Consumer Demand Analysis and Estimation Applied Problems

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Consumer Demand Analysis

Learning Objectives

A�er reading this chapter, you should be able to:

Understand that indifference curves can depict the consumer's tastes and preferences in product space and predict the consumer's reac�on to changes in price, income, and other variables that enter the consumer's decision func�on. Explain that the price effect is always nega�ve, such that demand curves slope downwards. Dis�nguish between the income and subs�tu�on effects of a price change, and explain why the income effect is posi�ve for superior goods and nega�ve for inferior goods. Dis�nguish between changes in demand (i.e., shi�s of the demand curve) and changes in quan�ty demanded (i.e., movements along a demand curve). Explain that choice between compe�ng brands can be modeled as deriving from the different a�ribute combina�ons inherent in differen�ated products. Discuss how the firm can increase its value proposi�on to consumers by changing one or more of the four "P" marke�ng variables.

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A consumer's preference for Coca-Cola over Pepsi can be be�er understood through brand-based analysis, which evaluates consumer reac�on to changes in product design, promo�on, place of sale, and packaging and service quality.

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Introduction

Managers make many of their decisions based on what they expect their customers to do. By tradi�on, economists call these customers consumers, meaning the ones who

purchase (and typically also consume)1 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/ch03introduc�on#ch03txt1) the firm's products.2

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/ch03introduc�on#ch03txt2) Managers can influence the purchasing behavior of consumers by adjus�ng one or more of the variables that enter the consumer's decision purchasing process—these variables are known as decision variables and include product price, product design and packaging, product availability, and product promo�on. It is important for managers to understand how consumers are likely to respond to changes in these variables because changes cost money to implement and have subsequent cost and revenue impacts. In this chapter, we examine consumer decisions using a predic�ve model that indicates how consumers are likely to react to changes in both a firm's controllable decision variables, such as those men�oned above, as well as to changes in uncontrollable variables, or variables that are not controlled by the firm, such as consumer income levels and changes in compe��ve behavior by rival firms.

Consumers make choices within product categories (between different brands of so� drinks) and between product categories (between taking a vaca�on or buying a new car). Within product categories the products are close subs�tutes, meaning they are differen�ated but qualita�vely similar, and the customer will choose one brand in preference to the other brands. Across different product categories, the products are dissimilar but are gross subs�tutes, meaning that if one buys one product this limits the amount of money le� to buy products in other categories. In this chapter we will consider the consumer's decision problem in both scenarios. We first consider the consumer's choice problem in the context of different product categories For example, the consumer is choosing between his or her preferred so� drink (Coca-Cola) and his or her preferred brand of cheese (Swissco's Gruyere). In this context, we will examine the impact on quan�ty demanded of these two products for changes in prices and consumer incomes. The main issue here is to understand how consumers, with limited income and unlimited wants and needs, allocate that limited income among the available product and service categories such that they maximize their u�lity.

In the la�er half of this chapter we ask what is it about products that cause the consumer to want to buy a par�cular brand within a product category. Thus, we will shi� our level of analysis from between products to within products to consider what characteris�cs of a brand are desirable to the consumer. So, whereas our analysis is ini�ally product category based—the choice of so� drinks versus cheese—we shi� to brand-based analysis within a par�cular category—the choice of Coca-Cola versus Pepsi. This allows us to consider the consumer's reac�on to changes in the firm's controllable decision variables such as changes in product design, promo�on, place of sale, packaging, and service quality. For example, one brand may gain sales by improving the quality of its product, adver�sing more, offering it for purchase online, and so on. You may note that these are tradi�onally considered marke�ng decisions, and indeed we want to examine the underlying economics of these marke�ng decisions in the context of managerial economics, as an aim of this book is to integrate managerial economics with other business disciplines.

1. In some cases the purchaser of the firm's product buys it for someone else to consume, such as dog food or children's clothes, in which case we say there is indirect demand for the firm's product from the end consumer (i.e., the dog or the child). In other cases of indirect demand, such as in business-to-business (B2B) retailing, one firm buys the firm's products in order to re-sell them to the end consumer. In general, the purchaser buys the product expec�ng to best serve the end consumer's wants and needs. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/ch03introduc�on#return1) ]

2. We use the term "product" to mean the outcome of the firm's produc�on process. Thus "products" might mean either goods or services, and indeed are generally a combina�on of the two, such as a haircut with fla�ery, a meal with a�en�ve service, or a baseball game with a hotdog. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/ch03introduc�on#return1) ]

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3.1 Consumer Choice Between Product Categories

The model we will use to predict consumer behavior is the u�lity-maximizing model. This is the same model that was introduced in Chapter 2 to explain how managers make decisions that include risk and uncertainty. The u�lity-maximizing model of consumer behavior says that individual consumers make decisions to buy products based on the expecta�on that the purchase will allow them to gain the most psychic sa�sfac�on, or u�lity, from their limited incomes. In Chapter 2, we saw that the individual's u�lity can be depicted by indifference curves, which are curves joining combina�ons of items that give equal u�lity to the individual. In Chapter 2, we considered indifference curves in risk and return space, where the individual gained u�lity from return and disu�lity (i.e., nega�ve u�lity) from risk. In the risk–return applica�on, the indifference curves were posi�vely sloping because, to stay at the same level of total u�lity, a combina�on that had more risk must also have more return. However, when we analyze consumer choice in product space we generally consider only items that give the consumer u�lity, since people would not willingly purchase products that would

give them disu�lity (such as garbage).3 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt3) When both the items under considera�on generate u�lity, we will have nega�vely-sloping indifference curves, since there must be reduced consump�on of one item to stay at the same level of total u�lity when consump�on of the other is increased. Indifference curve analysis allows us to predict the choices that a consumer will make in response to changes in product prices and consumer incomes, as we shall see.

Let us illustrate this in the context of Bob Goodguy, who likes to spend his discre�onary income (what is le� from his pay check a�er paying for his necessary expenditures, such as accommoda�ons, food, and commu�ng expenses) on entertainment. He loves to go to baseball games and watch new movies in the theater. Using indifference curve analysis we can plot out his preferences in baseball–movie space, as shown in Figure 3.1. The number of movies is shown on the ver�cal (or Y) axis and the number of baseball games is shown on the horizontal (or X) axis. Each indifference curve shows combina�ons of baseball and movies that Bob considers equivalent in terms of total u�lity.

Figure 3.1: Indifference curves in product space

In Figure 3.1, point A represents 5 movies and 2 baseball games. Because point A and point B are on the same indifference curve (I3), Bob must consider 5 movies and 2

games to be equally sa�sfying as 4 movies and 3 games. Note that point C, represen�ng about 2.6 movies and 3 baseball games, offers less total u�lity than point B since it

has the same number of games but fewer movies.4 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt4) Also note that point C offers more u�lity than point D since it has the same number of movies but more games. Finally, note that since points A, B, and E are superior to point C, and since point C is superior to point D, then points A, B, and E must also be superior to point D.

Indifference curves depict the preference structure of the individual—that is, what products the person likes and how much they like the various products. Indifference curves show what combina�ons of two products are considered equal to, inferior to, or superior to any other combina�on. Figure 3.1 shows the indifference map for Bob Goodguy in baseball–movie space, but necessarily shows only a few of his indifference curves. Because every point in the space would have an indifference curve passing through it, the complete indifference map showing every indifference curve would totally black out the space and we would see nothing, so we show only selected indifference curves to illustrate the consumer's choice problem that we wish to explain.

It is important to note four specific proper�es of indifference curves. First, points on higher curves are preferred to lower curves, because we assume that, all other things being equal, consumers always prefers more rather than less of any product. Second, indifference curves in product space are nega�vely sloped throughout, because we assume that the consumer always gains posi�ve u�lity from both goods. Giving up one unit of product Y (in this case movies) must require gaining more of product X (baseball games) to stay at the same level of total u�lity. Third, indifference curves neither meet nor intersect, due to the assump�on of transi�ve preferences. For example, in Figure 3.1, if B is preferred to C, and C is preferred to D, then B must be preferred to D. Fourth, indifference curves are convex from below. Convexity means that the slope of the indifference curve becomes increasingly fla�er as we move down that indifference curve. This convexity is due to the phenomenon of diminishing marginal u�lity.

Diminishing Marginal Utility

In Figure 3.1 we see that the consumer is willing to subs�tute movies for baseball games, or vice-versa, to stay at the same level of u�lity on a par�cular indifference curve. The rate at which Bob Goodguy subs�tutes movies for baseball games can be seen in Figure 3.1—moving from point A to B, he gives up one movie for one addi�onal baseball game (ra�o 1:1), but moving from point B to point E he gives up 1.4 movies (from 4 movies to 2.6 movies) for an addi�onal 1.7 baseball games (from 3 games to 4.7 games) which is a ra�o of 0.8235:1. It is clear that the rate at which he is willing to subs�tute movies for games changes as he sees fewer movies and more games. We call this rate the marginal rate of subs�tu�on (MRS), which is defined as the amount of product Y (movies in this example) that the consumer will be willing to give up for one more unit of product X (baseball games) while remaining at the same level of total u�lity. The s�pula�on that the consumer remains at the same level of total u�lity makes it clear that we are talking about a movement along a par�cular indifference curve and by conven�on we define the MRS for a movement down a par�cular indifference curve. Since a movement down an indifference curve must follow the slope of that indifference curve, it is clear that the MRS is equal to the slope of theProcessing math: 0%

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Diminishing marginal u�lity is commonly observed for virtually all goods and services including water. Economists assume that marginal u�lity decreases for all products for all people.

© Comstock/Thinkstock

indifference curve at any point. Because we have drawn the indifference curves to be convex to the origin, the slope becomes increasingly fla�er as we move down an indifference curve, illustra�ng that the MRS declines as we move down an indifference curve.

As indicated above, the convexity of an indifference curve is due to the assump�on of diminishing marginal u�lity. The marginal u�lity (MU) of a product is defined as the change in total u�lity that is due to the consump�on of one more unit of that product, holding constant the consump�on of all other products (i.e., with all other things being equal). Consumers normally find that their perceived MU declines progressively as consump�on of any par�cular product increases, other things being equal. For example, suppose you have just finished exercising and really want a drink of water. You might expect to gain a lot of u�lity, say, 20 u�ls (i.e., 20 units of u�lity) from that bo�le of water. Suppose a�er you drink this bo�le you then consider drinking another bo�le. You might s�ll be quite thirsty but would certainly expect to gain less u�lity from the second bo�le than from the first, say 10 u�ls. A third bo�le is likely to promise even less u�lity, say 5 u�ls, and a fourth bo�le only 2 u�ls, and so on. Note that addi�onal bo�les of water would make you feel uncomfortable or sick and we assume that people stop consuming a product before MU becomes nega�ve. Diminishing marginal u�lity is commonly observed for virtually all goods and services, so economists assume

that MU decreases for all products for all people.5 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt5)

To understand why diminishing marginal u�lity causes indifference curves to be convex, note that moving down an indifference curve means the consumer is consuming more of product X and less of product Y but total u�lity is not changing. Thus, the loss in total u�lity due to giving up units of Y must be equal to the gain in total u�lity from the addi�onal units of X as the consumer moves along the indifference curve. Since the consumer is giving up units of Y, the MU of the units of Y being given up must be ge�ng progressively higher, and conversely, since the consumer is gaining units of X, the MU of these units of X must be ge�ng progressively lower. So to remain at the same level of total u�lity the amount of product Y must be decreasing and the amount of

product X must be increasing, and thus the indifference curve is convex.6

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt6)

The Consumer's Budget Constraint

Using indifference curves, we have modeled the consumer's preferences, so we now know what the consumer wants. Next we have to consider what the consumer can afford. For simplicity we will assume that the consumer earns a salary each week and can spend that money on goods and services. This analysis is easily extended to recognize credit cards, bank loans, and previously accumulated wealth on the one hand, and nondiscre�onary expenditures on the other, but a simple introduc�on is provided by assuming that the consumer has a limited budget equal to his or her weekly wage or salary income.

How far will the consumer's income stretch? That depends on the prices, of course. Let's go back to Bob Goodguy and assume that Bob's budget is $120 per week, that the price of a baseball game is $20, and the price of a movie is $23 (these prices include extra items like a hotdog at the baseball game and popcorn at the movies). If Bob spent all $120 on baseball games, he could afford to go to 6 games a week (120/20 = 6), or if he spent the en�re $120 budget on movies he could go to 5.22 movies a week (120/23 = 5.22). While diminishing marginal u�lity suggests he will not want to do either of these two extreme budget alloca�ons, these boundaries define the points where the budget constraint line intercepts the X and Y axes, at 6 baseball games and 5.22 movies, respec�vely, as shown in Figure 3.2. A straight line drawn between these points joins all the combina�ons of baseball and movies that will cost $120 in total.

In Figure 3.2, we see that Bob's u�lity-maximizing combina�on of these two products is to a�end baseball games at the rate of 3 per week and movies at the rate of 2.6 per week. Any combina�ons that offer more total u�lity must lie on indifference curves that lie above I2 and are not affordable given Bob's budget constraint. The u�lity-

maximizing combina�on of products that the consumer can afford is thus found at the point of tangency between the budget line and the highest a�ainable indifference curve. Any lower indifference curve would cut the budget line twice and points on that curve would be an inefficient way to spend his income. Any combina�on that lies on a higher indifference curve would not touch the budget line at all, and thus would be unaffordable. Thus, the model predicts that Bob will allocate his income between

baseball and movies such that he maximizes u�lity from his limited income.7 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt7)

Figure 3.2: The u�lity-maximizing combina�on of products given a budget constraint

Price Changes and the Individual's Demand Curve

The consumer's demand curve shows how much the consumer will demand at various prices that the firm might set. Managers o�en consider changing their prices to gain more profit, and they would like to know by how much individuals would change their quan�ty demanded as a result of the change in price. We know that the consumer's budget constraint line is located according to his or her budget constraint and the prices of the two products. Accordingly, we should expect that if any one of these three variables changes, the budget line must change and a new combina�on of the two products will become u�lity-maximizing. We shall illustrate with the price of baseball

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When baseball club management wants to increase profits they need to know whether raising prices to get more money from those who already come to the games or reducing prices to en�ce more people to a�end the games will generate greater profits.

© Eric Thayer/Reuters/Corbis

�ckets. Suppose a baseball club's management is trying to increase profits so they can buy be�er pitchers for the team. They first need to know whether they should raise �cket prices (to get more money from those who already come to the games) or reduce prices (to en�ce more people to come to the games). Suppose they start doing market research and interview our typical baseball fan, Bob Goodguy. They ask Bob how many �mes a week he would come to the games if the �cket price (including Bob's hot dog and other incidentals) were $10, $15, $20, and $30, respec�vely. To predict Bob's answers, we can look at his preference map and the impact of the price changes on the affordability of the baseball games at these four different prices, as shown in Figure 3.3.

As you can see in the upper half of Figure 3.3, we have rotated the budget line around to the right to reflect the four different price levels, while holding the price of movies the same as before. The intersec�on points on the horizontal axis must be the income constraint ($120) divided by the price of baseball games in each case, and so are 120/30 = 4 (for the steepest budget line); then 120/20 = 6; then 120/15 = 8; and finally 120/10 = 12 (for the fla�est budget line shown), respec�vely. Note that one of Bob's indifference curves is tangent to each of these budget lines, indica�ng that Bob would maximize u�lity if he consumed 1.5, 3, 4.5, and 6 baseball games per week under each of the different price scenarios, respec�vely. Note that the number of movies chosen varies according to the price of the baseball �ckets as well. It does not follow that Bob will necessarily choose more movies when the price of baseball rises; it also depends on the MRS at various levels of consump�on of the two products.

Figure 3.3: The price effect and the consumer's demand curve

Now, look at the lower part of Figure 3.3 where we have plo�ed the price of the baseball games on the ver�cal axis but retain the same horizontal axis showing the quan�ty of baseball games per week that Bob could a�end. The line joining the price–quan�ty combina�ons, labeled d, is Bob's demand curve for baseball games, other things (including his income, his preference structure, and the prices of other products) being constant.

Thus, the individual's demand curve demonstrates the price effect, that is, when price is higher, the individual will demand fewer units of the product, and conversely, when price is lower, the individual will demand more units of the product. The price effect will differ across individuals and across different products because people have different incomes and different preferences.

The Income Effect

Managers must also be aware that changes in consumer incomes will change the demand for their products. Generally, when consumers have more income, they will buy more of the focal product (i.e., the product we are focusing on). In those cases where consumers buy more units of a product as their incomes rise, we say that the product

is a superior good.8 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt8) In some cases, however, the consumer will buy less of the focal product when incomes rise because the consumer can now afford a be�er product, and in this case the focal product is called an inferior good. It is important for managers to know whether their products are generally considered superior or inferior goods because changes in consumer income may happen suddenly and are outside their control. Such changes might occur due to an economic downturn, a natural disaster, a global financial crisis, changes in foreign exchange rates, or because some of the firm's customers have lost their jobs, for example.

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When the consumer's income increases, the budget line will shi� outward in a parallel fashion; that is, its slope will stay the same. The slope of the budget line does not change because its slope is equal to the ra�o of the two prices and those prices have not changed. Note that the ver�cal intercept of the budget line is the number of units of product Y that can be afforded, so it is equal to the budget (B) divided by the price of product Y, or B/PY. Similarly, the horizontal intercept is equal to the budget divided

by the price of product X, or B/PX. Since the slope of any line is equal to the rise over the run, the slope of the budget line is equal to −B/PY (the "rise," with the nega�ve

sign reflec�ng the fact that the "rise" is actually a fall) over B/PX (the run) which simplifies to −PX/PY, or the nega�ve ra�o of the two prices. Thus, when the consumer's

income increases, with prices unchanged, the budget line has a new higher intercept on each axis (because B increases) and the slope is unchanged. Accordingly, we can say that the budget line shi�s outward in a parallel fashion, meaning that the consumer is able to buy more of both products X and Y.

In Figure 3.4 we show a budget increase for two other consumers who have different indifference maps reflec�ng their differing preferences for movies and baseball. On the le�-hand graph we show a person who regards both products as superior goods, and thus the move from point a to point b illustrates an increase in purchasing both products when income is increased. On the right-hand graph we show a different person who regards baseball as an inferior good, and so the move from point aʹ to point bʹ illustrates a decrease in purchasing baseball �ckets (product X) when his income increases. With greater income this person decides to shi� expenditure away from baseball and towards other products that he views as more consistent with a higher income lifestyle. This is easier to understand if we view product Y on the ver�cal axis not as single product but as represen�ng a "basket of all other goods" and that this basket includes, for example, caviar. At a higher income level the consumer might want to shi�

expenditure away from baseball �ckets and towards caviar as part of adop�ng a more "refined" lifestyle.9 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt9)

Figure 3.4: The income effect for superior and inferior goods

Conversely, the demand for inferior goods will increase when income levels fall. This is because people shi� their consump�on expenditure from higher quality goods (steak) to lower quality goods (sausages) when incomes fall and they are unable to afford to maintain the consump�on pa�ern associated with their former standard of living. Similarly, people might switch from used cars to new cars when incomes increase, but later revert to buying a used car if they experience a fall in their income. It is important for managers to understand whether their products are generally regarded as superior or as inferior goods so they will know which way the demand for their product will go in the event of a change in consumer incomes. For example, a food store in a suburban area that is currently undergoing gentrifica�on—meaning that higher income people are moving in and renova�ng the houses—might increase its sales and profit by stocking food items that are considered "higher class," such as grass-fed steaks and caviar, since the newer residents are likely to subs�tute these superior goods for cheaper cuts of meat and regular snacks.

The Income and Substitution Effects of a Price Change

We have seen that the demand for a product will increase (1) when its price is reduced (the price effect); (2) when consumers' incomes rise (if the focal product is a superior good); and (3) when the price of an inferior subs�tute good increases. What we are seeing is a combina�on of income and subs�tu�on effects. The income effect, as we have just learned, is either posi�ve or nega�ve depending on whether the focal product is a superior or inferior good, and is equal to the change in the demand for the focal product that is due only to the change in income. The subs�tu�on effect is always nega�ve, and is due to the change in the demand for the focal product that is due only to the change in its own price. We will see that the price effect (i.e., the change in consumer demand due to a change in the price level) is made up of two separate effects—an income effect and a subs�tu�on effect.

To be�er understand the income effect component of the price effect we must dis�nguish between monetary income and real income. Monetary income, also known as nominal income, is the face value of the consumer's income, for example Bob Goodguy's earnings of $120 per week. Real income is the purchasing power of the monetary income and is equal to monetary income divided by some measure of the price level. In our simple two-product model there are only two prices, and when one of them changes, real income must change. From the preceding analysis we know that if the price of one product rises, the consumer can afford fewer units of one or both products, and so the purchasing power of monetary income (i.e., real income) has gone down. Conversely, if a price falls, the consumer will buy more of at least that product and may also buy more of the other product (or "all other products" in a mul�product model) because his or her real income has increased.

So the income effect component of the price effect is due to the consumer's real income either going up or going down, and, as we have seen, this income effect might be either posi�ve (for superior goods) or nega�ve (for inferior goods). For a price reduc�on for product X (causing an increase in real income), we expect the income effect—the change in the consump�on of

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Real income is the purchasing power of monetary income and is equal to monetary income divided by some measure of the price level.

product X divided by the change in real income—to be posi�ve (i.e., both consump�on and income move in the same direc�on, or +/+) if X is a superior good, but nega�ve (i.e., consump�on and income move in opposite direc�ons, or –/+) if X is an inferior good. Similarly, for a price increase for product X (causing a reduc�on in real income), the income effect will be posi�ve (–/–) if X is a superior good and nega�ve (+/–) if X is an inferior good.

The other component of the price effect is the subs�tu�on effect, which is due to the change in rela�ve prices, other things being equal. One of the other things that must remain equal is real income, so, to find the subs�tu�on effect we must (theore�cally) adjust monetary income to keep real income constant. For example, if the rent on

your apartment went up by $100 a month, you would stay at the same real income level if your money income was also raised by $100 a month.10

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt10) The subs�tu�on effect is always nega�ve; that is, if PX goes down rela�ve to PY, the quan�ty demanded of X

will go up and, oppositely, if PX goes up rela�ve to PY the quan�ty demanded of X will go down. Since the price effect is always nega�ve (i.e., the quan�ty demanded always

moves in the opposite direc�on to price), the income effect moves in the same direc�on as, or reinforces, the subs�tu�on effect for superior goods. However, it moves against, or par�ally offsets, the subs�tu�on effect for inferior goods.

