This case study "Soft Drink Demand Estimation" delves into the factors affecting the soft drink consumption and the ways to enhance its sales. It likewise looks into the factors positively or negatively affecting demand and sales.
James R. McGuigan; R. Charles Moyer; Frederick H.deB. Harris
Cengage Learning (14th Edition)
September 26, 2016
Case questions answered:
- Estimate the demand for soft drinks using a multiple regression program on your computer.
- Interpret the coefficients and calculate the price elasticity of soft drink demand.
- Omit price from the regression equation and observe the bias introduced into the parameter estimate for income.
- Now, omit both price and temperature from the regression equation. Should a marketing plan for soft drinks be designed that relocates most canned drink machines into low-income neighborhoods? Why or why not?
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Soft Drink Demand Estimation Case Answers
This case solution includes an Excel file with calculations.
Soft Drink Demand Estimation
The soft drink industry is a large industry that deals with a wide variety of product lines ranging from carbonated soft drinks, sports drinks, bottled water, and fruit beverages. The major players and powerful brands in the soft drink industry are Coca-Cola (Coke), Pepsi, and Snapple, with Coca-Cola being the leading manufacturer, marketer, and distributor of soft drinks syrups and concentrates.
The U.S. soft drinks market size is anticipated to reach USD 388.4 billion by 2025. It is projected to post a compound annual growth rate (CAGR) of 5.1% during the forecast period. This growth in the industry is attributed to the easy availability and low price of soft drinks benefiting the growth of the market. (Source: www.grandviewresearch.com).
Industry Earnings: (Source: Change lab beverage report, 2012-www.changelabsolutions.org)
Soft Drink Manufacturing Industry
Soft drink manufacturing -is a $47·2 billion manufacturing industry in the United States based on revenue. It was forecast to generate a profit of $1·7 billion in 2010. The industry’s annual growth was 1·8% from 2005 to 2010, and it is expected to maintain this growth rate between 2010 and 2015.
Flavoring Syrup and Concentrate Manufacturing Industry
Flavoring syrup and concentrate manufacturing is an $8 billion industry in the United States based on revenue. It was forecast to generate a profit of $1·4 billion in 2010. The industry’s annual growth rate declined by 1·4% from 2005 to 2010 but is expected to increase by 0·8% from 2010 to 2015.
Soft drinks- North America
Revenue in the Soft Drinks segment amounted to US$112,515m in 2018. The market is expected to grow annually by 1.3% (CAGR 2018-2021). In global comparison, most revenue is generated in the United States (US$98,583m in 2018.). In relation to total population figures, per-person revenues of US$ 226.35 were generated in 2018. The average per capita consumption stood at 167.5L in 2018. (source: www.statista.com)
Carbonated Soft Drinks
45% of industry revenues come from well-known brands such as Coke and Pepsi sold in supermarkets and discount chains. In 2015, Coca-Cola carbonated soft drink market share amounted to 42.5%.
Key problems
Factors affecting the soft drink consumption (demand)
It is important to understand what aspects influence the consumption of soft drinks because it helps in finding ways to improve consumption. Knowing their level of demand and the determinants in the market is the most critical thing if a company wants to enhance sales in the long run. Proper analysis of demand and annual sales forecasting is key to improving production and general growth in this industry.
Examining the determinants of demand, such as prices, income levels, consumers’ tastes and preferences, and availability of substitutes, shows how demand and sales are affected either positively or negatively.
Determinants of demand- Analysis of demand
Prices of Soft drinks
Price determination in the market is important – the amount that both buyers and suppliers are willing to exchange for the commodity. Price elasticity of demand shows the measure of the responsiveness of quantity demanded of a good to changes in prices. Based on the case, the demand for soft drinks is price elastic, meaning an increase in price will lead to a decrease in the quantity demanded, and a decrease in prices result in an increase in the quantity demanded.
The price elasticity of demand for soft drinks is (-1.98); therefore, a 1.98% increase in prices leads to a 1.98% decrease in the quantity demanded – there is a negative relationship between the prices and quantity demanded.
Demand function- Q=164.55-155.95P+2.54Y+5.305F
A unit increase in price will result in a 155.95 decrease in the quantity demanded for annual cans per capita consumption.
Income per Capita of consumers
Consumer disposable income affects demand as a fall in the prices of normal goods increases consumers’ real income, making them more able to purchase goods.
The income elasticity of demand from the case study calculation is (0.28), so the demand for soft drinks is income elastic, and as consumers’ income increases, the demand increases as well.
There is a positive direct relationship between consumer’s income and the number of soft drinks the consumers are willing to buy.
Demand function- Q=264.32-4.69Y
On the other hand, when prices are omitted, the demand function is Q=264.32-4.69Y, resulting in a negative income elasticity (-4.69), which makes the soft drinks a type of inferior good meaning an increase in income will lead to a decrease in demand for soft drinks.
Consumers taste and preferences & availability of substitutes
Another factor affecting the demand for soft drinks is the change in tastes and preferences. Many consumers are now concerned about health, and their consumption habits have changed over time. This lowers the demand for other soft drinks, such as sodas, and increases demand for others, like bottled water and organic drinks.
Best demand equation-demand function
I think the best equation that describes the demand for soft drinks is equation one Q=164.55-155.95P+2.54Y+5. 305F.This best shows the relationships between the variables based on running the linear regression, such as the prices.
As the prices increase, the annual sales will decrease by 155.95, and as income increases, the sales will increase by 2.54, and as the temperature increases, the demand for soft drinks increases. It clearly depicts a linear relationship between the variables and calls for a cause of action in case of any important decisions to be made by a company.
Methodology of multiple linear regression
Analysis of the case or running a linear regression using multiple linear regression helped in explaining the relationships between the dependent and independent variables (Cans per capita, prices, income per capita, and temperature). Price is the independent variable, and cans (quantity, income, and temperature are the dependent variables.
Based on the demand equations- Q=164.55-155.95P+2.54Y+5.305F and Q=264.32-4.69Y and Q=195.31+0.164Y+6.34F, we see the strength of effect that the independent variable (price) has on dependent variables.
It also helps us to understand how much the dependent variables will change when the independent variable is omitted from the equation. For instance, when the price is removed from the equation Q= 195.31+0.164Y+6.34F, the value of R-square is reduced, and for the equation Q=264.32-4.69Y, it shows some biases with income.
Recommendation
From the demand equation Q=164.55-155.95P+0.164Y+6.34F, soft drink consumption can be improved by decreasing the prices charged for every soft drink. When this is done, the quantity demanded will go up, consumers’ income will increase, hence increased quantity, and finally, an increase in the total revenue.
Again, most of the soft drinks vending machines should be in major population areas like cities and shopping centers because demand is highest in those areas.
Additional File:
Excel Spreadsheet. Download here.
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