A theoretical comparison of the economic impact of large and small events.
Agha, Nola ; Taks, Marijke
Introduction
Much of the economic impact research to date has focused on
mega-event impact such as the Olympic Games or the FIFA World Cup (e.g.,
Baade & Matheson, 2004; Matheson, 2006a; 2009; Maennig &
Zimbalist, 2012; Porter & Fletcher, 2008; Preuss, 2004; 2007; Tien,
Lo, & Lin, 2011). Recently, the focus has shifted to smaller events
(e.g., Agha & Rascher, in press; Coates & Depken, 2011; Daniels
& Norman, 2003; Matheson, 2006b; Mondello & Riche, 2004; Taks,
Green, Chalip, Kesenne, & Martyn, 2013; Taks, Kesenne, Chalip,
Green, & Martyn, 2011; Veltri, Miller, & Harris, 2009; Wilson,
2006). While smaller events may generate limited economic activity,
their outcomes and net benefits for the local community might actually
be more positive (Matheson, 2006b; Seaman, 2004). As such, the purpose
of this paper is to use a theoretical framework to determine whether
large or small events have more beneficial economic impacts.
However, a comparison of economic impact using only event size is
insufficient. Characteristics of the host destination are equally
important in assessing impact. As articulated by Getz (2012), "even
small music festivals can have 'mega' impacts on a small town
in terms of tourists, economic benefits or disruption" (p. 45).
Thus, to determine if large or small events have higher positive
economic outcomes or net benefits for host communities, we create a
framework that takes both event and city characteristics into
consideration.
The structure of the paper is as follows. Given the complexity of
the political decision making process for hosting events, we first
provide the context why it is important to introduce a resource-based
framework and focus on the value of smaller-sized events in general, and
their economic value in particular. In order to do so, we redefine
events as continuums of required resources instead of using existing
event typologies. Similarly, cities are redefined as continuums of
supplied resources. Once events and cities are defined in the same
terms, we use well-known drivers of economic impact to create a
theoretical framework and a visual presentation of economic impact based
on an interaction of event resource demand and city resource supply. To
generate an applied perspective, we include local economic conditions
that shift the supply of available city resources, create a city
resource deficiency, and create a realistic view of the economic impact
of an event on a city. It is only this applied framework that can
determine the economic impact of different sized events in different
sized cities which then allows us to draw conclusions.
The Value of Smaller-Sized Events in Host Communities
Events of various sizes can generate a variety of impacts and
outcomes for host communities. Two themes have dominated the research
agenda in the past, namely a focus on economic impact and large-scale
events (e.g., Maennig & Zimbalist, 2012). Recently, researchers have
started to shift their attention towards more intangible assets or
returns of events (e.g., Preuss, 2007), such as social (e.g., Heere et
al., 2013), urban regeneration (e.g., Smith, 2012), physical activity
and sport participation (e.g., Craig & Bauman, 2014; Weed et al.
2009), and environmental impacts (e.g., Chappelet, 2008). While the
underlying reasons from political officials to host events may be
unclear and serve (their) hidden (political) agendas, they like to rave
about the positive impacts events can generate for the host community.
However, they most often rely on economic justifications (including
tourism). This is particularly true when taxpayers' dollars are
used to stage the (often too expensive) event. In most cases,
policymakers rely on standard economic impact analysis (EIA) to make
their claims. These studies are not without controversy and more
researchers point towards the necessity to perform more accurate
cost-benefit analyses (CBA; e.g., Kesenne, 2012). The framework proposed
in this paper builds on this idea, and specifically allows politicians,
policymakers, and event organizers to make more rational economic
decisions.
The focus on large-scale events also warrants a shift, as more
research starts to reveal valuable outcomes of hosting smaller-scale
events, be it from an economic (e.g., Mondello & Rishe, 2004;
Matheson, 2006b; Taks et al., 2011), tourism (e.g., Gibson, Kaplanidou,
& Kang, 2012), social (Djaballah, Hautbois, & Desbordes, 2015),
or sport participation perspective (e.g., Taks, et al., 2014). The added
value of smaller-scale events is partially based on the potential for
social capital through tighter social networks, a sense of ownership,
and connectedness of the local population with the event as opposed to
large or mega-events (Taks, 2013). More research on smaller-scale events
is needed to substantiate these claims. The current paper contributes to
this endeavor in the realm of economic impact. The proposed
resource-based framework demonstrates that smaller-sized events can
generate more optimal economic outcomes for host communities, and can
assist public officials and elected leaders to understand the
opportunities and real economic value of smaller-scale events.
