Analysing Competition Among Shopping

Alternatives Within the Quebec Metropolitan Area:How GIS can further modelling of consumer’s destination choice behaviour

Marius Thériault, Gjin Biba, François Des Rosiers & Paul Marius Thériault, Gjin Biba, François Des Rosiers & Paul

VilleneuveVilleneuve

PROCESSUS : 2nd International Colloquium on the

Behavioural Foundations of Integrated Land-use and

Transportation Models

University of Toronto, June 12-15, 2005

Outline

1. Context of retail market transformations

2. Methodological approach and database

3. Main findings:i. Market area and spatial competition among retail

facilities

ii. Store choice behaviour of consumers

4. Conclusion

Transformation of Retail Markets

Evolution of retail structure (during the 20th Century)

- Changes of lifestyles: - increasing employment (feminization)- increasing motorization

- Evolution of consumer’s preferences- Spatial and economic transformation

1

Commercial Streets

2

Shopping Centers(after 1950)

3

Big Boxes(in expansion since 1990)

- Homogenization of shopping centres- Urban sprawl (motorways)- Technical and organizational innovations in the retail sector (e.g. just in time)

Two main impacts:

(i) Modifying consumer destination choice behaviour and retail industry competition(ii) Changing urban dynamics (i.e. land use, activities location, transportation demand…)

Context of Quebec Metropolitan Area (QMA)

Agglomeration of 700 000 persons (7th in Canada and 2nd in Quebec)

12 % of workforce (~ 50 000 persons) employed in retail sector; annual market of 8.2 billion of CAN$

Economic and urban environment marked by: Household purchasing power is 4 % above the provincial average Strong urban sprawl Highly developed motorway network (21 Kilometres / 100,000 inhabitants)

Retail structure (in 2001): 87 shopping centers (including 2,300 stores, Total Floor Area > 11 M sq ft) 44 big boxes (Total Floor Area > 3 M sq ft) Roughly 5,000 individual stores (2,600 on 72 commercial street segments)

Evolution (1990-2001) of the retail structure: Stagnation, even recession, of the number of shopping centers Implementation of several isolated big boxes and power centres Transformation of commercial streets (revitalization)

Sources: Statistic Canada, Quebec City, CRAD

Accessibility to Shops - Consumer Behaviour

1991 1996 2001

Car 81,7 83,8 85,5

Bus 11,3 7,3 4,2

Walking 6,2 7,8 9,1

Others 0,7 1,1 1,1

Total 100,0 100,0 100,0

Source: Origins-Destinations surveys, 1991, 1996, 2001

b) Change of transportation modes used during shopping trips (%)

MAIN CHANGES :

• Better accessibility to the new stores (reduced travel time)

• More prevalent car use for shopping trips

• Decreasing use of public transportation for shopping and leisure activities

a) Evolution of distance and duration of shopping trips within QMA (1991 – 2001)

Source: Origins-Destinations surveys, 1991, 1996, 2001

0

2

4

6

8

10

12

1991 1996 2001

Average Trip Length (Km) Average trip duration (Min)

Research Purpose

Objectives : Identify market areas and analyse spatial competition among

commercial streets, shopping centers and big boxes

Investigate consumer behaviour when choosing retail store

Better understand social, economic and spatial impacts of new large retail outlets (big boxes and power centres)

Combining GIS and travel survey may contribute to analyse retail market dynamics and consumer choice behaviour

Methodology:

Locating consumers and shopping trips (origin and destination)

Estimating markets share for each retail outlet

Delineating primary (50%) and secondary (80%) market areas

Modelling consumer store choice (discrete choice modelling)

Database

Business Directory (2001) for the QMA

• 5,000 individual stores (50% located on commercial streets)

• 54 neighborhood and 23 community shopping centers

• 6 large shopping centers (3 regional and 3 super-regional)

• 44 big boxes

Geo-referenced using topographic maps (1: 20 000)

Origin - Destination Survey (2001) Monday-Friday

174 243 trips 68 121 persons 27 839 households

25 522 shopping trips17 943 persons13 074 households

Shopping Purposes (all trips) 21.8 % Grocery 11.9 % Restaurants 26.6 % Leisure 39.7 % Buy other products

Shortest Route Simulation Using TransCAD GIS (Travel time by Car)

Retail Outlets Distribution

kilometres

0 2,5 5

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Retail forms

Neighbourhood shopping center (54)

Community shopping center (23)

Commercial street > 10 stores/Km (72)

Big box > 50 000 sq Ft (44)

