of non-prot sport clubs in Germany

Pamela Wicker a,*, Christoph Breuer b, Ben Hennigs b

aDepartment of Tourism, Leisure, Hotel and Sport Management, Grifth University, Nathan Campus, 170 Kessels Road, Nathan, Queensland 4111, Australiab Institute of Sport Economics and Sport Management, German Sport University Cologne, Am Sportpark Muengersdorf 6, 50933 Cologne, Germany

Sport Management Review 15 (2012) 318329

A R T I C L E I N F O

Article history:

Received 23 June 2011

Received in revised form 20 December 2011

Accepted 22 December 2011

Keywords:

Non-prot sport organisation

Income portfolio

Crowd-out effect

Crowd-in effect

Uncertainty

Elasticity

A B S T R A C T

The revenue composition of for-prot and non-prot organisations is fundamentally

different. Non-prot organisations have diversied revenues and must therefore manage

an income portfolio. For the management of the income portfolio of a non-prot sport club

it is not only important that sufcient revenues are available, but also where they come

from as complex interactions exist among different revenue sources. These interactions

are referred to as crowd-out effects (increases in one revenue source lead to decreases in

another source) and crowd-in effects, respectively. The interactions among revenue

categories of non-prot sport clubs were analysed using a longitudinal dataset from a

nationwide sport club survey in Germany (n = 5026). Elasticity measures were calculated

within a regression framework which provided information about the nature and

signicance of interactions. The results revealed a signicant positive interaction between

revenues from donations and sport supply (e.g., membership and service fees) pointing

towards a crowd-in effect, i.e., increased revenues from donations have crowded in

revenues from sport supply. Moreover, increased revenues from subsidies were found to

crowd in revenues from donations and economic activities (e.g., sponsorship). Signicant

negative interactions were observed for revenues from economic activities and other

supply suggesting that increased revenues from economic activities have crowded out

revenues from other supply. The ndings indicated an increased level of commercialisa-

Contents lists available at SciVerse ScienceDirect

Sport Management Review1. Introduction

Many countries have Sport for All policies aiming at increasing mass sport participation (e.g., Bergsgard, Houlihan,Mangset, Nodland, & Rommetvedt, 2007). These policies are supposed to be implemented by local community sport clubswhich represent important sport providers and can therefore be considered the backbone of the voluntary sport system in

tion supporting a modernisation of German clubs. Furthermore, the uncertainties have

increased and therefore sport clubs have to consider the level of uncertainty of their

revenue sources when they manage their income portfolio.

2011 Sport Management Association of Australia and New Zealand. Published byElsevier Ltd. All rights reserved.Understanding the interactions among revenue categories usingelasticity measuresEvidence from a longitudinal sample

jo u rn al h om ep age: w ww.els evier .c o m/lo c ate /s mrmany European countries and overseas (e.g., Breuer & Wicker, 2009; Lamprecht, Fischer, & Stamm, 2011; Lasby & Sperling,2007; Scheerder et al., 2010; Taylor, Barrett, & Nichols, 2009). In Germany for example, more than 90,000 sport clubs with

* Corresponding author. Tel.: +61 7 3735 3759; fax: +61 7 3735 6743.

E-mail address: p.wicker@grifth.edu.au (P. Wicker).

1441-3523/$ see front matter 2011 Sport Management Association of Australia and New Zealand. Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.smr.2011.12.004

P. Wicker et al. / Sport Management Review 15 (2012) 318329 319over 27 million memberships provide sport programmes for the population (German Olympic Sports Confederation, 2011).These community sport clubs are non-prot organisations which receive, among other income sources, governmentalsubsidies for the implementation of Sport for All policies. In many European countries, the subsidiarity principle has gainedin importance and policy-makers tend to build their policy objectives into conditional subsidies (Vos et al., 2011).

In order to be able to provide sporting opportunities for the population, to meet criteria for the reception of governmentalsubsidies, and to survive, non-prot sport clubs must be nancially healthy. As indicated by Young (2007, p. 3), money isvery important to the sustenance and success of nonprot organizations. However, non-prot organisations can experienceproblems in raising sufcient revenues and in securing capital (Young, 2007). Financial solvency can be a major issue forsport clubs with evidence showing that 28% of the clubs in the UK suffered a loss in 2009, i.e., they did not break even (Tayloret al., 2009). Although non-prot organisations are nancially restricted by the non-distribution constraint, i.e., they are notallowed to distribute prots among the members (Hansmann, 1980), they are required to break even (Young, 2007). It is notonly crucial for non-prot organisations to have enough revenues available; the revenue source is also important (Kearns,2007). The composition of an organisations total revenues can have an impact on the perceived legitimacy and importanceof the organisation by its publics (Chang & Tuckman, 1994). Therefore, non-prot organisations must not only pay attentionto the overall revenues, but also to the composition of their income portfolio. A further challenge of the portfoliomanagement is that revenue sources can change over time.

The aim of this paper is to give insights into the development of and the interactions among revenue categories of non-prot sport clubs as complex interactions exist among the different revenue sources of non-prot organisations (Anheier,2010). For example, increases in some revenue categories might lead to decreases in other categories, an interaction that isreferred to as crowd-out effect (Anheier, 2010; Young, 2007). In contrast, crowd-in effects can also occur, i.e., increases in somerevenue sources might lead to increases in other revenue sources (Kearns, 2007). This study has the following main researchquestion: how do the revenue categories of non-prot sport clubs interact with each other? The research question isanalysed with a unique longitudinal dataset (20072009) from a nationwide survey of non-prot sport clubs in Germany(n = 5026). The interactions are estimated using elasticity measures (Young, 2007). Elasticity measures indicate whetherchanges (increases or decreases) in one revenue category were related to changes in other categories and vice versa. Thestudy contributes to a further understanding of the complex interactions among different types of revenue sources andconsequently the importance of the management of the income portfolio for community sport clubs.