Operational Definition of Events as Continuums of Resources
There are no universal definitions of different types of events.
However, events are often defined as a function of their assumed
economic impact. For example, Gratton and Taylor (2000) define
"Type A" events as "irregular, one-off, major
international spectator events generating significant economic activity
and media interest;" "Type B" events as "major
spectator events generating significant economic activity, media
interest and part of an annual cycle of sport events;" "Type
C" events as "irregular, one-off major international
spectator/competitor events, generating limited economic activity;"
and "Type D" event as "major competitor events generating
limited economic activity and part of an annual cycle of sport
events" (p. 190). While Type C and D events may possibly generate
limited economic activity, their outcome and net benefit for the local
community might actually be more positive (or negative) compared to Type
A and B events (e.g., Mondello & Riche, 2004; Matheson, 2006b).
Moreover, economic impact is a function of both an event and the city
where it occurs, thus we offer an alternative to categorizing events on
assumed impact.
Instead of defining events categorically, we argue that the size of
the event is a function of the resources needed to stage the event and
the resources needed to host all of the event-related attendees
(participants, spectators, officials, media, etc.). In other words, we
direct focus on the required local resources rather than the event
outcomes (e.g., economic impact).
Events require investments of human, financial, and physical
resources from communities that stage them. Human resources include the
employees and volunteers required to stage the event. Financial
resources include private and government investments. Physical resources
comprise aspects such as venues, accommodation, private and public
transportation, and food services. Generally, large events tend to
attract more visitors and higher levels of business and government
support because of their high profile and often global reach, and thus
require more resources (e.g., Horne & Manzenreiter, 2006; Preuss,
2009). In contrast, smaller events generally attract fewer visitors and
lower levels of business and government support, and thus require fewer
resources (e.g., Gibson, Kaplanidou, & Kang, 2012). We recognize
that events have all of these characteristics but we emphasize the
importance of the resource requirements.
We introduce the concept of event resource demand (ERD) as a
multivariate measure of the total resources needed to stage an event.
Events are bundles of human, financial, and physical resources that
differ in the types of resources needed and the quantity of each of
those resources depending on the nature of the event. For example, a
multi-sport participatory event may require few paid staff, many
volunteers, multiple venues, few hotel rooms, and no public funding; in
comparison, a singlesport international championship may need the
involvement of paid staff, fewer volunteers, the usage (or possibly
construction) of one large venue, many hotel rooms, and public funding.
Thus, instead of using existing categorical typologies of events,
we define large events as those with high ERD and small events with low
ERD and acknowledge that there are an infinite number of events that
fall on the ERD continuum. In the remainder of this paper, the term
large event does not apply to previous event typologies or event
outcomes, but instead to an event with a high ERD. Similarly, the term
small event refers to one with a low ERD.
Operational Definition of Cities as Continuums of Resources
Cities (1) can be defined on a spectrum of demographic, economic,
geographic, and financial terms. These measures can provide a
description of a city's population, GDP, land area, or per capita
income. While these measures are informative, they are insufficient to
predict economic impact. The city characteristics that affect the
economic impact of an event are instead the available resources: the
supply of labor (human resources), government and private investment
(financial resources), and the capital infrastructure in terms of
airports, roads, hospitality, and event venues (physical resources).
Similar to events, cities offer bundles of resources in which the type
and quantity of each resource differs.
Instead of defining cities categorically, we introduce the concept
of city resource supply (CRS) as a multivariate measure of the total
resources a city supplies to stage the event (venues, volunteers, staff,
etc.) and to host the event attendees (participants, spectators,
officials, media, etc.). For example, a city with a small population
that is a highly sought after tourism destination will have a
well-developed hospitality industry including a specialized labor force,
and may have state-of-the-art venues. On the other hand, a city with a
larger population that is not a tourism destination will have fewer
hospitality accommodations and a less developed labor force, and may
have fewer and older venues. In this case the city with the lower
population may have a higher CRS to stage a sport event compared to the
city with the higher population. Thus, in the context of CRS, large
cities are those that have more local resources to stage and host events
compared to small cities that have fewer local resources. Similar to
events, we view city size along this continuum of resource supply.
