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Chapter 3
Demand Analysis and Optimal Pricing
scores of fares, ranging from first-class roundtrip tickets at $2,400 and greater to discount tickets below $250. On average, half the tickets sold for fares below $400, some 20 percent of tickets were priced above $800, with the remainder priced in between. Some travelers cashed in frequent flier miles. Some purchased at discounts from third-party providers; others received lower fares for restricted tickets requiring Saturday stayovers. In general, early buyers paid less, but fares fluctuated day-to-day depending on demand. The question here is: How can demand analysis help the airlines win the game of yield management?
In Chapter 2, we presented a simple model of profit maximization. There the manager began with demand and cost functions and used them to determine the profit-maximizing price and output level for a given product or service. In this chapter, we will take a closer look at demand and the role it plays in managerial decision making. The notion of demand is much richer than the simple formulation given in Chapter 2. For instance, up until now we have studied the dependence of demand on a single factor: price. We begin this chapter by considering the multiple determinants of demand. Next, we look more closely at the responsiveness of demand to these factors, a concept captured in the basic definition of elasticity. In the remaining sections, we present a richer formulation of demand and show how it can be used to guide managers in their goal of maximizing profits. Toward this end, we will refine our optimization techniques to account for more complicated demand conditions—those that include the possibilities of market segmentation and price discrimination.
DETERMINANTS OF DEMAND The Demand Function To illustrate the basic quantitative aspects of demand, let’s start with a concrete example: the demand for air travel.2 Put yourself in the position of a manager for a leading regional airline. One of your specific responsibilities is to analyze the state of travel demand for a nonstop route between Houston, Texas, and a rapidly growing city in Florida. Your airline flies one daily departure from each city to the other (two flights in all) and faces a single competitor that offers two daily flights from each city. Your task is complicated by the fact that the number of travelers on your airline (and therefore the revenue your company earns) has fluctuated considerably in the past three years. Reviewing this past experience, you realize the main determinants of your airline’s traffic are your own price and the price of your competitor. In addition, traffic between the two 2
We are not ready yet to analyze the complicated problem of setting multiple fares described in the opening of this chapter. That must wait until the concluding section.
