Organizational capacity building in non-profit sport clubs: exploring the role of competition as a capacity building stimulus

ABSTRACT

Research question

Non-profit sport clubs are operating in an increasingly competitive market due to the growth of the for-profit sport sector and changes in sport participation patterns. To counteract competition, clubs are expected to take strategic action by investing in their organizational capacities. The aim of the present study is to explore if and how perceived competition from other organizations acts as an external capacity building stimulus for non-profit sport clubs.

Research methods

Longitudinal data were drawn from a nationwide online survey of non-profit sport clubs in Germany between the years 2011 and 2020 (ranging between n = 1366 and n = 5315 observations).

Results and findings

The results highlight that clubs faced with competition from commercial providers are driven to invest in paid staff, whereas the number of volunteers’ decreases and clubs are less likely to break even. Clubs faced with competition from other clubs are less likely to report having a strategic concept. The possession of club-owned facilities and gyms remains unaffected.

Implications

The findings reveal the limited effects of competition on the development of organizational capacities, with significant effects occurring only in the human resource capacity as a driver of professionalization. Implications for theory and practice are discussed.

KEYWORDS:

• Strategic management
• competitiveness
• organizational change
• quantitative research

Introduction

In many countries, non-profit sport clubs play a major role in providing sport programs for the general population (Breuer et al., 2015; Doherty & Cuskelly, 2020; Harris et al., 2009). However, non-profit sport clubs are operating in an increasingly competitive market. On the one hand, sport participation patterns have diversified, and non-organized sport practices have become more popular among the general population (Borgers et al., 2015; Harris et al., 2017). On the other hand, private sport entities have entered the market which has traditionally been served by non-profit sport clubs (Laine & Vehmas, 2017). Especially, the latter has blurred the lines between the formerly distinct sectors of private, commercial sport provision, and non-profit sport. The phenomenon of sector blurring is thus apparent in the sport market (Dees & Anderson, 2003; Misener & Misener, 2017) and non-profit sport clubs need to consider the logic of all three sectors: non-profit, for-profit, and public (Szerovay, 2022).

The emergence of market competition in a traditionally non-profit-dominated market can have differing effects. For one, competition from other organizations can lead to a diffusion of management practices and organizational setups as a signal of good practices (Leiter, 2013). In light of institutional theory, this would mean that organizations become increasingly alike as competition serves as an isomorphic condition, meaning competition serves as a force to sort out ineffective organizational structures which in turn leads organizations to adopt similar, effective structures and practices (Beckert, 2010). In contrast, non-profit organizations can also take strategic action and differentiate to counteract competition (Barman, 2002). In the sport context, previous research has shown that sport organizations are less affected by their environment in terms of isomorphic conditions whereas strategic actions play a bigger role (Cunningham & Ashley, 2001).

One potential strategic action that clubs can take is to invest in their resources to sustain their competitive advantage or strengthen their strategic position (Barney, 1991). In the sport context, this resource-based view has often been transferred to the organizational capacity perspective (e.g. Elmose-Østerlund et al., 2021). Previous literature has started looking into the process of how organizational capacity is built within non-profit sport organizations (Elmose-Østerlund et al., 2021; Hanlon et al., 2022; Millar & Doherty, 2016, 2018, 2021). However, no research has yet investigated the role of competition from other actors within the market (i.e. other non-profit sport clubs or commercial sport providers) as a stimulus for capacity building.

The aim of the present study is thus to address this research gap by exploring the role of competition as a capacity building stimulus. This approach is especially relevant as first, Millar and Doherty (2016) stated: ‘The nature and relative importance of particular internal and/or external forces requires empirical investigation that may inform understanding of the stimulus to capacity building’ (Millar & Doherty, 2016, p. 372). Our findings provide empirical evidence on the role of competition as an external stimulus. Second, current research has identified the role of competition in the strategic management process of non-profit sport organizations using qualitative methods (Morrison & Misener, 2021). By using a quantitative approach based on longitudinal data from a nationwide survey of non-profit sport clubs in Germany and by focusing on the role of competition in the development of organizational capacities, we extend the body of research both in the strategic management literature and in the organizational capacity literature. Lastly, our findings have practical implications for sport managers as they highlight which strategic actions non-profit sport clubs have taken in reaction to competition and which options have been mostly neglected, respectively which potential pitfalls need to be considered.

The paper starts with an overview of the literature on strategic management and capacity building in the non-profit sport context, followed by an introduction of the theoretical framework based on the model of organizational capacity building by Millar and Doherty (2016). Next, the empirical results of the study are presented and discussed in the light of theory and previous findings. The study concludes with theoretical and managerial implications as well as limitations and an outlook for future research.