It is important to note that the definition of CRS captures many
city-related features that affect economic impact. For example, a
smaller, geographically isolated city will have fewer inherent
resources, placing them lower on the continuum of CRS, but will have
more money coming from the outside, generating new visitor spending
until its resources are fully utilized. On the other hand,
geographically isolated cities will incur considerable leakages to
obtain any resources the event demands that are not locally available.
In this way, CRS captures city-related features to predict economic
impact.
In order to compare the economic impact of large and small events
using an analysis of resources, we next introduce 10 well-known drivers
of economic impact that allow us to interact ERD and CRS.
Economic Impact Drivers
Hundreds, or perhaps thousands, of event- and city-related
variables must be taken into consideration when quantifying economic
impact. These variables range from time switchers to the source of
funding for a new venue. As such, it is nearly impossible to compare any
two events, especially when these events are held in different cities.
To solve this problem we note that, fundamentally, these variables
measure every event expenditure that either increases or decreases
economic impact. In order to compare events of different sizes on the
same terms in a way that does not involve the analysis of hundreds of
variables that differ from event to event, we categorize decades of
academic research on economic impact (e.g., Baade, Baumann, &
Matheson, 2008; Campbell & Brown, 2003; Coates, 2007; Cobb &
Olberding, 2007; Crompton, 1999; Crompton & Howard, 2013; Downward,
Dawson, & Dejonghe, 2009; Dwyer, Forsyth, & Spurr, 2006; Johnson
& Whitehead, 2000; Kesenne, 2012; Preuss, 2005; Rosentraub &
Swindell, 1991; Taks, Girginov, & Boucher, 2006; Taks et al., 2013)
into 10 activities we call economic impact drivers (EID). The 10 drivers
presented in Figure 1 were motivated by previous attempts to classify
EID (Agha & Rascher, in press) and provide a framework for
determining the costs and benefits of events in the most basic terms. It
is imperative to understand that every feature that relates to economic
impact is captured by five benefit drivers that increase economic impact
and five cost drivers that decrease economic impact. Henceforth, we use
an analysis of resources (ERD and CRS) to illustrate the economic impact
of various events using a cost benefit analysis (CBA) approach (e.g.,
Taks et al., 2011).
Theoretical Perspective on the Interaction of Event Size and City
Size
If we continue to view cities as bundles of supplied resources and
events as bundles of demanded resources, then we can match supply and
demand (see Figure 2). First, there are the cases where every resource
that an event demands (ERD) is locally available. In the case of Event 1
([E.sub.1]), City 1 ([C.sub.1]) can exactly supply the resources
demanded by Event 1 (CRS=ERD). Similarly, in the case of Event 2
([E.sub.2]), the city has more than enough resources (CRS) to meet the
needs of the event (CRS>ERD). In the case of [E.sub.1] and [E.sub.2],
there will be new spending, job creation, increased tax revenues, and
very little, if any, crowding out, leakages, or opportunity costs.
There are also cases where every resource that an event demands
(ERD) is not entirely locally available. In the case of Event 3
([E.sub.3]), City 1 does not have all necessary resources demanded by
the event (CRS<ERD) which means the city will not benefit from some
of the new spending, job creation, and tax revenues. Other visitors are
crowded out, more leakages occur beyond normal economic flows, and
opportunity costs increase due to necessary capital investments.
Cost Benefit Analysis of Large and Small Events in Large and Small
Cities
In what follows, we continue the discussion of matching ERD and CRS
by contrasting large events and small events in small and large cities.
We use the 10 drivers to determine the benefits, costs, and net economic
impact of each event-city combination. For the sake of simplicity, we
illustrate the extreme points of the continuums: (a) a large event not
exceeding the CRS in a large city; (b) a large event exceeding the CRS
in a small city; (c) a small event not exceeding CRS in a large city;
and, (d) a small event not exceeding the CRS in a small city. For
clarity, we reiterate that the terms large and small events refer to the
resources demanded to stage them. Similarly, the terms large and small
city refer to the resources available to stage events.
