Description
The purpose of this paper is to examine the spending patterns of non-local participants and
spectators at a medium-sized international sport event, to segment their spending patterns and
consider implications for the quality of each segment’s event experience
International Journal of Culture, Tourism and Hospitality Research
Visitor composition and event-related spending
Marijke Taks B. Christine Green Laurence Chalip Stefan Kesenne Scott Martyn
Article information:
To cite this document:
Marijke Taks B. Christine Green Laurence Chalip Stefan Kesenne Scott Martyn, (2013),"Visitor composition and event-related spending",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 7 Iss 2 pp. 132 - 147
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Bing Pan, Tzung-Cheng Huan, (2013),"New perspectives on festival and events research", International J ournal of Culture, Tourism and
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J udith Mair, Michelle Whitford, (2013),"An exploration of events research: event topics, themes and emerging trends", International J ournal
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Stephen Litvin, Bing Pan, Wayne Smith, (2013),"Festivals, special events, and the “rising tide”", International J ournal of Culture, Tourism
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Visitor composition and event-related
spending
Marijke Taks, B. Christine Green, Laurence Chalip, Stefan Kesenne and Scott Martyn
Abstract
Purpose – The purpose of this paper is to examine the spending patterns of non-local participants and
spectators at a medium-sized international sport event, to segment their spending patterns and
consider implications for the quality of each segment’s event experience.
Design/methodology/approach – Spending in nine sectors of the economy is measured via
self-report, and respondents are segmented into ?ve groups: spectators, athletes, coaches, of?cials,
and other participants (e.g. media, medical staff). The daily and aggregate spend for each segment in
each economic sector is calculated and compared. Regression analysis tests differences among
segments for each economic sector.
Findings – Participants account for 39 per cent of aggregate spend; coaches are the biggest
spenders; athletes spend relatively little. The segments spend differently on hospitality, private
transportation, grocery, and retail, with spectators spending signi?cantly more than the participant
groups on hospitality and private transportation, and signi?cantly less on groceries and merchandise.
Spending in sectors normally associated with celebration and festivity accounts for only 8 per cent of
total spend.
Research limitations/implications – Findings are derived from a single event, but are consistent with
other work, suggesting that inadequate attention is given to opportunities for festive celebration,
especially among athletes.
Practical implications – Coaches are a particularly useful target market for retailers, whereas hoteliers
and service stations should target their marketing at spectators. Event organizers should do more to
build festivals.
Originality/value – This paper identi?es the ways that different segments organize their spending at an
event, and demonstrates that greater attention to festivals could enhance a sport event’s overall impact.
Keywords Sporting events, Economic sectors, Hospitality, Festivals, Visitor spending,
Event segmentation, Economic impact, Leisure activities
Paper type Research paper
Introduction
Events have become a vital part of community economic development and planning (Chalip,
2004) – so much so that communities often develop an entire portfolio of events in order
optimize the overall economic value obtained (Ziakas, 2010). Yet, when the expenditures of
event visitors are analysed, it is sometimes noted that the economic bene?ts do not reach the
levels that are expected or desired (Crompton and Lee, 2000) or that the distribution of
bene?ts is so poor that some sectors of the economy do well, while others may actually be
worse off (Putsis, 1998). Indeed, it has been shown that event visitors may spend very little
beyond the event itself, particularly in the case of small or medium-sized events (Nogawa
et al., 1996), although the amount that visitors spend for things other than event fees,
accommodation, and food varies substantially across events (Daniels and Norman, 2003).
When events are compared, it appears that the key to optimizing spend is to create
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Marijke Taks is based in the
Department of Kinesiology,
University of Windsor,
Windsor, Canada.
B. Christine Green and
Laurence Chalip are based
in the Department of
Kinesiology and Health
Education, University of
Texas at Austin, Austin,
Texas, USA. StefanKesenne
is based in the Department
of Economics, University of
Antwerp, Antwerp,
Belgium; and Human
Kinesiology Department,
Catholic University of
Leuven, Leuven, Belgium;
and Euromed Marseille
School of Management,
Marseille, France.
Scott Martyn is based in the
Department of Kinesiology,
University of Windsor,
Windsor, Canada.
The authors gratefully
acknowledge the research
grant received from the Social
Sciences and Humanities
Research Council of Canada for
this project (no. 140370).
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conditions that encourage spending (Wilson, 2006). This is one reason that event strategists
encourage sport event organizers to foster festival; it creates a sense of celebration (see
Handelman, 1990) that can stimulate visitor spending (Chalip and Leyns, 2002; Green and
Chalip, 1998).
To date, studies of spending by event attendees have focused on their aggregate spend
across economic sectors. Previous work has typically chosen not to segment the spend by
visitor category. From a practical marketing standpoint, it would be particularly useful to
understand how event visitor segments differ in their spending patterns, as that could
enable more targeted marketing. From a conceptual standpoint, understanding the ways
that different groups choose to spend can enable a better grasp of the ways that event
visitors construct their event experience. In particular, it is of interest to consider the relative
degree to which spending is strictly in support of event attendance, and the degree to which
spending may also support festive celebrations. This study examines those matters.
Literature review
Although sport events are typically described in terms of the competition and entertainment
they provide, one of the core attractions of sport events is that they enable an array of festive
occurrences, some of which are designed and some of which are spontaneous.
Consequently, a number of sport events now incorporate festivals as add-ons to the
competition speci?cally to attract spectators or participants (Burdsey, 2008; Jowdy and
McDonald, 2002/2003), while others provide festival spaces to enable spontaneous
production of festival during events (Frew and McGillivray, 2008). While there is certainly
some advantage to festival that is incorporated into event design, the spontaneous
emergence of festive behaviour provides a particularly positive hedonic experience (Green
and Chalip, 1998).
The experience of a sport event encompasses much more than the sport activity or
entertainment. The event is part of the overall tourism experience. Indeed, it becomes more
attractive to the degree that attendees can incorporate an array of tourism experiences
during the event (Chalip and McGuirty, 2004), particularly because those can help to impart
a sense of festivity (Chalip, 1992, 2006). This is important not merely because it represents
an added attraction to the event, but also because it can stimulate spending during an
event, which therefore enhances the event’s overall economic impact (Chalip, 2004; Wilson,
2006). Thus, strategic leverage designed to amplify an event’s economic impact requires
attention to the creation of festival, while the creation of festival must be informed by an
understanding of event attendees’ preferred patterns of consumption.
There has been increasing interest in determining the spending patterns of different tourists
in order to enable better prediction of tourist demand and enhanced targeting of marketing
communications (Laesser and Crouch, 2006), and to enhance the overall quality of the
consumption experience (Bailey et al., 2009). This is particularly important for events, as
event attendees differ from other tourists not merely in terms of their particular interest in
sport, but also in their patterns of consumption (Boo et al., 2009). They are comparatively
less interested in traditional tourismactivities and souvenirs, and more interested in activities
and products that can complement their overall event experience. Consequently, there is
clear value in identifying the ways that spending varies among different segments of event
visitors (Preuss et al., 2007).
The challenge, of course, is to segment attendees in a manner that is meaningful both
conceptually and practically. The sport tourism literature argues that many different types of
event attendees can be distinguished. Robinson and Gammon (2004), for instance,
distinguish ‘‘sport tourist’’ (i.e. primary visitors) and ‘‘tourism sport’’ (i.e. casual visitors),
based on the consumer’s motivation. Other authors differentiate between ‘‘active’’ and
‘‘passive’’ sport tourists, based on the consumer’s behaviour (e.g. Gibson, 1998; Ritchie
et al., 2002; Standeven and De Knop, 1999). Economic impact studies make a distinction
between ‘‘local’’ and ‘‘non-local’’ visitors (Dwyer et al., 2000; Hodur and Leistritz, 2006).
Preuss (2005) suggests 11 different types of event-affected persons: residents, home
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stayers, runaways, changers, casuals, time switchers, avoiders/cancellers, avoiders/ pre-,
post switchers, extensioners, and event visitors. He argues that some of these types of event
attendees bring new money from outside into the host region, potentially creating a positive
economic impact, while other types of affected persons create a crowding out effect, leaking
money out of the local economy and thus inducing a negative economic effect.
As compelling as the various kinds of segments might seem, it is often impractical to identify
and classify attendees in advance of the event, when their expected spending differences
would be useful for planning. Contemporary methods for collecting spending data also make
it impractical to segment the event market into a large array of conceptual categories.
However, event attendees do take on different roles at events (e.g. spectators, athletes,
coaches, of?cials), and those roles are suf?ciently visible that it is relatively straightforward to
differentiate those groups prior to the event. Further, their roles are often associated with other
factors known to affect spending, such as patterns of interest, age, and income (see Fennell
et al., 2003; Lehto et al., 2002). Consequently, it is of some interest to explore the degree to
which spending can be usefully segmented as a function of the attendee’s role in the event.
The purpose of the study is to analyse event visitor role and event-related spending in order
to determine which sectors in the local economy bene?t most from which visitor role, and to
derive implications for fostering future event and tourism spending. The study examines
these matters via an analysis of The 2005 Pan American Junior Athletic Championships. As a
one-time international sport event, for which a new stadium was built, this event created very
high expectations for the hosting community. The event was considered to provide unique
opportunities to boost tourism, positively impacting local business and thus the local
economy. In addition, as a prime example of a ‘‘spectator/competitor event’’ (Gratton and
Taylor, 2000) this type of event provided the range of visitor segments required for this study.
Other annual tournaments hosted in this region, such as hockey tournaments, represent
‘‘participant events’’ (Gratton and Taylor, 2000). Spectators of the latter types of events are
limited in number and are mainly accompanying persons. Overall, these annual events draw
fewer non-event related spectators than international events like the Pan American Junior
Athletic Championships. The 2005 Pan American Junior Athletic Championships were
therefore an appropriate context for this study.
The Pan American Junior Athletic Championships
The Pan American Junior Athletic Championships are organised bi-annually in various Pan
American countries under the auspices of the International Association of Athletics
Federations (IAAF) and the Pan-American Athletics Commission (PAC). The 2005 event was
hosted in Windsor, from28-31 July, by the University of Windsor (Ontario), in partnership with
the local Track and Field Club, the community, and corporate and regional partners. A total
of 35 countries were represented at the Championships. Since it was a ‘‘junior’’
championship, the athletes were under 19 years of age. Consequently, the athletes
travelled with their team and were accompanied by coaches and team of?cials. In some
cases, family members and/or friends also accompanied the athletes on their journey. Event
organizers sought to foster a festive atmosphere, and visitors were encouraged by event
organizers to experience the city of Windsor, including its shops, parks, restaurants, and
entertainments.