A rela�vely simple diagram showing the separa�on of the income and subs�tu�on effects will help to explain the two component parts of the price effect. Because the price effect contains both the income effect and the subs�tu�on effect, we can find one simply by subtrac�ng the other from the price effect. In Figure 3.5 we show the indifference curves for a par�cular consumer and an ini�al budget line (drawn as the line AB) stretching between the ver�cal axis and the horizontal axis with slope –PX/PY.

The consumer maximizes u�lity on indifference curve I1 at point a by choosing to consume X1 units of product X and Y1 of product Y. Now consider a price reduc�on for

product X, which causes the price ra�o –PX/PY to fall, causing a fla�er slope of the budget line, which rotates from AB to AC. This allows the consumer to reach the higher

indifference curve I2 which is tangent to budget line AC at point b, where it can be seen that the consumer now consumes X2 units of product X and Y2 units of product Y.

Thus, the price effect is the total change in the quan�ty demanded of product X (from X1 to X2) and within that price effect we need to separate the income effect from the

subs�tu�on effect.

Figure 3.5: Income and subs�tu�on effects when X is a superior good

So, to find the income effect, we would perform a hypothe�cal income adjustment by shi�ing the budget line outwards (from AB to DE), keeping constant the ini�al price ra�o un�l it is just tangent to the higher indifference curve I2 at point c. This new hypothe�cal budget line (DE) shows how much addi�onal income would have been

necessary to allow the consumer to reach indifference curve I2 if there had been no price change. Thus, the income effect is the change in quan�ty demanded from X1 to Xʹ.

This leaves the subs�tu�on effect as the movement from Xʹ to X2, and as you can see, it is effec�vely the movement along indifference curve I2 from point c to point b.

Note that the real income is effec�vely proxied by the level of u�lity the consumer can gain from his or her monetary income and it is necessarily the same at all points on the same indifference curve (I2). The heavy arrows show that the income effect is addi�ve to the subs�tu�on effect because X is regarded as a superior good by this

par�cular consumer.

Conversely, if X is regarded as an inferior good by a different consumer, the income effect will be in the opposite direc�on to the subs�tu�on effect and thus partly offset it, causing the price effect to be much smaller. In Figure 3.6 we show the case where a different consumer regards product X as an inferior good and thus the indifference map

is different from the previous case.11 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt11) No�ce that the indifference curves are not approximately parallel as

before but tend to flare out as more and more of product X is included in this consumer's profit-maximizing combina�on of the two products.12

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt12)

Figure 3.6: Income and subs�tu�on effects when X is an inferior good

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In Figure 3.6 we see that for a price reduc�on of product X, the budget line rotates from AB to AC as before, and thus causes this different consumer to shi� from the ini�al u�lity-maximizing product combina�on at point a to the product combina�on at point c. The price effect is again nega�ve (i.e., more of product X is demanded when its price falls) but note that the income effect (the change in demand for X due to an increase in real income, from X1 to Xʹ) is nega�ve in this case, confirming that this

consumer regards X as an inferior good. This consumer nonetheless buys more of product X because the subs�tu�on effect (from Xʹ to X2) is posi�ve and outweighs the

income effect.13 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt13)

Changes in Demand Versus Changes in Quantity Demanded

In the previous explana�ons, we have been talking about the change in quan�ty demanded by an individual consumer. Such changes have been in response to a change in the price level of the focal product (product X) or, in the case of changes in the quan�ty demanded of product Y, were due to the change in the price of an alterna�ve product (i.e., product X). We saw in Figure 3.2 that the consumer has a demand curve for product X that summarizes the quan�ty demanded of X at any price for product X, assuming monetary income and the price of product Y, and indeed all other influences on the demand for product X, remain constant. Thus, a demand curve is applicable only if all other things are the same.

If there is a change in any of the other variables that influence the demand for product X, there will be a shi� of the demand curve. For clarity of discussion we say that a shi� of the demand curve is a change in demand, as dis�nct from a change in the quan�ty demanded (which is due to a change in the price of X). Thus, a change in its own price causes a movement along the demand curve for product X, and a change in any one of the other determining variables causes a shi� of the demand curve for product X. The demand curve must shi� to reflect the changed quan�ty demanded at the same price level due to the new level of the variable that caused it to shi�.

In Figure 3.7 we show shi�s of the consumer's demand curve for product X at three different points in �me. Quan�ty demanded at price PX on the ini�al (�me t1) demand

curve dt1 is equal to Xt1. We suppose that subsequently some other variable (that influences demand for X) changes and causes the quan�ty demanded to increase to Xt2 (at the same price PX) and thus the demand curve must have shi�ed outwards to dt2. S�ll later, one or more variables change such that the quan�ty demanded at price PX falls to Xt3, and thus the demand curve has shi�ed back to the le� to the point shown as dt3.

Figure 3.7: Shi�s of the demand curve

Variables That Shift the Consumer's Demand Curve

The variables that cause the consumer's demand curve for a product to shi� are immensely important to the manager trying to maximize profits. Changes in the "other things" that influence demand will mean that more (or less) of the product will be demanded at the exis�ng price. Consequently, the profit-maximizing price will usually need to be changed, and the manager needs to know whether to change price up or down, and by how much.

Changes in Monetary Income

From the foregoing analysis you already know that a change in the consumer's monetary income will cause a change in demand (i.e., a shi� in the demand curve). Within Figures 3.5 and 3.6 (and ignoring the change in the price of X in both cases) we can see the impact of a change in monetary income. In the case of Figure 3.5, we saw that the quan�ty demanded for a superior good (holding constant the price of X) increased from X1 to Xʹ when addi�onal monetary income was hypothe�cally given to the

consumer. We can also see that the quan�ty demanded of Y increased while holding constant the price of Y, due only to the change in monetary income. In the case of the consumer who regards X as an inferior good (see Figure 3.6), quan�ty demanded of X decreases while the quan�ty of Y increases (at constant prices) when addi�onal monetary income is hypothe�cally received. Thus, we can see that changes in monetary income will shi� the consumer's demand curve to the right when the product is regarded as a superior good, or to the le� when it is regarded as an inferior good.

Changes in the Price of Related Goods

The second variable that will shi� the demand curve for a product is the price of related goods. We saw already that changes in the price of X caused the consumer to change the quan�ty demanded of product Y—this will change by a larger amount if X is an inferior good and Y is a superior subs�tute, as was inferred earlier. What do we mean by related goods? We have already men�oned subs�tutes—these are alterna�ves in consump�on, you choose one at the expense of the other, such as the choice between an orange drink and a cranberry drink, or between Coca-Cola and Pepsi. Marketers call these rival products within their respec�ve product categories. Within product categories the products will tend to be rela�vely close subs�tutes and across categories the products (e.g., orange drink and Coca-Cola) are usually considered distant subs�tutes—although these drinks are quite different they can both be used to sa�sfy your thirst. Many other product categories, such as music or sports, are unrelated to either of the fruit drink or cola product categories and are said to be nonsubs�tutes (or gross subs�tutes as men�oned at the beginning of the chapter). It will make sense to you that the quan�ty demanded of a product will increase (and thus the demand curve will shi� to the right) when a subs�tute product's price increases, orProcessing math: 0%

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Complements are products that typically go together such as toothbrushes and toothpaste. If the price of a complement increases, consump�on is expected to decrease not only for the product whose price went up but also for its complement.

© Hemera/Thinkstock

Marke�ng Strategies

conversely, the demand curve will shi� to the le� when a subs�tute's price is reduced, because in both cases the consumer will tend to switch to the cheaper subs�tute.14

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt14)

The other category of related goods is complements. These are products that typically go together, that complement each other in use, such as bu�er and toast, or food and drink, respec�vely. Logic suggests that since they complement each other their consump�on will be posi�vely related to each other; for example, the more toast you eat the more bu�er you will eat. But if the price of a complement goes up, your real income will decrease, so you will tend to reduce consump�on not only of the product whose price went up (the price effect) but also of its complement (due to an income effect). Oppositely, if the price of a complement goes down there will be a nega�ve price effect for that product and a posi�ve income effect for its complement. Thus, the demand curve for a product will shi� to the right when the price of a complementary good decreases, or conversely, the demand curve will shi� to the le� when the price of a complementary good increases.

Accordingly, managers of firms need to keep an eye on the prices of both subs�tute goods and complementary goods since changes in these prices will shi� the demand curve for the firm's product and necessitate a price adjustment for that product if the firm is to maximize its profits.

Changes in Marke�ng Variables

Marketers have tradi�onally talked about the "four Ps" that influence the quan�ty demanded of their products —these are price, product design, promo�on, and place of sale (or distribu�on system). These four variables are the "control levers" that marke�ng managers can use

strategically to increase or reduce demand for their products.15 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt15) Of these four Ps we have so far considered only price. We have seen that changes in a product's price will cause a movement along the demand curve, while a change in the price of a related good will cause a shi� of the demand curve, other things being equal. Changes in the other three Ps controlled by the firm will cause a shi� of the demand curve as well, as these change the amount that the consumer will want to purchase at any par�cular price level.

Product design is about the quality of the product. Product design reflects a series of decisions that are made about which component materials, what process of manufacturing, what shapes and colors will be used, and so on. But note that one person's quality (e.g., purple shag wool carpets) might be another person's aesthe�c nightmare. Accordingly, quality is as perceived by the target customer. If a firm redesigns its product to be perceived as higher quality by its target customers (like the latest version of the iPad), we expect those customers to want to buy more of that product at any price, and so the demand curve for that product will shi� to the right. Oppositely, changes in design that reduce the perceived quality (like the unpopular design of the Ford Edsel in the late 1950s; or Coca-Cola's changing the formula for its "New Coke" in 1985; or cell phones made larger and heavier by the addi�on of flip-down keyboards early in this century) will cause a reduc�on in demand such that the demand curve shi�s back to the le�. Note that changes in quality percep�ons may be outside the control of the firm; for example, the release of new medical evidence that a par�cular food prevents (or causes) cancer will raise (or reduce) the perceived quality of that food and shi� the demand curve to the right (or the le�).

Product design includes packaging, or the way the product is presented to the poten�al customer at the place of sale. Packaging might include a cardboard box with artwork depic�ng the product and how to use it. Protec�ve padding inside the box might ensure that the product will not be scratched or broken in transit. Packaging might include a user's manual and instruc�ons for assembly. All of these things increase the customer's apprecia�on of the product, or put another way, raise the u�lity of the product to the consumer and increase the likelihood that the consumer will want to buy the product. Thus, be�er packaging is expected to shi� the demand curves to the right for at least some consumers and increase market demand. Conversely demand curves may shi� to the le� for changes to packaging that are perceived to be worse than the former standard of packaging, such as the use of nonbiodegradable materials in an environmentally conscious world.

Product design also includes the quality of service that accompanies the sales or delivery of the product to the consumer. The salesperson can provide friendly and a�en�ve service, informa�on, fla�ery, free food and beverages, and other benefits that provide u�lity to the consumer, and thus increase consumer demand for the product at any par�cular price level. The demand curves of at least some individuals (others may not care) will shi� to the right if the quality of service is increased, and the firm will expect its demand curve to also shi� to the right. Conversely, a reduc�on in service quality is likely to reduce demand from at least some consumers and for the market in aggregate.

Promo�on is about efforts made by the firm to inform poten�al customers about, and persuade them to buy, the firm's product. It may take the form of adver�sing, website development, point-of-purchase displays, direct-selling efforts, and so on. It serves to raise both customer awareness and apprecia�on of the product, targe�ng either or both poten�al customers and repeat customers to build their interest or loyalty. Increased promo�on efforts (unless done badly) will cause an increase in the quan�ty demanded by at least some consumers and so their demand curves will shi� to the right. Reduced spending on promo�on (or offensive or annoying promo�on) by the firm will reduce at least some customers' awareness and apprecia�on of the product, par�cularly if rival products are being adver�sed vigorously. Consequently, the firm should expect the market demand for its product to shi� to the le�. As with product design, note that external forces can have posi�ve or nega�ve promo�onal influence on the firm's demand. For example, good (bad) publicity for the firm or for the firm's country of origin effec�vely helps (hurts) customer awareness or apprecia�on of the product and shi�s the demand curve to the right (le�).

Place of sale is about where the customer can gain access to and purchase the product and is thus part of what marketers call the distribu�on system. This could be direct from the firm to the customer—like door-to-door sales, telemarke�ng, and Internet sales—or indirect via a hierarchy of wholesalers and retailers. Customers o�en want to see and touch products before purchasing them, so a network of showrooms may be necessary for displaying those products. Showrooms need to be geographically dispersed to make it more convenient for poten�al customers to gain first-hand impressions and experience with the product before they make the final decision to

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Internet-based firms such as Amazon.com o�en offer lower prices and a�ract customers who may have previously visited retail stores to see the product in person.

© Armin Weigel/dpa/Corbis

purchase. Such brick-and-mortar facili�es allow the firm to iden�fy poten�al customers with at least some interest in the product and perhaps a predisposi�on to purchase and also provide the opportunity for sales staff to persuade these poten�al customers to make the purchase decision.

Access to the Internet and the development of more sophis�cated websites has meant that poten�al customers can become fully informed about the product and also learn about the experience of previous buyers with that product without visi�ng any store. For established products that are well known to the customer due to repeat purchase (like groceries, hardware items, household appliances, parts for cars, etc.) many Internet-based firms choose to have no physical store at all, with all sales taking place via the Internet. Indeed, due to the costs savings associated with having li�le or no physical store and few salespeople, Internet-based firms can offer lower prices and a�ract customers who may have visited retail stores to gain informa�on and to see and touch the product but subsequently choose to buy online.

So, if the firm expands its distribu�on network, it might expect to sell more product at the exis�ng price level. This would cause the demand curves of at least some consumers to shi� to the right and thus, the market demand curve (being the aggrega�on of all consumers' demands) would shi� to the right as well. Conversely, if a firm closes down some retail sites it will be less accessible to some consumers who will then stop buying or demand fewer units of the product in favor of buying a more accessible rival product.

Note that all firms have the four "P" variables to control the demand curves for their own products. Those other firms that produce related goods, that is, either subs�tutes or complements, will cause an impact on the demand curves for the focal firm's product if they change any of their four Ps. We have already seen that there will be a shi� of the demand curve for the focal firm's product when either subs�tutes or complements change their prices. For a subs�tute product, changes in any of the four Ps that increase demand for that subs�tute product will decrease the demand for product X, and vice versa. For complementary products, changes in any of the four Ps that increase demand for the complementary product will increase the demand for product X. Oppositely, changes to any of the four Ps by firms producing complementary goods that reduce demand for those goods will cause reduced demand, and thus a shi� to the le� of the individual or the market demand curves for product X.

Changes in Expecta�ons

Finally, we consider changes in consumer expecta�ons with regard to the future values of variables that influence the quan�ty demand of product X. Star�ng with the four Ps, you will understand that if consumers expect that future prices will be lower, future quality will be higher, future promo�onal campaigns will offer be�er ancillary benefits to purchasers, or future accessibility to the distribu�on system will be more convenient, then consumers might decide to delay purchase from the current period and shi� their demand into a future period. For example, news of a new version of the iPad to be released will cause the current period demand curve to shi� to the le�, as many consumers will delay their purchase of the iPad un�l the new version is available. Conversely, if the four Ps in the future are expected, on balance, to be worse than they are today, consumers may be able to shi� their demand from a future period to the current period. For example, car manufacturers offer 0% APR financing on new vehicles for a limited �me, causing the current period demand curve to shi� to the right. Now you can see that a product can be a subs�tute for itself across �me periods. If consumers decide to defer purchase of product X into a future period, the demand curves for X in the current period must shi� to the le�; and conversely, if they decide

to shi� demand from a future period back into the current period, the current period demand curve must shi� to the right.16

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#ch03txt16)

As well as expecta�ons about the future value of the four Ps, expected changes in income will have an impact on consumer quan�ty demanded in the present and future periods as consumers react by switching demand from one �me period to another. If consumers expect their income in a future period to be higher they may defer purchase of a product into a future period, or conversely buy the product in the current period because they expect they will be unable to afford it in the future.

The final change in expecta�ons that we will introduce is a change in the u�lity that the consumer expects to derive from consump�on of the focal product—economists call this a change in consumer tastes and preferences. It is usually preceded by the receipt of new informa�on that causes the consumer to re-evaluate his or her apprecia�on of the product in comparison to its subs�tute products. For example, medical research showing that carrots are sta�s�cally related to the avoidance of cancer would cause many people to expect to gain more u�lity from carrot juice and, subsequently, to want to consume more carrot juice at the expense of other juices. Similarly, new informa�on about a complementary product, such as medical results indica�ng bu�er is a major contributor to obesity, may cause many consumers to use less or no bu�er on their toast and, expec�ng to enjoy ea�ng toast less, they will reduce their demand for toast as well.

Typically, a change in consumer tastes and preferences for a product is due to the consumer's changed apprecia�on for a specific a�ribute of a mul�-a�ribute product (e.g., carotene in carrots, or animal fat in bu�er) within a product category, so we will defer discussion of the impact of changed consumer tastes into the following sec�on where we focus on the consumer's choice between subs�tute products within a product category, where consumers compare specific a�ributes of rival products to determine which of those products they will purchase.

3. Economists talk about goods, which give the consumer u�lity, and bads, which give the consumer disu�lity (such as risk). Some�mes we have to buy bads even though we don't want to, like parking �ckets or speeding fines. We do this because it is be�er than the alterna�ve, that is, what would happen if we don't buy the bad. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return3) ]

4. Don't worry about these frac�onal amounts—by considering a longer �me period they will even out. For example by going to the movies at the rate of 2.6 �mes per week, the consumer would consume 26 movies over a 10-week period. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return4) ]

5. Even addic�ve products, such as cigare�es, alcohol, and other drugs, give diminishing marginal u�lity if you keep taking more of the product at any one si�ng. While addic�on increases one's desire for taking the drug at a later point in �me, on any one occasion the MU of successive doses of the drug declines, other things being equal. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return5) ]

6. Here is the proof that indifference curves must be convex due to diminishing marginal u�lity. The change in total u�lity (TU) due to a change in Y is equal to ΔY.MUY (that is the change in consump�on of

product Y �mes the MU associated with the last unit of Y) and the change in TU due to a change in consump�on of X is equal to ΔX.MUX (that is the change in consump�on of product X �mes the MU

associated with the last unit of X) and these changes in TU are equal in magnitude, so ΔY.MUY = ΔX.MUX. The le�-hand side of this equa�on measures how much u�lity is lost by giving up ΔY, and the

right-hand side measures how much total u�lity is gained by ge�ng an extra amount of X. By rearranging this equa�on we get ΔY/ΔX = MUX/MUY. We already know that MRS = ΔY/ΔX, so subs�tu�ng for

MRS we find MRS = MUX/MUY. So, the MRS is equal to the ra�o of the marginal u�li�es and is also equal to the slope of the indifference curve. Since MUX is posi�ve (and declining) while the MUY is

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nega�ve (and increasing in absolute magnitude) as we move down the indifference curve, the MRS (and therefore the slope of the indifference curve) must be declining. Thus convexity of indifference curves is due to the assump�on of diminishing marginal u�lity for every product. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return6) ]

7. As indicated earlier, this is a predic�ve model without necessarily explaining Bob's thought processes as he allocates his income. Most likely Bob just does what feels right for him, and his a�empts to maximize the sa�sfac�on that he gets from his limited income cause him to make choices that are usually quite well predicted by the u�lity-maximizing model of consumer behavior. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return7) ]

8. Superior goods are o�en called normal goods because normally consumers will buy more of them when incomes increase and less of them when incomes fall. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return8) ]

9. We could alterna�vely have started the en�re analysis with the assump�on that the ver�cal axis represented "All Other Goods" but that would have introduced the difficult problems of (1) how to measure the quan�ty of, and (2) how to represent the price level for, a basket of dissimilar goods and services. In a more complex (mathema�cal) mul�product model we could represent all other products separately and show which products the consumer shi�s in favor of when he or she treats one or more products as inferior goods. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return9) ]

10. This $100 compensa�on for the price increase is a simple case where the price effect is not immediate because the quan�ty demanded of your accommoda�on is fixed in the short term. You cannot reduce the quan�ty demanded of your par�cular apartment immediately, although you may want to hunt around for a cheaper place to live and subsequently move to a cheaper place. More likely the increased price of your rental accommoda�on will force you to cut back on dining out and other discre�onary expenditures. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return10) ]

11. Alterna�vely it could be the same consumer but a different product X—one that our consumer regards as an inferior good [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return11) ].

12. Since indifference curves pass through every point in product space, it might seem that if we did show all the indifference curves passing through the rela�vely wide spaces between the indifference curves that are shown on the right-hand side of the indifference map, that all those curves could not possibly fit through the rela�vely narrow spaces between the curves that are shown on the le�-hand side of the indifference map. But indeed they can, because product X and Y are infinitesimally divisible and so the indifference curves are really infinitely narrow. We just show them as rela�vely thick lines so that we can see them! [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return11) ]

13. It is conceivable that for very large changes in the price of an inferior good, and for individuals who have extreme preferences for an alterna�ve product in place of X, the income effect could outweigh the subs�tu�on effect and consequently that the price effect could be posi�ve (i.e., less would be demanded) for some people. But as you can deduce from Figure 3.6 the price of X fell to less than half of its original level and the price effect is s�ll nega�ve for the consumer depicted. When considering all consumers in the market for product X, as we shall in Chapter 4, it is considered unlikely for the price effect to be posi�ve in aggregate—indeed such a product would not be produced by a profit-maximizing firm if incomes were expected to con�nue to rise. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return13) ]

14. You might say that you prefer, say, Coca-Cola, and would not switch to Pepsi when the price of Pepsi is reduced, and I would believe you for rela�vely small reduc�ons in the price of Pepsi (or small increases in the price of Coke). Most consumers will s�ck to their preferred brand within a limited range of price reduc�ons for subs�tutes but at some larger price differen�al they will concede that their favorite brand is too expensive and will make the switch. This consumer loyalty for par�cular brands is cul�vated by firms as it restricts the ability of rival products to steal sales by making small price changes. As we shall see in later chapters, it depends on both the degree of product differen�a�on the firm is able to achieve and also the consumer's switching costs. Although individual consumers will demonstrate reluctance to switch for small price changes, when consumers are aggregated to form the market demand for the product there is always some customers who will switch as the price differen�al goes beyond the limit of their loyalty to their preferred brand. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return14) ]

15. Note that more demand is not necessarily be�er. For example, if the firm's per unit cost of produc�on is rising when its demand increases this may cause the unit cost of the product to rise above the price level, which would reduce the firm's profit. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return15) ]

16. Note that we divide �me into the "current" period and various future periods, and are careful to emphasize that the horizontal axis measures quan�ty per �me period (Q/t), such as per week or per month. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.1#return16) ]

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Demand for cars is derived from the demand for the a�ributes that the car supplies such as comfort, pres�ge, security, and privacy, not for its physical composi�on of metal, plas�c, and glass.