2. Revenues of non-prot (sport) organisations

The composition of revenues differs between for-prot and non-prot organisations. For-prot organisations rely mainlyon one source of revenue, i.e. (external) sales revenues (Young, 2007). In contrast, non-prot organisations depend onmultiple types of revenues and have an income portfolio to ensure sustenance and to effectively address their manifold socialmissions (Froelich, 1999; Young, 2007). By having multiple nancial resources non-prot organisations try to diversify theirrevenue streams as means of a risk reducing strategy and to combat resource dependence (Fischer, Wilsker, & Young, 2010).As stated in the resource dependence theory by Pfeffer and Salancik (1978) the key to organisational survival is the ability toacquire and maintain resources (p. 2). Organisations that rely on few income sources become highly dependent on them,which makes them vulnerable if one source decreases (Froelich, 1999).

Although revenue diversication is a distinct feature of non-prot organisations, the importance of revenue categoriesdiffers among organisations in different elds. While non-prot organisations in the eld of education rely mostly on fees,non-prot organisations in the eld of arts depend mostly on private giving and fee revenue (Young, 2007). Non-protorganisations in the elds of health (e.g., hospitals) rely heavily on revenues from government (70% of all revenues), followedby earned income (22%), and gifts and donations (4%; Gumulka, Barr, Lasby, & Brownlee, 2005). The importance ofmembership fees is distinctive for non-prot organisations in the eld of sport (e.g., Breuer & Wicker, 2009; Lamprecht et al.,2011; Taylor et al., 2009), a nding that is not surprising since active sport participation is the core product of sport clubs forwhich members pay their membership fees. Non-prot organisations from other areas like arts, culture or education do notrely so heavily on membership fees (Steinberg, 2007). Non-prot sport organisations also differ from non-protorganisations in other elds in terms of the overall revenues that are generated. Research has shown that non-prot sportorganisations have fewer nancial resources at hand than other types of non-prot organisations (e.g., Lasby & Sperling,2007).

An overview of the revenue mix of non-prot sport clubs in different countries including Europe, the UK, and Canada isprovided in Table 1. Sport clubs in Europe were found to rely heavily on revenues from membership fees as they representedtheir main source of income (Allison, 2001; Breuer & Wicker, 2009; Lamprecht et al., 2011; Scheerder et al., 2010; Tayloret al., 2009). Nevertheless, the importance of membership fees in terms of the contribution to the overall income differedamong clubs in different countries. In sport clubs in Scotland, revenues from membership fees made up 56% (Allison, 2001) ofthe total income indicating that Scottish clubs strongly rely on membership fees. In German clubs (Breuer & Wicker, 2009)and Flemish clubs (Scheerder et al., 2010), the contribution of membership fees to the overall income was found to be slightlylower (47.1% and 41.4%, respectively). Although being the most important income source, revenues from membership feesmade up 36% of all revenues in sport clubs in Switzerland (Lamprecht et al., 2011) and 29% in sport clubs in the UK (Tayloret al., 2009). The income source of second importance was income from fundraising in Scottish clubs (Allison, 2001) andFlemish clubs (Vos et al., 2011), revenues from bar, catering, and hospitality in sport in sport clubs in the UK (Taylor et al.,

P. Wicker et al. / Sport Management Review 15 (2012) 3183293202009), income from sponsorship deals in sport clubs in Switzerland (Lamprecht et al., 2011), and revenues from publicsubsidies in German sport clubs (Breuer & Wicker, 2009; Table 1).

The revenue composition of non-prot sport organisations was found to be slightly different in Canada, where fees forgoods and services represented the most important income source for sport and recreation organisations (31% of allrevenues; Gumulka et al., 2005). Sports and recreation organisations in the province of Ontario, Canada, generated the mainshare of their revenues from corporate sponsorships, gifts, donations and grants (30% of all revenues; Lasby & Sperling,2007). Revenues from membership fees were found to be the second important income source contributing 25% (Gumulka

Table 1

Overview of the revenue mix of non-prot sport clubs in different countries (in chronological order).

Author(s) Country Main ndings

Allison (2001) Scotland Membership fees were the most important income source (56% of

all revenues), followed by fundraising (15%), and bar/catering (8%)

Gumulka et al. (2005) Canada Fees for goods and services were the most important income

source (31% of all revenues), followed by membership fees (25%),

and corporate sponsorships, donations, and grants (15%); total

revenues decreased in 24% and increased in 30% of all

organisations between 2000 and 2003

Lasby and Sperling (2007) Ontario (Canada) Corporate sponsorships, gifts, donations, and grants were the most

important income source (30% of all revenues), followed by

membership fees (28%), fees for goods and services, excluding fees

charged to government (21%); total revenues decreased in 28%

and increased in 29% of all organisations between 2000 and 2003

Breuer and Wicker (2009) Germany Membership fees were the most important income source (47.1%

of all revenues), followed by public subsidies (9.7%), donations

(9.3%), fees for services (7.1%), and sponsorship (4.0%); revenues

from membership fees increased by 12% between 2004 and 2006

Taylor et al. (2009) UK Membership fees were the most important income source (29% of

all revenues), followed by bar, catering, and hospitality (25%), and

match/game/tournament fees (9%)

Scheerder et al. (2010),

Vos et al. (2011)

Flanders (Belgium) Membership fees were the most important income source (41.4%

of the total income), followed by fundraising (15.4%), sponsorship

(13.3%), and revenues from canteen (11.3%)

Lamprecht et al. (2011) Switzerland Membership fees were the most important income source (36% of

all revenues), followed by sponsorship deals (14%), and social

events (13%); revenues from membership fees increased by 7%

over the last 15 yearset al., 2005) and 28% (Lasby & Sperling, 2007) to the total income, respectively (Table 1).Previous research has shown that total revenues and income sources are not constant; instead changing over time

(Table 1). With regard to the development of total revenues, 24% of the sports and recreation organisations in Canadareported decreases in the total revenues and 30% stated increases in total revenues between 2000 and 2003 (Gumulkaet al., 2005). During the same period, 29% of the sports and recreation organisations in the province of Ontario, Canada,reported increases in revenues, 44% stated that their revenues had stayed about the same, and 28% reported decreases inrevenues (Lasby & Sperling, 2007). Regarding the development of specic income sources, the revenues frommembership fees increased by 8% over the last 15 years in sport clubs in Switzerland. This increase in revenues frommembership fees came along with a decrease in entrance fees, donations, interest, and rental revenues (Lamprecht et al.,2011). In German sport clubs, the revenues from membership fees have increased by 12% between 2004 and 2006 (Breuer& Wicker, 2009; Table 1).

