Carriers’ pricing behaviors in the United States airline industry

Chi, Junwook; Koo, Won W.

doi:10.1016/j.tre.2009.04.009

Cited by 17 publications

(17 citation statements)

References 14 publications

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“…As distance increases, average fares can be expected to rise since carriers' operating costs with regard to fuel, in-flight service and wages will increase (Borenstein, 1989;Vowles, 2006;Windle and Dresner, 1995). Because it can readily be assumed that passengers are not willing to pay for longer routing because of intermediate stops, the model uses the non-stop distance of a route irrespective of the actual route segments (Chi and Koo, 2009). The expected sign for DISTANCE is positive.…”

Section: Model Specificationmentioning

confidence: 99%

“…Researchers have found that airfares to cities in Florida, Hawaii, Nevada and Puerto Rico are lower because those cities are likely to have high competition for holiday travellers (Borenstein, 1989;Chi and Koo, 2009;Dresner et al, 1996;Dresner, 1995, 1999). In our framework, Miami (MIA) is the only holiday destination.…”

Section: Model Specificationmentioning

confidence: 99%

“…The severe delays and the longer departure procedure at ORD may increase passengers' travel time and reduce the service level. This may decrease demand and lead to a decline in airfares (Chi and Koo, 2009). The expected sign of SLOTCONTROL is negative.…”

Section: Model Specificationmentioning

confidence: 99%

“…The extensive literature on airfare pricing strategies in the US aviation market predominantly focuses on (i) individual carriers' overall route networks (Chi and Koo, 2009;Lee and Luengo-Prado, 2005), (ii) the United States air transportation network as a whole (Borenstein, 1989;Brueckner et al, 1992) or (iii) specific airports (Borenstein, 2005; US Department of Transportation, 2001). As a consequence, there has been relatively little research exclusively focused on how carriers determine airfares in hub-to-hub (HH) markets, where both origin and destination are to some degree dominated by a full-service carrier (FSC).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The impact of hub hierarchy and market competition on airfare pricing in US hub-to-hub markets

Zhang

Derudder

Witlox

2013

Journal of Air Transport Management

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This paper explores factors influencing the pricing behaviour of full-service carriers in hub-to-hub markets, which to date have rarely been the exclusive focus of research. Drawing on a 2009 dataset containing route and airfare information, we estimate a pricing model for hub-to-hub markets in the United States. Our econometric analysis suggests that an airport's position in carriers' hub hierarchies, competition from low-cost carriers, and other market structure variables influence average airfares.

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Section: Model Specificationmentioning

confidence: 99%

Section: Model Specificationmentioning

confidence: 99%

Section: Model Specificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The impact of hub hierarchy and market competition on airfare pricing in US hub-to-hub markets

Zhang

Derudder

Witlox

2013

Journal of Air Transport Management

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“…non-stop or connecting route) and distance. The variables measuring demand side include income, population, tourist or business travellers orientation of the origin and destination cites and other market characteristics (e.g., hub airport, slot-controlled airport, and multiple airports) (Chi and Koo, 2009).…”

Section: Determinants Of Airline Pricingmentioning

confidence: 99%

Airport dominance and airline pricing power: An investigation of hub premiums in the Chinese domestic market

Chen

Lei

2017

Transportation Research Part A: Policy and Practice

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Concerns on market power conferred by airport dominance and the debates of hub premiums have attracted longstanding attention from governments and academics alike. Most previous studies mainly focus on the fully deregulated markets such as the United States and Europe, what remains unknown is how such effects change when a country evolves from a tightly controlled regime to a deregulated market. This research analyses the effects of airport dominance on airline pricing power with the empirical study based on the Chinese domestic market using fixedeffect panel data models. Results from the regression analysis indicate that airport dominance is the most important source of pricing power in the gradually deregulated Chinese domestic market. Hub carriers are able to charge higher prices to premium class passengers and non-hub carriers can benefit from the "umbrella effects" of hub premiums. However, hub carriers are not able to translate their airport dominance to pricing power in the economy class market, whereas non-hub carriers even have to reduce the prices as their market shares at major airports increase. This study contributes to the literature by explicitly segmenting the market into economy and premium classes. The results have important policy implications.

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