Gratton and Taylor (2000) de?ne this type of event as a ‘‘type C’’ sporting event (i.e. an
irregular, one-off major international spectator/competitor event). Accurate numbers for the
different types of event attendees were available from the Local Organizing Committee
(LOC, 2005), from which population estimates could be calculated. Since economic impact
should only be measured from the ?ow of foreign money into the city, region, or country, and
the additional income created (Crompton, 1995; Putsis, 1998), only expenditures of
non-local visitors, whose primary purpose was to attend the event, were taken into account
(assuming locals did not behave differently because of the event). ‘‘Non-locals’’ are de?ned
as visitors living outside the county region under investigation. In this particular type of event,
the majority of the participants are non-locals, while only a small portion of the spectators are
non-local.
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Method
Questionnaire
Data on visitor spending were collected from responses to written questionnaires
administered during the event. Two slightly different questionnaires were developed for
the spectators and the participants. The complete questionnaire for the spectators
consisted of four major parts, including a section on: the respondent’s role in the event and
daily expenditures; tourism behaviour; motives and identity of event attendees; and
demographic data. The ?rst three sections were also incorporated in the participants’
questionnaire. The latter did not include a separate section on demographics, but enquired
about age and gender at the beginning of the questionnaire. This paper uses the data on
visitor spending that were collected in section 1. The section on visitor spending differed
slightly between spectators and participants. The survey instrument queried spectators
about: their role in the event (related to any of the event participants or not), place of
residence (to distinguish between locals and non-locals), purpose of the visit (primary,
casual), daily spending of their party during the visit (tickets and admission fees,
transportation, food, lodging, shopping, entertainment, other), length of stay (number of
nights), the number of people in the party, type and location of accommodation. The
question about daily expenditures for spectators enquired about their actual spending and
was as follows: ‘‘Thinking about all the things that you did yesterday, approximately how
much did you and your immediate travel party spend (regardless of who was paying the bill)
in the Windsor-Essex County area for each of the following categories. If you arrived today,
please answer in terms of today’s expenditures.’’
The participant survey queried: their role (athlete, coach, administrator, of?cial,
journalist/media, other), their involvement in athletics (number of years and speciality),
place of residence (to distinguish between locals and non-locals), the number of
accompanying people (relatives or friends), and personal daily spending during the visit
(expenditure categories similar to those of the spectators except for tickets and admission
fees), and length of stay (number of nights). The question about daily expenditures for
participants was based on their estimation, and was phrased as follows: ‘‘How much money
will you personally spend on a daily basis during your visit in the Windsor/Essex County area
for each of the following categories’’. The questionnaires were available in English and
Spanish, because of the Pan American context.
Data collection
The data collection was different for spectators and participants. Spectator data were
collected during the opening ceremony and during all sessions of the three day event.
Members of the research team randomly approached as many event attendees as possible
and invited them to participate in the study as they entered the front gate, and as they
watched fromthe stands. Members of the research team were stationed at different areas of
the facility. If the spectators agreed to participate, they received a pencil and an envelope
containing the survey and a letter of information and consent explaining the study and
describing respondents’ ethical rights concerning their participation. The survey took
approximately ten minutes to complete. Respondents were instructed to place the
completed survey in the envelope provided and return it to the research booth (located
nearby) in exchange for a token of appreciation (a frisbee bearing the event logo). All
participants (athletes, coaches, and of?cials) received the questionnaire in their welcome
package. They were asked to return their completed questionnaire to the research booth any
time during the event. As an incentive to partake in the study, the participants were invited to
participate in a draw for a prize.
Sample
A total, of 2,067 questionnaires were handed out to the spectators, of which 1,290 were
returned (response rate ¼ 62:41 per cent); of the 740 questionnaires handed out to the
participants, 256 were returned (response rate 34.59 per cent). Thus, of the total of 2,829
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questionnaires that were distributed, 1,546 were returned (response rate ¼ 54:64 per cent),
of which 1,379 were usable.
For the purpose of this study, only the expenditures of non-local event attendees (n ¼ 428
responses) are considered, as these generate new spending for the local economy. The
following ?ve visitor segments are distinguished:
1. spectators (n ¼ 217);
2. athletes (n ¼ 123);
3. coaches (n ¼ 32);
4. of?cials (n ¼ 38); and
5. ‘‘other’’ participants (such as media, therapists, medical staff, other administrative roles;
n ¼ 18).
In the spectator group, only spectators whose primary purpose was to attend the event were
included, as the objective was to determine spending stimulated by the event, rather than
coincident with it. Note that athletes, coaches, of?cial and ‘‘other participants’’ all completed
the participant survey, and are therefore segments within the participant group.
Population numbers with regard to the spectators were estimated as follows: the numbers of
spectators at opening night was approximately 4,000, and another 4,000/day for the
subsequent three event days, totalling 16,000 spectators. However, this number includes
double counting. The average attendance of the spectators was 1.7948 (SD ¼ 0:86) days.
The number of ‘‘unique’’ spectators is thus estimated to be 8,915. According to our survey,
19 per cent of the spectators were non-local visitors whose primary purpose was to attend
the event, compared to 76 per cent locals, and 5 per cent non-local casual spectators. The
total number of non-local primary spectators is therefore estimated to be 1,694.
Exact numbers of non-local participants were available from the Local Organizing
Committee (LOC, 2005) for the athletes (n ¼ 442), coaches (n ¼ 143) and of?cials (n ¼ 65).
The number of ‘‘other participants’’ (n ¼ 47) was estimated based on survey results (of the
’’other participants’’, 82 per cent were non-local). The share of each participant category in
the response group aligns with the actual attendance numbers; coaches are slightly
underrepresented in the response group while of?cials are slightly overrepresented.
Data analysis
Cross-sector distribution is estimated by calculating the amount of money spent in nine
different economic sectors by each visitor segment during the time of the event:
1. private transportation rental;
2. private transportation operation (parking, gas, repairs);
3. local transportation (bus, taxi, limo);
4. hospitality (hotels, lodging);
5. food and beverage at grocery stores;
6. food and beverage at restaurants, bars and concessions;
7. entertainment and recreation;
8. retail and merchandise (clothing, gifts, souvenirs, merchandise); and
9. other retail.
Event expenditures were calculated by multiplying the daily expenditures in each sector of
the local economy by the number of days. ‘‘Number of days’’ was a newly created variable
based on the ‘‘number of nights’’, an original variable in the survey; if the number of nights
was 0, then the number of days was 1; else the number of days equalled the number of
nights þ0.5. This assumption was based on the fact that people who spent, for example 2
nights, normally arrived half a day early, or stayed another half a day before leaving. The
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average number of days for the non-local spectators was 3 (SD ¼ 2:1), for the athletes 6.15
(SD ¼ 1:2), for the coaches 6.19 (SD ¼ 1:30), the of?cials 5.08 (SD ¼ 1:4) and the other
participants 6.44 (SD ¼ 1:11; see also Table I).
Daily expenditures more than two standard deviations from the mean were considered to be
outliers. Outliers were replaced with the next highest daily expenditure level within each
visitor segment. In addition, spectators’ daily expenditures were initially asked based on the
number of people in the party; therefore, daily expenditures of spectators were ?rst divided
by the number of people in the party, and subsequently multiplied by the number of days, in
order to calculate an average event expenditure per person per visitor segment. All dollar
amounts are reported in Canadian dollars.
Descriptive statistics illustrate the characteristics of each visitor segment (spectator,
athletes, coaches, of?cials, other participants). In order to predict which visitor segment best
predicts event expenditure in a speci?c sector in the local economy, a linear regression was
executed with visitor segments (dummy variables), age and gender as independent
variables. The dependant variables, event expenditures in each sector, were log
transformed to normalize the distribution. This is a standard procedure when modelling
economic data, and is typically essential in order to enable the estimation of linear
relationships among variables when performing regression analyses (Wang, 2009, pp. 22-3).
The regression model was:
Log event expenditure by eector ¼ f{age, gender, visitor type[dummy variables,
1 type as reference category]}.
Finally, the overall impact of the visitor segments on each sector of the local economy was
calculated at the aggregate level by multiplying sector event expenditures per visitor
segment by the population numbers in each segment. The overall contribution in each
economic sector is calculated, and then analysed for each visitor segment.
Event expenditures by visitor segment
Table I describes the characteristics of each visitor segment. Coaches and of?cials are
predominantly male (66 per cent and 58 per cent respectively); while spectators, athletes
and ‘‘other participants’’ are predominantly female (53 per cent, 55 per cent, and 61 per cent
respectively). The athletes stand out with regard to their age (M ¼ 18). All other visitor
segments are middle aged, with averages from 41 for ‘‘other participants’’ to 45 for the
spectators.
Inspection of Table I shows that coaches are the big spenders with an average total event
expenditure of $1,452, followed by ‘‘other participants’’ (M ¼ $994). The three other
Table I Descriptive statistics: sex, age, length of stay, and average event expenditure by visitor segment
Spectators Athletes Coaches Of?cials Other part.
n SD n SD n SD n SD n SD
n-response 217 123 32 38 18
Women (%) 53 55 34 42 61
Age (yrs) 45 16 18 1.4 42 9 53 13 41 11
n-days 3 2.1 6.15 1.2 6.19 1.3 5.08 1.4 6.44 1.1
Average Expenditure ($ CND)
Priv. transp. rental 34 117 8 49 20 98 8 46 150 635
Priv. transp. operation 33 85 7 42 9 49 28 74 11 48
Local transportation 5 32 8 32 45 144 3 18 23 80
Hospitality 174 400 55 282 195 767 31 136 101 300
Food and beverage at grocer 13 39 26 57 72 163 25 54 45 65
Food and beverage at restaurants 112 210 64 131 278 476 164 215 176 273
Entertainment and recreation 19 95 25 78 48 145 55 136 76 160
Retail and merchandise 76 177 275 353 727 735 207 233 402 514
Other retail 5 36 23 124 58 228 11 37 10 29
Total per person spend 472 841 492 675 1,452 1,971 532 400 994 1,299
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segments (spectators, athletes and of?cials) each spent around $500 per event. The
coaches’ expenditures stand out in four sectors of the local economy: retail and
merchandising ($727), food and beverage at restaurants and concessions ($278), food and
beverage at grocery stores ($72) and local transportation ($45). Their expenditure for
hospitality is also substantial ($195). As is the case for coaches, ‘‘other participants’’ spent
the largest portion of their event expenditures on retail and merchandise ($402), followed by
food and beverages at restaurants ($176). This segment stands out with regard to private
transportation, speci?cally car rental ($150), compared to other visitor segments. This group
also shows the highest expenditure in the entertainment sector ($76).