[FIGURE 2 OMITTED]
Large events organized in large and small cities
Absolute benefits. In absolute numbers, the new money spent locally
is higher when a large event is organized in a large city (Point A in
Figure 3, CRS=ERD) because large cities, by definition, have more
resources available (B1, see column 2 in Table 1). When large events are
being organized in small cities (Point B in Figure 3, CRS<ERD), small
cities lose out on some new local spending because of fewer local
resources. For example, visitors may have to stay overnight elsewhere
because there is no availability in the small city. Large events may
trigger residents and businesses to tap into their savings to
participate in the event, in which case the economic benefits are
slightly larger in large cities than in small cities due to the
available resources (B2). In absolute numbers, a large event would need
the same number of new jobs in a large and a small city but a large city
has more human resources to provide these jobs than a small city (B3).
Having higher levels of spending in large cities generates higher tax
revenues and thus a higher economic benefit for large cities than for
small cities (B4).
Public good value will always be higher in cities with a higher
population size (e.g., Johnson & Whitehead, 2000; Taks et al.,
2011); however, in our definition of city size, high CRS cities do not
always have higher populations. Consumer surplus of a large event in a
large city is less than in a small city because there are fewer
alternatives available in smaller cities. Community pride may be lower
in a large city than a small city because the profile of a large event
is unique enough to define a small city's identity for generations
(e.g., Jago, Chalip, Brown, Mules, & Ali, 2003; Ritchie & Lyons,
1990). Thus, the net effect of the intangible benefits of large events
in large versus small cities remains unknown at this time (B5).
Thus, using ERD, CRS, and the five benefit drivers we show that
from a benefit perspective, there are larger absolute economic benefits
of large events in larger cities compared to smaller cities.
Absolute costs. In terms of costs, a large event in a small city
crowds out more absolute visitors simply because the small city does not
have the physical resources to accommodate all crowds (C1). The behavior
of residents in large and small cities in the context of large events
may be similar, but can take two forms with opposite effects. For
example, fewer residents may be inclined to flee because of the
uniqueness of a large event. On the other hand, because of congestion
residents may want to leave regardless of the size of the city. Without
knowing the net effect of these behaviors, the potential for crowding
out residents in large cities is greater in absolute numbers compared to
small cities (C2).
[FIGURE 3 OMITTED]
Large events are more likely than small events to disrupt host
communities regardless of CRS but this disruption is higher in small
cities. However, in absolute numbers, more local businesses in larger
cities are negatively impacted by a large event (C3). Similarly, with
regard to the location of a large event organized outside the central
business district, in absolute numbers a larger amount of local business
activity will be crowded out in larger cities because there are fewer
opportunities for that to happen in small cities (C3).
Large events create an excessive amount of leakages in small cities
by the mere fact that not all necessary resources are locally available.
Much of the initial new spending from visitors, the event organizer,
non-local businesses, and even non-local governments will be leaked from
the local economy (C4). In absolute terms, the opportunity cost of large
events is the same for large and small cities (C5).
Overall, crowding out visitors (C1) and leakages (C4) are larger in
absolute terms than any crowding out of residents (C2) or local business
activity (C3) (e.g., Dwyer et al., 2006), making these drivers the
dominant determinants of cost. Therefore, from a cost perspective, there
are larger absolute economic costs of large events in small cities that
do not meet the ERD compared to large cities that meet the ERD.
Net effect. Overall, we see higher benefits and smaller costs for
large events in large cities (Point A, Figure 3). The opposite holds
true for large events in small cities where we find lower benefits and
higher costs (Point B, Figure 3). Thus, the overall net economic impact
of large events is higher in large cities where CRS matches ERD.
Small events organized in large and small cities
Absolute benefits. Column 3 in Table 1 illustrates the interaction
effect of small events in large and small cities. In absolute numbers,
the new money spent locally (B1) is the same when a small event is
organized in a large city (Point C in Figure 4, CRS>ERD) as when
organized in a small city (Point D in Figure 4, CRS=ERD).
