- Email: [email protected]
commercial geomatics analysis
Progress in Planning 60 (2003) 75–92 www.elsevier.com/locate/pplann
Spatial fluctuations in the health of the consumer services sector within a metropolis: a business/commercial geomatics analysis Ken Jones Centre for the Study of Commercial Activity, Ryerson University, 350 Victoria Street, Toronto, Ont., Canada M5B 2K3
Issues related to data aggregation have typically limited detailed spatial analyses of the supply-side of the consumer service sector of the economy. The major restriction has been the lack of disaggregated, longitudinal data below the metropolitan level (Eppli and Laposa, 1997). Thus, it has been difficult to examine even downtown/inner city/suburban changes in the supply-side of the commercial sector. This paper extends previous analyses by examining the spatial dynamics of the urban consumer service economy at a microgeographic scale (Simmons and Yeates, 1998). Three metrics of change have been chosen to reflect the fluctuations in ‘health’ of over a thousand commercial shopping districts or nodes in a large metropolitan region These concentrations serve a variety of functions that are associated with the consumer services sector. In general, each of these shopping areas incorporates some combination of retailing, financial, personal and business service activities. The urban commercial economy under investigation comprises approximately 50 000 stores that are located within the confines of the Greater Toronto Area (GTA). A database, collected on an annual basis between 1996 and 2001, permits monitoring of the spatial fluctuations at a variety of scales within the Toronto region. In this paper, three measures are used to examine change: (i) vacancy rates; (ii) business type; and (iii) the number of store/tenant turnovers. By examining both spatial and temporal variations in these attributes across an entire urban system, it is possible to examine the variability and volatility of an urban retail/commercial landscape across a number of dimensions, and provide insights into a variety of social and economic issues. These can include the health of local neighborhoods and the impact of new retail formats, and the relative performance of different retail real estate assets and classes. E-mail address: [email protected] (K. Jones). 0305-9006/03/$ - see front matter q 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0305-9006(02)00092-2
76
K. Jones / Progress in Planning 60 (2003) 75–92
The early literature of urban retail change can be traced to the empirical findings of researchers in the 1960s and 1970s. Simmons (1964, 1966) developed a model that examined the associations between urban retail growth and various socio-economic correlates for Metropolitan Toronto. Retail change was linked to a complex set of temporal and spatial variables that took into account variations in income, technological developments, and shifts in demography. These factors affected consumer behaviours and preferences and led to adjustments in the composition and growth of local retail areas. Schell (1964) examined urban retail change in Boston, while both Sibley (1976) and Shaw (1978) examined the long-term patterns of retail change for a selected urban case in Britain. In these latter two studies, changes in the retail pattern were viewed as the outcome of the aggregate adaptive behaviours of independent retailers and multi-unit chains to changes in the retail environment. More recently, Simmons and Simmons (1997) examined retail change for a four-year period for a set of 174 retail strips within Metropolitan Toronto. This study concluded that the economic role of strips was shifting toward the service sector; growth in retail strips took place in and around the downtown core and in the larger, more specialized strips; and the turnover rates of retailers in strips approached 15%. Finally, Yeates and Montgomery (1999) provide one of the few studies that examine a set of supply side indicators of retail change for some smaller urban centres. This study concluded that the overall high levels of vacancy and volatility of the local retail system was an indicator of over-storing and reflected a complex set of factors that included nearness to a major metropolitan market, new forms of direct competition, and shifts in the health of the local economy.
K. Jones / Progress in Planning 60 (2003) 75–92
77
CHAPTER 1 The data The data used in the analysis are collected and maintained by the Centre for the Study of Commercial Activity at Ryerson University. Since 1996, an annual survey has been undertaken for the consumer services sector within the Greater Toronto Area. Table 1 provides a description of the size of this database in terms of number shopping areas and stores for four distinct shopping environments—retail streets (strips), shopping centres, underground malls, and power centres. For data collection purposes, each retail area is located and then its areal dimensions are defined. Then, for each outlet/store, data are collected with respect to its business type (Standard Industrial Classification code), business name, address, selling area, and ethnicity. This database is then geo-coded and digital maps of the retail structure and retail change are generated. This spatial database permits the monitoring of retail change at a variety of spatial scales, and for specific business types. In this paper, the tenant data has been aggregated to retail concentrations in order to provide measures of retail change for each of the four distinct retail environments over a 6 year period (Table 2). Table 1 provides an overview of the dimensions and general characteristics of the database. Since 1996, this database has increased in size as a result of two factors—new construction activity (such as power centres and underground malls), and an increase in areal extent of the data collection with the inclusion of suburban retail streets and convenience shopping centres. The resultant database captures the retail/commercial structure of major retail streets, all shopping centres in excess of 50 000 ft2 of gross leasable area, the underground mall system, and the network of power centres within the Greater Toronto Area. For each of these retail types, information can be generated for the tenant mix, turnover rates and vacancy levels on a property-by-property basis. The specific objective of the paper, therefore, is to explore the dynamics of retail change for each of the four retail environments in the Greater Toronto Area (GTA) for the 1996 –2001 period. For each property class, changes in the vacancy rates, business composition and turnover rates are assessed. As part of this evaluation, GIS (Geographic Information Systems) has been used to analyze and interpret the general patterns of change Table 1 Retail composition in the GTA Year
No. of Retail streets (strips)
No. of Stores
No. of Shopping centres
No. of Stores
No. of Underground malls
No. of Stores
No. of Power centres
No. of Stores
1996 1997 1998 1999 2000 2001
212 212 260 278 301 302
17 18 21 22 24 24
537 570 609 637 663 676
17 19 20 21 22 22
24 24 30 33 33 33
1115 1135 1252 1276 1291 1291
22 26 34 39 39 49
270 354 510 767 885 1043
973 401 001 734 465 981
484 514 808 387 014 181
78
K. Jones / Progress in Planning 60 (2003) 75–92
Table 2 Vacancy rates by retail environment: 1996–2001 Year
Retail streets (strips) (%)
Shopping centres (%)
Underground malls (%)
Power centres (%)
1996 1997 1998 1999 2000 2001
9.7 9.3 9.2 9.1 9.3 8.8
9.5 10.3 10.8 10.6 9.9 9.1
9.8 9.2 8.9 8.1 7.4 5.3
4.6 5.7 4.7 5.4 5.4 6.9
Average
9.2
10.0
8.1
5.5
that are shaping the urban commercial economy in the GTA. The results of the analysis may be used for comparative purposes and bench-marking in other metropolitan areas that are undergoing rapid market growth and significant commercial innovation.