Literature review

Strategic management in the non-profit (sport) sector

Strategic management refers to ‘the major intended and emergent initiatives taken by general managers on behalf of owners, involving utilization of resources, to enhance the performance of firms in their external environments’ (Nag et al., 2007, p. 944). Research on strategic management in the general non-profit context has evolved from a focus on strategy formulation and implementation in non-profit organizations (Stone et al., 1999) to a diversification of strategies pursued (Laurett & Ferreira, 2018). In the context of non-profit sports, research on strategic management has focused on the one hand on internal factors in the strategic management process, such as the role of the board (Ferkins et al., 2005; Ferkins & Shilbury, 2010; Morrison & Misener, 2022a), organizational structures (Amis et al., 2004), and dynamic capabilities (Gerke et al., 2022). In their early work, Thibault et al. (1993) developed a framework for studying strategic management in non-profit sports based on the two dimensions of program attractiveness and competitive positions. The latter referred to equipment costs and affiliation fees (Thibault et al., 1993). The empirical verification has confirmed the applicability of the model in national-level sport organizations (Thibault et al., 1994). Recent studies have stressed the importance of the environment in the strategic management process. To develop strategic capabilities in non-profit sport organizations, it is imperative to collaborate with the environment as inter-organizational relationships have been found to increase strategic capabilities (Ferkins & Shilbury, 2010). The importance of external relationships has also been found to play an important role in innovation processes in the context of sport for development and peace organizations (Svensson & Hambrick, 2019). In the context of Canadian non-profit sport clubs, Morrison and Misener (2021) showed that external factors including competition from other local actors influence the strategic management process of non-profit sport clubs. Inter-club competition was identified as an isomorphic condition, meaning a force leading clubs to become increasingly alike, as clubs in competition reported feeling pressured to adapt. This has been supported by further qualitative findings that leaders of community sport organizations consider their organization’s readiness for growth and environmental dynamism in the strategy formulation process (Morrison & Misener, 2022b).

Which type of strategy non-profit sport clubs choose can differ. Examples of strategies that have been investigated in sport include diversification to distinguish the club from commercial sport providers (Zimmer et al., 2018) and membership growth strategies (Morrison & Misener, 2022b). In terms of business strategies based on Porter’s generic strategies, Wicker et al. (2015) highlighted that those strategies have differing effects on the organizational problems of non-profit sport clubs. While focus and cost leadership have been found to decrease organizational problems of non-profit sport clubs, differentiation can have differing effects. Thus, strategies can be used to address organizational problems, which in turn require non-profit sport organizations to take strategic action, for example in the form of capacity building.

Capacity building as a strategic action

Current research has investigated the process of organizational capacity building both in the general non-profit sector (e.g. Andersson et al., 2016; Cairns et al., 2005; Kapucu et al., 2011) and in the non-profit sport context (Millar & Doherty, 2016, 2018) as well as the sport for development context (Wegner et al., 2022). It has been shown that capacity building is impacted by the readiness to build capacity (Casey et al., 2012; Millar & Doherty, 2021) as well as leadership, congruence, technical support, and partnerships (Joffres et al., 2004). The initiation of the building process is the perception of a stimulus. This stimulus can occur internally (e.g. a decline in membership) or externally in the form of competition and market demand (Millar & Doherty, 2021) or funding trends (Kapucu et al., 2011).

Research on the role of stimuli to build capacity has so far been scarce. In the general non-profit context, previous studies have mostly looked into the effects of specific capacity building initiatives as part of foundations’ funding programs (Faulk & Stewart, 2017; Kapucu et al., 2011; Minzner et al., 2014). The results revealed an increase in financial assets (Faulk & Stewart, 2017), organizational knowledge (Kapucu et al., 2011), and organizational capacity overall (Minzner et al., 2014). In an early study in the sport context, Casey et al. (2009) investigated the effect of a state-wide health promotion program for sport organizations on the implementation of health promotion programs. The results indicated that external funding and workforce development strategies helped sport organizations to focus on health promotion and increase staffing capacity. Similar results have been found in the Danish context, where long-term effects of a capacity-building program have occurred especially in the human resource dimension (i.e. volunteer motivation, work attitude) (Elmose-Østerlund et al., 2021).

Apart from explicit capacity building programs, the introduction of sport policy can play a role as an external capacity building stimulus. Hanlon et al. (2022) uncovered that in response to the Australian governmental policy to increase female participation in physical activity and sport, moderate levels of capacity existed in sport organizations. While building strategies were undertaken, these did not align with the identified capacity needs. Lastly, the role of sport mega-events has been explored (Girginov et al., 2017). In the example of the Olympic Games in London 2012 and Sotchi 2014, Girginov et al. (2017) showed that sport clubs used the events to enhance their organizational capacity in the areas of staff qualifications, organizational learning, and performance management.

Research gap

Overall, the literature on strategic management and organizational capacity in both the general non-profit context and non-profit sports is still growing. Current research has turned its eye on the role of capacity building as a strategic action for sport clubs. However, the role of internal and external stimuli in the capacity building process and their effects on capacity outcomes is still under-researched. Only a few external stimuli have been addressed in sport and only in a few selected contexts (e.g. in Australia: Casey et al., 2009; Hanlon et al., 2022; in Canada: Millar & Doherty, 2018; in Denmark: Elmose-Østerlund et al., 2021; in UK and Russia: Girginov et al., 2017). In contrast, strategic management literature has identified the importance of environmental factors including competition from other actors in the strategic planning process. These findings are however often based on qualitative research in the Canadian context (e.g. Morrison & Misener, 2021, 2022b), thus are not generalizable to non-profit sport overall. The present study, therefore, aims to connect both research streams by looking into the role of competition as an external capacity building stimulus and by utilizing a large dataset of sport clubs from another country (Germany).