Interestingly, retail and merchandise consumes a substantial portion of the event expenditures
of all segments for the participant group, but is much less important in the budget of
spectators. The non-local spectators spent most of their money on hospitality, which is
normally hotels ($174)) and food and beverage at restaurant and concession stands ($112).
Predictors of event expenditures in speci?c economic sectors
Event expenditures were log normalized and predicted based on visitor segments, age and
gender. Visitor segments were transformed into dummy variables. The correlation matrix for
variables in the model is presented in Table II. (Correlations between visitor segments are
irrelevant and are therefore not represented in the table.) The correlation between athlete role
and age accounts for almost 50 per cent of the variance. This is not surprising, since the event
is a junior event, and all athletes are younger than 19 years of age. Inspection of Table II also
shows that spectators are signi?cantly older than those in other roles, as are the of?cials. There
does not seem to be any signi?cant relationship between gender and spectator segment.
Results of the regression analyses are presented in Table III. Only the four categories of
spend for which signi?cant prediction was obtained are shown. The segment ‘‘other
participants’’ is left out of the model as it serves as reference group for the other four visitor
segments. Four models were signi?cant: hospitality, food and beverage at restaurants,
private transportation operation and retail and merchandise (R
2
varying from 0.03 to 0.24).
Inspection of Table III shows that spectators contribute signi?cantly to the hospitality sector
through spending on hotel accommodation. Spectators also positively impact the local
Table II Correlation matrix of variables in the regression model
Sex Spectators Athletes Coaches Of?cials Other participants
Age 0.11 0.42 20.70 0.08 0.28 0.04
Sex 20.03 20.05 0.10 0.06 20.04
Table III Predictors of sector spending: results of the regression analyses
Hospitality
Food and beverage at
grocery stores Private transport operation Retail and merchandise
Predictors B SE b B SE b B SE b B SE b
Constant 0.09 0.67 2.3 0.53 20.27 0.44 4.40 0.6
Age 0.02 0.01 0.11 20.01 0.01 20.06 0.01 0.01 .14* 0.01 0.01 0.10
Gender 0.10 0.23 0.02 20.14 0.18 20.04 20.06 0.15 20.02 20.32 0.22 20.06
Spectators 1.50 0.57 0.30** 21.09 0.45 20.29* 1.62 0.38 0.46*** 22.63 0.56 20.51***
Athletes 0.02 0.62 0.00 20.88 0.49 20.21 0.21 0.41 0.05 20.28 0.61 20.05
Coaches 20.30 0.69 20.03 20.39 0.55 20.06 20.12 0.46 20.02 0.93 0.67 0.10
Of?cials 20.41 0.67 20.05 20.63 0.54 20.10 0.59 0.45 0.10 20.95 0.66 20.11
R
2
0.14 0.03 0.24 0.22
F(6, 421) 11.631 2.062 22.38 20.136
p *** ,0.057 *** ***
Note: *p , 0:05; **p , 0:01; ***p , 0:001
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transportation operation sector through expenditures related to gas and parking fees.
Spectators contribute substantially less to the food and beverage retail sector (grocery) and
the retail and merchandise sector than do other segments. Age only appears to be a
signi?cant predictor for private transportation operation (i.e. older people spent more money
on gas and parking). Remaining models predicting food and beverage at restaurants and
concessions, private transportation rentals, local transportation, entertainment and
recreation, and other retail failed to yield signi?cant prediction.
The dummy variables for sector are estimated with reference to the ‘‘other participant’’
category. In order to compare sectors, it is useful to note whether the parameter estimate for
each is more than two standard errors fromany other (in other words, whether the difference
between the two standard errors is non-zero at the 95 per cent con?dence level). In one
case, the prediction of retail and merchandise expenditures, the parameter for coaches is
more than two standard errors from every other estimate. Thus, although the parameter
estimate for coaches does not differ signi?cantly from the baseline set by ‘‘other
participants’’, it is signi?cantly different from that of all other segments. Further, the
parameter is positive while others are negative. Thus, coaches spent signi?cantly more on
retail and merchandise than did spectators, athletes, or of?cials.
Cross-sector distribution by visitor segment at the aggregate level
The analyses reported above show different expenditure patterns according to visitor
segments. The aggregate impact of each sector on the local economy is, of course,
dependent on the size of these segments. Aggregated expenditures in the different sectors
of the local economy are calculated using the average event expenditure £ population
estimates for each visitor segment. The numbers are presented in Table IV, and graphically
illustrated in Figures 1 and 2.
Inspection of Table IV shows that spectators made up 71 per cent of the non-local visitors,
and spent approximately $800,000 (61 per cent) of the total newmoney coming into the local
community. The participant group (i.e. athletes, coaches, of?cials, and ‘‘others’’) made up
29 per cent of the non-local visitors and contributed approximately $500,000 (39 per cent) of
the new money coming into the local community.
Almost one-third of all non-local visitor spending goes to retail and merchandise (30 per
cent), followed by hospitality (27 per cent) and food and beverage at restaurants (21 per
cent). The large share of retail and merchandise is linked to the spending patterns of the
participant segments, while the shares in the hospitality and restaurant sectors are due to
spectator spending. Thus, although smaller in numbers, the participant segments spent a
substantial amount of money in the retail and merchandise sector. For athletes and coaches
this is about 50 per cent, and for of?cials and ‘‘other participants’’ about 40 per cent of their
total spending. This is in contrast to the spectators who spent only 16 per cent of their total
event expenditure on retail and merchandise.
At the aggregate level, the impact of the of?cials and ‘‘other participants’’ is minimal, due to
their low numbers. Aggregate spending of athletes and coaches is fairly equitable in sectors
such as retail and merchandise, hospitality, and food and beverage at restaurants.
Therefore, Figure 2 compares the ?nal expenditure of non-local spectators versus the
participant group (including all participant segments: athletes, coaches, of?cials, and other
participants). Non-local spectators contribute substantially more to four of the nine
economic sectors (i.e. hospitality, food and beverage at restaurants, private transportation
rental and operation). Participants, although lower in numbers, contribute substantially more
to the retail and merchandise sector and ‘‘other retail’’.
Discussion
Results are consistent with Gratton and Taylor’s (2000) typology of sport events. In their
typology, this event would be classi?ed as a ‘‘spectator/competitor’’ event. It generates a fair
bit of new spending into the local economy (estimated here at over $1.3 million) while using
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predominantly volunteer labour. In addition, a new facility was built to host the event,
increasing the overall economic impact on the local economy to about $ 11,000,000 in direct
spending (Taks et al., 2008). While these ?nal expenditures are often used as a basis to
calculate a net increase in economic activity in the local economy through input-output
modelling, the relevance of these types of economic impact analyses is being questioned
since it omits the cost of hosting the event. Therefore, several authors argue that cost-bene?t
analysis is a more appropriate way to re?ect on the net effects of events (e.g. Dwyer et al.,
2006a, b; Kesenne, 2005; Mules and Dwyer, 2005; Porter and Fletcher, 2008). Previous
calculations for the 2005 Pan American Junior Athletic Championships support this claim.
Input-output analysis revealed that the ?nal expenditures of $ 11,000,000 generated a net
increase in economic activity in the city of Windsor of $ 5,617,681 (Taks et al., 2008), while
the cost-bene?t analysis disclosed a net de?cit of $ 451,676 (Taks et al., 2010). Further,
participants account for well over a third of the total new expenditures. This is quite different
from mega sporting events, where most of the impact is generated from spectators. The
utility of segmenting the spending is illustrated by the fact that the different segments of
non-local event attendees show different expenditure pro?les during the event.
Coaches were the big spenders during this event, with an average spend of about $1500.
This is three times the amount spent by athletes, of?cials or non-local spectators, who spent
Table IV Non-local visitor spending at the aggregate level in the different sectors of the local economy by visitor segment
Spectators Athletes Coaches Of?cials Other part. Total
n-population 1,694 442 143 65 47 2,391
% 71 18 6 3 2 100
$ % $ % $ % $ % $ % $ %
Retail and merchandise
$ 128,744 16 121,550 56 103,961 50 13,455 39 18,894 40 386,604 30
% 33 31 27 3 5 100
Hospitality
$ 294,756 37 24,310 11 27,885 13 2,015 6 4,747 10 353,713 27
% 83 7 8 1 1 100
Food and beverage at rest.
$ 189,728 24 28,288 13 39,754 19 10,660 31 8,272 18 276,702 21
% 69 10 14 4 3 100
Priv. transp. rental
$ 57,596 7 3,536 2 2,860 1 520 2 7,050 15 71,562 5
% 80 5 4 1 10 100
Priv. transp. operation
$ 55,902 7 3,094 1 1,287 1 1,820 5 517 1 62,620 5
% 89 5 2 3 1 100
Food and beverage at groc.
$ 22,022 3 11,492 5 10,296 5 1,625 5 2,115 5 47,550 4
% 46 24 22 3 4 100
Entertainment and recr.
$ 32,186 4 11,050 5 6,864 3 3,575 10 3,572 8 57,247 4
% 56 19 12 6 6 100
Other retail
$ 8,470 1 10,166 5 8,294 4 715 2 470 1 28,115 2
% 30 36 30 2 2 100
Local transportation
$ 8470 1 3,536 2 6,435 3 195 1 1,081 2 19,717 2
% 43 18 33 1 5 100
Total event spending
$ 799,568 100 217,464 100 207,636 100 34,580 100 46,718 100 1,305,966 100
% 61 17 16 3 3 100
Note: % in italic is cross sector distribution; percentages may not add to 100 due to rounding
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an average of $500. ‘‘Other participants’’ are somewhere in between, with event
expenditures around $1,000. It is reasonable to expect that the different categories of
event visitors face different budget constraints, which may explain some of the differences in
expenditure behaviours among attendees from different categories (see Eugenio-Martin,
2003). Travel and accommodation costs for coaches are usually covered by sport governing
bodies. Therefore, coaches have more disposable income available to spend during the
event, with a high preference for retail and merchandised goods. Since non-local spectators
have to spend a substantial amount towards hospitality and food and beverage, they have
less money available to spend in other areas of the local economy. Athletes, on the other
Figure 1 Cross sector distribution at the aggregate level
Figure 2 Cross sector distribution of spectators versus the participant group (including
athletes, coaches, of?cials, other participants)
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hand, are focused on the competition, and have less time for shopping and socializing. That
fact, plus the fact that they tend to be younger than other participants, which may limit their
resources, limits their overall capacity to spend. Of?cials are a separate segment, and show
some af?nity for retail and merchandise, as well as restaurants, but they limit their overall
expenditure. They are de?nitely not the big spenders at this type of event. Lastly, the
spending of ‘‘other participants’’ falls between that of coaches and of?cials.