Regional (3) and super-regional center (3)

Distribution of Trips Among Destinations (O-D, 2001) (Monday to Friday)

Neighbourhood centres8.1%

Community centres12.0%

Commercial streets17.4%

Big boxes &Power centres

8.1%

Regional & Super-regional centres

18.0%

Small individual stores36.4%

Delineation of Market Areas

1,5 30

kilometres

Primary Market Area(Convex Hull - 50% of closest customers using travel time)

Secondary Market Area(80% of customers)

The polygon of a Commercial Street

(Shopping destination is “Avenue Cartier”)

Shopping trips origines

Primary and Secondary Market Areas (2001)

Commercial Streets with Neighbourhood Shopping Center

24 segments; 1,645 individual shops

Primary Market Area = 5.6 sq. Km

Average Control of Market = 12.3 %

Secondary Market Area = 30 sq. Km

Average Control of Market = 6.8 %

Commercial Streets Without Shopping Center

42 Segments; 1,062 individual shops

Primary Market Area = 4.8 sq. Km

Average Control of Market = 9.4 %

Secondary Market Area = 20.5 sq. Km

Average Control of Market = 8.3 %

Community Shopping Centres

23 centres; 686 individual shops

Primary Market Area = 7.7 sq. Km

Average Control of Market = 11.9 %

Secondary Market Area = 54.1 sq. Km

Average Control of Market = 9.5 %

Regional and Super-regional Shopping Centres

6 centres; 1,124 individual shops

Primary Market Area = 47.8 sq. Km

Average Control of Market = 14.2 %

Secondary Market Area = 297.1 sq. Km

Average Control of Market = 9.9 %

Big Boxes – Grocery & Beverage

11 stores; Total Floor Area=76 710 sq. m

Primary Market Area = 19.3 sq. Km

Average Control of Market = 3.8 %

Secondary Market Area = 82.6 sq. Km

Average Control of Market = 1.6 %

Big Boxes - Renovation Products

6 stores; Total Floor Area = 48 946 sq. m.

Primary Market Area = 66.4 sq. Km

Average Control of Market = 1.3 %

Secondary Market Area = 117.6 sq. Km

Average Control of Market = 0.9 %

Big Boxes - Car related products (Canadian Tire)

5 stores; Total Floor Area = 38 785 sq. m.

Primary Market area = 11.0 sq. Km

Average Control of Market = 2.0 %

Secondary Market Area = 39.6 sq. Km

Average Control of Market = 1.0 %

Big Boxes - Mixed Products (Wal–Mart)

3 stores; Total Floor Area 31 850 sq. m

Primary Market Area = 33.8 sq. Km

Average Control of Market = 6.6 %

Secondary Market Area = 56.5 sq. Km

Average Control of Market = 5.7 %

Others Big boxes

5 stores; Total Floor Area = 21 074 sq. m.

Primary Market Area = 10.3 sq. Km

Average Control of Market = 2.9 %

Secondary Market Area = 48.0 sq. Km

Average Control of Market = 0.8 %

Modelling Consumer’s Destination Choice

«We investigate consumer destination choice (type of outlet) rather than consumer behaviour within commercial space»

Multinomial Logistic Regression Model Adjusted using O-D Survey Data

Satisfaction

Set of shopping choice alternatives:i. Commercial streets (with/without

neighbourhood shopping center) ii. Community shopping centresiii. Regional and super regional shopping centresiv. Big boxes and power centers

Where, When, and How go shopping ?

Consumer store choice = f (utility) = f (retail structure, consumer profile, spatial determinants)

Consumer profile: - Socio-economic and professional status- Household characteristics

Spatial determinants: - Consumer origin and destination place- Transportation mode and trip attributes

Accessibility

Attributes of Trips by Retail Form (%)

Factors

Big box (n=2031)

Commercial street (with or without neighbourhood centers)

(n=4395)

Community centre

(n= 2977)

Regional and supra regional centre

(n=5510)

Total (n= 14913)

