and Europe in terms of its network organisation, management, service and operating characteristics. The US ‘low-cost’ operators are examined in the paper in terms of their traffic distribution patterns using the same summary measures used for the full-service operators. It is demonstrated that the low-cost carriers have a lower level of concentration on average than the full-service carriers. The low-cost carriers focus their traffic flows around a limited number of key nodes—these nodes function as points of entry or exit rather than transfer points.
... One reason for such unbalance in academia is that the economic contribution of the air cargo industry has drawn increasing attention only during recent years. Most of the previous studies have identified the small-world and scale-free properties on a variety of geographical scales [20] [21]. e authors of [22,23] analyzed the world airport network and uncovered the fact that the traffic between airports is subject to the capacity of the airports, and by simulating a global epidemic outbreak, they conclude that the air transport network could accelerate the speed of transmission. ...
... From a temporal perspective, [60] suggested that the long-term OECD air transportation demand depends on the level of liberalization policies. Additionally, the prevalence of the LCC (low-cost carriers) across the globe has tremendously stimulated local and regional economic growth [7,20,[61][62][63][64][65]. ...
As the US air cargo network (USACN) becomes a crucial part of the economy, it is pivotal to understand the structural evolution of the network and how it would be affected by unexpected events. We investigated the network structure, efficiency, and robustness of the USACN from 1990 to 2019 due to targeted attacks based on complex network theory from a dynamic and spatiotemporal perspective. Our results suggest that the USACN has enhanced robustness. Moreover, we find that attacks based on betweenness centrality are the most effective way to cause a collapse compared with attacks based on degree and closeness centrality. In addition, airports of the USACN have formed an increasing number of communities with geographical ties, and airports in the noncontiguous regions are more vulnerable than other communities in the lower 48 states. Further, we discover that the average path lengths have increased, and the overall efficiency has decreased from 0.7 to 0.4 due to the dependency of the hub-and-spoke structure. This paper complements previous studies on the dynamic structure evolution of air cargo networks through the lens of complex network theory with spatial-temporal data.
... Southwest, JetBlue) as those with less complicated routines. Such a delineation is intuitive, and is well supported in extant research (Alderighi et al., 2007;Reynolds-Feighan, 2001). Further, leveraging such a context offers us at least three empirical benefits. ...
... Our next set of independent variables capture the complexity of routines. Following prior literature, we operationalize routine complexity by categorizing airlines as full-service carriers (FSCs) or low-cost carriers (LCCs) (Fu et al., 2006;Reynolds-Feighan, 2001). FSCs show higher complexity in operational routines than LCCs (Alderighi et al., 2007;Gillen and Morrison, 2003). ...
We study the effect of firm disruptions on competitor performance in the presence of shared resources, and conditions under which competitors experience performance degradation. We propose that the impact of disruption is moderated by the routine complexity of both a disrupted firm and a competitor. We examine these questions in the context of the U.S. airline industry, leveraging four large IT outages from 2011-2016. Competitors' flights which originated from, or were inbound to, a disrupted hub experienced significant changes in on-time performance, depending on the routine complexity of the disrupted airline. Performance deteriorated during the disruption of full-service carriers, but improved during that of a low-cost carrier. We also find that this effect is strongly moderated by the competitors' routine complexity.
... tanich linii oraz nowe rozwiązaniach marketingowe (Mason 2001, Doganis 2002. Przedmiotem badań stały się również zmiany sieci połączeń lotniczych (Reynolds-Feighan 2001, Swan 2002, a szczególnie nowa koncepcja rozwoju sieci dużych przewoźników oparta na głównym punkcie przesiadkowym i trasach dolotowych (hub and spokes system) (O'Kelly 1998, Derudder i in. 2007). ...
... Cechą sytemu "hub and spokes" była nie tylko koncentracja przestrzenna sieci połączeń, ale również czasowa. Oparcie systemu połączeń na głównym punkcie przesiadkowym powoduje "falową" strukturę odlotów i przylotów (Reynolds-Feighan 2001, Maciuk 2004. Jest to związane z próbą skrócenia łącznego czasu podróży pasażera przez minimalizację czasu na przesiadkę w punkcie przesiadkowym. ...
... A recent accomplishment (2008) includes the first phase of an Open Sky Agreement between the EU and the US, giving carriers registered in the EU or the US the right to operate services between any points in the EU and US. There is a large body of literature showing the impacts of de-regulation on the allocation of airport seat capacity and airline network configurations (see, for example, Reynolds-Feighan (1998, 2001, 2007a, 2007b, Goetz and Graham (2004), Burghouwt (2007), Suau-Sanchez andBurghouwt (2011)). ...
... A recent accomplishment (2008) includes the first phase of an Open Sky Agreement between the EU and the US, giving carriers registered in the EU or the US the right to operate services between any points in the EU and US. There is a large body of literature showing the impacts of de-regulation on the allocation of airport seat capacity and airline network configurations (see, for example, Reynolds-Feighan (1998, 2001, 2007a, 2007b, Goetz and Graham (2004), Burghouwt (2007), Suau-Sanchez andBurghouwt (2011)). ...
This paper covers the development dynamics of the air transportation industry. Having the evolutionary economic geography as the frame of reference, we analyze the co-evolution of the market (selective environment), the aeronautics knowledge and equipment (technology) and the air transportation institutional policy (policy). The stress is on those factors affecting network formation and tie selection. The results of this investigation add to the limited empirical research on the evolution of transport network systems. We found that air transport shows a path dependency; although at the same time has a strong level of uncertainty due to exogenous factors. Also, the co-evolution between the selective market environment, technology and institutional decisions has been verified. The latter happen to be key, as the evolution of air transportation can only be understood in the context of a mixed regulatory environment that provides different levels of freedom for network formation.
... A fight plan containing basic information on the aircraft's fight intent was formulated and submitted several days before performing the fying mission. Economic beneft and operation efciency are the most important objectives to achieve when designing a fight plan to maximize the airline's interests [28,29]. Terefore, to advance the air safety assurance work to the strategic stage, it is important to propose a safety assessment method for fight plan, which is able to provide a quantitative evaluation criterion for fight plan adjustment and early warning, and provide better assurance for the aviation system. ...
This article presents a novel risk assessment method for aircraft flight plans in a four-dimensional trajectory-based operation background. With the increasing air transport volume and airspace demand and during the allocation and modification of flight plans, safety should also be considered in addition to economic benefits and competitiveness. By employing the time geography concept, this article first quantifies the space-time accessibility and estimates the visiting probability of aircraft in the four-dimensional trajectory-based operation context. On this basis, this article studies the method and process to evaluate the conflict risk between one flight plan and a special airspace, the weather-influenced airspace, and another flight plan. This article also proposes the conflict risk alerting strategy. The achievements of the study are expected to provide assistance for air traffic controllers in strategic conflict avoidance and are of great significance in assuring air transport safety.