Theoretical framework

To model how competition can act as a capacity building stimulus, we draw from the organizational capacity framework (Hall et al., 2003) and more explicitly, the organizational capacity building model introduced by Millar and Doherty (2016).

The concept of organizational capacity has been applied frequently in the context of non-profit sport clubs (e.g. Balduck et al., 2015; Doherty et al., 2014; Feiler & Breuer, 2021; Misener & Doherty, 2009; Wicker & Breuer, 2011, 2013, 2014). Capacities can be defined as ‘a set of attributes that help or enable an organization to fulfill its mission’ (Eisinger, 2002, p. 117). Based on the model by Hall et al. (2003), organizational capacities can be distinguished in the dimensions of human resource capacity, financial capacity, and structural capacity. The latter is further split up into infrastructure and process capacity, planning and development capacity, and relationship and network capacity. Previous research in the non-profit sport context has shown, that sport clubs’ organizational capacities are among others related to the level of organizational problems (Wicker & Breuer, 2011), inter-organizational relationships (Misener & Doherty, 2013; Wicker et al., 2013), and organizational performance (Doherty & Cuskelly, 2020).

The human resource capacity is the most critical in non-profit sport clubs (Doherty & Cuskelly, 2020; Misener & Doherty, 2009) and relates mostly to volunteers and their engagement in the clubs (Doherty et al., 2014). Paid staff play only a minor role in the administration of clubs and as paid coaches (Wicker & Breuer, 2011). The financial capacity refers to the revenue and expenditure of sport clubs (Doherty et al., 2014). Most of the revenue in non-profit sport clubs is usually derived from membership fees, whereas expenditures relate among others to expenditures for coaches and volunteers, registration fees to local and provincial state sport organizations, and costs for facility management (Misener & Doherty, 2009). The infrastructure and process capacity mostly refers to the facilities that sport clubs use to offer their programs, whereas the planning and development capacity relates to the level of strategic planning that clubs employ (Doherty et al., 2014). Lastly, the relationship and network capacity considers the inter-organizational relationships that clubs enter, for example with other sport clubs, the community, or other actors in the sport market (Wicker & Breuer, 2011).

While previous research investigated the extent of these capacities in non-profit sport clubs, recent studies have started looking into the process of how capacity within sport clubs is built. Capacity building refers to the process of ‘introducing planned changes within an organization in response to new or changing situations in an organization’s environment’ (Hanlon et al., 2022, p. 3). Millar and Doherty (2016) introduced a process model of capacity building, which integrated five key concepts identified in previous literature in one model and framed it from an organizational change and strategic management perspective. The first concept in this model is the capacity building stimulus. The stimulus refers to a force in the external or internal environment of the organization, which prompts a response. These forces can present an opportunity or threat to the organization. Millar and Doherty (2016) point out that organizations will be more likely to react to forces that have a direct effect on their programs and services, whereas lateral forces will be less likely to prompt a response. Once the force has been detected and a response has been prompted, organizations carry on by assessing their organizational capacity needs, meaning the deficits that hinder clubs from reacting effectively to the stimulus right away. If an organization concludes that the capacities it possesses are sufficient, then the capacity building process will not take place. This would be the case if an organization would possess sufficient resources to introduce new programs or initiatives to react to an external force, for example in form of competition. If deficits in organizational capacities are detected, then organizations are expected to address this need by building capacity. Once the capacity building process is initiated, it depends on the organization’s readiness for capacity building, meaning the challenges and opportunities faced by the organization in achieving its desired outcome.

In the model of Millar and Doherty (2016), readiness for capacity building is a multidimensional concept relating to organizational readiness, congruence, capacity to build, and capacity to sustain. Moreover, this step includes the assessment of alternative strategies. Organizations come up with a variety of strategies to address their capacity needs. However, it is expected that that strategy is chosen that addresses the organizational need most adequately and is feasible for the organization based on its readiness to build capacity. Once the chosen strategy is implemented, it leads to capacity building outcomes. The outcomes, as explained before, are dependent on the readiness of the organization to build capacity. Outcomes can occur both short-term as a direct increase in capacity and thus as an objective achieved, and long-term as sustained growth in capacity. Lastly, the capacity growth is expected to reach the organization’s program and service delivery as these are affected by the stimulus. For example, an increase in financial capacity through a new funding program might enable a sport club to initiate a new sport program and hire new coaches. This change in program and service delivery might thus present a new stimulus for capacity building and start the process over again (Millar & Doherty, 2016).

The focus of the present study is on the role of competition in the capacity building process, more specifically as an external capacity building stimulus. From a strategic management perspective, competition refers to the economic structure of an industry which consists of organizations offering products that can substitute for each other (Porter, 1980). In the context of non-profit sport clubs, competition can occur as other organizations such as other sport clubs in the community or commercial sport providers offer alternative opportunities for sport participation. Competition can thus present a threat for sport clubs as (1) they might face declining membership figures as individuals choose to practice sport elsewhere and (2) they compete for similar resources (e.g. coaches, facilities, external funding) as their competitors. In light of the organizational capacity building model, this competitive threat serves as an external stimulus for capacity building as non-profit sport clubs invest in their resources to maintain a competitive advantage (Millar & Doherty, 2016). However, it is unclear if competition does lead clubs to build capacity and if so, which capacities are built.

