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Profiling Major Sport Event Visitors:
The 2002 Commonwealth Games
a b c
Holger Preuss , Benoit Seguin & Norm O'reilly
a
Institute of Sport Science, Johannes Gutenberg-University ,
Mainz, Germany
b
School of Human Kinetics, University of Ottawa , Ottawa,
Canada
c
School of Sports Administration, Faculty of Management,
Laurentian University , Sudbury, Canada
Published online: 07 Aug 2007.
To cite this article: Holger Preuss , Benoit Seguin & Norm O'reilly (2007) Profiling Major Sport
Event Visitors: The 2002 Commonwealth Games, Journal of Sport & Tourism, 12:1, 5-23, DOI:
10.1080/14775080701496719
To link to this article: http://dx.doi.org/10.1080/14775080701496719
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Downloaded by [136.243.18.10] at 01:10 05 March 2015Journal of Sport & Tourism
Vol. 12, No. 1, February 2007, pp. 5 – 23
Profiling Major Sport Event Visitors:
The 2002 Commonwealth Games
Holger Preuss, Benoit Seguin & Norm O’Reilly
It has become common practice for governments and municipalities around the world to
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bid for the right to host a major sporting event. Prior to embarking on the bidding process,
politicians attempt to determine whether such an event will be of value to their
municipality; and often focus on the estimated economic consequences of hosting such
an event. Frequently, studies are commissioned to predict the event’s economic value.
However, these studies often miscalculate the potential impact of sport event visitors as
consumers. We argue that enhanced profiling of these visitors will enable a more
accurate assessment of economic impact. The current research surveys 1,196 spectators
of the 2002 Commonwealth Games to demonstrate four important aspects of visitor
profiles related to economic impact: (i) visitor typology, (ii) sport tourist behaviors,
(iii) consumption patterns determined by interest, and (iv) consumption patterns
determined by distance traveled. Overall, the work makes three important
contributions to the literature by: (i) empirically supporting that different sports attract
different market demographics, (ii) underlining the need for segmentation in economic
impact studies, and (iii) identifying the need to develop metrics of economic impact
analysis that consider segmentation effects.
Keywords: Sport Tourism; Economic Impact; Major Sport Events; Commonwealth
Games; Event Management; Event Visitors; Spectators
Introduction
Large municipalities are often very interested in attracting major sport events. As a
result, the bidding competition for the rights to host such events is quite fierce.
Häußermann & Siebel (1993) examined the ‘Festivalisation’ of city politics and
described how major sporting events can attract ‘fresh’ money to the host city by pro-
viding additional resources to develop and restructure the city and improve its image.
Holger Preuss is in the Institute of Sport Science, Johannes Gutenberg-University, Mainz, Germany. Benoit Seguin
is in the School of Human Kinetics, University of Ottawa, Ottawa, Canada. Norm O’Reilly, is in the School of
Sports Administration, Faculty of Management, Laurentian University, Sudbury, Canada. Email: preuss@
uni-mainz.de.
ISSN 1477-5085 (print)/ISSN 1029-5399 (online) # 2007 Taylor & Francis
DOI: 10.1080/147750807014967196 H. Preuss et al.
However, their study is quite critical about the magnitude of these effects
(Häußermann & Siebel, 1993). Indeed, many politicians believe that hosting major
events will attract both direct and indirect spending to the local economy. Visitors
make expenditures directly related to the event, while indirect benefits include such
items as future tourism from destination marketing, post-event economic growth,
and governmental subsidies towards the construction of the infrastructure needed
to host the event.
Major sport events such as the Olympic Games, Pan American Games, FIFA Foot-
ball World Cup or Commonwealth Games are large-scale events that require a large
number of sport facilities and training sites. These facilities must meet the highest
international standards. Further, the International Olympic Committee (IOC) and
other International Federations (IF) have recognized that spectator capacity should
be reduced in order to avoid the construction of ‘white elephants’ (IOC, 2003).
While it is obvious that the potential television audience for major sport events far
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exceeds the number of visitors to a city, we suggest that visitors to these events
should be given special consideration. In fact, such visitors create an atmosphere
that differs considerably from local-only events (Preuss & Messing, 2003). They
consume a number of products during their stay in the city and may also provide valu-
able word-of-mouth advertising for a host city as a travel destination.
A well known method of measuring the benefits of events is known as cost-benefit-
analysis, where the direct, indirect, and intangible costs and benefits of an event are
measured. These cost-benefit assessments need to include several sources of infor-
mation about the visitors on a number of specific variables. However, it is important
to note that ticket revenue and expenditures differ among the visitors. Thus, the con-
siderable contribution by visitors towards the overall economic impact is often miscal-
culated due to the complexity of measuring it. Many studies investigate the impact of
events on tourism (e.g. Getz, 1989, 1991; Hall, 1992; Kang & Perdue, 1994; Dwyer
et al., 2004), and only recently have researchers considered the event-related impact
on spending in the local economy. For example, Dwyer et al. (2006) suggest that
the use of a computable general equilibrium approach (CGE) is better suited to
distinguish the effects on the host regions as compared to other regions.
The considerable potential economic benefit of hosting a major sporting event has
played a key role in attracting the interest of cities. The influx of a large number of
visitors to the host city is partly responsible for driving this economic benefit.