© Martyn Goddard/Corbis

3.2 Analysis of Consumer Choice Within Product Categories

The tradi�onal model of consumer behavior dates back well over a century, before branding of products became widespread and before differen�a�on of products was widely understood to be a good way to increase business profitability (Marshall, 1890). These days, marke�ng managers want to know a lot more about their products than the price effect and the income effect. Why do some consumers prefer the brand A product while others prefer the brand B product (in the same product category)? How can we improve the design of brand A so that more consumers will prefer it? What benefits offered by brand A should we stress in our adver�sing to gain the most impact from our promo�onal dollar? Is our product vulnerable to the invasion by a new product that offers other benefits that our product does not?

To answer these ques�ons we must restate the theory of consumer demand in terms, not of products, but of characteris�cs or a�ributes of the products. The a�ribute theory of demand argues that consumers buy products because of the product a�ributes, that is, the benefits consumers perceive to be delivered by those products (Lancaster, 1966, 1971). For example, a car is desired not for its physical composi�on (of metal, plas�c, and glass) but instead for the services it provides, such as transporta�on, comfort, pres�ge, security, and privacy. Demand for cars is, thus, derived from the demand for the a�ributes that the car supplies. Similarly, a meal in a quality restaurant is not purchased simply to fill one's stomach, but also to enjoy pleasant surroundings, courteous service, exo�c food, good company, and no mess to clean up. Viewing consumer demand as demand for specific a�ributes allows managers to see why some products in a category sell more than others, and how managers might redesign their product to make it more compe��ve by adding desired a�ributes or dele�ng undesirable a�ributes. Marke�ng managers, and par�cularly their brand managers, are always looking for ways to sell more products, and will find the answer lies in modifying the a�ributes offered by their products.

Depicting Products in Attribute Space

Because our graphs are two-dimensional we will assume that only two a�ributes are important to the consumer. Although this may seem overly simplis�c, many consumer decisions are made on the basis of two main a�ributes, and in any case this analysis could be performed using mathema�cs when more than two a�ributes enter the consumer's decision func�on. Our purpose here is to gain a conceptual understanding of the way consumers dis�nguish between rival products in a product category so we will confine ourselves to the two-a�ribute case.

Consider Mr. Magnus Corpus, who likes to dine out once a week and who makes his choice among restaurants based on his percep�on of the "exo�c atmosphere" and the "haute cuisine" offered by those restaurants. This immediately rules out fast-food restaurants, of course, but he has iden�fied six restaurants that do offer these two a�ributes. Using the Internet to view their menus and promo�onal photos, and to find other peoples' ra�ng of these restaurants, we suppose that he rates each restaurant on a scale of 0–100 on each a�ribute, as shown in Table 3.1. For simplicity we assume that the restaurants have set the same price ($100) for essen�ally the same three- course meal, and that Magnus has an income that is sufficient to allow him to dine at one of these restaurants each week and also to buy other things he needs. A�er we find out which is his preferred restaurant we could revert to the "between product" alloca�on problem (as in sec�on 3.2 above) to examine the alloca�on of his limited income between his chosen restaurant and all other goods and services.

Table 3.1: A�ributes and prices in six restaurants Restaurant Exo�c Atmosphere (EA) Haute Cuisine (HC) Ra�o of EA to HC Price of a similar three-course meal

A 90 20 4.5 $100

B 80 55 1.45 $100

C 72 70 1.03 $100

D 60 80 0.75 $100

E 30 97 0.31 $100

F 15 100 0.15 $100

You will note that the restaurants differ in their a�ribute mix and thus the ra�o of exo�c atmosphere to haute cuisine also differs—some offer a high score on one and a low score on the other, and some achieve a high or moderate score on both a�ributes. It is clear that on the single criteria of atmosphere, restaurant A would be the winner, while on the single criteria of cuisine, restaurant F would be the winner. But how will Magnus, who likes both atmosphere and cuisine, choose among these restaurants? It will depend on his marginal rate of subs�tu�on between atmosphere and cuisine, as we shall see.

In Figure 3.8, we show the six restaurants in a�ribute space as the rays labeled A to F—the slope of each ray is equal to the ra�o of atmosphere to cuisine, from Table 3.1. To understand each ray, think about buying the meal in each restaurant. In restaurant A, for example, spending $100 would allow the consumer to "travel" out along the ray to a point in a�ribute space that has the coordinates 90 units of exo�c atmosphere and 20 units of haute cuisine, the slope of which is (rise) 90 units of atmosphere for (run) of approximately 20 units of cuisine (slope equals 90/20 = 4.5 to 1). Similarly, for each of the other restaurants, the consumer would travel out through a�ribute space at the slope of the a�ribute ra�o provided by that restaurant, and the length of the ray will depend on the price of the meal in that restaurant. The heavy kinked line joining the points abcdef in Figure 3.8 that joins each of the product rays at the point represen�ng the full meal in each restaurant is called the efficiency fron�er. This line shows the maximum combina�on of the two a�ributes that can be obtained at each restaurant (for a given meal and the price of that meal).

Figure 3.8: The consumer's choice of product in a�ribute space

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Now, since Magnus Corpus likes both atmosphere and cuisine, he will have an indifference curve map in atmosphere–cuisine space and there will be combina�ons of exo�c atmosphere and cuisine that he considers superior, equivalent, or inferior to other combina�ons. In Figure 3.8 we have shown only one of these indifference curves, namely I*, this being the highest a�ainable indifference curve given the a�ributes and prices set by the six restaurants. Note that Magnus should choose restaurant D because it offers the a�ributes in the ra�o that allows him to get onto the highest a�ainable indifference curve in the context of his choice between restaurants. Each of the other restaurants would see Mr. Corpus on a lower indifference curve, and would represent an inefficient alloca�on of his income (i.e., the indifference curves [not shown] that pass through points a, b, c, e, and f must lie below I*).

The Price Effect in Attribute Space

We can easily show the price effect using the a�ribute approach. Suppose the manager of restaurant C decides to cut menu prices to increase sales at her restaurant. We suppose she cuts menu prices (or includes dessert for free) such that the similar meal now costs only $90 in restaurant C. This means that for $100, Magnus Corpus can now get more exo�c atmosphere and haute cuisine than before at restaurant C (by ea�ng there at the rate of 1.111 �mes per week, i.e., 10 �mes over 9 weeks). Thus, the quantum of exo�c atmosphere would be 72 × 1.111 = 80 per week and the quantum of haute cuisine would be 70 × 1.111 = 77.8 per week. The new coordinates (80; 77.8) for the meal at restaurant C are thus shown in Figure 3.9 as point cʹ, and the new efficiency fron�er is the kinked line ac'ef and you will note that it effec�vely eclipses

restaurants B and D.17 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.2#ch03txt17)

So, Magnus Corpus now eats at restaurant C, and so do others who previously dined at restaurants B and D, since restaurant Cʹs new price and quality offer dominates that of these other two restaurants—anyone who previously dined there would find themselves on a higher indifference curve at point cʹ by dining at restaurant C. So the only people ea�ng at restaurants B and D will be either those who have not done their homework to find out the ra�ngs of the restaurants in atmosphere–cuisine space, or they choose those restaurants based on other a�ributes, such as convenient loca�on and friendly service, which are not included in our simple model.

Figure 3.9: The price effect in a�ribute space

The Value Proposition and Market Niches

In effect, restaurant C has significantly increased its value proposi�on to Magnus Corpus and to people like him who have similar tastes and preferences. We can think of the value proposi�on as quality divided by price, or

VX = KX/PX (3-1)

where VX is some measure of value to the consumer, KX is the perceived quality of product X, and PX is the price of the product. A measure of value is the total u�lity

derived from the product (i.e., I** in Figure 3.9) and the relevant measure of quality is the quantum of the a�ributes that enter the consumer's decision func�on—in this case exo�c atmosphere and haute cuisine. Restaurant C offers more quality per dollar, or as some might say, more "bang for the buck," than either restaurant B or D when it comes to these two a�ributes and for people whose tastes are similar to that of Mr. Corpus. People who have similar tastes and preferences collec�vely cons�tute a market niche and this par�cular market niche is characterized by people who want exo�c atmospheres and haute cuisine as the main benefits associated with dining out, and who have marginal rates of subs�tu�on (MRS) between these that might be called "moderate." Others, who have substan�ally lower MRS between these two a�ributes (fla�erProcessing math: 0%

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In a first class airline, adding more of a desirable a�ribute such as larger seats and reducing the quantum of an undesirable a�ribute such as noise should make first class �ckets more desirable to more consumers.

© Stephen Swintek/Ge�y Images

indifference curves) will prefer restaurant A, while others, with substan�ally higher MRS (steeper indifference curves) will prefer restaurants E and F.18

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Changes in Product Quality

From the previous explana�ons, it is clear that a change in product quality must entail a change in quantum of a�ributes offered by that product. Adding a new a�ribute that is thought to be desired by consumers changes the quantum from zero to some new level. Adding more of a desirable a�ribute should make the product more a�rac�ve to more consumers, and reducing the quantum of an undesirable a�ribute (e.g., noise) should make the product more desirable to more consumers. Rather than add yet another diagram to illustrate this, look again at Figure 3.9 and assume that instead of reducing price, restaurant C ramped up the exo�c atmosphere and the haute cuisine to the new levels shown while maintaining the $100 meal price. In this scenario, Magnus Corpus and customers like him who have similar MRS between exo�c atmosphere and haute cuisine, along with customers who previously preferred restaurant B and D, would have found restaurant C's new offer to be a be�er value proposi�on that allows them to a�ain a higher indifference curve represen�ng a higher level of total u�lity.

Looking at Figure 3.9 through the lens of an increase in product quality you will see that the extension of the ray (0C to 0Cʹ) represen�ng product C assumes that both a�ributes would be increased in the same ra�o—this is not necessarily the case, of course. A restaurant might hire a new chef, and increase haute cuisine while holding exo�c atmosphere constant, and thus the ra�o of the two a�ributes would change (and the ray represen�ng the product in atmosphere–cuisine space would become fla�er). Again this reposi�oning of the product is likely to capture sales from consumers who include haute cuisine in their decision func�on (in conjunc�on with whatever other a�ributes are offered by restaurants) for choosing between restaurants, since it will shi� out the efficiency fron�er and thus push through the consumer's previously highest a�ainable indifference curve to reach a new and higher indifference curve.

Changes in Promotion Leading to Changes in Consumer Preferences

We saw earlier that the firm has four main levers to control the quan�ty demanded of its product. Now let us consider the impact on consumer demand of increased promo�on for a firm's product. Suppose the manager decides to mount an adver�sing campaign. The effec�veness of this promo�onal effort will depend on what a�ributes of the product the adver�sing focuses on and what a�ributes does the consumer care about! Adver�sing will only increase demand for the product if it increases the customer's awareness of the existence of the a�ributes that are contained in the product (i.e., informa�ve adver�sing) or increases the customer's apprecia�on for some aspect of the exis�ng product (i.e., persuasive adver�sing), or some combina�on of the two. In the case of purely informa�ve adver�sing, consumers may gain new informa�on from the adver�sing (that the product contains more of a�ribute X than it did previously, or more than they previously thought it did). If customers become aware of the product for the first �me, they may subsequently admit that product into their "choice set" (e.g., the six restaurants in Figure 3.9) and would become customers of that firm for the first �me if the new combina�on of a�ributes and its price represents a superior value proposi�on (and allows consumers to reach a higher indifference curve). If customers were previously aware of the product but are now informed that it contains more of a desirable a�ribute (or less of an undesirable a�ribute) than they thought before, this will shi� the product's ray in a�ribute space and poten�ally cause the efficiency fron�er to move outward and allow a�ainment of a higher indifference curve.

When the firm's promo�on has a persuasive effect, it will cause consumers to re-evaluate the u�lity they expect to get from the product because they expect to gain more or less u�lity from one or more of the a�ributes of that product. Suppose that a firm adver�ses that sugar is a major cause of obesity and that its cookies have very low sugar content. We will demonstrate the impact of this in Figure 3.10 for consumers who desire both sweetness and crunchiness in their cookies. The target consumer will s�ll like the sweetness delivered by sugar but now knows that sugar is bad for his or her health, so he or she will like it somewhat less than before. This means that the marginal u�lity of sugar, and thus the MRS between sugar and any other a�ribute, will decline for all levels of sugar consump�on, and so the consumer's indifference curves in "sweet and crunchy" a�ribute space will be fla�er than before. In effect, the consumer's indifference curve map rotates in a�ribute space such that each indifference curve will be fla�er than before.

In Figure 3.10 we show three firms, A, B, and C, who offer chocolate chip cookies that are differen�ated only by their sweetness and crunchiness. Firm A offers a cookie that has a rela�vely high ra�o of crunchiness to sweetness; firm B offers a cookie that is moderately sweet and moderately crunchy; and firm C offers a cookie that is rela�vely low on crunchiness but rela�vely high on sweetness. We show one indifference curve rela�ng to the consumer's tastes before the impact of the adver�sing campaign (i.e., the rela�vely steep indifference curve I* drawn with a solid line). Under this taste pa�ern the consumer will prefer cookie C, since it puts him on the highest a�ainable indifference curve. A�er the impact of the adver�sing campaign the highest a�ainable indifference curve with the new taste pa�ern is represented by the rela�vely flat indifference curve shown by do�ed line labeled Iʹ and we see that the consumer will have switched from brand C to brand A to maximize his or her u�lity.

Figure 3.10: Brand switching due to changed consumer tastes

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When a consumer decides to change products, such as trading in a Blackberry for an iPhone, switching costs are incurred. These include search, transac�on, learning, and conversion costs.

© Oleksiy Maksymenko/All Canada Photos/SuperStock

Note that the levels of total u�lity represented by the curves I* and Iʹ are not comparable with each other. We cannot tell whether the consumer gets more total u�lity from cookie A before the change in tastes or from cookie C a�er the change in tastes. All we can say is that given the change in tastes, he or she gets more u�lity from A than he or she would from C, and, in our example, he or she was induced to switch from brand C to brand A by the persuasive impact of the promo�onal campaign conducted by firm A.

Other Changes That Impact Quantity Demanded

You will readily understand how a change in the place of sale variable will impact the consumer's quan�ty demanded. This controllable variable can be regarded as an a�ribute of the product because it provides a benefit to customers, namely convenience of purchase. Accordingly, we could subs�tute this a�ribute into the figures above and analyze the impact of changing place of sale on the quan�ty demanded by par�cular consumers for whom convenience of purchase is one of the two main a�ributes. We should expect to find that more convenient loca�ons of the firm will cause some consumers to switch to buy from the focal firm, other things being equal.

Changes in consumer income are easy to show in the a�ribute approach—note that the length of the ray for each product in a product category reflects the consumer's budget divided by the price of each product. We saw earlier in the case of the price reduc�on by restaurant C that this caused the length of C's product ray in a�ribute space to lengthen. Conversely, if all prices had stayed the same and instead the consumer's income had risen, the length of the product rays would have all increased commensurately. As we have seen previously in the "between product categories case," we expect that the consumer would con�nue to buy the same product in each

category as before, but would buy more of it (in each �me period) if it is regarded as a superior good, or less of it (per �me period) if it is regarded as an inferior good.19

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.2#ch03txt19)

Switching Costs

Switching costs are the costs that would be incurred by the consumer in switching from one brand to another. They include the search costs of finding and comparing the informa�on about the quality (i.e., the composi�on of a�ributes) of the products in a product category; the transac�on costs associated with actually buying and taking possession of a different product; the learning costs associated with learning how to use the unfamiliar new product rather than the familiar old product; conversion costs associated with making other products interact with the newly purchased product; and the loss of salvage value associated with inability to sell the unused inventory of goods or services involved in the product to be replaced.

For example, suppose I have an old plasma TV and think that a new LED TV would give me more u�lity. Before switching, however, I must incur �me and money to find out if indeed the picture and performance of the LED TV is be�er than my plasma TV (search costs); I would have to drive to the appliance store and spend �me actually buying the new TV (transac�on costs); I would have to spend �me connec�ng the new TV to my old DVD and sound system and have to buy a wider table for the new TV to stand upon (conversion costs); I would have to spend �me reading the manual to learn how to get the most out of the extra capabili�es of the new TV (learning costs); I would incur a fee for termina�ng my lease agreement with the rental company from which I currently lease my plasma TV (contractual costs); and I would not be able to sell my old TV table because nobody wants old-fashioned TV tables like that anymore (loss of salvage value).

Adding up all of these switching costs might make me decide that it is not worthwhile to make the switch, at least not yet, un�l some of the above switching costs fall. You should note that the preceding analysis silently assumed zero switching costs and that switching would only take place when a subs�tute product offers a be�er deal, that is, more total u�lity to the consumer. In prac�ce, switching costs will inhibit consumers from switching to a subs�tute product un�l there is enough difference in expected u�lity (between the two alterna�ves) to compensate for the disu�lity of the switching costs.

17. Note that no one will dine at restaurants B and D (assuming they only want exo�c atmosphere and haute cuisine, and that they have full informa�on about quality and prices) un�l these restaurants either reduce their prices or increase their quality significantly. But in reality other diners seeking different a�ributes (e.g., service quality) may patronize restaurants B and D. But if restaurant C's price reduc�on does cause a substan�al loss of business for these other two restaurants, price reduc�ons might be expected and again Mr. Corpus and people like him would need to re-evaluate their purchases accordingly. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.2#return17) ]

18. Market niches can be defined narrowly in terms of customers with similar MRS values, as above, or more broadly, in terms of customers seeking similar bundles of a�ributes, in which case all six restaurants would be considered as serving the same market niche. Also note that where products contain more than two a�ributes firms may serve more than one market niche at the same �me, as in the above example where people seeking convenient loca�on and good service could also choose to dine at one or other of these restaurants. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.2#return18) ]Processing math: 0%

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19. Although we will not go into it here, the a�ributes of a product may be regarded by consumers as inferior or superior. For example, new houses might be characterized by the a�ributes "insula�on efficiency" and "interior brightness" and some building companies might offer house designs with fewer and smaller windows while others offer house designs with more and larger windows. At a rela�vely low income the new-home purchaser might prefer a house with rela�vely few and smaller windows to allow savings on energy needed to heat and cool the house, but at a higher income this same person might prefer the extra brightness during daylight hours of more and larger windows, because at the higher income they can afford to pay for the extra energy consumed. Thus for increases in income, with other things being equal, the consumer would reduce demand for solid wall area with be�er insula�on and increase demand for glass wall area with less-effec�ve insula�on. For this to happen the indifference curves in a�ribute space would not be parallel but would "flare out" at higher levels of the a�ributes, just as they did for inferior products in Figure 3.6 above. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec3.2#return19) ]

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Summary

In this chapter we inves�gated the underpinnings of consumer demand for goods and services. Managers need to know what mo�vates customers to buy more or less of their products at different �mes and in response to changes in variables that are both within and outside their control. Managers have four main controllable variables they can use to influence the quan�ty demanded by consumers, namely price, product design, promo�on, and place of sale, otherwise known as the "four Ps" of marke�ng. Uncontrollable variables that impact on consumer demand for the firm's product include the four Ps of other firms producing related goods (either subs�tutes or complements) and the consumer's income level and expecta�ons. We saw that each consumer will (no�onally at least) have a demand curve for each product and argued that the aggrega�on of these will cons�tute the market demand for the firm's product. Changes in the firm's own price will cause a movement along the demand curve, while changes in any of the other variables that influence consumer demand will cause a shi� of the demand curve.

The direc�on of the shi� of the demand curve for the focal firm's product caused by changes in a related firm's controllable variables will vary depending on the type of product the focal firm produces. If the focal firm's product is a subs�tute for the other product, the demand curve will shi� back to the le� as a result of any change that causes the other firm's demand to increase, such as a price reduc�on, enhancement of product design, increase in promo�on, or improved distribu�on system (and oppositely for changes that cause the demand for the subs�tute product to decline). If the focal firm's product is a complement for the other firm's product, the shi� of the focal firm's demand curve will be in the opposite direc�on, compared to subs�tute products. Similarly, changes in consumer incomes will cause a shi� outward of the consumers' demand curves for the focal product if it is regarded as a superior good, or inwards if it is regarded as an inferior good.

To arrive at these predic�ons we u�lized u�lity theory and assumed that individuals choose the products they consume to maximize their psychic sa�sfac�on. We used indifference-curve analysis and noted the consumer's u�lity-maximizing changes to quan�ty demanded as we varied the firm's own price, the prices of related products, other controllable and uncontrollable variables, and the consumer's income. This analysis took place in the context of consumer choices between product categories. In the second half of the chapter we focused on the consumer's choice within a product category, examining the consumer's choice among subs�tute products within a par�cular product category, that is, among the products that managers usually think of as the compe��on.

To achieve this we looked at the product a�ributes, that is, the benefits provided by products that are of interest to the consumer. We saw that when consumers view products in terms of the a�ributes provided by those products, they will differen�ate between these products and select the brand that offers the desired a�ributes in the ra�o, and at the price, that allows the consumer to maximize u�lity from that product. We noted that to gain the customer's business the firm must offer the best value proposi�on, where value is measured by quality over price. The best value proposi�on will be the one that allows the customer to maximize u�lity, and that will occur when the product offers the a�ributes in the ra�o and at the price level that allows the consumer to reach the highest a�ainable indifference curve in a�ribute space.