First, to react to competition as a capacity building stimulus clubs need to be aware of their competitive situation. As previous research has shown, the level of perceived competition (focused on competition from commercial sport providers) is relatively low in non-profit sport clubs (Rossi et al., 2020). Second, clubs might not identify a need for capacity building based on their competitive situation as they possess sufficient and adequate resources to counteract competition (Millar & Doherty, 2016). These factors might limit the role of competition as a capacity building stimulus. To explore this matter, we pose the following research question:

RQ: How does perceived competition from other organizations act as a stimulus for organizational capacity building?

Methodology

Database

To answer the research question, a quantitative approach was chosen by estimating eight models on organizational capacity outcomes. Data were derived from the Sport Development Report (SDR), a large-scale, nationwide online survey of non-profit sport clubs in Germany. The SDR has been conducted since 2005 and in a two-year cycle monitors sport clubs’ situations and challenges. The project is jointly funded by the Federal Institute of Sport Science, the German Olympic Sport Association, and the 16 State Sport Confederations.

The present study used a longitudinal dataset derived from the 4th wave (2011/2012), the 5th wave (2013/2014), the 6th wave (2015/2016), the 7th wave (2017/2018), and the 8th wave (2020–2022). Data were collected through an online survey in each survey wave. Clubs were contacted via email and invited to take part in the online survey. Email addresses were provided by the State Sport Confederations. Data collection took part in three-month time frames in the years 2011, 2013, 2015, 2017, and 2020. While the year 2020 presents the year that the COVID-19 pandemic hit globally, clubs were mostly asked about their situation pre-COVID. For example, all financial variables relate to the year 2019. Thus, no COVID-related effects are expected to interfere with the panel analysis. In each wave, two reminder emails were sent out to improve the response rates (Muñoz-Leiva et al., 2010). As only clubs that provided information on their finances were included in the present study, the sample resulted in an unbalanced panel of n = 19,944 sport clubs in Germany with n = 28,963 observations. Due to missing values in the dataset, observations included in the statistical models ranged between n = 1,366 to n = 5,315 observations (see Tables 2 and 3).

Operationalization

The dependent variables reflected the organizational capacities based on the framework by Hall et al. (2003) and were measured in waves 6, 7, and 8 of the SDR (t). While the model by Hall et al. (2003) contains several aspects in each capacity dimension, which have also been operationalized in the sport context (Doherty & Cuskelly, 2020), we relied on measures that were present in two or more waves of the SDR since not all variables are included in all waves. Thus, the measurement of the organizational capacity dimension is limited to selected aspects of each dimension.

As the extent of organizational capacities and therefore the organizational structures are related to organizational size (Amis & Slack, 1996), we used per-capita measures for the metric variables in the human resource capacity, financial capacity, and planning capacity. Human resource capacity was measured by the number of volunteers per capita (volunteer_capita) and the number of paid staff per capita (paidstaff_capita). The financial capacity was measured by the total amount of revenue per capita (ln_revenue_capita), and expenditure per capita (ln_expenditure_capita) of clubs. To achieve normal distribution, the natural log of total revenue and total expenditure was used. Additionally, the financial capacity was measured by a variable measuring if clubs break even or not (breakeven) to reflect the financial situation of the club. The planning and development capacity was measured by the item ‘Our club has a strategic concept’ which was measured on a five-point Likert scale (1 = do not agree to 5 = totally agree). The variable was recoded in a dummy variable with all clubs scoring ‘0’ if they indicated a weak level of agreement to having a strategic concept (scale values ‘1’ to ‘3’ in the original variable) and ‘1’ if clubs indicated a strong agreement to having a strategic concept (scale values ‘4’ and ‘5’ in the original variable). Lastly, the infrastructure and process capacity was reflected by clubs’ possession of a facility (own_facility) and club-owned fitness gym (own_gym). As only the 8^th wave of the SDR contained information on clubs’ collaborations, the relationship and network capacity could not be included in the empirical analysis.

The independent variables reflected the level of competition as perceived by the clubs. The competition items were derived from a larger problem-statement battery, which asked clubs ‘How great do you perceive the following problem?’. The extent of the problem was measured on a five-point Likert scale (1 = no problem to 5 = a very big problem). The present study included the items on competition from other clubs (Comp_club_t-2) and competition from commercial sport providers (Comp_commercial_t-2). As the stimulus to build capacity must occur at the start of the capacity building process, the independent variables were measured as lagged variables two waves prior, thus in waves 4, 5, and 6 of the SDR (t-2). Thus, there is a four-year lag between the stimulus (perceived competition) and capacities, which is a similar time frame as in the study by Elmose-Østerlund et al. (2021). As some variables were only measured in selected waves (paidstaff_capita, strategy_dummy, own_gym), these models were estimated on a reduced sample.

