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RETAIL STORE LOCATION

Objectives: Role of location in retail business

Delineate the process of deciding location

Understand Trading Area and Site Identification Process

Decide locations for Networks

STORE LOCATION

DISCUSSION QUESTIONS

1. What factors do retailers consider when evaluating an area of the country to locate stores?

2. What retail locations are best for departmental stores, consumer electronics, category killers, specialty apparel stores and warehouse stores?

IMPORTANCE OF LOCATION DECISION

Location is a major cost factor because:• It involves large capital cost• Affects transportation costs• Affects human resource cost, e.g salariesLocation is a major revenue factor because:• It affects the amount of customer traffic• Affects volume of business

ROLE OF LOCATION IN RETAIL BUSINESS

Location becomes a very critical decision for a retailer for several reasons– Location is generally one of the most important factors

customers consider while choosing a store

– Store location is the least flexible element of a retailers strategy mix due to its fixed nature, the amount of investment and the length of lease agreements

– Good location may let a retailer succeed even if its strategic mix is mediocre

– A store ‘inherits’ a lot of its character from its location

THE PROCESS OF DECIDING LOCATION

In deciding a store location, two broad decisions need to be made:

• The current and future potential of the catchment area of the store

• The exact site of the store

LOCATION PLANNING- TYPES OF LOCATIONS

A. High- Street Locations:– Very busy with high customer traffic– Has an array of retail stores in small sizes– Has stores that are generally found in clusters based on product

categories– High real- estate rentalsEg. Linking Rd. Bandra, Brigade Rd. Bangalore, South Extn, New Delhi

B. Destination/ Free Standing Location– Does not have high footfall rate– May not be a commercial retail area at all– Low real estate rental– May have large parking areaEg. Phoenix Mills Compound and Shoppers’ Stop, Mumbai

LOCATION PLANNING- TYPES OF LOCATIONSC. Shopping Centre / Mall Locations:

– Has existing mall traffic– Has a clear environment– Has a designated parking area– Medium to high rental costEg. DLF Mall in NCR, Spencer Plaza in Chennai, Cross Roads in Mumbai

Location Mapping:While planning the location strategy, it is imperative to map the locations so that the extent of each stores’ location reach is well defined

Location Parameters:Necessary to define the store location identification parameters in a format and see if the desired attributes are available


The process consists of:

• Evaluate alternate geographic (trading) areas in terms of potential characteristics of residents, offices, commercial settlements, and existing retailers

• Determine what type of sites are desirable from the three basic location formats: isolated, unplanned district, or planned centre

• Select the general location of the store• Evaluate specific alternate store sites

STEPS IN DECIDING STORE LOCATIONSTEPS IN LOCATION DECISION MAKING

Trading Area Analysis

Competition

Shopper Profile Size

Natural

Geographic Area

Constitution

Site Analysis

Economies of Scale

TravellingType of Site

SU

Isol

ated

Sto

re /

Unp

lann

ed

Busi

ness

Dis

tric

t/ P

lann

ed

Shop

ping

Cen

tre

Limits/Barriers

Infrastructure Economic Activity Housing pattern

Yes

No

ProfileLegal Aspects

List SizeList Value

PhysicalPsychological

Growth of market

Clearly differentiated

Demographic…

Enough for Growth/ Others to survive

LEVELS OF LOCATION DECISIONSTEPS IN LOCATION DECISION MAKING

Selection of city Site decisionArea within city

• Size of the city’s trading area

• Population and growth trends

• Purchasing power and its distribution

• Trade potential• Number, size

quality of completion

• Adequacy and potential traffic

• Complementary nature of adjacent store

• Adequacy of parking

• Customer attraction of shopping district

• Quantitative and qualitative nature of competition

• Availability of access route

• Nature of zoning regulation

• Direction of the area expansion CB


1. Evaluate alternate trading areas, geographical area, level of competition and shopper profile

1(a) Trading areas can be divided into three zones:– Primary zone - the highest density of customers to

population and the highest per capita sales– Secondary zone - generating about 20 percent of a

store’s sales– Tertiary zone - includes some out shoppers who

are willing to travel greater distances to patronize certain stores.