There are some interesting implications here. From the standpoint of nurturing spending, it
would seem that coaches are a particularly good target market, especially with reference to
retail spending. Pre-event market research should seek to identify the kinds of purchases
that coaches want to make, and this group should be particularly targeted. Promotions, such
as coupons or offers for discounted activity bundles, targeted speci?cally at coaches might
be particularly useful (see Chalip and Leyns, 2002; Chalip and McGuirty, 2004).
These ?ndings may also have some implications for event sponsorship. Businesses that
could bene?t from access to segments with highest potential yield and businesses that
could help to enable festival might be particularly appropriate sponsors. Since sponsors, the
host destination, and event organizers have a shared interest in fostering a sense of festival,
and given the potential thereby to enhance sponsors’ revenues during the event, there is a
potential here for enhancing an event’s mix of sponsors (see Chalip, 2006; Frew and
McGillivray, 2008; Jowdy and McDonald, 2002/2003).
The low spending by athletes is also important. Sport policymakers and sport critics have
long been concerned about the ?nancial stresses experienced by athletes, as athletes
sacri?ce income and often spend heavily to enable their training and competition (Connor,
2009). Financial stress has been identi?ed as a cause of poor nutrition (Heaney et al., 2008),
burnout (Cresswell and Eklund, 2004), and career termination (Lavallee et al., 1997) among
athletes. To the degree that spending at the event enables participation in the informal sense
of festival that events seeks to nurture (see Green and Chalip, 1998) and the long-term
bene?ts that events seek to bequeath (see Taks et al., 2009) then athletes at this level may be
among the least able to participate. This elevates the importance of organised festival
elements at events for athletes (e.g. celebrations, social mixers) and free or low-cost festival
opportunities enabled through spaces dedicated to informal celebration (see Frew and
McGillivray, 2008).
The regression analyses indicate that the hospitality and the private transportation operation
sectors are the primary bene?ciaries of spending by spectators. Local businesses in these
sectors should therefore speci?cally target the spectator segment in their marketing
strategies. The retail and merchandise sector as well as grocery stores are not impacted by
spectator spending. The most ef?cient strategy for these sectors will be to target event
participants, rather than spectators. From the spending pro?les it is clear that event
merchandise is extremely important for the participant group, especially for the coaches, but
also for the other participants, athletes, and of?cials. Identi?cation with the event through
merchandise seems an important feature for this group of people, more so than for non-local
spectators.
At the aggregate level it becomes clear that participants, although fewer in number, spent
proportionally more money in the local economy than did spectators. The non-local
spectators boost the hospitality, food and beverage and private transportation sectors of the
local economy, as expected. Since accommodation and meals are provided to the
‘‘participant group’’ it is not surprising that these sectors do not bene?t greatly from this
category of event attendees. However, all segments of the participant group spend large
portions of their budget on retail and merchandise items, as well other retail. Measuring the
incremental economic impact of medium sized sporting events is an important component
of the marketing activities of event organizers and hosting cities. Understanding economic
redistribution and individual expenditures by category can aid future event organizers in
shaping event attributes based on visitors spending (see Putsis, 1998), as illustrated above.
When dealing with straightforward spectator and/or participants events, visitor
segmentation in terms of participant or spectator may not be useful because one group is
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so dominant over the other – spectators at spectator events, and participants at participant
events. However, for mixed ‘‘spectator/competitor events’’ it is useful to differentiate
spectators and participants, because spending does differ as a function of visitor segment.
Although non-local spectators are larger in number, the participant group in this study spent
proportionally more in the local economy. At the aggregate level, however, the size of the
segments starts to play a role. Segmenting becomes relevant, therefore, only if the segments
are large enough to render a substantial economic impact (see Kotler, 1988; Wedel and
Kamakura, 1998).
Nevertheless, spend is not merely a matter of economic impact, as it is also relevant to the
festive sense of the event to the degree that spending can engender a sense of celebration
(Chalip, 2006). For that reason, it is particularly interesting to note how little was spent on
elements such as entertainment and recreation, or food and beverage purchases at
groceries (perhaps to support a party). Expenditures in these categories were among the
lowest for every segment, constituting barely 8 per cent of the total spend in aggregate. This
can be explained, at least in part, by the special events and ceremonies staged in the
context of the Pan American Junior Athletic Championship, which were free for spectators
and participants. Besides the formal opening, closing and victory ceremonies, which
created enjoyable experiences for the participants and the spectators, a Team Canada
parade and pep rally was organised two days prior to the event at Windsor’s downtown
waterfront. Local citizens, business owners, and fans lined up to honour the team members.
The opening night concluded with a musical celebration with Motown and Latin Rock tunes
for both participants and spectators. The Closing Ceremonies were less formal than the
Opening Ceremonies in that the athletes all marched together, not by country, displaying
‘‘camaraderie and friendship’’ (LOC, 2005, p. 21). Closing night was concluded by a
?reworks celebration after which participants, volunteers and spectators were invited to
attend a music festival in the University’s Field House to celebrate the success of the event.
In their study of a women’s football tournament, Green and Chalip (1998) argued that the
quality of the experience and participants’’ consequent satisfaction and desire to return
depended on the quality of entertainment, recreation, and socializing that participants
obtained. They criticised event organizers’’ myopic focus on sport, and inadequate attention
to festival. Although it appears that in the case of the Pan American Junior Athletic
Championships adequate attention was given to festival, it did seem to suppress spending
because the of?cially organised festivities were essentially free (or included in the admission
fee for spectators). Thus, while greater attention to the festivities associated with a sport
event may be important for improving the quality of experience that spectators and
participants obtain, festive activities that are built into the event may suppress visitor spend
– not only because the events are for free, but also because the time taken up by these
activities is time not devoted to other forms of celebration. Event attendees spent their time in
the venue attending the activities of the event. These activities might therefore be crowding
out potential revenue for local business (e.g. Mules and Dwyer, 2005; Preuss, 2005;
Kesenne, 2005), not allowing local businesses to bene?t from the event in the manner
recommended by Chalip and Leyns (2002).
There is a related issue here having to do with the differences between festival and spectacle
at an event (Chalip, 2006; MacAloon, 1984). Most opening and closing ceremonies aim to
produce spectacle, and are not really about festival, even if they are called ‘‘festival’’ by
event organizers. When event attendees remain in the role of audience, and performances
are staged for them, then they are not participants in festive celebrations; they are merely an
audience to whatever performances are provided. Much of what is staged is intended to be
spectacular, such as parades during the ceremonies and ?reworks at the end. Event
attendees are not invited to become active celebrants during these activities. Yet, it has
been shown elsewhere that the capacity to become active participants in a celebration can
play a pivotal role in participants’ enduring sense that the event was worthwhile and their
consequent spending (Ehrenreich, 2007; Green and Chalip, 1998; Veno and Veno, 1992). To
the degree that performances crowded out festival, the event’s overall economic value may
have been reduced. These ?ndings suggest the value of future work that examines ways to
foster festival at events (see Handelman, 1990).
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Limitations
This study has focused on spending patterns at the Pan American Junior Athletic
Championships, which were a unique event for the city of Windsor. It would be worthwhile to
compare these ?ndings with spending patterns of attendees of other events, in order to
explore variations in the ways that spending is segmented, and the ways that event
organizers do or do not nurture a sense of festival among attendees.
The survey relied on self-reported spending (recall in the case of spectators, estimates in the
case of participants). A different approach to collect spending data, such as a spending
journal, could provide more accurate spending patterns, but would limit the number of
attendees who could be surveyed. Although accurate population numbers were available for
the participants through the Local Organizing Committee (LOC, 2005), the population
numbers for the spectators had to be estimated in order to calculate the aggregate numbers.
It should be noted that small differences in these population estimates can have an impact on
aggregated numbers. Thus, some caution is warranted when estimations are used.
Concluding observation
Insight into event-related spending of different visitor segments allows speci?c economic
sectors to strengthen their marketing strategies by targeting the speci?c segments that
bene?t fromtheir products and services. It also suggests the need for greater attention to the
festival that sport events are intended to enable.
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About the authors
Dr Marijke Taks has expertise in socio-economic aspects of sport and leisure, with particular
interests in consumer behaviour of various sport-oriented groups. She researches impacts
of sport events from a variety of perspectives, including economic, tourism, and sport
participation. She teaches courses in sport marketing, socio-economic aspects of sport and
leisure and global issues in sport management. She is currently the editor of the European
Sport Management Quarterly.
Dr B. Christine Green, whose work focuses on sport development, has examined consumer
behaviour in sport, sport and event tourism, and development of sport organisations. She
teaches courses in sport marketing, organisational behaviour in sport, sport development,
and sport events. She is a Research Fellow of the North American Society for Sport
Management, and former editor of Sport Management Review.
Dr Laurence Chalip, whose work focuses on sport policy, has examined the formulation and
implementation of sport policies, sport marketing, and the leverage of sport events. He
teaches courses in sport marketing, sport policy, and sport economics. He is a Research
Fellow of the North American Society for Sport Management, founding editor of Sport
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Management Review, and former editor of the Journal of Sport Management. Dr Laurence
Chalip is the corresponding author and can be contacted at: [email protected]
Stefan Kesenne, whose main expertise is the economic theory of professional team sports,
teaches a class of Sports Economics at the Economics Department of the University of
Antwerp, at the Human Kinesiology Department of the Catholic Univerity of Leuven, and at
the Euromed Marseille School of Management. He is a member of the Editorial Board of the
Journal of Sports Economics and of the European Sport Management Quarterly.
Dr Scott Martyn, whose research expertise is in the area of the historical evolution of the
Olympic Games and af?liated insignia as sport marketing properties, has served on the
executive council of the International Centre for Olympic Studies, and continues to serve on
executive councils of the North American Society for Sport History, and the International
Society for Comparative Physical Education and Sport. He is also the chief editor of
International Sports Studies, and the managing editor of Olympika: The International Journal
of Olympic Studies.