The review of prior literature showed that many cross-sectional studies exist which provides evidence of the resourcecomposition of non-prot sport clubs; however, there are only a few longitudinal studies that analyse the development ofdifferent income sources. The interaction among different income sources within an income portfolio has been largelyneglected in previous research.

3. Environment for sport clubs in Germany

The development of the non-prot sector in Germany has been different from other countries such as the USA, GreatBritain, Canada, and Australia. In Germany, a corporatist non-prot sector has developed in conjunction with the state andthe relationship between the state and the non-prot sector has been characterised by cooperation and subsidiarity.Elements of decentralisation and privatisation have played a major role in the principle of subsidiarity that reinforced thelocal self-governance of non-prot (sport) organisations and provided the political and economic bedrock for the Germannonprot sector (Anheier, 2010, p. 298). The welfare policies of the 20th century contributed to the expansion of this strongpattern of cooperation between the state and the non-prot sector. Nevertheless, the state should respect the autonomy ofthe non-prot organisations (Anheier, 2010). This postulation could be supported by previous research suggesting thatgovernment funding did not have a detrimental impact on the autonomy of non-prot organisations (Horch, 1994).

P. Wicker et al. / Sport Management Review 15 (2012) 318329 321As a result of this strong relationship, changes in the German government do not lead to substantial changes in thepolicies for non-prot (sport) organisations. In Germany, the state supports elite sport, whereas the federal states andmunicipalities are responsible for community sport and for the provision of public subsidies (like in Belgium; Vos et al.,2011). Federal states do rather support competitive sport and the construction of sport facilities and municipalities providenancial support for the clubs sport programmes. However, the amount of public subsidies is not regulated by law.Therefore, subsidies can be subject to (changes in) the nancial situation of public households and vary heavily acrossmunicipalities (Voigt, 2006).

With the introduction of New Public Management the legitimacy of public subsidies has been questioned (Rittner &Breuer, 2002) and governmental pressures for sport clubs have increased. Subsidies for sport clubs are linked with conditionssuch as a certain number of children, a minimum level of membership fees, and mission statements related to the purpose ofserving the community. The latter relate to policy goals of the municipality such as health promotion, social integration,community building, promotion of solidarity, and gender equality (Breuer, 2010). If sport clubs in Germany do not full theserequirements, public subsidies are reduced or completely cut. In other countries, governmental subsidies are also built intoconditions: in Flanders (Belgium), governmental subsidies are linked with conditions regarding the qualication of staff (Voset al., 2011) and in Scotland, sport clubs need development plans to receive funding (Allison, 2001). In the province of Alberta(Canada), sport organisations have to comply with reporting requirements induced by the federal government in order toreceive public funding (Edwards, Mason, & Washington, 2009).

In the context of New Public Management, the non-prot sector has also been required to implement techniques andpractices from the for-prot sector in order to improve the quality and efciency of the delivery of public services. Oneexample is a publicprivate-partnership for the use and maintenance of sport facilities. In these partnerships, themunicipality only provides the sport facility which is then used and maintained by other institutions such as sport clubs.Similarly, even more rigorous changes took place in the UK where public services have been commercialised in the context ofNew Managerialism (Grix, 2009) and two national sport organisations (Sport England and UK Sport) have been modernised(Houlihan & Green, 2009). In the UK, Sport England and UK Sport also face governmental pressures because funding levels arelinked with specic increases in sport participation rates among the population and elite sport success, respectively(Houlihan & Green, 2009). Further governmental pressures on sport clubs in Germany arise from changes in the Germaneducational system as a result of the implementation of all-day schools. Sport clubs are required to increasingly collaboratewith schools, for example in terms of the use of public sport facilities or the recruitment of young athletes. In 2009, 27.3% ofall German sport clubs have already provided sport programmes in collaboration with schools and 11.2% of the clubs havexed this collaboration in a written contract (Breuer & Wicker, 2011).

Previous research on German sport clubs has investigated the relationship between the clubs and the state. The rstnationwide studies on sport clubs, the so-called nancial and structural analysis of sport clubs (FISAS), have shown thatrevenues from public subsidies made up approximately 10% of the total revenues of a sport club (e.g., Anders, 1991; Emrich,Pitsch, & Papathanassiou, 2001; Heinemann & Schubert, 1994). The Sport Development Reports were the follow-up studiesof the FISAS and supported the nding that public subsidies contributed approximately 10% to the overall revenues.However, a more detailed analysis of public subsidies indicated that not all sport clubs generated revenues from publicsubsidies, as for example only 62% of all clubs received subsidies from sports federations, 38% from the municipality, and 15%from the federal state (Hovemann, Horch, & Schubert, 2007). Generally speaking, sport clubs with more members were foundto be more likely to receive public subsidies (Breuer & Wicker, 2009; Heinemann & Horch, 1991). The tendencies ofdecreasing subsidies due to policy changes (New Public Management) and municipalities experiencing nancial difcultiescould be supported by the nding that 43.3% of the clubs suffered from decreased public subsidies in 2006 (Breuer & Wicker,2009).

In addition to changes in public subsidies, further issues can represent a challenge for the nancial situation of sportclubs. Many sport clubs experience decreases in memberships as a result of an increased number of substitutes for clubparticipation and demographic trends. Some decades ago, everybody who wanted to participate in sport was likely to be amember of a sport club. Nowadays, sport clubs are increasingly competing for members with commercial sport providers(tness centres), self-organised sporting arrangements, and other leisure activities that represent substitutes forparticipation in a sport club (Breuer, 2005). Furthermore, the potential membership base of sport clubs has been decreaseddue to demographic trends in Germany, i.e., the shares of older people, women, and people with a migration backgroundhave increased and fewer children have been born (Federal Institute for Population Research, 2008). This development canbe considered problematic as the importance of such population groups is increasing yet they are less likely to practice sportin a sport club. The typical member of a sport club was described as a young, German male (Nagel, 2003). These twodevelopments can lead to fewer revenues from members (e.g., membership fees, course fees); however, the costs of the sportprogrammes are not expected to decrease as some xed costs remain similar (e.g., costs for sport facilities, staff), a commonproblem of non-prot organisations (Anheier, 2010). For example, the costs of a sport course in a gym remain similar, nomatter whether 10 or 20 people participate, as the coach and the rent of the sport facility have to be paid anyway.

