Approaching predictors of success for sports clubs by applying the organizational capacity framework

Many previous scientific investigations of sports clubs have lacked an appropriate approach for reflecting the diversity of sports-related organizations. The purpose of this paper is to measure sports clubs’ performance by considering the problems they experience. To perform this, the organizational capacity framework (OCF), which captures various internal and external resources possessed by organizations, is used to investigate various human, financial, and structural capacities of sports clubs located in Rhineland, Germany (n = 1000). This research also serves to test the organizational capacity framework’s applicability in this context. The results of multiple regression analysis showed that the framework is suitable for measuring the characteristics of sports clubs; however, further research is required to obtain more precise data. Regarding organizational problems, the present findings indicate that having sufficient board members, possessing good finances, and engaging in strategic planning are the factors with the greatest influence on reducing problems among sports clubs.


Introduction
The sporting landscape unites a large number of clubs with a diverse range of goals. This raises the question of which independent, overarching factors can explain or influence sports clubs' performance and serve as a means of identifying clubs' respective strengths and weaknesses (Meier, Kukuk, & Thiel, 2017), which is a notable issue in the field. As sports clubs can be heterogeneous in terms of goals, this hinders measurement of their success; moreover, established economic representations of successarealsounsuitableforthiscontextbecause many clubs have only a regional focus and lack profit orientation. Furthermore, researchers have also encountered the problem of transforming the complex interrelationships between organizations, their members, and the environment into a model the logic of action of sports clubs (Nagel, 2007). Accordingly, scientific studies in this field have primarily focused on identifying aspects, conditions, or benchmarks that serve as indicators of success (Wicker, 2017).
This study aims to close the research gap regarding means of measuring success among organizations and identifying the resources required to achieve success. Following Doherty and Cuskelly (2020), who applied the organizational capacity framework (OCF) to examine sports clubs' performance, this study focuses on organizations' resources and problems associated with resource deficiency, as this can reveal organizational weak-nesses that require solving (Geisinger & Hoepfner, 2008); an absence of such problems indicates a solution-focused and well-performing organization. The OCF considers organizations' ability to access various intra-organizational and external resources (Hall et al., 2003) and has previously been verified as a suitable tool for assessing organizations (Balduck, Lucidarme, Marlier, & Willem, 2015;Kitchin & Crossin, 2018;Seippel et al., 2020). In the present study, to consider success among sports clubs, organizational problems were considered cumulatively.
The basic assumptions of this study are that an absence of problems is equivalent to good organizational performance and that an organization's resource health has an impact on the severity of its problems. The present study applies the introduced framework to sports clubs based in Rhineland, Germany; thus, this study may contribute to identifying predictors of success among sports clubs.

