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The magnetism of suburban
shopping centers: do size and
Cineplex matter?
Joseph T.L. Ooi and Loo-Lee Sim
Department of Real Estate, National University of Singapore, Singapore
Do size and
Cineplex matter?
111
Received January 2006
Accepted September 2006
Abstract
Purpose – This paper aims to address two questions related to the magnetism or drawing power of
suburban malls: first, does physical size matter, and second, what is the externalities effect of housing
a Cineplex within a shopping center?
Design/methodology/approach – The study was carried out through an extensive survey
covering 1,283 shoppers in nine selected suburban shopping centers in Singapore. The effects of
physical size and the presence of Cineplex on the magnetism on the selected suburban shopping
centers are evaluated using analysis of variance (ANOVA) tests. Their effect on shopping
duration and expenditure pattern is also empirically tested using a recursive simultaneous
equations model.
Findings – The survey results affirm that both physical size and the presence of a Cineplex enhance
the magnetism of suburban shopping centers. A larger shopping center can facilitate a greater variety
of shops and create a more pleasant environment for the shoppers, thus enticing shoppers to visit and
stay longer. Cinema patrons prefer to watch movies at Cineplex located in shopping centers.
Controlling for the endogenous relationship between duration of visit and amount spent in the
shopping center, the regression results show that, while physical size and Cineplex have a positive
effect on the duration of visit, they do not necessarily have a direct effect on the amount spent by the
patrons in the shopping center.
Originality/value – One of the main challenges for mall owners and managers located outside the
traditional shopping belt is how to attract shoppers to patronize their malls. While the impact of
shopping center size on retail rents and center attractiveness has been addressed in the literature, this
paper adds some new insights into the field. The focus on whether the presence of a cinema complex
within a shopping center affects its magnetism or not is novel.
Keywords Shopping centres, User studies, Consumer behaviour, Cinema, Singapore
Paper type Research paper
I. Introduction
The proliferation of shopping centers outside the traditional shopping belt is
happening across the world. The first suburban enclosed shopping center in the
USA, called Southdale Mall, was opened near Minneapolis in 1956 (Eppli and
Benjamin, 1994). Over the years, shopping centers have grown larger and their
one-stop convenience having expanded to include service outlets and entertainment
providers. These neighborhood and community shopping centers offer an
The authors acknowledge Mark Eppli, the two reviewers and participants at the 2005 American
Real Estate Society Meeting in Santa Fe, USA for their comments and feedback on an earlier
draft of this paper. They would also like to thank Ivy Loh, Pearl Lok, Larrisa Lim, Eileen Chen
and Samantha Seow for their assistance with the data coding and processing.
Journal of Property Investment &
Finance
Vol. 25 No. 2, 2007
pp. 111-135
q Emerald Group Publishing Limited
1463-578X
DOI 10.1108/14635780710733816
JPIF
25,2
112
environmentally controlled protected setting with an array of services, from post
offices, medical services, and transient and permanent housing, to entertainment,
including theaters, and even amusement parks and suburbia. They offer shoppers
an attractive sanitized urban experience, but without the associated negatives such
as traffic congestion or crime and security issues in traditional shopping districts
(Bloch et al., 1994; Roulac, 1994; Erkip, 2003). Suburban shopping centers have
indeed become more than a retail place for the local community. In Singapore, they
have significantly altered the residents’ lifestyle with their tenant mix of customary
retail shops, entertainment outlets, cinemas, public library, and food courts (Ibrahim
and Ng, 2002).
An important issue face by owners and managers of suburban shopping centers
is how to attract shoppers to patronize their malls, especially when they are located
outside the primary shopping belt. Convenience, although usually having the largest
impact, is by no means the sole determinant of shopping center choices (Severin
et al., 2001). While the retail sales are normally related positively to the income level
and demographic characteristics of the population in their immediate market, this
relationship may be confounded by outshoppers, which are defined as consumers
who move across markets (Russel, 1957; Lillis and Hawkins, 1974; Anderson and
Kamisky, 1985). Hence, shopping malls that create an appropriate appeal can
themselves become destination attractions. The mega-sized Mall of America in
Minnnesota, for example, is reported to have drawn one-third of its visitors to travel
more than 150 miles to reach the mall (Roulac, 1994). Similarly, the West Edmonton
Mall in Alberta was reported to have become Canada’s top tourist attractions with
its 800 stores, 110 restaurants, and 400,000 square feet theme park (Bloch et al.,
1994). Given that the entertainment motive has become more important in enhancing
shoppers’ experience in the recent years, Cineplex are now commonly located within
suburban shopping centers.
This paper focuses on the magnetism of suburban shopping centers which,
because of their location, need to provide a sufficiently attractive shopping
experience to offset the distance inertia. In this paper, we gauge the magnetism or
drawing power of suburban shopping centers by their ability to first, promote
frequent visits from local residents, second, entice “outshoppers” to travel to the
mall and finally, encourage both groups to stay longer and spend more during their
visit. The paper addresses two questions related to the magnetism of suburban
shopping centers: first, does their physical size matter, and second, what is the
externalities effect of accommodating a Cineplex within a suburban shopping
center? Reilly’s (1931) Law of Retail Gravitation Model and the extension by Huff
(1964), which modeled the attractiveness of a shopping center as decreasing with
distance and increasing with the size of the shopping center, hypothesize that the
magnetism of a suburban shopping center is a function of its physical size[1]. As one
of the major tenants in term of space occupied, the Cineplex is expected to contribute
to the shopping center by acting as an attractor to increase traffic flow and
consequently, generate positive externality for other stores. However, the success of
Cineplex in generating positive externality for other stores within the shopping
center is still not very clear. This will be related to whether the proprietors of
Cineplex deserved to be charged a lower rental rate than other tenants? This paper is
the first attempt to examine the payoffs associated with housing a Cineplex within a
suburban shopping center.
Our study involves a survey of 1,283 shoppers in nine suburban shopping centers
in Singapore. The results indicate that physical size does matters to the
attractiveness of a suburban shopping center. Whilst mall size, in itself, is ranked
6th in terms of importance, a large-sized shopping center can however facilitate a
greater variety of shops and more anchor tenants, which are ranked as important to
the shoppers. The benefits of having a cinema as an anchor tenant in suburban
shopping centers are also established. In particular, more than 72 percent of those
interviewed feel that the presence of a Cineplex would entice them to visit a
shopping center more often. Playing the role of any attractor, the Cineplex increases
mall traffic and induces more sales for other stores. In the multivariate analysis, we
employ a recursive simultaneous equations model to control for the endogenous
relationship between duration of visit and amount spent in the shopping center. The
estimation results indicate that whilst physical size and Cineplex have a positive
effect on the duration of visit, they only have an indirect effect on the amount spent
by the visitors in the shopping center.
The rest of this paper is structured as follows. In section II, we review previous
studies on the patronage of shopping centers. Section III presents the research plan and
introduces our measurement of the magnetism of shopping centers. Section IV
describes the survey sample. This is followed by a discussion on the size effect in
section V and the Cineplex effect in section VI. Section VII presents the results of our
simultaneous regression on the impact of both factors on the patrons’ expenditure.
Section VIII concludes.