As a result of the abovementioned challenges, sport clubs can experience nancial problems. Previous research hasshown that one out of three German sport clubs (33.7%) could not break even in 2006 (Breuer & Wicker, 2009). However,nancial difculties are not unique to sport clubs in Germany. Sport clubs in other countries have also experienced nancialproblems (e.g., Allison, 2001; Lamprecht et al., 2011; Lasby & Sperling, 2007; Taylor et al., 2009; Taks, Renson, & Vanreusel,1999). It must be noted that for-prot organisations can also experience nancial difculties. Nevertheless, it is suggested

that the management of an income portfolio is less important to them, as they rely mainly on one income source (i.e., salesrevenues).

4. Interactions among revenue categories

The management of the income portfolio of a non-prot organisation can be challenging (Kearns, 2007). First, the amountof revenues is important as sufcient revenues must be made available. Generally speaking, the overall nancial resourcesneeded by a sport club are determined by the overall amount of money that is needed to nance the sport programmes andsocial offerings for the members (Horch, 1992; Nagel, 2008). Second, and of importance to this study, is the composition ofthe income portfolio. The literature review (Table 1) has shown that the composition of the income portfolio and theimportance of revenue categories differed among clubs in different countries. When managing the income portfolio, it has tobe taken into account that complex interactions exist among the different sources (Anheier, 2010, p. 205). Theseinteractions among income sources are referred to as crowd-out effects (and crowd-in effects, respectively; Kearns, 2007).They indicate how the providers of one income source are inuenced by the providers of other income sources (Young, 2007).

P. Wicker et al. / Sport Management Review 15 (2012) 318329322Crowd-out effects occur when increases in some revenue categories lead to reductions in other categories (Anheier,2010). For example, a sport club can seek to increase revenues from membership fees. This increasing contribution frommembers through membership fees can lead to a reduced willingness of club members to donate and consequently this sportclub could experience a decrease in donations as a result of increasing revenues from membership fees. In this case, themembership fees would have crowded out the donations. In previous research, government spending was found to crowd outdonations (Kingma, 1989; Payne, 1998; for an overview see Steinberg, 1991) as was sales revenues (Kingma, 1995).

In addition to crowd-out effects, crowd-in effects also have to be considered in the management of the income portfolio.Crowd-in effects occur, when support providers are more inclined to provide resources to organisations that alreadygenerate many resources (Kearns, 2007). For example, a sport club receives many donations and consequently a businesscompany might feel this club would make a signicant contribution to the community and would therefore be worthy ofsponsorship money. In this case, donations would have crowded in sponsorship income. In contrast to the previously notedcrowd-out effects between government spending and donations, some previous studies have also shown that governmentalsubsidies have crowded in donations (e.g., Schiff, 1985, 1990). Moreover, public capital was found to crowd in private capital(Aschauer, 1989). In voluntary sport organisations in Norway, the most commercialised organisations were found to receivethe largest share of public funds (Enjolras, 2002) supporting a crowd-in effect. It must be noted that crowd-in and crowd-outeffects can also occur within one revenue category (e.g., donations crowd in more donations); however, the focal point of thecurrent study is on interactions among revenue categories, not within categories. The review of literature on crowd-out/crowd-in effects revealed that the sport sector has been neglected in previous research with only a few exceptions (Enjolras,2002).

The composition of the income portfolio is critical for the development of uncertainties (Galaskiewicz & Bielefeld, 1998).Some income sources can be considered more uncertain than others and thus increase nancial risk. To investigate theinteractions among revenues, it is crucial to divide the income sources of sport clubs into autonomous and heteronymousdepending on their level of autonomy (Emrich et al., 2001). Autonomous revenues are characterised by the fact that the clubcan exert a certain inuence on them, i.e., the club has some control over the prices. This control should lead to reduceduncertainty. Not to misunderstand, the total amount of revenue that comes from autonomous revenues cannot be controlledby the club. In fact, the total amount of revenue cannot be fully controlled in any category, as all revenues are somewhatsubject to uncertainty. Only the level of uncertainty is different. Heteronymous revenues can be characterised by a lowerlevel of autonomy and consequently a higher level of uncertainty. The club cannot control the prices in these revenuecategories. Heteronymous revenues are likely to be inuenced by the current economic situation and government policy.One objective of the income portfolio management is to reduce uncertainty. This objective could be achieved by relying moreon autonomous than on heteronymous revenues. An overview of the seven revenue categories in the current study, theirdegree of autonomy, and the inherent income sources is provided in Table 2.

Table 2

Categorisation of revenues.

Revenue category Degree of autonomy Income sources

Sport supply Autonomous Membership fees, admission fees, service fees for members and non-members (e.g., rent),

course fees

Other supply Autonomous Self-operated restaurant, sporting events (e.g., admission fees), social events

Asset management Autonomous Asset management (e.g., interest)

Subsidies Heteronymous Public subsidies from the federal state, from the municipality, from sports confederations,

from national governing bodies, from the European Union, and other subsidies

Donations Heteronymous Donations

Economic activities Heteronymous Sponsorship revenues from endorsement deals, broadcasting rights, periphery, and printed

advertisements; business operations

Credits Heteronymous Credits

P. Wicker et al. / Sport Management Review 15 (2012) 318329 323In the current study, revenues from sport supply, other supply, and asset management represent the autonomousrevenue categories (Table 2). Revenues from sport supply come from the core product of sport clubs, i.e., the provision ofsport programmes. The members of the sport club pay admission fees, membership fees, and fees for additional services likerent for using the facilities of the club. Many sport clubs also offer services for non-members who are charged separate fees.These revenues are considered autonomous as sport clubs can individually determine the amount of the fees they charge, i.e.,the level of admission fees, membership fees, and service fees (not the overall revenues). Revenues from other supply are alsoconsidered autonomous as the club can control the prices of the inherent goods and services. They include income from self-operated restaurants where food and beverages are sold (i.e., the club can determine the prices of food and beverages), fromsporting events where entrance fees are charged (i.e., the club can determine the price of the entrance fee), and from socialevents like club parties (i.e., the club can determine the prices of all products that are sold at these events). The thirdautonomous revenue category is asset management. Clubs can generate income by putting money in a bank to earn interest.As clubs can control their bank deposits and inuence their income from interest, these revenues are also consideredautonomous (Table 2).