In the rare occurrence that small events trigger residents and
businesses to tap into their savings to participate in the event the
effect would be higher in absolute terms in large cities (B2). Given the
unlikelihood of this occurring, the effect is expected to be equivalent.
Job creation is unlikely in the context of small events in both large
and small cities (B3). Similarly, if it were to happen the effect would
be equivalent in absolute terms. Tax revenues will be similar (B4).
The overall intangible benefits remain unknown (B5). For example,
consumer surplus of small events in small cities may be higher than in
large cities because of very few alternatives in small cities. Public
good values may have higher per capita values in small cities and
smaller values in large cities, but the effect will be larger in cities
with higher populations (note that in our definition of city size, high
CRS cities do not always have higher populations). In the extreme case,
a small event could have no value in a large city, which illustrates why
the overall intangible effect is unknown.
[FIGURE 4 OMITTED]
Using ERD, CRS, and the five benefit drivers we show that from a
benefit perspective, and in absolute terms, there is no difference in
benefits of small events in larger cities compared to smaller cities.
Absolute costs. In terms of costs, both large and small cities have
the physical resources to accommodate all crowds in the case of a small
event (Points C and D in Figure 4), thus there is no crowding out of
visitors (C1). A small event will not crowd out residents in large
cities nor will it happen in the context of small cities (C2). Small
events will not disrupt host communities when ERD is less than CRS but
disruption will be more conspicuous where ERD nears CRS at Point D
compared to Point C (C3). With regard to the location of a small event
organized outside the central business district, in absolute numbers an
equivalent amount of local business activity will be crowded out in
large or small cities (C3). By definition, leakages for small events are
higher in small cities (C4). In absolute terms, the opportunity cost of
small events is the same for large and small cities (C5).
From a cost perspective, there are slightly higher costs for
smaller events in small cities because of leakages and the greater
potential for disruptions.
Net effect. Overall, we see an equal level of benefits for small
events in small and large cities, but slightly higher costs for small
events in small cities (Point D). The opposite holds true for small
events in large cities, where we find slightly lower costs (Point C).
Thus, the overall net economic impact of small events is higher in large
cities where CRS exceeds ERD.
Local Economic Conditions That Change the Capacity of CRS
So far, we defined CRS in terms of the existence of resources,
assuming that every possible local resource is available ([C.sub.1max]
in Figure 5). Obviously this is a theoretical case at one end of the
continuum. However, realistically there are local economic conditions
(e.g., a tourism destination at peak tourism season or level of
employment) that may reduce the available capacity of those resources
([C.sub.1s] in Figure 5). On the other end of the continuum is the
extreme case when the city is at full capacity and has no resources left
to host an event ([C.sub.1fc] in Figure 5) ,which becomes a small city
in the context of defining city size in terms of CRS.
The local economic conditions of the host community that shift the
CRS affect each of the 10 economic impact drivers and hence the
direction and the degree of the economic impact of the event. In a city
where the capacity of resources is reduced, the economic impacts of the
benefits remain positive although this may to be a lesser degree. For
example, new money that would normally be spent locally (B1) may have to
be spent elsewhere (e.g., a visitor having to stay at a hotel outside
the host community). Similarly, increased spending by residents may be
reduced because of overcrowding (B2). This reduction in overall spending
will lower local tax revenues (B3). In the case of full employment, job
creation is reversed into a negative impact; new jobs cannot be created
and new hires will need to come from elsewhere (B4). While the event may
still generate intangible benefits, they too may be experienced at a
lower degree (B5).
From a cost perspective, the economic impacts of the costs remain
negative although this may to be a greater degree. For example, an event
during peak tourism season will crowd out more visitors (C1), more
residents (C2), be more disruptive (C3), and generate greater leakages
(C4) (e.g., Porter, 1999). Opportunity costs will also increase because
resources have to be taken away from other projects (C5).
[FIGURE 5 OMITTED]
Overall, the 10 drivers indicate that with decreased benefits and
increased costs, the net economic impact under capacity constraints of
the resources is lower than when all of a city's resources are
available regardless of the size of the event.
Applied Perspective on the Interaction of Event Size and City Size
In what follows, we now apply the concept of capacity constraints
of CRS by taking the local economic conditions into consideration. We
draw a more realistic picture of the economic impact of different sized
events in different sized cities and then derive important conclusions.
