Jun Liang, Geography @ UNC Lecture 20 Huff Model – A probabilistic Analysis of Shopping Center Trade Area 20-1 Introduction William J. Reilly – Applying.

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Jun Liang, Geography @ UNC Lecture 20 Huff Model – A probabilistic Analysis of Shopping Center Trade Area 20-1 Introduction William J. Reilly – Applying the gravity concept to retail trade area analysis: Purpose is to determine the relative retail pulling power of two competing cities on an intervening area. Hypothesis: Two cities attract retail trade from an intermediate city or town in the vicinity of the breaking point approximately in direct proportion to the populations of the two cities and in inverse proportion to the square of the distances from the two cities to the intermediate town. 2018/11/15 Jun Liang, Geography @ UNC

Jun Liang, Geography @ UNC 20-1 Introduction (Cont.) The mathematical expression of Reilly’s hypothesis is as follows: 2018/11/15 Jun Liang, Geography @ UNC

Jun Liang, Geography @ UNC 20-1 Introduction (Cont.) An example of Reilly’s model: B A X 20 miles 30 miles Pop:100000 Pop:200000 The percentage of the population of town x attracted to city A is 53%, to city B is 47%. 2018/11/15 Jun Liang, Geography @ UNC

Jun Liang, Geography @ UNC 20-2 Breaking Point In 1947, the Curtis Publishing Company adopted Reilly’s formula to calculate the break point between two cities. Such a boundary line, where Ba=Bb, represents the dominant trading areas for city A and B. 2018/11/15 Jun Liang, Geography @ UNC

20-2 Breaking Point (Cont.) An example of this formulation: Break Point from B is 33.3 miles. B A 80 miles Pop:200000 Pop:400000 2018/11/15 Jun Liang, Geography @ UNC

20-3 Shopping Center Breaking Point The modified Reilly’s formulation has also been used to estimate trading areas of proposed shopping center within cities. Generally, the square footage of each retail center is substituted for population and travel time between retail centers is substituted for physical distance. See Table-1 for a hypothetical example. 2018/11/15 Jun Liang, Geography @ UNC

20-3 Shopping Center Breaking Point (Cont.) Table 1 – Hypothetical Data Used in Delineating Trading Area of Proposed Shopping Center Shopping Center Sq. Footage of Selling Space Travel Time From A Breaking Point From Shopping Center to A A 200000 B 100000 15 6.2 C 150000 20 9.3 D 50000 10 3.3 E 3000000 25 13.8 2018/11/15 Jun Liang, Geography @ UNC

20-3 Shopping Center Breaking Point (Cont.) Limitation of Gravity Model The calculation of breaking points to delimit a retail trade area conveys an impression that a trading area is a fixed boundary circumscribing the market potential of a retail facility. Distance exponent is a variable (ranged from 1.5 to over 3 – depending on the trip type as well as other factors.) Possesses very little theoretical content. 2018/11/15 Jun Liang, Geography @ UNC

Jun Liang, Geography @ UNC 20-4 Huff Model How huff improves Reilly’s model: Will utilize the conceptual properties of the gravity model Focus on the consumer rather than on the retail firm. Measuring a Shopping Center’s Utility: The number of items of the kind a consumer desires that are carried by various shopping centers The travel time that is involved in getting from a consumer’s travel base to alternative shopping centers. 2018/11/15 Jun Liang, Geography @ UNC

Jun Liang, Geography @ UNC 20-4 Huff Model (Cont.) The probability of a consumer at a given point of origin I traveling to given shopping center j can be described: 2018/11/15 Jun Liang, Geography @ UNC

20-5 An example of Huff Model Five steps: Divide the area into small statistical unit. Determine the square footage of retail selling space of all shopping centers included within the area of analysis. Compute travel time. Calculate the probability of consumers in each unit going to the particular shopping center. Map the trading area of the shopping center in question by drawing lines connecting all statistical units having like probabilities. 2018/11/15 Jun Liang, Geography @ UNC

20-5 An example of Huff Model (Cont.) 6. Calculate the number of households within each of the statistical units. Then multiply each of these figures by their appropriate probability values to determine the expected number of consumers. 2018/11/15 Jun Liang, Geography @ UNC

20-5 An example of Huff Model (Cont.) 7. Determine the annual average per household incomes of each of the statistical units. Then calculated the expected annual sales potential for shopping center j with respect to a given product class from each of the statistical units. 2018/11/15 Jun Liang, Geography @ UNC

20-6 An example of Huff Model (Cont.) We may also incorporate additional variables, such as the average number of shopping trips that consumers make with respect to various types of product purchases within particular time period. 2018/11/15 Jun Liang, Geography @ UNC

20-6 An example of Huff Model (Cont.) 2018/11/15 Jun Liang, Geography @ UNC