K. Jones / Progress in Planning 60 (2003) 75–92
79
CHAPTER 2 Commercial strips Commercial strips present a paradox for while turnover rates, and levels of vacancy for individual properties, often appear high, many strips appear surprisingly healthy. This is probably because they are often able to expand and contract rather easily. This rapidity of change reflects the special role that retail strips play within the urban retail system, and the vulnerability of independent retailers and commercial outlets to shifts in local market conditions. From a structural perspective, commercial strips comprise a variety of types. Across the GTA, collectively they account for approximately 25 000 business locations and contribute approximately 30 million square feet of selling space to the commercial inventory (Yeates, 2000). In aggregate, these retail streets represent the most complex urban shopping classification. They can comprise major shopping streets (for example, Yonge Street in downtown Toronto); ethnic retail concentrations (such as St Clair Avenue West), specialized retail areas (for example, trendy Queen Street West), fashionable shopping districts (such as in the Yorkville district); ‘historic’ downtowns (such as ‘Main Street’ Unionville or Newmarket); and small neighborhood shopping streets. The Toronto area is well served by these shopping areas that in total contribute approximately one quarter of the retail space in the urban area. Moreover, as Simmons and Simmons (1997) have noted, these unplanned districts reflect the local demographic and socio-economic characteristics of their respective communities. During the 6 year period under investigation, commercial strips have, in the aggregate, experienced a remarkably stable vacancy rate of 9.2% (Table 2). However, as Table 3 indicates, over this period the composition of the retail strips in the Toronto region changed dramatically. In total, six categories (restaurants, personal services, other retailing, business services, hair and beauty, and health services) added over 4000 stores to the retail street inventory. More importantly, these six sectors accounted for approximately 70% of the new retail development along the strips during the study period. Clearly, the fabric of commercial strips in the Toronto area has experienced radical change. In almost every strip, retailing is being replaced with services. In many cases, non-retailing functions such as restaurants and various personal and business services now dominate. The spatial variation in vacancy and turnover rates is, however, considerable throughout the GTA. In Figs. 1 and 2, the symbols used to reflect the vacancy and turnover rates are over-laid on a map that illustrates the size of each retail area (measured in terms of the number of stores). Fig. 1 indicates the average vacancy rates for the 1996– 2001 period—the spatial variability in the overall pattern of vacancy rates is considerable. For the individual strips, the average annual vacancy rates vary from a low of 0% to a high of 32%. Moreover, certain areas of the city exhibit consistently high vacancies. For example, east of the downtown core a cluster of strips exhibited vacancies in the 24% range over the 6 year period under investigation. This high rate of change in the area is associated with the changing local market as the area shifts from low income residential to an area of new
80
K. Jones / Progress in Planning 60 (2003) 75–92
Table 3 Net retail change by category: 1996–2001 Sector
Strips
Shopping centres
Underground malls
Power centres
Book and stationery stores Business services Cleaners Drug stores Financial and insurance industries Florists lawn and garden centres Food/grocery Food and beverage services General merchandise Hair and beauty services Hardware stores Health services Household and appliance stores Jewellery stores Liquor Men’s clothing Music stores Other clothing and fabric stores Other retail Personal and household services Recreational services Shoe stores Sporting goods Women’s clothing
32 540 127 52 272 52 243 1142 37 533 44 445 436 56 39 222 28 102 636 722 199 5 42 84
242 174 132 75 231 20 359 737 98 434 214 418 263 147 30 2147 9 87 301 344 130 11 6 93
28 4 4 21 21 2 17 72 8 9 10 10 27 10 1 7 0 8 48 17 22 22 22 24
20 5 5 4 15 21 13 160 20 15 15 15 80 4 4 34 4 50 38 4 34 30 11 39
Total stores
5846
3896
222
618
condominiums for ‘young urban professionals’. Other areas of high vacancy rates area associated with the lower income areas to the north and west of the core area. For many of these neighborhood shopping streets, annual vacancy rates are in excess of 25%. Fig. 2 indicates the average turnover rates for the 1996– 2001 period. Turnovers provide a clear measure of the volatility of the urban retail system—in general, the average annual turnover rate in the GTA is 14.7%. Noteworthy is the constant pattern of turnover across the region—80% of the commercial strips in the Toronto region experienced yearly turnover rates between 10 and 20%. These rates do not appear to be clustered in any particular part of the metropolitan region—high and low rates occur in suburban areas as randomly as they appear to occur in the city.
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 1. Average vacancy rates for retail strips: 1996–2001.
Fig. 2. Average turnover rates for retail strips: 1996–2001.
81
82
K. Jones / Progress in Planning 60 (2003) 75–92
CHAPTER 3 Shopping centres The shopping centre system in the GTA comprises approximately 650 centres (with more than 30 000 ft2 of commercial space) and 21 000 stores. These malls, accounting for approximately 75 million square feet of space, form a hierarchy of planned centres according to size and function. In general, there are five classes of centres: convenience, neighborhood, community, regional, and super-regional (Doucet and Jones, 1997). Although these centres dominate the consumer service sector in the GTA (as malls do in every North American metropolis), their primacy, after 50 years of growth, is now being threatened, and some mall closures, or transformations, have occurred. Several factors have been cited as being associated with these closures and transformations. These include: competition from big-box retailers, particularly since 1990; over-saturation of the North American market with commercial space; the emergence of e-tailing; and changes in consumer shopping behaviours and preferences. Under-performing and/or declining shopping centre properties are often referred to as greyfield properties (Insausti et al., 2000). Typical signs of declining health include: (1) high vacancies; (2) increases in tenant turnovers; (3) loss of anchor tenants and national chains; and (4) decline and/or lack of reinvestment in the physical structure of the malls. From 1996 to 2001, shopping centres in the GTA experienced an average vacancy rate of 10% (Table 2). However, when malls are examined according to their size, major variations in vacancy rates are noted. There is a significant change in vacancy rates between malls above and below 700 000 ft2, with the vacancy rate of large regional malls normally below 6%. Changes in the composition of tenant mix of the shopping centres are less pronounced than experienced in commercial strips (Table 3). Moreover, three retail categories actually showed a net decline in the number of mall stores—men’s fashion, book and hardware stores. These decreases were the direct outcome big-box competition in the case of books and hardware, and a major decline in fashion spending in the case of men’s fashion. Major increases were noted in the following sectors—restaurants, hair and beauty, health services, food retailing, personal services, other retailing, housewares and financial services. These eight categories accounted for 77% of the net change in shopping centre tenants and reflect the increase in convenience-oriented shops and a major shift toward services across the entire urban shopping centre network. Major spatial variations occur in the health and stability of the shopping centre system. In Figs. 3 – 7, centre size is linked to symbols that are used to indicate average vacancy and turnover rates across the network of shopping centres. For clarity, the shopping centre system is subdivided into two classes: those with less than 1 000 000 ft2 of commercial space, generally referred to as convenience and neighborhood centres; and those with more than 100 000 ft2, generally referred to as community and regional centres.
