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Combine with census tract identify the primary rst 60

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Unformatted text preview: he store, it is possible to estimate the level of penetration into each neighborhood. • Combine with Census Tract • identify the primary (first 60%) and secondary market (next 25%) 3.3 • • • • • 4 4.1 Relevant Concepts Distance decay, friction of distance Disincentive nature of distance Location and Competition (Hotelling) Utility (distance, size, attraction) Unifying/Simplifying assumptions Site Selection Techniques Seven Methods Top ⇒ Down : Qualitative ⇒ Quantitative c D. Wang & C.Zhao, 2006 8 5 1. 2. 3. 4. 5. 6. THE GEOGRAPHY OF DEMAND: THE MARKET Rule of Thumb: intuition, experience, observation, “gut feeling” Descriptive inventories: checklist of key factors, which site has the most? Ranking: rank sites on the basis of key factors thought to be most important Ratios: sales/population, sales/store, etc. Analogues: Duplication of existing well performancing sites (follow the leader) Location Allocation: best set of sites to service existing population • more likely found in public services, like hospitals 7. Regressive Models • Only include if statistics verified. • Verification of relevance of factors • Simple Regression • Multiple Regression 4.2 Concept of Regression Simple Regression the association between two variables (one dependent and one independent) Regression coefficient intuitive and counter-intuitive variables positive and negative association 4.3 Site Evaluation Using Multiple Regression Dependent Variable Definition: This variable changes as other variable changes Independent Variable Definition: This variable does not change as other variable changes Multiple Regression Definition: the relationship between a dependent variable ($ sales) and several site and situational variables (independent variables: e.g. population, household) How to Apply Regression Analysis 1. For a set of existing sites, need data on sales and potential independent variables 2. Isolated key factors, the individual association of independent variables 3. Develop/Calibrate the regression model Example: central city sites: car accessability is negative related to sales (counter intuitive) Because • More competitors...
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