Further information on clubs’ characteristics was included to control for existing capacity at the time t-2. To account for the size of the club, the total number of members (members_sum_t-2) was included in the logistic regression analysis on the binary outcome measures (strategy_dummy, breakeven, own_facility, own_gym). Again, this was done to account for the relationship between the size of non-profit sport clubs and their organizational structure (Amis & Slack, 1996), similar to the per-capita approach in the metric variables. Finally, we controlled for the number of sports offered by clubs, meaning if clubs offer only a single type of sport or multiple sports (multisport_t-2), for community size (community_size_t-2) as previous research has shown that perceived competition is stronger in larger communities (Rossi et al., 2020), and for the survey year (year). To be able to track changes in the dependent variables (organizational capacity dimensions) and to account for potential serial correlation (Drukker, 2003), we included the lagged variables of the dependent variables in the respective models (volunteer_capita_t-2, paidstaff_capita_t-2, ln_revenue_capita_t-2, ln_expense_capita_t-2, strategy_dummy_t-2, breakeven_t-2, own_facility_t-2, own_gym_t-2). The independent variables reflected the level of competition and control variables at the point of time four years before the measurement of the dependent variables, thus no changes in the independent variables were measured. An overview of all variables examined is presented in Table 1.

Table 1. Operationalization and summary stats of variables in the model.

Variable	Operationalization	Measurement	2011 Mean (SD)	2013 Mean (SD)	2015 Mean (SD)	2017 Mean (SD)	2020 Mean (SD)
Dependent Variables: Organizational capacity dimensions
HR: volunteers_capita	Total number of volunteers per capita	Metric	.089 (.123)	.140 (.197)	.149 (.210)	.149 (.173)	.178 (.528)
HR: paidstaff_capita	Total number of paid staff per capita	Metric	N/A	.005 (.026)	.016 (.039)	N/A	.010 (.126)
F: ln_revenue_capita	Logged total revenue per capita (in €)	Metric	.120 (.141)	.108 (.125)	.118 (.142)	.121 (.146)	.112 (.137)
F: ln_expenditure_capita	Logged total expenditure per capita (in €)	Metric	.118 (.139)	.106 (.123)	.116 (.140)	.120 (.145)	.110 (.136)
F: breakeven	Club has a positive revenue-expenditure account	Binary (1 = yes)	.778	.759	.765	.727	.738
P: strategy_dummy	Club has a strategic concept	Binary (1 = yes)	.539	.504	.504	N/A	N/A
I: own_facility	Club owns a facility	Binary (1 = yes)	.443	.450	.442	.389	.407
I: own_gym	Club owns a fitness gym	Binary (1 = yes)	.034	N/A	.033	.033	N/A
Independent variables: Organizational capacity building stimulus
comp_club	Level of perceived problem of competition from other clubs	Ordinal (1 = no problem, 5 = a very big problem)	1.948 (1.141)	1.978 (1.146)	1.918 (1.135)	N/A	N/A
comp_commercial	Level of perceived problem of competition from commercial sport providers	Ordinal (1 = no problem, 5 = a very big problem)	1.668 (1.026)	1.664 (1.017)	1.619 (1.005)	N/A	N/A
Control variables: Organizational characteristics
members_thd	Total number of members (in 1,000)	Metric	.310 (.561)	.333 (.882)	.303 (.495)	.286 (.470)	.324 (.509)
multisport	Club offers more than one sport	Binary (1 = yes)	.368	.545	.441	.466	.409
community_hthd	Number of inhabitants in the community (in 100,000)	Metric	2.136 (6.173)	1.848 (5.596)	1.826 (5.449)	1.906 (5.755)	2.026 (6.143)
year	Survey year (reference year: 2011)	Binary (1 = yes)	.161	.228	.216	.184	.212

Data analysis

The data analysis process consisted of two steps. First, descriptive statistics were computed to explore how the organizational capacity dimensions investigated in this study changed between the survey years 2011 (4th wave), 2013 (5th wave), 2015 (6th wave), 2017 (7th wave), and 2020 (8th wave). This was done to explore if clubs in the sample reported changes in the investigated organizational capacity dimensions at all. Mean values with standard deviation were considered (see Table 1).

Second, to answer the research question of this study, the impact of perceived competition on organizational capacities four years later was analyzed using linear and logistic regression analysis. The models with the dependent variables volunteer_capita, paidstaff_capita, ln_revenue_capita, and ln_expenditure_capita were estimated using a pooled ordinary least square (OLS) linear regression with a maximum likelihood estimator. Due to the nature of the dependent variables, the models on logged revenue and logged expenditure were log-linear. The models with the dependent variables strategy_dummy, breakeven, own_facility, and own_gym were estimated using a logistic regression to account for the binary nature of the dependent variables. All models were checked for multicollinearity using the variance inflation factors (VIF). Multicollinearity presented no problem as all VIFs were below 2 and thus below the threshold of 10 (Hair et al., 2014). Serial correlation was tested using the Woolridge serial correlation test for panel data (Woolridge, 2002). As the tests were not significant, serial correlation presented no problem (Drukker, 2003). To account for the panel structure of the data, all models were estimated with cluster-robust standard errors (Cameron & Miller, 2015).