Shopping purpose

Any products 56.5 27.3 43.8 83.8 51.2

Grocery 37.0 31.4 34.5 4.8 24.9

Restaurants 1.6 17.4 7.3 6.1 9.9

Leisure 4.9 24.0 14.4 5.3 13.9

Length of trip

0.00-4.99 Km 43.5 70.9 65.8 41.0 57.3

5.00 - 9.99 Km 35.5 16.6 21.8 30.2 24.2

10.00 - 14.99 Km 11.3 7.6 7.3 16.5 10.7

15.00 - 19.99 Km 5.1 2.7 2.8 7.6 4.5

> 20.00 Km 4.6 2.2 2.3 4.8 3.3

Transportation mode

Car 96.7 74.3 86.2 88.6 83.9

Bus 0.7 4.6 3.8 7.5 4.7

Walk 2.3 19.7 9.1 3.2 10.3

Other 0.4 1.4 1.0 0.7 1.0

Car per driver in

household

Without car or without driver 2.2 13.7 9.3 7.9 9.6

Less than one car per driver 38.9 33.9 36.0 37.7 36.1

One car per driver 56.4 49.5 52.5 52.4 51.9

More than one car per driver 2.4 2.9 2.1 2.0 2.4

GenderMan 48.2 43.6 39.7 38.0 41.8

Woman 51.8 56.4 60.3 62.0 58.2

Type of household

Two adults or more without children 54.5 49.3 57.1 54.8 53.2

Two adults or more with children 32.2 25.7 21.3 26.1 25.8

Lone person 10.6 21.1 18.9 15.9 17.7

Single parent family 2.8 3.9 2.7 3.2 3.3

Factors Commercial Streets (with or without neighbourhood shopping centre)

Community Shopping Centre

Regional and Super-regional Shopping Centre

Trip Purpose(Ref. Buying others

products)

Grocery .6 *** 1.1 ** --

Restaurant 2.9 *** 1.6 *** 1.3 ***

Leisure 4.6 *** 1.4 *** 1.4 ***

Departure Place(Ref. Home)

Work/School 1.6 *** -- 1.3 **

Other (trip chaining) .7 *** .8 ** .6 **

Day of Week (Mo-Tu-We/Th-Fr.) 1.1 *** 1,1 *** --

Departure Time (6PM-12PM/8AM-6PM) -- -- 1.2 **

Trip Length(Ref. = less then 5 Km)

5.0 - 9.99 Km .7 ** .8 *** .6 ***

10.0 - 14.99 Km .4 *** .5 *** .9 ***

15.0 - 19.99 Km .3 *** .3 *** .8 ***

>= 20 Km -- .2 *** .6 ***

Transportation Mode(Ref. = Car diver or

pasenger)

Bus 5.8 *** 3,8 *** 5.7 ***

Walk 6.2*** 2,6 *** 1.5 ***

Other -- -- 1.3 **

Car Ownership (household)

(Ref. One car per driver)

Without car or without driver 1.6 ** 1.6 ** 1.5 **

Less than one car per driver 1.3 *** -- --

More than one car per driver -- -- 1.4 **

Gender Woman / Man 1.9 *** 1.5 *** 1.6 ***

Household Type(Ref. 2 adults or more

with children)

Lone person 2.2 *** 1.8 *** 2.0 ***

2 adults or more without child 1.6 *** 1.3 ** 1.3 **

Single-parent family 1.9 *** 1.4 ** 1.5 ***

Occupation(Ref. = Bleu collar

worker)

Professional 1.3 ** -- 1.2 **

Student 1.8 *** .7 * 1.1 *

Retired 1.7 *** 1.5 *** 1.3 *

Other 1.3 ** -- --

Type of Shop Choice: MNL Parameters

Significant levels: -- non significant; * 0.1; ** 0.5; *** 0.01

Reference is “Big Boxes - Power Centres” [Figures present odds ratios]

Conclusion

Methodology: Combining GIS and Statistical Analysis was efficient for modeling

both spatial and non-spatial determinant of retail trade market

Competition among retail facilities and consumer behaviour: Commercial streets (week days, resist fairly well to competition):

Multi-purpose trips especially Leisure and Restaurant, Lone persons Integration of small shopping centres yields a comparative advantage

Community shopping centres (threatened by big boxes development):

Grocery, Single - parent families, Retired Their endurance is mostly related to strategic location

Regional & super-regional shopping centres (yet very competitive): Proximity to workplaces and bus routes; Large choice of products, Women One of their last competition strategy may be to agglomerate with power centres

Big Boxes (extending their geographic and economic market shares): Car trips, Men, Workers, Households with children The most competitive are in grocery, mixed products and renovation sectors

Retail evolution, impacts on transportation and urban dynamics: Big boxes are threatening for shopping centres (mostly at neighbourhood and

regional levels) Increases car use and demand for new transportation infrastructures Strong competition means potential readjustment of commercial real estate

values, activities redistribution (or relocation), traffic, road infrastructures…