Theoretical background
Recently, OCF has been applied to gain holistic insights into sports clubs' performance and problems by dividing an organization into substantive resource dimensions (Seippel et al., 2020;Wicker & Breuer, 2013). This framework is based on Hall et al. (2003) and focuses on organizations' ability to acquire and marshal various resources and mobilize different forms of capital and, thus, can identify a sports club's potential to achieve its goals (Balduck et al., 2015;Kitchin & Crossin, 2018). Accordingly, organizational capacity is understood as the maximum performance or production ability of an organization. This approach can be customized by selecting relevant variables (for the context in question) across three dimensions: human resource, financial, and structural capacity, which is further divided into infrastructure and process, network and relationship, and planning and development capacity (Misener & Doherty, 2009;Svensson, Hancock, & Hums, 2017).
Human resources are the most relevant resource for nonprofit organizations (NPOs; Doherty & Cuskelly, 2020;Hall et al., 2003). Looking beyond this, various revenue sources ensure sustainable development(Doherty&Cuskelly, 2020); this means financial resources represent secondary requisites for the achievement of goals (Balduck et al., 2015;Wicker, 2017). Subsequently, both dimensions are crucial for acquiring additional structural resources necessary for the provision of sports services. Next, infrastructure and process capacity impact infrastructural availabilities and usage, as well as the maintenance and efficiency of daily operations (Hall et al., 2003;Kitchin & Crossin, 2018); meanwhile, clubs' level of cooperation with other organizations, which represents clubs' network and relationship capacities, indicates their ability to leverage relationships with different types of organizations and, thus, reflects their social orientation (Balduck et al., 2015). Finally, planning and develop- Fig. 1 8 Organizational capacity model and significance of variables in explaining organizational problems, whereby a large sum of organizational problems corresponds to a low level of organization success ment capacity represents an organization's ability to pursue strategic development and conduct long-term planning and, therefore, the organization's degree of forward-looking thinking and motivation to develop (Svensson et al., 2017).
However, there are some criticisms of the OCF, as the term "capacity" is extremely vague, lacking a clear and consistent definition or conceptualization (Svensson, Andersson, & Faulk, 2020). In addition, the lack of uniform predetermination of variables, and the fact that some aspects cannot be assigned to a single dimension, may mean important variables are omitted, leading to inaccuracies in results (Wicker & Breuer, 2014). Moreover, specific capacity needs vary across organizations, which can also limit the level of understanding afforded by this approach (Andersson, Faulk, & Stewart, 2016). Further, exclusive valuation of various key figures disregards the interdependency between them. In the context of success, the wide range of sports, different numbers of members, and various statutory purposes mean there are a multitude of heteroge-neous organizations, which impedes the development of an all-encompassing and uniform definition of success. Studies have suggested that the identification of success-predicting factors leads to numerous imitations, which consequently causes these factors to become standard (Kieser & Nicolai, 2003); however, Kieser (2011) emphasized reflecting on practice with the help of theory, and stated that science and practice reveal different perspectives to each other.
Although previous studies have found member satisfaction to be correlated with success (Klenk, Schlesinger, & Nagel, 2017), a reliance on satisfaction is inherently associated with the problem of subjectivity, as perceptions can differ among members (Gough & Madill, 2012). Objective predictors of success, such as the number of volunteers, however, are limited in their informative value because of a lack of reference values. For instance, consideration of member growth is unsuitable because clubs have differing targets regarding numbers of members (Meier et al., 2017). Furthermore, the num-ber of volunteers is not representative of their given contribution. While the consideration of monetary aspects has not provided significant results (Wicker & Breuer, 2013), paid staff can either be a result of professionalization or a sign of volunteer overload (Cuskelly, 2004). Geisinger and Hoepfner (2008) circumvented this problem by defining the absence or avoidance of errors as efficient management, suggesting that the presence of quality deficiencies and/or the implementation of problem fixes are accompanied by financial and/or time expenditures that reduce clubs' efficiency and, therefore, performance.
Public-funding cuts, membership turnover, difficulty attracting and retaining volunteers, competition from commercial providers, and public engagement in unorganized recreational sports or alternative activities are some of the numerous problems that may be encountered by sports clubs (Breuer & Feiler, 2019). In particular, the acquisition and retention of volunteers has been identified as the most serious problem in Germany (Breuer & Feiler, 2019). Human resources are most relevant for such organizations because people are responsible for the acquisition and utilization of other resources (Elmose-Østerlund, Cuskelly, Høyer-Kruse, & Voldby, 2021;Hall et al., 2003) and, thus, personal problems lead to problems in other areas.
The underlying model used for the present research is derived from previous literature, starting with the concept that, for sports clubs, the perceived absence (on the part of representatives of the clubs) of problems can be used as a representation of success. Furthermore, various aspects that have previously been found to be relevant to organizational capacity and problems were chosen for each capacity dimension in this research. Consequently, by combining both approaches, it should be possible to identify individual resources that are relevant to organizational problems and performance (Doherty & Cuskelly, 2020).
An overview of the selected variables is presented in . Fig. 1. Organizational success is approached by examining, among each club, the cumulative perception of problems encountered in regard to recruiting and retaining members, voluntary officials, trainers, and instructors; the availability of sports facilities; competition from providers of other sports; and restrictions due to all-day schools; as these aspects are most relevant in the context of German sports clubs (Breuer & Feiler, 2019).
The relevance of human resources has been examined in numerous scientific studies, which have focused on aspects such as sociodemographic characteristics, and individuals' motivation, skills, and knowledge (Misener & Doherty, 2009;Wicker, 2017;Wicker & Breuer, 2013). Regarding success, previous studies on sports clubs have found that having a high percentage of female board members and a high number of volunteers are both associated with fewer problems and better performance (Doherty & Cuskelly, 2020;Wicker & Breuer, 2013). Individuals' willingness to volunteer, in turn, has been found to be influenced by the existence of paid staff and perceived links with the organization; the latter can be strengthened through the hold-ing of social events (Swierzy, Wicker, & Breuer, 2019;Wicker & Breuer, 2013). Following Swierzy et al. (2019). In the present study, finances are considered through examining financial problems, because fewer financial problems should lead to less severe general problems.
Moreover, various structural capacity variables have been shown to impact organizational success. The use of both owned and municipal facilities is associated with problems (Wicker & Breuer, 2013, 2014; this may be explained by the high construction and maintenance costs associated with possessing sports facilities and by sharing municipal facilities (Swierzy et al., 2019). Thus, in the present study the usage and accessibility of facilities are considered within infrastructural capacity. Further, the variety of sports programs and departments (i.e., the different sports provided) offered by a club, which represent social inclusion and sporting focus, and communication within the board afford insight into the processes of the organization (Wicker & Breuer, 2014).
Quantity and type of cooperation can indicate the quality of an organization's external network (Swierzy et al., 2019;Wicker & Breuer, 2014); the present research examines clubs' cooperation with different types of organizations (. Fig. 1). As it has previously been found that strategic planning is significant for reducing problems (Wicker & Breuer, 2013), consideration of clubs' formulation of strategic concepts and long-term planning is included to capture their planning and development capacities (Svensson et al., 2017;Swierzy et al., 2019). In addition, the size of clubs is considered, because membership numbers significantly influence different capacity items (Balduck et al., 2015).

