lect4b

# lect4b - Airline Demand Analysis and Spill Modeling...

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Airline Demand Analysis and Spill Modeling 16.75J/1.234J Airline Management Dr. Peter P. Belobaba February 2006 Stochastic and Cyclical Nature of Demand The total demand for a particular flight even at a given time of day fluctuates by day of week and season of the year. In addition to these more predictable or “cyclical” fluctuations in demand, there are also less predictable or “stochastic” variations in demand around the mean or expected value for a flight: We can represent the total uncertainty of demand for a future flight departure with a probability distribution (density) of expected demand. Historically, a Gaussian (Normal) distribution of demand has been assumed, with a mean and standard deviation that depend on the market being studied and on the nature of its traffic. Based on many empirical studies of actual airline data, the standard deviation of total demand for a flight relative to the mean demand is typically between 0.20 and 0.40. This measure is also known as the “coefficient of variation ” or “k- factor ” of demand, defined as: k-factor = standard deviation / mean demand The “k-factor” of demand for a given flight will depend on the variability of demand over a series of days, weeks or months. Leisure markets typically will have higher k-factors of demand than business or mixed travel markets with more stable demand patterns. It is important to understand that, in practice, it is difficult if not impossible to observe the actual “demand” for a flight. This is especially true if at least some of the departures of a series of flights on the same route at the same time of day and/or day of week depart full: Airlines have no way of keeping track of how many requests for bookings on a given flight departure were turned away or rejected if there was not enough space on the aircraft to accommodate all passengers that wished to travel on the flight. The notion of “total demand” for a particular flight or set of flights operated over a period of time is therefore a theoretical concept. Thus, the analysis of “total demand” (as opposed to the number of passengers who actually were transported) requires models and assumptions, as described below. 1

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Terms and Definitions DEMAND : The total number of potential passengers wishing to make a reservation on a particular scheduled flight leg. In line with our definition of “demand” for an origin-destination market in Air Transportation Economics, the “demand” for a flight leg reflects a maximum potential, independent of the capacity being offered on the flight. LOAD : The total number of passengers who are actually carried on the flight leg. Because the demand for a flight can sometimes be greater than its capacity, it must be
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lect4b - Airline Demand Analysis and Spill Modeling...

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