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doc_974668104.pdf
The purpose of this paper is to examine the spending patterns of non-local participants and
spectators at a medium-sized international sport event, to segment their spending patterns and
consider implications for the quality of each segment’s event experience
International Journal of Culture, Tourism and Hospitality Research
Visitor composition and event-related spending
Marijke Taks B. Christine Green Laurence Chalip Stefan Kesenne Scott Martyn
Article information:
To cite this document:
Marijke Taks B. Christine Green Laurence Chalip Stefan Kesenne Scott Martyn, (2013),"Visitor composition and event-related spending",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 7 Iss 2 pp. 132 - 147
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Visitor composition and event-related
spending
Marijke Taks, B. Christine Green, Laurence Chalip, Stefan Kesenne and Scott Martyn
Abstract
Purpose – The purpose of this paper is to examine the spending patterns of non-local participants and
spectators at a medium-sized international sport event, to segment their spending patterns and
consider implications for the quality of each segment’s event experience.
Design/methodology/approach – Spending in nine sectors of the economy is measured via
self-report, and respondents are segmented into ?ve groups: spectators, athletes, coaches, of?cials,
and other participants (e.g. media, medical staff). The daily and aggregate spend for each segment in
each economic sector is calculated and compared. Regression analysis tests differences among
segments for each economic sector.
Findings – Participants account for 39 per cent of aggregate spend; coaches are the biggest
spenders; athletes spend relatively little. The segments spend differently on hospitality, private
transportation, grocery, and retail, with spectators spending signi?cantly more than the participant
groups on hospitality and private transportation, and signi?cantly less on groceries and merchandise.
Spending in sectors normally associated with celebration and festivity accounts for only 8 per cent of
total spend.
Research limitations/implications – Findings are derived from a single event, but are consistent with
other work, suggesting that inadequate attention is given to opportunities for festive celebration,
especially among athletes.
Practical implications – Coaches are a particularly useful target market for retailers, whereas hoteliers
and service stations should target their marketing at spectators. Event organizers should do more to
build festivals.
Originality/value – This paper identi?es the ways that different segments organize their spending at an
event, and demonstrates that greater attention to festivals could enhance a sport event’s overall impact.
Keywords Sporting events, Economic sectors, Hospitality, Festivals, Visitor spending,
Event segmentation, Economic impact, Leisure activities
Paper type Research paper
Introduction
Events have become a vital part of community economic development and planning (Chalip,
2004) – so much so that communities often develop an entire portfolio of events in order
optimize the overall economic value obtained (Ziakas, 2010). Yet, when the expenditures of
event visitors are analysed, it is sometimes noted that the economic bene?ts do not reach the
levels that are expected or desired (Crompton and Lee, 2000) or that the distribution of
bene?ts is so poor that some sectors of the economy do well, while others may actually be
worse off (Putsis, 1998). Indeed, it has been shown that event visitors may spend very little
beyond the event itself, particularly in the case of small or medium-sized events (Nogawa
et al., 1996), although the amount that visitors spend for things other than event fees,
accommodation, and food varies substantially across events (Daniels and Norman, 2003).
When events are compared, it appears that the key to optimizing spend is to create
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VOL. 7 NO. 2 2013, pp. 132-147, Q Emerald Group Publishing Limited, ISSN 1750-6182 DOI 10.1108/IJCTHR-04-2013-0020
Marijke Taks is based in the
Department of Kinesiology,
University of Windsor,
Windsor, Canada.
B. Christine Green and
Laurence Chalip are based
in the Department of
Kinesiology and Health
Education, University of
Texas at Austin, Austin,
Texas, USA. StefanKesenne
is based in the Department
of Economics, University of
Antwerp, Antwerp,
Belgium; and Human
Kinesiology Department,
Catholic University of
Leuven, Leuven, Belgium;
and Euromed Marseille
School of Management,
Marseille, France.
Scott Martyn is based in the
Department of Kinesiology,
University of Windsor,
Windsor, Canada.
The authors gratefully
acknowledge the research
grant received from the Social
Sciences and Humanities
Research Council of Canada for
this project (no. 140370).
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conditions that encourage spending (Wilson, 2006). This is one reason that event strategists
encourage sport event organizers to foster festival; it creates a sense of celebration (see
Handelman, 1990) that can stimulate visitor spending (Chalip and Leyns, 2002; Green and
Chalip, 1998).
To date, studies of spending by event attendees have focused on their aggregate spend
across economic sectors. Previous work has typically chosen not to segment the spend by
visitor category. From a practical marketing standpoint, it would be particularly useful to
understand how event visitor segments differ in their spending patterns, as that could
enable more targeted marketing. From a conceptual standpoint, understanding the ways
that different groups choose to spend can enable a better grasp of the ways that event
visitors construct their event experience. In particular, it is of interest to consider the relative
degree to which spending is strictly in support of event attendance, and the degree to which
spending may also support festive celebrations. This study examines those matters.
Literature review
Although sport events are typically described in terms of the competition and entertainment
they provide, one of the core attractions of sport events is that they enable an array of festive
occurrences, some of which are designed and some of which are spontaneous.
Consequently, a number of sport events now incorporate festivals as add-ons to the
competition speci?cally to attract spectators or participants (Burdsey, 2008; Jowdy and
McDonald, 2002/2003), while others provide festival spaces to enable spontaneous
production of festival during events (Frew and McGillivray, 2008). While there is certainly
some advantage to festival that is incorporated into event design, the spontaneous
emergence of festive behaviour provides a particularly positive hedonic experience (Green
and Chalip, 1998).
The experience of a sport event encompasses much more than the sport activity or
entertainment. The event is part of the overall tourism experience. Indeed, it becomes more
attractive to the degree that attendees can incorporate an array of tourism experiences
during the event (Chalip and McGuirty, 2004), particularly because those can help to impart
a sense of festivity (Chalip, 1992, 2006). This is important not merely because it represents
an added attraction to the event, but also because it can stimulate spending during an
event, which therefore enhances the event’s overall economic impact (Chalip, 2004; Wilson,
2006). Thus, strategic leverage designed to amplify an event’s economic impact requires
attention to the creation of festival, while the creation of festival must be informed by an
understanding of event attendees’ preferred patterns of consumption.
There has been increasing interest in determining the spending patterns of different tourists
in order to enable better prediction of tourist demand and enhanced targeting of marketing
communications (Laesser and Crouch, 2006), and to enhance the overall quality of the
consumption experience (Bailey et al., 2009). This is particularly important for events, as
event attendees differ from other tourists not merely in terms of their particular interest in
sport, but also in their patterns of consumption (Boo et al., 2009). They are comparatively
less interested in traditional tourismactivities and souvenirs, and more interested in activities
and products that can complement their overall event experience. Consequently, there is
clear value in identifying the ways that spending varies among different segments of event
visitors (Preuss et al., 2007).
The challenge, of course, is to segment attendees in a manner that is meaningful both
conceptually and practically. The sport tourism literature argues that many different types of
event attendees can be distinguished. Robinson and Gammon (2004), for instance,
distinguish ‘‘sport tourist’’ (i.e. primary visitors) and ‘‘tourism sport’’ (i.e. casual visitors),
based on the consumer’s motivation. Other authors differentiate between ‘‘active’’ and
‘‘passive’’ sport tourists, based on the consumer’s behaviour (e.g. Gibson, 1998; Ritchie
et al., 2002; Standeven and De Knop, 1999). Economic impact studies make a distinction
between ‘‘local’’ and ‘‘non-local’’ visitors (Dwyer et al., 2000; Hodur and Leistritz, 2006).
Preuss (2005) suggests 11 different types of event-affected persons: residents, home
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stayers, runaways, changers, casuals, time switchers, avoiders/cancellers, avoiders/ pre-,
post switchers, extensioners, and event visitors. He argues that some of these types of event
attendees bring new money from outside into the host region, potentially creating a positive
economic impact, while other types of affected persons create a crowding out effect, leaking
money out of the local economy and thus inducing a negative economic effect.
As compelling as the various kinds of segments might seem, it is often impractical to identify
and classify attendees in advance of the event, when their expected spending differences
would be useful for planning. Contemporary methods for collecting spending data also make
it impractical to segment the event market into a large array of conceptual categories.
However, event attendees do take on different roles at events (e.g. spectators, athletes,
coaches, of?cials), and those roles are suf?ciently visible that it is relatively straightforward to
differentiate those groups prior to the event. Further, their roles are often associated with other
factors known to affect spending, such as patterns of interest, age, and income (see Fennell
et al., 2003; Lehto et al., 2002). Consequently, it is of some interest to explore the degree to
which spending can be usefully segmented as a function of the attendee’s role in the event.
The purpose of the study is to analyse event visitor role and event-related spending in order
to determine which sectors in the local economy bene?t most from which visitor role, and to
derive implications for fostering future event and tourism spending. The study examines
these matters via an analysis of The 2005 Pan American Junior Athletic Championships. As a
one-time international sport event, for which a new stadium was built, this event created very
high expectations for the hosting community. The event was considered to provide unique
opportunities to boost tourism, positively impacting local business and thus the local
economy. In addition, as a prime example of a ‘‘spectator/competitor event’’ (Gratton and
Taylor, 2000) this type of event provided the range of visitor segments required for this study.
Other annual tournaments hosted in this region, such as hockey tournaments, represent
‘‘participant events’’ (Gratton and Taylor, 2000). Spectators of the latter types of events are
limited in number and are mainly accompanying persons. Overall, these annual events draw
fewer non-event related spectators than international events like the Pan American Junior
Athletic Championships. The 2005 Pan American Junior Athletic Championships were
therefore an appropriate context for this study.
The Pan American Junior Athletic Championships
The Pan American Junior Athletic Championships are organised bi-annually in various Pan
American countries under the auspices of the International Association of Athletics
Federations (IAAF) and the Pan-American Athletics Commission (PAC). The 2005 event was
hosted in Windsor, from28-31 July, by the University of Windsor (Ontario), in partnership with
the local Track and Field Club, the community, and corporate and regional partners. A total
of 35 countries were represented at the Championships. Since it was a ‘‘junior’’
championship, the athletes were under 19 years of age. Consequently, the athletes
travelled with their team and were accompanied by coaches and team of?cials. In some
cases, family members and/or friends also accompanied the athletes on their journey. Event
organizers sought to foster a festive atmosphere, and visitors were encouraged by event
organizers to experience the city of Windsor, including its shops, parks, restaurants, and
entertainments.