Data analysis
This study aims at answering the following research question: What organizational resources are required to reduce the perceived problems of sports clubs? To identify predictors of organizational success among sports clubs Abstract Many previous scientific investigations of sports clubs have lacked an appropriate approach for reflecting the diversity of sports-related organizations. The purpose of this paper is to measure sports clubs' performance by considering the problems they experience. To perform this, the organizational capacity framework (OCF), which captures various internal and external resources possessed by organizations, is used to investigate various human, financial, and structural capacities of sports clubs located in Rhineland, Germany (n = 1000). This research also serves to test the organizational capacity framework's applicability in this context. The results of multiple regression analysis showed that the framework is suitable for measuring the characteristics of sports clubs; however, further research is required to obtain more precise data. Regarding organizational problems, the present findings indicate that having sufficient board members, possessing good finances, and engaging in strategic planning are the factors with the greatest influence on reducing problems among sports clubs.

Keywords
Sports clubs · Success factors · Organizational problems · Resources · Volunteers by considering organizational resources and problems, multiple regression analysis was conducted with listwise case exclusion. As a requirement and since multitude of variables are included, testing for multicollinearity is important (Kim, 2019). Accordingly, to ensure the stability and sensitivity of the regression model, an exact bivariate linear relationship among the independent variables should be avoided (Shrestha, 2020). By calculating, for each independent variable, the linear regressions of the other predictors, the causal influence between the variables is represented through the variance inflation factor (VIF) or its inverse, the tolerance. Although a rela- tionship between the predictors is unavoidable, the VIF value should be lower than 5.00, as a high VIF value indicates a high correlation and, therefore, possibly erroneous results (Kim, 2019;Shrestha, 2020).

Data collection
Through an online survey administered between October and November 2019, data were collected from the board of the sports clubs located in Rhineland; the survey was commissioned by the umbrella organization, the Sportbund Rheinland (SBR