... In this scenario, ac-cording to industry analysts, three major changes are influencing the competitive constraints and productivity of airports: more footloose airlines, greater passenger choice and higher reactivity of airports 2 ( ACI, 2009 ). Furthermore, the changes in the aviation industry, shifting from a point-to-point system to a hub-and-spoke network, have redefined the industry globally by creating patterns of traffic concentration: in the early 20 0 0s, hubbing network strategies emerged in US, Europe and Southeast Asia ( Bowen, 20 0 0 ;Button, 2002 ;Goetz & Sutton, 1997 ;Reynolds-Feighan, 2001 ). After the deregulation period, airlines developed Hub-and-spoke networks, allowing them to aggregate demand, increase frequency, decrease airfares and preclude entry into the marketplace ( Adler, 2001 ). ...
This paper analyses the potential impact of airport competition on technical efficiency by applying the spatial stochastic frontier approach (SSFA) rather than the traditional model (SFA). The SSFA allows for isolating the cross-sectional spatial dependence and evaluating the role of intangible factors in influencing an airport's economic performance through the inclusion of the distance matrix and the shared destinations matrix calibrated for different distances. By analysing the statistical differences between the traditional and the spatial model, it is possible to identify the competition effects. This study includes 206 airports at the worldwide level. The results show the existence of the spatial component: we detected a different influence of airports’ efficiency levels according to the geographical distances. This could have not been captured by the traditional SFA. We conclude that when incorporating spatial spillover effects into the airport efficiency analysis, the efficiency dynamics are strongly dependent on the spatial distance among airports.
... The most extensively researched aspect of aviation network strategies has been the economic aspect. Reynolds-Feighan (2001) determines that, post deregulation, traffic flow is concentrated at a certain number of key nodes (hubs) in the United States, thus pointing to the effectiveness of the hubbed strategy. de Wit and Zuidberg (2012) explore the thriving conditions and bottlenecks for the LCCs. ...
The Indian aviation industry has grown by over 20% annually in the past two years. It is likely to grow at a double digit growth rate in the coming decade. The stupendous rise in its economic activity has raked up concerns about its environmental impact. India has signed up for Carbon Offset and Reduction Scheme for International Aviation (CORSIA) in 2016, which is to be mandated from 2026. This article discerns the possible implications that such an environmental policy can have on the Indian aviation sector by modelling the impact of a prospective carbon tax on the domestic aviation sector.
... In the air transportation system, a complex airline network is formed between city nodes through a large number of air route connections. Many studies on airline networks have been conducted using complex network theory and methods to discuss the structural features and evolution characteristics of airline networks [1][2][3][4][5][6]. Complex network-based research have concluded that global airline networks [7][8][9][10], Australian airline networks [11], Italian airline networks [12], Indian airline networks [13], and Chinese airline networks [14,15] have obvious scale-free and small-world characteristics. ...
Passenger airline networks are an important agent of social and economic connections between cities, and embody characteristics of complex networks. The study on the survivability of passenger airline networks has positive significance on their healthy and safe development. There have been several in-depth empirical studies on the impact of macrostructural characteristics of complex networks on network survivability, however few studies have focused on the impact of microstructure on network survivability, which is the focus of this paper. As the basic building blocks of the network, colored motifs can distinguish the different functions of nodes or edges in the motif, and then comprehensively depict the network microstructure. We used this characteristic to study the impact of microstructure on network survivability, in this paper. Passenger airline networks of different airlines in China during 2018, were studied, and the three-node and four-node colored motifs of different airline networks were identified. Complex network indexes were used to measure the survivability of airline networks under intentional and random attacks. Multiple linear regression analysis was conducted between the survivability coefficient of each airline network and the concentration of colored motifs to explore the impact of colored motif characteristics on network survivability. The results show that: (1) microscopic topological structures represented by colored motifs in airline networks are closely related to the macro spatial structural modes of airline networks (such as hub and spoke model); (2) vast majority of passenger airline networks in China are more vulnerable to intentional attacks and are robust in the face of random attacks; (3) from the perspective of topological structures of network motifs, motifs with radial and loop structures have positive impacts on network survivability under intentional attacks, while motifs with loop structures had negative impacts on network survivability under random attacks; (4) from the perspective of the type of colored motifs, motifs with a large number of hub nodes, high degree of agglomeration, and strong hub-and-spoke effect can enhance the ability of the network to resist intentional attacks. The agglomeration of non-hub nodes has a positive effect on network survivability under intentional attacks, and a linear structure with hub nodes at both ends can enhance the ability of airline networks to resist random attacks. In actual route planning, adjusting the type of colored motif from the microstructural perspective can be a good means to enhance the survivability of the entire airline network.
... 2006). The subject of research was also changes in the air connection network (Reynolds-Feighan 2001), and in particular, a new concept of developing a network of large carriers based on the main transfer point and hub and spokes system (Derudder et al. . 2007). ...
The United States, along with some other developed countries, is the world’s largest international and domestic aviation market. The United States is among the two largest economies in the world, and the scale of the civil aviation industry in China and the United States ranks first and second, respectively, in the world. The American aviation markets have the characteristics of both domestic and international markets, which is a global feature. It also has the unique, innovative development model of American civil aviation. Various technological, political, social, and economic changes in the global market, causing the dynamics of the US industry to change, have resulted in the creation of challenging situations for the corporations from this industry.
According to the annual statistical report on air transportation released by the US Department of Transportation, the volume of US commercial air passenger traffic increased by 3.5% in 2016 to reach a record 928 million passengers, of which domestic air passenger traffic was 719 million passengers, an increase of 3.3%; international passenger traffic was 20989 million Person-times, an increase of 3.97%. The United States is the world’s largest aviation market, and it has remained strong for a long time. Considering constantly in comparison, seeing the goals and gaps, recognizing bottlenecks and shortcomings, the civil aviation of the United States is forced to level their game up to retain dominancy in the market against newly emerging contenders.
This research aims at setting a direction for addressing the challenges by beginning to explore the current challenges in the management of aerospace corporations with the ever-changing dynamics of the aviation industry in the United States.