We also considered changes in consumer tastes, as triggered by the firm's promo�onal efforts, but of course tastes could change for a variety of other reasons as well, such as via social networking, exposure to new informa�on, re-evalua�on of personal goals, and so on. If the consumer's tastes change away from a par�cular a�ribute of the product (e.g., its carbon footprint) we expect the consumer to shi� demand toward subs�tute products that include less of that a�ribute in their makeup. Alterna�vely, if tastes change in favor of a par�cular a�ribute (e.g., carotene in foods), we expect consumers to switch to products that contain more of that a�ribute. We noted that consumers are likely to face switching costs and that these will delay or prevent the switch in prac�ce un�l either switching costs fall or the u�lity expected from the alterna�ve product increases significantly.

Armed with this knowledge about the behavior of individual consumers we are now ready to move on to Chapter 4 where we consider the market demand for a firm's product, this being the aggrega�on of the individual consumers' demand curves. Managers must consider the market as a whole, since individual consumer differences mean that some consumers will react to changes in the firm's controllable variables while others will not, and those that do react will react to different degrees—it is the overall impact on the firm's demand that is of most interest to the manager.

Ques�ons for Review and Discussion

Click on each ques�on to reveal the answer.

1. Some of the determinants of consumer demand are controllable by managers while others are uncontrollable by managers. Discuss. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The determinants of consumer demand are things that cause or induce the consumer to buy more or less of the product in ques�on. The firm may adjust its strategic (4P) variables of price, product design (including packaging and service levels), promo�onal efforts, and place of sale, in an a�empt to influence customer purchases. Other determinants of consumer demand are uncontrollable, including consumer incomes, tastes, and expecta�ons; the four Ps of rival and complementary firms; and external business environment variables such as interest, exchange, and unemployment rates.

2. State and explain why the four proper�es of indifference curves are important for the logical analysis of consumer behavior. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

Indifference curves are constructed to model ra�onal behavior of the individual. Higher curves are preferred to lower curves to reflect the general presump�on that consump�on of more items is preferable to consump�on of fewer items. Indifference curves are nega�vely sloped to reflect the trade-off between things that are valued by the consumer—to remain at the same level of u�lity as one product is increased requires fewer units of the other item. Indifference curves not intersec�ng or crossing reflects the transi�vity (or consistency) of consumer preferences. The convexity of indifference curves reflects diminishing marginal u�lity for any par�cular product, which is generally observed.

3. What is the marginal rate of subs�tu�on (MRS) and why does it diminish as the consumer con�nues to subs�tute one product for another? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The marginal rate of subs�tu�on (MRS) is the rate at which a person would be willing to give up units of one product (X) in return for addi�onal units of another product (Y) such that the person's total u�lity remains the same. It is equal to the ra�o of the marginal u�li�es (MU) of the two products. The MRS declines because of the assump�on of diminishing marginal u�lity for all products and services. It diminishes as the consumer con�nues to increase consump�on of product Y while decreasing consump�on of product X, because the MU of product Y is falling (as more units are consumed) and the MU of product X is decreasing is rising (as fewer units are consumed). The value of a ra�o for which the numerator is declining and the denominator is increasing must necessarily increase.

4. Define the consumer's budget constraint line, and explain what causes it to (a) shi� outward in a parallel fashion, and (b) change its slope. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

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The consumer's budget constraint is a line joining combina�on of goods and services that all cost the same amount, that amount being equal to the consumer's income. It intercepts the ver�cal axis at the value equal to income divided by the price of product Y, and it intercepts the horizontal axis at the value equal to income divided by the price of product X. For example, if Px = $4 and Py = $2 and the budget is $20, the ver�cal intercept will be 20/2 = 10, and the horizontal intercept will be 20/4 = 5. The slope of the budget line will be the rise (10) over the run (5) equals 2. Its slope is equal to the ra�o of Px /Py = 4/2 = 2. Thus, if income increases, the intercept points each increase and the budget line shi�s outward, and if the slope changes only if the price of either product changes.

5. Dis�nguish between superior goods and inferior goods. If an economy goes into a recession, which of these would suffer a reduc�on in consumer demand, and why? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The demand for superior goods increases when consumer incomes increase, and the demand for inferior goods decreases when incomes increase (because consumers are able to afford a be�er quality subs�tute product). Conversely, when consumer incomes decrease, as in a recession, demand for superior goods will decline as consumers subs�tute towards cheaper inferior goods to sa�sfy their needs.

6. Dis�nguish between the income effect and the subs�tu�on effect of a price change, and compare these for superior and inferior goods. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The income effect of a price change is the change in quan�ty demanded that is due to a change in real income, holding constant prices of all products. The subs�tu�on effect of a price change is the change in quan�ty demanded that is due to the change in rela�ve prices, holding real income constant. For superior goods, the income and subs�tu�on effects move in the same direc�on (e.g., both posi�ve for a price reduc�on) whereas for an inferior good these effects move in opposite direc�ons (e.g., income effect nega�ve and subs�tu�on effect posi�ve for a price reduc�on).

7. Explain why a price increase for a complementary good causes a shi� of the demand curve for the focal product. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

A price increase for any product causes decreased demand for that product. This induces a decrease in the demand for any products that are complementary in consump�on, such as popcorn sales at the movies—fewer people going to the movies buy less popcorn although the price of popcorn has not changed. This would occur for any price of popcorn, so the demand curve for popcorn must shi� to the le� because of the price increase for movies.

8. What a�ributes do you think are being sought by a consumer who chooses to fly to Las Vegas for a vaca�on compared to another consumer who prefers to drive to Las Vegas for a vaca�on? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The "flyer" might enjoy flying, and enjoy spending �me in Las Vegas more than spending �me driving. The "driver" might enjoy driving (or hate flying), and enjoy the solitude of driving rather than the hec�c pace of life in Las Vegas. The driver might prefer the convenience of having a car to get around in, rather than take cabs or hire a car while in Las Vegas (and the flyer might prefer the opposite).

9. Dis�nguish between a change in consumer percep�ons and a change in consumer preference. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

A change in consumer percep�ons is a change in the a�ributes perceived within a product, induced by adver�sing or by other forms of informa�on provision, including consump�on experience. A change in consumer preferences is a change in the u�lity the consumer expects to derive from the a�ributes within the product, again induced by new informa�on or consump�on experience. For example, informa�on that sugar contributes to weight gain may cause a person to ques�on how much sugar is in a food product and simultaneously to cause the consumer to enjoy that product less because it contains a substan�al amount of sugar.

10. Reconcile the consumer's choice of the best value proposi�on (V = K/P) with the u�lity-maximizing choice of brand within a product category. What happens if there are significant switching costs for the consumer wan�ng to change brands to maximize u�lity? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The value proposi�on is quality over price, where quality is effec�vely measured as the perceived (marginal) u�lity from one (more) unit of the product. The u�lity- maximizing rule can be expressed as choosing the product for which the ra�o of MU/P is highest and con�nuing to do so un�l the budget is all spent. This is consistent with choosing the best value proposi�on in each product category and buying more than one unit is some product categories (and none in others because they do not offer a superior value proposi�on). Switching costs effec�vely add to the price of the subs�tute product that may offer a superior value proposi�on if switching costs are ignored, but if considered prevent that product from being the superior value proposi�on.

Decision Problems

1. Using indifference curves in one graph, show the effects of the following series of events: a price reduc�on for product X; followed by an increase in the consumer's income; followed by a change in the consumer's tastes away from product X.

a. What happens to the quan�ty demanded when price is reduced, and why? b. What happens to quan�ty demanded of X when income increases, and why? Does your graph depict superior or inferior goods? c. What happens to quan�ty demanded when tastes change away from product X, and why?

2. Imagine two music lovers, Ms. Imogene Smith and Mr. Robert Brown, who have substan�ally different tastes in music. Ms. Smith loves classical music for its subtlety, its nuances, and its intriguing build-ups to crescendos with subsequent a�enua�on to calming melodic sequences. She nonetheless also appreciates country music and occasionally downloads an album of this genre. But Mr. Brown loves country music! He loves it for its hear�elt rendi�ons of the human condi�on, for its emo�on-s�rring stories of love gained and lost, and its apprecia�on of the contribu�on made to our lives by dogs, horses, and ca�le. Notwithstanding this Mr. Brown is no bumpkin; he also enjoys listening to the odd piece of classical music and occasionally downloads an album of this genre.

a. Using indifference maps that you think are appropriate for each of these music lovers, derive their individual demand curves for each product category. b. Aggregate their individual demands at each price to find their total demand for each genre of music at each of several price levels.

3. The Blushing Cheeks Company sells a cosme�c product that has several close subs�tutes. At its present price, however, this product is not selling enough to be profitable, so the finance manager wants to increase its price substan�ally. The marke�ng manager wants to spend money on a promo�onal campaign before the price is raised, but the finance manager says this expenditure is counter-produc�ve since the firm wants to maximize profits.

a. Explain the marke�ng manager's reasoning using the a�ribute approach to consumer behavior. b. Dis�nguish between the impact of informa�onal adver�sing and the impact of persuasive adver�sing on the quan�ty demanded of product X; that is, which lines or

curves in your a�ribute analysis of the problem are impacted by adver�sing of these two types?

4. In a par�cular city two brands of beer, EasyLite and ThirstBuster, account for the great majority of beer sold in that city, each having about 45% share of the market. Norbert Brewing Company is considering entering that market with a new brew that it calls Lifestyle beer. Norbert's market research indicates that the choice of beer brand in that

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city is typically based on two main a�ributes, these being lightness (low calories) and thirst-quenching (tangy hops). EasyLite beer is perceived by the average consumer to contain 10 units of lightness and 5 units of thirst-quench, and costs $0.80 a bo�le. ThirstBuster is perceived by the average consumer to contain 5 units of lightness and 10 units of thirst-quench, and costs $0.67 per bo�le. Norbert's Lifestyle beer has been designed to have 8 units of lightness and 7 units of thirst-quench. Research also shows that the average consumer spends about $10 per week on packaged beer purchases.

a. What is the maximum price that might be charged for Lifestyle beer such that its ray in a�ribute space will reach the efficiency fron�er for the average consumer with $10 to spend per week? (An approximate answer derived from your graph will suffice.)

b. Suppose Norbert's average cost of produc�on is $0.50 per bo�le (and that this is about 50% higher than the produc�on cost of the other two beers). What price do you suggest they set for Lifestyle beer, and why?

5. Richard Poirier has recently completed his MBA and upon receipt of his first paycheck began planning to buy a European sports car. He is considering four major a�ributes in his choice among different sports cars: pres�ge, performance, reliability, and winter driving capability (i.e., trac�on in snow and icy condi�ons). But the value he places on each a�ribute differs according to whether his employment remains in California or whether his employer transfers him to upstate New York. If he remains in California, Richard considers performance to be twice as important as reliability; pres�ge to be three �mes as important as reliability; and winter driving capability to be only half as important as reliability. If he is transferred to upstate New York where he expects much colder winters, he considers winter driving capability to be three �mes as important as reliability; performance to be half as important as reliability; and pres�ge twice as important as reliability. He is equally apprecia�ve of reliability whether he lives in California or upstate New York. Richard has found two used European sports cars for sale, each costs $20,000, and they appear to be in equally good mechanical condi�on. He has rated each car on a scale of 100 for each of the four a�ributes, as follows:

A�ribute Car A Car B

Pres�ge 80 60

Performance 80 90

Reliability 70 90

Winter Driving Capability 80 60

a. Advise Richard which car he should buy if he is to remain in California. Hint: Don't a�empt a graphical answer to this one! Calculate the u�lity "part-worths" to find his total expected u�lity from each car.

b. Advise Richard which car he should buy if he is to live in upstate New York. c. Which car should he buy if the probability of his being transferred to New York can be reliably es�mated as 0.7? Explain your reasoning.

Key Terms

Click on each key term to see the defini�on.

complements (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Products that are typically consumed together, and thus their demand curves are inter-related. For example, when the demand for one increases, demand for the other one also increases.

consumers (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Individuals that purchase and use goods and services in an economy.

decision variables (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The variables that enter a consumer's purchasing decision process, including the product's price, design, packaging, place of sale (availability), and impact of promo�onal efforts.

demand curve (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A line graph that demonstrates the nega�ve rela�onship between the price of a product and the quan�ty demanded of that product at various price levels.

discre�onary income (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The sum that remains in an individual's budget a�er all expenses necessary for living have been purchased or deducted, which may be used for discre�onary or nonvital expenses.

efficiency fron�er (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The line joining the points on the product rays represen�ng the maximum combina�on of the two a�ributes that can be obtained from each product given the consumer's income constraint.

expected changes in income (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The individual's percep�on of the future level of his or her income, which has an impact on the quan�ty of goods and services demanded in the present and future periods, as consumers react by switching demand from one �me period to another.Processing math: 0%

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income effect (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The change in quan�ty demanded due to a change in the consumer's income level, holding all other determinants of quan�ty demanded constant.

indifference map (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A system of curved lines that represents a person's tastes and preferences between the variables depicted on the ver�cal and horizontal axes. Indifference maps typically only show selected indifference curves to illustrate the focal consumer's choice problem.

inferior good (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Goods that consumers tend to buy less of as their income increases.

marginal u�lity (MU) (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The change in total u�lity due to a one-unit change in consump�on of a par�cular product. Marginal u�lity is expected to diminish as a person consumes progressively more units of any product.

market niche (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A subset of the total market for a product category comprising a group of consumers who have similar preferences and similar incomes, and who thus confine their purchases to a subset of the brands available.

monetary income (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The face value of the consumer's income from employment or investments over a given period of �me. Also known as nominal income, monetary income is dis�nct from real income, which is the purchasing power of monetary income.

place of sale (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The loca�on where a transac�on takes place between the buyer and seller—it can be in a store, at the place of consump�on (e.g., door-to-door sales), or over the Internet with subsequent delivery.

point of tangency (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The point at which a curved line touches but does not cross another line—the two lines converge towards the point of tangency and diverge a�er the point of tangency.

preference structure (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A system of tastes and preferences exhibited by a person rela�ng to choices between products or other choice alterna�ves (e.g., risk and return). A preference structure can be depicted by the indifference curves for a given individual.

price effect (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The change in the quan�ty demanded of a product due to the change in the price of that product with all other determinants of quan�ty demanded held constant. It is demonstrated by the nega�ve slope of a demand curve. When the price is higher, fewer units of the product will be demanded, and conversely, when price is lower the individual will demand more units of the product.

product a�ributes (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The perceived benefits contained within or delivered by products. Also known as product characteris�cs, they determine the consumers' demand for a given product.

product design (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The perceived characteris�cs (or a�ributes) of the product that define the quality of the product. Product design reflects a series of decisions made during pre-produc�on about a�ributes such as component materials, the manufacturing or service process, and u�lized shapes and colors.

promo�on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Marke�ng communica�on ac�vi�es undertaken by the firm to provide informa�ve or persuasive messages to poten�al consumers. Promo�on is designed to increase the overall sales of a product or service, including adver�sing, point-of-purchase displays, and other sales-enhancing tools.

real income (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The purchasing power of the consumer's monetary income, equal to the face value of that income divided by an index of prices. Processing math: 0%

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related goods (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Products with demand curves that are inter-related to the demand for the focal firm's product. They include subs�tutes and complements.

subs�tutes (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Similar yet differen�ated products that serve the same consumer needs or wants. Subs�tutes are usually different brands within the same product category, and range from very close subs�tutes (nearly iden�cal to each other, like brands of milk) to distant subs�tutes (substan�ally differen�ated, like brands of cars).

subs�tu�on effect (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The tendency for the consumer to change from one product to a subs�tute product when the rela�ve prices of subs�tute products change, holding constant all other determinants of quan�ty demanded including real income.

superior good (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A product for which quan�ty demanded will increase when real income increases and conversely decrease when real income decreases.

switching costs (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Monetary and psychological costs consumers would suffer if they were to switch products, brands, or providers. They include search costs, transac�on costs, learning costs, conversion costs, and the poten�al loss of salvage value.

u�lity-maximizing model of consumer behavior (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A model that is used to depict human choice between alterna�ve items in terms of the psychic sa�sfac�on (u�lity) they expect to derive from those items. These models can be solved graphically using indifference curves, or algebraically using equa�ons, to find the combina�on of items that maximizes psychic sa�sfac�on for the person concerned.

u�ls (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A numerical value given to units of psychic sa�sfac�on (u�lity) to theore�cally measure how much total or marginal u�lity the consumer expects to derive from different product combina�ons.

value proposi�on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The ra�o of the perceived quality of a product (reflec�ng product a�ributes contained) to the price of that product, which the prospec�ve customer can compare with the value proposi�ons of other products before choosing the one with the superior value proposi�on.

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4

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Market Demand Analysis and Estimation

Learning Objectives

A�er reading this chapter, you should be able to:

Iden�fy the rela�onship between the demand curve and the demand func�on and between the demand curve and the total and marginal revenue curves. Discuss the rela�onship between price elas�city of demand and the change in total revenue for a price reduc�on or increase. Explain the concepts and usefulness for managerial decision making of income elas�city, cross-price elas�city, adver�sing elas�city, and other elas�ci�es of demand. Describe how primary data required for the es�ma�on of demand func�ons and curves might be collected using marke�ng research methods. Explain how regression analysis can be u�lized to es�mate the demand func�on using secondary data and how these es�mates can be used to derive the demand curve and various elas�city of demand measure.

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Introduction

The firm’s market demand for a par�cular product is the aggrega�on (or horizontal summa�on) of the demand curves of individual consumers for that product.1

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/ch04introduc�on#footernote1) Managers need to understand the underlying determinants of market demand and, in par�cular, how responsive it is likely to be to changes in the firm’s controllable variables (such as the four Ps of marke�ng) and to changes in uncontrollable variables (such as changes in consumer incomes or the strategic ac�ons of rival firms), since the firm’s revenues depend on the market demand for its products. The sensi�vity of quan�ty demanded to a change in an underlying determinant variable is known as an elas�city of demand. Elas�ci�es of demand convey important informa�on to managers about the impact on market demand (and hence on the firm’s revenues) due to changes in controllable and uncontrollable variables. In this chapter we will inves�gate several elas�ci�es of demand that are of interest to prac�cing managers.

In the second half of this chapter, we concern ourselves with the es�ma�on of market demand for the firm. Managers need to es�mate the volume of demand in the current and future periods so that they can plan effec�vely for hiring and training employees, ordering raw materials, expanding physical plant and equipment, introducing new products, replacing obsolete products, and so on. Es�ma�on of market demand involves gathering data and interpre�ng that data to provide a numerical es�mate of demand in the current and future �me periods. We consider the gathering of data via interviews, surveys, and market experiments, as well as the use of regression analysis to es�mate the responsiveness of quan�ty demanded to changes in the firm’s controllable and uncontrollable variables.

1. For example, hundreds of consumers might buy 0, 1, 2, 3 or more units each at the price of $10 per unit, and in aggregate the market demand might be, say, 680 units at price $10. At a lower price, for example, $9, these consumers might increase their quan�ty demanded by one or a few units each, such that market demand is, say, 920 units. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/ch04introduc�on#return1) ]

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Since consumers adjust their purchases to maximize their u�lity, when a subs�tute firm reduces its price, it will sell more, and the focal firm will sell less, leading to price compe��on.

© Photodisc/Thinkstock

4.1 The Demand Function and the Inverse Demand Curve

To clarify terms, note that the demand func�on refers to the rela�onship that exists between the quan�ty demanded of a par�cular product and all the determinants of that demand that we discussed in detail in the preceding chapter. The demand curve, on the other hand, refers to the rela�onship that exists between the quan�ty demanded of a par�cular product and the price of that product, with all other determinants held constant. The demand curve is thus a subset of the demand func�on where ceteris paribus applies to all determinants except price. As noted in Chapter 3, when we simply say "demand for a product," we will generally mean the demand curve for that product. So that if we say "a change in demand" or "demand has changed," we will mean that the demand curve for that product has shi�ed. To reiterate, changes in price cause movements along the demand curve, while changes in all other determining variables cause a shi� of the demand curve.

Controllable and Uncontrollable Variables That Affect the Demand Curve

In Chapter 3 we considered the main determinants of consumer demand. Those that are controllable by the firm are the four Ps of marke�ng, namely price, product design (or quality), promo�on, and the place of sale (distribu�on system). We saw that changes in price cause a movement along the consumer’s demand curve, while changes in the other controllable variables (and in uncontrollable variables) will cause a shi� of the consumer’s demand curve. Since the market demand curve is the horizontal summa�on of these individual consumer demand curves, we expect the market demand curve to shi� in the same direc�on (as individual demand curves) when these "demand shi�ers" change. The direc�on of the shi� for each of the other three Ps is summarized in Table 4.1.

Table 4.1: Controllable shi� variables for the firm’s demand curve Controllable shi� variable Demand curve will shi� outward for: Demand curve will shi� inward for:

Promo�on and adver�sing Promo�onal campaigns that mo�vate consumers to buy the product for the first �me, or to buy more of it

Reduc�ons in promo�onal ac�vity or unsuccessful promo�on that upsets people and turns them against the product

Product design or quality Product design changes that are perceived as enhancements by the market

Perceived reduc�ons in product design or quality aspects

Place of sale (distribu�on) Changes to the distribu�on system that makes purchasing more convenient for the customer

Changes to the distribu�on system that reduce convenience or accessibility

In addi�on, a variety of uncontrollable variables affect the firm’s demand. These uncontrollable variables can be discussed under three main headings, namely (a) ac�ons by related-product firms; (b) consumer variables; and (c) changes in the business environment.