Survey and variables
The survey was divided into five parts (resources, the club, environment, board work, and personal information) and col-lected various structural data. These data were supplemented by membership figures collected by the SBR. The main structure of the survey was based on studies by Thieme, Liebetreu, and Wallrodt (2017) and Breuer and Feiler (2019), who previously examined problems in acquiring and retaining board members. The variables chosen, based on their assumed influence on success, are summarized in . Table 1.
The survey included several Likert items that captured respondents' perceptions and enabled the use of parametric statistics. However, from a statistical viewpoint, the application of parametric methods to pseudo-interval scaled data should be avoided (Carifio & Perla, 2008); therefore, the present author distinguishes between summations of scores from Likert scales, which represent the explained variable, and scores for individual Likert items, which represent predictors (Carifio & Perla, 2008). If respondents provided scores for all scales, the individual ratings for seven different problems were summed (average method) to create an indicator of sports clubs' organizational problems: recruiting members (P1), retaining members (P2), recruiting and retaining voluntary officials (P3), recruiting and retaining trainers and instructors (P4), availability of sports facilities (P5), competition from other recreational and commercial sports providers (P6), and general restrictions imposed by all-day schools (P7). The severity of each problem was ranked using a five-point Likert scale. Although this method hides variations and particular problem areas, it provides an overview of the status of the club.
Six variables were used to capture human-resource capacity. Whether clubs had a sufficient number of individuals to support the organization, through providing voluntary or paid services, was measured through items concerning the proportion of central (HR1) and secondary (HR2) volunteers in relation to the total number of members, the existence of paid employees (HR3), and whether clubs had sufficient active board members (HR4). Furthermore, the gender diversity of officials was determined by considering the proportion of women on the board (HR5). Finally, the holding of social events (HR6), which can strengthen the relationship between sports clubs and their volunteers and members, was also considered. Financial capacity was captured through the respondents' perceptions of financial problems within their organizations; this was measured using a single Likert item (F1).
Infrastructural capacity was captured through measuring whether the clubs used their own (I1) or municipal sports facilities (I2), and the accessibilityofthese facilities (I3). Moreover, the number of departments in the sports clubs (I4) and assessments of board communication (I5) were considered in order to gain insight into the processes and interactions within the organization. Regarding network and relationship capacity, the present study examined the diversity of the clubs' external relationships by investigating whether they had agreed or loose cooperation with any of the following types of organizations: other sports clubs (N1), schools (N2), kindergartens (N3), commercial sports providers (N4), and youth organizations (N5). Regarding planning and development capacity, the basic attitude of the organizations with regard to strategic planning and future development (S1) was captured. Here, a score was calculated by summing levels of agreement/disagreement, captured through Likert items, with the following statements: "our club has a strategic concept, " "our club pursues long-term planning, " and "our club is optimistic about the future. " The reliability of these three items was assessed using Cronbach's alpha (α). Here, α = 0.738, indicating good internal consistency among the three items (Streiner, 2003); furthermore, consistency did not improve if any of the items were deleted.

Results
An overview of the descriptive data is provided in . Table 2. The importance of human resources to the sports clubs is illustrated by the finding that the majority of the clubs (79.8%) were exclusively voluntarily organized, as well as by the percentages of people who volunteered regularly (11.05%) and sporadically (20.70%). However, the standard deviation (SD; HR2 = 20.09) showed considerable differences between the organizations. Nevertheless, the majority of the organizations (82.5%) had a sufficient number of active board members; however, the percentage of women on the boards (33.19%) and the associated SD (25.59) indicated problems regarding gender equality. Notably, 729 clubs organized events to attract and retain volunteers, which also highlights the relevance of human resources. On average, financial problems were rated at 4.10/5, indicating clubs had minor problems with their financial situations; the associated SD of 1.079 implies that even clubs with average deviations from this rating did not have any major problems in this regard.
The infrastructural variables highlighted the relevance of municipal infrastructure, as 66.4% of clubs used these facilities. Furthermore, 47.3% of the organizations owned facilities, which indicated that some sports clubs used both municipal and own facilities. However, the accessibility of the facilities was rated poor on average (2.52/5). The average number of departments was 3.05, which shows that most clubs concentrated on a small number of sports. Regarding process organization, communication among board members was generally good (4.09/5). Cooperation with any type of organization was rare, as less than one-third of the organizations collaborated with either another sports club (32.2%) or a school (21.9%); this indicated low social orientation. In contrast, strategic planning was determined to be relevant, but not a priority, as indicated by the average rating of 9.87/15 (SD = 2.546). Regarding size, the majority of the clubs (72.9%) were small organizations with fewer than 300 members.
The severity of problems varied among the sports clubs. While the average score for overall problems was 18.86/35, indicating moderate problems, the SD of 5.044 reflects a broad range of perceptions in this regard. The descriptive statistics for the problems indicate that human resources were the most problematic area. While acquiring and retaining officials (3.65/5) and trainers (3.16/5) were considered major problems, less relevance was attached to the availability of sports facilities (1.95/5), restrictions imposed by the presence of all-day schools (2.01/5), and competition from other sports and leisure providers (2.46/5).
Prior to discussing the results, multicollinearity was considered to exclude biases caused by interrelated coefficients. All VIF values were between 1.045 and 2.888, indicating no interdependency and, thus, no multicollinearity. The overall regression model was significant, F(19, 614) = 13.59, p < 0.001, R 2 = 0.296. Accordingly, the chosen model was suitable for predicting approximately onethird of the variance in organizational problems, and provided initial insights into the predictors of success among Among these 202 sports clubs, only 27 organizations employed full-time staff sports clubs. However, the rather low R 2 value was an indicator that the chosen items were not suitable for serving as a unified framework. Nevertheless, the practical relevance of the multiple regression can be underlined by its effect size; Cohen's f 2 equaled 0.377, indicating a large effect and, thus, high practical relevance (Cohen, 1992).
To enable a comparison with effect size, the standardized coefficients, which are presented in . Table 3, were interpreted. Based on a significance level of α = 0.05, six variables were identified as significant predictors for problems: paid staff (HR3), sufficient board members (HR4), financial problems (F1), municipal facilities (I2), accessibility of facilities (I3), and strategic development (S1).
The results suggest that the existence of paid staff (0.122) and the usage of municipal facilities (0.121) have a positive influence on the dependent variable; that is, they increase perceived organizational problems. In contrast, sufficient board members (-0.103), financial problems (-0.299), accessibility of facilities (-0.104), and strategic development (-0.288) showed a negative impact on the perceived problems. Among these variables, financial problems and strategic planning had the greatest influence, while the influence of human and infrastructural resources had a comparatively lesser influence.