II. Literature review
What do we know about the success factors of shopping centers? The literature has a
lot to say about what makes a shopping center attractive to shoppers. Essentially, both
spatial and non-spatial factors are important. A number of studies have examined their
influence as determinants of shopping center rent (Sirmans and Guidry, 1993; Gatzlaff
et al., 1994; Hardin and Wolverton, 2000). Biba et al. (2006) brings additional insights
into the factors affecting customers’ choice for a shopping centre.
With respect to location, the two most commonly noted determinants of retail
patronage are accessibility and visibility (Simmons, 1992; Ownbey et al., 1994;
Forgey et al., 1995). Size and quality of facilities are also relevant to retail patronage
to the extent that unfavorable design characteristics may negate the attractions of
an accessible and visible site (Brown, 1999). The gravity and potential models have
traditionally been used for defining trading areas surrounding major cities. They
prescribe that shoppers choose which centers to patronize by balancing between the
utility (proxied by the size of the center) and the cost (proxied by distance) of the
center to the shopper. With the growth of the regional shopping center, these “laws”
have been utilized to predict market boundaries between competing retail facilities
within metropolitan areas (Bucklin, 1971). More recently, Eppli and Shilling (1996)
employ a retail gravity model to test the importance of retail agglomeration and
proximity to competition. They estimate aggregate retail sales (Rij) in retail market i
for center j as:
Do size and
Cineplex matter?
113
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Ri;j ¼ Y i *
M aj
Dgi;j
m
X
M ak
k¼j
114
!
Dbi;k
where Mj is the size (in square feet of the jth shopping center, Dij is the distance from
the ith consumer to the jth shopping center, Mk is the size of the kth shopping center,
Dik is the distance from the ith consumer to the kth shopping center, Yi is total retail
expenditures in the trade area, and a, b and g are friction parameters (a low value
for a indicates that shopping center size is of little importance and low values for b
and g means that distance is not inhibiting when selecting a shopping center. Using
actual retail sales at 38 regional shopping centers, the authors find that the retail
sales are largely determined by center size, and to a lesser extent, by proximity to
competition. They find that a decrease in competitive shopping center size of 20
percent increase center J sales by 30 percent to 40 percent. Conversely, a 20 percent
increase in the size of competitive shopping center reduces center J sales by 16
percent to 21 percent. In a recent study on Quebec City, Canada, Des Rosiers et al.
(2005) developed two space-related indices to measure regional and super-regional
shopping centers’ economic potential and centre attraction.
Recent studies have shown that enhancement of shopping experiences through
the employment of exciting trade types and activities can serve as a better magnetic
attraction to shoppers. Non-spatial factors such as retail image and tenant mix are
equally critical in enhancing shopping center patronage[2]. Generally, shopping
center owners expend resources to achieve a right image to draw shoppers (Mejia
and Benjamin, 2002). Similarly, retail mix, which is defined as the combination of
stores occupying a shopping center, affects its overall image, patronage and rentals
(Kirkup and Rafiq, 1994; Gerbich, 1998). The empirical evidence has shown that the
drawing power of a shopping center can be increased by clustering together a large
number of similar stores because of agglomeration benefits (Hotelling, 1929; Miceli
et al., 1998). Tenant placement within a shopping center is also important to extract
maximum rental (Brueckner, 1993). Nelson (1958) and more recently, Eppli and
Shilling (1993) attempted to measure the degree of spillover shopping, or “retail
compatibility” across different types of non-anchor stores. Based on a sample of
stores in 54 shopping centers in the USA, Eppli and Shilling (1993) estimate the
degree of retail compatibility (as measured by percentage of customer interchange)
as follows: highly compatible (. 30 percent), moderately compatible (10-30 percent),
slightly compatible (5-10 percent), incompatible (0 percent) and deleterious (, 0
percent).
Anchor tenants also serve as a major drawing power to a retail mall. According to
Miceli et al. (1998), developers should be interested not just in an individual store’s
profits, but also in the “traffic” it generates, since more traffic will produce larger
spillover benefits (and hence profits) for other types of stores. Hence, shopping
centers usually have one or more department stores, which are typically charged
lower rents, to generate demand for smaller retailers and to insure the success of the
shopping centers (Nevin and Houston, 1980; Eppli and Shilling, 1993; Pashigian and
Gould, 1998; Konishi and Sandfort, 2003). In his seminal paper, Brueckner (1993)
models the rent differential between stores on the basis that tenants differ in their
external generating abilities. Ingene and Ghosh (1990) further suggest that demand
externalities flow only in one direction from anchor tenants to non-anchor tenants.
Roulac (1994), however, note the demise of the competitive strength of traditional
department stores as well as the disinclination of new anchor merchandisers to
locate in shopping centers. Gatzlaff et al. (1994) tried to quantify the impact of a loss
of anchor tenant on the rental rates of 36 neighborhood and community shopping
centers located across Florida and Georgia. They find that a shopping center’s
aggregate rental would reduce by approximately 25 percent due to the loss of an
anchor tenant. An implication of this development is that shopping center owners
need to be more selective as to which tenants should anchor their shopping center to
maximize revenue and minimize attrition rate.
III. Research methodology
Before we examine the influence of mall size and Cineplex, the performance of the
shopping malls need to be defined first. There are numerous ways in which a shopping
center’s performance can be benchmarked – the most direct way would, of course, be
to gauge its profitability through its rental revenue or total receipts from retail sales.
The Urban Land Institute (ULI) and the International Council of Shopping Centers
(ICSC), for example, measure shopping center performance in terms of non-anchor
retail sales per square foot[3]. However, due to confidentiality, we are unable to obtain
the relevant financial data for the selected shopping centers. Other possible
non-monetary performance measures for shopping centers are traffic count, shoppers
and tenants’ satisfaction survey, occupancy and turnover rate. For the purpose of this
study, we gauge the shopping centers’ performance by their magnetism, which is
defined as the ability to attract and retain shoppers. Like the gravitational pull of a
magnet, the attractiveness of a shopping center is measured by its ability to first, pull
shoppers toward the mall and second, to entice them to stay longer and hopefully,
spend more in the shopping center.
An extensive survey was conducted at selected suburban shopping centers in
Singapore over two weeks, between mid to end September 2003. Nine suburban
retail malls were selected for the study, out of which three are located each in the
North, East and West regions of Singapore. The location of the selected shopping
centers is marked in the map presented in Figure 1 together with the location of
Orchard Road, which is the prime shopping belt in Singapore. Easch shopping
center is supported by a specific public housing estate with no competition in the
form of other malls within the nearby area. The exception being Tampines Mall
(29,233 m2) and Century Square (19,517 m2), which are located adjacent to each
other in the same housing estate. For the purpose of this study, we have aggregated
their details and presented them as though they are one shopping center. Acting as
a focal point for the local community, the suburban shopping centers are more like
the community shopping centers in the USA. However, these shopping centers have
greater potential to attract residents from outside their immediate catchments
because they are within easy reach by public transport as they are situated next to a
subway (MRT) station and within walking distance from a major bus interchange.
Basic details of the sampled shopping centers are provided in Table I.
Do size and
Cineplex matter?