When calculating economic impact, one must consider the number of visitors
coming to the city, their consumption patterns, the duration of their stay, and the
‘crowded-out’ effects (i.e. the opportunity costs as some long-term tourists will
avoid the destination due to the event). Thus, an exact assessment of the tourism-
based economic impact is an important component in calculating the overall potential
economic benefit to a city staging a major sport event (Kesenne, 2005; Preuss, 2005).
The works of Crompton (1999), Gratton et al. (2000), and Coleman (2004) focus
on small and medium-sized special sport events. A major sport event is defined here as
‘irregular major international spectator events generating significant economic activity
and media interest’ (Coleman, 2004, p. 11). The 2002 Commonwealth Games can beJournal of Sport & Tourism 7
described as a multi-sport event that stages world-class sport competitions in one city
at the same time. This research explores the specifics of the effects of visitors through
an assessment of visitors to a major sport event, the 2002 Commonwealth Games in
Manchester, UK. Hence, this paper examines three issues:
1. The complexity of measuring the different groups (event segments) to be con-
sidered in economic impact studies as shown by visitors to the 2002 Common-
wealth Games.
2. The differences between visitors to the 2002 Commonwealth Games and normal
tourists (i.e. tourists in Manchester for reasons other than the Games) coming to
the city of Manchester on a variety of measures, such as: (i) length of stay; (ii)
spending on tickets, merchandise, accommodation, food, and shopping; and (iii)
interest in traveling before and/or after the event.
3. Segmenting 2002 Commonwealth Games visitors by their duration of stay, outlay/
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effort to attend the Games or distance traveled to Manchester.
Overview of Literature
It is believed that sport is the primary reason for travel in approximately 25% of all
holidays (Weed & Bull, 1998). The literature has responded to this point and research
related to sport tourism and major sport events has increased significantly in recent
years. Many studies (e.g. Redmond, 1990; Dreyer, 1998; Weed & Bull, 1997; Standeven
& De Knop, 1999; Kartakoullis et al., 2003; Preuss, 2004) have highlighted the corre-
lation between sport and tourism. This paper’s focus is on sport event tourism, or vis-
iting a destination to watch a sporting event, which is one of the three types of sport
tourism identified by Gibson (1998). In noting that considerable debate exists in the
literature on the definition of sport tourism, Gibson (1998, p. 47) suggests the follow-
ing working definition of sport tourism: ‘Leisure-based travel that takes individuals
temporarily outside of their home communities to play, watch physical activities, or
venerate attractions associated with these activities’.
The ability to determine the economic impact of major sport events has been the
focus of numerous studies over the years (Burgan & Mules, 2001; Burns & Mules,
1986; Crompton, 1995; Dwyer et al., 2003, 2005, 2006; Gratton et al., 2004; Hall,
1992; Shibli & Gratton, 2001; Mules & Faulkner, 1996; Preuss, 2004). While there
has been debate over how to best estimate the economic impact of events (e.g.
using Input– Output analysis or Computable General Equilibrium Approach), the
research on the subject has been of great value to both public and private organizations
in communities that are interested in hosting such events. In fact, a number of cities
have incorporated sport events into their economic development mix (Chalip & Leyns,
2002), thus increasing interest in the evaluation of their impact. From an economic
perspective, the hosting of major sport events has been shown to bring significant
economic activity to local industry, and, in particular, to the construction and hospi-
tality industries (Sub-Committee, 1998). These events can also be leveraged by man-
agers in order to increase the interest and involvement of both visitors and residents.8 H. Preuss et al.
Mega-events (Ritchie, 1984) can be used as an opportunity ‘to establish a destination’s
tourism credential at the international level’ (Croutch & Ritchie, 1999, p. 148). This, in
turn, can provide a city (or region) with ‘destination competitiveness’ (see the concep-
tual model of destination competitiveness in Crouch & Ritchie, 1999). Despite the
benefits suggested above, there remains some uncertainty regarding the tourism-
related benefits a region experiences as a result of hosting a major sport event.
To resolve this uncertainty, two important steps must be implemented by cities who
hope to host a major sport event. First, the complex nature of visitor-generated econ-
omic impact must be articulated. This infers that the money entering the region,
minus the money that leaves the region through event visitors, has to be identified,
and the flow of transactions traced. Second, the resulting visitor-generated primary
impact can be inserted into one of the many available models to calculate the
overall economic impact such as RIMS (Regional Input– Output Modeling System)
(Donnelly et al., 1998; Wang, 1997) or IMPLAN (Impact Analysis for PLANing)
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(Dawson et al., 1993; Donnelly et al., 1998; Wang, 1997). However, these models
need a realistic estimate of the primary impact of a given event, and, as such, may
be considered insufficient. Prior to using the models to calculate the economic
impact of Games visitors, one must first determine the consumption patterns of
these visitors. Given this, it is surprising that consumption patterns of visitors at
major sport events have yet to receive much attention in the literature. Empirical
research by Crompton (1999) investigated the consumption patterns of tourists at
several smaller festivals, including 14 sporting events. Gratton et al. (2000) look at
the regional impact of six special sporting events in England. The Sports Industry
Research Centre at Sheffield Hallam University coordinated by Coleman (2004) did
a study of 17 sport events from 1997 to 2003 in UK. All three of these studies
compare the consumption of visitors, officials, athletes, and media, and calculate
the economic impact of such events, but they focus solely on small events.