... More generally, deregulation has been said to have posed a threat to thin markets (Reynolds-Feighan, 1995) and to have had a direct impact over increased congestion levels, a byproduct of diseconomies of scale in the wake of increased traffic concentrations on a few nodes of airlines' networks, as they turned themselves increasingly more towards a hub-and-spoke network configuration (e.g., Reynolds-Feighan, 2001;Alderighi et al. 2007). However, on the other side, as suggested by Reynolds-Feighan (2000) in the case of the US, deregulation has also provoked changes in the network structures of airlines, with the author finding evidence that the relationship between enplanements and population size was stronger for small and medium hubs when compared with larger ones. ...
This paper examines the evolution of the geographic concentration of the Brazilian air transport network with a focus on its determinants and possible detachments from the spatial patterns of socioeconomic activity. We develop an econometric framework employing and contrasting the results of Gini, Herfindahl-Hirschman and Theil indexes, with and without normalisation to account for economic and demographic spatial dynamics. Our results suggest that the spatial dynamics of the air network and that of the country's economy and population are strongly tied for the majority of the considered determinants. However, we find suggestive evidence that the time trend after deregulation has produced some asymmetries in the evolution of these dimensions. As such, our analysis presents some implications for airline network planning and regulators, as it offers additional information to be considered for the understanding of extra-economic and extra-demographic impacts which may be inducive of significant changes in air transport markets.
... 2 Outside of Europe, studies in the late 1990s and early 2000s concluded that traffic concentration in the form of "hub and spoke" network dominated the airline industry in the US (e.g., Goetz and Sutton, 1997;Reynolds-Feighan, 2001) and in Southeast Asia (Bowen, 2000). Later studies nevertheless suggest a more mixed outlook, or even a dispersal trend in global air travel (e.g., O'Connor, 2003;Reynolds-Feighan, 2010;Wong et al., 2019aWong et al., , 2019b. ...
This paper studies the evolution of global air transport network over the period 2006–2016. A Global Airport Connectivity Index (GACI) is proposed, combining degree, closeness and eigenvector topological indicators and two new volumetric indicators. We find faster passenger growth for larger airports that have improved in GACI. While America and North Asia focused on regional hub developments, serving short- to medium-haul routes, West Europe, South East Asia and Middle East focused on developing their major airports into global hubs. Our analysis shows that increasing GACI improves an airport’s competitive position and gives rise to increased influence over other airports.
... They are expressed in two units of measure; those that measure dependency are expressed as a percentage (0%-100%) and those that measure concentration are expressed with the Gini index (0-1) (Gastwirth, 1972). The Gini index has already been used to measure air transport distribution (Reynolds-Feighan, 2001), air transport liberalisation and airport dependency (Koo et al., 2016). This simplification of the units of measurement makes it easier for the results to be interpreted by decision makers. ...
Tourist destinations are vulnerable to the decisions of commercial stakeholders that may have different organisational priorities to theirs. A high level of tourism concentration, and dependence on certain airports and airlines, can increase the strategic risks and threaten the competitiveness of destinations. This paper develops a novel methodology to measure the vulnerability of tourist destinations to the availability of air transport through the use of composite indexes. The applicability of the methodology is demonstrated in Catalonia (Spain) from 2007 to 2017. The result is a rigorous control of easy interpretation that allows multiple analyses and flexible application to different circumstances. The system provides politicians and technical staff with the tools they need to have a comprehensive and integrated understanding of the vulnerability of their destination. It also provides robust data that can be used to analyse current policies, negotiate contractual conditions and prepare contingency plans for those instances where the collective needs at a destination differ from those of individual commercial stakeholders.
... To adequately compete in certain markets, LCAs also may utilize point-to-point flights along with occasional connections to FSA hubs (Akguc et al., 2018). As a result, some of these LCA networks can have high traffic concentrations (Reynolds-Feighan, 2001). Unlike FSA hub and spoke networks which support long-haul flights, LCA networks typically do not include long-haul flights (Dobruszkes, 2006). ...
The top seven low-cost airlines in the EU, as ranked by 2018 passenger travel, are evaluated over a 4 year time frame using stock market performance in order to ascertain which airlines provide superior performance in relation to the others in the group and in relation to the European stock market. Several topics are discussed relating to this group of airlines including business models, operating strategies, airline networks, regional airports, and standardized fleets. Three airlines emerge with superior stock market performance: Jet2, WizzAir, and Ryanair.
... Focus of study Reynolds-Feighan (2001) Uses Gini Index to discuss traffic distribution of LCC and FSC in the United States of America (USA). Forsyth (2003) Investigation into why LCC failed to gain market share in Australia. ...
Lotka-Volterra model to assess the change in influence of LCC over South Korean tourism and airline industries.
... In this context, research has emerged that mainly addressed the issue of describing and classifying networks by means of geographical concentration indices of traffic or flight frequency (Caves et al., 1984;Reynolds-Feighan, 2001). These measures, such as the Gini concentration index (Gini, 1912), provide a proper measure of traffic concentration of the main airports in a simple and well-organized network. ...
This paper is dedicated to the structure of airline networks as a sink of efficient airline operations. Parameters of complexity were derived and mirrored on level of service as well as efficiency parameters. Airlines usually considerers an operational overhead to predict the total flight operation cost. This parameter includes the expected cost for disruptions and delays. When an airline has to mobilize an aircraft in a base for recovering the service or for breaking an emergent dynamic, then it is running extra costs. The cost of managing complexity in the airline industry has a direct impact on profit and loss account. Therefore, this paper presents an integrated approach to evaluate this cost, based on padding and aircrafts dedicated to recover disruptions. Finally, some additional indicators are derived to evaluate reliability improvement as part of complex performance.
... Q uestions to do with aviation networks in a market environment, their formation, development, and competitive dynamics (or lack thereof) have been discussed before. For example, Reynolds-Feighan (2001), Ald e righi et al (2005), Martin andVoltes-Dorta (2009), andHuber (2009) have aimed at assessing the major effects caused by liberalisation and competition on air transportation networks by measuring market concentration. More rece n tly, structural aspects of networks, such as connectivity, have been examined in greater detail (Reynolds-Feighan 2010;Shaw 2009: 293). ...
Examining the multidimensional patterns of network characteristics for scheduled Indian airlines between 2006 and 2014, this article goes on to discuss their evolutionary paths. The well-known skewed traffic distribution, which spatially concentrates traffic around a few airports, serves as the starting point for dividing the system into its constituent route types. This analysis points to inferences that can be drawn about the development path of the Indian commercial air traffic system.
