The Central Place theory describes the central places the center of commerce of a village, town or city which comprises of a cluster of retail organizations. In this theory, two important concepts are presented – the range and the threshold. The range is the maximum that consumer is willing to travel for a particular product or service and the threshold is the minimum amount of consumer demand that must exist for a store to survive. Technically, the range should be greater than the threshold for a store to be economically viable.
The needs of the groups of consumers residing in a particular location, dictate the needs of retail development. Thus, this theory implies that all consumer groups or areas are not able to support all types of retail activities. The level of development tells a retailer about which type of retail activity is likely to develop in that area in the future.
Huff’s Model of Trading Area Analysis:
David Huff introduced this model in 1963. Its popularity and longevity can be attributed to its conceptual appeal, relative ease and applicability to a wide range of problems, of which predicting consumer spatial behavior is the most commonly known. The probability (Pij) that a consumer located at i will choose to shop at store j is calculated according to the following formula:
Pij = A αj Dij –β / Σ Aj α –Dij–β
Aj is a measure of attractiveness of store j, such as square footage.
Dij is the distance from i to j
α is an attractiveness parameter estimated from empirical observations
β is the distance decay parameter estimated from empirical observations
n is the total number of stores including store j.
The quotient received from dividing Ajα by Dijβ is known as the perceived utility of store j by a consumer located at i. The α parameter is an exponent to which store’s attractiveness value is raised, and enables the user to account for the non linear behavior of the attractiveness variable. The β parameter models the rate of decay in the drawing power of the store, as potential customers are located further away from he store. Increasing the exponent would decrease the relative influence of a store on more distant customers.
The theories of market identification provide a broad framework for identifying the attractiveness of the market. A common practice by many international retailers is to use various softwares available in the market, for determining the location of the store.
MapInfo Helps TESCO to make sound Business Decisions for World Wide Brand Building
In the 1990s, Tesco started to expand its operations outside the UK. In Eastern Europe, it has met growing consumer aspirations by developing stores in Poland, Hungary, Slovakia and the Czech Republic. It has also expanded into Taiwan, Thailand and South Korea.
MapInfo’s software has played a vital role in helping the organization to penetrate these markets ensuring that stores are located in the right places to attract profitable customers and serve the precise needs of the local community. It is currently being used to assess opportunities in China and Japan and is an invaluable tool in the development of Tesco’s global strategy.
Tesco has 35 licenses and uses MapInfo’s core business mapping software MapInfo Professional and MapInfo Drive time, which creates maps showing drive time catchment boundaries and other MapInfo market analysis solutions.
The MapInfo software is used to support site location outside the UK and has already proved to be a vital part of the planning process in the opening of the stores in Eastern Europe and Asia. By utilizing location based software. Tesco is helping to minimize capital expenditure risks that are associated with moving into previously unexplored markets.
MapInfo was selected because of its portability ease of use the fact that it requires minimal technical support and training. The software can simply be loaded on a desktop computer on any country and, with a minimal amount of training can be used immediately. It can be linked into wealth of data type and used in the field by anybody within the team.
Tesco mainly uses MapInfo as a mapping intelligence tool to help understand the demographics and topology of an area so that it can establish the best location to place the stores. As it moves into relatively untracked regions, it is essential that the company gets to grips with what people want out of a tore, how easy it is for them to get to and from a particular site and meet different cultural requirements. It also allows the company to see where other competitive outlets are situated and how they may affect its profitability.
MapInfo’s drive time product has allows Tesco to generate catchment maps around proposed sites, allowing them to see how many customers they are likely to attract and how they would travel to that site. As a consequence, modeling strategies can be increased in sophisticated. For example, prospective customers may only be a few mile from the store, but it may take them an extremely long time to reach it because of the existing road network and transport infrastructure. Using the software, Tesco can quickly and easily find out if an alternative site might attract more relevant customers.