City Resource Deficiency
The effect of the local economic conditions described above are
graphically illustrated in Figure 6 in the context of hypothetical Event
1 ([E.sub.1]). The shift from the theoretical [C.sub.1max] to a more
realistic Cis changes the CRS=ERD equilibrium at Point A to Point
[x.sub.1] where CRS<ERD. This shift results in a deficiency of
available resources to host E1 in City 1 which we define as city
resource supply deficiency (CRS-De). If [C.sub.1s] hosts [E.sub.1],
CRS-De is a measure of the resources that the event needs and the city
does not yet have. Because CRS-De is a multivariate measure, the CRS-De
could be, for example, an insufficient number of venues or an
insufficient number of rooms to accommodate athletes and visitors. In
either case, the acquisition of these resources generates costs (C5).
Even in the extreme case where the resources are provided through
funding from an external source (e.g., from the federal or state
government or private investors to construct a venue) this could only be
a benefit (B1) if the labor and raw materials were sourced locally.
Considerable research suggests this is rarely, if ever, the case (e.g.,
Miller, 2002).
[FIGURE 6 OMITTED]
Effect of City Resource Deficiency on Economic Impact
Economic impact is generated through the use of available
resources. When City 2 ([C.sub.2]) hosts Event 2 ([E.sub.2]) in Figure
6, the event uses all of the available city resources (Point [x.sub.3]).
If [C.sub.1s] hosts [E.sub.2], it generates a similar economic impact by
utilizing city resources up to Point [x.sub.4] but also has an excess
supply of resources between [x.sub.4] and [x.sub.2], which we define as
city resource supply surplus (CRS-Su).
If [C.sub.1s] hosts [E.sub.1], the use of the resources available
up to [x.sub.2] results in positive economic impact. However, [C.sub.1s]
must also provide the resources between [x.sub.2] and [x.sub.1] and can
only do so by incurring additional costs, therefore lowering the
economic impact generated up to point [x.sub.2].
As CRS and ERD are multivariate measures, the costs incurred to
obtain missing resources can be large or small depending on the resource
deficiency. Venue construction may costs millions of dollars while a
city lacking 50 hotel rooms will commonly provide accommodations outside
the area of impact in a nearby city. Although accommodation spending
occurs outside of the area it is possible that other expenditures on
food, merchandise, or other items do occur within the area of impact. In
either case, the result is that the full potential benefit derived from
the consumption of local resources is not captured. Thus, we refer to
point [x.sub.2] as the optimal impact. It is the point where the
consumption of all local resources provides an economic benefit and
acquisition of external resources has not yet incurred costs. To be
clear, it is still possible for the actual economic impact to increase
in a state of resource deficiency (as local spending on food or
merchandise in the example of the 50 hotel rooms) although the actual
values will depend on the specific nature of the deficient resources.
[FIGURE 7 OMITTED]
Key Findings
In this section, we now include this new notion of CRS-De in the
context of the interaction of large events in large cities and small
events in small cities. This analysis discloses three important key
points.
First, no city has ever had the required resources to stage events
with the largest ERD (e.g., mega-events such as the Summer Olympic
Games, FIFA World Cup), thus making Point X in Figure 7 entirely
theoretical. The gray areas in Figure 7 illustrate that there are a
range of mega-events that exceed the maximum CRS of any city so that in
the case of these mega-events CRS is always less than ERD and these
cities will always incur costs to provide resources that are not locally
available. These costs will reduce the economic impact. The larger the
resource deficiency, the larger the reduction in economic impact.
Second, the hosting of a large event ([E.sub.x]) in a large city
([C.sub.x]) is represented in Figure 7, illustrating the resource
deficiency (CRS-[De.sub.x]) for this scenario. Similarly, we look at a
case where the ERD of a smaller-sized event ([E.sub.2]) surpasses the
available resources of a smaller-sized city ([C.sub.2]) with the
deficiency illustrated by CRS-[De.sub.2]. A smaller CRSDe brings a city
closer to the optimal economic impact than does a larger CRS-De. At this
point it is clear the CRS-[De.sub.x] of the large event exceeds the
CRS-[De.sub.2] of the smaller event, indicating that smaller events with
a lower resource demand have a higher potential for optimal economic
impact compared to larger events with higher resource demands.