The four heteronymous revenue categories are subsidies, donations, revenues from economic activities, and credits(Table 2). Sport clubs can receive subsidies from different providers such as the federal state or the municipality.However, the amount of public subsidies is subject to the nancial situation of the municipality and can hardly becontrolled by the club; therefore, revenues from public subsidies go along with increased uncertainty. Moreover,subsidies are usually all-or-nothing in nature which further contributes to uncertainty. Donations can come either fromprivate households or businesses that usually offset these donations against their tax liabilities. They are consideredheteronymous revenues as clubs can hardly control the amount of donations they receive (i.e., how much moneyresource providers want to donate). Revenues from economic activities comprise income from sponsorship andendorsement deals as well as advertisement and sale of broadcasting rights for sporting events. Sponsorship revenuescan depend on the broader economic conditions which cannot be controlled by the club and are therefore consideredheteronymous revenues. Revenues from sponsorship and donations usually drop in tough economic times. In thenancial market clubs can generate cash by raising credits from nancial institutions. Although these revenues areconsidered heteronymous, it must be mentioned that the club management can nevertheless have an inuence on thegeneration of these revenues. A well managed and successful sport club should be more likely to receive donations andsponsorship income.

5. Method

5.1. Data source and collection

The interactions among revenue categories were analysed using data from the Sports Development Report 2009/2010 inGermany. The Sports Development Report is a third party research project that is nanced by the German Olympic SportsConfederation, the Federal Institute of Sports Sciences, and the 16 federal state sports confederations. Within this project,sport clubs in Germany are surveyed every two years. Up to now, there have been three waves of this project: 2005/2006,2007/2008, and 2009/2010. The project is a panel study which means that there is not only cross-sectional data available, butalso longitudinal data.

The data of the Sports Development Report were collected using an online survey. The e-mail addresses of the sport clubswere provided by the federal state sports confederations. Thus, every sport club that had a valid e-mail address at the federalstate sports confederation was invited via e-mail to take part in the survey. In the e-mail, the clubs received a personalisedlink to the online questionnaire. This personalised link implies that every club has its own online questionnaire and thus hasseveral advantages compared with a normal link. First, the questionnaire must not be completed in one go as the clubs couldlog in and log out. Second, the questionnaire could be completed by several persons; for example, the treasurer could ll inthe nancial data and the president could answer general questions about the club. In most cases the questionnaire wascompleted by a voluntary board member.

In the online survey, the sport clubs were asked for their situation regarding the structure of members, offered sportsprogrammes, use of public and own sport facilities, volunteers, paid staff, clubs philosophy, general problems, need ofsupport, and nances (including expenses and revenues). It must be noted that the gures on the number of members andthe nances (clubs expenses and revenues) referred to the year before the survey in each wave. This means that the nancialdata from 2007 referred to the year 2006 and the data from 2009 to the year 2008. The data on the clubs revenues wererelevant to this study. The income sources that were asked for in the questionnaire are summarised in the third column ofTable 2. The remaining revenue category other revenues was excluded from the analysis as it could not be attributed to eitherautonomous or heteronymous revenues.

In the second wave in 2007, 44,367 (out of the existing 90,467 sport clubs in Germany) were delivered to the project teamfrom the federal state sports confederations and these sport clubs were invited to take part in the survey. The online surveywas carried out from October to December 2007 and n = 13,068 sport clubs participated in the survey (response rate: 35.1%).For the third wave in 2009, 63,468 sport clubs were invited to participate in the survey as these clubs had a correct e-mailaddress at their federal state sports confederation. The survey took place from October to December 2009 and n = 19,345sport clubs participated in it (response rate: 33.3%).

P. Wicker et al. / Sport Management Review 15 (2012) 3183293245.2. Longitudinal data and sample characteristics

From these two cross-sectional samples in 2007 (n = 13,068) and 2009 (n = 19,345) a longitudinal dataset was created.This dataset contained all clubs that participated in both waves. The two datasets were matched using an unchangeable clubnumber (id) as key variable. This id was given to the sport clubs before the survey and every club had the same id in everywave of the project. After the datasets were matched, it could be seen that n = 5026 sport clubs participated in both wavesand therefore represent the longitudinal dataset 20072009 which is relevant to this study.

The clubs of this longitudinal sample were founded in 1950 on average with 37.2% of the clubs being founded before/in1945, 34.6% between 1946 and 1980, and 28.2% after 1980. The clubs in the sample had on average 443.9 members in 2006and 442.3 in 2008 (the change in members was not signicant: t = .291, p = .771). Most of the clubs had up to 300 members(2006: 60.1%; 2008: 61.7%), more than one fth between 301 and 800 members (2006: 23.9%; 2008: 22.2%), 12.6% between801 and 2000 members in both years, and approximately 3% had over 2000 members (2006: 3.5%; 2008: 3.4%). The clubsoffered 5.0 sports on average in both years with 61.0% of the clubs being multi-sport clubs in 2007 and 53.2% in 2009.

5.3. Data analysis

The data analysis was two-fold. First, descriptive statistics about the revenues in every category, the total revenues, andthe total expenditure were carried out to provide an overview of the nancial situation of the clubs in 2006 and 2008. Percapita values were presented due to the differences in club size in terms of the number of members. They were calculated bydividing the revenues/expenditure by the total number of members in the club. To provide information about thedevelopment of revenues and expenditure, the percentage change between 2006 and 2008 was displayed. It was alsochecked whether the percentage changes were statistically signicant using paired t-tests. An a-level of .1 was used for allstatistical tests.