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 3. Average vacancy rates for shopping centres , 100,000 square feet: 1996– 2001.
Fig. 4. Average vacancy rates for shopping centres . 100,000 square feet: 1996–2001.
83
84
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 5. Average turnover rates for shopping centres , 100,000 square feet: 1996–2001.
Fig. 6. Average turnover rates for shopping centres . 100,000 square feet: 1996–2001.
K. Jones / Progress in Planning 60 (2003) 75–92
85
Fig. 7. Average vacancy rates for the underground mail system: 1996–2001.
Fig. 3 presents the average vacancy rates for the 1996 – 2001 period for the 442 smaller centres within the urban area. Although these malls record an average vacancy rate of 9.6%, there is considerable spatial variability, with pockets of higher vacancies noted in the eastern and northern suburbs, and smaller centres in the central area exhibiting lower vacancy rates. Fig. 4 illustrates the pattern of vacancies for the set of 159 larger centres. The distribution of the vacancy rates for these malls exhibits a much more regular pattern and surprisingly, in aggregate, the larger malls experienced a higher average vacancy of 10.5%. Upon closer inspection, for this larger category, the pattern of vacancies is somewhat bipolar. Twelve malls experienced extremely high vacancy rates—in excess of 27%. Typically, these malls are situated in the suburban areas and tended to serve either new developing residential markets, or are located in highly competitive clusters. Conversely, the 10 large super-regional malls (those in excess of 900 000 ft2) consistently exhibited vacancy rates in the 5% range. This trend points out the obvious importance of accessibility and shopping centre attraction to the overall success of planned shopping centres. The annual turnover rate for the entire of shopping centre network was approximately 16% for the 1996– 2001 period. Unlike vacancy rates, the spatial variation in turnover rates is similar for both large and small malls (Figs. 5 and 6). In both cases, approximately 25% of the centres had turnover rates in excess of 20%.
86
K. Jones / Progress in Planning 60 (2003) 75–92
However, upon closer inspection, a larger proportion of the small centres (21.8%) had annual tenant turnovers of less than 10%, while for the larger centres this figure decreased to 16.3%. It should be noted that tenant turnovers in many instances could be viewed as a good thing as the need to refresh retail properties is constant as both market and competitive pressures are always in flux. This is particularly evident with the group of super-regional malls that collectively experienced a relatively high annual turnover of 13.3%.
K. Jones / Progress in Planning 60 (2003) 75–92
87
CHAPTER 4 Underground malls One dominant element of Toronto’s retail economy is the underground retailing system (Jones, 1998). Currently, this network of linked retail spaces comprises 33 malls with over 1250 tenants, providing 3 million square feet of commercial space in the downtown. This extensive, inter-linked, network of malls serves the large daytime work force of approximately 200 000 who are employed in the various office complexes in the downtown area. Most of the office buildings are liked directly to these underground commercial spaces, and these, in turn, are linked to a subway system that serves the City of Toronto, and a GO-train commuter railroad system that connects the outer suburbs with the downtown area (Yeates and Jones, 1998). During the 1996– 2001 period, the underground system experienced an average annual vacancy rate of 8.2%. Moreover, over this 6 year period the system experienced a consistent decline in vacancies from a high of 9.8% in 1996 to a low of 5.3% in 2001. This decline reflects the boom economy of the late 1990s and the heavy reliance of the underground merchants on the health of the financial services sector during the period. From a tenant mix perspective, the changing tenant composition of the underground system mirrors the general findings of both shopping centres and commercial strips. Net increases occurred restaurants, financial and personal services, with moderate growth in certain specialty retail activities such as jewellery and men’s fashion. A number of retail
Fig. 8. Average turnover rates for the underground mail system: 1996– 2001.
88
K. Jones / Progress in Planning 60 (2003) 75–92
categories, such as books, women’s fashion, shoes, recreation and sporting goods, exhibit small declines. The spatial variation in vacancy and turnover rates for the underground mall system are illustrated in Figs. 7 and 8. The system experienced an average vacancy of 8.1% over the 6 years of study. As Fig. 7 illustrates, the vacancy rates ranged from a low of 0% to a high of 77% for the 33 mall properties. In general, the smaller, more peripheral malls in the underground complex experienced higher vacancies—due undoubtedly to poor access to the main concentrations of the daytime workforce, and limited access to the main flow of consumer traffic. Fig. 8 depicts the annual tenant turnover rates in the underground complex. On average, 17.8% of the tenants turned over on an annual basis. The pattern of tenant turnover was more regular and ranged from a high of 100% to a low of less than 6%. More importantly, the five larger properties in the system (i.e. those directly linked to the head offices of the five major banks) experienced much lower turnover rates (i.e. in the 8% range).