Price and Nonprice Ac�ons of Related-Product Firms

As we saw in Chapter 3, related products are those that are either subs�tutes or complements for the focal firm’s product. Producers of subs�tute products are in direct compe��on with the focal firm—their ac�ons that increase demand for their products will simultaneously reduce the demand for the focal firm’s product. For example, if Ford reduces the price of its line of compact sedans it will sell more of these, but General Motors, Toyota, and other rivals will sell fewer compact sedans a�er consumers

adjust their purchases to maximize their u�lity. The impact on quan�ty demanded due to a subs�tute product’s price reduc�on may, in some market situa�ons,2

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote2) lead to a retaliatory price reduc�on by the focal firm (and by other compe�tors), perhaps followed then by another price reduc�on by the firm that ini�ated the price cu�ng. We call this price compe��on, and if the price cu�ng con�nues it might degenerate into a price war. In extreme cases prices may be driven down to below costs and all firms might lose money. Since this is a predictable outcome, firms are usually sensible enough to avoid being drawn into a price war and usually try to increase their demand by adjus�ng one of the remaining three controllable variables.

Adjus�ng the nonprice controllable variables (i.e., product design, promo�on, and place of sale) is called nonprice compe��on and this is the most common form of compe��ve rivalry in most markets. Whereas price compe��on is reac�ve and immediate, nonprice compe��on is proac�ve and delayed—it takes �me and talent to design increased quality into the product, to develop and execute an effec�ve promo�onal campaign, or to set up new distribu�on channels. Since it takes �me to retaliate to nonprice compe��on, and since the success of such retalia�on is not at all assured (in prospect), firms that ini�ate nonprice compe��on usually benefit from the change they have ini�ated for a considerable period of �me and thereby earn financial payback on the investment they have made in changing product design, promo�on, or other nonprice variable.

Producers of complementary products should also be expected to adjust their controllable variables in their own best interests, but in this case what is good for the complementary firm is also good for the focal firm. As we saw in Chapter 3, ac�ons by complementary firms that increase the demand for their products will also increase the demand for the focal firm’s products, and oppositely, ac�ons that reduce demand for the complement will also reduce demand for the focal firm’s product. For example, if interna�onal airfares to France were reduced (increasing the quan�ty demanded of air travel to France) the demand curve for French hotel accommoda�on would shi� to the right, increasing the quan�ty demanded at any price. Conversely, if the price of French hotels went up significantly, for example due to the reduced value of the U.S. dollar in terms of the Euro, the demand curve for air travel from the United States to France would shi� to the le�, causing a reduced quan�ty demanded at the current airfare levels.

Consumer Variables: Incomes, Tastes, and Expecta�ons Processing math: 0%

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Winning the Fare War

Purchasing behavior is shaped by consumer expecta�ons. A homeowner might take on a larger mortgage because he or she expects to afford the future loan payments.

© iStockphoto/Thinkstock

As we saw in the preceding chapter, increases in consumers’ incomes will cause increased quan�ty demanded for

superior3 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote3) products (by defini�on), while increases in consumer income will cause reduced quan�ty for inferior products (by defini�on). Thus, if the focal firm’s product is an inferior product, then demand for this product will move oppositely to changes in consumer incomes. When consumers’ incomes are generally rising, as in a period of macroeconomic expansion, the firm’s demand should be expected to fall as its customers switch to a superior subs�tute, and conversely when consumers’ incomes are falling, as in a recession, the demand for an inferior good should be expected to increase. Macroeconomic expansions and recessions, also known as the business cycle, are likely to cause changes in the incomes of many (but not all) consumers, but note that consumers might at any �me receive salary increases or bonuses, or conversely work fewer hours or lose their jobs and thus suffer reduced incomes, independent of the general trend

of macroeconomic condi�ons.4 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote4)

Consumers’ tastes may change and cause the quan�ty demanded of the firm’s product to increase when tastes change in favor of that product, or oppositely cause the quan�ty demanded to fall when tastes change against the firm’s product. As we learned in Chapter 3, consumer tastes relate to a�ributes of the product which consumers see as benefits offered by the product. Their "tastes" are really a euphemism for the u�lity they expect to gain from the consump�on of the product, and underlying that is the u�lity they expect to gain from the a�ributes of the product. Changes in tastes are usually prompted by new informa�on, such as a medical report showing that carotene is related to the preven�on of cancer, or that saturated fats are related to heart disease. Similarly, if the firm engages in "green" prac�ces to save the natural environment, its brand name may be viewed more favorably by at least some consumers and it should expect increased market demand as a result. Conversely, if a firm pollutes the environment or prac�ces discrimina�on in its workforce, it should expect a nega�ve change in tastes for the

firm’s products for at least some of its customers, and hence, there will be a le�ward shi� of its demand curve.5

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote5)

Consumer expecta�ons underlie their purchasing behavior. For example, if a person expects to con�nue earning a salary, he or she might take on a large mortgage for a new house, or take a loan to buy an expensive luxury car, because he or she expects to be able to afford the loan payments into the future. If these expecta�ons change, for example due to a global financial crisis, he or she might want to proceed more cau�ously and subsequently defer or cancel such purchases. Consumers will also form expecta�ons about future price and quality levels and should be expected to defer purchases into a future period if they expect prices to fall substan�ally or quality to improve substan�ally. For example, if a firm announces that next month it will put its products on sale, it should expect to experience reduced demand in the current month because at least some consumers will defer their purchase of these products un�l next month. On the other side of the coin, expecta�ons of quality reduc�ons or price increases in future periods might arise and cause the consumer to accelerate purchases of some products rather than buy lesser quality or at higher prices in later periods. The same applies for expecta�ons of limited availability (shortages) of preferred products in the future—consumers will tend to stock up in advance rather than be unable to buy the product in a future period.

Changes in the Business Environment

In this sec�on we will discuss changes that could happen in the firm’s external business environment and consequently affect demand for its product (see Table 4.2). Ac�ons by governments may lead to changes in demand for the firm’s product. Governments pass new laws and regula�ons banning some products, legi�mizing others, and manda�ng consump�on of s�ll others, such as seat belts in cars. Governments take ac�on to discourage consump�on of cigare�es, alcohol, and drugs. A government might prohibit or place temporary restric�ons on trade with par�cular na�ons, or, oppositely, open trade rela�ons with na�ons that were previously closed. As an example of government regula�on, increasing social concern over global warming has led various governments to implement "carbon taxes" that will have a detrimental impact on the demand for products that have a rela�vely large carbon footprint as consumers switch to suppliers that have smaller carbon footprints. Similarly, new taxes in some countries on fat in food will reduce demand for foods with rela�vely high-fat content.

Growth in popula�on will typically mean more demand for a firm’s product, but demand for par�cular products is likely to be related to changes in the structure of total popula�on. Demographic change refers to variables such as age, ethnicity, gender, geographic distribu�on, and employment type that change over �me and are likely to affect the demand for products that are consumed more (or less) by a par�cular age, ethnic, gender, or regional group. For example, changes in the rela�ve size of an age cohort (i.e., people of the same age, or in the same five-year age bracket, such as 25–29 years old) occur due to changes in birth, death, immigra�on and emigra�on rates, such that a par�cular age cohort might be growing or shrinking in size. Thus, the market for things that a par�cular cohort consumes is likely to move in the same direc�on as the size of that age cohort. Where a firm’s product is targe�ng a rela�vely narrow age group (e.g., training wheels for bicycles typically used by kids 3–5 years old), changes in the size of this cohort (due to earlier changes in the birth rate) can be expected to significantly affect sales from year to year.

A third factor that impacts the external business environment for the firm is weather condi�ons. Severe snowstorms might paralyze the transporta�on system and cause electric power failures, meaning that sales will be lost as consumers stay at home or allocate their limited funds to blankets, snowplows, or household repairs. At the other extreme, heat waves cause a re-alloca�on of consumer expenditures toward air condi�oners and electricity to drive the air condi�oners at the expense of other expenditures. A recurring weather phenomenon with major economic impact is the cycle of El Niño and La Niña weather events that are due to the changing temperature of Pacific Ocean currents. In summary, products for which consump�on pa�erns are weather-related should expect to have increases or decreases in demand due to changing weather condi�ons. Finally, natural disasters, most prominently earthquakes and tsunamis, but also forest fires and floods, are low probability but high impact external events that cause massive infrastructure disrup�on and loss of life and property. They reduce demand for many firms asProcessing math: 0%

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When severe snowstorms occur, sales o�en decline due to limited transporta�on and consumers choosing to stay at home or allocate their funds elsewhere.

© iStockphoto/Thinkstock consumers delay or forego consump�on due to diver�ng their limited income towards other products that are necessary to rec�fy the damage caused by the natural disaster.

Table 4.2: Uncontrollable shi� variables for the firm’s demand curve Shi� variable Demand curve will shi� outward for: Demand curve will shi� inward for:

Prices of subs�tutes Price increases for subs�tutes Price reduc�ons for subs�tutes

Prices of complements Price reduc�ons for complements Price increases for complements

Nonprice compe��on by subs�tutes (rivals)

Changes in nonprice controllable variables that shi� the rival’s demand curve inward

Changes in nonprice controllable variables that shi� the rival’s demand curve outward

Nonprice compe��on by complements

Changes in nonprice variables that shi� the complement’s demand curve outward

Changes in nonprice variables that shi� the complement’s demand curve inward

Consumer incomes Increases in incomes (for superior goods) OR decreases in income (for inferior goods)

Decreases in incomes (for superior goods) OR increases in income (for inferior goods)

Consumer tastes Changes of consumer tastes in favor of the focal firm’s product (or its a�ributes)

Changes of consumer tastes away from the focal firm’s product (or its a�ributes).

Consumer expecta�ons Changes in expecta�ons that cause consumers to buy now rather than in a future period

Changes in expecta�ons that cause consumers to postpone purchases into a future period

Ac�ons by governments Changes to laws or regula�ons that encourage consump�on of the product

Changes to laws or regula�ons that discourage consump�on of the product

Demographic changes Increases in the age and gender cohorts that buy the focal firm’s product

Decreases in the age and gender cohorts that buy the focal firm’s product

Weather condi�ons Changes in weather pa�erns or condi�ons that cause more to be demanded

Changes in weather pa�erns or condi�ons that cause more to be demanded

Natural disasters Events causing damage that requires purchase of products necessary to cope with the damage caused by the event

Events that cause consump�on of a product to be impossible or inappropriate to consume

The Form of the Demand Function

We are now ready to consider the business implica�ons of the demand func�on, which we shall express in mathema�cal forms as shown in equa�on 4-1. You may be alarmed to think we are about to embark on a mathema�cal discussion; but fear not, the symbols are used as a shorthand way of iden�fying the variables and will serve to

facilitate our discussion, which in turn will facilitate your understanding of the important issues. Let us express the demand func�on6

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote6) in symbols as:

QDx = α + β1PX + β2PY + β3AX + β4AY + β5GNI (4-1)

Where QDx represents the quan�ty demanded of product X (the dependent variable); α (alpha) represents the part of QDx that is unexplained by the independent variables listed; β1 − β5 (the betas) show the impact of a one unit change in each independent variables (PX and PY; AX and AY) on QDx; PX and PY represent the prices of products X and Y, respec�vely; AX and AY represent the adver�sing expenditures for product X and Y, respec�vely; and GNI represents the level of Gross Na�onal Income.

Demand es�ma�on techniques (to be introduced later in this chapter) allow us to es�mate the values for a and the various bs, such that, if we know the current values of the independent variables (those on the right hand side), we can predict the value of the dependent variable, in this case QDx. For now, let us suppose that we have

collected data on the independent variables shown in equa�on 4-1 and have conducted mul�ple regression analysis to find the following values for a and the various bs for a par�cular product:

QDx = 5,030 − 3,806.2(PX) + 1,458.5(PY) + 256.6(AX) − 32.3(AY) + 0.18(GNI) (4-2)

Suppose we want to predict demand (QDX) for the current month using this demand func�on es�mated from recently collected data. First, we will subs�tute into this

equa�on the current values for the independent variables—suppose these are PX = $8; PY = $6; AX = $168 (thousands); AY = $182 (thousands), and GNI = $12,875 (billions). 7

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote7) Mul�plying each of these variables by the appropriate β coefficient, and summing the results, we would find QDx = 22,879 units, and this would be our predic�on for quan�ty demanded in the current month.

Since a demand curve shows the impact on quan�ty demanded for a change in PX with all other determinants held constant, we can isolate the impact of price on quan�ty

demanded by amalgama�ng the impact of the other variables into a single quan�ty, which we shall call AOV (for "All Other Variables"), and express the demand curve in the form QDX = AOV + βPX as follows:

QDx = 53,328.7 − 3,806.2(PX) (4-3)

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Note that this expression for the demand curve depends on all other variables remaining constant, and we require this so we can isolate the impact on quan�ty demanded of price, alone.

The Inverse Demand Curve

Economists, following the conven�on set by the classical economist Alfred Marshall, tradi�onally draw the demand curve with price (the independent variable) on the ver�cal axis and quan�ty (the dependent variable) on the horizontal axis, which is opposite to the way mathema�cians like to draw graphs—they would place the dependent variable on the ver�cal (Y) axis and the independent variable on the horizontal (X) axis. The economist’s conven�on makes it easier to compare prices and costs in later chapters, however. To express equa�on 4-3 in terms of PX we will add 3,806.2PX to both sides, take QDX from both sides, and divide both sides by 3,806.2 to find:

PX = 53,328.7/3,806.2 − 1/3,806.2(QDx) (4-4)

This simplifies to PX = 14.011 − 0.000263(QDx). This very small coefficient to QDx is hard to comprehend, so for convenience we shall now express QDx in units of one

thousand, and rewrite this as:

PX = 14.011 − 0.263QDx (4-5)

The demand for product X is now expressed in the form of an inverse demand curve of the generic form:

PX = a + bQDx (4-6)

where a = AOV/−β and b = 1/β. If we now plot this inverse demand curve on a graph with PX on the ver�cal axis, it will intercept the ver�cal axis at 14.011 (since PX =

14.011 when QDx = 0). Further, from equa�on 4-3 above, we would find the horizontal intercept by no�ng that QDx = 53,328.7 when PX = 0. These intercept values of the

inverse demand curve serve to locate the demand curve at the correct height within the graph, as shown in Figure 4.1, so that this demand curve will provide useful results within the relevant range of prices, that is, for prices around the current price level. Note that, henceforth, we shall simply refer to it as the demand curve rather than repeatedly saying the inverse demand curve.

Figure 4.1: The inverse demand curve

Total Revenue and Marginal Revenue

In Figure 4.1 you can see the full range of prices and quan��es demanded for the market demand curve. The manager will want to know what happens to total revenue (TR) when price is changed and whether TR will rise or fall when price is increased (or reduced). There is a simple rela�onship between the demand curve, the total revenue curve and the marginal revenue curve, which we will now demonstrate. In Table 4.3 we show several levels of price ranging from $14.011 (when QDx = 0) to zero, (when QDx = 53.328). Note that total revenue is equal to price �mes the quan�ty demanded, that is:

TR = PxQDx (4-7)

In Table 4.3 you will note that TR starts from zero (when nothing is sold), rises to a maximum when price is $7, and then falls all the way to zero again as price is reduced further. No�ce that TR is maximized at $186,795 halfway down the demand curve (where PX = $7, which is half of the ver�cal intercept value and QDx = 26.685, which is

half of the horizontal intercept value). You can see that TR rises in a smooth curve to its maximum value and then falls in a smooth curve, as shown in Figure 4.2.

Table 4.3: Price �mes quan�ty demanded equals total revenue Price Quan�ty demanded Total revenue

     $14.011 0      $0

  $12 7,654 $91,848

  $10 15,267 $152,670

 $8 22,879 $183,032

 $7 26,685 $186,795Processing math: 0%

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 $6 30,492 $182,952

 $4 38,104 $152,416

 $2 45,716 $91,432

 $0 53,329      $0

Now we consider marginal revenue (MR), which is defined as the change in total revenue for a one-unit change in quan�ty demanded. MR is important because it indicates "where the firm is" on the TR curve and the firm surely does not want to be on that part of the TR curve where total revenue is falling. Given the defini�on of MR above, we can express it in terms of TR and quan�ty demanded, as follows:

MR = ΔTR/ΔQDx (4-8)

where the symbol Δ (uppercase delta) signifies a discrete change in each of the variables indicated. You will quickly appreciate that MR is a measure of the slope of the TR curve, since ΔTR represents the rise of the TR curve and ΔQDx represents the run of that curve. Clearly the slope (and hence MR) is posi�ve but falling as the TR curve rises

at a decreasing rate (becoming progressively less steep) un�l MR = 0 when TR is maximized, and therea�er MR is nega�ve and takes increasingly larger nega�ve values as TR falls toward zero. In Figure 4.2 the MR curve is shown as star�ng at the ver�cal intercept and falling exactly twice as fast as the demand curve (since it cuts the horizontal axis at half the quan�ty demanded, i.e., about 26,685 compared to 53,328). The MR curve starts at about $14, frac�onally below the intercept value (which is 14.011) where the first unit is demanded, because the first unit sold caused TR to increase from zero to about $14. Thus, the MR curve can be represented as having the same ver�cal

intercept as the demand curve and twice the slope of the demand curve8 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#footernote8) as follows:

MRx = a + 2bQDx (4-9)

Figure 4.2: Demand, total revenue and marginal revenue curves

What we learn from all this is that there is a happy medium in terms of the price to be set by the firm. If price is set "too high" on the demand curve, TR could be increased by reducing price, and oppositely, if price is set "too low" on the demand curve, TR could be increased by increasing price. But note that TR is not profit—we have not yet considered the costs of produc�on, so we are not yet ready to say exactly where on the demand curve the price should be set to maximize profits. We can readily see that the lower half of the demand curve is a bad idea. Marginal revenue would be nega�ve, so TR would be increased by moving to the upper half of the demand curve. But, the profit-maximizing price level will depend on the level of costs, as we shall see in Chapter 7.

2. Price wars are likely to happen in oligopoly markets (where there are rela�vely few compe�ng firms, such as the automobile market), which we examine in Chapter 7. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return2) ]

3. Some texts use the term normal products to describe what we are calling superior products here. Later in this chapter we will see that superior (also known as normal) products can be divided into necessi�es, which increase by a lesser propor�on than does income, and luxuries, that increase by a greater propor�on than does income. [return

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(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return3) ] 4. The macroeconomic system tends to follow a cyclical pa�ern of faster growth followed by slower (or nega�ve) growth of gross na�onal product (GNP), followed by faster growth again. These cycles of

economic expansion followed by recession are known as business cycles. Thus, we say that the demand for superior products is procyclical, meaning that it is generally in synchroniza�on with the business cycle, whereas the demand for inferior products is an�cyclical, meaning that it generally moves oppositely to the changes in GNP. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return3) ]

5. Note that the firm’s brand name is an a�ribute of the product because it connotes informa�on about the firm’s a�tudes to business ethics, product quality, the natural environment, social equity and jus�ce, and so on. A brand name is effec�vely a stock of knowledge held by the consumer, so that new informa�on that enhances the brand is likely to result in increased demand for the firm’s product. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return5) ]

6. Note that only some of the controllable and uncontrollable determinants of market demand are listed in this par�cular demand func�on. We suppose that either data could not be collected on the other independent variables, or that data collected on the other poten�al determinants revealed that these variables had insignificant impact on QDx for this product. Also note that the linear (i.e., addi�ve)

demand func�on depicted by equa�on 4-1 is just one form of the demand func�on—the actual form is an empirical issue, demand could be a nonlinear func�on of some variables, for example, it depends on what the data reveals when we es�mate the demand func�on. We use a linear demand func�on here for simplicity of exposi�on. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return6) ]

7. We are using gross na�onal income (a macroeconomic concept) here as a proxy measure of the income levels of consumers of product X, assuming that their incomes would rise or fall in synchroniza�on with GNI. This is an oversimplifica�on, of course, but we note that GNI data is readily available and allows the manager to avoid the search costs of gaining actual data on changes in consumers’ incomes, which may be only slightly more accurate. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return7) ]

8. This is because TR is a quadra�c expression in Q, which we can specify by recalling from equa�on 4-6 that Px = a + bQDx and subs�tu�ng for Px into equa�on 4-7 we find TR = aQDX + bQDx 2. Marginal

revenue (MR) is the deriva�ve of the TR expression, so MR = a + 2bQDX. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.1#return8) ]

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4.2 Elasticities of Demand

Managers will be interested in the elas�city of demand with respect to each of the determining variables because these measure the rela�ve responsiveness of quan�ty demanded to a small change in a par�cular determining variable. Because many independent variables operate to determine quan�ty demanded, there are many elas�city measures that the manager will be interested in. We shall look at the main ones here, but you will see that an elas�city value can easily be calculated for any variable that

significantly influences demand.9 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#footernote9)

Price Elasticity of Demand

Price elas�city of demand is defined as the percentage change in quan�ty demanded divided by the percentage change in price. That is:

(4-10)

where ε (the Greek le�er epsilon) is the conven�onal symbol for price elas�city and Δ (the Greek le�er [capital] delta) represents a discrete change in the relevant variable. Expanding this out, we can equivalently say:

(4-11)

Cancelling the 100/1 terms and rearranging we find:

(4-12)

Now note that the first term in this expression (ΔQDx/ΔPx) is equal to β1 from the demand func�on, so:

(4-13)

Note that β1 shows the responsiveness of QDx to a small change in Px. Since β1 = −3,806.2 in our earlier example, we can say that a $1 increase in the price of product X will

cause a decrease in quan�ty demanded of 3,806.2 units. But note that elas�ci�es of demand are measures of rela�ve responsiveness, so the β1 coefficient is weighted by

the ra�o of price to quan�ty demanded to find the price elas�city value.10 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#footernote10) Evalua�ng equa�on 4-14 for β1 =

−3,806.2, Px = $8, and QDx = 22,879 we find ε = −1.331. So, price elas�city is equal to the coefficient to price from the demand func�on weighted by the ra�o of price to

quan�ty demanded. Since the ra�o of Px to QDx varies from infinity (when QDx = 0) to zero (when Px = 0) price elas�city must vary from very high nega�ve numbers to very

low nega�ve numbers as we move down the demand curve. We can see this in Table 4.4, using the data from the previous example.