Discussion
The assumption that the ability to acquire resources affects the problems encountered or success of an organization led to the creation of the regression model presented in this study and indicates that a variety of variables must be considered in order to understand the complex structures and causal relationships that impact sports clubs. With regard to the individual problems, the present findings correspond with those of previous studies by identifying human resources as the primary source of problems (Breuer & Feiler, 2019;Wicker & Breuer, 2013).
Previous qualitative and quantitative applications of the OCF as a means of understanding NPOs have produced significant results regarding organizational ambition or entrepreneurial behavior (Balduck et al., 2015;Svensson et al., 2020). However, the variance that arises from an absence of predetermined variables meant that, here, just 29.6% of the variance in organizational problems was represented by the variables chosen. As the regression model merely constitutes a simplified representation of reality, many success predictors shown to be important in previous studies, such as the diversity of revenue sources and cultural orientation, were excluded from the present research (Swierzy et al., 2019;Wicker & Breuer, 2013). Nevertheless, as evidenced by Wicker and Breuer (2013), broad statements regarding the emergence of problems in organizations can be drawn from the multiple regression approach applied in the present study.
Six items from across four superordinate capacity dimensions were found to have a significant impact on organizational problems (. Fig. 1). The present results emphasized the significance of finances for the good performance of NPOs; this corresponds to findings from other studies, which showed that stable revenues and expenses are relevant for securing sustainable performance (Misener & Doherty, 2009). Furthermore, the present study emphasizes the relevance of strategic planning in order to pursue the goals of achieving successful development, developing a future orientation, and reducing organizational  (Seippel et al., 2020;Svensson et al., 2017). Similarly, Wicker and Breuer (2013) connected individual organizational problems to strategy, and identified strategic development as an important contributor to the reduction of problems.
Human resources were originally hypothesized to be the most relevant factor regarding the emergence and reductionof problems among sports clubs; however, only two associated variables were found to have a significant impact on problems. Although a sufficient number of board members, to ensure that all tasks are covered and work is adequately divided, has previously been shown to be a significant predictor of success (Thieme et al., 2017), the effect size was smaller than that for financial problems and strategies. A possible explanation for this is the ongoing trend away from elected positions and toward project-based volunteerism (Breuer et al., 2021). This trend could relieve the burden on board members, as other people assume their tasks or entire areas of responsibility but, consequently, the influence of the board becomes smaller.
The second human-resources-related variable was paid staff, with the presence of paid staff being found to increase the perceived sum of problems. This contradicts previous findings, for example, Wicker and Breuer (2013) suggested that sports clubs create paid positions to relieve the burden on board members. Although the presence of paid staff has previously been shown to be an indicator of organizational growth and increased professionalization and, thus, could be interpreted as a predictor of success (Seippel et al., 2020), it might also be a sign that volunteers had been experiencing an excessive burden. Another potential reason for the positive correlation between problems and paid employees is that increasing membership leads to an increase in heterogeneous interests, which can increase complexity; however, this hypothesis is invalidated by further scrutiny as, here, the size of a club and its number of departments were found not to significantly influence problems.
It is possible that the monetary benefits and support services secured from umbrella organizations, professional associations, and governments are sufficiently large to compensate for the disadvantages resulting from the abovementioned complexity. Furthermore, previous studies have associated issues such as difficulties financing professional positions, staff shortages, inadequate qualifications among workers, legal and insurance-related problems, and conflicts between paid and volunteer staff with the presence of paid staff (Horch, Hovemann, & Schubert, 2007).
Regarding the dimension of infrastructure and process capacity, the use of municipal facilities was found to increase perceived organizations' problems. This may be associated with long travel distances to the facilities and the need to share their use with different groups or all-day schools, which reduces the available time slots (public schools have a right to use such facilities; Wicker & Breuer, 2013). This assumption is supported by the finding that the availability of facilities can negatively influence problems; further, poor condition of sports facilities, which can also lead to restrictions on their use, might amplify this effect (Breuer & Feiler, 2019). Flatau, Pierdzioch, Pitsch, and Emrich (2011) already found that there is no positive influence of monetary subsidies on sports clubs' members; in this study these results are even extended by a negative influence of indirect subsidies.
In summary, multiple regression showed that sports clubs' problems are significantly influenced by the organizations' board of directors, financial stability, possession of a strategy, and infrastructural conditions. Unexpectedly, human resources are not the biggest influencing factor for problems; nevertheless, their influence is shown because people are responsible for finances and strategy.

