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ARP > GIS for Retail Analysis: Buffer and Overlay > Flashcards

GIS for Retail Analysis: Buffer and Overlay Flashcards

1
Q

What is GIS for retail analysis?

A

Use of buffer and overlays in order to create catchments around store locations to identify expected levels of demand

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2
Q

How did Pearson (2007) use GIS to map demand?

A

Population overlay

Identified 6 variables important for unique demand estimation

Households must satisfy all 6 variables in a ‘sieving effect’ leaving only households that match criteria

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3
Q

What were the 6 variables used by Pearson (2007)?

A
  1. Household income > $45,000
  2. Family income > $60,000
  3. Bachelor’s degree or higher > 40%
  4. Median age between 25 and 46
  5. Median mortgage > $1,050
  6. House value > $139,000

Multicollinearity between variables

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4
Q

What is sieve mapping?

A

Creation of variables that need to be satisfied to leave very few, but ideal, store locations - achieved through the creation of buffers around existing stores drawn in relation to store size

Can remove locations not right for store e.g. low income areas for Waitrose

Can overlay a number of characteristics to get the most accurate idea location

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5
Q

How was GIS used for mapping demand for the Pawn Brokers in Houston?

A

Sieve mapping through a scoring system

Created 5 categories

Each category split into ranges and awarded points 1-5

Variables 1, 2, 4 and 5: low values = 1, high values = 5
Other way around for variables 3

Higher the total score, better the locations

Mapped through hotspot mapping

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6
Q

What were the 5 categories used in the Pawn Brokers example?

A
  1. pop. size
  2. household income
  3. no. rented households
  4. household size
  5. pop. density
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7
Q

What are the 3 ways GIS can be used for network analysis?

A
  1. Accessibility
  2. Location-allocation models
  3. Food miles analysis
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8
Q

GIS for network analysis: ACCESSIBILITY

A

Used to assess how well provided/easy it is for customers to access e.g. food deserts

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9
Q

GIS for network analysis: LOCATION-ALLOCATION MODELS

A

Used in network analysis in order to find the ideal location for existing demand and travel time for consumers

  1. Take a map of demand variables and ask where the best ‘x’ no. locations would be
  2. Model tries ‘x’ locations in every possible combination
  3. Calculates distance people would travel to access tore
  4. Finds idea location to min. travel time
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10
Q

How does ArcGIS map location-allocation models?

A

Creates ‘spider maps’
Centre of spider is suggested location
‘Legs’ = distance travelled

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11
Q

Why are location-allocation models limited?

A
  1. Assumes only travel from home
  2. Assumes brand loyalty
  3. Assumes everyone has a car
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12
Q

What is the Hotelling Theorm (1929)?

A

Argues against the use of LAMs as says that optimum location based on distance is incorrect because of the need for competition:

  1. Retailers will move/locate near competitors to steal customers
  2. Market is too competitive to serve optimal consumer base profit driven
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13
Q

What 4 reasons have lead to an increase in food miles?

A
  1. Agricultural trade liberalisation
  2. Technological innovation & agricultural intensification
  3. Changing consumer demands
  4. Logistical changes in domestic food supply chain
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14
Q

How has agricultural trade liberalisation increased food miles?

A

Agreement on Agriculture, 1995
Meant that domestic support was cut and export subsidies reduced - lead to an increase in access to foreign products which are often cheaper

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15
Q

How has tech. innovation and agricultural intensification increased food miles?

A

Increased mechanisation leads to more produce
Increased specialisation and efficiency
Lead to surplus of produce that needs to be distributed elsewhere, therefore abroad

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16
Q

How has changing consumer demands increased food miles?

A

Increased ethnic diversity
Change in lifestyles
Demand for seasonal produce e.g. strawberries all year round

17
Q

How has changes in the food supply increased food miles?

A

Supermarkets control grocery market: goods sent to warehouses then redistributed, increasing road travel

18
Q

What have ASDA done to try and reduce food miles associated with their distribution of produce?

A

More and more supermarkets trying to source locally but food miles associated with distributing these to stores, therefore:

Created 11 ‘local hubs’ - local suppliers deliver to these hubs then ASDA redistributes in bigger lorries

19
Q

What is the local food miles calculator?

A

Designed to measure and compare the distance and emissions associated with moving local products to ASDA stores via 8 distribution strategies - finding the ideal distribution method with the lowest associated food miles

20
Q

How can GIS be used for revenue estimation?

A
  1. Define catchment area size - calculated by comparing with existing stores to know average travel time
  2. Draw buffer
  3. Overlay demand variables e.g. pop. size/spending power etc. - INTERPOLATION
  4. Estimate revenue - Arby’s ‘Fair Share’ method
21
Q

Why does interpolation have to be used when overlaying the demand variables for revenue estimation?

A

Because buffers may cut through 6 zones but not totally consume them, therefore don’t know exact pop. size - have to get % of the pop. in the buffer

22
Q

Why is interpolation inaccurate for revenue estimation?

A

Assumed equal spread of the pop. between zones/catchments

23
Q

What is Arby’s ‘Fair Share’ method of revenue estimation?

A

Assumes store equidistant will have the same % of revenue i.e. they will get equal customer base

24
Q

What are the 6 issues with buffer and overlay for retail planning?

A
  1. No distance-decay: assumes those far from the store are just as likely to visit as those right by
  2. Fair share method of revenue allocation: realistically, each store won’t get same % of revenue
  3. Flows in and out of buffer: ignores those outside the buffer that may still go to the store
  4. Interpolation issues
  5. Overlapping catchment areas: too many buffers close together, therefore can’t identify which store is in each buffer
  6. MapInfo software issues
25
Q

What is one solution for overlapping catchment areas?

A

THIESSEN POLYGONS: gives each store its own distinct catchment area

BUT still quite meaningless in retail - people don’t stick to buffers

26
Q

What is population overlay?

A

A buffer is drawn around the store location of either distance or travel time, then demand is overlayed within the buffer

Demand in way of pop. size and /or spending power

27
Q

How can GIS be used to reduce food miles?

A

Find alternative distribution routes/strategies to minimise carbon footprint

ARP (9 decks)

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