... That complex interplay has been explored in analyses of major geographical factors that influence airfare pricing in different domestic markets. The relative importance, and the spatial consequences, of these factors tend to play out differently: pricing in a large and liberalized market such as the United States (Reynolds-Feighan, 2001) obviously differs from that in a geographically smaller and regulated market such as Japan (Yamachuci, 2000, Zhang et al. 2008), while at a continental scale the experience of pricing in Canada (Mentzer, 2000) and the US differs from that in the European Union (Alderighi et al., 2004, Goetz and Graham, 2004). This is partly because of the impact and presence of alternative travel modes and the geographical outline of the respective urban systems. ...
Deregulation of the airline industry in Australia has produced lower airfares. However this perspective rarely incorporates spatial insights and usually utilizes archival data. The purpose of this paper is to conduct a first-stage confirmatory analysis of up-to-date airfares charged on 24 major routes within Australia using Skyscanner, a web-based and consumer-oriented tool to access airfares. This tool displays fares during an on-line booking process prior to purchase, just as consumers would experience it. We apply Skyscanner to extract one set of current fares -- lowest fare data -- on the routes and then use linear modelling to establish variables that can be utilized to predict these lowest fare prices. While far from a full accounting of the cost of Australian air services, this test of Skyscanner as a data source, along with the successful confirmatory linear analysis, shows that the underlying configuration of the nation’s urban population, distance, direct connections, and characteristics of links and networks of low cost carriers are powerful influences upon prices charged. We suggest that Skyscanner and similar data sources may provide researchers with alternative low cost data that may shed insight into many air transport pricing questions.
... XX w. Podobnie jak w Stanach Zjednoczonych i w Europie Zachodniej, deregulacja i liberalizacja przyczyniły się do wzrostu konkurencyjności i obniżenia cen podróży lotniczych oraz gwałtownego wzrostu liczby podróżujących drogą lotniczą, zwłaszcza w okresie następującym bezpośrednio po deregulacji [Reynolds-Feighan 1998, 2001 Debbage 2005]. Główna różnica polega natomiast na znacznie krótszej skali czasowej obserwowanych zjawisk i czasie trwania poszczególnych faz rozwoju . ...
PHASES OF DEVELOPMENT OF REGIONAL AIRPORTS IN POLAND AND OTHER CENTRAL-EASTERN EUROPEAN COUNTRIES, AFTER ACCESSION TO EUROPEAN UNION
Abstract: Polish accession to the European Union and related liberalization of air transport have caused a range of changes on the air passenger market, including the development of regional airports. This paper aims to show the evolution of Polish regional airports and to compare with changes experienced by regional airports in other Central-Eastern European countries. The latter include countries which joined the EU both along with Poland (Czech Republic, Estonia, Hungary, Latvia, Lithuania, Slovakia) and at a later date (Bulgaria, Romania). The key research question is whether development trends experienced at regional airports in various countries were similar or different. Eurostat database, data from civil aviation authorities and information from airports themselves were used in the comparative analysis. Connection networks were examined using past and contemporary flight timetables. Differences between countries and airports have mainly quantitative character, reflecting the size of a country (area, population), but a clear three-stage temporal pattern of expansion, followed by crisis and then consolidation, emerges in most countries. These phases of development do not typify Central-Eastern Europe only, but were also characteristic for markets which were de-regulated earlier (USA, western Europe). However, the duration of each phase in Central-Eastern Europe was markedly shorter.
... Using the Gini to compare the extent of imbalance in regional development in China, Li, Goh, Qiu & Meng (2015) find evidence that spatial disparity of the tourism industry in China (proxied by tourism receipts and number of hotel rooms in each province) is more extreme than the spatial disparity in provincial GDP. Although common in other fields such as transport (e.g., Koo, Halpern, Papatheodorou, Graham, & Arvanitis, 2016;Halpern, 2011;Papatheodorou and Arvanitis, 2009;Reynolds-Feighan, 2001), the above study by Li, Goh, Zhang, Qiu, and Meng (2015) is one of very few examples of using the Gini as a method to gauge the spatiality of tourism. Below, we theoretically motivate a spatial inequality perspective in assessing the suitability of Gini as a method to measure tourist dispersal. ...
Compared to the metrics of tourism seasonality or tourism income distribution, metrics of tourism spatiality remains under-explored. Our principal aim is to enhance the way we measure the geographic dispersal of visitors by developing a Gini index–inspired dispersal metric. We discuss the theoretical criteria for an ideal spatial metric and use these criteria to highlight the important links and differences between Gini and the common ratio approach. Applying the methods to inbound Australian tourism data, we find that considering only one method in isolation not only increases the risk of incorrectly measuring the spatial performance of markets but also ignores interesting, and often offsetting, heterogeneous influences in the data. We expect the outcomes to aid tourism researchers and managers wanting to widen their repertoire in spatial measurement methods, and aid the choice of most appropriate method based on criteria firmly grounded in theory.
... There are, of course, alternatives to the hub-and-spoke system, including the point-to-point topologies used by many LCCs upon startup (Alderighi et al., 2005). These smaller point-to-point systems can often provide the market with lower fares than legacy carriers operating with hub-and-spoke topologies (Doganis, 2001;Reynolds-Feighan, 2001;Williams, 2001;Burghouwt et al., 2003;Burghouwt and de Wit, 2005) because they are purposefully structured to maximize profits when the distances between origin/destination pairs are small (Lederer and Nambimadom, 1998;Grubesic and Zook, 2007). ...
... The index shows the summary status of the Lorenz curve, indicating unfairness among respective businesses. The values of the Gini coefficient range from '0' to '1', where '0' shows complete equality and '1' reveals complete inequality (Reynolds-Feighan, 2001). The equation of the Gini coefficient is as follows: ...
The aim of this research is to identify the success factors for shipping management companies (SMCs), to evaluate the importance of these factors, and finally to determine the differences in perceptions between ship owners and SMCs. The fuzzy evaluation method together with experts' knowledge is used, because they are capable of overcoming evaluation difficulties by accommodating both tangible and intangible variables in one single framework of evaluation. The differences between ship owners and SMCs' perceptions are then established. The results show that SMCs rank 'quick responses to ship owners' first, followed by 'ship management fees' and 'the efficient management of ships' operational costs'. Ship owners perceive 'the efficient management of ships' operational costs', 'the ability to recruit the full required manpower' and 'the potential for high-quality management' as most important.
... For instance, in transport research, the index has been used to measure the spatiality of airline network (e.g. Burghouwt, 2007;Reynolds-Feighan, 1998), including how low-cost carrier network differs from that of network carriers (Reynolds-Feighan, 2001), as well as to measure the impact of a significant policy change such as deregulation of the airline sector (e.g. Suau-Sanchez & Burghouwt, 2011). ...