The literature on special sport event spectators is somewhat limited. Delpy et al.
(2001) argue that while much has been written and researched around major sport
events such as the Olympic Games, the spectator’s role is often ignored, particularly
when assessed from an economic point of view. Other research, however, suggests
that this may change as both ticket prices and the commercialization of major sport
events continue to increase (e.g. Seguin et al., 2005). This, in turn, brings special atten-
tion to the role of the spectator (Chalip & Leyns, 2002). The vast majority of research
on major sport events has focused on the Olympic Games. However, there is a need to
expand this view and broaden the analyses of major sport events – and, certainly, there
is a dire need to improve our understanding of both spectators and visitors.
Groups to be Considered in Economic Impact Studies
An important component of economic impact calculations involves estimating the
number of people who come specifically to see the event and bring ‘fresh’ money
into the host city. However, identifying the exact number of visitors at an event can
prove to be quite challenging. The 2002 Commonwealth Games in Manchester wasJournal of Sport & Tourism 9
no different. Ticket sales numbers and the availability of seats were considered as
methods to calculate attendance, but both proved to be insufficient, mainly due to
the fact that a large number of people, such as VIPs, media, referees, athletes and
team staff, had free access to the facilities. To further complicate measurement,
some visitors attended multiple sessions on the same day. Despite these limitations,
‘ticketed Games sessions are estimated to have been attended by 400,000 people and
2% of the UK adult population reported that they were a spectator at the Games,
40% of whom originated from the Northwest . . . One million visitors came to
Manchester over the 10 days of the Games’ (Maunsell, 2004, pp. 17– 18). In addition
to their limited accuracy, these calculations were also not sufficient to calculate the
primary economic impact of visitors because they did not indicate who brought in
‘fresh’ money. It was, thus, necessary to embark on this study and conduct a more
detailed analysis of the origin of the spectators attending the 2002 Commonwealth
Games.
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Prior to presenting results concerning the groups of individuals to be considered for
the regional economic impact analysis, a few key terms are presented and defined here.
. Event-affected persons are persons who are attracted by the event (e.g. spectators,
workers in tourism industry, etc) and those who avoid the event by leaving or not
entering a host city/region because of the event.
. Spectators are persons who attend sessions of the event. They have no work commit-
ments during the event and can be residents, tourists, or day visitors.
. Tourists and day visitors are persons who do not live in the city/region. Tourists stay
one night or longer in the host city/region, while day visitors enter and leave the
city/region in the same day.
. Residents are persons who live permanently in the city/region.
By presenting a framework, Figure 1 gives a theoretical overview of event-affected
persons’ movements to and from a host city/region (Preuss, 2005).
Preuss (2005) refers to ‘Extentioners’ (A), ‘Event visitors’ (B), and ‘Home Stayers’
(C) as event visitors who spend ‘fresh’ money and create a significant economic
impact. The group of residents who avoid the event are distinguished as ‘Runaways’
(D) and ‘Changers’ (F). The Changers are the persons who had planned a holiday
trip and decided to change the dates of the trip to coincide with the event. While
they were scheduled to be away during the event, they did not carry more money
out of the city/region during the event than they would have carried away normally
over the year (Preuss, 2005). However, it is suggested that Runaways create opportu-
nity costs. These residents plan an additional trip and leave the city (running away)
during the Games. As a result, they spend money out of the region that otherwise
would have stayed within the city/region, thus representing an ‘opportunity cost’ to
the city. The impact of their behavior may be significant. For example, at the 1992
Olympic Games in Barcelona, it was reported that 16% of the people interviewed
six months prior to Games considered spending their holidays outside the city
during the event (Brunet, 1993). Similarly, results of the 1998 Traveland Survey
suggested that 18% of residents intended to leave Sydney to travel abroad during10 H. Preuss et al.
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Figure 1 Movements of Event-affected Persons during Event-time. Source: Preuss (2005,
p. 288).
the 2000 Olympic Games in Sydney (TFC, 1998). Theoretically, the risk to a host city is
that Runaways and Changers may discover new holiday destinations and decide to
return there again in the future.
Preuss (2005) suggests that the ‘Casuals’ (G) and ‘Time switchers’ (H) be
considered in economic impact studies. He argues that while the expenditures of
Casuals would occur even without the event, and the Time Switchers would come
to the city/region anyway, the two groups spend their money and time during the
event on event-related actions rather than on everyday tourist attractions. For
example, attendance figures at popular non-Olympic-related tourist attractions were
down 30 to 50% during the 1984 Olympic Games in Los Angeles (ERA, 1984). The
difference in the consumption patterns of Casuals and Time Switchers during major
Games necessitates further and more in-depth studies of event-related economic
impact. In addition, it was shown that these groups are more likely to spend additional
money due to the event than they would have spent otherwise.