Results

Descriptive results

The descriptive results show that the organizational capacities of sport clubs in the sample fluctuated between 2011 and 2020. In terms of human resources, clubs had on average .09 volunteers per member in 2011, whereas the share increased to .18 in 2020. The share of paid staff increased between 2013 and 2015 from .005 to .016 but decreased again to .01 in 2020. Regarding finances, the logged values of revenue and expenditure per member reveal a slight decrease but this development is inconsistent over the survey years. In line with this decrease is the development of breakeven. While 78% of clubs reported a positive revenue-expenditure account in 2011, this share decreased to 74% in 2020. The development in terms of strategic planning between 2011 and 2015 highlighted a similar development as the share of clubs having a strategic concept decreased from 53.9% in 2011 to 50.4% in 2015. In terms of infrastructure, the share of clubs in possession of their own facilities showed a slight decrease between 2011 and 2020. 44% of clubs owned a facility in 2011 whereas the share decreased to 41% of clubs in 2020. Only 3% of clubs reported owning a fitness gym, with this share being constant between 2011 and 2017 (see Table 1).

The level of perceived competition has remained relatively stable throughout the investigation. Perceived competition from other clubs decreased slightly from M = 1.95 in 2011 to M = 1.92 in 2015. The level of competition from commercial sport providers decreased also slightly over time (2011: M = 1.67; 2015: M = 1.62) (see Table 1).

Analytical results

The results of the regression models are summarized in Tables 2 and 3. The results show that perceived competition from commercial sport providers has a significant positive effect on the number of paid staff (β = .001, p = .046). In contrast, the number of volunteers (β = -.004, p = 085) and the likelihood of breaking even (β = -.088, p = .047) are affected negatively by perceived competition from commercial sport providers (see Tables 2 and 3). However, the effect on the number of volunteers is only significant at the 10% level. Moreover, the likelihood of having a strategic concept is negatively affected by competition from other clubs (β = -.119, p = .055) at the 10% level. There are no significant effects of perceived competition from other clubs or perceived competition from commercial sport providers on the measures of the infrastructure and process capacity. Furthermore, the results show that club size in terms of the number of members has a significant positive effect in all four logistic regression models (see Table 3), whereas being a multisport club has a negative effect on the number of volunteers per member, logged revenue and expenditure per member, having a strategic concept, and owning a facility (see Tables 2 and 3). Only in the model on breakeven, being a multisport club has a positive effect, however only at the 10% level (see Table 3). The likelihood of owning a facility, in general, is decreased in larger communities (see Table 3). As expected, all lagged dependent variables have a significant positive effect on the capacities two years later, except for the number of volunteers per member (see Table 2).

Table 2. Results of the pooled OLS regression models (displayed are standardized coefficients with cluster-robust standard errors in parentheses).

	Model 1: volunteers_capita	Model 2: paidstaff_capita	Model 3: ln_revenue_capita	Model 4: ln_expenditure_capita
comp_club t-2	-.003 (.002)	-.000 (.000)	-.000 (.001)	.000 (.001)
comp_commercial t-2	-.004 (.003)^+	.001 (.001)*	-.000 (.001)	.000 (.001)
multisport t-2	-.077 (.007)***	-.001 (.000)	-.010 (.003)***	-.010 (.003)***
community_hthd t-2	.000 (.000)	.000 (.000)	-.000 (.000)	-.000 (.000)
volunteers_capita t-2	.068 (.060)	-	-	-
paidstaff_capita t-2	-	.189 (.039)***	-	-
ln_revenue_capita t-2	-	-	.931 (.033)***	-
ln_expenditure_capita t-2	-	-	-	.937 (.034)***
year	Included	Included	Included	Included
constant	.192 (.014)***	.004 (.001)***	.020 (.005)***	.018 (.005)***
F	36.67***	6.38***	320.65***	325.35***
R²	.0722	.0968	.7679	.7783
n (observations)	4897	1987	4023	3830

***p ≤ .001; **p ≤ .01; *p ≤ .05; ⁺p ≤ .1.

Table 3. Results of the logistic regression analysis (displayed are standardized coefficients with cluster-robust standard errors in parentheses).

	Model 5: strategy_dummy	Model 6: breakeven	Model 7: own_facility	Model 8: own_gym
comp_club t-2	-.119 (.062)^+	-.001 (.039)	.040 (.049)	.162 (.234)
comp_commercial t-2	.013 (.069)	-.088 (.044)*	.035 (.053)	-.338 (.302)
multisport t-2	-.285 (.144)*	.156 (.084)^+	-.432 (.104)***	.618 (.486)
community_hthd t-2	.011 (.009)	.002 (.006)	-.013 (.007)^+	.038 (.032)
members_thd t-2	.391 (.132)**	.166 (.080)*	.484 (.107)***	.719 (.153)***
strategy_dummyt-2	1.349 (.123)***	-	-	-
breakeven t-2	-	.402 (.086)***	-	-
own_facility t-2	-	-	4.113 (.102)***	-
own_gym t-2	-	-	-	4.658 (.429)***
year	Included	Included	Included	Included
constant	-.567 (.160)***	.657 (.120)***	−2.768 (.138)***	−5.028 (.634)***
−2LL	−775.09	−2,072.10	−1,673.63	−97.87
χ²	136.09***	39.27***	1800.36***	153.11***
Nagelkerke R²	.0891	.0096	.5007	.4785
n (observations)	1228	3631	4991	1265