115
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116
Figure 1.
Locations of sampled
suburban retail malls
48,750
39,662
37,904
25,986
22,321
19,320
14,891
14,864
27,962
216,100
199,100
211,000
123,500
67,800
136,200
113,100
58,700
140,688
4.4
5.0
5.6
4.8
3.0
7.0
7.6
3.9
5.2
270
175
220
130
108
95
112
93
150
1995
1998
1995
2002
1993
1996
1998
1999
–
2000
1999
Net retail area (m2) Local population Population/m2 of net retail area No. of shops Year open expansion
Source: Authors’ field research, Merrill Lynch (2005), Housing and Development Board (2004)
Tampines Mall and Century Square
Causeway Point
Jurong Point
Compass Point
Junction 8
Lot One Mall
West Mall
Sun Plaza
Mean
Suburban mall
Do size and
Cineplex matter?
117
Table I.
Details of sampled
suburban malls
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The average age of the nine suburban shopping centers in our sample is eight years.
The newest shopping center is four years old, whilst the oldest shopping center was
completed some 13 years ago. Most of the shopping centers are at or close to full
occupancy. All have food court and supermarkets. Eight of the shopping centers have
department store as anchor tenants. Five of the shopping centers have a branch of the
national library and only one mall (Compass Point) does not have a Cineplex. The
average size of the shopping malls is 24,855 m2, ranging from 14,864 m2 to 48,750 m2[4].
The number of shops in the shopping malls varies from 93 to 270, averaging 150
retailers in each shopping center. The average space allocated to each retailer range
from 133 sq m to 227 m2[5], which is comparable to the average size of retail outlets in
New Zealand’s community shopping centers (Gerbich, 1998). On a per m2 basis, the
mean net retail space provided is 0.192 m2 for each resident in the immediate housing
estate. Not surprisingly, the size of the suburban shopping centers is positively related
to the population of the immediate housing estate. For example, the three largest
suburban shopping centers, namely Tampines Mall/Century Square (48,750 m2),
Causeway Point (39,662 m2) and Jurong Point (37,904 m2) are located in the three most
populated public housing estates in Singapore, namely Tampines (216,100 residents),
Woodlands (199,100 residents) and Jurong West (211,000 residents). Conversely, Sun
Plaza, which has only 14,864 m2 of retail space, supports 58,700 residents in the
Sembawang housing estate.
Following the retail gravity models, we hypothesize that the magnetism of a
suburban shopping center increases with the size of the mall. Similarly, the presence
of a Cineplex would enhance the magnetism of a suburban shopping center. The
relationships are tested in two stages. First, we examine the effects of physical size
and the presence of Cineplex on the magnetism of the selected suburban shopping
centers from the survey results. Second, we empirically test their effect on shopping
duration and expenditure pattern using multivariate regression models. In order to
control for the endogenous relationship between duration of visit and amount spent
in the shopping center, a recursive simultaneous equations model is employed as
follows:
EXPENDITURE ¼ f ðSIZE; MOVIE; DURATIONÞ;
ð1Þ
DURATION ¼ f ðSIZE; MOVIE; TRAVELÞ
ð2Þ
where EXPENDITURE is the dollar amount spent on each visit to the shopping
center, DURATION is the time spent in the shopping center, SIZE is the size of the
shopping mall, MOVIE is a binary variable indicating whether the main purpose of
visiting the shopping center is watching a movie, and TRAVEL is the time taken to
reach the shopping center. We also control for the characteristics of the respondents
(age and gender), the day of interview (weekend or weekdays), whether the main
reason for visiting the mall is shopping, whether they are visiting alone or
accompanied by family, relatives or friends and how often they shop and watch
movies. These factors have been found in previous studies to have a significant
influence on shoppers’ spending patterns.
The estimator employed is the full information maximum likelihood. Typical of
models involving expenditure, which are usually censored, equation (1) is estimated
using the “tobit” model. Two fit measures, namely R2ANOVA and R2DECOMPOSITION , are
generated using the full sample of observations. The first fit measure takes the
variance of the estimated conditional mean divided by the variance of the observed
variable. The second measure takes the variance of the conditional mean function
around the overall mean of the data in the numerator, whilst the denominator contains
the sum of the numerator and a residual variance, the true value minus the conditional
mean function (Greene, 2002)[6].
Do size and
Cineplex matter?
119
IV. Description of survey sample
Mall visitors and cinema patrons were randomly intercepted while they were inside the
shopping centers and invited to participate in the survey. To insure that the survey
results are not concentrated on specific group of shoppers based on the timing of their
visits, the interviews were spread out over different days of the week. In total, 1,283
shoppers obliged to our request to be interviewed. The survey sample is composed of
42 percent of interviews conducted over the weekends and 58 percent during
weekdays. The gender of the respondents is also equally distributed with 46 percent of
the respondents being males and 54 percent females. The mall and age distributions of
the interviewees are presented in Figures 2 and 3. Approximately 25 percent of the
respondents were below 20 years of age. The majority (61 percent) fall between the
20-40 years old age group. Respondents above 40 years old constitute another 14
percent of the survey sample.
On the whole, Singaporeans tend to visit shopping center more often – all the
interviewees said they visit a shopping center at least once a month. In comparison,
Figure 2.
Distribution of survey
respondents by malls
Figure 3.
Profile of survey
respondents by age
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120
75 percent of Americans go to a mall at least once a month (Bloch et al., 1994). Figure 4
shows that 63 percent of the respondents visit a shopping center at least once a week,
whilst another 21 percent visit a shopping center once a fortnight. With respect to the
mode of transport, the majority of those interviewed (63 percent) took public transport to
visit the shopping centre. A total of 17 percent walk to the shopping center, while the
remaining 20 percent relied on private transport. Further analysis on the travel time for
various modes of transport reveals that the average travel time is 11.6, 20.1 and 28.4
minutes for those who walk, take their own vehicle and take public transportation,
respectively.
Consistent with the literature which suggests that most shopping trips are
multipurpose (Hanson, 1980; O’Kelly, 1981), most of the respondents indicated more
than one activity for making a trip to a shopping center. The three most popular
activities are spending time with family and friends (57.7 percent), patronizing the
shops (52.7 percent) and having meals (46.0 percent). Table II tabulates the main
reasons given for visiting suburban shopping centers. Overall, the results indicate that
the suburban malls are more than a place to shop and leisure activities are equally
prominent in the visitors’ agenda of activities to do in a shopping center. One in four of
those surveyed indicate that they were at the shopping center to catch a movie, whilst
another 20.4 percent were at the shopping center to use ancillary services such as using
toilet, banking, postal and library facilities provided within the shopping center. As a
further indication of the social role of the suburban shopping center in providing
leisure and complementary facilities for the community, 88 percent of those surveyed
indicate that they are normally accompanied by their friends and family or relatives
Figure 4.
Frequency of visits to
shopping centers
Reasons
Table II.
Main reasons for visiting
a suburban shopping
center
1.
2.
3.
4.
5.
% of responses
Walk around
Shopping
Eating
Watching movie
Ancillary services
Source: Authors’ survey
57.7
52.7
46.0
25.2
20.4
when visiting suburban shopping centers. Shopping centers serve as an important
socializing and meeting place with family and friends.