K. Jones / Progress in Planning 60 (2003) 75–92
89
CHAPTER 5 Power centres The recent establishment of big-box retailers and associated power centres has altered dramatically the competitive retail landscape of the Greater Toronto Area (Jones and Doucet, 2001). Big-box activity exploded onto the GTA scene in the early 1990s. They include a variety of retail forms that are based on: low prices, achieved through low land costs (often unused industrially zoned land) and labour inputs, and/or, a wide selection of brand-name merchandise in large stores monitored minute-by-minute with highly computerized sales/inventory/ordering systems. Their real innovation lies, therefore, with the magnitude of the scale economies of their enterprises, which, in the first flush of competition, generate enormous efficiency advantages over smaller operators. Power centres are essentially commercial real estate developments consisting of two or more bigboxes sharing the same parking facilities. The concentration of big-boxes into power centres is basically a post-1994 phenomenon, though Crossroads Power Centre (Weston Rd/401), established in 1987, is generally regarded as the first power centre in the GTA. The number power centres in the Toronto region increased from 22 in 1996 to 49 in 2001, and the number of power centre tenants has increased four fold (Table 1). The growth of this retail form has been dramatic and has provided direct competition to the existing shopping centre system. By 2001, power centres in the GTA contributed over 1000 stores to the retail inventory and accounted for over 17 million square feet of space. Over the 1996 –2001 period, vacancy rates in power centres averaged 5.5%—the lowest for any retail format. This relatively low value reflects the continual demand for power centre space over the later half of the 1990s and the associated market growth in suburban areas of the in the GTA—the principal source of demand for the power centre retailers. From a structural perspective, the power centres show growth in virtually every category. But, unlike the other three commercial forms, much of the growth is associated with retail activity. Sectors of major growth include housewares, women’s clothing, other retailing, other clothing (unisex), men’s clothing, shoes, general merchandise (Wal-Mart), books and hardware (Home Depot), as well as family style restaurants. Thus, power centres have become significant nodes of retail activity, while planned shopping centres and commercial strips have become more service-oriented. Since 2000, however, power centres have begun to augment their retail offerings with a limited assortment of business and personal services. Fig. 9 provides evidence of the general health and distribution of power centres in the Toronto region. Power centres are primarily a suburban phenomenon, with most of the locations situated in close proximity to major expressways. Initially, they were located to serve the expanding residential markets in the outer suburbs of the GTA, but increasingly some new power centres have emerged in more central locations where developers have taken advantage of the availability of low cost parcels of vacant industrial properties. The sequence of occupancy is quite simple—as the economy restructured and industrial firms left the Toronto area in the early 1990s, a number of relatively low cost industrially zoned parcels were converted to power centres without much planning opposition due to the need
90
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 9. Average turnover rates for power centres: 1996–2001.
to re-cycle the properties. There is also a tendency for power centres to cluster at major expressway/highway intersections, creating power nodes. Power nodes, being composites of power centres, are undoubtedly the big-box related innovative wrinkle of the early 21st century. They encompass nearly all types of consumer services—retail stores, general services (particularly entertainment and restaurants), and the broad range of consumer-oriented financial services. Power centres within major power nodes are, in particular, being planned by developers to include major retail and entertainment anchors that will (hopefully) generate crossover shopping/spending (that is, externalities). Thus, whereas malls are designed to generate externalities through internal pedestrian traffic flow, power centres within some nodes are now being designed to generate externalities in what has hitherto been a single-purpose, entirely auto-oriented, destination environment. Since power centres are a relatively new feature on the commercial landscape, and many of the existing centres are still underdevelopment, an assessment of vacancy rates has not been undertaken for this class of property. However, turnover rates have been examined (Fig. 9). Though turnover rates are generally quite low—ranging from a low of 0% to a high of 20%—there are some distinct spatial variations. The highest turnover rates are associated with a set of power centres in the southwest area of the region, and in the area of the Highway 7-400 power node in the northwest. This tendency appears to reflect a more competitive big-box (power centre) environment in the western portion of the GTA.
K. Jones / Progress in Planning 60 (2003) 75–92
91
CHAPTER 6 Conclusion This paper has provided two distinct outcomes. First, the results provide new insights into the dynamics of the urban consumer services sector. The analysis of the Toronto region has revealed the complex nature and the speed of change that operates within a contemporary metropolitan consumer service economy—particularly consequent to the new big-box/power centre commercial innovation. More importantly, the use of disaggregate information permits identification of the extremes in both the permanence and the functional structure of our commercial strips, shopping centres, and power centres. The results of the study reinforce the need for policy makers, investors, retail analysts and urban planners to develop a greater spatial understanding of the variability and speed of change of the urban service economy. Frequently, policies and investment decisions that relate to commercial environments are made without detailed knowledge of the economic health and direction of change. Secondly, the paper illustrates the importance of business/commercial geomatics and large longitudinal, spatial databases as necessary prerequisites for informed decisionmaking. What is required is the discipline and allocation of resources to create and maintain annual inventories of the commercial economy and link these with other socioeconomic databases. When these databases are fused, powerful insights can be generated on a year-over basis and the dynamics of the commercial spatial economy can be traced, interpreted and projected.
References Doucet, M., Jones, K., 1997. Shopping centre dynamics in the Greater Toronto Area, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 97-4. Eppli, M.J., Laposa, S.P., 1997. A descriptive analysis of retail real estate markets at the metropolitan level. Journal of Real Estate Research 14 (3), 321 –338. Insausti, R., Erguden, T., Jones, K., 2000. Geryfield shopping centres: myth or reality?, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 2000-11. Jones, K., 1998. Retail Dynamics in the Toronto Underground System, 1993–1997, Centre for the Study of Commercial Activity, Ryerson, Toronto, RP 98-11. Jones, K., Doucet, M., 2001. The big-box, the flagship, and beyond: impacts and trends in the Greater Toronto Area. The Canadian Geographer 45 (4), 494– 512. Schell, E., 1964. Changes in Boston’s Retail Landscape, National Merchants Association, New York. Shaw, G., 1978. Process and Pattern in the Geography of Retail Change with Special Reference to Kingstonupon-Hull: 1880–1950, Occasional Papers in Geography No. 24, Department of Geography, University of Hull, Hull, UK. Sibley, D., 1976. The Small Shop in the City, Occasional Papers in Geography No. 22, Department of Geography, University of Hull, Hull, UK. Simmons, J.W., 1964a. The Changing Pattern of Retail Location, Department of Geography, University of Chicago, Chicago, RP #92. Simmons, J.W., 1964b. Toronto’s Changing Retail Complex: A Study of Growth and Blight, Department of Geography, University of Chicago, Chicago, RP #104.
92
K. Jones / Progress in Planning 60 (2003) 75–92
Simmons, J., Simmons, S., 1997. The changes in retail strips: Metro Toronto 1993–1996, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 97-12. Simmons, J., Yeates, M., 1998. Toronto: commercial structure and change. Progress in Planning 50 (part 4), 253 –272. Yeates, M., 2000. The GTA@Y2K, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 2001-1. Yeates, M., Jones, K., 1998. Rapid transit and commuter rail induced retail development. Journal of Shopping Centre Research 5 (2), 7 –38. Yeates, M., Montgomery, D., 1999. The changing commercial structure of non-metropolitan urban centres and vacancy rates. Canadian Geographer 43 (4), 382–399.