***p ≤ .001; **p ≤ .01; *p ≤ .05; ⁺p ≤ .1.

Discussion

The findings of the present study have explored the role of competition from other organizations on the capacity building process of non-profit sport clubs. The descriptive results show that organizational capacities change only slightly over the investigated waves of the SDR, with clubs reporting slightly higher numbers of paid staff and volunteers in later waves and slightly lower amounts of revenue, expenditure, having a strategic concept, and owning a facility. However, the analytical results reveal that perceived competition from other organizations has an effect on some of these developments of the organizational capacity dimensions under study. In terms of the development of the number of volunteers and paid staff as selected aspects of the human resource capacity, perceived competition from commercial sport providers effects non-profit sport clubs significantly. While the descriptive results show a slight increase both in paid staff and volunteers across all clubs over time, the results of the regression analyses show that clubs that experienced higher levels of competition four years earlier report a higher number of paid staff and a lower number of volunteers than clubs that experienced lower levels of perceived competition. This finding is in line with other findings on external capacity building stimuli that show that changes occur especially in the human resource capacity (Casey et al., 2009; Elmose-Østerlund et al., 2021; Girginov et al., 2017). Based on the theoretical considerations by Millar and Doherty (2016), clubs’ focused investment in human resources is to be expected as human resources are the most critical capacity in non-profit sport clubs (Doherty & Cuskelly, 2020; Misener & Doherty, 2009) and therefore in the focus of strategic management processes. However, as our results show, competitive forces increase only paid employment in non-profit sport clubs, whereas the number of volunteers – which has been the focus of previous studies on capacity building as they present the main workforce for non-profit sport clubs (Elmose-Østerlund et al., 2021; Wicker & Breuer, 2011) – are decreasing. One explanation for this finding could be that non-profit sports clubs are affected by commercial competition in terms of their workforce and therefore identify a need for capacity building. While commercial sport providers pay their coaches, non-profit sports clubs traditionally rely on volunteers for program delivery. When commercial sport providers offer similar programs as non-profit sports clubs, they attract not only similar target groups in terms of members but also increasingly in terms of coaches and instructors. Thus, the incentive for coaches and instructors to volunteer in non-profit sports clubs is lower as they can get a higher financial return for their work when they offer their courses in a commercial setting. Non-profit sports clubs are therefore pressured to pay their coaches and instructors as well. This phenomenon has been previously identified in qualitative inquiries (Rossi et al., 2020). This finding thus shows that competition acts as a driver of professionalization of human resources in the non-profit sport sector, adding to qualitative findings on the evolution of non-profit sports clubs towards professionalized membership associations (Zimmer et al., 2018).

Looking at the financial capacity of clubs, the results show no effect of perceived competition on the total revenue and expenses per member, but a decrease in the likelihood of having a positive revenue-expenditure account (breakeven). Thus, it appears that non-profit sport clubs do not increase their financial capacity in terms of revenue and expenses to counteract competition, which contrasts previous findings on specific capacity building initiatives in the general NPO context (Faulk & Stewart, 2017). Rather, on the contrary, perceived competition appears to worsen the financial situation of sport clubs. This could relate to the first finding of increased professionalization due to perceived commercial competition. Hiring paid staff demands higher financial investments from sport clubs than relying on volunteers. Indeed, in a previous study, Wicker and Breuer (2013) identified a positive effect of voluntary engagement on financial problems, meaning that sport clubs with a larger volunteer workforce reported smaller problems in terms of finances. Thus, it appears that while sport clubs react to perceived competition by investing in more paid staff, they neglect the resulting higher financial demands which in turn worsens their overall financial situation.

Lastly, considering the structural capacity, the study shows that perceived competition does not lead clubs to invest in their infrastructure in terms of facility ownership or to develop a strategic plan. Looking at facility ownership as one facet of the infrastructure and process capacity, the lack of stimulus effect of perceived competition could be caused by the chosen time frame in the study. Four years might be too short to lead to such high investments as needed for buying and/or building new facilities such as sport halls or a gym. Using a similar time frame, Elmose-Østerlund et al. (2021) could also detect no significant capacity building efforts in acquiring new facilities. Rather, they identified changes in the process dimensions of the infrastructure and process capacity, which could not be investigated in the present study. Considering the strategy and planning capacity, which in the present study was measured as having a strategic plan within a club, the results are relatively surprising. Previous studies have shown that competition plays a role in clubs’ strategic management process (Morrison & Misener, 2021, 2022b). Thus, it would be expected that clubs facing higher perceived competition from other clubs or commercial sport providers should invest in their strategy and planning capacity to address these challenges accordingly. In contrast, our results show that competition from other clubs has a negative effect on the likelihood of having a strategic plan. One explanation for the lack of effect on the strategic dimension could be that sport clubs do not identify a capacity need as strategic concepts and management tools are not central to program and service delivery and thus are deemed less important in the capacity building process (Millar & Doherty, 2016). However, more research is needed to investigate this contradiction.