Table 4.4: Price elas�city at various price levels PX QDx PX/QDx β1 ε

$14.011 0 ∞ −3,806.2 ∞

$12 7,654 1.568 −3,806.2 −5.967

$10 15,267 0.655 −3,806.2 −2.493

$8 22,879 0.350 −3,806.2 −1.331

$7 26,685 0.262 −3,806.2 −1.000

$6 30,492 0.197 −3,806.2 −0.749

$4 38,104 0.105 −3,806.2 −0.400

$2 45,716 0.044 −3,806.2 −0.167

$0 53,329 $0 −3,806.2 0

Note that the price elas�city values are nega�ve because β1 is nega�ve (due to the inverse rela�onship between price and quan�ty demanded). Also note that the price

elas�city rises from high nega�ve numbers to smaller nega�ve numbers as we move down the demand curve, and that ε = −1 at the midpoint of the demand curve. Talking about numerically larger nega�ve values can be confusing. A be�er way of communica�ng about price elas�city is to talk about it in absolute terms, ignoring the nega�ve sign. Thus, economists say the price elas�city gets higher (in absolute terms) as we move up the demand curve. For example, we say that price elas�city at price $12 is higher than it is at price $10, and so on. By conven�on we say demand is price elas�c above the midpoint of the demand curve (for ε > |1|, i.e., for values of ε greater than

one in absolute terms) and conversely is price inelas�c below the midpoint of the demand curve (for ε < |1|, i.e., for values of ε less than one in absolute terms).11

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#footernote11)

We can now summarize the rela�onships between price, price elas�city, total revenue, and marginal revenue that are apparent in Figure 4.2. If price elas�city is greater than 1 (in absolute terms) then the current price must be on the upper half of the demand curve; MR must be posi�ve; and TR will decrease for a price increase (or increase for a price decrease). Oppositely, if ε < 1 (in absolute terms) then the current price must be on the lower half of the demand curve; MR must be nega�ve; and TR will increase for a price increase (or decrease for a price reduc�on). Thus, price elas�city is a number that conveys a lot of useful informa�on to the managerial decision maker.

Income Elasticity of Demand

Income elas�city of demand is defined as the percentage change in quan�ty demanded divided by the percentage change in income (that caused the change in demand). That is:Processing math: 0%

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Although caviar is a luxury good for many, this is not the case for everyone since everybody’s tastes and income levels are different.

© iStockphoto/Thinkstock

(4-14)

where θ (the Greek le�er theta) is the conven�onal symbol for income elas�city. Following the earlier example we are using GNI (gross na�onal income) to represent the income level. Following the same procedure as before we can "cut to the chase" and simply say that:

(4-15)

where β5 is the coefficient to GNI from the demand func�on es�mated earlier as equa�on 4-1. Evalua�ng equa�on 4-15, using the earlier values of β5 = 0.18, GNI = 12,875,

and QDx = 22,879, we find θ = 0.1013. Thus, according to our data, we expect that the responsiveness of demand to a one-unit change (i.e., one billion) in GNI will be about

0.18 units of product X (i.e., the value β5), but that the rela�ve responsiveness (i.e., the income elas�city) is 0.1013. The income elas�city implies that quan�ty demanded

would increase by only about one tenth of 1% for a 1% increase in GNI (or 1.013% for a 10% increase in GNI), which is to say that quan�ty demanded is virtually unresponsive to changes in GNI. As with price elas�city, economists use the income elas�city value (θ) to provide informa�on over and above the responsiveness value, as we shall soon see.

From our earlier discussion of superior and inferior goods we know that product X must be a superior good since its quan�ty demanded increases when income increases. Indeed we could have concluded that simply by looking at the posi�ve sign of the β5 coefficient to income in the demand func�on. If on the other hand, β5 had been a

nega�ve number, we would know that the product was an inferior good. Note that some consumers may indeed consider product X to be an inferior good but on balance the income elas�city shows it is a superior good, since the overall effect of an income change on quan�ty demanded is slightly posi�ve, and this overall effect is what the manager will want to know.

Luxury and Necessity Goods

We can make a further dis�nc�on within superior goods based on the size of the income elas�city. If θ is greater than 1, we say that the product is a luxury good. Values of θ > 1 mean that demand for the product increases by a larger percentage than the percentage increase in consumer incomes. For example, suppose your income is currently $100,000 and you buy caviar four �mes a year, spending say $400 a year on 20 ounces of caviar. Suppose your income rises by 10% to $110,000 a year, and you then increase your caviar consump�on to six �mes (30 ounces total) a year. The percentage increase in your demand for caviar is 50% and the percentage increase in your income is 10%, so θ = 5. As we suspected of course, this makes caviar a luxury good for you, but not necessarily for everyone, since everybody’s tastes and income levels are different. Extraordinarily rich people may already be buying as much caviar as they can eat and may respond to an increase in their incomes by not buying more, and most people on lower incomes will not be buying any caviar at all. Again, the manager will look at the aggregate change in market demand when incomes

change rather than the varia�on across consumers within his or her market.12

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#footernote12)

Conversely, if θ is posi�ve but less than one we say that the product is a necessity good. In our earlier example product X would be classified as a necessity good, since θ = 0.1013. For necessity goods, demand certainly increases when income rises, but its rela�ve responsiveness is less than one. Examples of necessity goods include all basic foodstuffs, ordinary clothing, basic housing and transporta�on services, and other basic things that consumers need to buy to stay warm and stay well as they go about their normal lives whether working, unemployed, or re�red. Luxury goods are those subs�tute products that one aspires to but cannot afford while on rela�vely low incomes. For example, as income rises people might want to replace a low-status brand handbag with a high- status brand handbag, or replace cheap Scotch whisky with single-malt Scotch whisky. No�ce that the low-status handbag and the cheap Scotch are inferior goods for these people in these examples, since their quan�ty demanded for these products decreases as their incomes rise. But also note that these products are not necessarily inferior goods at the aggregate market level—for very poor people they might be luxury goods that can only be purchased as incomes rise from very low levels. Managers will want to predict changes in the market demand for their products when incomes change, and while this will include some people increasing and some people reducing their quan�ty demanded, they will want to be able to predict that the net effect will go one way (superior goods) or the other (inferior goods).

Cross-Price Elasticity of Demand

Cross-price elas�city of demand is defined as the percentage change in quan�ty demanded for product X divided by the percentage change in the price of a related product Y. That is:

(4-16)

where η (the Greek le�er eta) is the conven�onal symbol for cross-price elas�city of demand. Following the same procedure as before we can say that:

(4-17)

where β2 is the coefficient to PY in the demand func�on shown earlier as equa�on 4-1. Evalua�ng equa�on 4-17 for the values of β2 = 1,458.5, PY = 6, and QDx = 22,879,

we find η = 0.382. Thus, according to our data, we expect that the responsiveness of QDx to a one-unit increase in PY (i.e., from $6 to $7), will be 1,485.5 addi�onal units of

X, but that the rela�ve responsiveness (i.e., the cross-price elas�city) will be 0.382. This implies that a 10% increase in the price of product Y would cause the quan�ty demanded for X to increase by about 3.82%, or conversely a 10% price reduc�on for product Y would cause the demand for product X to decline by about 3.82%. Thus product X and product Y are subs�tutes for each other—increases in the price of one would cause some consumers to switch from that product towards the other in order to maximize their u�lity.

To summarize, the sign of the coefficient to the price of a related product in the demand func�on (β2 in this example) and the sign of the cross-price elas�city measure (η)

indicates whether that product is a subs�tute or a complement for the focal product X. If the β coefficient and hence the cross-price elas�city had shown a nega�ve sign, we would know that product Y is a complement for product X, that is, X and Y are complementary in consump�on, meaning they are typically consumed together. The size of

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Price Elas�city

the coefficient will show the responsiveness of QDx to a one unit change in PY, and the size of the cross-price elas�city measure will imply the percentage change in QDx for

a one-percentage change in PY.

Other Elasticities of Demand

Because the es�mated demand func�on we introduced earlier provides data on the responsiveness of demand for product X to changes in adver�sing for product X, we can calculate the elas�city of demand with respect to the firm’s adver�sing expenditures. Again, the elas�city measure will be the percentage change in QDX divided by the

percentage change in adver�sing, but is more quickly calculated by weigh�ng the coefficient to the adver�sing variable in the demand func�on (β3) by the ra�o of the adver�sing expenditure (Ax) over the dependent variable

(QDx). Evalua�ng for β3 = 256.6, Ax = 168 (in thousands) and QDx = 22,879 we find the adver�sing elas�city to be

1.884.

Thus, the responsiveness of quan�ty demanded to adver�sing expenditures is expected to be 256.6 addi�onal units of product X for every addi�onal $1,000 of adver�sing expenditure. The rela�ve responsiveness of demand to adver�sing is that a 1% increase in adver�sing would lead to a 1.884% increase in quan�ty demanded. But whether the firm should do any more adver�sing depends on how much each addi�onal unit of product X would

contribute to the firm’s expenses or contribu�on margin.13

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#footernote13) Obviously it is only worth spending another $1,000 on adver�ng if the extra sales (256.6 units) contribute at least $1,000 (i.e., about $4 each per unit) to overhead and profit. The informa�on gained from the es�mated demand curve, plus informa�on gained from cost es�ma�on (see Chapter 6) will help the manager make the decision whether to change the adver�sing level or not. We shall also consider the firm’s adver�sing decision in Chapter 11.

Cross-Adver�sing Elas�city

The es�mated demand func�on also provided data on the impact of firm Y’s adver�sing on the quan�ty demanded of product X. The cross-adver�sing elas�city will be the coefficient (β4) to the AY variable in the demand func�on weighted by the ra�o of the independent variable (AY) over the dependent variable (QDx). Evalua�ng for β4 =

−32.3, AY = 182 (in thousands) and QDx = 22,879 we find the cross-adver�sing elas�city to be −0.257. Thus, the responsiveness of quan�ty demanded of X to increased

adver�sing expenditures by Y is expected to be −32.3 units of product X for every addi�onal $1,000 spent on adver�sing by firm Y, and the rela�ve responsiveness of demand for X to adver�sing by Y is that a 10% increase in adver�sing by Y would lead to a 2.57% decrease in the quan�ty demanded of X. Thus, the firm’s demand is not very sensi�ve to changes in the adver�sing of this rival firm. But managers at firm X need to know how vulnerable they are to increases in adver�sing (or promo�onal efforts more generally) by related-product firms, so they can decide on their own adver�sing policy. Should they spend more on adver�sing to win these customers back? Would it be worth it? That depends, again, on the contribu�on margin for product X. If it is thousands of dollars per unit of X (such as it might be for heavy machinery, MBA programs, or sales of luxury cars) then firm X may well find it more profitable to increase its own adver�sing, or reduce their price, to increase market share. On the other hand, if the contribu�on margin is rela�vely small it will not be worth either adjustment, given the costs of changing prices or moun�ng an adver�sing campaign. We defer resolu�on of this decision problem to Chapter 11.

Quality Elas�city of Demand

Finally, we will briefly consider the firm’s quality elas�city of demand. Quality elas�city is defined as the percentage change in quan�ty demanded of product X divided by the percentage change in the quality of product X. We argued in Chapter 3 that a perceived increase in quality would cause an outward shi� in the demand curve for individual consumers, and that this, in aggregate, would cause an outward shi� in the market demand curve. The manager will want to know "how far will the demand curve shi� if I increase product quality?" Keep in mind that increased product quality will typically cause per unit costs to be higher, so again the manager will want to know "will an increase in quality lead to an increase in my profits?" In a simple example, suppose that increased quality causes variable costs to rise by $1 per unit, but the market will buy the same or greater volume at a price that is $1.25 higher than before, you can see that the firm will be more profitable as a result. In Chapter 11 we will

look at more complex examples where there are diminishing returns to adver�sing effec�veness and also where variable costs increase at higher levels of produc�on.14

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#footernote14)

9. Elas�ci�es of demand are deduced from the values found in the demand func�on. Thus, although we have for convenience expressed QDx in thousands in the demand curve, we will con�nue to express

QDx in single units in the calcula�ons of the various elas�ci�es. Alterna�vely, we could divide each of the β coefficients by 1000 (e.g., β1 which was found to be 3,806.2 would be 3.8062), and so on, for the

other coefficients. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#return9) ] 10. This is an important difference between the jargons of marke�ng and economics. When marketers speak of "price responsiveness," they usually mean the β1 value. Economists use the term "price

elas�city" to show the rela�ve responsiveness of ΔQDx to ΔPx and they use ε value to convey informa�on about the change in total revenue that is associated with a price change, as we will see. [return

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#return10) ] 11. Note that firms do not want to have their prices fall on the lower half of the demand curve, since MR is nega�ve and TR would be increased by raising price un�l it was higher than the midpoint of the

demand curve. As we shall see in Chapter 7, only firms opera�ng in oligopolies (few compe�ng firms) who expect heavy sales reduc�ons if they raise prices (because they expect their rivals to not follow their price increases) have to worry about that. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#return11) ]

12. Of course all caviars are not the same. There are quality differences that reside in the different a�ributes and a�ribute ra�os for the various brands of caviar. So a brand manager pursuing a niche marke�ng strategy will be very interested in the tastes and preferences of consumers in the targeted niche market, and it is the niche market’s demand, rather than the total market demand for all caviars, that is important to the manager. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#return12) ]

13. The contribu�on margin is the difference between price and variable cost per unit and represents the contribu�on that each unit of product X makes toward the firm’s overhead (fixed) costs and profits a�er the incremental variable costs have been covered. We will spend more �me talking about the contribu�on margin in the next two chapters. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#return13) ]

14. To include product quality as an independent variable in an es�mated demand func�on, the firm would need to have reliable data that reflects product quality. Assuming efficiency in produc�on (see Chapter 6), and other things remaining the same, such as the output rate, wages, and other input costs, the cost of goods sold per unit might be a sufficiently reliable indicator of product quality. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.2#return14) ]Processing math: 0%

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Focus groups are useful for uncovering new informa�on about buyers’ probable reac�ons to changes in price and other determining variables.

© Digital Vision/Thinkstock

4.3 Estimating Market Demand From Primary Data

In the remainder of this chapter, we will discuss methods that are used to obtain data rela�ng to the firm’s demand func�on so we can derive the coefficients that indicate the responsiveness of quan�ty demanded to each of the independent variables that collec�vely determine the firm’s demand. We begin by discussing direct methods of demand es�ma�on whereby primary data is collected from actual or poten�al buyers via interviews, surveys, and market experiments. Indirect methods of demand es�ma�on involve the sta�s�cal examina�on of data previously collected for official government sta�s�cs, or found in reports researched and wri�en for other purposes (so- called secondary data). We will discuss the use of regression analysis as a tool to quan�fy the dependence of quan�ty demanded on the independent variables in the demand func�on. Special a�en�on is given to the interpreta�on of the regression results and the avoidance of six major pi�alls of regression analysis.

Interviews, Focus Groups, and Surveys

The most direct method of demand es�ma�on is to simply ask buyers or poten�al buyers about their probable reac�ons to changes in price or other determining variables. Interviews usually follow a ques�onnaire to ensure that respondents provide answers to specific ques�ons. Ques�onnaire design is an art form and should not be treated lightly—unless the ques�ons are asked in words that the respondent fully understands, the results might not be reliable. Focus groups are less structured and are useful for finding new informa�on about what consumers want in terms of product design or their collec�ve response to planned price changes, for example. Usually the researcher will let conversa�on range freely within the focus group, le�ng people’s ideas and opinions emerge, and occasionally redirec�ng discussion back to issues of concern to the researcher. Surveys u�lize structured ques�onnaires and are administered either by mail, by telephone, by email, or via online survey tools such as SurveyMonkey.

Let us work through a simple example of a survey to find the demand curve for a new product. Suppose a firm plans to introduce a new product and wants to know how much would be demanded at various price levels. From the popula�on of poten�al buyers a random sample of 500 people is drawn, perhaps by contac�ng every 10th name on a list of probable buyers. Suppose we then contact these people a�er dividing them into five groups of 100 each. For each group we would describe the new product and its usefulness in the same way, but would state a different price for each group, as shown in Table 4.5. We would then ask them

whether they would buy the product at the price stated, and list the number of posi�ve responses in the table as shown.15

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.3#footernote15)

Table 4.5: Survey results for various suggested prices Sample Group 1 2 3 4 5

Price stated $6 $4 $5 $7 $8

Quan�ty demanded 198 305 262 155 97

These price–quan�ty coordinates would then be plo�ed, as shown in Figure 4.3, and a line of best fit would be drawn freehand across the data points. A line of best fit summarizes the apparent rela�onship between the two variables. We should not expect all (or any) of the observa�ons to lie exactly on the line of best fit. There is likely to be random varia�ons among the five groups that cause them to demand a li�le more, or a li�le less, than another group would have at the same price. We posi�on the line of best fit such that we think it minimizes the gap between the data points and the line. Then we note the intercept point on the price axis and the slope of the line of best fit. The intercept appears to be close to $10 and the slope appears to be roughly −1/50 = −0.02. Thus, our es�mate of the sample’s demand curve for this new product is Px = 10 − 0.02QDx.

Figure 4.3: Freehand line of best fit to price-quan�ty data pairs

But note that these results relate to a sample of only 500 people. To es�mate the demand curve for the en�re market we would mul�ply the slope term by the sampling propor�on. Suppose 5% (or one in 20 people) of the popula�on was sampled, so we need to mul�ply the slope term by 1/20 to arrive at an es�mate of the market demandProcessing math: 0%

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Hiring a marke�ng research firm to design a professional ques�onnaire is money well spent for managers contempla�ng large investments in new products, reposi�oning of product prices or quali�es, and product line extensions.

© iStockphoto/Thinkstock

curve, which would be PX = 10 − 0.001QDX. From this, we can easily determine that the horizontal intercept of the es�mated demand curve occurs at about 10,000 units.

Thus, marginal revenue would cut the horizontal axis at about 5,000 units, so that the total revenue curve would rise to a maximum of about ($5 × 5,000 units =) $25,000 (per period) and would then fall if price were to be reduced below $5.

Poten�al Problems With Interview and Survey Data

Survey methods may not lead to reliable results if any one of the seven following problems exists. First, we may not have a random sample of our target consumers. Methods exist to ensure that samples are sufficiently random, and tests can be made to ensure that sample selec�on bias or nonresponse bias are not likely to be present in the data (Hair, Black, Babin, & Anderson, 2010). A second problem is that answers reported to you directly (o�en called espoused data) by the survey respondent may be unreliable. The presence of the interviewer, or even the fact that someone later will see the answers given, may cause the respondents to be less than fully frank with their answers, which is known as interviewer bias. For example, people may overstate their income in order to seem more successful than they really are. A third problem is social desirability bias, that is, if the researcher asks a personal ques�on, the respondents might understate or overstate the true amount because they would be embarrassed to reveal the truth. Ques�ons about poli�cs, religion, income, and lifestyle are likely to induce a social desirability bias. A fourth problem is self-serving bias, where interviewees have the incen�ve to not reveal the exact truth since it might adversely affect future outcomes for them. For example, if a firm were to ask how much more would consumers pay for a 20% improvement in quality, respondents would have an incen�ve to say an amount smaller than what they really would be prepared to pay. A fi�h problem is disinterested or busy par�cipants who give random answers or rush through �cking boxes without really considering the ques�ons asked. Even if the answers given are completely truthful, a sixth problem is the best-of-inten�ons problem whereby the respondents say what they believe they will do (e.g., I will buy the product at a price of $7) but do not subsequently actually buy it due to the interven�on of other issues, such as losing a job or discovering another product that is a be�er value proposi�on. Finally, the responses may be unreliable if the ques�ons are confusing, misinterpreted, or unknowable. New products, when described briefly for the first �me, may not easily be imagined by consumers as part of their lifestyle or work environment. For example, IBM vastly underes�mated the demand for its personal computers in the early 1980s a�er surveying hundreds of business execu�ves who saw the desktop computer simply as a fancy typewriter for their secretaries.

To combat these problems, it is important to design the ques�onnaire carefully, which is best done by experts. Marke�ng research firms, or freelance consultants specializing in survey design, can be u�lized to design ques�onnaires that will minimize these problems; for example, rather than asking ques�ons about price directly, the ques�on might ask about "value" (recall that value equals quality over price) that consumers perceive in a series of price–quality combina�ons. Money spent on professional ques�onnaire design will be money well spent for managers contempla�ng large investments in new products, reposi�oning of

product prices or quali�es, product line extensions, and so on (Hair et al., 2010).16

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Simulated Market Situations

Marketers o�en conduct simulated market situa�ons, also known as consumer clinics, where they construct an ar�ficial shopping environment and observe the choices of customers, while varying the prices of some products, the shelf placement of products, and point-of-purchase informa�on about product quality, for different groups of shoppers. Par�cipants are usually a�racted to these experiments by the promise of free products; for example, they may be given $100 of "monopoly money" to spend as they wish within an hour. Researchers monitor hidden cameras to observe shopping behavior and tally up the purchases at the cash register on the way out. If the par�cipants are randomly drawn from the popula�on of poten�al customers for the focal products, market researchers may conclude that the en�re market would react to price changes and changes in other product a�ributes in the same way. The quan�ta�ve results of a simulated market experiment (e.g., how many units of X were purchased by each sample of 100 shoppers) can be analyzed in the same manner as above for the survey data, with an es�mated line of best fit scaled up to reflect the ra�o of sample size to the popula�on of poten�al customers for the focal product. Similarly, for different quali�es of the same product, higher shelf placement,

and end-of-aisle placement, the researchers could mul�ply the sample groups’ responses to es�mate the overall market’s response to changes in these variables.17

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Market Experiments

Market experiments involve real people in real markets spending their own money on the products they probably really do want. The firm will select a specific city or region that is representa�ve of other ci�es or regions or perhaps is representa�ve of the en�re na�on (e.g., San Diego is said to be quite representa�ve of southern California). The firm then introduces a new price, or new quality (i.e., changed a�ributes) of its product, or new promo�onal campaign into all stores in this test market (via its established distribu�on systems), and observes the impact on quan�ty demanded in that city or region. The firm then predicts a similar result will occur in other ci�es or regions that are similar to the test market, perhaps proceeding to a "na�onal rollout" to the en�re market. Such experiments are obviously very large scale and will require a large investment that may be lost if the experiment is not successful or conducted well. On the other hand, such market experiments limit the poten�al loss to only some frac�on of what it might be if the firm had gone directly to a na�onal rollout. Thus, market experiments can be used to validate managers’ decisions about changes in controlled variables in a limited context before they embark on full-scale implementa�on of the changes. As we saw in Chapter 2, managers will want to integrate such risk considera�ons into their decision making.

