Buying Power Index - Explained
What is the Buying Power Index?
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Table of ContentsWhat is the Buying Power Index?How does the Buying Power Index Work? Consumer Buying Power and InflationConsumer Price IndexManufacturing and Consumer Buying PowerAcademic Research on Buying Power Index
What is the Buying Power Index?
The Buying Power Index is a tool used by retailers to assess the purchase power or buying power of a region over another. When retailers have the opportunity of selling their products in different locations, before selecting which location is most profitable, they use the buying power index. This will help determine the success of a location over another and vice versa. The buying power index uses a mathematical formula based on three important elements that determine the success or otherwise of a particular market region. These are the market population or size, the effective buying income and the retail sales of the location.
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How does the Buying Power Index Work?
The Buying power index will be estimated using the following equation; Buying Power Index = 0.5 (markets percentage of U.S. effective buying income) + 0.3 ( market's percentage of U.S. retail sales) + 0.2 (the market's percentage of U.S. population). The above three basic elements population, retail sales and effective buying income are used in measuring the buying power index of market regions. The degree of these three elements vary from one geographical region to another, the retailer must evaluate these to determine which region will be more profitable. For example, a region filled with people who have the financial resources (personal income) have buying power but this alone is not enough. The market population and retail sales are to be weighted as well.
Consumer Buying Power and Inflation
Economic factors such as inflation and deflation affect consumer buying power and the overall buying power index of a region for a specific time. Inflation has negative impacts on the economy, the real value of money is decreased, therefore, the value of consumer's personal income will also be affected, wages and the overall value of the nations currency will retrograde. Deflation also affects the purchase power of consumers as well as the value of debt in the market. In a period of inflation, the prices of goods will rise and the amounts of goods that can be purchased with the personal income will decrease. Consumers will be able to buy fewer goods. However, increase in wages and stability in prices of goods men that consumers have more to buy more goods.
Consumer Price Index
The consumer price index estimates changes in the price level of a basket of consumer goods and services that households purchase. It measures the weighted average of prices of a basket of consumer goods and services. The basket consists of 8 items. The statistics of changes in prices of goods such as transportation, beverages, food, medical care and others that different household and labor force segments can purchase is presented. A change in the price of goods and services also suggest a change in consumer buying power. Both positive and negative changes in prices affect consumer buying power. If the prices of goods reduce, consumers can buy more, uif the prices increase, they buy less.
Manufacturing and Consumer Buying Power
The consumer buying power is also affected by production or manufacturing processes. If affordable goods are manufactured, consumers are able to purchase as much as they can based on their income, howner, if goods manufactured are too expensive, there will be a restraint on the part of the consumers, they are unable to afford the products and purchase less. However, it is important that manufacturers know the purchasing power of different markets, while consumers in some markets can afford expensive products, consumers in another market might not be able to afford this. Hence, manufacturers must produce products that suit the buying power of different markets.
Academic Research on Buying Power Index
- Purchasing power at the bottom of the pyramid: differences across geographic regions and income tiers, Guesalaga, R., & Marshall, P. (2008). Journal of Consumer Marketing, 25(7), 413-418.
- The measurement of monopsony power, Blair, R. D., & Harrison, J. L. (1992). The Antitrust Bulletin, 37(1), 133-150.
- Cooperative Buying, Monopsony Power, and Antitrust Policy, Blair, R. D., & Harrison, J. L. (1991). Nw. UL Rev., 86, 331.
- Buyer power and its impact on competition in the food retail distribution sector of the European Union, Dobson, P. W., Clarke, R., Davies, S., & Waterson, M. (2001). Journal of Industry, Competition and Trade, 1(3), 247-281.
- Wal-Mart's monopsony power in metro and non-metro labor markets, Bonanno, A., & Lopez, R. A. (2012). Regional Science and Urban Economics, 42(4), 569-579.
- Monopsony Revisited: A Comment on Blair & Harrison, Jacobson, J. M., & Dorman, G. J. (1992). The Antitrust Bulletin, 37(1), 151-169.
- Price-based Techniques for Market Definition & Buying Power Index, Fotis, P. N. (2012).
- The impact of a customer service intervention and facility design on firm performance, Sulek, J. M., Lind, M. R., & Marucheck, A. S. (1995). Management Science, 41(11), 1763-1773.
- How to win spend and influence partners: Lessons in behavioral operations from the outsourcing game, Amaral, J., & Tsay, A. A. (2009). Production and Operations Management, 18(6), 621-634.
- Economic Tools for Merger Appraisal: A Theoretical and Empirical Standpoint, Fotis, P. N. (2014). Journal of Reviews on Global Economics, 3, 24-32.
- Retail location decision making using a market potential approach: A group project, Darian, J. C. (1988). Journal of Marketing Education, 10(2), 79-84. In the project, each student group chooses a particular type of store and constructs an index of market potential to help choose a new location for the store. In addition to gaining experience in making decisions based on limited information, students also are exposed to online data bases and gain practice using Lotus 1-2-3
- Determining business models in bottom-of-the-pyramid markets, Jun, S., Lee, D., & Park, J. (2013). Industrial Management & Data Systems, 113(7), 1064-1082.