Table III shows the visiting and shopping patterns of those interviewed,
sub-categorized by their age, gender and time taken to reach the shopping center.
Those in the 20-40 age groups took the longest time to travel to the shopping center.
74.8 percent of the respondents take less than 30 minutes. They are likely to be those
who stay in close proximity to the shopping center and therefore, fall within the local
retail market boundary of the individual shopping centers. The 25.2 percent who
traveled more than 30 minutes to reach the suburban shopping centers be can be
defined as “outshoppers”[7].
On average, the respondents spend S$30 on each visit with the actual amount
varying significantly across different age group. More specifically, the average amount
spent ranges from S$66.50 for those below 20 years old to S$134 a month for those
above 40 years old. The result is not surprising since those in the younger age group
tend to have less to spend than those in the older age group. However, the data show
that teens visit the shopping centers more regularly and they stay longer during each
visit. In the past, heavy teen traffic and the many hours spent by teens at shopping
centers were viewed unfavorably by the shopping center managers as
“inconveniences” that can negatively impact security and operations. However, with
the teen population on the rise, retailers have recently seen the benefit to targeting teen
shoppers and their large discretionary spending power. In a recent study, Mangleburg
et al. (2004) observe that teens who shop with friends (as opposed to shopping alone)
are likely to shop more often. They also spend relatively more when shopping with
friends than when alone.
The average shopper stays in the suburban shopping centers for around 1.86
hours[8]. Table III shows that male patrons tend to stay longer than female patrons in
the suburban shopping centers[9]. The differences in the means between the groups are
statistically significant. This is a surprising result, which we will come back to later
when we discuss the regression results. However, women shoppers tend to visit the
shopping center more frequently and spent more on each visit. On average, they spent
just below S$100 a month while the male shoppers spent around S$86 a month in
suburban shopping malls.
It would not be unreasonable to expect suburban malls to attract the patronage of
more local shoppers and at higher frequency. Panel C of Table III reveals the duration
and frequency of visit as well as the average expenditure of patrons categorized by
their travel time. Those who stayed closest to the suburban shopping centers not
surprisingly visited the mall more frequently but they also do not stay too long nor
spend a lot during their visit. Those who stayed furthest from the mall, on the other
hand, do not visit the shopping center as frequently but they do stay longer in the mall
in each visit. However, their expenditure of S$80 a month is below average.
V. The size effect
Table IV presents the magnetism of the nine shopping centers based on the feedback of
1,283 shoppers on how long they take to travel to shopping center and the duration of
their visit. Overall, the survey results are consistent with the hypothesis that larger
suburban shopping centers are able to attract a higher percentage of “outshoppers”
who take a longer time to travel to the shopping centers. For example, approximately
Do size and
Cineplex matter?
121
Table III.
Analysis on shopping
patterns
23.6
23.7
23.7
–
–
–
23.7
0.541
0.459
1.000
0.342
0.390
0.268
1.000
Note: * ANOVA test is statistically significant at 1 percent level
21.5
25.4
20.7
23.7 *
0.251
0.613
0.136
1.000
Average travel time
(Mins)
1.46
1.99
2.18
1.86 *
1.97
2.02
1.86 *
1.95
1.83
1.83
1.86
Duration
(Hours)
3.56
3.04
2.66
3.12 *
3.26
2.96
3.12 *
3.50
3.02
2.82
3.12 *
Visits per month
25.00
33.00
30.00
30.00 *
30.50
29.00
30.00
19.00
34.50
47.50
30.00 *
Expenses per visit
(S$)
89.00
100.32
79.80
93.60 *
99.43
85.84
93.60 *
66.50
104.19
133.95
93.60 *
Expenses per month
(S$)
122
Panel A: by age (years)
, 20
20-40
. 40
All
Panel B: by gender
Female
Male
All
Panel C: by travel time
, 15 mins
15-30 mins
. 30 mins
All
Ratio of respondents
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0.335
0.319
0.340
0.294
0.323
0.358
0.405
0.493
0.358
0.380
0.389
0.404
0.441
0.371
0.394
0.456
0.282
0.390
0.284
0.293
0.256
0.265
0.305
0.248
0.139
0.225
0.252
Travel time to mall (% of shoppers)
, 15 mins
15-30 mins
. 30 mins
Note: * ANOVA test is statistically significant at 1 percent level
Tampines Mall and Century Square
Causeway Point
Jurong Point
Compass Point
Junction 8
Lot One Mall
West Mall
Sun Plaza
All
Suburban mall
24.4
24.5
25.0
24.4
24.5
22.7
19.1
20.4
23.7 *
Average travel time
(Mins)
2.0
2.1
2.0
1.7
1.9
1.7
1.4
1.6
1.9 *
Duration of visit
(Hours)
Do size and
Cineplex matter?
123
Table IV.
Magnetism of suburban
malls
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124
30 percent of the shoppers in Causeway Point, Junction 8 and Tampines Malls travel
more than 30 minutes to visit the shopping centers. Conversely, only less than 14
percent of the shoppers in West Mall traveled more than 30 minutes to reach the
shopping center. The same conclusion applies when we examine the travel time of
shoppers visiting the shopping center. Results of the analysis of variance (ANOVA)
test show that the differences in the travel time between the different shopping centers
are statistically significant at 1 percent level. While the whole sample took 23.7
minutes, on average, to reach their destination, the average travel time for the smaller
shopping centers is significantly lower. While one may argue that travel time could be
linked to accessibility, it should be noted that all the shopping centers are located next
to a mass transit station and within walking distance to a major bus interchange. Also
consistent with the notion of smaller shopping centers attracting mainly local
shoppers, around 38 percent of the respondents state that they walked to Sun Plaza,
which is the smallest suburban shopping center in our sample. In contrast, only 14-15
percent of the respondents indicated that they walked to the four largest sampled
shopping centers.
The last column in Table IV presents the duration of visit for the average shopper in
each of the respective shopping centers. The survey results show clearly that larger
shopping centers can retain shoppers for a longer duration. For example, the average
visiting time for large shopping centers is around 2 hours. On the other hand, shoppers
only spent 1.4 to 1.6 hours in West Mall and Sun Plaza, the two smallest shopping
centers in our sample. Physical size, however, does not appear to have any significant
influence on the frequency of visit, which averaged 3.12 times a month for our whole
sample. The results are consistent even after controlling for the gender and age of the
respondents.
In the survey, we also asked the respondents which shopping mall they patronized
frequently and the main reason/s for their choice. The results in Table V show that
shoppers are less concern with the cost and ease of finding a parking lot in the
shopping center. The branding of suburban shopping center in terms of its prestige
and exclusivity is also not important. Convenient location, which is not surprising, had
the largest influence on suburban shopping center choices (64.2 percent). Consistent
Determining factors
Table V.
