Trade Area Analysis Essay

Trade Area Analysis: The Example of Best Buy in Toronto Area
Part A: Trade area delimitation for Best Buy stores
Ten Best Buy stores are shown on the map and have an almost even distribution all over Toronto. However, there is still a higher concentration of the stores in the south-western section of Toronto city, which is more densely populated. Apparently, Best Buy aspires to serve all the customers in Toronto, and this explains the wide area distribution of its stores. Each store is located a relatively far distance away from other stores to avoid overlapping the market, while at the same time covering a larger market area.

Possible new store locations can be identified using the Thiessen polygon technique to Map One. Theoretically, the boundary line vertices are considered as being the best sites for new stores. These locations are recognized as being poorly served areas since the people residing around the areas have to travel fairly long distance to get to a Best Buy store. Moreover, best Buy stores in such locations are less likely to be in competition with Best Buy stores around it. 

Possible new Best Buy stores are identified using little triangles. There are nine locations identified as possible new Best Buy store locations. Of all the locations under consideration, West Site location seems the most unrealistic. Although it is found on the junction of boundaries, it is located exactly where the Pearson International Airport is which has a sparse human population. Opening a new store at this location is not pragmatic as most of the market area will be occupied by the Pearson International airport and so will not have any significant impact on new customers or sales for Best Buy chain. Similarly, the sixth spot falls on the Toronto Zoo and the whole location is covered by green spaces therefore; there is no economic point in opening a new best Buy store at this location. West Site numbers two and three locations are very close to each other so it is more appropriate to choose only one of the sites. On the East Site, location numbers four and five are also located close to each other so only one spot should be chosen as the location for a new Best buy store.

With the two new possible Best buy sites; the South Site and the East Site on the map, market areas for existing new Best Buy stores changes. The stores not affected by the new store locations are Oakville, Woodbridge, Heartland, Bramptch and Ajax. The market areas for Downsview, Sherway, Markham, Leaside and Scarborough will be slashed into smaller areas. As is seen on Map Two, these market areas will become much smaller and more evenly distributed and will result in the capture of more customers. The two sites are both located in the in the vertices of the polygons, which implies that these areas are poorly served by Best Buy. Adding the new stores will make it more convenient for best Buy customers as they will be able to travel shorter distances to reach a store.

Comparing the East and South Sites, it is clear they are both densely populated. Judging from the satellite imagery, most of the people in the area live in houses with both the areas being easily accessible. Although they will cause a shift in the market share, the market areas for the existing and new Best Buy stores will be more even. The present challenge however, is the availability of space for the new proposed stores. The theoretical new store locations are both found inside residential areas. However, expanding the potential areas will enable the location of available suitable spaces to construct new stores. Apart from finding a location to construct the stores, opening new Best Buy stores in the two locations will not result in the “cannibalisation” of the neighbouring stores.

As can be seen from the map, the Fairview Mall store and the downtown store are very close to the two possible new store sites identified in Map One. The two stores are found in the region where customers were originally served poorly. Now the customers will be better off as they will travel shorter distances, while the new store locations will likely capture more customers. However, the two stores are located close to the polygon edge meaning that they may be too close to the neighbouring stores and will likely to compete with each other. 

The smaller polygons show the relatively well served regions, so closing a store in one of these areas with smaller polygons will theoretically not result in significant inconvenience to Best Buy customers. It depends on how far customers will have to travel to access another store after one or some of the stores are closed and how this compares to the distance the customer travelled before closure. In practice, other factors should be put into consideration when deciding to open new stores or close existing ones. For example, it can be tricky to open or close a store when determining the acceptable distance customers have to cover to reach a store. Best Buy stores in reality are not identical such that closing one and opening another will have no effect on consumer preferences. Some customers could prefer using one store to another because of the micro differentiation of each best buy store. Closing a store can also result in Best Buy’s competitors finding an opportunity to set up, resulting in an overall loss of customers.

To efficiently apply the Thiessen polygon technique several assumptions have to be made such as a disincentive to travel long distance as has been assumed in real life. Another assumption is that all the stores are identical to each other. This assumption will work well on the Best Buy store chains as the products in each of the stores are similar in quality and price, while they are similar in size. Although there might be a variation in service in each store, it does not have a significant bearing on the consumers. Consumers are assumed to be economic operators who are fully informed and know all the locations and distances to stores so they make the most rational choices by going to the nearest Best Buy store. For instance, it will be easy for consumers to Google or use mapping software like GPS and find the nearest Best Buy store. Though a having a chain of Best Buy stores fits this model better than others, the method still has downsides to its sue. In reality, stores can never be absolutely identical, information transparency may not exist, and customers may not be as rational as they can be. If Best Buy stores form part of a large shopping area that vary in size, the Thiessen polygon technique will not be very effective. Larger shopping areas have a tendency to attract more customers. The indifference line will be further away from the large shopping areas rather than splitting the market through the middle. This phenomenon is referred to as the gravity model.

Converse breakpoint method takes into account both the distance and size when delimiting market areas. In this method, a formula exists for calculating a breakpoints’ position. Determining the size entails establishing the store area, the employee numbers, and number of parking spaces, among other factors. This model is more suitable since it allows variation in the store sizes. However, this method assumes the existence of a special monopoly in the market area. In reality, market areas commonly overlap so monopolies are rare. This problem can be overcome using the Huff model as it calculates the probability that customers in this area will prefer shop at one of a number of stores, enabling the creation of a map of overlapped market areas.

Part B: Market
Comparison of data in census tracts 0005 and 0061 in the year 2001
The average income for a family in 2000 in census tract 0005 was $39641 that was less by about $4000 than that in 0061. However, the median family income in tract 0005 was just less by $850, which was $32493. This implies that the family incomes had a more even distribution tract in 0061 than that in tract 0005. The employment rate of people aged between 15 and 24 in 0005 was 45.8 per cent, while for people aged over 25 years was 56.3 percent. In tract 0061, the numbers were 54.2 percent and 48.4 percent, respectively. In 0005, 35.9 percent of the families had no children, while 53 percent of the families have between one and two children, and 11 per cent of the families have three children or more. In contrast 0061 had 53.8 percent of families having no children, 37.5 percent have two children or less and no family had more than three children.

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