Passenger Demand For Air Transportation In A Hub And Spoke Network

Author : Bo Zou (Writer on transportation)
Publisher :
ISBN 13 :
Total Pages : 238 pages
Book Rating : 4.:/5 (81 download)

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Download or read book Flight Delays, Capacity Investment and Welfare Under Air Transport System Equilibrium written by Bo Zou (Writer on transportation) and published by . This book was released on 2012 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Infrastructure capacity investment has been traditionally viewed as an important means to mitigate congestion and delay in the air transportation system. Given the huge amount of cost involved, justifying the benefit returns is of critical importance when making investment decisions. This dissertation proposes an equilibrium-based benefit assessment framework for aviation infrastructure capacity investment. This framework takes into consideration the interplays among key system components, including flight delay, passenger demand, flight traffic, airline cost, and airfare, and their responses to infrastructure capacity investment. We explicitly account for the impact of service quantity changes on benefit assessment. Greater service quantity is associated with two positive feedback effects: the so-called Mohring effect and economies of link/segment density. On the other hand, greater service quantity results in diseconomies of density at nodes/airports, because higher traffic density at the airport leads to greater airport delays. The capacity-constrained system equilibrium is derived from those competing forces. Two approaches are developed to investigate air transport system equilibrium and its shift in response to infrastructure capacity expansion. In Chapter 2, we first view the system equilibrium from the airline competition perspective. We model airlines' gaming behavior for airfare and frequency in duopoly markets, assuming that airlines have the knowledge of individuals' utility structure while making decisions, and that delay negatively affects individuals' utility and increases airline operating cost. The theoretical airline competition model developed in Chapter 2 provides analytical insights into the interactions among various system components. Under a symmetric Nash equilibrium, we find that the presence of flight delay increases passenger generalized cost and discourages air travel. Airlines would not pass delay cost entirely onto passengers through higher fare, but also account for the impact of service degradation on passenger willingness-to-pay and consequently passenger demand. To avoid exorbitant flight delays, airlines would use larger aircraft, meanwhile taking advantage of economies of aircraft size. The resulting unit cost reduction partially offsets operating delay cost increase. The equilibrium shift triggered by capacity expansion reduces both schedule delay and flight delay, leading to lower passenger generalized cost and higher demand, despite slightly increased airfare. Airlines will receive larger profit, and consumer welfare will increase, as a result of the expansion. Although delay reduction is less than expected because of induced demand, the overall benefit, which encompasses reduction in both schedule delay and flight delay, would be much greater than estimated from a purely delay-based standpoint. The equilibrium analysis can be alternatively approached from a traveler-centric perspective. The premise of an air transport user (i.e. traveler) equilibrium is that each traveler in the air transportation system maximizes his/her utility when making travel decisions. The utility depends upon market supply and performance characteristics, consisting of airfare, flight frequency, and flight delay. The extent of airline competition is implicitly reflected in the determination of airfare and flight frequency. Given the limited empirical evidence of the delay effect on air transportation system supply, two econometric models for airfare and flight frequency are estimated in Chapter 3. We find positive delay effect on fare, which should be interpreted as the net effect of airlines' tendency to pass delay cost to passengers while also compensating for service quality degradation. Higher delay discourages carriers from scheduling more flights on a segment. Both delay effects, however, are relatively small. The estimated fare and frequency models, together with passenger demand and airport delay models presented in Chapter 4, are integrated to formulate the air transport user equilibrium as fixed point and variational inequality problems. We prove that the equilibrium existence is guaranteed; whereas equilibrium uniqueness cannot be guaranteed. We apply the user equilibrium to a fully connected, hypothetical network with the co-existence of direct and connecting air services. Using a simple, heuristic algorithm, we find that the equilibrium is insensitive to initial demand values, suggesting that there may be a single equilibrium for this particular model instance. Hub capacity investment attracts spoke-spoke passengers from non-stop routes, and generates new demand on hub-related routes. At the market level, hub capacity expansion would result in greater total demand and consequently passenger benefits in almost all markets--except for ones where a predominant portion of passengers choose non-stop routes due to extremely high circuity for one-stop travel. In the latter set of markets, after capacity expansion passenger demand and benefits would be both reduced. This counter-intuitive result carries important implications that capacity increase does not necessarily benefit everyone in the system. Similar to the findings from the airline competition model, with changes in flight delay, schedule delay, airfare, and total demand, the user equilibrium model yields much higher passenger benefits from capacity investment than the conventional method; whereas hub delay saving is offset by traffic diversion and induced demand. With continuous capacity investment, the air transportation network will witness substantial changes in service supply and traffic patterns.