Determinants of mall
choice
Spatial factors
1. Proximity
2. Mall size
3. Car park
Tenant mix
1. Variety of tenants
2. Complementary services
3. Cineplex
Branding strategy
1. Management and promotions
2. Reasonable prices
3. Quality and prestige
Source: Authors’ survey
% of responses
64.2
26.5
8.6
62.7
30.9
29.3
32.8
23.9
14.1
with the literature, the survey shows that whilst convenience is critical to the success of
a suburban shopping center, the non-spatial factors also play an equally important
role. Having a good tenant mix and a wide selection of shops strongly affects the
popularity of a shopping center. Good management and promotions (32.8 percent),
having a wide range of complementary services such as banking, library and food
court (30.9 percent) and a Cineplex (29.3 percent) are also cited by around one-third of
those interviewed.
Only one in four respondents indicated that the size of a shopping center is an
important factor in determining their choice of shopping center to patronize. Although
it is ranked 6th in importance, physical size is a key contributing factor to many
desired characteristics of a shopping mall. In particular, a small-sized shopping center
may not have enough space to facilitate a wide variety of tenants as well as
complementary services expected by shoppers. Even if smaller shopping centers try to
squeeze in more tenants, this will be at the expense of making the centers feeling
cramped and congested. A large-sized shopping center, on the other hand, is less
constrained by space availability to accommodate more tenants to achieve the optimal
retail mix and right concept to attract and retain high traffic. An added advantage of
being large is the ability to provide wider atriums and circulation networks within the
shopping center. These spaces provide a pleasant environment for shoppers, facilitate
their social interaction and mingling, as well as provide a venue where promotional
events can be held to draw in more visitors.
In summary, the survey results support our hypothesis that physical size has a
positive impact on the magnetism of a suburban shopping center. Larger shopping
centers have a greater ability to firstly, attract those staying outside its captive market
to visit it and secondly, hold the visitors longer within the shopping center.
Do size and
Cineplex matter?
125
VI. The Cineplex effect
The average respondent in our survey watches one movie a month (see Figure 5). Only
8 percent indicate that they rarely or do not watch movie in the cinema. The majority
watches at least one movie in three months (57 percent). Interestingly, 35 percent of the
respondents acknowledged that they are avid movie goers who watch at least one
movie every fortnight.
Cineplex, like other anchor tenants, serves as an attraction for a suburban shopping
center. This notion is supported in our survey with 72.4 percent of the respondents
Figure 5.
Frequency of watching
movie
JPIF
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126
indicating that the presence of a Cineplex would entice them to visit the shopping
center more often. With respect to the choice of cinema, 65.5 percent of the respondents
also indicate that it is important for the cinema to be located close to complementary
amenities. More specifically, 71 percent of the respondents also said they prefer to
watch movie in a Cineplex housed within a shopping center. In contrast, only 4 percent
indicate that they prefer to watch movie in standalone cinema, whilst the balance 25
percent do not have any preference. Table V also shows earlier that the presence of a
Cineplex, which was ranked 5th in order of importance, is a primary consideration in
the choice of shopping center to visit. Figure 4 also shows that one in four respondents
cite watching movie as one of the main reasons for visiting shopping centers.
Table VI contrasts the shopping behaviors of cinema patrons clustered by their
frequency of watching a movie in the Cineplex. It is clear from the survey that there is a
strong positive relationship between the frequency of watching movie and the
frequency of visiting a shopping center. For example, those who catch one movie at
least once a fortnight visit the shopping centers 3.5 times a month as compared to less
than three times for those who watch less than one movie a month. Frequent movie
goers also tend to stay longer in a shopping center, although they do not necessarily
travel further.
In short, accommodating a Cineplex within the shopping mall enhances the
shopping center’s magnetism by attracting a specific user group to visit it more
frequently and also, entice them to stay longer. One may, however, argue that this
group of patrons is passive as they are unlikely to incur expenditure while watching a
movie in the Cineplex. Our survey, however, reveals that cinema patrons actually
spend more per visit as well. In particular, the most avid cinema fan spends between
S$98.61 and S$130.50 a month in a suburban shopping center as compared to less than
S$90 a month for those who do not patronize the Cineplex frequently. After deducting
the cost of movie tickets and tidbits, each cinema patron on average still spends
between S$64 and S$95.70 elsewhere in the shopping center. In addition, 93 percent of
the cinema patrons indicate that they have companions when watching a movie.
Assuming their companions spend the same amount as the average cinema patron, the
spill-over effects to others retailers in the shopping center is further multiplied by the
number of accompanying persons. Of relevance are several studies on consumer
behavior which suggests that shoppers who shop in groups may cover larger areas of
stores, purchase more, and spend more money than when shopping alone (Granbois,
1968; Woodside and Sims, 1976; Sommer et al., 1992; Mangleburg et al., 2004).
To further examine the externality benefits of having a Cineplex, we survey the
activities of cinema patrons before and after watching a movie. With regard to their
time of arrival, the survey shows that around one-third (33.4 percent) would arrive at
the cinema just in time for the movie screening. Another 38.7 percent said they would
arrive at least 30 minutes before the scheduled screen time, while 17.7 percent would
arrive around 60 minutes before the show. A total of 10.2 percent indicated that they
would come much earlier than 60 minutes. The survey also asked them what they
usually do whilst waiting for the show to begin. Generally, a large number of movie
goers patronize the retail outlets and or eat in the food establishments within the
suburban shopping center before and after watching a movie show. In particular, the
survey shows that their favorite activities before watching the movie are having a meal
(43.3 percent), walking around (43.3 percent) and shopping (31.1 percent). Only 8.5
0.085
0.260
0.267
0.306
0.083
1.000
Ratio of respondents
20.85
24.36
23.43
24.36
23.28
23.7
2.02
2.05
1.87
1.73
1.57
1.86 *
Duration
of visit
(Hours)
Notes: *, * * ANOVA test is statistically significant at 1 percent and 5 percent level, respectively
One a week
One a fortnight
One a month
One in 2-3 months
Rarely
All
Frequency of watching movie
Average travel
time
(Mins)
3.48
3.46
3.24
2.74
2.50
3.12 *
No of
visits/month
Expenses
per month
(S$)
130.50
98.61
87.48
83.57
90.00
93.60 *
Expenses
per visit
(S$)
37.50
28.50
27.00
30.50
36.00
30.00 * *
Do size and
Cineplex matter?
127
Table VI.
Analysis on shopping
patterns of cinema
patrons
JPIF
25,2
percent indicate that they would wait at the cinema. The percentages, based on the
categorization by Nelson (1958) and Eppli and Shilling (1993), indicate high
compatibility of a Cineplex with food court and other stores in the suburban shopping
center. After the movie, 23 percent indicate that they would go back immediately. The
others will walk around (39.7 percent), have meals (35.6 percent) and shop (22.8
percent) within the shopping center.
128
VII. Analysis of simultaneous regressions
So far, we have examined the magnetism of the suburban shopping centers based on
the survey results. We focused primarily on how physical size and the presence of a
Cineplex enhance the drawing power and retaining power of the shopping centers. In
this part of the study, we extend our study to examine their effect on the dollar amount
spent within the suburban shopping centers. We employed a Tobit model embedded in
a recursive simultaneous equations model to test the isolating effects of physical size
and the presence of a Cineplex. The specification of the regression models are
presented earlier in Section III.
The definitions and pair-wise correlations of the variables used to test the
relationships are provided in Table VII, which reveals several interesting relationships.