Gratton and Taylor (2000) de?ne this type of event as a ‘‘type C’’ sporting event (i.e. an
irregular, one-off major international spectator/competitor event). Accurate numbers for the
different types of event attendees were available from the Local Organizing Committee
(LOC, 2005), from which population estimates could be calculated. Since economic impact
should only be measured from the ?ow of foreign money into the city, region, or country, and
the additional income created (Crompton, 1995; Putsis, 1998), only expenditures of
non-local visitors, whose primary purpose was to attend the event, were taken into account
(assuming locals did not behave differently because of the event). ‘‘Non-locals’’ are de?ned
as visitors living outside the county region under investigation. In this particular type of event,
the majority of the participants are non-locals, while only a small portion of the spectators are
non-local.
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Method
Questionnaire
Data on visitor spending were collected from responses to written questionnaires
administered during the event. Two slightly different questionnaires were developed for
the spectators and the participants. The complete questionnaire for the spectators
consisted of four major parts, including a section on: the respondent’s role in the event and
daily expenditures; tourism behaviour; motives and identity of event attendees; and
demographic data. The ?rst three sections were also incorporated in the participants’
questionnaire. The latter did not include a separate section on demographics, but enquired
about age and gender at the beginning of the questionnaire. This paper uses the data on
visitor spending that were collected in section 1. The section on visitor spending differed
slightly between spectators and participants. The survey instrument queried spectators
about: their role in the event (related to any of the event participants or not), place of
residence (to distinguish between locals and non-locals), purpose of the visit (primary,
casual), daily spending of their party during the visit (tickets and admission fees,
transportation, food, lodging, shopping, entertainment, other), length of stay (number of
nights), the number of people in the party, type and location of accommodation. The
question about daily expenditures for spectators enquired about their actual spending and
was as follows: ‘‘Thinking about all the things that you did yesterday, approximately how
much did you and your immediate travel party spend (regardless of who was paying the bill)
in the Windsor-Essex County area for each of the following categories. If you arrived today,
please answer in terms of today’s expenditures.’’
The participant survey queried: their role (athlete, coach, administrator, of?cial,
journalist/media, other), their involvement in athletics (number of years and speciality),
place of residence (to distinguish between locals and non-locals), the number of
accompanying people (relatives or friends), and personal daily spending during the visit
(expenditure categories similar to those of the spectators except for tickets and admission
fees), and length of stay (number of nights). The question about daily expenditures for
participants was based on their estimation, and was phrased as follows: ‘‘How much money
will you personally spend on a daily basis during your visit in the Windsor/Essex County area
for each of the following categories’’. The questionnaires were available in English and
Spanish, because of the Pan American context.
Data collection
The data collection was different for spectators and participants. Spectator data were
collected during the opening ceremony and during all sessions of the three day event.
Members of the research team randomly approached as many event attendees as possible
and invited them to participate in the study as they entered the front gate, and as they
watched fromthe stands. Members of the research team were stationed at different areas of
the facility. If the spectators agreed to participate, they received a pencil and an envelope
containing the survey and a letter of information and consent explaining the study and
describing respondents’ ethical rights concerning their participation. The survey took
approximately ten minutes to complete. Respondents were instructed to place the
completed survey in the envelope provided and return it to the research booth (located
nearby) in exchange for a token of appreciation (a frisbee bearing the event logo). All
participants (athletes, coaches, and of?cials) received the questionnaire in their welcome
package. They were asked to return their completed questionnaire to the research booth any
time during the event. As an incentive to partake in the study, the participants were invited to
participate in a draw for a prize.
Sample
A total, of 2,067 questionnaires were handed out to the spectators, of which 1,290 were
returned (response rate ¼ 62:41 per cent); of the 740 questionnaires handed out to the
participants, 256 were returned (response rate 34.59 per cent). Thus, of the total of 2,829
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questionnaires that were distributed, 1,546 were returned (response rate ¼ 54:64 per cent),
of which 1,379 were usable.
For the purpose of this study, only the expenditures of non-local event attendees (n ¼ 428
responses) are considered, as these generate new spending for the local economy. The
following ?ve visitor segments are distinguished:
1. spectators (n ¼ 217);
2. athletes (n ¼ 123);
3. coaches (n ¼ 32);
4. of?cials (n ¼ 38); and
5. ‘‘other’’ participants (such as media, therapists, medical staff, other administrative roles;
n ¼ 18).
In the spectator group, only spectators whose primary purpose was to attend the event were
included, as the objective was to determine spending stimulated by the event, rather than
coincident with it. Note that athletes, coaches, of?cial and ‘‘other participants’’ all completed
the participant survey, and are therefore segments within the participant group.
Population numbers with regard to the spectators were estimated as follows: the numbers of
spectators at opening night was approximately 4,000, and another 4,000/day for the
subsequent three event days, totalling 16,000 spectators. However, this number includes
double counting. The average attendance of the spectators was 1.7948 (SD ¼ 0:86) days.
The number of ‘‘unique’’ spectators is thus estimated to be 8,915. According to our survey,
19 per cent of the spectators were non-local visitors whose primary purpose was to attend
the event, compared to 76 per cent locals, and 5 per cent non-local casual spectators. The
total number of non-local primary spectators is therefore estimated to be 1,694.
Exact numbers of non-local participants were available from the Local Organizing
Committee (LOC, 2005) for the athletes (n ¼ 442), coaches (n ¼ 143) and of?cials (n ¼ 65).
The number of ‘‘other participants’’ (n ¼ 47) was estimated based on survey results (of the
’’other participants’’, 82 per cent were non-local). The share of each participant category in
the response group aligns with the actual attendance numbers; coaches are slightly
underrepresented in the response group while of?cials are slightly overrepresented.
Data analysis
Cross-sector distribution is estimated by calculating the amount of money spent in nine
different economic sectors by each visitor segment during the time of the event:
1. private transportation rental;
2. private transportation operation (parking, gas, repairs);
3. local transportation (bus, taxi, limo);
4. hospitality (hotels, lodging);
5. food and beverage at grocery stores;
6. food and beverage at restaurants, bars and concessions;
7. entertainment and recreation;
8. retail and merchandise (clothing, gifts, souvenirs, merchandise); and
9. other retail.
Event expenditures were calculated by multiplying the daily expenditures in each sector of
the local economy by the number of days. ‘‘Number of days’’ was a newly created variable
based on the ‘‘number of nights’’, an original variable in the survey; if the number of nights
was 0, then the number of days was 1; else the number of days equalled the number of
nights þ0.5. This assumption was based on the fact that people who spent, for example 2
nights, normally arrived half a day early, or stayed another half a day before leaving. The
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average number of days for the non-local spectators was 3 (SD ¼ 2:1), for the athletes 6.15
(SD ¼ 1:2), for the coaches 6.19 (SD ¼ 1:30), the of?cials 5.08 (SD ¼ 1:4) and the other
participants 6.44 (SD ¼ 1:11; see also Table I).
Daily expenditures more than two standard deviations from the mean were considered to be
outliers. Outliers were replaced with the next highest daily expenditure level within each
visitor segment. In addition, spectators’ daily expenditures were initially asked based on the
number of people in the party; therefore, daily expenditures of spectators were ?rst divided
by the number of people in the party, and subsequently multiplied by the number of days, in
order to calculate an average event expenditure per person per visitor segment. All dollar
amounts are reported in Canadian dollars.
Descriptive statistics illustrate the characteristics of each visitor segment (spectator,
athletes, coaches, of?cials, other participants). In order to predict which visitor segment best
predicts event expenditure in a speci?c sector in the local economy, a linear regression was
executed with visitor segments (dummy variables), age and gender as independent
variables. The dependant variables, event expenditures in each sector, were log
transformed to normalize the distribution. This is a standard procedure when modelling
economic data, and is typically essential in order to enable the estimation of linear
relationships among variables when performing regression analyses (Wang, 2009, pp. 22-3).
The regression model was:
Log event expenditure by eector ¼ f{age, gender, visitor type[dummy variables,
1 type as reference category]}.
Finally, the overall impact of the visitor segments on each sector of the local economy was
calculated at the aggregate level by multiplying sector event expenditures per visitor
segment by the population numbers in each segment. The overall contribution in each
economic sector is calculated, and then analysed for each visitor segment.
Event expenditures by visitor segment
Table I describes the characteristics of each visitor segment. Coaches and of?cials are
predominantly male (66 per cent and 58 per cent respectively); while spectators, athletes
and ‘‘other participants’’ are predominantly female (53 per cent, 55 per cent, and 61 per cent
respectively). The athletes stand out with regard to their age (M ¼ 18). All other visitor
segments are middle aged, with averages from 41 for ‘‘other participants’’ to 45 for the
spectators.
Inspection of Table I shows that coaches are the big spenders with an average total event
expenditure of $1,452, followed by ‘‘other participants’’ (M ¼ $994). The three other
Table I Descriptive statistics: sex, age, length of stay, and average event expenditure by visitor segment
Spectators Athletes Coaches Of?cials Other part.
n SD n SD n SD n SD n SD
n-response 217 123 32 38 18
Women (%) 53 55 34 42 61
Age (yrs) 45 16 18 1.4 42 9 53 13 41 11
n-days 3 2.1 6.15 1.2 6.19 1.3 5.08 1.4 6.44 1.1
Average Expenditure ($ CND)
Priv. transp. rental 34 117 8 49 20 98 8 46 150 635
Priv. transp. operation 33 85 7 42 9 49 28 74 11 48
Local transportation 5 32 8 32 45 144 3 18 23 80
Hospitality 174 400 55 282 195 767 31 136 101 300
Food and beverage at grocer 13 39 26 57 72 163 25 54 45 65
Food and beverage at restaurants 112 210 64 131 278 476 164 215 176 273
Entertainment and recreation 19 95 25 78 48 145 55 136 76 160
Retail and merchandise 76 177 275 353 727 735 207 233 402 514
Other retail 5 36 23 124 58 228 11 37 10 29
Total per person spend 472 841 492 675 1,452 1,971 532 400 994 1,299
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segments (spectators, athletes and of?cials) each spent around $500 per event. The
coaches’ expenditures stand out in four sectors of the local economy: retail and
merchandising ($727), food and beverage at restaurants and concessions ($278), food and
beverage at grocery stores ($72) and local transportation ($45). Their expenditure for
hospitality is also substantial ($195). As is the case for coaches, ‘‘other participants’’ spent
the largest portion of their event expenditures on retail and merchandise ($402), followed by
food and beverages at restaurants ($176). This segment stands out with regard to private
transportation, speci?cally car rental ($150), compared to other visitor segments. This group
also shows the highest expenditure in the entertainment sector ($76).