TRADE AREAS FOR VARIOUS PRODUCTS

4.05 km4.3 km

1.5 km1.51km

Apparel

Grocery

1.86 km2.43 km

Cosmetics

4.6 km

3.26 km

Jewelry

2.14 km1.88 km Books

2.54 km

1.92 km

Music

YR. 2000YR. 2001

5 km

1 km

4 km

3 km

THE PROCESS OF DECIDING LOCATION1(b) Geographical Area

– Transportation network, banking facilities and other support services play an important role in the development of retail in a given area

– Physical barriers, such as toll bridges, poor roads, high traffic, railway crossings, one way streets, would reduce the size and determine the shape of the trading areas

– Economic barriers (difference in sales tax between towns) also affect the size and shape of trading areas

– Economic prosperity eg. Bangalore is a big retailing hub– Customers also consider psychological barriers such as avoidance

of locations due to racial, religious causes

Location (Margin Free Market):Kerala based retail chain specializing in grocery and toiletry product •Target audience – middle & lower middle class consumers. Deposit paid by card holders•250 stores in small town of Kerala•First retailer to cross Rs, 500 cr turn over (USD 4 mln.)•Unable to venture to North India because of steep real estate costs.Location (Nilgiris):Bangalore based retail chain specializing in bakery and dairy products •Beginning to look for franchisees in Delhi, Mumbai, and Kolkata•Right location and right partners absolutely essential for the success of venture.

Zoning (McDonals):Located on the outskirts of Delhi- Ludhiana highway•Destination location for consumers and highway travelers•Check post established just before McDonald store to comply with new municipal order•Every vehicle passing through from Ludhiana have to now pay tax using highway before reaching McDonald•Adversely affected business

THE PROCESS OF DECIDING LOCATION1(c) The role of competition in deciding the location

May effect success of a store . It can be defined as saturated, under stored or over stored

– A retailer would assess the impact and decide whether competition would divide the market or it would help grow the market

– The level of competition in a market can be measured with certain ratios based on the output of the stores in a given area such as average sales per retail store, average sales per retail store category, average sales per square foot of selling


1(d) Shopper Profile: A retailer could consider the following– Growth of population and its income

• Life-style store in areas with high income house hold• Toy store in areas with higher no. of families

– Size and composition of households – The composition of the population

• Self-service retail outlets in areas with high density of cosmopolitan population

– Knowledge about an area’s population characteristics can be gained from reports of organizations like Central Statistical Organization of India, NCAER, A.C Nielsen and IMRB.

STEPS IN DECIDING STORE LOCATIONSTEPS IN LOCATION DECISION MAKING

Trading Area Analysis

Competition

Shopper Profile

Geographic Area

Site Analysis

Economies of Scale

Type of Site

SU

Isol

ated

Sto

re /

Unp

lann

ed

Busi

ness

Dis

tric

t/ P

lann

ed

Shop

ping

Cen

tre

Legal Aspects

THE PROCESS OF DECIDING LOCATION2. Analysing The Site

Having identified the area, determine the site where the retailer would trade suiting it’s positioning, costs, merchandise and customers. This analysis is done on the basis of:

A. Store type and size:• Isolated Store

Free standing retail outlet located on either a highway or street• Unplanned Business District

Type of location where two or more stores are situated together• Planned Business District

Locations developed as independent shopping areas- malls, govt developed markets eg. Chandigarh

B. Economies of scale: Retailers generally do not choose on the basis of best locations but for multiple locations. This enables them to achieve economies of scale in promotion and distribution (Subhiksha makes direct purchases).

C. Legal aspects of the site: Zoning, rent, tenancy laws, taxation, sales tax rate across states, Value-Added Taxation (VAT).

WHAT IS MEANT BY A PARASITE STORE?

Does not create its own traffic nor does it have a trading area of its own• Magazine stand in a hotel lobby• Snack bar in a shopping centre• In India such stores are many in temples, bus

stations,, and railway stations.• Airport retailing??