Direct Marke�ng Experiments

Direct marke�ng occurs when the producer of the product sells directly to the consumer of the product rather than u�lizing conven�onal distribu�on channels that involve wholesalers and retailers as intermediaries between the producer and the consumer. An example of direct marke�ng is Internet sales direct from the manufacturer to the consumer, and many retailers also sell products via their Internet websites. However, many people s�ll read newspapers, magazines, and le�ers sent to them via "snail mail," and these remain effec�ve vehicles for direct marke�ng experiments. Researchers send different price and quality offers to different poten�al customers, who then decide whether to buy the product at the price and quality they have been offered. Researchers expect to find a nega�ve price effect and a posi�ve quality effect, of course, but it is a measure of the extent of those effects (i.e., the responsiveness of demand to the changes made) that they seek. For example, a firm might want to test three different price points and two different quality points before choosing one price–quality combina�on to commit to full-scale produc�on. It would send mail to, call, or email all six possible combina�ons as an offer (only one offer to each person) to individuals on its mailing, telephone, or email list, or social network. By making different offers to different poten�al customers and tallying up the actual sales made for each combina�on, the firm’s managers would es�mate the price effect and the quality effect and decide which combina�on to proceed with.Processing math: 0%

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Direct marke�ng occurs when the producer of the product sells directly to the consumer. This can be accomplished through Internet sales, newspapers adver�sements, or direct mailings sent in the mail.

© Jerry Arcieri/Corbis

Internet websites allow firms to compile a list of poten�al customers by encouraging people to ask for further informa�on or a price quote, and consumers must supply their email address to receive an answer. Since those customers are typically not connected to each other, or are not likely to communicate with each other effec�vely, they are not likely to know that the firm is making mul�ple offers and will typically make up their own mind on the basis of the offer made to them. Similarly, special-interest magazines and na�onal newspapers that are printed in two or more loca�ons to save freight and postage cost, or are printed in two or more print runs, can contain different adver�sements for the same product being read by different poten�al customers, with subsequent sales data providing informa�on on the price effect, quality effect, impact of packaging or promo�onal changes, and so on.

15. Rather than a Yes/No answer, we might ask the respondent to choose a point on a 1–5 scale where 1 = not at all likely to buy; 2 = somewhat likely to buy; 3 = not sure; 4 = quite likely to buy; and = 5 very likely to buy. We would then record in a table the number of people who chose either 4 or 5. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.3#return15) ]

16. Market researchers o�en use "conjoint analysis" to provide data that is revealed by choices among alterna�ves, rather than simply espoused. Respondents consider several product a�ributes conjointly (i.e., together, in the context of each other). For example, the manager might want to know whether consumers value higher product quality and increased purchasing convenience enough to warrant charging a higher price. In the experiment, the level of price, quality, and convenience of purchasing are varied across mul�ple scenarios. For example, scenario 1 might be stated as high price, high quality, and high convenience (i.e., high-high-high), while scenario 2 might be stated as low-high-high; scenario 3 as high-high-low; and so on. Respondents are asked to rate the a�rac�veness of each scenario on a 1–7 scale ranging from 1 = highly una�rac�ve to 7 = highly a�rac�ve. The conjoint method assigns values to the high se�ng for each of the three variables to find revealed a�tudes to high price, high quality, and high convenience. These will reveal whether the disu�lity of the higher price is offset by the increased u�lity associated with the higher quality and higher convenience. See Hair, J.F., Black, W.C., Babin, B.J., and Anderson, R.E. Mul�variate Data Analysis, Pearson, 2010. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.3#return16) ]

17. Again, such results are not always reliable, for three main reasons: First, the samples may not be a random sample of the overall market, perhaps under- represen�ng consumers who (a) are working and cannot par�cipate during the day, or (b) that have higher incomes and don’t consider $100 worth of free products worth the trouble, or (c) that value their privacy highly. Second, people may spend other people’s money differently than how they spend their own, and might decide to buy luxury goods in the market simula�on that they would not buy from their own income. A third problem is that these market simula�ons are very expensive. Hundreds of shoppers take away thousands of dollars worth of products. It is expensive to set up ini�ally and to monitor the "store." [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.3#return17) ]

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4.4 Regression Analysis of the Demand Function

Regression analysis calculates a mathema�cal equa�on that best summarizes the rela�onship exis�ng between two or more variables. Bivariate regression analysis, also known as correla�on analysis, calculates the rela�onship between two variables, such as price and quan�ty demanded, and provides an equa�on that specifies the intercept and slope terms of the line of best fit to the data. In the simple two-variable case, it is quite easy to sketch in a freehand line of best fit for a small number of observa�ons as we did in Figure 4.3. But imagine if you had 100 or more data points; it would take a long �me to carefully plot them on a graph before you even got to the point of sketching in the line of best fit, and so we rely on computers to quickly and accurately produce the parameters of the line of best fit. Mul�ple regression analysis, that is, with mul�ple independent variables, effec�vely provides the responsiveness coefficients (β) of the rela�onships between quan�ty demanded and each of the independent variables in the demand func�on, so that the impact on demand of all the independent variables can be found simultaneously, with all other independent variables effec�vely held constant. The Excel spreadsheet package (with a sta�s�cal add-in module) can accomplish bivariate or mul�ple regression analysis in milliseconds once you have arranged the data in columns. More powerful sta�s�cal so�ware packages, such SPSS or STATA, are generally used by academics and other researchers, but these rather expensive programs are less likely to be provided in a business firm, or, if you are self-employed you would have to buy one of those packages separately. For our

purposes here, Excel is more than enough.18 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote18)

To illustrate how a computer regression program finds the line of best fit, we shall start with a simple two-variable (bivariate correla�on) case, where Y depends on X. In Figure 4.4, we show several Y,X data points plo�ed on a graph with the line of best fit shown as Y = A + βX. The ordinary least squares method posi�ons the line of best fit such that it minimizes the sum of the squared devia�ons of the observa�ons from the line—the devia�ons are squared to avoid posi�ve devia�ons offse�ng nega�ve varia�ons and to more heavily weight the larger devia�ons. A computer regression program calculates the sum of the squared devia�ons in a few milliseconds, and effec�vely compares different loca�ons of the line of best fit (or the mul�variate analog) and selects the one that minimizes the sum of these squares. Essen�ally, the mathema�cal procedure passes the line through the point represen�ng the mean values of the Y and X observa�ons (which we call Y-bar and X-bar), and then pivots that line around this mean–mean point to find the slope (and thus the intercept) that minimizes the sum of the squared devia�ons from the line. A similar process is involved for mul�ple regression analysis. The mathema�cal procedure can be imagined to pivot the lines of best fit between the dependent variable Y and each of the mul�ple independent variables simultaneously un�l it finds the values for the various β coefficients that minimize the sum of the squares of the devia�ons (which are also known as the residuals or error terms).

Figure 4.4: Ordinary least-squares method of fi�ng the line of best fit

Statistics Provided by Regression Software

Before we use Excel to find the coefficients for a demand func�on, we need to consider some sta�s�cs that are provided by regression analysis and that allow us to judge how well the line of best fit actually fits the data, and how reliable are predic�ons that are made based on the data.

The Coefficient of Determina�on (R2)

The coefficient of determina�on indicates the explained variance of Y, that is, the propor�on of the varia�on in Y (from its mean value) that is explained by the variance in

X (or mul�ple X variables) from its (their) mean value(s). In effect the coefficient of determina�on, commonly called R2, tells us how well the regression equa�on fits the

data.19 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote19) The value of R2 will be between 0 and 1; for example, an R2 of 0.98 would indicate an amazingly

good fit to the data, such as we saw in Figure 4.3. By contrast, the R2 for the data shown in Figure 4.4 is probably only about 0.6, indica�ng that only 60% of the variance in Y is explained by variance in X. That means there is 40% of the variance that is unexplained by the X. This unexplained variance will be largely a�ributed to missing variables, that is, other determinants of Y for which data has not been collected or that were not entered into the regression analysis. A second cause of unexplained

variance could be measurement error in the data. We have to be sure we are measuring the variables correctly or we will introduce variance into the analysis.20

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote20) For example, the use of GNI in the earlier example as a proxy for the incomes of the consumers in the target market is a fairly imprecise measure that almost certainly contains measurement error, since GNI includes business profits as well as household incomes and not all profits

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are paid out as dividends. To minimize measurement error we need to seek the most precise measure we can get for each variable and only use proxy variables when we have no be�er data available.

The Standard Error of Es�mate

The standard error of es�mate (Se) is a measure of the dispersion of the data points from the line of best fit. Using this sta�s�c we can calculate confidence intervals

around the predicted value of Y given a set of values for the independent variables. A confidence interval is a range of values that we expect the actual value of Y to fall within for every value of X within a par�cular sta�s�cal confidence level. We commonly use the 95% confidence interval to indicate the range, between a lower es�mate and an upper es�mate of the Y value (associated with any X value), within which we expect the actual value of Y to fall 95% of the �me.

Assuming that the error terms are normally distributed around the line of best fit, we can use the proper�es of the normal distribu�on to calculate the upper and lower points of the 95% confidence interval. As we saw in Chapter 2, a normal distribu�on will be a symmetric bell-shaped distribu�on of data points around the mean of those data points, and the height of the bell will be such that 68% of the observa�ons will lie within plus or minus one standard devia�on from the mean; and 95% of the observa�ons will lie between plus or minus two standard devia�ons from the mean; and 99.7% of the observa�ons will lie between plus or minus three standard devia�ons from the mean. Note that a standard devia�on is the square root of the variance of the observa�ons around the mean of a single variable. The standard error of es�mate is the analog when there are two or more variables—it measures the square root of the variance of the Y values around the predicted value given the observed values of the independent variables that cause that variance in Y. So, the 95% confidence interval around the predicted value of Y will be given by the predicted value of Y plus or minus two standard errors of es�mate. Put another way, there is only a 5% chance of the predicted value of Y falling outside that confidence interval for any selected value of X.

The Standard Error of the Coefficient

The standard error of the coefficient (Sβ) is a measure of the accuracy of the calculated value of the β coefficient generated by the regression analysis. For mul�ple

regression there is a Sβ value for each one of the independent (X) variables. If Sβ is rela�vely small, we can be more confident that the es�mated value of β is close to the

true value of β, and conversely, if it is rela�vely large we can have less confidence that the es�mated β is close to the true value. (The true value of the coefficients could be found if we were to survey the en�re popula�on of customers rather than just a sample). In short, Sβ is the standard devia�on of the mean β observed for each

independent variable from the sample. Again, using the proper�es of a normal distribu�on, we can establish confidence intervals around the es�mated value of β, and be confident at the 95% confidence level that the responsiveness of the dependent variable to changes of an independent variable will lie within the range described by the relevant β plus or minus two standard errors of the coefficient.

Using Excel to Conduct Regression Analysis

There are many sta�s�cs add-in modules that work with the Microso� Excel spreadsheet program that will make you quite capable of conduc�ng basic regression

analyses.21 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote21) Let us now work through how to set up and conduct regression analysis using Excel. You would first open a new worksheet in Excel. Supposing you have 100 observa�ons, leave the top row empty and enter the numbers 1–100 down the first column (in cells A2, A3, A4, and so on down to cell A101). This allows us to refer to specific observa�ons by their iden�fying observa�on number in case we later find there are serious outliers that

need to be removed.22 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote22) Then label the columns across the top of the spreadsheet with the variable names, star�ng with the dependent variable in cell B1, and the names of the independent variables in cells C1, D1, E1, and so on. Enter the data for the dependent variable observa�ons all the way down the second column (cells B2–B101), and then enter the independent variables corresponding to each observa�on down each of the columns to the right, as shown in Table 4.6.

Table 4.6: Se�ng up an Excel spreadsheet to conduct mul�ple regression analysis Obs’n Sales of X Price of X Price of Y Advert X Advert Y Income Avg. temp Exch. rate

1  9,637 6.99 6.99 128.4  96.3 3,100.2 48.4 1.0434

2 10,815 6.49 6.99 143.1  98.1 3,327.1 52.4 1.0889

3 12,886 5.99 5.99 165.9 120.8 3,654.7 64.8 1.1054

4  9,847 6.49 5.99 132.5 105.6 3,229.3 58.8 1.0226

etc. etc. etc. etc. etc. etc. etc. etc. etc.

Leave a spare row below the last observa�on, and calculate the mean and standard devia�on for the dependent variable by entering =avg(B2-B101) and =stdev(B2-B101) in cells B103 and B104, respec�vely. Then enter =min(B2-B101) and =max(B2-B101) in cells B105 and B106, respec�vely to find the smallest and largest values for the dependent variable. To drag these formulas over to the right for the other data columns, highlight the cells B103–106, locate the small square in the bo�om right hand corner of cell B106 and drag it to the right, out to the last column of data. This should immediately produce the means, standard devia�ons, minima and maxima of the independent variables. We want to take a quick look at these sta�s�cs of the data to give us a feel for the data and to iden�fy any outliers. Looking down each column and comparing the data points with the above sta�s�cs might also reveal obvious data entry errors that we can fix before moving on.

To conduct the regression analysis we first move the cursor to a loca�on below the data so that the results will be posted there. We then go to the "Sta�s�cs" menu and pull down the "Regression" tab to iden�fy the algorithm we need. Clicking on that algorithm will place it in the chosen cell, and we then click on the column heading for the dependent variable (or highlight the data down that column), then in sequence iden�fy which of the independent variables are to be entered into the regression analysis. A�er all have been entered, close the bracket in the algorithm and press "Enter" and the calcula�ons will proceed. A table showing the results will appear in the chosen

area of the spreadsheet. This will include the value of the α and the various β sta�s�cs, as well as the R2, Se , and Sβ sta�s�cs.

We then observe and interpret these sta�s�cs. The α sta�s�c represents that part of the dependent variable that is due to all other variables that are not included in the regression equa�on. Each of the β sta�s�cs shows the responsiveness of the independent variable to the relevant independent variable, and the signs (posi�ve or nega�ve)

should be as hypothesized; that is, nega�ve for the price effect; posi�ve for the other three Ps (if entered into the equa�on)23

(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote23) ; either posi�ve or nega�ve for the income effect; posi�ve for the price of subs�tutes; nega�ve for the price Processing math: 0%

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of complements; nega�ve for the nonprice strategic variables of subs�tutes; posi�ve for the nonprice strategic variables of complements; posi�ve for suppor�ng business environment variables (such as popula�on growth) and nega�ve for damaging business environment variables (such as bad weather or new legisla�on).

From this data we are able to calculate the inverse demand curve (P = a + bQDx) by first calcula�ng the compressed form of the demand func�on (QDx = AOV + β1Px) where

AOV includes the impact of all other variables except Px, as detailed earlier in this chapter. The intercept term in the demand curve expression is calculated as a = −AOV/β1

and the slope term of the demand curve is b = 1/β1. The marginal revenue curve is then MR = a + 2bQDx and the total revenue func�on is TR = aQ + bQ 2. We can also

calculate the elas�city value for each independent variable as the responsiveness coefficient (β) �mes the ra�o of the relevant independent variable and the value for QDx,

such as ε = β1. Px /QDx.

Pitfalls of Regression Analysis

There is an old expression "garbage in, garbage out" that certainly relates to regression analysis. If your data is garbage, your regression results will be too! I will briefly men�on here six common pi�alls of regression analysis that may compromise the accuracy of your results. Specifica�on errors relate to the hypothesized func�onal form of the regression equa�on. If you set up the equa�on in linear form, but in reality the dependent variable has a curvilinear rela�onship with any independent variable, or there are important missing variables, the output sta�s�cs of the regression analysis must be inaccurate. We have also previously men�oned measurement errors whereby the data collected is not an accurate measure of the variable that you want to measure. Next, if there is a simultaneous equa�on rela�onship, such as Y depends on X and simultaneously X depends on Z, we cannot expect a single equa�on to be a true reflec�on of a mul�ple-equa�on rela�onship. Mul�collinearity occurs when there is a significant correla�on between two or more of the supposedly independent variables—this violates a basic assump�on of regression analysis that the independent variables are independent of each other. Heteroscedas�city occurs when the variance of the error terms depends on the magnitude of the independent variables and is therefore not as assumed by the mathema�cs of regression analysis. Finally autocorrela�on (also known as serial correla�on) might occur in �me–series data and indicates that the error terms are serially related, that is, get progressively larger or smaller as �me increases.

Any one of these problems will seriously compromise your regression results. Fortunately, most of these problems can be fixed by respecifying the func�onal form of the equa�on; by collec�ng be�er data; by using a structural equa�on model (with mul�ple equa�ons); by elimina�ng one of the colinear independent variables; or by plo�ng and observing the error terms and subsequently respecifying the regression model. But these "fixes" would take us beyond a managerial economics course into a

quan�ta�ve methods course or a research method textbook.24 (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#footernote24) Our purpose here was to show that basic regression analysis can be conducted easily using the readily available Excel spreadsheet package (with a sta�s�cal module added in) to provide a first level es�mate of the demand func�on and the responsiveness of quan�ty demanded to each of the independent variables for managerial decision-making purposes.

18. Computer programs have turned the old fashioned way of compu�ng the regression equa�on by hand into an unnecessary waste of �me, and also eliminate calcula�on errors. Accordingly, students in managerial economics courses do not need to learn the complex equa�ons that allow the regression parameters to be calculated by hand. We can rely on computers and concentrate on ensuring that the input data quality is high. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return18) ]

19. Note that a "good fit" does not confirm causality, however, since other factors might be driving this, such as misspecifica�on of constructs, poor measurement of variables, endogeneity of variables, and so on. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return19) ]

20. Unexplained variance could also be due to the pure randomness. Note that the same consumer may end up with different decisions on the same product with the same price on different days. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return19) ]

21. One such "sta�s�cs add-in" is Statpro, developed to accompany a popular Sta�s�cs textbook by Albright et al. This add-in is free to download and will allow you to conduct mul�ple regressions using Excel spreadsheets. Use Google to find the Statpro website and follow the instruc�ons to download it into your Excel program. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return21) ]

22. An outlier is an observa�on that has a value for one or more variables that is way outside what appears to be the normal range of devia�ons from the line of best fit (i.e., the regression equa�on). It is important not to delete observa�ons that include large varia�ons that might reasonably be correctly measured but simply include a large random error term—that would amount to falsifying the data. As a simple rule of thumb, and mindful of the proper�es of a normal distribu�on, you might decide to delete observa�ons that are more than three standard devia�ons from the mean value of the variable, assuming an approximately normal distribu�on of the data. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return21) ]

23. If the β for any of the other three Ps (product design, promo�on, or place of sale) is nega�ve, this would indicate that that variable has been taken too far, beyond the op�mum, and is having a nega�ve impact on quan�ty demanded, so should be reduced if the firm wishes to maximize its profits. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return23) ]

24. For example, Hair et al., 2010, Mul�variate Data Analysis text, cited earlier. [return (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/sec4.4#return24) ]

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Summary

In this chapter we began by reviewing the impact of various factors on the firm’s demand func�on, and stated the demand func�on as a linear equa�on that showed quan�ty demanded as a func�on of the independent variables that collec�vely determine market demand. Market demand is influenced by the firm’s controllable variables (price, promo�on, product design, and place of sale) and by other variables that are uncontrollable by the firm (the 4 Ps of other firms, consumer incomes, consumer tastes, consumer expecta�ons, ac�ons by governments, demographic changes, weather events, and natural disasters). We converted the demand func�on to an inverse demand curve of the form P = a + bQDx, which states the price in terms of a ver�cal intercept term (a) and a slope term (b). We then derived the rela�onships between the demand

curve, the total revenue curve and the marginal revenue curve. The marginal revenue (MR) curve has the same intercept value but twice the slope of the demand curve. The total revenue (TR) curve has an inverted-U shape, increasing up to the point where MR falls to zero, and then falling. Next we introduced price elas�city of demand (denoted by the Greek le�er epsilon, ε) and related this to the above curves—price elas�city is a summary measure that indicates what will happen to marginal and total revenue when price is either increased or decreased. We say that demand is price elas�c when price elas�city measure is greater than one in absolute terms, that is, ε > |1|, and that demand is price inelas�c when ε < |1|. We know that TR will be rising (for price reduc�ons) when demand is price elas�c and falling (for price reduc�ons) when demand is inelas�c.

Similarly, other elas�ci�es were introduced as summary measures of the rela�ve responsiveness of quan�ty demanded to changes in variables that affect the quan�ty demanded. In each case the responsiveness of quan�ty demanded is shown by the sign and size of the relevant β coefficient in the demand func�on, and the elas�city (rela�ve responsiveness) measure is the β coefficient weighted by the ra�o of the relevant independent variable to the quan�ty demanded. Managers need to be aware of these elas�ci�es because they each communicate relevant informa�on to the decision maker. Income elas�city of demand (denoted by theta, θ) is a measure of the rela�vely responsiveness of quan�ty demanded to changes in consumers’ incomes. Normal or superior goods have posi�ve income elas�city (θ > 0) while inferior goods have nega�ve income elas�city (θ < 0). Superior goods can be further categorized as luxury goods if income elas�city exceeds one (θ > 1), necessity goods if income elas�city value lies between zero and one (0 < θ < 1). Cross-price elas�city of demand was denoted where η (the Greek le�er eta) was posi�ve for price changes of subs�tute goods and nega�ve for price changes of complementary goods. Cross-adver�sing elas�city of demand was similarly posi�ve for subs�tute goods and nega�ve for complementary goods. We also considered the firm’s own adver�sing elas�city of demand and quality elas�city of demand, no�ng that when these are posi�ve it means that addi�onal adver�sing or quality will lead to addi�onal quan�ty demanded, but where nega�ve it means that the market has responded badly to the firm’s change in that controllable variable.