This research highlights findings from an application of a multilevel Gini decomposition method to measure the degree of spatial concentration of tourism markets in Australia. The overall level of spatial concentration in Australia is decomposed into two levels: inbound country and travel purpose. While travel purpose is an important factor associated with the concentration patterns of tourism, the nature of its impact differs significantly by country of origin. Due to the variation in market share and the market’s underlying dispersal characteristics, an increase in the share of one market may require a more than proportionate increase in the shares of several markets in order to counterbalance the spatial concentration pressures. Findings show that considering only one factor in the decomposition process can hide important offsetting influences of market segments on concentration and dispersion.
... As mentioned above, airline traffic is usually measured in terms of enplanements. Most studies use outgoing traffic flows for this purpose (e.g., Debbage and Delk 2001;Toh and Higgins 1985;Reynolds-Feighan 2001;Martín and Voltes-Dorta 2008). Rare examples (e.g., Hensher 2002), however, consider incoming and outgoing movements to assess traffic. ...
An efficient and service-oriented transportation network is a necessary resource for successful less-than-truckload operations. The design and evaluation of transportation networks are mainly driven by quantitative particularly cost-oriented measures, such as transport and transshipment costs. This type of measurement, however, simply cannot represent the manifold performance of a transportation network. In particular, incorporating network concentration into network design decisions overcomes the shortcomings of purely cost-oriented decisions because spatial network concentration is at the root of many aspects of network performance (e.g., congestion and network vulnerability). This paper suggests modifications to the network concentration index and the hubbing concentration index from the passenger airline context for less-than-truckload road transportation. The modified indices enable information to be conveyed by network concentration into less-than-truckload network design decisions and provide a suitable perspective to include service-oriented aspects into network design.
... Oparcie systemu połączeń na głównym punkcie przesiadkowym powoduje "falową" strukturę odlotów i przylotów (Reynolds-Feighan 2001). Jest to związane z próbą skrócenia łącznego czasu podróży pasażera przez minimalizację czasu na przesiadkę w punkcie przesiadkowym. ...
... Although some researchers find a spatial concentration pattern of air traffic at a few airports as a result of airline hub-and-spoke strategies in deregulated markets (Goetz and Sutton, 1997;Reynolds-Feighan, 1998, 2001, others end up with a more differentiated picture. Burghouwt and Hakfoort (2001) show that intra-European air traffic displays a spatial de-concentration pattern due to the growth of regional and low-cost airlines at small and medium-sized airports. ...
This paper approaches the airport location problem as a function of accessibility considerations. First, a structural equation model is established to find the relationship between the size of an airport catchment area and its flight network scale. Landside and airside accessibilities are measured by the qualities and costs of surface transportation and flight networks. The two accessibilities are combined to form a regional air transportation accessibility profile, which can be used as a criterion to evaluate airport locations at a macro-planning level. Finally, the scenarios of airport locations in terms of small and large areas are analyzed using two regional case studies in China.
... De Herfindahl-Hirschman index HHI wordt berekend door de aandelen passagiers van alle steden of verbindingen te sommeren (Reynolds-Feighan, 2001). Door het kwadrateren van de percentages worden de steden of verbindingen van een lagere rangen dus een relatief groot proportioneel aandeelmeer beklemtoond. ...
This paper analyzes to what extent different indices are able to measure the concentration in air transport networks. First, we illustrate the theoretical characteristics of the concentration ratio, Herfindahl-Hirschman index, network concentration index and Theilindex by applying these to socalled toy networks with known parameters. Second, the practical applicability of these indices is assessed by calculating them for three domestic airline networks (France, Germany and the United States). The dimensions of the concentration in each of these three networks as a proxy for the city systems are intuitively clear so that the results provide us with an appropriate touchstone for assessing the advantages and drawbacks of each of the indices. Based on the analyses of both the ideal-typical and the actually existing networks, the main implications for future research on concentration indices are discussed.
... The (two-stop) hub-and-spoke network became the most common network structure in the USA after the deregulation and typically consists of three to seven hubs (Jaillet et al., 1996;Lederer & Nambimadom, 1998;Reynolds-Feighan, 2001;Button, 2005). However, on average there are more direct connections today than before 1978 (Barnett et al., 1992). ...
Two approaches for integrated airline scheduling were presented and evaluated. They integrate the subproblems network design, frequency assignment, flight scheduling, fleet assignment, and aircraft routing. Furthermore, a schedule evaluation procedure was developed and calibrated that is required by both airline scheduling approaches. Both planning approaches are able to represent airline operations and practical requirements on a higher level of detail compared to many solution models presented so far. There are fewer simplifying assumptions or restrictions to certain planning scenarios. Their only requirement is to receive a quality measure for each schedule processed. The first airline scheduling approach follows the traditional sequential planning paradigm. This stepwise approach is realized in an iterative procedure consisting of solution models from literature. In contrast, the second planning approach represents a truly simultaneous model. In a self-adaptive metaheuristic, each processed solution represents a complete airline schedule, thus including all former subproblems implicitly. A comparison in which both approaches are applied to the same scenarios confirmed the postulated higher performance of a simultaneous optimization since the simultaneous approach outperformed the sequential approach with regard to the operating profit of the obtained schedules and the required computational effort. The capability of the simultaneous planning approach is further investigated by its application to scenarios that were modified implying a certain structure of the optimal solutions. For all experiments, the resulting schedules are in accordance with theoretical expectations.
... A number between zero and one, G is typically used in economics for the purpose of describing the distribution of wealth within a nation. Here it is used to characterize the disparity in the assignment of flows to the edges of a network, something that has been done before for transportation systems such as the air traffic network [18]. For example, if all flows were concentrated onto one edge, G would be one, whilst if the flows were spread evenly across all edges, G would be zero. ...
Space plays an important role in the behaviour of both individual infrastructures, and the interdependencies between them. In this Chapter, we first review spatial effects, their relevance in the study of networks, and their characterization. The impact of spatial embedding in interdependent networks is then described in detail via the important example of efficient transport (or routing) with multiple sources and sinks. In this case, there is an optimal interdependence which relies on a subtle interplay between spatial structure and patterns of traffic flow. Although simplified, this type of model highlights emergent behaviour and brings new understanding to the study of coupled spatial infrastructures.