Spatial fluctuations in the health of the consumer services sector within a metropolis: a business/commercial geomatics analysis Ken Jones Centre for the Study of Commercial Activity, Ryerson University, 350 Victoria Street, Toronto, Ont., Canada M5B 2K3
Issues related to data aggregation have typically limited detailed spatial analyses of the supply-side of the consumer service sector of the economy. The major restriction has been the lack of disaggregated, longitudinal data below the metropolitan level (Eppli and Laposa, 1997). Thus, it has been difficult to examine even downtown/inner city/suburban changes in the supply-side of the commercial sector. This paper extends previous analyses by examining the spatial dynamics of the urban consumer service economy at a microgeographic scale (Simmons and Yeates, 1998). Three metrics of change have been chosen to reflect the fluctuations in ‘health’ of over a thousand commercial shopping districts or nodes in a large metropolitan region These concentrations serve a variety of functions that are associated with the consumer services sector. In general, each of these shopping areas incorporates some combination of retailing, financial, personal and business service activities. The urban commercial economy under investigation comprises approximately 50 000 stores that are located within the confines of the Greater Toronto Area (GTA). A database, collected on an annual basis between 1996 and 2001, permits monitoring of the spatial fluctuations at a variety of scales within the Toronto region. In this paper, three measures are used to examine change: (i) vacancy rates; (ii) business type; and (iii) the number of store/tenant turnovers. By examining both spatial and temporal variations in these attributes across an entire urban system, it is possible to examine the variability and volatility of an urban retail/commercial landscape across a number of dimensions, and provide insights into a variety of social and economic issues. These can include the health of local neighborhoods and the impact of new retail formats, and the relative performance of different retail real estate assets and classes. E-mail address: [email protected] (K. Jones). 0305-9006/03/$ - see front matter q 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0305-9006(02)00092-2
76
K. Jones / Progress in Planning 60 (2003) 75–92
The early literature of urban retail change can be traced to the empirical findings of researchers in the 1960s and 1970s. Simmons (1964, 1966) developed a model that examined the associations between urban retail growth and various socio-economic correlates for Metropolitan Toronto. Retail change was linked to a complex set of temporal and spatial variables that took into account variations in income, technological developments, and shifts in demography. These factors affected consumer behaviours and preferences and led to adjustments in the composition and growth of local retail areas. Schell (1964) examined urban retail change in Boston, while both Sibley (1976) and Shaw (1978) examined the long-term patterns of retail change for a selected urban case in Britain. In these latter two studies, changes in the retail pattern were viewed as the outcome of the aggregate adaptive behaviours of independent retailers and multi-unit chains to changes in the retail environment. More recently, Simmons and Simmons (1997) examined retail change for a four-year period for a set of 174 retail strips within Metropolitan Toronto. This study concluded that the economic role of strips was shifting toward the service sector; growth in retail strips took place in and around the downtown core and in the larger, more specialized strips; and the turnover rates of retailers in strips approached 15%. Finally, Yeates and Montgomery (1999) provide one of the few studies that examine a set of supply side indicators of retail change for some smaller urban centres. This study concluded that the overall high levels of vacancy and volatility of the local retail system was an indicator of over-storing and reflected a complex set of factors that included nearness to a major metropolitan market, new forms of direct competition, and shifts in the health of the local economy.
K. Jones / Progress in Planning 60 (2003) 75–92
77
CHAPTER 1 The data The data used in the analysis are collected and maintained by the Centre for the Study of Commercial Activity at Ryerson University. Since 1996, an annual survey has been undertaken for the consumer services sector within the Greater Toronto Area. Table 1 provides a description of the size of this database in terms of number shopping areas and stores for four distinct shopping environments—retail streets (strips), shopping centres, underground malls, and power centres. For data collection purposes, each retail area is located and then its areal dimensions are defined. Then, for each outlet/store, data are collected with respect to its business type (Standard Industrial Classification code), business name, address, selling area, and ethnicity. This database is then geo-coded and digital maps of the retail structure and retail change are generated. This spatial database permits the monitoring of retail change at a variety of spatial scales, and for specific business types. In this paper, the tenant data has been aggregated to retail concentrations in order to provide measures of retail change for each of the four distinct retail environments over a 6 year period (Table 2). Table 1 provides an overview of the dimensions and general characteristics of the database. Since 1996, this database has increased in size as a result of two factors—new construction activity (such as power centres and underground malls), and an increase in areal extent of the data collection with the inclusion of suburban retail streets and convenience shopping centres. The resultant database captures the retail/commercial structure of major retail streets, all shopping centres in excess of 50 000 ft2 of gross leasable area, the underground mall system, and the network of power centres within the Greater Toronto Area. For each of these retail types, information can be generated for the tenant mix, turnover rates and vacancy levels on a property-by-property basis. The specific objective of the paper, therefore, is to explore the dynamics of retail change for each of the four retail environments in the Greater Toronto Area (GTA) for the 1996 –2001 period. For each property class, changes in the vacancy rates, business composition and turnover rates are assessed. As part of this evaluation, GIS (Geographic Information Systems) has been used to analyze and interpret the general patterns of change Table 1 Retail composition in the GTA Year
No. of Retail streets (strips)
No. of Stores
No. of Shopping centres
No. of Stores
No. of Underground malls
No. of Stores
No. of Power centres
No. of Stores
1996 1997 1998 1999 2000 2001
212 212 260 278 301 302
17 18 21 22 24 24
537 570 609 637 663 676
17 19 20 21 22 22
24 24 30 33 33 33
1115 1135 1252 1276 1291 1291
22 26 34 39 39 49
270 354 510 767 885 1043
973 401 001 734 465 981
484 514 808 387 014 181
78
K. Jones / Progress in Planning 60 (2003) 75–92
Table 2 Vacancy rates by retail environment: 1996–2001 Year
Retail streets (strips) (%)
Shopping centres (%)
Underground malls (%)
Power centres (%)
1996 1997 1998 1999 2000 2001
9.7 9.3 9.2 9.1 9.3 8.8
9.5 10.3 10.8 10.6 9.9 9.1
9.8 9.2 8.9 8.1 7.4 5.3
4.6 5.7 4.7 5.4 5.4 6.9
Average
9.2
10.0
8.1
5.5
that are shaping the urban commercial economy in the GTA. The results of the analysis may be used for comparative purposes and bench-marking in other metropolitan areas that are undergoing rapid market growth and significant commercial innovation.