‘Avoiders’ (E) plan a visit to a specific city or region and decide to stay away because
of the event, thus representing opportunity cost to the host city. For example, a 1999 –
2000 Utah Skier Survey found nearly 50% of non-resident skiers indicated that they
would not consider skiing in Utah during the 2002 Olympic Winter Games in Salt
Lake City. When probed as to their reasons for this, the respondents indicated that
crowds (76%) and higher prices (20%) were the primary deterrents to skiing inJournal of Sport & Tourism 11
Utah during the Games (GOPB, 2000). In similar studies, 66% of Danish tourists indi-
cated that they avoided the Lillehammer region during the 1994 Olympic Winter
Games (Getz, 1997), and the Costa Brava region of Spain was shown to have lost
part of its summer season tourists during the 1992 Olympic Games in Barcelona
(Ministerio de Economı́ca, 1991, 1992, 1993; Ministerio de Industria, 1990). Similar
situations occurred during the 1984 Olympics in Los Angeles to theme park hotel
owners (ERA, 1984), and during the 1988 Olympic Games in Calgary with skier
visits (GOPB, 2000). As indicated in the model, Group E is further divided in two
subgroups: the ‘Pre/Post Switchers’ (E2) and the ‘Cancellers’ (E1). The Pre/Post
Switchers will come to the city/region but change the time of their visits to pre- or
post- event. On the other hand, the Cancellers will cancel their visit entirely. Preuss
(2005) also argues that new tourists and MICE tourists (Meetings–Incentives –
Conventions–Events) that are attracted by a major sport event will likely overcompensate
through increased consumption for both subgroup E1 and those who lose their interest
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in traveling to the host city/region due to a subjective negative image of the event.
Method
A 49-item questionnaire was developed to investigate a number of sport event tourism
issues. The analysis of the data from this study is expected to contribute to the litera-
ture by improving the methodology in order to better predict visitor impact during
major sport events. The questionnaire was developed following an in-depth assess-
ment of previous instruments and a comprehensive review of the scientific literature.
An instrument developed for investigating small events by Gratton et al. (2000) was
particularly important to this study, especially for items concerning the consumption
patterns of visitors. The method of examining consumption patterns by interest also
exists in the literature (Deery et al., 2005). The current research goes a step further by
seeking to identify the consumption patterns that are relevant to the study of econ-
omic impact. Here, an initial examination of the spending intentions of visitors pro-
vides the basis from which to decide whether or not event-affected persons provide
‘fresh’ money to the region. To measure this, the questionnaire was designed to
assess visitors by the intention of their visit (see Figure 1). Other areas important to
segmentation were: (a) the number and type of visitors at the Commonwealth
Games; (b) the number and prices of tickets purchased; (c) interest in other cultural
attractions or trips before and after the Games; (d) length of stay; (e) group visit; and
(f) visitor accommodations while in Manchester.
The 2002 Commonwealth Games was one of the largest sporting events in the world
with a sport program that included 17 sports and 3,690 participating athletes repre-
senting 72 nations. The event’s official website reported that ‘around one million visi-
tors are thought to have come to Manchester to see the event live and the world
television audience was estimated to top one billion’ (Manchester, 2002). Data collec-
tion took place during the 2002 Commonwealth Games in the four day period
between 2 August and 5 August 2002. The research team consisted of six sport man-
agement university students. Training sessions were conducted prior to leaving for12 H. Preuss et al.
Manchester and some of the researchers had previous field research experience from
the 2002 Olympic Games in Salt Lake City. The researchers disbursed across 15 differ-
ent locations to prevent bias from profiling only one type of spectator. The question-
naires were administered in English and the data were analyzed using SPSS.
Results
The results section includes demographic information on the respondents of this
study. Next, an analysis of the different groups that should be considered in estimating
economic impact will be presented. This will be followed by an examination of the
consumption patterns of multi-sport-event visitors.
From the 1,800 administered surveys, a total of 1,196 (66.4%) usable surveys were
achieved, with 51% of respondents being male and 49% female. Figure 2 outlines the
distances traveled by respondents to attend the 2002 Commonwealth Games. It is
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important to note that these data refer to distance traveled from last destination
visited and not necessarily the visitor’s home country.
Further, 91.3% of respondents came from the United Kingdom, meaning that
only 8.7% of visitors traveled from overseas destinations such as Australia (2.7%)
and New Zealand (1.9%). It is, however, important to note that 21.3% of respondents
did not answer the question related to distance traveled to the Games. Although we
cannot provide a precise reason for why this occurred, it is possible that the visitor
was not sure about how far they traveled, or perhaps they did not have to travel
any significant distance to attend.
The respondents’ ages ranged from 16 to 82 years, with a median age of 26, a mean
of 40.6 years and a standard deviation of 15 years. Figure 3 provides the average age of
respondents by locations investigated.
Figure 2 Distance Visitors had to Travel to Manchester (n ¼ 941).Journal of Sport & Tourism 13
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Figure 3 Average Age of Respondents by Sport Venue (Mean 40.6).
Further investigation of the data provided in Figure 3 reveals significant differences
in the age of spectators attending different events. For example, Field Hockey
(t ¼ 22.9; p , 0.05), Netball (t ¼ 217.85; p , 0.001), and Lawn Bowls (t ¼ 8.77;
p , 0.001) showed significant differences by age, with Lawn Bowl spectators being sig-
nificantly older while Field Hockey and Netball spectators were significantly younger.
To further emphasize the point that different sports attract different spectator groups,
a multiple logistic regression model using eight independent variables was conducted.