Taiwanese carriers face the difficulty in developing European direct flight market due to the air route limitation. Therefore, most passengers fly indirectly and mainly transit via other airports between Taiwan and Europe. In order to extend Taiwan - Europe flight market and improve Taiwan Taoyuan International Airport's (TPE) hub position, this study aims to indicate the potential European direct flight market by analyzing the passenger transfer dependency and further propose the flight frequency through the result of Cost-effectiveness analysis. One of the interesting results shows that passengers heavily rely on Dubai International Airport (DXB) and Hong Kong International Airport (HKG) for transferring between Taiwan and Europe. In addition, London Heathrow Airport (LHR) is the most profitable destination to launching new direct services. The results of this study provide the practical strategy to increase the connectivity of Taiwan-Europe flight market.
Asian airports are keen to develop into hubs to strengthen their respective positions in the region. When a hub airport launches more routes and increases flight frequencies, its neighbouring airports might be affected by depending on them for transfers to additional destinations. To analyse the situation in Asia, this paper develops two composite indexes referred to as the Airport Transfer Dependency Index (ATDI) and Airport Transfer Dependency Degree (ATDD) based on the Gini coefficient and Hub Connectivity Performance Index (HCPI) to measure an airport’s transfer dependency on other airports. The analysis focuses on the case of Taiwan’s Taoyuan Airport’s dependency on its neighbouring hubs for destinations to North America (NA), Europe (EU), the Middle East (ME), Africa (AF) and Oceania (OC). The results reveal that Taoyuan Airport has significant transfer dependency on Tokyo’s Narita Airport for North America (NA) routes and on Hong Kong Airport for the other long-haul routes. The analysis presented in this paper could help airport authorities strengthen their weak connectivity on certain routes in order to reduce their dependence on neighbouring hubs.
The existing literature appears to suggest that low-cost carriers (LCCs) tend to focus their business at “secondary airports” instead of “primary airports”. However, there lack systematic quantifiers to distinguish the two airport types. The present paper investigates whether this remark still holds today, and if not, whether the change is a worldwide phenomenon. We first establish a systematic parameterization to classify airport types, based on aviation network connectivity, regional importance, and MAR (multi-airport region) effects. With this classification of world airports, our analysis of the latest empirical data shows that some previously indubitable features of LCCs might have slowly changed. In particular, LCCs are expanding fast at both upper-tiers’ and lower-tiers’ airports, and there is a trend of shifting airport choice from lower-tiers’ to upper-tiers’ airports for LCCs in some continents. The evolving competition relationship between the full-service carriers (FSCs) and LCCs is also discussed.
The economic performance of a city or region is considered to be intertwined with its air travel capability. It is thus important for planners and stakeholders to understand the changes in the global aviation network. This study investigates the global aviation network, taking 10 years worth's OAG data from the years 2006–2015 and examines whether a spatial dispersal trend dominates the development of the aviation industry. It considers the aviation network at the airport level, and the airport–city level, which may consist of one or more airports. After clarification of the various definitions of concentration, we find that there appears a trend toward a dispersal pattern in the global aviation network at the airport level. On the other hand, there appears a slight concentration at the airport–city level. Besides, there have been some major capacity expansions at airports in the Middle East and East Asia, while the capacities of some traditional hubs in Europe and North America have become increasingly constrained since the 2008 global financial crisis. Furthermore, our study provides further observations consistent with the phenomenon of bypassing of traditional hubs, especially mega-hubs. Competition for passengers among hubs and secondary airports, especially in multi-airport cities, is discussed.
The development of modern economy makes the problem of traffic congestion increasingly serious. Many real traffic systems can be abstracted as that a variety of networks coupled and interconnected with each other. In this paper, the traffic dynamics on a double layer coupled network system is studied based on cellular automata model considering physical queuing. We explore the effect of maximal velocities in the two layer networks on the network capacity, and the mean and standard deviation of travel time. The results show that the increase of upper network velocity is beneficial to the traffic capacity and the efficiency of long-distance travel, but will also lead to larger deviation and lower reliability. We explain the phenomena by studying the usage of upper network. Finally, we investigate the vehicle distribution by adopting the Gini coefficient. It is found that the increase of upper network speed will make the traffic load distributed more uniformly in the system.
The paper explores patterns of flows within India’s Air Traffic System through the lens of carriers’ networks and route structures between 2006 and 2014. Through observations of frequency distributions and their distinct patterns an analytic framework is derived heuristically by means of classification and aggregation. The well-known skewed traffic distribution which spatially concentrates traffic around relatively few airports serves as the starting point for decomposing the air traffic system (ATS) into its constituent route types. Airline operations along distinct route classes allows for classifying individual carrier’s network features as an embedded part of the system. Discussion of their role includes a spatial component. Inferences about development paths – past, present, future – of the Indian commercial ATS can be made.
The emergence of low-cost carriers (LCC) in the aviation industry has dramatically decreased the cost of short-to-medium distance air travel, alongside the growth of the tourism industry. LCC has also changed the competitive dynamics within the aviation industry, challenging the traditional market dominated by conventional full-service carriers. Past studies have demonstrated the scale of impact of LCC on the aviation market, but have yet to explore the intricate dynamics of competition in greater detail. This paper utilizes the Lotka–Volterra model to assess the changing impact of the entrance of LCC on South Korean tourism and airline industries. Our results offer insights to industry players on developing sustainable strategic plans for future routes and tourism destinations in Asia and beyond.
To address the issues of military supply distribution and transportation under the restrictions of concealment during war preparation and warfare periods, this study proposes a double-entropy model to measure the degree of the comprehensive concealment of military supply transportation from the perspectives of transportation and detection. With respect to the real road conditions, we further develop this double-entropy model with consideration of the width and length of roads and introduction of the limitations of average transportation. The reasonability of this model and its related definitions are then demonstrated by theoretical analysis and mathematical proof. Subsequently, three distinctive properties of military supply transportation via a road or a road network, namely unordering, scalability, and directionality, are investigated. Based on the double-entropy model and the above properties, a flow distribution model of military supply is designed, which addresses a vital issue in the event of a military confrontation or regional war. Finally, we provide an example that calculates an optimal flow distribution schedule to carry out a regional military drill in the Jiangsu Province of China to demonstrate the proposed concepts and approaches.
Recently, while building or expanding of a large hub airport becomes controversial in economic, social and environmental facets, the idea of inter-modal substitution of short-haul air spokes by high-speed trains (HST) becomes a realistic option. This paper aims to analyze what shape of inter-modal network is efficient, and how beneficial it would be on passengers. Genetic Algorithm is applied to find the best mixture of Haneda Airport’s operation capacity allocation to domestic destinations and the spatial configuration of HST network, maximizing the consumer surplus of Japanese domestic inter-city passengers. The result of our analysis shows that HST service of 2400 km as provided in 2000 is essential for keep mobility, and that operation capacity shortage problem at Haneda is solved by additional HST service. The shape of optimal HST network becomes different according to the change of the operation capacity of Haneda.