In a second step, elasticity measures were used to estimate the interactions among revenue categories (Young, 2007). Thiseconomic tool has rarely been applied in the non-prot sport sector with a few exceptions (Gratton & Taylor, 1995; Wicker,2009). Elasticity is a sensitivity measure from micro-economics that represents the percentage change in a dependentvariable (DV) as a result of a percentage change in an independent variable (IV; Hardes, Schmitz, & Uhly, 2002). By denition,an elasticity value can be obtained by dividing the percentage change in the DV by the percentage change in the IV. In thecurrent study, revenue elasticities were estimated within a regression framework to obtain the marginal effects. Theelasticity values provide information about how much the revenues in one category have changed (DV) depending on thechanges in revenues in another category (IV). For example, the elasticity between subsidies (IV) and sport supply (DV)indicates the percentage change in revenues from sport supply between 2006 and 2008 as a result of the percentage changein revenues from subsidies during the same period. All revenue categories except asset management were used as IVs. It isassumed that assets would only be liquidated when there was a need for it and thus asset management was alwayspresumed to be a DV.

Elasticity values can range between 1 and +1. Some thresholds must be considered for their interpretation. Anelasticity of 1 is labelled unit elastic, i.e., a decrease (increase) by 1% in one revenue category corresponds to an increase(decrease) in another category of exactly 1%. Elasticity values between 1 and +1 are referred to as inelastic, i.e., thepercentage change in the DV is smaller than the percentage change in the IV (disproportionate change). An exception is anelasticity of zero (e = 0; zero elastic) where a change in one revenue category would have no effect on the other revenuecategory. Elasticity measures smaller than 1 or larger than +1 are said to be elastic, i.e., the percentage change in the DV ishigher than the percentage change in the IV (over proportional change). For the interpretation of the elasticity values, thesign is also important as it indicates if the two revenue categories move in the same direction (positive sign) or in oppositedirections (negative sign).

6. Results

Table 3 gives an overview of the revenues and expenditure of German sport clubs in 2006 and 2008. In both years,revenues from sport supply were the most important revenue category, followed by revenues from other supply, donations,and subsidies. The average per capita revenues from sport supply, other supply, and economic activities have signicantlyincreased from 2006 to 2008. The increases in revenues from subsidies and donations were not signicant. Revenues fromasset management and credits have decreased during the same period; however, the changes were not statisticallysignicant. It must be noted that there might still be clubs with decreasing revenues in some categories, although most of themean values have increased between 2006 and 2008. The signicant increase in total revenues by 10.5% was accompanied byan increase in total expenditure by 9.8%. Only 71.7% of the clubs could break even in 2008 despite signicant increases intotal revenues.

An overview of the revenue elasticity measures is provided in Table 4. The elasticities revealed that revenues in somecategories signicantly interacted with revenues in other categories. Autonomous revenues from sport supply (DV; ColumnA) were found to interact only with revenues from donations; a signicant positive interaction was found (e = .044). Thispositive interaction was conrmed by the elasticity in Column E (e = .186). With regard to autonomous revenues from othersupply, a signicant negative interaction was found with revenues from economic activities (e = .150; Column B). The

P. Wicker et al. / Sport Management Review 15 (2012) 318329 325Table 3

Development of revenues and expenditure from 2006 to 2008.

2006 2008 Change from 2006 to 2008 (in %)

Per capita values (mean in s)Sport supply 71.67 82.43 +15.0***

Other supply 14.64 17.95 +22.6***

Asset management 2.21 2.10 5.0Subsidies 12.23 13.98 +14.3

Donations 12.53 17.14 +36.8

Economic activities 4.57 6.37 +39.4**

Credits 2.90 1.16 60.0Other revenues 17.33 11.39 34.3***Total revenues 138.08 152.52 +10.5***

Total expenditure 132.64 145.63 +9.8**

Proportion of clubs which could at least break even (in %) 63.6 71.7 +12.7***

*** p < .01.** p < .05.

Table 4

Summary of elasticity values.

Column A Column B Column C Column D Column E Column F Column G

Sport supply Other supply Asset management Subsidies Donations Economic activities Credits

Autonomous

Sport supply .036 .107 .055 .186** .009 .001Other supply .007 .042 .002 .012 .105*** .031*Asset management elasticity covering the impact of changes in revenues from other supply on revenues from economic activities (e = .105;Column F) conrmed the negative interaction. In addition, a negative interaction was evident between revenues from othersupply and credits (e = .031; Column G). The negative interaction was conrmed by the elasticity in Column B (e = .166).Autonomous revenues from asset management were found to be determined by changes in revenues from donations andeconomic activities (Column C). Signicant positive interactions were found between revenues from donations and assetmanagement (e = .111) as well as between economic activities and asset management (e = .127).

Heteronymous revenues from subsidies were found to interact signicantly with revenues from donations and economicactivities (Columns DF of Table 4). Positive interactions were evident between revenues from subsidies and donations(e = .164; Column E). This signicant positive interaction was conrmed by the elasticity value in Column D (e = .133).Another signicant and positive interaction could be found between revenues from subsidies and economic activities(e = .067; Column F). The positive interaction was conrmed by the elasticity value in Column D (e = .061; Table 4).

7. Discussion

The composition of the income portfolio of non-prot sport clubs in Germany showed that clubs did not depend on onesingle revenue source. In fact, they have multiple revenues at hand and can therefore be considered relatively independent intheir decision making (Horch, 1992). However, sport clubs have to keep their mission in mind, which is to serve theirmembers and are therefore bound in their decision making in this respect (Nagel, 2008; Thiel & Mayer, 2009). The per capitavalues of different revenue categories demonstrated that autonomous revenues from sport supply including revenues frommembership fees were the most important revenue source of sport clubs. This nding is in accordance with prior literatureon the revenues of non-prot sport clubs in Europe (e.g., Lamprecht et al., 2011; Scheerder et al., 2010; Taylor et al., 2009).Revenues from public subsidies were the fourth highest revenue category supporting the previously noted cooperationbetween the state and the non-prot sector and the principle of subsidiarity (see Section 3).

