Store Location:Evaluation and Choice Based on

Geographical Consumer Information

Auke HunnemanTammo H.A. Bijmolt

J. Paul Elhorst

University of GroningenThe Netherlands

ERSA Summerschool in Regional Science4-12 July, 2006

2

Importance of Store Location

• For many consumers, store location is a key factor driving store choice.

• Store location determines the trade area.

• Store location is a source of competitive advantage.

• The decision is almost irreversible costs of mistakes are high.

• Changing environment experience becomes a less reliable guide.

• Competition importance of growth.

3

Situation:Chain of Stores with Many Outlets

Important issues:

1. Performance of current outlets

2. Site selection for new outlets ?

4

Modeling Framework

1. Current outlets: Determine impact of drivers of store performance (characteristics of customers, outlet, and market/competition)

2. Copy relationships found in stage 1 to new sites to determine potential performance.

5

The Conceptual Framework

Store Characteristics, including:LocationComposition

Consumer Characteristics, including:GeodemographicsNumber of households

Market Characteristics, including:Number of competitorsRetail activity

Store PerformanceExisting storesNew stores Main and Interaction

effects

6

Which Consumers?

= Trade area

Our approach:

We use a distance measure to include all zip code areas that are within a 10 miles driving distance to the store

Store

7

The Model (1)

Van Heerde & Bijmolt (JMR 2005):Total sales of a store i in period t can bedecomposed into• Sales to loyalty card holders• Sales to other customers

ititit SNSLS

itSNitSL

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The Model (2)

Sales to loyalty card holders can be furtherdecomposed into:

ijtijtjt

J

jjt

J

jijtit EPNVPRNHSLSL

ii

***11

i: Store

j: Zip code

t: Time period

jtNH

jtPR

ijtEPijtNV

= number of households in zip code area j

= penetration rate of the loyalty card in zip code area j

= avg number of visits of loyalty card holders in j

= avg expenditures per visit of loyalty card holders in j

Sales tomembers

Sales fromzip code j=1

Sales fromzip code j=2

Sales fromzip code j=3

Sales fromzip code j=4

Penetration rateat j=3

Avg no of visitsat j=3

Avg expendituresat j=3

No of HHsat j=3

Sales tonon-members

Store revenues

Trade area

+ + +

x x x

+

Sales from membersoutside trade area

Sales from memberswithin trade area

+

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Dependent Variables

• Per Zip code:

Penetration of loyalty card (Logit)

Average number of visits (Ln)

Average purchase amount (Ln)

• (Percentage) sales to other customers

• (Percentage) sales to LC holders outside

trade area

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Explanatory Variables

Components of the sales equation to be explainedby factors concerning characteristics of:• Store;• Consumer;• Market/Competition.

E.g.,

iNV,NV,itk

K

kkNV,NV,iNV, UXγγβ

NV

01

0000

NV,ijtNV,jtn

N

nNV,niNV,ijt RZβNV

NV

1

0ln

Zj predictors that vary between zip code areas

Xi store specific predictors

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The Spatial Model

llll ξWRλR

lλ

lξ

• Relation between zip codes that are close to each other.

• Spatial error model: weight matrix in the error term accounts for spatial autocorrelation.

• Here:

the spatial autoregressive coefficient for the error lag W;

a spatially uncorrelated and homoskedastic error term.

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Empirical Study

• Dutch chain of clothing retailer

• 28 stores throughout The Netherlands

• Trade area: about 60 to 200 zip code areas per store.

• 3 years (2002-2004)

• We have data for each store as well as data about characteristics of their market areas.

• Hierarchical model: ZIP codes nested within stores.

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Further Research

• Model improvements: Cross-level interactions Random slopes Multivariate model Spatial weight matrix

• Predictive validity: Predict sales for potential new locations

• Comparison to benchmark models

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Independent Variables (1)

STORE• M2TOT

Total selling space (in m2)• %FEMASS, %KIDSASS

Percentage of selling space attributed to female and kids assortment respectively

• ESTABLISHNumber of years the store has been established after the first store

• PAYMENTTotal salaries paid per year

MARKET/COMPETITION• COMPETITION

Number of local competitors

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Independent Variables (2)

CONSUMER• HHCHILD

% of HH with children• COUPLE

% of couples without children• DOUBLEINC

% of double-income families• HPROS, >AVGPROS, AVGPROS, LPROS

% of families with high, above average, average, low, and minimum prosperity respectively

• DAVGHIGH, D>AVGHIGH, DAVGSEC, D>AVGSEC, DAVGELEM, D>AVGELEMDummy variables indicating average and above average number of people with higher, secondary, and elementary education

• DISTANCETravel distance to the store