K. Jones / Progress in Planning 60 (2003) 75–92
79
CHAPTER 2 Commercial strips Commercial strips present a paradox for while turnover rates, and levels of vacancy for individual properties, often appear high, many strips appear surprisingly healthy. This is probably because they are often able to expand and contract rather easily. This rapidity of change reflects the special role that retail strips play within the urban retail system, and the vulnerability of independent retailers and commercial outlets to shifts in local market conditions. From a structural perspective, commercial strips comprise a variety of types. Across the GTA, collectively they account for approximately 25 000 business locations and contribute approximately 30 million square feet of selling space to the commercial inventory (Yeates, 2000). In aggregate, these retail streets represent the most complex urban shopping classification. They can comprise major shopping streets (for example, Yonge Street in downtown Toronto); ethnic retail concentrations (such as St Clair Avenue West), specialized retail areas (for example, trendy Queen Street West), fashionable shopping districts (such as in the Yorkville district); ‘historic’ downtowns (such as ‘Main Street’ Unionville or Newmarket); and small neighborhood shopping streets. The Toronto area is well served by these shopping areas that in total contribute approximately one quarter of the retail space in the urban area. Moreover, as Simmons and Simmons (1997) have noted, these unplanned districts reflect the local demographic and socio-economic characteristics of their respective communities. During the 6 year period under investigation, commercial strips have, in the aggregate, experienced a remarkably stable vacancy rate of 9.2% (Table 2). However, as Table 3 indicates, over this period the composition of the retail strips in the Toronto region changed dramatically. In total, six categories (restaurants, personal services, other retailing, business services, hair and beauty, and health services) added over 4000 stores to the retail street inventory. More importantly, these six sectors accounted for approximately 70% of the new retail development along the strips during the study period. Clearly, the fabric of commercial strips in the Toronto area has experienced radical change. In almost every strip, retailing is being replaced with services. In many cases, non-retailing functions such as restaurants and various personal and business services now dominate. The spatial variation in vacancy and turnover rates is, however, considerable throughout the GTA. In Figs. 1 and 2, the symbols used to reflect the vacancy and turnover rates are over-laid on a map that illustrates the size of each retail area (measured in terms of the number of stores). Fig. 1 indicates the average vacancy rates for the 1996– 2001 period—the spatial variability in the overall pattern of vacancy rates is considerable. For the individual strips, the average annual vacancy rates vary from a low of 0% to a high of 32%. Moreover, certain areas of the city exhibit consistently high vacancies. For example, east of the downtown core a cluster of strips exhibited vacancies in the 24% range over the 6 year period under investigation. This high rate of change in the area is associated with the changing local market as the area shifts from low income residential to an area of new
80
K. Jones / Progress in Planning 60 (2003) 75–92
Table 3 Net retail change by category: 1996–2001 Sector
Strips
Shopping centres
Underground malls
Power centres
Book and stationery stores Business services Cleaners Drug stores Financial and insurance industries Florists lawn and garden centres Food/grocery Food and beverage services General merchandise Hair and beauty services Hardware stores Health services Household and appliance stores Jewellery stores Liquor Men’s clothing Music stores Other clothing and fabric stores Other retail Personal and household services Recreational services Shoe stores Sporting goods Women’s clothing
32 540 127 52 272 52 243 1142 37 533 44 445 436 56 39 222 28 102 636 722 199 5 42 84
242 174 132 75 231 20 359 737 98 434 214 418 263 147 30 2147 9 87 301 344 130 11 6 93
28 4 4 21 21 2 17 72 8 9 10 10 27 10 1 7 0 8 48 17 22 22 22 24
20 5 5 4 15 21 13 160 20 15 15 15 80 4 4 34 4 50 38 4 34 30 11 39
Total stores
5846
3896
222
618
condominiums for ‘young urban professionals’. Other areas of high vacancy rates area associated with the lower income areas to the north and west of the core area. For many of these neighborhood shopping streets, annual vacancy rates are in excess of 25%. Fig. 2 indicates the average turnover rates for the 1996– 2001 period. Turnovers provide a clear measure of the volatility of the urban retail system—in general, the average annual turnover rate in the GTA is 14.7%. Noteworthy is the constant pattern of turnover across the region—80% of the commercial strips in the Toronto region experienced yearly turnover rates between 10 and 20%. These rates do not appear to be clustered in any particular part of the metropolitan region—high and low rates occur in suburban areas as randomly as they appear to occur in the city.
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 1. Average vacancy rates for retail strips: 1996–2001.
Fig. 2. Average turnover rates for retail strips: 1996–2001.
81
82
K. Jones / Progress in Planning 60 (2003) 75–92
CHAPTER 3 Shopping centres The shopping centre system in the GTA comprises approximately 650 centres (with more than 30 000 ft2 of commercial space) and 21 000 stores. These malls, accounting for approximately 75 million square feet of space, form a hierarchy of planned centres according to size and function. In general, there are five classes of centres: convenience, neighborhood, community, regional, and super-regional (Doucet and Jones, 1997). Although these centres dominate the consumer service sector in the GTA (as malls do in every North American metropolis), their primacy, after 50 years of growth, is now being threatened, and some mall closures, or transformations, have occurred. Several factors have been cited as being associated with these closures and transformations. These include: competition from big-box retailers, particularly since 1990; over-saturation of the North American market with commercial space; the emergence of e-tailing; and changes in consumer shopping behaviours and preferences. Under-performing and/or declining shopping centre properties are often referred to as greyfield properties (Insausti et al., 2000). Typical signs of declining health include: (1) high vacancies; (2) increases in tenant turnovers; (3) loss of anchor tenants and national chains; and (4) decline and/or lack of reinvestment in the physical structure of the malls. From 1996 to 2001, shopping centres in the GTA experienced an average vacancy rate of 10% (Table 2). However, when malls are examined according to their size, major variations in vacancy rates are noted. There is a significant change in vacancy rates between malls above and below 700 000 ft2, with the vacancy rate of large regional malls normally below 6%. Changes in the composition of tenant mix of the shopping centres are less pronounced than experienced in commercial strips (Table 3). Moreover, three retail categories actually showed a net decline in the number of mall stores—men’s fashion, book and hardware stores. These decreases were the direct outcome big-box competition in the case of books and hardware, and a major decline in fashion spending in the case of men’s fashion. Major increases were noted in the following sectors—restaurants, hair and beauty, health services, food retailing, personal services, other retailing, housewares and financial services. These eight categories accounted for 77% of the net change in shopping centre tenants and reflect the increase in convenience-oriented shops and a major shift toward services across the entire urban shopping centre network. Major spatial variations occur in the health and stability of the shopping centre system. In Figs. 3 – 7, centre size is linked to symbols that are used to indicate average vacancy and turnover rates across the network of shopping centres. For clarity, the shopping centre system is subdivided into two classes: those with less than 1 000 000 ft2 of commercial space, generally referred to as convenience and neighborhood centres; and those with more than 100 000 ft2, generally referred to as community and regional centres.