Third, the ERD of smaller-sized events (E2) can meet the CRS of
more cities (as illustrated by the bold arrow in Figure 8) than can
large events (illustrated by the dashed arrow). In fact, [E.sub.2]
generates the same amount of economic impact in all cities to the right
of [C.sub.2]; however, [C.sub.2] would have the optimal economic benefit
while the other cities have a CRS-Su on which they do not capitalize.
[FIGURE 8 OMITTED]
In sum, smaller events are more likely to operate in the context
where there is a surplus of local resources. Even in the case of small
events where CRS is less than ERD, these events are closer to reaching
the optimal economic impact than large events.
Limitations
ERD and CRS are important concepts in reconceptualizing the
economic impact of events of any size in cities of any size, yet the
framework has limitations. It does not account for sustained economic
impact that would occur if there is an increase in future tourism,
generating future revenue streams (e.g., Preuss, 2007). However, the
occurrence of additional revenues generated from increased future
tourism through events is highly doubtful (e.g., Solberg & Preuss,
2007). The proposed framework also does not account for other event
goals beyond economic impact that a city may pursue, for example, city
branding (e.g., Jago et al., 2003) or urban regeneration (e.g., Hiller,
2000; Taks, 2013).
The discussion thus far has centered on absolute impacts while many
of the existing arguments for small events are based on relative size
(e.g., Matheson, 2006b). For example, small events can have positive
impacts, which in the context of a small city may be relatively more
important than their positive impact in a big city. Similarly, it could
be argued that the relative cost of hosting a large event in a small
city will be more devastating in economic terms than hosting a small
event in a small city.
Finally, in the discussion of local economic conditions when a city
is at full capacity the prices of commodities and labor increase (e.g.,
Dwyer et al., 2006; Porter, 1999). Whether these increased prices
generate a net benefit for the local economy remains unclear (and is not
included in the model), but price increases may be a burden for the
residents, and thus negatively perceived, thereby lowering the
intangible benefit (e.g., the public good value).
Practical Application
The resource requirements for hosting a single event do not vary
and different cities offer different bundles of resources. Thus, if the
goal of hosting an event is to generate positive economic impact, city
planners and event managers can do so by carefully selecting an event
that requires resources that are available locally. If the goal is to
maximize economic impact, they can do so by selecting events that
perfectly match the available city resources and demanded event
resources. Hence, the first step in making an informed decision for
hosting an event is a thorough analysis of event resource requirements,
available city resources, and local economic conditions. For example, if
the city has the option to choose between an event occurring during peak
tourism season that needs a new pool and an event not occurring during
peak tourism season that does not require building new venues, the later
event will generate a higher economic impact, all else being equal.
Furthermore, the same event held in different cities will
experience different levels of participant and spectator demand. For
example, a well-known tourism destination, easily accessible through
transportation networks, or a regional interest in a particular sport
will increase demand. This illustrates how practitioners must take into
consideration the local conditions. This variation in demand is captured
in the framework not only through increased benefits from new visitor
spending but also through costs as an event with more demand will
require more resources.
In the framework of an event portfolio (e.g., Chalip, 2004; Ziakas
& Costa, 2011), multiple smaller events that do not exceed a
city's available resources will be cumulatively more beneficial
than a large event that exceeds a city's resources and requires
significant expenditures to obtain the missing resources.
Finally, in deciding which events to host, a city can use the
economic impact drivers to select events that have features that lend
themselves to higher benefits. For example, an event that draws more
visitors will have a larger impact than one with predominately local
attendees. Similarly, an event with lots of features associated with
cost drivers will have a smaller impact.
Conclusion
We began this paper with the objective to determine whether smaller
events generate more positive net benefits for local communities
compared to large events. In order to support this assertion, we
developed a three-way interaction between the drivers of economic
impact, city size, and event size. To do this required several steps.
First, we defined events as continuums of demanded resources. Next,
we redefined cities, similar to events, on a continuum of available
resources. The idea of city resource supply and event resource demand
allowed for the comparison of events of any size and cities of any size.
