berman ch 09 11e
TRANSCRIPT
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9-1Retail Mgt. 11e (c) 2010 Pearson Education, Inc. pu blishi ng as Prentice Hall
Trading-Area
Analysis RETAILMANAGEMENT:A ST RAT EGIC
APPROACH 11th Edition
BERM N EV NS
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Chapter ObjectivesTo demonstrate the importance of store location for aretailer and to outline the process of choosing a store
locationTo discuss the concept of a trading-area and its relatedcomponentsTo show how trading-areas may be delineated for
existing and new storesTo examine three major factors: populationcharacteristics, economic base characteristics, andcompetition/level of saturation
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9-3Retail Mgt. 11e (c) 2010 Pearson Education, Inc. pu blishi ng as Prentice Hall
Location, Location, LocationCriteria to consider include
population size and traits
competitiontransportation accessparking availabilitynature of nearby storesproperty costslength of agreementlegal restrictions
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Figure 9-1: Location and Nine West
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9-5Retail Mgt. 11e (c) 2010 Pearson Education, Inc. pu blishi ng as Prentice Hall
Choosing a Store Location
Step 1: Evaluate alternate geographic (trading)areas in terms of residents and existing retailers
Step 3: Select the location type
Step 2: Determine whether to locate as anisolated store or in a planned shopping center
Step 4: Analyze alternate sites contained in thespecific retail location type
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Trading-Area Analysis
A trading-area is a geographicarea containing the customersof a particular firm or groupof firms for specific goods or
services.
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Benefits of Trading-Area Analysis
Discovery of consumerdemographics and
socioeconomiccharacteristicsOpportunity todetermine focus ofpromotional activitiesOpportunity to viewmedia coveragepatterns
Assessment of effects oftrading area overlap
Ascertain whether chainscompetitors will opennearbyDiscovery of ideal
number of outlets,geographic weaknessesReview of other issues(e.g. transportation)
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Figure 9-2: The Trading-Areas of Current andProposed Outlets
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GIS Software
Geographic Information SystemsDigitized mapping with key location-specific
data used to graphically depict trading-areacharacteristics such as
population demographicsdata on customer purchases
listings of current, proposed, and competitorlocations
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Figure 9-3(A): GIS Software in Action
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Figure 9-3(B): GIS Software in Action
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Figure 9-3(C): GIS Software in Action
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Figure 9-3(D): GIS Software in Action
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Figure 9-4: The Segments of a Trading-Area
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Figure 9-5: Delineating Trading-Area Segments
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The Size and Shape of Trading-Areas
Primary trading-area
50-80% of a stores customersSecondary trading-area15-25% of a stores customers
Fringe trading-area all remaining customers
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Destination Versus Parasite Stores
Destination stores have a better
assortment,promotion, andimage.They generatetrading-areas muchlarger thancompetitors.Dunkin Donuts: Its worth the trip!
Parasite stores do notcreate their own traffic
and have no realtrading-area of theirown.These stores depend onpeople who are drawnto area for otherreasons.
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Trading Areas and Store Types
Largest
TRADINGAREAS
Smallest
Department stores
Supermarkets
Apparel stores
Gift stores
Convenience stores
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The Trading-Area of a New Store
Different tools must be used when an area is
evaluated in terms of opportunities rather thancurrent patronage and traffic patterns:Trend analysisConsumer surveys
Computerized trading-area analysis models
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Computerized Trading-Area Analysis Models
Analog Model
Regression Model
Gravity Model
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Reillys Law
Reillys law of retail gravitationatraditional means of trading-area
delineationestablishes a point ofindifference between two cities or
communities so that the trading-area ofeach can be determined.
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Limitations of Reillys Law
Distance is only measured by majorthoroughfares; some people will travel shorterdistances along cross streets.Travel time does not reflect distance traveled.Many people are more concerned with timetraveled than with distance.
Actual distance may not correspond withperceptions of distance.
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Huffs Law
Huffs law of shopper attraction
delineates trading-areas on the basis ofproduct assortment at various shoppinglocations, travel times from the
shoppers home to alternative locations,
and the sensitivity of the kind ofshopping to travel time.
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Table 9-1a: Chief Factors to Consider in Evaluating
Retail Trading-Areas
Total size and density Age distribution Average educationallevelPercentage ofresidents owninghomes
Total disposableincomePer-capita disposableincome
OccupationdistributionTrends
Population Size and Characteristics
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Table 9-1b: Chief Factors to Consider in Evaluating
Retail Trading-Areas
ManagementManagement traineesClerical
Availability of Labor
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Table 9-1c: Chief Factors to Consider in Evaluating
Retail Trading-Areas
Delivery costsTimelinessNumber ofmanufacturers
Number of wholesalers Availability of productlinesReliability of product
lines
Closeness to Sources of Supply
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Table 9-1d: Chief Factors to Consider in Evaluating
Retail Trading-Areas
Dominant industryExtent ofdiversificationGrowth projections
Freedom fromeconomic andseasonal fluctuations Availability of creditand financial facilities
Economic Base
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Table 9-1e: Chief Factors to Consider in Evaluating
Retail Trading-Areas
Number and size ofexisting competitionEvaluation ofcompetitor strengthsand weaknesses
Short- and long-runoutlookLevel of saturation
Competit ive Situation
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Table 9-1f: Chief Factors to Consider in Evaluating
Retail Trading-Areas
Number and type ofstore locations Access totransportation
Owning versus leasingopportunitiesZoning restrictionsCosts
Availability of Store Locations
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Table 9-1g: Chief Factors to Consider in Evaluating
Retail Trading-Areas
TaxesLicensingOperations
Minimum wagesZoning
Regulations
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Elements in Trading-Area Selection
PopulationCharacteristics
Economic BaseCharacteristics
Nature and Saturationof Competition
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Figure 9-9: The Census Tracts of
Long Beach, NY
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Table 9-3: Selected Population Statistics forTrading Areas A and B
Characteristics Area A Area B
Total population, 2000 13,732 15,499
Population change, 1990-2000 +8.2 +2.5
College graduates, 25 +, 2000 (%) 41.4 39.2
Median household income, 2000 $61,236 $61,242
Managerial and professionaloccupations (%), 2000 45.3 45.0
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