Specific to our study focus, the expenditure amount spent per visit is influenced largely
by the characteristics of the visitors rather than the motive of their visit to the
shopping center. While the physical size of a shopping center has a positive influence
on how long a patron would stay in the shopping center, the strongest determinant of
stay duration is movie watching. The matrix shows that avid movie goers, not
surprisingly, tend to be young and single but they usually watch movies with friends.
The estimation results of equations (1) and (2) are presented in Table VIII. Model 1,
which is presented mainly for comparison purpose, is based on a Tobit regression of a
single equation on amount spent per visit (equation (1)). Model 2, which is our focus, is
a two-equation model that controls for the simultaneity of duration of visit and the
amount spent in the shopping center. The magnitude of the R2ANOVA and
R2DECOMPOSITION indicates that around 14.7 per cent of the variations in the patron’s
expenditure are explained by the variables in our model. In addition, the diagnostic LM
statistic for Cragg’s model shows that the censoring is the appropriate specification for
the expenditure model. A simple t-test analysis confirms the exogeneity of y2, namely
the time spent by patrons in a shopping center, in Regression 1 of Model 2.
Results of Model 1 show that expenditure amount of shopping center patrons is
determined primarily by their age, which is highly correlated to their income level.
Not surprisingly, those who indicated that their main purpose of visit is shopping
tend to spend more. In addition, patrons who stay longer in a shopping center also
spend more. While the size of the shopping mall and watching movie per se do not
significantly increase the expenditure pattern of the patrons, the results suggest
that those who watch movie frequently tend to spend more in shopping centers as
well.
The estimation results of Model 2 provide more insight into the dynamics of how
physical size and the presence of a Cineplex affect the performance of the shopping
centers. The first regression shows that once the simultaneity of visit duration is
taken into account, mall size and watching movie actually have negative marginal
effects on expenditure. However, interpretation of the results is not as
0.136
1.000
0.060
0.187
1.000
TTIME
20.023
0.116
0.062
1.000
SIZE
0.017
0.279
2 0.011
0.107
1.000
MOVIE
0.086
0.030
20.005
0.016
0.082
1.000
SHOP
20.040
20.088
0.002
20.092
0.037
20.094
1.000
MALE
0.313
2 0.064
2 0.039
2 0.088
2 0.171
0.036
0.037
1.000
AGE
0.148
0.106
0.304
0.048
0.019
20.011
0.060
0.080
1.000
FREQ
20.007
0.122
20.026
0.050
0.206
0.020
0.037
20.360
20.097
1.000
M-FAN
W-END
0.089
0.054
2 0.047
2 0.094
0.078
0.049
0.032
0.051
0.085
2 0.035
0.019
COM
0.025
0.099
0.059
0.040
0.119
0.029
20.014
20.125
0.063
0.138
1.000
Note: Correlation coefficients for the pair-wise relationships are computed based on a final sample of 1,214 observations. Definitions of the variables are
as follows: Expenditure per visit (EXP), duration of visit (STIME), travel time to shopping center (TTIME), size of shopping center (SIZE), main purpose
of visit is to catch a movie (MOVIE), main purpose of visit is shopping (SHOP), sex of respondent (MALE), age of respondent (AGE), frequency of mall
visit (FREQ), frequency of watching movie (M-FAN) and whether respondent is alone or with companion/s (COM)
EXP
STIME
TTIME
SIZE
MOVIE
SHOP
MALE
AGE
FREQ
M-FAN
COM
STIME
Do size and
Cineplex matter?
129
Table VII.
Correlation matrix
JPIF
25,2
130
Table VIII.
Regression results
Model 1: single equation Tobit model
LM test [df] for Tobit ¼ 2:683 [9]
R2ANOVA ¼ 0:1468; R2DECOMPOSITION ¼ 0:1469
Dependent Variable ¼ Expenditure
Constant
Size (net lettable ’000 m2)
Watching movie
Shopping
Male respondent
Age of respondent
Movie fan
Companion
Stay time
Model 2: simultaneous equations Tobit model
LM test [df] for Tobit ¼ 24; 151:326 [9]
T-test of the hypothesis that r½11; 12 is
0 ¼ 23:454 * * *
Regression 1: dependent variable ¼ expenditure
Constant
Size (net lettable ’000 m2)
Watching movie
Shopping
Male respondent
Age of respondent
Movie fan
Companion
Stay time
Regression 2: dependent variable ¼ stay time
Constant
Size (net lettable ’000 m2)
Watching movie
Male respondent
Regular mall patrons
Travel time
Weekend
Companion
Coefficient
T-ratio
p-value
1.0785
20.0011
0.0367
0.0921
20.0352
0.2508
0.0691
0.0435
0.0842
9.58
20.67
0.78
2.39
20.90
13.10
3.67
0.68
5.22
0.0000
0.5058
0.4381
0.0170
0.3659
0.0000
0.0002
0.4947
0.0000
0.1024
20.0035
20.2483
0.0932
0.0474
0.2489
0.0705
20.0404
0.4325
0.32
21.72
22.52
2.27
0.88
13.13
3.71
20.55
4.14
0.7518
0.0861
0.0118
0.0231
0.3781
0.0000
0.0002
0.5801
0.0000
2.3423
0.0077
0.7679
20.2718
0.1757
0.1608
0.1694
0.2023
15.70
2.71
9.27
24.00
2.86
5.41
2.85
2.05
0.0000
0.0067
0.0000
0.0001
0.0042
0.0000
0.0043
0.0403
Notes: Number of observations is 1,214. The first model is based on a Tobit regression of a single
equation (equation (1)), while the second model is based on two equations to control for the
simultaneity of duration of visit and the amount spent in the shopping center. The results of Model 1
are presented for comparison purposes only
straightforward because both factors have a positive and significant influence in
the second regression. Duration of visit in turn has a positive and significant effect
on expenditure in the first regression. Overall, the results show that having a larger
shopping center and Cineplex induce shoppers to stay longer but their marginal
effect on expenditure pattern is at best indirect. Regression 2 further reveals that
patrons tend to stay longer during the weekends and when they are with
companions (either family members or friends). In contrast to our earlier
observation in Table III, the estimation results indicate that male patrons tend to
spend less time in a suburban shopping center than female patrons after taking into
account the confounding effects of other variables. Furthermore, those who took a
longer time to reach a shopping center tend to spend more time in the mall.
Although the correlation matrix suggests that Watching movie is only slightly
correlated with Movie fan (0.20), we repeated the recursive estimation by
withdrawing Movie fan from equation (1) to check if there may be some
multicollinearity between the two variables, thereby causing the sign of the
Watching movie in equation (1) to be negative. The estimation results, not reported,
show that our earlier findings are robust to the exclusion of the Movie fan variable
and hence, not affected by multicollinearity between the two variables. The results
are also robust when we substitute the age of respondents with either their marital
status or their income level.
VIII. Summary and conclusions
Two common problems faced by developers, owners and managers of shopping
centers located outside the traditional primary shopping area are addressed in this
paper: First, does size matters in the success of a suburban shopping center, and
second, what is the impact of accommodating a Cineplex within a suburban
shopping center. A survey on 1,283 shoppers was carried out in nine selected
suburban shopping centers in Singapore. The results indicate that physical size and
the presence of a Cineplex do enhance the magnetism of suburban shopping centers.