3. Select the general locations for the store based on:– Formats– Neighborhood– Frontage– Infrastructure– Basement vs. other floors– Bundling of purchases by customers– Rent– Legal requirements– Future expansions

THE PROCESS OF DECIDING LOCATION4. Methods Of Estimating Demand :

These take into account environment parameters like opportunity, size, competition in estimating demand and shopper behaviour.• Space sales ratio method This method is based on the assumption that a store's

sales are dependent on its size in comparison to the competition (core, secondary or primary)

• Proximal area method This method attaches a great importance to the proximity

of location of the store. It assumes that convenience is the primary driver of store

choice

PROXIMAL AREA METHOD A

B

D

C

L

M

N

O P

Q

STORE TERRITORIESA= LP + OPB= LQ + QMC= OP +PND= QM + QN

THE PROCESS OF DECIDING LOCATION4. Methods Of Estimating Demand • Analogue Model In order to estimate the size and sales potential of a

new location, match the customer demographics, the competition, and the sales of currently operating stores with similar parameters at a prospective location.This model helps in market expansion without bringing about changes in the retailer's strategy due to similarity of the target market. There are 3 steps:

a) Determine current trade areab) Define primary, secondary and tertiary zone based on

density of customersc) Match current store location with potential new store

location

ANALOGUE MODELAI Ahm. Bang. Chen. Kolkata Delhi Mum. Hyd. Pune

Est. HH (000)

180 ,000

833 1173 1369 2625 2666 3522 1021 802

A1 1.0 4.1 6.5 7.3 4.4 8.4 4.4 5.1 6.1

A2 1.7 8.5 7.0 6.0 4.7 8.6 5.4 10.2 6.0

B1 2.5 10.8 7.2 8.7 10.0 12.0 9.1 8.8 9.0

B2 2.4 9.8 7.9 7.7 7.6 8.8 7.5 7.0 5,8

C 6.3 20.9 26.0 24.7 17.7 21.9 28.3 20.7 25.3

D 7.0 24.8 22.5 22.9 26.2 19.5 24.5 18.6 23.5

E1 3.4 8.9 8.8 13.2 13.4 7.9 10.8 8.2 9.8

E2 5.5 12.2 14.2 9.6 16.0 12.8 9.9 21.3 14.5

Monthly Household Income

Up to Rs.3k

77.7 47.4 50.9 53.7 54.5 33.2 38.6 46.4 46.8

3k – 6k 16.2 30.3 33.3 26.4 29.7 35.0 41.7 29.0 32.6

6k – 10k 4.0 12.4 9.9 11.6 9.9 19.4 13.2 12.8 10.1

Household Demographic Data (Top & 8 Metros)

R K SWAMY GUIDE TO URBAN MARKETS.In order to understand the market potential of a town/ state, R K Swamy Guide to Urban Markets is made use of. The data covers and presents 784 towns with a population of over 50,000 in 21 states and three union territories. Three indices are computed for each town. Four factors are used for computing these indices. Each of these factors is represented by a few well-chosen indicators.

The three indices computed are:1. Market Intensity Index.2. Market Potential Value.3. Media Exposure Index.

The four factors used for computing these indices are:1. Means2. Consumption3. Awareness4. Market Support

R K SWAMY GUIDE – COMPUTING THE INDEXMeans, the first factor reflects the prosperity of the town. It is represented by three indicators, namely, per capita income, per capita bank deposit, proportion of households with the monthly income above Rs 10,000/-.Consumption, the second factor reflects the consumption pattern and has six indicators, namely, ownership of low priced consumer durables, medium priced consumer durables, high priced consumer durables, car, telephone and per capita consumption of fast moving consumer goods. Consumer awareness, the third factor is represented by five indicators namely, readership of print medium, cinema hall capacity, viewer ship of television, listenership of radio and female literacy. Market Support to facilitate marketing activity forms the fourth factor with four indicators comprising employment in trade, employment in transport, bank credit to trade and bank credit to transport.