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 3. Average vacancy rates for shopping centres , 100,000 square feet: 1996– 2001.
Fig. 4. Average vacancy rates for shopping centres . 100,000 square feet: 1996–2001.
83
84
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 5. Average turnover rates for shopping centres , 100,000 square feet: 1996–2001.
Fig. 6. Average turnover rates for shopping centres . 100,000 square feet: 1996–2001.
K. Jones / Progress in Planning 60 (2003) 75–92
85
Fig. 7. Average vacancy rates for the underground mail system: 1996–2001.
Fig. 3 presents the average vacancy rates for the 1996 – 2001 period for the 442 smaller centres within the urban area. Although these malls record an average vacancy rate of 9.6%, there is considerable spatial variability, with pockets of higher vacancies noted in the eastern and northern suburbs, and smaller centres in the central area exhibiting lower vacancy rates. Fig. 4 illustrates the pattern of vacancies for the set of 159 larger centres. The distribution of the vacancy rates for these malls exhibits a much more regular pattern and surprisingly, in aggregate, the larger malls experienced a higher average vacancy of 10.5%. Upon closer inspection, for this larger category, the pattern of vacancies is somewhat bipolar. Twelve malls experienced extremely high vacancy rates—in excess of 27%. Typically, these malls are situated in the suburban areas and tended to serve either new developing residential markets, or are located in highly competitive clusters. Conversely, the 10 large super-regional malls (those in excess of 900 000 ft2) consistently exhibited vacancy rates in the 5% range. This trend points out the obvious importance of accessibility and shopping centre attraction to the overall success of planned shopping centres. The annual turnover rate for the entire of shopping centre network was approximately 16% for the 1996– 2001 period. Unlike vacancy rates, the spatial variation in turnover rates is similar for both large and small malls (Figs. 5 and 6). In both cases, approximately 25% of the centres had turnover rates in excess of 20%.
86
K. Jones / Progress in Planning 60 (2003) 75–92
However, upon closer inspection, a larger proportion of the small centres (21.8%) had annual tenant turnovers of less than 10%, while for the larger centres this figure decreased to 16.3%. It should be noted that tenant turnovers in many instances could be viewed as a good thing as the need to refresh retail properties is constant as both market and competitive pressures are always in flux. This is particularly evident with the group of super-regional malls that collectively experienced a relatively high annual turnover of 13.3%.
K. Jones / Progress in Planning 60 (2003) 75–92
87
CHAPTER 4 Underground malls One dominant element of Toronto’s retail economy is the underground retailing system (Jones, 1998). Currently, this network of linked retail spaces comprises 33 malls with over 1250 tenants, providing 3 million square feet of commercial space in the downtown. This extensive, inter-linked, network of malls serves the large daytime work force of approximately 200 000 who are employed in the various office complexes in the downtown area. Most of the office buildings are liked directly to these underground commercial spaces, and these, in turn, are linked to a subway system that serves the City of Toronto, and a GO-train commuter railroad system that connects the outer suburbs with the downtown area (Yeates and Jones, 1998). During the 1996– 2001 period, the underground system experienced an average annual vacancy rate of 8.2%. Moreover, over this 6 year period the system experienced a consistent decline in vacancies from a high of 9.8% in 1996 to a low of 5.3% in 2001. This decline reflects the boom economy of the late 1990s and the heavy reliance of the underground merchants on the health of the financial services sector during the period. From a tenant mix perspective, the changing tenant composition of the underground system mirrors the general findings of both shopping centres and commercial strips. Net increases occurred restaurants, financial and personal services, with moderate growth in certain specialty retail activities such as jewellery and men’s fashion. A number of retail
Fig. 8. Average turnover rates for the underground mail system: 1996– 2001.
88
K. Jones / Progress in Planning 60 (2003) 75–92
categories, such as books, women’s fashion, shoes, recreation and sporting goods, exhibit small declines. The spatial variation in vacancy and turnover rates for the underground mall system are illustrated in Figs. 7 and 8. The system experienced an average vacancy of 8.1% over the 6 years of study. As Fig. 7 illustrates, the vacancy rates ranged from a low of 0% to a high of 77% for the 33 mall properties. In general, the smaller, more peripheral malls in the underground complex experienced higher vacancies—due undoubtedly to poor access to the main concentrations of the daytime workforce, and limited access to the main flow of consumer traffic. Fig. 8 depicts the annual tenant turnover rates in the underground complex. On average, 17.8% of the tenants turned over on an annual basis. The pattern of tenant turnover was more regular and ranged from a high of 100% to a low of less than 6%. More importantly, the five larger properties in the system (i.e. those directly linked to the head offices of the five major banks) experienced much lower turnover rates (i.e. in the 8% range).