Both factors enhance their ability to attract “outshoppers” and to make the visitors
stay longer in the shopping center. Although mall size, in itself, may not be ranked
very highly by shoppers when determining shopping center choices, a large
shopping center can facilitate a greater variety of shops and a more pleasant
environment to lure shoppers and make them stay longer. The survey further shows
that cinema patrons prefer to watch movies in Cineplex located in shopping centers
and that they generally stay longer in the shopping center as compared to non movie
goers. The presence of a Cineplex also has spill-over benefits for other stores within
the shopping center. Moreover, having a Cineplex in the suburban shopping center
fulfills its secondary role of providing a lifestyle and recreational facilities for the
local community. Although the regression results show that Cineplex and physical
size does not increase the S$ amount spent in the shopping center, the two factors
indirectly affect how long patrons will stay in the shopping center, which in turn is
positively related to expenditure level.
This paper contributes to the literature by drawing attention to the magnetism of
suburban shopping centers. As the trend move towards locating shopping malls
outside the prime shopping areas, enticing prospective shoppers to visit these
shopping centers becomes a critical survival issue for the owners. Hence, an
understanding of the magnetism or drawing power of shopping centers is important
to enhance the malls’ performance. The study also provides a richer understanding
of the shopping behavior and patronage of cinema patrons. Further insights here
would allow the developers and retailers to reach out and market to this segment
more effectively. It remains for us to acknowledge that while the conclusions are
interesting, the high-density urban fabric of Singapore, and eventually, the
shopping and leisure culture that prevails on the island may partly explain the
study findings. In particular, it has been noted that Singaporeans as a whole tend to
Do size and
Cineplex matter?
131
JPIF
25,2
132
frequent shopping center more often that the Americans. Furthermore, there may be
a scale effect since Singapore is a small island linked with a comprehensive public
transportation system, as compared to say America and UK where the suburbs are
further from one another. The question remains whether, and to what extent, the
conclusions derived from this study can be extended to other contexts. For
comparison purpose, it would be interesting if similar surveys and studies could be
carried out in other markets.
Notes
1. Although the term “magnetism” may appear to be similar to “attractiveness”, the former
terminology is adopted in this study to convey the managers’ active pursuit to first, attract
shoppers to the malls and then retaining them in the mall for a longer duration.
2. In their review of the literature, Mejia and Benjamin (2002) suggests that understanding the
effect of non-spatial factors is important because: non-spatial factors increase retailer
differentiation in competitive retail markets; they promote brand identity as retailers develop
alternative non-store retail formats; and they represent a source of shopping center
intangible value.
3. In most retail leases, the rental include a fixed rent component as well as an overage rent
which is calculated as a percentage of sales after a certain threshold level. Mejia and
Benjamin (2002) underline that understanding the creation of shopping center rents starts
with understanding the determinants of retail sales. The use of overage rent in retail
leases is seen as a landlord-tenant risk sharing tool (Brueckner, 1993; Lee, 1995; Miceli and
Sirmans, 1995; Colwell and Munneke, 1998). Pashigian and Gould (1998) and Wheaton
(2000) further characterize overage rents as an incentive for landlords to optimize tenant
mix.
4. The suburban malls in Singapore are comparatively much smaller than regional malls in
the USA, which have a competitive center size of 888,000 square feet (Eppli and Shilling,
1996).
5. Since the space occupied by anchor tenants is generally much larger than other tenants,
actual space occupied by non-anchor tenants will be much lower than 133-277 m2.
P
P
6. R2ANOVA ¼ ð1=n ni¼1 ðy^ i 2 y^ Þ2 Þ=ð1=n ni¼1 ð yi 2 y Þ2 Þ
¼ ðVar½ predicted conditional meanÞ=ðVar½dependent variableÞ and
P
P
P
2
RDECOMPOSITION ¼ ð1=n ni¼1 ðy^ i 2 y Þ2 Þ=ð1=n ni¼1 ðy^ i 2 y Þ2 þ 1=N ni¼1 ð yi 2 y^ i Þ2 Þ
¼ ðVariation of predicted meanÞ=ðVariation of predicted
mean þ Residual variationÞ.
7. This categorization follows from Mejia and Benjamin (2002) who indicate that the retail
market of a mall is traditionally referred to as the area from which a shopping center draws
70 percent-80 percent of its sales.
8. While it is possible that the results may be bias to the extent that those who spend more
time at the mall are more likely to be sample (Roy, 1994), the duration of visit are
nevertheless consistent with existing evidence. For example, a survey conducted by the
International Council of Shopping Centers (ICSC) in 2001 revealed that shoppers would
usually stay for an average of 73.4 minutes in malls less than 74,322 m2. Source: www/
icsc.org/about/about.shtml Erkip (2003) also observes that mall visitors in Turkey tend to
stay at most one to two hours.
9. Otnes and McGrath (2001) is the first study to focus on men’s shopping experiences in an
in-depth manner. They demonstrate how actual male shopping behavior belies three
common stereotypes of male shopping behavior: “Grab and Go,” “Whine and Wait,” and
“Fear of Feminine”.
References
Anderson, C.H. and Kamisky, M. (1985), “The outshopper problem: a group approach for small
retailers”, Entrepreneurship Theory and Practice, Vol. 9 No. 3, pp. 34-45.
Biba, G., Des Rosiers, F., Theriault, M. and Villeneuve, P.-Y. (2006), “Big boxes versus traditional
shopping centers: looking at households’ shopping patterns – a Canadian cast study”,
Journal of Real Estate Literature, Vol. 14 No. 2, pp. 175-202.
Bloch, P.H., Ridgway, N.M. and Dawson, S.A. (1994), “The shopping mall as consumer habitat”,
Journal of Retailing, Vol. 70 No. 1, pp. 23-42.
Brown, M.G. (1999), “Design and value: spatial form and the economic failure of a mall”, Journal
of Real Estate Research, Vol. 17 Nos 1/2, pp. 189-226.
Brueckner, J. (1993), “Inter-store externalities and space allocation in shopping centers”, Journal
of Real Estate Finance & Economics, Vol. 7 No. 1, pp. 5-16.
Bucklin, L.P. (1971), “Retail gravity models and consumer choice: a theoretical and empirical
critique”, Economic Georgraphy, Vol. 47 No. 4, pp. 489-97.
Colwell, P.F. and Munneke, H.J. (1998), “Percentage leases and the advantages of regional malls”,
Journal of Real Estate Research, Vol. 15 No. 3, pp. 239-52.
Des Rosiers, F., Theriault, M. and Menetrier, L. (2005), “Spatial versus non-spatial determinants
of shopping center rents: modelling location and neighboorhood-related factors”, Journal
of Real Estate Research, Vol. 27 No. 3, pp. 293-319.
Eppli, M. and Benjamin, J.D. (1994), “The evolution of shopping center research: a review and
analysis”, Journal of Real Estate Research, Vol. 9 No. 1, pp. 5-32.
Eppli, M. and Shilling, J. (1993), “Retail compatibility in regional shopping centers”, working
paper, University of Wisconsin-Madison, Madison, WI.