By recategorizing existing determinants of economic impact into five
benefit and five cost drivers we were able to interact city size and
event size and determine economic impact from a theoretical perspective.
Subsequently, local economic conditions were added to the analysis
because any situation that reduces the capacity of resources is crucial
in the final determination of economic impact. These adjustments to
resource availability allowed for a realistic perspective of the
interaction of event size and city size. The concept of city resource
supply deficiency was developed to illustrate its importance in the
determination of the actual economic impact of different sized events in
different sized cities.
Optimal economic impact of any event occurs when locally supplied
resources are equal to demanded event resources. Very few cities have
the local resources to host and stage an event with a large resource
demand, which creates a large resource deficiency. The costs of
supplying the deficient resources reduces the economic impact of large
events in large cities. In other words, an event that makes a city
exceed capacity will generate costs that lower the economic impact.
In contrast, by definition, small events require fewer resources
and are therefore more likely to operate with a smaller resource
deficiency or even at an optimum level where demanded and supplied
resources are well matched. In addition, there are more cases where
supplied resources are greater than demanded resources for a small event
than for a large event, suggesting that small events benefit more cities
than large events. Ultimately, many more small events can be hosted by
many more cities, thereby generating more benefits to more host
communities, which at the aggregate level could surpass any benefits of
a one-off, large-scale event.
In order to capture economic impact more accurately, future
research should apply this theoretical framework by analyzing and
quantifying the resource requirements of sport events and the resources
available in the cities in which the events are hosted. If resource
deficiencies occur, the costs associated with obtaining those resources
must be accurately examined, acknowledged, and integrated in current and
future event planning. Future research can also test the application of
this framework by city managers in the event selection process. The
definitions ERD and CRS offer a transparent framework to assist public
officials and elected leaders in making more rational economic decisions
when it comes to hosting events.
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Nola Agha, PhD, is an assistant professor in the Sport Management
Program. Her research interests include the economic impacts of teams
and stadiums, the efficiency and equity outcomes of stadium subsidies,
and a variety of issues related to minor league baseball.
Marijke Taks, PhD, is a professor in the Department of Kinesiology
and an adjunct professor in the Department of Kinesiology at the
University of Leuven (Belgium). Her grant-supported research focuses on
socioeconomic aspects of sport with a particular emphasis on impacts,
strategic outcomes, and leveraging of sport events.
Endnote
(1) Events can be hosted by a variety of geographic entities such
as cities, counties, regions, provinces, states, or nations. We refer
generically here to the city as the host entity.
Nola Agha [1] and Marijke Taks [2]
[1] University of San Francisco
[2] University of Windsor, Ontario, Canada
Table 1. Comparison of Economic Impacts between Different Sized
Events, Interacted with Different Sized Cities
(2) (3)
Large Events Small Events
Large Small Large Small
City City City City
Benefit Drivers
B1. New spending
(spent locally) by non-locals > =
B2. Increased spending
(spent locally) by residents > =
and businesses
B3. Job creation
B4. Tax revenues > =
B5. Intangible benefits > =
Cost Drivers -- --
C1. Crowding out other visitors
C2. Crowding out residents < =
C3. Crowding out local business > =
activity > <
C4. Leakages (local revenue
spent non-locally) < <
C5. Opportunity costs of local
money spent locally = =
Note. A large event in a large city aligns with Point A in Figure
3. Similarly, a large event in a small city aligns with Point B
in Figure 3. A small event in a large city is Point C and a small
event in a small city is Point D in Figure 4.
Legend.--means outcome unknown.
Figure 1. Economic impact drivers
Benefit Drivers Cost Drivers
Increase Economic Impact Decrease Economic Impact
B1. New spending C1. Crowding out other
(spent locally) by: visitors
--Visitors C2. Crowding out locals
--Event organizer C3. Crowding out local
business activity
--Non-local businesses --Disruption
--Non-local government --Event location
(set up)
B2. Increased spending C4. Leakages (local revenue
(spent locally) by: spent non-locally)
--Local residents C5. Opportunity costs of
local money spent
--Local businesses locally on:
--Local government --Short-term operating costs
(see C5) --Long-term operating costs
B3. Job creation --Capital costs
B4. Tax revenues
B5. Intangible benefits