These variables describe the spectators from very different perspectives. We used ‘dur-
ation of stay’, ‘cost of accommodation’ (shows wealth), ‘gender’, ‘age’, ‘with whom did
you attend’ (shows group interest), ‘budget spent on merchandise’ (shows identifi-
cation with Games/Sports), ‘interest to attend the Games to rest and relax’ (shows
other interests beyond sport), and ‘interest to attend the Games to see sport’ (shows
particular sport interest) was run against four selected sports (Field Hockey
(n ¼ 129), Badminton (n ¼ 164), Rugby (¼440) and Lawn Bowls (n ¼ 143)). The
resulting model showed many variables which significantly split the groups. The
regression model noted that the eight factors as a group are a good predictor for
Rugby visitors (85.7%), while Lawn Bowls (51.5%), Field Hockey (33.3%), and Bad-
minton visitors need to be segmented by other variables.
Figure 4 shows the gender of visitors by location where the majority of data was col-
lected. Only Netball showed significant differences (x2 ¼ 4.62; df ¼ 1; p , 0.05) in
gender, predominantly female in this sample (n ¼ 143).
An important objective of this research is to identify those groups who drive the
primary economic impact of a sporting event. In this regard, results demonstrate
that all groups (i.e. Home Stayers, Time Switchers, Casuals, Games Visitors, Exten-
tioners, and Residents) attended the Commonwealth Games in Manchester 2002
(see Table 1). Note that we opted to substitute the group label ‘Event Visitors,’14 H. Preuss et al.
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Figure 4 Sport Venue and Gender of Respondents.
as used by Preuss (see Figure 1), with ‘Games Visitors’ since our study is related specifi-
cally to the Commonwealth Games.
Our results indicate that less than 50% of the respondents were Games Visitors (A)
and Extentioners (B). This finding supports that the proportion of visitors who are
actually visiting the host city to attend the Games is often over-emphasized in econ-
omic impact studies.
For the Games in Manchester, event visitors can be segmented into three groups
based on the economic impact they bring to the region. The first group did not
bring ‘fresh’ money to Greater Manchester. Their contribution involved a re-allocation
of leisure consumption they would have expended anyways (E2, G, H and K). In econ-
omic impact study, this segment is considered only if certain visiting groups spent
additional money above and beyond their normal tourist consumption patterns or
changed their spending patterns, or if residents changed their long-term spending pat-
terns or propensity to consume. These differences in behaviors would result in a
Table 1 Groups of Visitors to the 2002 Commonwealth Games in Manchester
Per cent in
this survey Group related to Figure 4
15.8% (C) Home Stayers: ‘I am resident and abstained from my vacation
in order to attend the Games’
4.9% (H) Time Switchers: ‘I am a tourist who wanted to travel to
Manchester anyway, this year or next year’
17% (G) Casuals: ‘I am a tourist and would have visited Manchester
even without the Games’, and ‘I am a tourist who wanted to
travel to Manchester anyway this year or next year’
46% (B) Games Visitors
(A) Extentioners
16.8% (K) Residents: Citizens living less than 50 km from main stadiumJournal of Sport & Tourism 15
different macroeconomic impact. The second group includes those who bring ‘fresh’
money into Greater Manchester (A, B, C). While A and B come as tourists, group C are
the Home Stayers who do not vacation outside of the region. Here, it is important to
consider the money they would have spent abroad (known as import substitution).
The third group is comprised of individuals who do not spend money that would
have been spent in the Greater Manchester if the Commonwealth Games had not
occurred. This can be considered as an opportunity cost for the region, which
would then need to be subtracted from the event impact (E1, D). As an equation,
the three groups form the additional input into a region as follows:
DY ¼ D(E2 þ G þ H þ K) þ (A þ B þ C) (E1 þ D):
Consumption Patterns of Multi-sport Event Visitors
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Most economic impact studies of sport events include the consumption information
of ‘normal’ tourists to a host city. To demonstrate that this may be an incorrect
approach, the current study shows that there are significant differences in the con-
sumption patterns of tourists (n ¼ 573), day visitors (n ¼ 240), and the residents of
the host city (n ¼ 380). Government research on visitors to Northwest England in
2002 showed that they stayed an average of 4.3 days and spent £45.24 per day (UK
Industry, 2005). In comparison, the results of the current research suggest that visitors
to the Commonwealth Games spent between £79.3 (staying with friends or relatives)
and £196.4 (staying at a four to five star hotel) per day. In both cases, visitors to the
Games spent significantly more than the ‘normal’ visitor to the region at other times.
If we remove accommodation from the equation, daily expenditures are found to be
quite similar for all tourists – from an average low of £76.9 (Bed & Breakfast/Youth
Hostel) to an average high of £113.3 (four to five star hotel). Cluster analysis reveals
that there is only one main cluster of tourists, as well as two small groups we called
‘Extreme Luxury Stayers’ and ‘Heavy Shoppers’. If we compare ‘tourists’ to ‘day visi-
tors’ and ‘residents’, we are able to determine whether the respondents from each
group (tourists, day visitors, residents) felt they had changed their consumption
during the Games in comparison to other holidays or to their typical daily expendi-
tures when at home. Figure 5 summarizes how ‘tourists’ felt they had changed their
consumption during the Games by showing how they compared their Games experi-
ence to other normal holiday consumption experiences.