Interestingly, retail and merchandise consumes a substantial portion of the event expenditures
of all segments for the participant group, but is much less important in the budget of
spectators. The non-local spectators spent most of their money on hospitality, which is
normally hotels ($174)) and food and beverage at restaurant and concession stands ($112).
Predictors of event expenditures in speci?c economic sectors
Event expenditures were log normalized and predicted based on visitor segments, age and
gender. Visitor segments were transformed into dummy variables. The correlation matrix for
variables in the model is presented in Table II. (Correlations between visitor segments are
irrelevant and are therefore not represented in the table.) The correlation between athlete role
and age accounts for almost 50 per cent of the variance. This is not surprising, since the event
is a junior event, and all athletes are younger than 19 years of age. Inspection of Table II also
shows that spectators are signi?cantly older than those in other roles, as are the of?cials. There
does not seem to be any signi?cant relationship between gender and spectator segment.
Results of the regression analyses are presented in Table III. Only the four categories of
spend for which signi?cant prediction was obtained are shown. The segment ‘‘other
participants’’ is left out of the model as it serves as reference group for the other four visitor
segments. Four models were signi?cant: hospitality, food and beverage at restaurants,
private transportation operation and retail and merchandise (R
2
varying from 0.03 to 0.24).
Inspection of Table III shows that spectators contribute signi?cantly to the hospitality sector
through spending on hotel accommodation. Spectators also positively impact the local
Table II Correlation matrix of variables in the regression model
Sex Spectators Athletes Coaches Of?cials Other participants
Age 0.11 0.42 20.70 0.08 0.28 0.04
Sex 20.03 20.05 0.10 0.06 20.04
Table III Predictors of sector spending: results of the regression analyses
Hospitality
Food and beverage at
grocery stores Private transport operation Retail and merchandise
Predictors B SE b B SE b B SE b B SE b
Constant 0.09 0.67 2.3 0.53 20.27 0.44 4.40 0.6
Age 0.02 0.01 0.11 20.01 0.01 20.06 0.01 0.01 .14* 0.01 0.01 0.10
Gender 0.10 0.23 0.02 20.14 0.18 20.04 20.06 0.15 20.02 20.32 0.22 20.06
Spectators 1.50 0.57 0.30** 21.09 0.45 20.29* 1.62 0.38 0.46*** 22.63 0.56 20.51***
Athletes 0.02 0.62 0.00 20.88 0.49 20.21 0.21 0.41 0.05 20.28 0.61 20.05
Coaches 20.30 0.69 20.03 20.39 0.55 20.06 20.12 0.46 20.02 0.93 0.67 0.10
Of?cials 20.41 0.67 20.05 20.63 0.54 20.10 0.59 0.45 0.10 20.95 0.66 20.11
R
2
0.14 0.03 0.24 0.22
F(6, 421) 11.631 2.062 22.38 20.136
p *** ,0.057 *** ***
Note: *p , 0:05; **p , 0:01; ***p , 0:001
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transportation operation sector through expenditures related to gas and parking fees.
Spectators contribute substantially less to the food and beverage retail sector (grocery) and
the retail and merchandise sector than do other segments. Age only appears to be a
signi?cant predictor for private transportation operation (i.e. older people spent more money
on gas and parking). Remaining models predicting food and beverage at restaurants and
concessions, private transportation rentals, local transportation, entertainment and
recreation, and other retail failed to yield signi?cant prediction.
The dummy variables for sector are estimated with reference to the ‘‘other participant’’
category. In order to compare sectors, it is useful to note whether the parameter estimate for
each is more than two standard errors fromany other (in other words, whether the difference
between the two standard errors is non-zero at the 95 per cent con?dence level). In one
case, the prediction of retail and merchandise expenditures, the parameter for coaches is
more than two standard errors from every other estimate. Thus, although the parameter
estimate for coaches does not differ signi?cantly from the baseline set by ‘‘other
participants’’, it is signi?cantly different from that of all other segments. Further, the
parameter is positive while others are negative. Thus, coaches spent signi?cantly more on
retail and merchandise than did spectators, athletes, or of?cials.
Cross-sector distribution by visitor segment at the aggregate level
The analyses reported above show different expenditure patterns according to visitor
segments. The aggregate impact of each sector on the local economy is, of course,
dependent on the size of these segments. Aggregated expenditures in the different sectors
of the local economy are calculated using the average event expenditure £ population
estimates for each visitor segment. The numbers are presented in Table IV, and graphically
illustrated in Figures 1 and 2.
Inspection of Table IV shows that spectators made up 71 per cent of the non-local visitors,
and spent approximately $800,000 (61 per cent) of the total newmoney coming into the local
community. The participant group (i.e. athletes, coaches, of?cials, and ‘‘others’’) made up
29 per cent of the non-local visitors and contributed approximately $500,000 (39 per cent) of
the new money coming into the local community.
Almost one-third of all non-local visitor spending goes to retail and merchandise (30 per
cent), followed by hospitality (27 per cent) and food and beverage at restaurants (21 per
cent). The large share of retail and merchandise is linked to the spending patterns of the
participant segments, while the shares in the hospitality and restaurant sectors are due to
spectator spending. Thus, although smaller in numbers, the participant segments spent a
substantial amount of money in the retail and merchandise sector. For athletes and coaches
this is about 50 per cent, and for of?cials and ‘‘other participants’’ about 40 per cent of their
total spending. This is in contrast to the spectators who spent only 16 per cent of their total
event expenditure on retail and merchandise.
At the aggregate level, the impact of the of?cials and ‘‘other participants’’ is minimal, due to
their low numbers. Aggregate spending of athletes and coaches is fairly equitable in sectors
such as retail and merchandise, hospitality, and food and beverage at restaurants.
Therefore, Figure 2 compares the ?nal expenditure of non-local spectators versus the
participant group (including all participant segments: athletes, coaches, of?cials, and other
participants). Non-local spectators contribute substantially more to four of the nine
economic sectors (i.e. hospitality, food and beverage at restaurants, private transportation
rental and operation). Participants, although lower in numbers, contribute substantially more
to the retail and merchandise sector and ‘‘other retail’’.
Discussion
Results are consistent with Gratton and Taylor’s (2000) typology of sport events. In their
typology, this event would be classi?ed as a ‘‘spectator/competitor’’ event. It generates a fair
bit of new spending into the local economy (estimated here at over $1.3 million) while using
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predominantly volunteer labour. In addition, a new facility was built to host the event,
increasing the overall economic impact on the local economy to about $ 11,000,000 in direct
spending (Taks et al., 2008). While these ?nal expenditures are often used as a basis to
calculate a net increase in economic activity in the local economy through input-output
modelling, the relevance of these types of economic impact analyses is being questioned
since it omits the cost of hosting the event. Therefore, several authors argue that cost-bene?t
analysis is a more appropriate way to re?ect on the net effects of events (e.g. Dwyer et al.,
2006a, b; Kesenne, 2005; Mules and Dwyer, 2005; Porter and Fletcher, 2008). Previous
calculations for the 2005 Pan American Junior Athletic Championships support this claim.
Input-output analysis revealed that the ?nal expenditures of $ 11,000,000 generated a net
increase in economic activity in the city of Windsor of $ 5,617,681 (Taks et al., 2008), while
the cost-bene?t analysis disclosed a net de?cit of $ 451,676 (Taks et al., 2010). Further,
participants account for well over a third of the total new expenditures. This is quite different
from mega sporting events, where most of the impact is generated from spectators. The
utility of segmenting the spending is illustrated by the fact that the different segments of
non-local event attendees show different expenditure pro?les during the event.
Coaches were the big spenders during this event, with an average spend of about $1500.
This is three times the amount spent by athletes, of?cials or non-local spectators, who spent
Table IV Non-local visitor spending at the aggregate level in the different sectors of the local economy by visitor segment
Spectators Athletes Coaches Of?cials Other part. Total
n-population 1,694 442 143 65 47 2,391
% 71 18 6 3 2 100
$ % $ % $ % $ % $ % $ %
Retail and merchandise
$ 128,744 16 121,550 56 103,961 50 13,455 39 18,894 40 386,604 30
% 33 31 27 3 5 100
Hospitality
$ 294,756 37 24,310 11 27,885 13 2,015 6 4,747 10 353,713 27
% 83 7 8 1 1 100
Food and beverage at rest.
$ 189,728 24 28,288 13 39,754 19 10,660 31 8,272 18 276,702 21
% 69 10 14 4 3 100
Priv. transp. rental
$ 57,596 7 3,536 2 2,860 1 520 2 7,050 15 71,562 5
% 80 5 4 1 10 100
Priv. transp. operation
$ 55,902 7 3,094 1 1,287 1 1,820 5 517 1 62,620 5
% 89 5 2 3 1 100
Food and beverage at groc.
$ 22,022 3 11,492 5 10,296 5 1,625 5 2,115 5 47,550 4
% 46 24 22 3 4 100
Entertainment and recr.
$ 32,186 4 11,050 5 6,864 3 3,575 10 3,572 8 57,247 4
% 56 19 12 6 6 100
Other retail
$ 8,470 1 10,166 5 8,294 4 715 2 470 1 28,115 2
% 30 36 30 2 2 100
Local transportation
$ 8470 1 3,536 2 6,435 3 195 1 1,081 2 19,717 2
% 43 18 33 1 5 100
Total event spending
$ 799,568 100 217,464 100 207,636 100 34,580 100 46,718 100 1,305,966 100
% 61 17 16 3 3 100
Note: % in italic is cross sector distribution; percentages may not add to 100 due to rounding
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an average of $500. ‘‘Other participants’’ are somewhere in between, with event
expenditures around $1,000. It is reasonable to expect that the different categories of
event visitors face different budget constraints, which may explain some of the differences in
expenditure behaviours among attendees from different categories (see Eugenio-Martin,
2003). Travel and accommodation costs for coaches are usually covered by sport governing
bodies. Therefore, coaches have more disposable income available to spend during the
event, with a high preference for retail and merchandised goods. Since non-local spectators
have to spend a substantial amount towards hospitality and food and beverage, they have
less money available to spend in other areas of the local economy. Athletes, on the other
Figure 1 Cross sector distribution at the aggregate level
Figure 2 Cross sector distribution of spectators versus the participant group (including
athletes, coaches, of?cials, other participants)
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hand, are focused on the competition, and have less time for shopping and socializing. That
fact, plus the fact that they tend to be younger than other participants, which may limit their
resources, limits their overall capacity to spend. Of?cials are a separate segment, and show
some af?nity for retail and merchandise, as well as restaurants, but they limit their overall
expenditure. They are de?nitely not the big spenders at this type of event. Lastly, the
spending of ‘‘other participants’’ falls between that of coaches and of?cials.