TOWNS IN DESCENDING ORDER OF MPVAI

RANK MPV

TOWN STATE MPV POPULATION‘000

SHARE IN STATE %

MPV POPULATION

1. Greater Mumbai Maharashtra 1000 16368 55.7 46.2%

2. Delhi Delhi 789 12791 100 100%

3. Kolkata West Bengal 613 13216 74.5 66.9%4. Chennai Tamil Nadu 363 6424 43.9 34.7%

5. Hyderabad A.P 258 5533 37.6 30.2%

6. Bangalore Karnataka 254 5586 48.2 41.3%

7. Ahmedabad Gujarat 220 4519 30.9 27.7%

8. Pune Maharashtra 206 3755 11.5 10.6%

9. Surat Gujarat 124 2811 17.5 17.2%

10. Nagpur Maharashtra 104 2123 5.8 5.9%

THE PROCESS OF DECIDING LOCATION(The degree of attraction between 2 objects is based on the size of the object

and the distance between them)

The Law of Retail Gravitation, allows us to draw trade area boundaries around cities using the distance between the cities and the population of each city.Two cities of equal size have a trade area boundary midway between the two cities. When cities are of unequal size, the boundary lies closer to the smaller city, giving the larger city a larger trade area.Reilly called the boundary between two trade areas the breaking point (BP). On that line, exactly half the population shops at either of the two cities.One can determine the complete trade area of a city by determining the BP between multiple cities or centers

http://geography.about.com/cs/citiesurbangeo/a/aa041403a.htm

REILLY’S LAW(The degree of attraction between 2 objects is based on the size of

the object and the distance between them)

LOCALITY - APOPULATION

90,000

LOCALITY - BPOPULATION

10,000STORE

15 KM 5 KM

D ab = d

1 + Pb/ Pa

D ab = 20

1 + √(10,000/ 90,000)= 15 km

D ab= Limit of location A’s trading area along the road to location Bd= Distance along a major roadway between A & BP a = Population of location AP b = Population of location B

Limitations:1. Distance is measured by major thoroughfares and

does not involve cross streets2. Travel time does not necessarily reflect just

distance travelled3. Actual distance may not correspond with people’s

actual perception of distance

HUFF’S GRAVITY MODELHuff's Probability Model is a model formulation that can be used to determine the split of external-internal and external-external traffic. The model is formulated as a ratio of one cities attractiveness versus the summation of the attractiveness of all the other cities combined.This model is useful in identifying the percent of travelers from other cities that would be interested in patronizing the study area, and similarly, the percent of individuals who would be traveling through the study area to patronize businesses in other towns. These percentages are used to determine the amount of external-external traffic in the area. The percentage of individuals that would pass through the study area towards a different destination will be determined and the percentage will be factored into the current traffic volumes on the highways outside the area.

HUFF’S GRAVITY MODELThe equation calculates the likelihood that a person living in one city shops in another as well as the ability of one city to attract users from surrounding cities

THE PROCESS OF DECIDING LOCATION4. Methods Of Estimating Demand• Huff’s Gravity Model Huff’s Gravity model is based on the premise

that the probability that a given customer will shop in a particular store or shopping centre increases with the size of the store or centre and reduces with the distance or travel timeTo forecast sales, the probability of the customer shopping at a particular place is multiplied by an estimate of the customer’s expenditure. Then all the estimated expenditure in an area are aggregated to estimate sales from the area.

HUFF’S GRAVITY MODEL

P ij = S j ÷ Tⁿ ij

∑ S j ÷ Tⁿ ij

P ij = Probability of a customer at a given point of origin ‘i’ travelling to a particular shopping centre ‘j’S j = Size of shopping centre ‘j’Tⁿ ij = Travel time or distance from the customers’ starting point to the shopping centre; and ‘n’ an exponent of T ij that reflects the effect of travel time on different kind of shopping trips

Shopping Centre Size (sq. ft.) Distance from University

University Plaza 5,000 3

Barnes & Noble 1,000 5

Bookshelf 500 1

P ij = 5000 ÷ 3²

(5000 ÷ 3²) + (1000 ÷ 3²) + (500 ÷ 3²) = 0.51

Step 1:Determine the probability that a student in this university will shop at University Plaza. Using the formula for the Huff’s model and data for the centres,

Step 2:Forecast the no. of students who will buy their books at University Plaza. For this the probability is multiplied by the no. of students. Therefore, the no. of students who are likely to buy their books is:

0.51 x 12,000 students = 6,200 customers Step 3:Determine the sales forecast. Assuming that each customer will spend an average of Rs.150/- on books, the forecasted sales will be:

6,200 customers x 150 = Rs. 9,30,000/-

Similarly the forecasted sales for Bookshelf is Rs. 65,720/- and that for Kitab Kendra is Rs. 8,21,5000/-. Therefore the total forecasted book sales for the entire trade is Rs. 18,17,220/-

THE PROCESS OF DECIDING LOCATION4. Methods Of Estimating Demand• Multiple Regression Model The multiple regression model uses logic similar

to the Analogue approach, but uses statistics rather than judgment to predict sales for the new store. This approach is divided into 3 steps:

a) Identify an appropriate measure of performance such as per capita sales or market share

b) Create a set of variables useful in predicting performance

c) Use regression equation to project future sales

MONTHLY SALES AND POPULATION OF APPAREL STORES

Store No. Monthly Sales(Rs.000)

Population(within 4 km radius)

1 600 75,000

2 700 60,000

3 800 60,000

4 300 20,000

5 400 25,000

6 325 25,000

7 1000 80,000

8 1200 70,000

9 400 25,000

10 600 75,000

MULTIPLE REGRESSION MODELAssume that a proposed site had a population of 40,000 potential customers within 3 km. radius. The regression line is derived from

Sales = a + (b1) x (x1)where, a = constantb1 = co-efficient that defines the relationship between sales and the predictor variable(s);and, x1= the predictor variable (0 – 3 km ) population

Therefore, the projected performance for the proposed site is:Sales = 103 + (0.01 x 40,000) = Rs.5,39,000

In this case, as the population in that area is 40,000 people, and ‘a’ is derived as Rs,1,03,000, the sales is forecasted as Rs.5,39,000/-

The simplified illustration uses only one predictor variable. In case the retailer finds that the average family income also has a strong and statistically significant relationship to sales, the new regression equation would be:

Sales = a + (b1) x (x1) + (b2) x (x2)

SCATTER PLOT OF REGRESSION ANALYSIS(Past is a good reflection of the future)

Population

POPU

LATI

ON

0

2000

4000

6000

8000

10000

MONTHLY SALES (IN RS. 000)

500 1000

CHOOSING THE BEST METHOD– Analogue and Huff approaches

• Huff’s explicitly considers the attractiveness of competition and customers distance time

• Best when no. of stores with obtainable data are small (< 30)

• Used by small retailers• Huff’s model is particularly important to use in conjunction

with analogue or regression methods

– Regression approach• Best when multiple variables are expected to explain sales

– Methods may be applied to on-line stores as well, though accessibility to such stores is unlimited and shoppers from across the world can buy.

THE PROCESS OF DECIDING LOCATIONDetermining Locations for Networks

Developing such a network requires systematic evaluation of the impact of each store on the entire network of outlets

– Proximal-area-based models– Competition-ignoring model (CIM)

Objective function: Minimize total travel distanceAllocation rule: Travel to nearest centre.Comments: Assumes negative linear relationship between distance and utilization. Ignores competitive locations.

– Market-share model (MSM)Objective function: Maximize demand within proximal areas of outlets belonging to the firm.Allocation rule: Travel to nearest outlet.Comments: Consider location of competitive outlets. Locates in interstitial sites between proximal areas of existing outlets.

– Spatial-interaction-based modelsObjective function: Maximize expected market share or profit.Allocation rule: Based on spatial-interaction- model.Comments: Considers trade-off between distance and non-distance factors. Allocates fixed demand among outlets based on spatial-interaction- model.

THE PROCESS OF DECIDING LOCATION (FOR NETWORKS)

Covering Models• Set-covering model

Objective function: Locates minimum number of outlets to serve all demand within specified accessibility criterion.Allocation rule: Consumers patronize nearest outlet.Comments: Optimal location pattern assures universal accessibility.

• Maximal-covering modelObjective function: Minimize proportion of demand within accessibility criterion.

Allocation rule: Consumers patronize nearest outlet.Comments: Determine trade-off between service level and investment in outlets.

• Weighted-covering modelObjective function: Maximize utilization.Allocation rule: Travel to nearest outlet.Comments: Assumes stepwise relationship between accessibility and utilization.

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