Figure 5 Comparison of Consumption of Tourists during the Games and during other
Holidays.16 H. Preuss et al.
Figure 6 Comparison of Consumption of Day Visitors during Games and during other
Holidays.
Our findings suggest that tourists ate more fast food (t ¼ 3.42; p , 0.001) and used
more public transportation (t ¼ 4.46; p , 0.001) during the Games as compared to
other holidays. However, they also ate less often in restaurants (t ¼ 210.64;
p , 0.001), did less shopping (t ¼ 210.17; p , 0.001) and visited fewer ‘normal’
tourist attractions (t ¼ 213.29; p , 0.001).
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The ‘day visitors’ also showed significant differences in their consumption patterns.
One can note that the curve is shifted to the left when compared to that of the ‘tourists’
(see Figure 6).
Day visitors ate less fast food (t ¼ 22.28; p , 0.05) and went to restaurants less
often (t ¼ 212.03; p , 0.001). It seems that day visitors often brought their own
food to Manchester. This group also did less shopping (t ¼ 28.78; p , 0.001) and
visited normal tourist attractions less often (t ¼ 212.12; p , 0.001). This can be
explained by the fact that day visitors spent most of their time at the events
(purpose of the trip), thus leaving little time for other activities.
Residents were also asked about the changes in their consumption during the
Games versus their average daily consumption (see Figure 7).
Significant differences were found in two categories. Residents ate more fast food
(t ¼ 6.0; p , 0.001), and used public transportation more often than they did in
their normal daily lives (t ¼ 15.84; p , 0.001). However, it is important to note
that public transportation was free for Games ticket holders as parking capacity was
limited. Thus, the increase in public transportation should not be surprising.
Overall, these results strongly suggest that tourists, day visitors, and residents have
different consumption patterns during major sport events compared to during other
holidays, or during their normal daily lives.
To this point, we have distinguished the event-related persons as tourists, day visi-
tors and residents. The next step in our analysis is to determine whether there are other
Figure 7 Comparison of Consumption from Residents during Games and during
Daily Life.Journal of Sport & Tourism 17
variables that may split the group of visitors into subgroups with different consump-
tion patterns. This approach would mean a more precise evaluation of the economic
impact, and improve the ability to establish effective marketing strategies aimed at
specific target groups. The data is analyzed in two ways: (i) the visitors’ outlay (or
opportunity costs) to attend the Games, and (ii) the distance the visitor traveled to
Manchester.
The streams of persons (see Figure 1) leaving the city (D), or Crowded-Out Visitors
(E1), are often overlooked in economic impact studies but often create considerably
high opportunity costs. They could not be measured by our survey during the
Games (see more in Preuss, 2005, p. 292). However, results allowed for the segmenta-
tion of the visitors into four groups based on their interest in the Commonwealth
Games.
(1) ‘Residents’ (K): This is a group that visits the Games in their neighborhood. It is
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assumed that the majority of individuals making this group would not have tra-
veled to Commonwealth Games when hosted in other countries. This group has
both low costs to attend the Games and low opportunity costs resulting from the
Games.
(2) ‘Casuals’ (G) and ‘Time Switcher’ (H). These groups are visitors who are in
Manchester or wanted to visit Manchester at some point, regardless of the Com-
monwealth Games. Therefore these two groups do not purely come to Manchester
because of their interest in the Games. Their outlay to attend the Games is not very
high since they benefit from non-Games attractions and entertainment.
(3) ‘Home Stayers’ (C). These are also citizens of Manchester who have forgone their
typical holiday to another location in order to attend the Games. This is an import
substitution. Although their outlay to attend the Games is not high, they represent
high opportunity costs for the Home-Stayer as they forego their normal holiday
by preferring to stay for the Games.
(4) ‘Games Visitors’ (B) and ‘Extentioners’ (A). These are the real Games visitors who
came to or stayed in Manchester as a result of the Games. These groups spend con-
siderable amounts of money to attend the Games, which indicates a high prefer-
ence for the Commonwealth Games.
Based on the categorization above, it can be shown that the groups have different
consumption patterns (see Table 2).
On average, the respondents (n ¼ 1,196) attended the Games for 2.9 days. Resi-
dents (group 1) attended the Games for a shorter time period at 2.3 days
(t ¼ 26.04; p , 0.001), while Games Visitors (group 4) attended for a longer
period at 3.2 days (t ¼ 2.09; p , 0.05). The hypothesis that those who have higher
outlay attended more days than those who were living in Manchester proved to be
true. ANOVA was used to perform further analysis of the variables with standard
distribution, and non-parametric tests such as the Mann-Whitney-U-Test and
Kolmogorov-Smirnov-Z were used to analyze variables with non-standard distri-
bution. The tests revealed only a few significant differences between the
four groups. Home Stayers (group 3) and Games Visitors – those with higher18 H. Preuss et al.