In the second half of the chapter we introduced methods for es�ma�ng demand func�ons and demand curves. We considered primary data collec�on methods such as interviews, surveys, and market experiments and sketched in the line of best fit to indicate the responsiveness of quan�ty demanded to changes in price or whichever other determining variable the manager may be interested in. We then considered mul�ple regression analysis to compute the dependency of quan�ty demanded on each of the independent variables simultaneously. Regression analysis generates sta�s�cs that provide a measure (β) of the responsiveness of quan�ty demanded to changes in each of

the independent variables included in the regression equa�on, as well as the coefficient of determina�on (R2) that indicates how well the regression equa�on fits the data. The standard error of es�mate (Se) indicates how confident we can be in the predic�on made for the magnitude of quan�ty demanded, with a range of plus or minus 2

�mes the Se indica�ng the 95% confidence interval around that predic�on. The standard error of the coefficient (Sβ) similarly indicates how confident we can be that the β

coefficients derived from the sample data reflect the true rela�onship between the variables that would be found in the popula�on as a whole. We concluded by briefly considering six common pi�alls of regression analysis and emphasizing the need to call in the experts when conduc�ng regression analysis in a business situa�on when the stakes are high and the cost of making a mistake is likely to be higher than the cost of the consultant who could design and implement a study that would gain sufficiently accurate data.

In the next two chapters we turn our a�en�on to the cost side of the profit equa�on (where profit equals revenues minus costs), and again we will u�lize regression analysis to es�mate cost func�ons, so that the manager will have the data required to make profit-maximizing price and other strategic decisions, and that in turn is the subject ma�er for the following four chapters of this book.

Ques�ons for Review and Discussion

Click on each ques�on to reveal the answer.

1. What independent variables do you think should enter the demand func�on for �ckets to the home games of a Na�onal Football team? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The determinants of demand for �ckets to home games of a football team probably include price; loca�on in the stands of the seats available; whether under cover or not; whether reserved for that teams members/supporters or not; whether well-served with food and beverages or not; whether the team is winning games or not; and whether the games are early, mid-season or final series games. Maybe you can think of other a�ributes of football games that increase demand from your perspec�ve.

2. Assign the value "rela�vely high" or "rela�vely low" to the price elas�city of market demand for each of the following, and explain why you chose one or the other value. (a) Coca-Cola (b) Dr Pepper (c) Ar�ficial limbs (d) Levi’s jeans (e) Cure for AIDS (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

(a) Coca-Cola: rela�vely low price elas�city due to strong product differen�a�on supported by incessant adver�sing. (b) Dr Pepper: rela�vely low, due to strongly differen�ated taste (li�le or no close subs�tutes) and fana�cally loyal customers. (c) Ar�ficial limbs: rela�vely low, due to li�le or no close subs�tutes and the strong need for customiza�on to suit individuals. (d) Levi's jeans: rela�vely high, despite strong brand differen�a�on there are many other brands of jeans, each claiming be�er design, with strong promo�onal campaigns. (e) Cure for AIDS: rela�vely low price elas�city of demand due to no subs�tutes and strong need for the product by those afflicted with the disease.

3. If you knew that, for a par�cular product, the current price is $45, current quan�ty demanded is 250 (thousand units per month), and the price elas�city of demand is equal to −1.5, explain how you would find the expression for the demand curve (in the form P = a + bQ).Processing math: 0%

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(h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

Since elas�city can be expressed as ε = 1/b . P/Q we can subs�tute data provided and know that −1.5 = 1/b (45/250) so we can solve for b = 1/−8.333 = 0.12. Then values for P, b, and Q in the demand curve expression P = a + b Q to write 45 = a − 0.12(250). Solving for a, we find a = 75, and thus the expression for the demand curve is P = 75 − 0.12Q.

4. Given your knowledge of the elas�city concept, define the rainfall elas�city of umbrellas. What possible usefulness could such a concept have? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

An elas�city is a measure of the rela�ve responsiveness of one variable to changes in another variable, so the rainfall elas�city of umbrellas would be the percentage change in umbrella sales divided by the percentage change in rainfall; we expect that the more it rains the more umbrellas would be demanded. The value of this informa�on to umbrella vendors would be to es�mate how much stock they need to have in hand when rain is predicted. This would be especially valuable when the stock of umbrellas must be moved from a place of storage (e.g., a warehouse) to the place of sale (e.g., downtown shops) without delay, since umbrella demand is usually an impulse purchase, and if the vendor runs out of stock poten�al sales are lost.

5. Why would you expect the market demand for luxury goods, such as jewelry, to be more vola�le in periods of fluctua�ng incomes, as compared to items such as milk and bread? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The demand for luxury goods, such as jewelry, will fluctuate more than in propor�on to changes in the income levels because it serves a want rather than a need and when incomes go down people can postpone the sa�sfac�on of their wants. Necessity goods, such as milk and bread, sa�sfy the more urgent need for food. People are reluctant to cut back on their purchases of these goods and do so only slightly when their incomes fall.

6. List 10 ques�ons you would ask people in a survey designed to es�mate the demand func�on for a par�cular brand of toothpaste. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

There is no defini�ve answer to this ques�on. You might suggest ques�ons such as: What is your current brand of toothpaste? What other brands would you consider? Why do you prefer brand X? Why do you prefer it to brand Y and brand Z? What do you like about the taste of your toothpaste? Would you prefer it was different in some way? How do you think brand X toothpaste could be improved? What is your income level (in broad categories)? How much could the price of your brand (X) rise before you would switch to another brand?

7. Suppose you had annual data on the price and quan�ty demanded of newsprint over the past 20 years and plo�ed these (or conducted bivariate regression analysis) to find a line of best fit. Why would this be an unreliable es�mate of the demand curve? What other data would you need to make a more reliable es�mate of the demand curve for newsprint? (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

Annual data on price and quan�ty demanded would need to be supplemented by "control variables" that take account of other things that might be different from year to year, or might have changed over the 20-year data collec�on period. Changes in these variables would have caused the demand curve to shi� from �me to �me, such that the observed PQ data would not be on a single demand curve. Annual data on Gross Na�onal Income (as a proxy for customer incomes); newspaper circula�on numbers; and propor�on of the popula�on who buy newspapers (which would have been declining) would be a minimal requirement to control for such shi�s of the demand curve.

8. Summarize the issues you would need to check before concluding that the results of a regression analysis were a reliable basis for es�ma�ng the demand func�on. (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/

The coefficient of determina�on (R2) should be reasonably high to imply an apparent rela�onship between the dependent variable (DV) and the independent variables (IVs); the standard error es�mate should be rela�vely small to allow a rela�vely narrow range of vales within which we can expect the DV value to fall at the 95% confidence level; the standard error of the coefficient for each of the IVs should be rela�vely small to assure us that the es�mated b values are close to the true (popula�on) values; and the six pi�alls of regression analysis (specifica�on errors, measurement errors, simultaneous rela�onships, mul�collinearity, heteroscedas�city, and autocorrela�on) should be absent.

Decision Problems

1. The demand for Fritz Reinhart premium beer in a par�cular city has been es�mated to be:

Qx = 37,986.5 − 4,476.9Px + 2,994.2Py + 668.2Ax − 849.7Ay

Where Qx is quan�ty demanded (per month) and Px is the price of Fritz Reinhart beer (in six-packs); Py is the price of the main compe�tor beer, Urquhart Pilsner; Ax is

the adver�sing expenditure for Reinhart (in thousands of dollars per month) and Ay is the adver�sing expenditure of Urquhart (thousands of dollars per month). The

current values of the independent variables are Px = 9.95; Py = 8.95; Ax = 36; and Ay = 22.

a. Calculate the price elas�city of demand for Fritz Reinhart beer, and comment on the extent to which demand and total revenue would change if the price of this beer (per six-pack) were to be raised by a dollar.

b. Calculate the cross-price elas�city of demand and speculate how a price decrease to $8.50 for Urquhart beer would impact the quan�ty demanded of Reinhart beer. c. Would it be profit maximizing for Fritz Reinhart to increase its adver�sing expenditures by another $1,000 per month? (Assume the cost of produc�on is constant at $4

per six-pack.) d. What can Fritz Reinhart do to reduce the nega�ve impact of Urquhart’s adver�sing on its quan�ty demanded?

2. The demand func�on for Crispie Chips has been es�mated as follows:

Qx = −27.6887 − 37.73585Px + 44.1177Py + 0.2315Ax

Where Qx represents thousands of packets of chips; Px is the price per packet; Py is the average price per packet of the many other brands of similar chips; and Ax represents thousands of dollars spent adver�sing Crispie Chips. The current values of the independent variables are Ax = 216.0; Px = 0.85; Py = 0.79.

a. Calculate the price elas�city of demand for Crispie Chips and comment on its value. b. Derive an expression for the (inverse) demand curve for Crispie Chips and sketch this on a piece of paper. c. Suppose the cost of producing Crispie Chips is constant at $0.19 per packet. Should they reduce price and produce more (assuming they want to maximize profit)? d. Should Crispie Chips spend more on adver�sing?Processing math: 0%

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e. What assump�ons have you made regarding the reliability of the data and the accuracy of the es�mated demand func�on? 3. Jose Hermanos Tequila (JHT) has conducted an experiment in six different liquor stores that are spread around the suburbs of a major southwestern city, with approximately

similar customers for each store. JHT set different prices in each of the stores for its Hermanos Gold product, as follows, in each case with its product prominently displayed between the two other major tequila brands. Fortunately for JHT’s experiment there were no changes in the prices or promo�on of any other liquor products during the week of the experiment.

Store Price ($) Quan�ty demanded

A B C D E F

19.10 15.70 16.50 21.50 12.90 13.90

17 24 21 10 32 28

a. Sketch the line of best fit represen�ng the demand curve for Hermanos Gold in the typical liquor store in that city. b. What price promises to maximize total revenue (TR) for the JHT company? c. What is the price elas�city of demand at that price?

4. Axton Auto Accessories (AAA) has manufactured a new a product—a high-mounted rear brake light to replace the one that typically sits on the back window shelf of a passenger car. AAA’s product offers several new features, however, such as the ability to scroll messages across the light-emi�ng diode (LED) screen. These prerecorded messages are designed to facilitate communica�on between vehicles, with displays such as "Sorry!"; "Thank You!"; "Please let me in!"; and "This car for sale." The memory of the device can also be loaded (via your computer) with new messages such as your phone number, adver�sements for products, and support for sports teams or poli�cal par�es. This device is about a foot wide, and these messages only scroll across the screen when the vehicle is accelera�ng. The display reverts to bright red when the vehicle is braking, but also offers another innova�on by displaying the word "CAUTION" when the driver li�s his or her foot off the accelerator. Trial marke�ng of the product at different prices for a month in 10 stores of a major auto parts retail company has returned the following data:

Retail store Retail price ($) Quan�ty demanded

1 2 3 4 5 6 7 8 9

10

33.90 25.00 49.98 27.98 37.75 45.90 23.98 31.00 25.50 29.98

2,208 2,682 2,061 2,526 2,158 1,732 2,877 2,312 2,606 2,488

a. Load this price and quan�ty data into columns in an Excel spreadsheet and conduct bivariate regression analysis to determine the demand func�on in the form Qx =

AOV + βPx.

b. Convert the demand func�on to an inverse demand curve expressed in the form Px = a + bQx.

c. At what price level is total revenue (TR) maximized? d. Assuming that the cost of produc�on is constant at $8 and that the auto parts store marks up the wholesale price (its cost) by 100% to arrive at the retail price for its

customers, what wholesale price should AAA set to maximize its profit? 5. The consul�ng firm that you work for has been hired by the U.S. Government to provide an independent analysis of the demand-side effects of a contemplated increase in

the tax on gasoline. It provide you with a data set rela�ng to the period 1962–1987, which contains valuable historic lessons rela�ng to the impact of vola�le pump prices due to the supply restric�ons imposed by the Organiza�on of Petroleum Expor�ng Countries (OPEC) and the Corporate Average Fuel Economy (CAFE) regula�ons that required car manufacturers to increase the fuel efficiency of the cars they sold, while at the same �me Real Disposable Income (RDI) per capita was rising, the number of passenger cars (NPC) almost doubled, and infla�on was pushing up the Consumer Price Index (CPI).

Year QDx Px NPC MPG RDI CPI

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1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1084 1985 1986 1987

43,771 45,246 47,567 50,273 53,312 55,110 58,524 62,448 65,784 69,514 73,463 78,011 74,217 76,457 78,847 80,677 83,233 80,233 73,375 71,718 72,848 73,156 71,180 69,450 71,404 70,984

 20.36  20.11  19.98  20.70  21.57  22.55  22.93  23.85  24.55  25.20  24.46  26.88  40.41  45.44  47.44  50.70  53.09  74.33  104.73  112.75  102.65  95.36  91.46  89.64  63.63  66.33

 66,638  69,842  72,969  76,634  80,106  82,367  85,793  89,156  92,095  96,144  100,658  106,119  109,823  111,679  115,170  118,711  121,717  125,750  127,448  129,123  129,500  131,723  133,751  137,308  140,693  142,209

14.37 14.26 14.25 14.15 14.10 14.05 13.91 13.75 13.70 13.73 13.67 13.29 13.65 13.74 13.93 14.15 14.26 14.49 15.32 15.68 16.36 16.81 17.80 18.28 18.35 19.29

 6,271  6,378  6,727  7,027  7,280  7,513  7,728  7,891  8,134  8,322  8,562  9,042  8,867  8,944  9,175  9,381  9,735  9,829  9,722  9,769  9,725  9,930  10,419  10,662  10,947  10,976

 90.6  91.7  92.9  94.5  97.2 100.0 104.2 109.8 116.3 121.3 125.3 133.1 147.7 161.2 170.5 181.5 195.4 217.4 246.8 272.4 289.1 298.4 311.1 322.2 328.4 340.4

Where: Qx is the gasoline consump�on by passenger cars (in millions of gallons);

Px is the retail (pump) price of gasoline, in cents per gallon;

NPC is the number of registered passenger cars (in thousands);

MPG is the na�onal average of miles travelled per gallon of gasoline;

RDI is Real Disposable Income per capita (in 1982 dollars); and

CPI is the Consumer Price Index (base year 1967).

This data illustrates some very interes�ng issues that were happening over that tumultuous period of our history. You will note that the pump price of gasoline more than doubled five-fold from the mid-1960s to the mid-1970s, and then doubled again in the early 1980s, due to the OPEC crisis. The number of passenger cars climbed relentlessly with the love affair with "muscle cars" despite the increasing pump price of gasoline, and indeed outpacing the increases in real disposable income per capita. The average MPG climbed only slowly as manufacturers increased the fuel efficiency of new cars and consumers slowly traded up to the more efficient new cars and re�red their older vehicles. The changes in CPI show that the rate of infla�on was generally much greater than the rate of increase of pump prices as the increased produc�on and transporta�on costs, due to rising fuel prices, pervaded the en�re economy, pushing up the prices of food and other household items that drive the CPI.

a. Reconcile the fact that while the quan�ty demanded of gasoline and pump prices both rise over this period generally, they are inversely related along a demand curve. b. Conduct a mul�ple regression analysis to explain the quan�ty demanded of gasoline in terms of the other data provided. (Enter this data into an Excel spreadsheet and

use the Excel regression tool, if loaded, or alterna�vely, download an add-in regression program such as Statpro to find the regression sta�s�cs.) c. What propor�on of the variance in Qx is explained by these other variables? What missing variables might account for the remainder of the variance in the quan�ty

demanded of gasoline? d. Use the regression equa�on to predict the quan�ty demanded of gasoline in 1988 for the values Px = 68.5; NPC = 145,885; MPG = 20.36; RDI = 11,192; and CPI = 354.6.

e. What is the 95% confidence interval for your predic�on?

Key Terms

Click on each key term to see the defini�on.

absolute terms (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

An expression meaning that we ignore the nega�ve sign in front of a number, such that we say, for example, that −5 is larger than −4, typically used when dealing with price elas�city values, which are always nega�ve.

autocorrela�on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The dependence of data values in the current period on their value in the preceding period. Autocorrela�on violates an assump�on of regression analysis that the dependent variable is determined by the independent variables alone, not also by its own prior value.

business cycle (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The pa�ern of growth of the macroeconomy, typically with alterna�ng periods of expansion and recession (or at least slower growth rates) with associated fluctua�ons in macroeconomic variables such as interest rates, infla�on rates, and unemployment rates.

coefficient of determina�on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

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A sta�s�c produced by regression analysis that indicates what propor�on of the total variance in the dependent variable (Y) is explained by varia�ons in the independent variables (Xs).

confidence interval (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A range of values around the value of the dependent variable (Y) that is predicted (by the regression equa�on) for par�cular values of the independent variables (Xs), within which range we can be confident that the actual value of Y subsequently observed will fall (for example) 95% of the �me.

consumer clinics (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Ar�ficial shopping environments created by marketers to conduct simulated market situa�ons. Marketers observe the choices of customers, while varying the prices of some products, the shelf placement of products, and point-of-purchase informa�on about product quality, for different groups of shoppers.

contribu�on margin (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The excess of price per unit over average variable costs per unit, which contributes towards the firm’s fixed costs and profit.

cross-adver�sing elas�city (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The rela�ve responsiveness of one firm’s quan�ty demanded to changes in another firm’s adver�sing expenditures. It can be calculated as the percentage change in quan�ty demanded divided by the percentage change in the other firm’s adver�sing expenditures.

demand func�on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The func�onal rela�onship that exists between the quan�ty demanded of a par�cular product (dependent variable) and all determinants of that demand (the independent variables).

demographic change (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Changes over �me in variables such as age cohort size, ethnicity propor�ons, gender balance, geographic distribu�on, and employment type. These changes are likely to affect the demand for products that are consumed more (or less) by a par�cular age, ethnic, gender, regional, or employment group.

dependent variable (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A variable (such as quan�ty demanded in different �me periods) that is dependent on the concurrent values of independent variables (such as price, adver�sing, consumer incomes, and so on).

direct marke�ng (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Directly selling goods and services to consumers through direct marke�ng channels (such as the Internet, mailing campaigns, and telemarke�ng) rather than indirectly via wholesale and retail firms (who interface directly with the consumer).

direct methods (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Demand es�ma�on whereby primary data is collected from actual or poten�al buyers via interviews, surveys, and market experiments.

elas�city of demand (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The rela�ve responsiveness of quan�ty demanded to a change in one of the independent variables that help to determine quan�ty demanded. For example, price elas�city of demand is measured by the percentage change in quan�ty demanded divided by the percentage change in the price level.

es�ma�on of market demand (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A process by which the volume of demand in the current and future periods is es�mated. This process involves gathering and interpre�ng data to provide a numerical es�mate of demand in the current and future �me periods.

heteroscedas�city (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The circumstance where the error terms associated with a regression equa�on vary in a systema�c manner rela�ve to the magnitude of an independent variable, rather than occurring randomly as assumed by the mathema�cs of the regression equa�on. It introduces unreliability into the standard error of es�mate and the coefficient of determina�on.

independent variables (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Variables included on the right-hand side of a regression equa�on because they are expected to exert a determining influence on the dependent variable.

indirect methods (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

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Demand es�ma�on involving the sta�s�cal examina�on of data previously collected for official government sta�s�cs, or found in reports researched and wri�en for other purposes (so-called secondary data).

inverse demand curve (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Expresses price as a func�on of quan�ty demanded for product X, in the form Px = a + bQDx. This form is derived from the demand func�on which expresses quan�ty demanded as a func�on of the various independent variables, including price.

line of best fit (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A line best summarizing the apparent rela�onship between two variables. We should not expect any of the observa�ons to lie exactly on the line of best fit as there are likely to be random varia�ons within the data.

luxury good (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Items for which the quan�ty demanded increases more than propor�onately when consumer incomes increase. For example, income rises 5% and demand for caviar increases 10%.

marginal revenue (MR) (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A measure of how much the total revenue changes when one more unit is sold.

market demand (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The aggregate sum of the quan�ty demanded by all consumers of a par�cular product within a period of �me.

missing variables (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Other determinants (Xs) of the dependent variable (Y) for which data has not been collected or that were not entered into the regression analysis.

mul�collinearity (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The circumstance where the independent variables in a regression equa�on are in fact not independent of each other but instead are significantly correlated with each other. This causes the regression sta�s�cs to be unreliable.

necessity good (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A product that has an income elas�city value that is posi�ve but less than one, meaning that when incomes rise, quan�ty demanded of that product rises but by a lesser percentage than income has risen.

nonprice compe��on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Compe��on among rival firms that does not involve cu�ng price but rather involves the other three Ps of marke�ng, namely product design, promo�on, and place of sales.

ordinary least squares method (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A process that posi�ons the line of the best fit so that it minimizes the sum of the squared devia�ons of the observa�ons from the line. The devia�ons are squared to avoid posi�ve devia�ons offse�ng nega�ve varia�ons and to more heavily weight the larger devia�ons.

price compe��on (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A situa�on among two or more rival firms, where each sets its price in an a�empt to maximize its profits.

price elas�city (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The rela�ve responsiveness of quan�ty demanded to changes in the price level, for a par�cular product. It allows an es�mate of by what propor�on demand is likely to change when an item’s price is increased or decreased by a par�cular propor�on.

quality elas�city (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The rela�ve responsiveness of quan�ty demand to a change in the quality of a par�cular product. It is measured as the percentage change in quan�ty demanded of product X divided by the percentage change in the quality of product X.

regression analysis (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A method of analysis that determines the sta�s�cal rela�onship between a par�cular dependent variable and the independent variables that are expected to determine the value of that dependent variable.

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simultaneous equa�on rela�onship (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Exists when a dependent variable Y depends on X but simultaneously X depends on Z. Thus, a single regression equa�on cannot reliably be es�mated for the dependence of Y on X or Z.

specifica�on error (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

Occurs when the hypothesized func�onal form of the regression equa�on does not reflect the true rela�onship between the variables. Linear regression equa�ons are most commonly used, but some�mes there will be a nonlinear rela�onship (e.g., a quadra�c func�on) between the dependent variable and at least one of the independent variables.

standard error of es�mate (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A measure of the dispersion of the data points from the line of best fit. Using this sta�s�c we can calculate confidence intervals around the predicted value of Y given a set of values for the independent (X) variables.

standard error of the coefficient (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

A measure, for each of the independent variables, of the accuracy of the calculated value of the β coefficient generated by the regression analysis.

total revenue (TR) (h�p://content.thuzelearning.com/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�ons/fm/books/AUBUS640.12.1/sec�o

The combined sum of the revenues collected from all the buyers during a par�cular period of �me. It is equal to the price per unit mul�plied by the number of units sold.

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