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Products, Services, and Prices in the Free Market Economy: Price Elasticity of Demand

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Domino’s Pizza, Inc

In 1960 Tom Monaghan and his brother James bought DomiNicks, a pizza store in Ypsilanti, Michigan. In 1965 the company name was changed to Domino’s Pizza. Domino’s Pizza is one of the leading companies in the pizza delivery industry in the United States and around the world. The company headquarters is located in Ann Arbor, Michigan and they employ approximately 13,500 people. Total revenue was registered at $1,511.6 million during the fourth quarter of 2005, a growth of 4.5% over 2004. The performance gain of the company was $199.1 million during the fiscal year of 2005, a growth of 16.2% over 2004. The pure gain was $108.3 million in the fiscal year of 2005, a growth of 73.8% over 2004.

Domino’s enterprise performs through three sections: domestic dispersion, domestic stores, and global. The domestic dispersion section process dough and disperses food and supplies through 17 dough processing and dispersion centers to all the domestic company owned stores and over 98% of the home contract stores. The domestic stores section is composed of 4,511 contracted stores and 581 company owned stores. These contracted stores are enforced by industrialists who own and keep an average of three to four stores. The global section supervises 2,980 contracted stores and keeps seven company owned stores apart from the United States. The global section also disperses dough and process food and supplies in a controlled number of global venues.

The organization’s primary products include pizzas, beverages, desserts branded merchandise, and side items (bread sticks, buffalo wings and others). The company shines with its home delivery service.

This paper will show how Domino’s Pizza can increase or decrease its revenue by using price elasticity of demand and will discuss interpretations of elastic demand, inelastic demand and unit elasticity. Furthermore, this paper will show how determinants of price elasticity of demand affect decisions by analyzing substitutability and proportion of income and time. The determination of how to increase or decrease revenue is thoroughly investigated before implementation of any actions.

Price Elasticity Coefficient

Learning Team A used the hypothetical data for pizza in Table 1 to plot the demand curve in Figure 1 and the total revenue curve on Figure 2. For each reduction of $1 in the price of pizza Learning Team A assumed a 25% increase in the total quantity of pizzas demanded per month. The curve illustrates that even though no percentage change in price and the resulting percentage change in quantity demanded were the same, a price of $7 per pizza will produce the highest revenue.

The relation between price elasticity of demand for pizza and total revenue shows that the monthly demand for pizza is elastic at higher price ranges and inelastic at lower price ranges. When price falls from $10-$8 total revenue increases from $20-$24 million, meaning demand is elastic. When price falls to $7 per pizza total revenue reaches $24.5 million, which means demand is the closest to unit-elastic and revenue is at its highest. Finally when price falls below $7 total revenue declines, which means demand is inelastic.

Table 1

Domino’s Pizza

Total Quantity of Pizzas Demanded per Month Price per Pizza Elasticity Coefficient Total Monthly Revenue Total Revenue Test

2,000,000 $10 2.23 $20,000,000 Elastic

2,500,000 $9 1.63 $22,500,000 Elastic

3,000,000 $8 1.21 $24,000,000 Elastic

3,500,000 $7 0.91 $24,500,000 Inelastic

4,000,000 $6 0.68 $24,000,000 Inelastic

4,500,000 $5 0.50 $22,500,000 Inelastic

5,000,000 $4

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