The development of revenues from 2006 to 2008 indicated that on average, sport clubs have increased both autonomousand heteronymous revenue categories (except for revenues from credits and asset management). It seemed that clubs couldpay back credits and managed to be more nancially healthy, an assumption that could be supported by the signicant

Heteronymous

Subsidies .016 .003 .072 .164*** .067* .025Donations .044** .015 .111*** .133*** .030 .011

Economic activities .003 .150*** .127*** .061* .033 .028Credits .001 .166* .008 .084 .045 .103

*** p < .01.** p < .05.* p < .1.

P. Wicker et al. / Sport Management Review 15 (2012) 318329326increase in the proportion of clubs which could at least break even. Although the increase in total revenues between 2006and 2008 might be considered positive at rst glance, it has to be mentioned that the total expenditure has also increasedsignicantly during the same period. Therefore, sport clubs had to increase their total revenues to at least break even.However, the ndings also showed that despite the positive development of revenues, 28.3% of the sport clubs in Germanycould not break even in 2008. A similar proportion of clubs has been reported in the UK (28%; Taylor et al., 2009). The meanvalues might also hide that some clubs suffered from decreased revenues in some categories as not all increases in revenueswere statistically signicant.

A comparison of the development of revenues between autonomous and heteronymous revenue categories revealed thatthe percentage increases were higher for some heteronymous revenue categories (donations and economic activities). In linewith the previous classication of revenues this means that German sport clubs have increased their uncertainties(Galaskiewicz & Bielefeld, 1998). Although more sport clubs seemed to be nancially healthy in 2008 (i.e., they could breakeven), it appeared that the sport clubs have increased their nancial risk. They became more dependent on heteronymousrevenue sources where they have less control. Consequently, they experienced an increase in risk which could be consideredproblematic because it made the clubs more nancially vulnerable and dependent on external resource providers.

The results provided evidence on the interactions among different revenue categories of non-prot sport clubs. Asignicant positive interaction was found between revenues from donations and sport supply. Given the development ofdonations between 2006 and 2008 (increase; Table 3) this nding pointed towards a partial crowd-in effect, i.e., donationscould have crowded in revenues from sport supply. It can be suggested that club members would be more willing to paymembership fees and service fees when they feel they were not the sole support provider. They could be more likely to payfees when they see that the club management makes efforts to also increase other revenue sources. However, it is also likelythat donators might be more willing to provide charitable contributions if the club appears to be strong enough to generaterevenues from its core product, the sport supply. In this case, revenues from sport supply could have crowded in donations.

The signicant negative interaction between revenues from economic activities and other supply (Table 4) and thedevelopment of revenues (Table 3) pointed towards a partial crowd-out effect, i.e., increased revenues from economicactivities could have crowded out revenues from other supply. It is suggested that the club management might haveincreased the revenues from economic activities for example through attracting potential sponsors to the club. As the clubmanagement has some control over the prices of items related to other supply such as the club restaurant, sport events andsocial events (autonomous revenues), it seemed likely that the club management decided to decrease the prices andtherefore provide a nancial benet for the club members. Consequently, the club management might have adjusted theprices of for example food and beverages at the club restaurant or entrance fees for sport events. Nevertheless, the revenuesfrom other supply have increased between 2006 and 2008.

The negative interaction between revenues from other supply and credits pointed towards a partial crowd-out effect.According to the positive development of revenues from other supply between 2006 and 2008, it is suggested that increasedrevenues from other supply could have crowded out revenues from credits. It seemed that sport clubs have used increasedrevenues from other supply to pay back credits. Sport clubs can increase their revenues from other supply for example byorganising a social or sporting event. In doing so, they are able to generate revenues on short notice without the need to raisemembership fees. The inverse relationship (revenues from credits have crowded out revenues from other supply) seemedrather unlikely as revenues from other supply have increased between 2006 and 2008 and revenues from credits decreased.Moreover, it is suggested that sport clubs try to pay back their credits to reduce their uncertainties and nancial risk.

Signicant positive interactions were reported for revenues from donations and asset management as well as forrevenues from economic activities and asset management. Given the increase in revenues from donations and economicactivities between 2006 and 2008, partial crowd-in effects seemed likely, i.e., increased revenues from donations andeconomic activities could have crowded in revenues from asset management. This would mean that sport clubs have bankedmoney and could thus generate more revenues from interests. The average decrease in revenues from asset managementseems to contradict this development. However, the decrease is not statistically signicant and it could be suggested thatrevenues would have decreased even more without the evident crowd-in effects.

Signicant positive interactions were found between revenues from subsidies and donations as well as between revenuesfrom subsides and economic activities. According to the development of these three revenue categories (increase from 2006 to2008; Table 3), partial crowd-in effects seemed likely, i.e., increased revenues from subsidies could have crowded in revenuesfrom donations and economic activities. These crowd-in effects could be supported by previous research where public capitalcrowded in private capital (Aschauer, 1989) and government spending crowded in donations (Schiff, 1985, 1990). They can alsobe supported by a study on voluntary sport organisations in Norway where commercial resources crowded in public funds(Enjolras, 2002). However, the majority of studies documented that sales revenues and government spending would crowd outdonations (e.g., Kingma, 1995; for an overview see Steinberg, 1991). Possible explanations of these ndings can relate to the clubmanagement, the specic situation in sport, and the perceived legitimacy by the clubs publics.

The club management could have increased these three heteronymous revenues by stepping up in its efforts to apply forsubsidies, acquire new sponsors, and convince potential donators. Due to the previously mentioned nancial difculties ofmany municipalities and the principle of subsidiarity (see Section 3), subsidies have to be requested at the competentauthorities and clubs have to apply for them in a bureaucratic way. With regard to the attraction of revenues from donationsand economic activities, it might be especially promising for clubs to use the networks of their members. Members can haveinuential positions in the companies they work for and thus can try to use their position to inuence their companies to

P. Wicker et al. / Sport Management Review 15 (2012) 318329 327become sponsors of their respective sport clubs. The sporting context might serve as an appreciated platform as sport evokeshigh levels of identication and emotional attachment (Mullin, Hardy, & Sutton, 2007). These positive effects could betransferred to the products of the sponsor through sponsorship deals. Moreover, business rms are increasingly willing toshow corporate social responsibility (Shilbury, Westerbeek, Quick, & Funk, 2009), a development which should make iteasier for community sport clubs to benet from charitable contributions. In this context, the perceived legitimacy of thesport club might be important (Chang & Tuckman, 1994). Clubs that already receive public subsidies might be consideredworthy to receive additional funds from other resource providers (e.g., sponsors, donators).