K. Jones / Progress in Planning 60 (2003) 75–92
89
CHAPTER 5 Power centres The recent establishment of big-box retailers and associated power centres has altered dramatically the competitive retail landscape of the Greater Toronto Area (Jones and Doucet, 2001). Big-box activity exploded onto the GTA scene in the early 1990s. They include a variety of retail forms that are based on: low prices, achieved through low land costs (often unused industrially zoned land) and labour inputs, and/or, a wide selection of brand-name merchandise in large stores monitored minute-by-minute with highly computerized sales/inventory/ordering systems. Their real innovation lies, therefore, with the magnitude of the scale economies of their enterprises, which, in the first flush of competition, generate enormous efficiency advantages over smaller operators. Power centres are essentially commercial real estate developments consisting of two or more bigboxes sharing the same parking facilities. The concentration of big-boxes into power centres is basically a post-1994 phenomenon, though Crossroads Power Centre (Weston Rd/401), established in 1987, is generally regarded as the first power centre in the GTA. The number power centres in the Toronto region increased from 22 in 1996 to 49 in 2001, and the number of power centre tenants has increased four fold (Table 1). The growth of this retail form has been dramatic and has provided direct competition to the existing shopping centre system. By 2001, power centres in the GTA contributed over 1000 stores to the retail inventory and accounted for over 17 million square feet of space. Over the 1996 –2001 period, vacancy rates in power centres averaged 5.5%—the lowest for any retail format. This relatively low value reflects the continual demand for power centre space over the later half of the 1990s and the associated market growth in suburban areas of the in the GTA—the principal source of demand for the power centre retailers. From a structural perspective, the power centres show growth in virtually every category. But, unlike the other three commercial forms, much of the growth is associated with retail activity. Sectors of major growth include housewares, women’s clothing, other retailing, other clothing (unisex), men’s clothing, shoes, general merchandise (Wal-Mart), books and hardware (Home Depot), as well as family style restaurants. Thus, power centres have become significant nodes of retail activity, while planned shopping centres and commercial strips have become more service-oriented. Since 2000, however, power centres have begun to augment their retail offerings with a limited assortment of business and personal services. Fig. 9 provides evidence of the general health and distribution of power centres in the Toronto region. Power centres are primarily a suburban phenomenon, with most of the locations situated in close proximity to major expressways. Initially, they were located to serve the expanding residential markets in the outer suburbs of the GTA, but increasingly some new power centres have emerged in more central locations where developers have taken advantage of the availability of low cost parcels of vacant industrial properties. The sequence of occupancy is quite simple—as the economy restructured and industrial firms left the Toronto area in the early 1990s, a number of relatively low cost industrially zoned parcels were converted to power centres without much planning opposition due to the need
90
K. Jones / Progress in Planning 60 (2003) 75–92
Fig. 9. Average turnover rates for power centres: 1996–2001.
to re-cycle the properties. There is also a tendency for power centres to cluster at major expressway/highway intersections, creating power nodes. Power nodes, being composites of power centres, are undoubtedly the big-box related innovative wrinkle of the early 21st century. They encompass nearly all types of consumer services—retail stores, general services (particularly entertainment and restaurants), and the broad range of consumer-oriented financial services. Power centres within major power nodes are, in particular, being planned by developers to include major retail and entertainment anchors that will (hopefully) generate crossover shopping/spending (that is, externalities). Thus, whereas malls are designed to generate externalities through internal pedestrian traffic flow, power centres within some nodes are now being designed to generate externalities in what has hitherto been a single-purpose, entirely auto-oriented, destination environment. Since power centres are a relatively new feature on the commercial landscape, and many of the existing centres are still underdevelopment, an assessment of vacancy rates has not been undertaken for this class of property. However, turnover rates have been examined (Fig. 9). Though turnover rates are generally quite low—ranging from a low of 0% to a high of 20%—there are some distinct spatial variations. The highest turnover rates are associated with a set of power centres in the southwest area of the region, and in the area of the Highway 7-400 power node in the northwest. This tendency appears to reflect a more competitive big-box (power centre) environment in the western portion of the GTA.
K. Jones / Progress in Planning 60 (2003) 75–92
91
CHAPTER 6 Conclusion This paper has provided two distinct outcomes. First, the results provide new insights into the dynamics of the urban consumer services sector. The analysis of the Toronto region has revealed the complex nature and the speed of change that operates within a contemporary metropolitan consumer service economy—particularly consequent to the new big-box/power centre commercial innovation. More importantly, the use of disaggregate information permits identification of the extremes in both the permanence and the functional structure of our commercial strips, shopping centres, and power centres. The results of the study reinforce the need for policy makers, investors, retail analysts and urban planners to develop a greater spatial understanding of the variability and speed of change of the urban service economy. Frequently, policies and investment decisions that relate to commercial environments are made without detailed knowledge of the economic health and direction of change. Secondly, the paper illustrates the importance of business/commercial geomatics and large longitudinal, spatial databases as necessary prerequisites for informed decisionmaking. What is required is the discipline and allocation of resources to create and maintain annual inventories of the commercial economy and link these with other socioeconomic databases. When these databases are fused, powerful insights can be generated on a year-over basis and the dynamics of the commercial spatial economy can be traced, interpreted and projected.
References Doucet, M., Jones, K., 1997. Shopping centre dynamics in the Greater Toronto Area, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 97-4. Eppli, M.J., Laposa, S.P., 1997. A descriptive analysis of retail real estate markets at the metropolitan level. Journal of Real Estate Research 14 (3), 321 –338. Insausti, R., Erguden, T., Jones, K., 2000. Geryfield shopping centres: myth or reality?, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 2000-11. Jones, K., 1998. Retail Dynamics in the Toronto Underground System, 1993–1997, Centre for the Study of Commercial Activity, Ryerson, Toronto, RP 98-11. Jones, K., Doucet, M., 2001. The big-box, the flagship, and beyond: impacts and trends in the Greater Toronto Area. The Canadian Geographer 45 (4), 494– 512. Schell, E., 1964. Changes in Boston’s Retail Landscape, National Merchants Association, New York. Shaw, G., 1978. Process and Pattern in the Geography of Retail Change with Special Reference to Kingstonupon-Hull: 1880–1950, Occasional Papers in Geography No. 24, Department of Geography, University of Hull, Hull, UK. Sibley, D., 1976. The Small Shop in the City, Occasional Papers in Geography No. 22, Department of Geography, University of Hull, Hull, UK. Simmons, J.W., 1964a. The Changing Pattern of Retail Location, Department of Geography, University of Chicago, Chicago, RP #92. Simmons, J.W., 1964b. Toronto’s Changing Retail Complex: A Study of Growth and Blight, Department of Geography, University of Chicago, Chicago, RP #104.
92
K. Jones / Progress in Planning 60 (2003) 75–92
Simmons, J., Simmons, S., 1997. The changes in retail strips: Metro Toronto 1993–1996, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 97-12. Simmons, J., Yeates, M., 1998. Toronto: commercial structure and change. Progress in Planning 50 (part 4), 253 –272. Yeates, M., 2000. The GTA@Y2K, Centre for the Study of Commercial Activity, Ryerson University, Toronto, RP 2001-1. Yeates, M., Jones, K., 1998. Rapid transit and commuter rail induced retail development. Journal of Shopping Centre Research 5 (2), 7 –38. Yeates, M., Montgomery, D., 1999. The changing commercial structure of non-metropolitan urban centres and vacancy rates. Canadian Geographer 43 (4), 382–399.