In this study, a novel analytical method of airline network efficiency is developed and is applied to African airline network. The results suggest that the improvement of load factor, lower fare, and waiting time can be achieved by aggregation of flight routes. The improved network has fewer routes but a larger number of flights compared to the current network. In addition, long-distance routes would decline, but short-distance routes would increase, which would generate the improved network with the hub and spoke form. Especially, the network efficiency can be improved by using some of North African cities as hubs of the network connecting Europe and Africa. In the scenario of demand increase in 2030, some long-distance direct flights can be more profitable than connection flights demand. It would make African cities lose their significance of the hub roles, increasing connection demand through European cities.
Air transportation is one of the most dynamic modes of transport and it has been considerably influenced in the Slovak and Czech Republics by the politico-economical developments occasioning major changes since 1989. The aim of this paper is to analyze the aviation networks of Bratislava and Prague and particularly the changes of air transport connections between these cities from before the EU enlargement in 2003 until the present. Stability and actuality of aviation networks in these two cities were assessed by using comparative analyses. The liberalization and deregulation of air traffic in Europe have had a great impact on the airline networks of both airports. However, the Prague aviation network has shown much greater stability than the Bratislavan entity between 2003 and 2009.
The ‘hub-and-spoke’ network is an important design for a variety of transportation and communications systems. Critical to the hub-based model is the idea that flows between origins and destinations passing through intermediate switching points along the journey. Flows pass from origins via spokes to hub(s), and from hub to hub, and finally from hub to destination. Hubs can therefore be viewed as switching points for interactions. The location of these hubs has become an active area of research for geographers and others interested in the operational planning of diverse areas such as telecommunications, logistics, and passenger transportation. While there are many variants on the conceptual problem, they can be usefully broken down depending on their approaches to three key questions: do nodes connect to ‘single’ or to ‘multiple’ hubs; is the hub-to-hub subnetwork fully connected; and, are nodes permitted to be connected to each other directly, bypassing the use of hubs? A full suite of techniques from mathematical programming has been devoted to designing efficient solutions for such networks, under a variety of connection protocols. Important insights include the contrast between hub location and classical facility location, and extensive algorithmic work that has extended the theoretical models to practical cases.
Air transport networks have exhibited a trend towards complex dynamics in recent years. Using Lufthansa's networks as an example, this paper aims to illustrate the relevance of various network indicators - such as connectivity and concentration - for the empirical analysis of airline network configurations. The results highlight the actual strategic choices made by Lufthansa for its own network, as well in combination with its partners in Star Alliance.
This paper reviews the literature on the uneven patterns of airport seat capacity. Seat capacity distribution studies are useful to show air travel possibilities and whether economic development is concentrated in some particular regions. During the last decades, seat capacity patterns have been reshaped by an increasing process of deregulation of the air traffic market and liberalization of the former flagship carriers. Overall, literature agrees that intra-continental seat capacity has tended to deconcentrate, meaning that seats are more equally spread along the airport population, while inter-continental seat capacity, the most valuable for the exchange of face-to-face information and global supply chains, has tended to concentrate in fewer airports. Hence, in quantitative terms inequality has decreased, although in qualitative terms it has increased.
Considering coordinated layout of comprehensive transportation terminal, this paper increases two constraint conditions for transportation pattern and hub transfer ability in traditional model of passenger terminal planning, puts forward a nonlinear integer programming of comprehensive passenger transport multiple hubs based on capacity limitation and transportation pattern, and designs an improved genetic algorithm. LINGO software is applied to the model effectiveness test of optimized layout to cumulate the standard data of 8 nodes Solomon, the average operation time of LINGO is about 5 102 s and the optimum cost is 1 899 782 Yuan; the average operation time of genetic algorithm programming is about 59 s and the optimum cost is 1 948 796 Yuan. The average operation time is about 569 s and the optimum cost is 8 497 602 Yuan if cumulating 50 nodes data; the optimum cost is 154 932 Yuan if using AP data set of 25 nodes and taking 3 hubs, the average operation time is about 607 s and the optimum cost is 155 098 Yuan through traditional hub planning model, while the optimum cost reduces 166 Yuan when compared to the classical algorithm. So the optimization model of developed joint terminal layout has faster solving speed and less optimal cost than traditional model of joint terminal planning.
Over the last decade, the demand for domestic and international flights in Korea has increased substantially. To meet the strong flight demands, several low cost carriers have begun to offer flight services. In addition, full service carriers have been motivated to establish their own subsidiary low cost carriers to maintain their market share against rival low cost carriers. This paper studies the management strategies of three kinds of airlines - full service carrier, its subsidiary low cost carrier and rival low cost carrier - based on game theory in the competitive air transport market. Each airline is assumed to act as a player and chooses strategies regarding airfare, flight frequency, and the number of operating aircrafts for specific routes while maximizing its own profits. Demand leakages between the airlines are considered in the flight demand function according to the selected strategies of all airlines. Through various game situations reflecting realistic features, this study provides managerial insights that can be applied in the competitive air transport market.
Network aspects of the U.S. and E.U. air freight industries are examined. Distinctions between passenger and freight operations are made and the important role of an air carrier's network is discussed. In the U.S.A. after air cargo deregulation in 1977, all‐cargo carriers greatly increased their share of the air freight market by diversifying the range of air freight products offered and by developing multimodal networks. The all‐cargo operators organized their networks around single hub while the combination passenger/cargo carriers have developed interactive hub‐and‐spoke systems based around several regional hubs. These networks have evolved more for passenger needs than for cargo needs. The traffic distributions for several of the E.U. ‘flag carriers’ are then analysed. The E.U. carrier's network is typically a single hub operation, largely because regulations up until 1993 have prevented the development of hubs outside of the national territory. The liberalization of air transport now permits carriers to expand their networks within the E.U. by entering international community routes. E.U. carriers are likely to develop interactive hub‐and‐spoke networks involving several regional hubs as this network system has many economic and strategic advantages. Given congestion problems and the dominant position of flag carriers at their home ‘hub’ airports, these networks will develop through mergers and acquisitions rather than through independent growth. This liberalization will lead to further concentration of activity in the community's core area with many peripheral regions being made worse off as air services to smaller communities are reduced.
*The purpose of Practitioner's Corner is to publish brief methodological notes of interest to applied economists. The Editors welcome submissions of this sort.
