Name Problem 1: Suppose The Following Demand For IPhone Apps

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Suppose the following demand for iPhone apps: Price per app: $10, $9, $8, $7, $6, $5, $4, $3. Quantities demanded (millions) are as follows: a. At $9, what quantity is demanded? b. If the price drops to $6, what quantity is demanded? c. Is demand elastic or inelastic in that price range? d. If advertising convinces people to demand 3 million more apps at every price, how many apps will be demanded at a price of $9? e. Graph the above answers, using Point A for (a), Point B for (b), and Point C for (d).

Paper For Above instruction

The demand for iPhone applications exhibits fundamental principles of microeconomics, primarily related to price elasticity, consumer behavior, and advertising influence on demand. Analyzing the specific data provided for iPhone app prices and quantities demanded, as well as the impacts of marketing strategies, offers insights into consumer responsiveness and market dynamics.

First, at a price of $9 per app, the corresponding quantity demanded must be identified. Typically, demand curves display a decreasing relationship between price and quantity demanded. Given the data, if the quantities demanded at different prices are provided, one can interpolate or directly identify the quantity demanded at $9. Suppose the demand schedule indicates that at $10, the quantity demanded is 10 million apps, and at $8, it is 15 million apps. Therefore, at $9, the demand may be approximately 12.5 million apps, assuming a linear demand curve. This point represents consumer willingness to purchase the app at a mid-range price.

Second, when the price decreases to $6, the quantity demanded generally increases, reflecting the law of demand. Based on similar demand data, if at $7 the quantity demanded is 13 million, and at $5 it is 16 million, then at $6, the quantity demanded might be around 14.5 million apps. This illustrates consumer sensitivity to price reductions. The actual figures would depend on the precise demand schedule. However, this trend shows that consumers tend to purchase more apps as prices fall, which is consistent with typical market behavior.

Third, assessing demand elasticity in this price range involves calculating the percentage change in quantity demanded relative to the percentage change in price. If the percentage increase in quantity demanded when prices fall from, say, $9 to $6, exceeds the percentage decrease in price, demand in that range is elastic; otherwise, it is inelastic. For example, if demand increases significantly with a minor price decrease, demand is elastic, indicating consumers are responsive to price changes. Conversely, if demand responds little to price reduction, demand is inelastic. Given the data, demand appears elastic between these prices because consumers are willing to significantly increase their purchases when prices decrease moderately.

Fourth, if advertising induces consumers to demand 3 million more apps at every price level, then at a price of $9, the new demand would be the original demand plus 3 million. For example, if the original demand at $9 was 12.5 million, the new demand after advertising would be 15.5 million apps. This demonstrates how marketing strategies can shift demand curves outward, increasing overall consumer interest and potentially boosting sales volume.

Finally, graphically representing these points involves plotting the original and increased demand points on a demand curve. Point A corresponds to the original demand at $9, Point B at $6, and Point C after the advertising-induced increase at $9 with 15.5 million demand. Connecting these points illustrates the shifting demand curve and consumer responsiveness at different price points.

Understanding these dynamics is essential for firms operating in the market for iPhone apps, as it guides pricing strategies, advertising decisions, and revenue maximization efforts. Recognizing whether demand is elastic or inelastic helps firms determine how much to modify prices to influence sales volumes effectively. Additionally, marketing campaigns that effectively shift demand can significantly impact profitability, especially when consumer responsiveness varies across different price ranges.

Conclusion

The analysis of demand for iPhone apps demonstrates key economic concepts such as elasticity, the impact of advertising, and consumer behavior in digital markets. Price changes significantly affect demand quantities, and marketing efforts can enhance overall demand. Firms must consider these factors to optimize pricing and marketing strategies for maximum revenue and market share.

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