Overall, the present study has shown that perceived competition from other local actors has only small effects on the development of the investigated organizational capacity dimensions. In light of the organizational capacity building model by Millar and Doherty (2016), we interpret these findings as a hint that perceived competition acts only as a stimulus for capacity building in the human resource capacity. At first glance, this is surprising as qualitative studies on the strategic management process of clubs have shown that environmental factors including competition play a role in the clubs’ considerations (Morrison & Misener, 2021, 2022b). However, as Millar and Doherty (2021) have shown, clubs seem to focus more on internal stimuli in form of declining membership figures than external stimuli in form of competition. Our findings support and extend these findings as we provide empirical evidence for the effects of perceived competition on the development of organizational capacities and therefore provide first insights into the role of competition as an external capacity building stimulus. As pointed out in the theoretical framework, the limited effects of competition could be explained by either competition presenting a generally small problem in sport clubs (Rossi et al., 2020) or sport clubs identifying no need to build capacity to react to competition (Millar & Doherty, 2016). Our findings hint to the latter as it appears that perceived competition from commercial sport providers decreases the number of volunteers in clubs, which leads clubs to increase the number of paid staff. Thus, there seems to be only a need to build capacity in human resources. These findings lead to implications for both theory and practice.

Theoretical and practical implications

In terms of theory, our findings indicate that the limited effects of perceived competition in the development of organizational capacities of non-profit sport clubs need to be considered when applying strategic management principles. For one, perceived competition affects sport clubs in their human resources as it is a driver of professionalization in non-profit sport clubs. These professionalization processes need to be taken into account in the study of competition and strategic management in non-profit sport clubs. Moreover, relating these findings to the organizational capacity building model by Millar and Doherty (2016), the empirical results imply that non-profit sport clubs seem to be rather unresponsive to competition as an external capacity building stimulus. It is thus expected that internal stimuli in terms of declining membership figures, financial problems, or lack of volunteers play a bigger role in the capacity building process than an evaluation of the market.

In terms of practical implications, the results highlight that commercial competition does lead non-profit sport clubs to invest in paid staff. To prevent clubs from experiencing financial problems due to higher costs for paid staff, clubs should consider increasing their revenue when faced with commercial competition to have a financial backup. Potential revenue sources could be the acquisition of new sponsors, the charging of course fees, or an increase in membership fees. Especially the latter has so far been unrelated to competition (Feiler et al., 2019) but our results indicate that commercial competition should play a role in pricing as it comes with higher costs for paid staff members.

Moreover, our results show that clubs do not respond to competition by investing in a strategic concept. While this might be explained by a lack of need, clubs should nevertheless be advised to increase their strategic capacity to be able to track their environment and act proactively to changes in the environment. This is especially important in recent times as clubs compete for human resources after the COVID-19 pandemic (Doherty et al., 2022) and need to navigate through new challenges such as the current energy crisis. Building strategic capacity in turn can support clubs in addressing these challenges and decrease competitive pressures.

Limitations and future research

Despite careful consideration and conduct of the study, some limitations need to be addressed. First, the measurement of capacities is limited. Each capacity dimension was measured with only a few items, which reflected rather hard factors such as the number of paid staff, volunteers, club-owned facilities, etc. Other aspects of the model by Hall et al. (2003), which were operationalized by Doherty and Cuskelly (2020) could not be included due to the lack of information in the panel data. This limits our findings to the selected measures presented in the models. Thus, further effects on other aspects of the organizational capacities could be possible as pointed out in the discussion section. Second, there is a lack of information on the relationship and network capacity. This would have been beneficial as based on resource dependency theory, it can be assumed that higher competition is counteracted through strategic alliances and inter-organizational relationships. Lastly, the study contained no information on the readiness of clubs for capacity building and the explicit strategies and/or alternative strategies in counteracting competition. Thus, our findings can only be interpreted as effects on the development of organizational capacities but cannot illustrate the whole organizational capacity building process as modeled by Millar and Doherty (2016).

Future studies should address these gaps by investigating the relationship between the level of competition and further aspects of the organizational capacity dimensions. Especially the integration of further human resources variables such as human capital and enthusiasm, but also more aspects of the strategy and planning capacity could expand the results of this study. Also, the emergence of inter-organizational relationships as a strategic action to counteract competition should be addressed in future studies. Moreover, more quantitative research should be conducted in the strategic management processes in non-profit sport clubs to extend the valuable qualitative findings and to test the findings of the present study in terms of unresponsiveness to environmental forces. Last but not least, more empirical evidence is needed on the role of internal stimuli in the organizational capacity building process.

Conclusion

To conclude, we could show that the competitive situation of non-profit sport clubs has only limited effects on the development of organizational capacities of non-profit sport clubs. Clubs experiencing higher levels of perceived competition from commercial sport providers invest in their human resource capacity by employing more paid staff, while there appear to be no effects on the development of the other aspects of the capacity dimensions under study. We thus conclude that competitive forces in terms of perceived competition from commercial sport providers and others sport clubs play only a subordinate role in the strategic management and the capacity building process of non-profit sport clubs.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Federal Institute of Sport Science (BISp), the German Olympic Sports Confederation (DOSB), and the 16 federal State Sports Confederations (LSBs) (grant number IIA1-081801/11-17 and grant number ZMVI4-081802/17-26)