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Analysing Competition Among Shopping Alternatives Within the Quebec Metropolitan Area: How GIS can further modelling of consumers destination choice behaviour.

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Presentation on theme: "Analysing Competition Among Shopping Alternatives Within the Quebec Metropolitan Area: How GIS can further modelling of consumers destination choice behaviour."— Presentation transcript:

1 Analysing Competition Among Shopping Alternatives Within the Quebec Metropolitan Area: How GIS can further modelling of consumers destination choice behaviour Marius Thériault, Gjin Biba, François Des Rosiers & Paul Villeneuve PROCESSUS : 2 nd International Colloquium on the Behavioural Foundations of Integrated Land-use and Transportation Models University of Toronto, June 12-15, 2005

2 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

3 Transformation of Retail Markets Evolution of retail structure (during the 20 th Century) - Changes of lifestyles: - increasing employment (feminization) - increasing motorization - Evolution of consumers 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…)

4 Context of Quebec Metropolitan Area (QMA) Agglomeration of persons (7 th in Canada and 2 nd in Quebec) 12 % of workforce (~ 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 ( ) 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

5 Accessibility to Shops - Consumer Behaviour Car 81,783,885,5 Bus 11,37,34,2 Walking 6,27,89,1 Others 0,71,1 Total 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

6 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)

7 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: ) Origin - Destination Survey (2001) Monday-Friday trips persons households shopping trips persons 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)

8 Retail Outlets Distribution Retail forms Neighbourhood shopping center (54) Community shopping center (23) Commercial street > 10 stores/Km (72) Big box > sq Ft (44) Regional (3) and super-regional center (3)

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

10 Delineation of Market Areas 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

11 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 %

12 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 %

13 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 %

14 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 = sq. Km Average Control of Market = 9.9 %

15 Big Boxes – Grocery & Beverage 11 stores; Total Floor Area= 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 %

16 Big Boxes - Renovation Products 6 stores; Total Floor Area = sq. m. Primary Market Area = 66.4 sq. Km Average Control of Market = 1.3 % Secondary Market Area = sq. Km Average Control of Market = 0.9 %

17 Big Boxes - Car related products (Canadian Tire) 5 stores; Total Floor Area = 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 %

18 Big Boxes - Mixed Products (Wal–Mart) 3 stores; Total Floor Area 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 %

19 Others Big boxes 5 stores; Total Floor Area = 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 %

20 Modelling Consumers 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 centres iii. Regional and super regional shopping centres iv. 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

21 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 Grocery Restaurants Leisure Length of trip Km Km Km Km > Km Transportati on mode Car Bus Walk Other Car per driver in household Without car or without driver Less than one car per driver One car per driver More than one car per driver Gender Man Woman Type of household Two adults or more without children Two adults or more with children Lone person Single parent family

22 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 *** 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) ** Trip Length (Ref. = less then 5 Km) Km.7 **.8 ***.6 *** Km.4 ***.5 ***.9 *** Km.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 ** Car Ownership (household) (Ref. One car per driver) Without car or without driver 1.6 ** 1.5 ** Less than one car per driver 1.3 ***-- More than one car per driver ** GenderWoman / Man1.9 ***1.5 ***1.6 *** Household Type (Ref. 2 adults or more with children) Lone person2.2 ***1.8 ***2.0 *** 2 adults or more without child 1.6 ***1.3 ** Single-parent family1.9 ***1.4 **1.5 *** Occupation (Ref. = Bleu collar worker) Professional1.3 **--1.2 ** Student1.8 ***.7 *1.1 * Retired1.7 ***1.5 ***1.3 * Other1.3 **-- 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]

23 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…


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