This article provides the first evidence linking airfares to the structure of airline hub-and-spoke networks. The hypothesis tested is that any force that increases traffic volume on the spokes of a network will reduce fares in the markets it serves. This effect arises because of economies of density on the spokes. For example, since a large network (as measured by the number of city pairs that it connects) is expected to have low costs per passenger as a result of high traffic densities, fares in the individual markets served should be low, other things equal. Similarly, holding size fixed, a network that connects large cities should have higher traffic densities on its spokes (and thus lower fares in individual markets) than one serving small cities. Our empirical analysis supports these predictions. We find that network characteristics are important determinants of fares in 4-segment city-pair markets (these are markets requiring a connection at the hub). Furthermore, our empirical model predicts that the TWA-Ozark and Northwest-Republic mergers should have reduced fares in the 4-segment markets served by the hubs at St. Louis and Minneapolis.
There has been an inequality of concern throughout history about equality as a social issue. This varying concern serves, in part, to explain the exclusion of equality in many theoretical contexts. Equality did have its moments in the intellectual sun under the pens of Aristotle, Hobbes, Rousseau, Marx and Mill. Yet, with the rise of capitalism, inequality came to be accepted as a transitional economic reality necessary for the engine of economic progress. Indeed, Kant decreed that inequality among men was a rich source of much that was evil, but also of everything that was good. Over time inequalities were to slowly decrease as economic systems matured.
Airline hubbing can be viewed as a strategy to increase airline network efficiency and to reduce operating costs Alternatively hubbing can be viewed as a marketing strategy permitting airlines to achieve dominant market shares at their hub airports and to take advantage of market preferences for the increased frequancies that the strategy permits This study inquires into the hypothesis that significant cost reductions can be achieved by hubbing Using a detailed cost analysis of 13 airlines with different degrees of hubbing over the period 1976-1984 we find no evidence of a relation between the degree of hubbing and cost levels The current conclusion is that the explanation of hubbing is likely to be found in an analysis of airline marketing strategies and in market response to airline routing and networking decisions.
This paper measures the change in the extent of hub-and-spoke routing in the US since deregulation and the effect of this change on airline costs. The results indicate that hub-and-spoke routing has increased by 48 percent between 1977 and 1984 and that airline costs are reduced by 0.1 percent for every 1 percent increase in hub-and-spoke routing. The implications of this result for airline competitiveness are discussed. -Authors
The phenomenon of airline hubbing has been on the increase in recent years. Hubbing arises when airlines attempt to maintain high levels of aircraft utilization and to take advantage of scale economies. Passengers also appear to benefit from hubbing in the form of increased frequency of service. The nature of traffic generated at the hub airports implies some negative economic impacts which suggest that hub pricing should be considered seriously. This study shows hubbing to be “inelastic” to hub pricing and concludes that there are significant potential benefits to the airports to be gained from some form of hub pricing.
This note explores the extent to which airlines operating large hub-and-spoke networks secure a competitive advantage. More specifically, this paper explores the intricate relationship which arises among productive efficiencies and profitability when the size of the hub-and-spoke network expands. To this end, Brueckner and Spiller (1991, International Journal of Industrial Organization 9, 323–342) airline economics model is generalized by allowing the size of the hub-and-spoke network to vary. The central result shows that, although the model exhibits decreasing returns to firm/network size (RTNS), nonetheless there is a competitive advantage to increasing the size of a network.
In this paper, we analyze the service provided by the 13 largest U.S. passenger airlines to the 100 most populous U.S. metropolitan areas in 1989. We classify the route systems by their nature and geographic scope using a variety of measures based on route-level data. We then identify individual airline hub locations; derive and calculate several measures of the extent of competition on individual routes, for individual airlines, and at the airports in our sample; and analyze relationships among route structure, costs, and subsequent carrier performance. The results show the wide diversity of route networks that existed in the airline industry in 1989—a phenomenon that may help to explain the eventual failure of several major carriers.
This paper surveys changes in the U.S. National Airway System since the 1960s. The most appropriate measures for summarizing air traffic distributions at airports are investigated, with the Gini Index of Concentration being used extensively to analyze U.S. airport traffic patterns over a twenty-four-year period. The properties of the Gini index and other measures are compared and discussed in detail in the context of analyzing air traffic distribution. It is shown how concentration in the traffic patterns at the larger airports was at a high level prior to deregulation, but since 1978, the patterns have gradually become even more concentrated.
Thesis (Ph. D.)--Northwestern University, 1986. Includes bibliographical references.
Thesis--Columbia university. Bibliographical footnotes. Typewritten manuscript.
This article estimates a structural model of competition among hub-and-spoke airlines in order to measure the strength of economies of traffic density on individual route segments. We find that economies of density were strong during the sample period (fourth quarter 1985), stronger than previous estimates by Douglas Caves, Laurits Christensen, and Michael Tretheway derived from traditional cost-function methods. We also find that the airlines' competitive behavior was far from collusive in the markets under study (markets requiring a connection at a hub airport). Our structural model also provides plausible estimates of demand elasticities. We use our estimates to provide a cost-based rationale for the major changes in the structure of the industry following deregulation (for example, the increase in airport and industry-wide concentration, and the increase in competition at the city-pair market level) and to simulate the effects of a merger of airlines that share a hub. Copyright 1994 by the University of Chicago.
There has been a perception that U.S. trunk airlines had an inherent cost advantage over smaller regional airlines because of economies of scale. We have formulated a general model of airline costs, which we estimate by using panel data on large and small airlines. Differences in scale are shown to have no role in explaining higher costs for small airlines. The primary factor explaining cost differences is density of traffic within an airline's network. Also of major importance is the average length of individual flights.
The primary aim of this paper is to propose a new measure of poverty, which should avoid some of the shortcomings of the measures currently in use. An axiomatic approach is used to derive the measure. The conception of welfare in the axiom set is ordinal. The information requirement for the new measure is quite limited, permitting practical use.
The Low Cost Airline Service Revolution, US Department of Transportation
- Us Dot
US DOT, 1997. The Low Cost Airline Service Revolution, US Department of Transportation (available at: http://ostpxweb. dot.gov/aviation/domav/lcs. pdf).
The Economic Effects of Airline Deregulation A note on the competitive advantage of large hub-and-spoke networks
- S Morrison
- C Winston
Morrison, S., Winston, C., 1986. The Economic Effects of Airline Deregulation. Brookings Institution, Washington, DC. Nero, G., 1999. A note on the competitive advantage of large hub-and-spoke networks. Transportation Research E 35, 225–239.
U.S. Air Passenger Service
- Bania
Economics of density versus economies of scale
- Caves
Hubbing and airline costs
- Kanafani
EC and US air freight markets
- Reynolds-Feighan