This study has some limitations. First, elasticity measures are relative measures; they only provide information aboutpercentage changes and not about total values. Second, the analysis is restricted to a period of two years; therefore, only shortterm elasticities could be estimated. The interactions among revenue categories might be different in the long term as the clubscould act more strategically. However, as highlighted in the literature review (see Section 2), longitudinal datasets were quitescarce in sport club research as most studies were based on cross-sectional data. Only a few studies could really measuredevelopments using longitudinal data. Therefore, this dataset could be considered unique in terms of sample size and type(longitudinal) and its usage contributed to the understanding of the development of and the interactions among revenuecategories. Third, the dataset did not cover the period after the nancial crisis in 2008, unfortunately. In the fourth wave of theSports Development Report, data from the household year 2010 will be collected which will enable an analysis of the impact ofthe economic crisis on the nancial situation of sport clubs (however, the data were not yet collected at the time of the paper).

The results of the study can be related to sport policy as sport clubs are the organisations to implement sport policies suchas Sport for All. The ndings provided evidence that the price for implementing these policies became more expensivebecause the expenditure of sport clubs has signicantly increased from 2006 to 2008. As sport clubs have to nance the costsof their sport programmes and are required to break even (Young, 2007), it seemed that they have increased revenues inspecic categories. Relatively high percentage increases in revenues could be identied for revenues from economicactivities (39.4%) and revenues from other supply (22.6%; Table 3). These revenues related to commercial activities of theclub where the club generated revenues from activities within the club (other supply) or revenues from external resourceproviders (e.g., sponsors; economic activities). They provided support for an increased level of commercialisation amongGerman sport clubs, a nding that is similar to sport clubs in Norway (Enjolras, 2002). From a policy perspective, theseincreases in commercial revenues could point towards an effect of New Public Management and modernisation of Germansport clubs which seemed to have adopted more practices from for-prot rms. As previously mentioned two national sportorganisations in the UK, Sport England and UK Sport, have been subject to modernisation and were transformed into morebusiness-oriented organisations (Houlihan & Green, 2009). However, for the German sport clubs it remained unclearwhether this potential modernisation has been linked with an improvement in services as this was the case in the UK. Theincrease in commercial revenues could also be related to the social enterprise movement, which is characterised by thetendency that clubs look to venture [commercial] income as a way of bolstering their shaky nances (Young, 2007, p. 13).Although this strategy might be helpful to improve the nancial situation in the short term, organisations are likely toincrease their nancial risk and move away from their non-prot character. In the UK, the price paid for the modernisation ofnational sport organisations was a democratic decit (Houlihan & Green, 2009). For the mentioned reasons this movementhas to be regarded sceptically.

The evaluation of the evident interactions among revenue categories might differ among policy makers of differentpolitical directions and ofces (sport policy vs. treasurer). Based on the ndings of the current study, it could berecommended that policy makers provide public subsidies for sport clubs as subsidies were found to crowd in furtherrevenues. It is suggested that particularly sport policy makers would be likely to support this recommendation as they wantto provide nancial support for sport clubs which implement Sport for All policies. They would nd it troubling if nancialsupport for sport clubs was reduced. In contrast, it can be assumed that neo-liberal policy makers and treasurers might beless worried about the interactions among revenues and the development of revenues. They might appreciate the fact thatsport clubs have an income portfolio and seem to be nancially viable organisations, even when the total expenditureincreases. A labour government might also appreciate the increased commercialisation and modernisation of sport clubs,whereas conservatives would consider them rather troubling.

The ndings have implications for the management of sport clubs. The elasticity measures indicated that sport clubswould be nancially viable as they managed to balance the increases and decreases in revenue categories. For this balance, itis important that the club has revenues in several categories. Therefore, it can be recommended that sport clubs diversifytheir revenues and have an income portfolio. This suggestion is in accordance with previous research (e.g., Carroll & Stater,2008; Fischer et al., 2010; Lasby & Sperling, 2007). Revenue diversication is important because previous research has shownthat it was positively correlated with nancial health (Chang & Tuckman, 1994). Moreover, previous studies have shown thatorganisations with greater revenue diversication were less likely to cut programmes and services (e.g., Greenlee & Trussel,2000). However, the club management also has to nd a balance between autonomous and heteronymous revenue sourcesas they go along with different levels of uncertainty and nancial risk.

8. Conclusion

This study provided evidence about the interactions among different revenue sources using longitudinal data (20072009) from a survey of non-prot sport clubs in Germany. Elasticity measures were calculated within a multiple regression

P. Wicker et al. / Sport Management Review 15 (2012) 318329328framework that gave information about the nature and the signicance of the interaction. The results showed that signicantinteractions existed among revenue sources which could be related to crowd-out and crowd-in effects. For example,donations were found to crowd in revenues from sport supply and revenues from subsidies crowded in revenues fromdonations and economic activities. On the contrary, revenues from economic activities were found to crowd out revenuesfrom other supply.

As this study was among the rst to analyse crowd-in and crowd-out effects in a sporting context, future research isneeded to clarify the interactions. Further research should focus on the use of longitudinal samples and samples of a longerperiod of time which would allow analysing crowd-in and crowd-out effects over several years (i.e., in the long term).Moreover, international comparisons would give fruitful insights into the development of revenues as the importance ofdifferent revenues sources was found to differ among sport clubs in different countries.

Acknowledgment

The authors would like to thank Miss Jess Coleman for carefully proofreading the manuscript.

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Understanding the interactions among revenue categories using elasticity measures-Evidence from a longitudinal sample of non-profit sport clubs in GermanyIntroductionRevenues of non-profit (sport) organisationsEnvironment for sport clubs in GermanyInteractions among revenue categoriesMethodData source and collectionLongitudinal data and sample characteristicsData analysis

ResultsDiscussionConclusionAcknowledgmentReferences