There are some interesting implications here. From the standpoint of nurturing spending, it
would seem that coaches are a particularly good target market, especially with reference to
retail spending. Pre-event market research should seek to identify the kinds of purchases
that coaches want to make, and this group should be particularly targeted. Promotions, such
as coupons or offers for discounted activity bundles, targeted speci?cally at coaches might
be particularly useful (see Chalip and Leyns, 2002; Chalip and McGuirty, 2004).
These ?ndings may also have some implications for event sponsorship. Businesses that
could bene?t from access to segments with highest potential yield and businesses that
could help to enable festival might be particularly appropriate sponsors. Since sponsors, the
host destination, and event organizers have a shared interest in fostering a sense of festival,
and given the potential thereby to enhance sponsors’ revenues during the event, there is a
potential here for enhancing an event’s mix of sponsors (see Chalip, 2006; Frew and
McGillivray, 2008; Jowdy and McDonald, 2002/2003).
The low spending by athletes is also important. Sport policymakers and sport critics have
long been concerned about the ?nancial stresses experienced by athletes, as athletes
sacri?ce income and often spend heavily to enable their training and competition (Connor,
2009). Financial stress has been identi?ed as a cause of poor nutrition (Heaney et al., 2008),
burnout (Cresswell and Eklund, 2004), and career termination (Lavallee et al., 1997) among
athletes. To the degree that spending at the event enables participation in the informal sense
of festival that events seeks to nurture (see Green and Chalip, 1998) and the long-term
bene?ts that events seek to bequeath (see Taks et al., 2009) then athletes at this level may be
among the least able to participate. This elevates the importance of organised festival
elements at events for athletes (e.g. celebrations, social mixers) and free or low-cost festival
opportunities enabled through spaces dedicated to informal celebration (see Frew and
McGillivray, 2008).
The regression analyses indicate that the hospitality and the private transportation operation
sectors are the primary bene?ciaries of spending by spectators. Local businesses in these
sectors should therefore speci?cally target the spectator segment in their marketing
strategies. The retail and merchandise sector as well as grocery stores are not impacted by
spectator spending. The most ef?cient strategy for these sectors will be to target event
participants, rather than spectators. From the spending pro?les it is clear that event
merchandise is extremely important for the participant group, especially for the coaches, but
also for the other participants, athletes, and of?cials. Identi?cation with the event through
merchandise seems an important feature for this group of people, more so than for non-local
spectators.
At the aggregate level it becomes clear that participants, although fewer in number, spent
proportionally more money in the local economy than did spectators. The non-local
spectators boost the hospitality, food and beverage and private transportation sectors of the
local economy, as expected. Since accommodation and meals are provided to the
‘‘participant group’’ it is not surprising that these sectors do not bene?t greatly from this
category of event attendees. However, all segments of the participant group spend large
portions of their budget on retail and merchandise items, as well other retail. Measuring the
incremental economic impact of medium sized sporting events is an important component
of the marketing activities of event organizers and hosting cities. Understanding economic
redistribution and individual expenditures by category can aid future event organizers in
shaping event attributes based on visitors spending (see Putsis, 1998), as illustrated above.
When dealing with straightforward spectator and/or participants events, visitor
segmentation in terms of participant or spectator may not be useful because one group is
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so dominant over the other – spectators at spectator events, and participants at participant
events. However, for mixed ‘‘spectator/competitor events’’ it is useful to differentiate
spectators and participants, because spending does differ as a function of visitor segment.
Although non-local spectators are larger in number, the participant group in this study spent
proportionally more in the local economy. At the aggregate level, however, the size of the
segments starts to play a role. Segmenting becomes relevant, therefore, only if the segments
are large enough to render a substantial economic impact (see Kotler, 1988; Wedel and
Kamakura, 1998).
Nevertheless, spend is not merely a matter of economic impact, as it is also relevant to the
festive sense of the event to the degree that spending can engender a sense of celebration
(Chalip, 2006). For that reason, it is particularly interesting to note how little was spent on
elements such as entertainment and recreation, or food and beverage purchases at
groceries (perhaps to support a party). Expenditures in these categories were among the
lowest for every segment, constituting barely 8 per cent of the total spend in aggregate. This
can be explained, at least in part, by the special events and ceremonies staged in the
context of the Pan American Junior Athletic Championship, which were free for spectators
and participants. Besides the formal opening, closing and victory ceremonies, which
created enjoyable experiences for the participants and the spectators, a Team Canada
parade and pep rally was organised two days prior to the event at Windsor’s downtown
waterfront. Local citizens, business owners, and fans lined up to honour the team members.
The opening night concluded with a musical celebration with Motown and Latin Rock tunes
for both participants and spectators. The Closing Ceremonies were less formal than the
Opening Ceremonies in that the athletes all marched together, not by country, displaying
‘‘camaraderie and friendship’’ (LOC, 2005, p. 21). Closing night was concluded by a
?reworks celebration after which participants, volunteers and spectators were invited to
attend a music festival in the University’s Field House to celebrate the success of the event.
In their study of a women’s football tournament, Green and Chalip (1998) argued that the
quality of the experience and participants’’ consequent satisfaction and desire to return
depended on the quality of entertainment, recreation, and socializing that participants
obtained. They criticised event organizers’’ myopic focus on sport, and inadequate attention
to festival. Although it appears that in the case of the Pan American Junior Athletic
Championships adequate attention was given to festival, it did seem to suppress spending
because the of?cially organised festivities were essentially free (or included in the admission
fee for spectators). Thus, while greater attention to the festivities associated with a sport
event may be important for improving the quality of experience that spectators and
participants obtain, festive activities that are built into the event may suppress visitor spend
– not only because the events are for free, but also because the time taken up by these
activities is time not devoted to other forms of celebration. Event attendees spent their time in
the venue attending the activities of the event. These activities might therefore be crowding
out potential revenue for local business (e.g. Mules and Dwyer, 2005; Preuss, 2005;
Kesenne, 2005), not allowing local businesses to bene?t from the event in the manner
recommended by Chalip and Leyns (2002).
There is a related issue here having to do with the differences between festival and spectacle
at an event (Chalip, 2006; MacAloon, 1984). Most opening and closing ceremonies aim to
produce spectacle, and are not really about festival, even if they are called ‘‘festival’’ by
event organizers. When event attendees remain in the role of audience, and performances
are staged for them, then they are not participants in festive celebrations; they are merely an
audience to whatever performances are provided. Much of what is staged is intended to be
spectacular, such as parades during the ceremonies and ?reworks at the end. Event
attendees are not invited to become active celebrants during these activities. Yet, it has
been shown elsewhere that the capacity to become active participants in a celebration can
play a pivotal role in participants’ enduring sense that the event was worthwhile and their
consequent spending (Ehrenreich, 2007; Green and Chalip, 1998; Veno and Veno, 1992). To
the degree that performances crowded out festival, the event’s overall economic value may
have been reduced. These ?ndings suggest the value of future work that examines ways to
foster festival at events (see Handelman, 1990).
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Limitations
This study has focused on spending patterns at the Pan American Junior Athletic
Championships, which were a unique event for the city of Windsor. It would be worthwhile to
compare these ?ndings with spending patterns of attendees of other events, in order to
explore variations in the ways that spending is segmented, and the ways that event
organizers do or do not nurture a sense of festival among attendees.
The survey relied on self-reported spending (recall in the case of spectators, estimates in the
case of participants). A different approach to collect spending data, such as a spending
journal, could provide more accurate spending patterns, but would limit the number of
attendees who could be surveyed. Although accurate population numbers were available for
the participants through the Local Organizing Committee (LOC, 2005), the population
numbers for the spectators had to be estimated in order to calculate the aggregate numbers.
It should be noted that small differences in these population estimates can have an impact on
aggregated numbers. Thus, some caution is warranted when estimations are used.
Concluding observation
Insight into event-related spending of different visitor segments allows speci?c economic
sectors to strengthen their marketing strategies by targeting the speci?c segments that
bene?t fromtheir products and services. It also suggests the need for greater attention to the
festival that sport events are intended to enable.
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About the authors
Dr Marijke Taks has expertise in socio-economic aspects of sport and leisure, with particular
interests in consumer behaviour of various sport-oriented groups. She researches impacts
of sport events from a variety of perspectives, including economic, tourism, and sport
participation. She teaches courses in sport marketing, socio-economic aspects of sport and
leisure and global issues in sport management. She is currently the editor of the European
Sport Management Quarterly.
Dr B. Christine Green, whose work focuses on sport development, has examined consumer
behaviour in sport, sport and event tourism, and development of sport organisations. She
teaches courses in sport marketing, organisational behaviour in sport, sport development,
and sport events. She is a Research Fellow of the North American Society for Sport
Management, and former editor of Sport Management Review.
Dr Laurence Chalip, whose work focuses on sport policy, has examined the formulation and
implementation of sport policies, sport marketing, and the leverage of sport events. He
teaches courses in sport marketing, sport policy, and sport economics. He is a Research
Fellow of the North American Society for Sport Management, founding editor of Sport
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Management Review, and former editor of the Journal of Sport Management. Dr Laurence
Chalip is the corresponding author and can be contacted at: [email protected]
Stefan Kesenne, whose main expertise is the economic theory of professional team sports,
teaches a class of Sports Economics at the Economics Department of the University of
Antwerp, at the Human Kinesiology Department of the Catholic Univerity of Leuven, and at
the Euromed Marseille School of Management. He is a member of the Editorial Board of the
Journal of Sports Economics and of the European Sport Management Quarterly.
Dr Scott Martyn, whose research expertise is in the area of the historical evolution of the
Olympic Games and af?liated insignia as sport marketing properties, has served on the
executive council of the International Centre for Olympic Studies, and continues to serve on
executive councils of the North American Society for Sport History, and the International
Society for Comparative Physical Education and Sport. He is also the chief editor of
International Sports Studies, and the managing editor of Olympika: The International Journal
of Olympic Studies.
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