Table 2 Consumption Patterns of Visitors with Different Motivation to see the Games
Group 1 Group 2 Group 3 Group 4
Casuals & Time Games Visitors &
Residents Switchers Home Stayers Extentioners
Outlay (or low medium high very high
opportunity
costs )
Respondents n ¼ 166 (16.8%) n ¼ 222 (21.9%) n ¼ 160 (15.8%) n ¼ 466 (46%)
Ø number days 2.25 (n ¼ 162) 3.04 (n ¼ 212) 2.77 (n ¼ 156) 3.16 (n ¼ 459)
Ø number 1.1 (n ¼ 165) 1.05 (n ¼ 214) 1.26 (n ¼ 159) 1.24 (n ¼ 456)
tickets/day
Ø spending £21.41 (n ¼ 40) £15.44 (n ¼ 138) £20.00 (n ¼ 29) £27.74 (n ¼ 340)
merchandise
Ø spending £86.93 (n ¼ 29) £64.87 (n ¼ 153) £74.88 (n ¼ 34) £89.65 (n ¼ 365)
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tickets
Attended with 60.9% (n ¼ 165) 47.7% (n ¼ 215) 59.4% (n ¼ 159) 58.2% (n ¼ 459)
family
Significance: N/A 2.49 (n ¼ 179) N/A 2.24 (n ¼ 401)
relaxation
Significance: N/A 3.58 (n ¼ 177) N/A 3.55 (n ¼ 400)
sports
Significance: N/A 2.23 (n ¼ 196) N/A 1.81 (n ¼ 433)
cultural events
Significance: N/A 2.46 (n ¼ 178) N/A 1.94 (n ¼ 401)
travel UK
outlay – purchased significantly more tickets than did Residents. Further, Games Visi-
tors did significantly more shopping than did Casuals (group 2). When analyzing Resi-
dents and Games Visitors, we note that the differences in the motivation to attend the
Games are reflected in the willingness to spend more money and time on the Games.
On average, Games Visitors spent significantly more money for tickets, and, when
compared against the Casuals, they spent significantly more on merchandising. All
these findings support the hypothesis that groups that accept higher outlay only do
so because they expect event-related benefits in return. This expectation translated
into longer stays in the host city, and increased spending on tickets and merchandise.
Other findings suggest that visitors were also attracted by the cultural activities that
ran parallel to the main sport event. These activities included the Culture Shock, the
Spirit of Friendship Festival, Queer Up North and a comedy festival. Three sites in
Castlefield, Exchange Square and Great Northern Square were established for live
broadcasts of the Games Opening and Closing Ceremonies. We find that Casuals
assigned significantly more importance to participating in cultural events than did
Games Visitors (F ¼ 8.52; p , 0.001). It also appears that Casuals were more prone
to travel before and/or after the Games in the UK (F ¼ 9.57; p , 0.001). Both
results were not surprising, since Casuals were in Manchester for reasons not
related to the Commonwealth Games.Journal of Sport & Tourism 19
When examining the social facet of the Games, it was discovered that only 3% of
spectators attended the Commonwealth Games alone. Casuals and Time Switchers
attended the Games with friends, while, for the most part, all other groups attended
with family members. In general, the varying visiting pattern was highly significant
among the groups (x2 ¼ 26.45; df ¼ 6; p , 0.001). Finally, it appears that the
Home Stayers (group 3) and the Games Visitors and Extentioners (group 4) had a
greater interest in the Games. In fact, they bought more tickets and merchandise
than did the Casuals and Time Switchers (group 2) and Residents (group 1). Their
increased interest in the Games is further suggested by their higher outlay.
We also conducted an empirical analysis of consumption patterns of visitors by dis-
tance traveled to Manchester (Table 3).
Results suggest that the number of days attended by visitors at the Games increased
by distance traveled to the Games. Similarly, the ANOVA analysis indicates that
average spending per day for merchandise and tickets appeared to increase in relation
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to the distance traveled as a significant difference (ANOVA) was found on the amount
spent on tickets between group 4 and groups 1 to 3. The analysis on merchandising did
not show significant differences, likely as a result of the high standard deviations of this
data. Non-parametric tests for this variable did not show differences as well. Simple
Table 3 Consumption Patterns of Visitors with Different Distances from Home to
Manchester
Group 1 Group 2 Group 3 Group 4 Group 5
Residents and
Home Stayers Day visitors Northern UK Rest of UK Foreign country
Distance traveled 0 – 30 miles 31– 150 miles 151 –270 miles .271 miles By airplane
Respondents n ¼ 128 n ¼ 338 n ¼ 324 n ¼ 69 n ¼ 82
(13.6%) (35.9%) (34.4%) (7.3%) (8.7%)
Ø number days 2.34 2.33 3.28 4.04 4.82
(n ¼ 125) (n ¼ 328) (n ¼ 316) (n ¼ 67) (n ¼ 79)
Ø number 1.31 1.39 1.16 1.17 1.00
tickets/day (n ¼ 126) (n ¼ 327) (n ¼ 320) (n ¼ 65) (n ¼ 80)
Ø spending £18.8 £21.89 £24.91 £31.69 £37.09
merchandise (n ¼ 60) (n ¼ 229) (n ¼ 243) (n ¼ 49) (n ¼ 53)
Ø spending £71.44 £77.17 £83.19 £123.65 £106.36
tickets (n ¼ 77) (n ¼ 252) (n ¼ 260) (n ¼ 54) (n ¼ 59)
Attended with 54.7% 59.2% 54.7% 56.7% 45.6%
family (n ¼ 128) (n ¼ 331) (n ¼ 316) (n ¼ 67) (n ¼ 79)
Significance: 2.21 2.34 2.35 2.12 2.35
relaxation (n ¼ 71) (n ¼ 272) (n ¼ 282) (n ¼ 60) (n ¼ 69)
Significance: 3.36 3.50 3.67 3.70 3.50
sports (n ¼ 78) (n ¼ 303) (n ¼ 310) (n ¼ 64) (n ¼ 76)
Significance: 1.87 1.88 1.91 1.97 2.22
cultural events (n ¼ 67) (n ¼ 271) (n ¼ 278) (n ¼ 60) (n ¼ 68)
Significance: 2.04 1.92 2.08 2.05 3.04
travel UK (n ¼ 67) (n ¼ 273) (n ¼ 279) (n ¼ 59) (n ¼ 74)20 H. Preuss et al.