Eppli, M. and Shilling, J. (1996), “How critical is a good location to a regional shopping center?”,
Journal of Real Estate Research, Vol. 12 No. 3, pp. 459-68.
Erkip, F. (2003), “The shopping mall as an emergent public space in Turkey”, Environment and
Planning A, Vol. 35, pp. 1073-93.
Forgey, F.A., Goebel, P.R. and Nixon, B. (1995), “Addressing tenant selection to maintain
shopping center success”, Economic Development Review, Vol. 13 No. 2, pp. 56-9.
Gatzlaff, D.H., Sirmans, G.S. and Diskin, B.A. (1994), “The effect of anchor tenant loss on
shopping center rents”, Journal of Real Estate Research, Vol. 9 No. 1, pp. 99-110.
Gerbich, M. (1998), “Shopping center rentals: an empirical analysis of the retail tenant mix”,
Journal of Real Estate Research, Vol. 15 No. 3, pp. 283-96.
Granbois, D.H. (1968), “Improving the study of customer in-store behavior”, Journal of
Marketing, Vol. 32 No. 4, pp. 28-32.
Greene, W.H. (2002), LIMDEP Version 8.0 Econometric Modeling Guide, Vol. 2, Econometric
Software, New York, NY.
Hanson, S. (1980), “Spatial diversification and multipurpose travel: implications for choice
theory”, Geographical Analysis, Vol. 12 No. 3, pp. 245-57.
Hardin, W.G. III and Wolverton, M.L. (2000), “Micro-market determinants of neighborhood center
rental rates”, Journal of Real Estate Research, Vol. 20 No. 3, pp. 299-322.
Do size and
Cineplex matter?
133
JPIF
25,2
134
Hotelling, H. (1929), “Stability in competition”, Economic Journal, Vol. 39, pp. 41-57.
Housing and Development Board (2004), HDB Annual Report 2003/04, Housing and
Development Board, Singapore, p. 85.
Huff, D.L. (1964), “Defining and estimating a trade area”, Journal of Marketing, Vol. 28 No. 3,
pp. 29-37.
Ibrahim, M.F. and Ng, C.W. (2002), “Determinants of entertaining shopping experiences and their
link to consumer behavior: case studies of shopping centers in Singapore”, Journal of
Leisure Property, Vol. 2 No. 4, pp. 338-57.
Ingene, C.A. and Ghosh, A. (1990), “Consumer and producer behavior in a multipurpose shopping
environment”, Geographical Analysis, Vol. 22, January, pp. 70-91.
Kirkup, M. and Rafiq, M. (1994), “Managing tenant mix in shopping centres”, International
Journal of Retail & Distribution Management, Vol. 22 No. 6, pp. 29-37.
Konishi, H. and Sandfort, M.T. (2003), “Anchor stores”, Journal of Urban Economics, Vol. 53,
pp. 413-35.
Lee, K. (1995), “Optimal retail lease contracts”, Regional Science and Urban Economics, Vol. 25
No. 6, pp. 727-38.
Lillis, C.M. and Hawkins, D.I. (1974), “Retail expenditure flows in continuous trade areas”,
Journal of Retailing, Vol. 50 No. 2, pp. 31-42.
Mangleburg, T.F., Doney, P.M. and Bristol, T. (2004), “Shopping with friends and teens’
susceptibility to peer influence”, Journal of Retailing, Vol. 80 No. 2, pp. 101-16.
Mejia, L.C. and Benjamin, J.D. (2002), “What do we know about the determinants of shopping
center sales? Spatial vs non-spatial factors”, Journal of Real Estate Literature, Vol. 10 No. 1,
pp. 3-26.
Merrill Lynch (2005), “Inititation on S-REITs”, Commetn, January 24, p. 9.
Miceli, T.J. and Sirmans, C.F. (1995), “Contracting with spatial externalities and agency
problems: the case of retail leases”, Regional Science and Urban Economics, Vol. 25 No. 3,
pp. 355-72.
Miceli, T.J., Sirmans, C.F. and Stake, D. (1998), “Optimal competition and allocation of space in
shopping centers”, Journal of Real Estate Research, Vol. 16 No. 1, pp. 113-26.
Nelson, R.L. (1958), The Selection of Retail Locations, Dodge, New York, NY.
Nevin, J.R. and Houston, M.J. (1980), “Image as a component of attraction to intraurban shopping
areas”, Journal of Retailing, Vol. 56 No. 1, pp. 77-93.
O’Kelly, M.E. (1981), “A model of the demand for retail facilities, incorporating multistop,
multipurpose trips”, Geographical Analysis, Vol. 13 No. 2, pp. 134-48.
Otnes, C. and McGrath, M.A. (2001), “Perception and realities of male shopping behavior”,
Journal of Retailing, Vol. 77, pp. 111-37.
Ownbey, K.L., Davis, K. and Sundel, H.H. (1994), “The effect of location variables on the gross
rents of neighborhood shopping centers”, Journal of Real Estate Research, Vol. 9 No. 1,
pp. 111-23.
Pashigian, B.P. and Gould, E.G. (1998), “Internalizing externalities: the pricing of space in
shopping malls”, Journal of Law and Economics, Vol. 108, pp. 843-67.
Reilly, W.J. (1931), The Laws of Retail Gravitation, Knickerbocker Press, New York, NY.
Roulac, S.E. (1994), “Retail real estate in the 21st century: information technology þ time
consciousness þ unintelligent stores ¼ intelligent shopping? Not!”, Journal of Real Estate
Research, Vol. 9 No. 1, pp. 125-50.
Roy, A. (1994), “Correlates of mall visit frequency”, Journal of Retailing, Vol. 70 No. 2, pp. 139-61.
Russel, V. (1957), “The relationship between income and retail sales in local areas”, Journal of
Marketing, Vol. 21 No. 3, pp. 329-32.
Severin, V., Louviere, J.J. and Finn, A. (2001), “The stability of retail shopping choices over time
and across countries”, Journal of Retailing, Vol. 77 No. 2, pp. 185-202.
Simmons, R.A. (1992), “Site attributes in retail leasing: an analysis of a fast-food restaurant
market”, The Appraisal Journal, Vol. 60 No. 4, pp. 521-31.
Sirmans, C.F. and Guidry, K.A. (1993), “The determinants of shopping center rents”, Journal of
Real Estate Research, Vol. 8, pp. 105-15.
Sommer, R., Waynes, M. and Brinkley, G. (1992), “Social facilitation effects in shopping
behavior”, Environment and Behavior, Vol. 24 No. 3, pp. 285-97.
Wheaton, W.C. (2000), “Percentage rent in retail leasing: the alignment of landlord-tenant
interests”, Real Estate Economics, Vol. 28 No. 2, pp. 185-204.
Woodside, A.G. and Sims, J.T. (1976), “Retail sales transactions and customer ‘purchase pal’
effects on buying behavior”, Journal of Retailing, Vol. 52 No. 3, pp. 57-64, 95.
Corresponding author
Joseph T.L. Ooi can be contacted at: rstooitl@nus.edu.sg
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Do size and
Cineplex matter?
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