correlation analysis indicates a significant correlation between consumption and dis-
tance traveled. The greater the travel distance to the Commonwealth Games, the more
money was spent on tickets (r ¼ 0.12; p , 0.05). The greater distance traveled also led
to an increase in the number of tickets purchased (r ¼ 0.199; p , 0.001), as well as
significantly longer stays in the city (r ¼ 0.319; p , 0.001). With the exception of
Overseas Visitors (group 5), over 50% of the members of each group traveled to the
venues with family members. This demonstrates the importance of social factors in
the consumption patterns of visitors at major sporting events. It was not surprising
to find that Overseas Visitors were significantly more interested in traveling
within the UK before and/or after the Games (F ¼ 16.52; p , 0.001) than residents
of the UK.
Conclusion
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The empirical findings of this study, which profiled visitors of the 2002 Common-
wealth Games in Manchester, provide the following results:
(1) Calculating the economic impact that results from the consumption of Games-
affected persons is very difficult. Many different groups must be considered in
order to detect the overall consumption impact. For example, opportunity costs
of crowded-out visitors and residents that leave the city during the Games are
complex to measure but still must be considered.
(2) Games Visitors to the Commonwealth Games can be segmented into different
groups. As shown with Lawn Bowls, Netball and Field Hockey the spectators
differ significantly in age and gender. Our regression analysis suggests that it
may be possible to predict the type of visitors/spectators at different sporting
events. This information could be used to develop targeted marketing strategies
designed to draw the different groups to specific sporting venues. More research
should be conducted over time to refine this model.
(3) Even if we measure subjective appraisals, the aggregation of data shows that
Games Visitors consume differently during Games than they do during normal
holidays. Furthermore, we noted that Residents make changes in their consump-
tion patterns during the Games. This should be further explored in future econ-
omic impact studies.
(4) The consumption pattern of spectators is dependent upon their outlay (opportu-
nity costs). Those that have higher outlay show a greater intention to attend the
Commonwealth Games and therefore spend more time in Manchester, and buy
more tickets and merchandise. It is not surprising that we also found significant
differences, other than consumption, among those visitors who wanted to travel
to Manchester even in the absence of the Games. They demonstrated greater inter-
est in visiting cultural events or adding a trip in the UK before or after the Games
than those who came only to see the Games.
(5) The consumption pattern was also correlated to the distance traveled by spectators
to attend the Commonwealth Games. The greater the distance a visitor traveled,Journal of Sport & Tourism 21
the more time and money they spent in the city. Therefore, it may be economically
wise to attract as many foreign visitors as possible for to major sport events.
(6) The cluster analysis on the consumption pattern did not show many strong
clusters. Only one cluster dominated, revealing that the pattern of spectators
(food, tickets, transport, shopping, entertainment, others) was dominated by
large standard deviation. Thus, for future research, an economic impact analysis
could work with an average consumption pattern of Games visitors. The signifi-
cant differences in money spent on accommodations should also be considered.
As a result, the different groups may be built into an analysis using accommo-
dation categories.
The importance of emphasizing the consumption patterns of residents and tourists
in forecasting the economic impact of major sport events was revealed through this
study. When political decisions to host or not to host a major sport event are based
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on studies that do not correctly estimate the visitors’ impact, there may be two con-
sequences: first, public authorities might decide whether or not to bid for an event
based on false assumptions; second, the local tourism industry might fail to prepare
adequately for the consumption needs of their customers.
Overall, this research makes three important contributions to the literature. First, it
provides empirical evidence that different sports attract people of different ages and
genders. This means that event hosts must be aware of the visitor demographics
they attract and adjust their targeted marketing efforts accordingly. Second, an
important clarification for economic impact study is highlighted; namely, that it is
inappropriate to the potential impact of visitors without first carrying out a segmen-
tation exercise. Finally, and importantly, the need for improved metrics for economic
impact study was clearly identified. Specifically, it was noted that there is a need for
metrics that measure economic impact while considering segmentation effects.
In terms of future research, it is suggested that the consumption patterns of visitors
be evaluated at other major events. The results of this research also demonstrate how
visitors at major sport events are also the physical audience at the events and produce
an atmosphere that appeals to television audiences and broadcasters. As seen at the
2004 Olympic Games in Athens and the 2006 Olympic Games in Turin, small live
audiences decrease the special aura of excitement at the Olympic Games. A large tele-
vision audience is a key element in maximizing revenues from the sales of broadcast-
ing. However, revenues from broadcasting rights do not necessarily lead to financial
benefits for the host city. For the host community, increased visitor consumption
during the Games is a key factor to its financial success.
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