Conclusion
This study, by adapting the OCF to sports clubs, provides initial insight into predictors of success represented by perceived problems. As demonstrated in previ-ous research, the consideration of the resources enables the identification of key predictors for different purposes (Kitchin & Crossin, 2018;Swierzy et al., 2019). In the present study, the multiple regression model achieved moderate variance resolution for summations of problems in sports clubs (R 2 = 0.296); this is possibly a result of the exclusion of relevant aspects or predictors that affected only a subset of organizations.
The OCF was used to narrow relevant items to explain problems experienced by sports clubs. Here, the relevance of items concerning human resources and, in particular, the board of directors was confirmed because board members strongly contribute to maintaining clubs' financial stability and the development of clubs' strategies. For board members, the most effective means of increasing success is to emphasize cooperation, value financial security and strategic direction, and ensure the accessibility of sports facilities. Accordingly, the present results demonstrate the multifaceted influence of the board and indicate that, in future studies, it might be advisable to consider related variables, such as the board's responsibilities.

Limitations
The theoretical foundation and character of the survey (primarily the perception of the problems) create limitations regarding the expressiveness of the results and the practical implications that can be gleaned therefrom. The lack of standardized items of the OCF reduced the comparability of the findings. Moreover, the underlying complex reality of the subject means not all relevant variables can be considered (Clarke, 2005), for example, items capturing cultural aspects were omitted. Furthermore, identified predictors, or their influence, may be affected by aspects that are not considered, leading to an endogeneity problem: omitted variable bias (Wooldridge, 2012). As an omitted variable might influence one or more further variables, multiple regression may erroneously identify a significant relationship between variables (Clarke, 2005;Wooldridge, 2012). On the other hand, the inclusion of irrelevant aspects can lead to an increase in the coefficient of determination R 2 (goodness-of-fit measure) without increasing the explanatory power of the model (Wooldridge, 2012).
Financial capacity was captured exclusively through subjective perceptions of financial problems; no objective measures were considered. This limited the available insight into clubs' financial situations. Moreover, the collected data may have been subject to bias, because the respondents were responsible for providing data for all endogenous and exogenous variables, this approach carried a risk of common method bias and erroneous conclusions (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Furthermore, the variables reflected the subjective perceptions of the respondents and the possible attempt to respond in a socially desirable manner. These biases could have been amplified by the fact that the SBR commissioned the survey. Possibly, the sports clubs sought to portray themselves more favorably or negatively than is in fact the case in order to try to demonstrate strength or overstate the seriousness of an issue to attract attention to a particular aspect (Thieme et al.,2017). Accordingly, the club's own perception of success could differ from the chosen method of capturing success. In addition, this cross-sectional study captured respondents' perceptions at a specific point in time, and was limited to clubs based in Rhineland, which reduced the overarching explanatory power.

Practical implications
Despite the above limitations, the results have practical implications for sports clubs, the SBR, and municipalities. First, organizations should be aware of the impact the board has on the problems encountered. It is advisable to prioritize the rapid replacement of retiring or resigning board members, and organizations should seek to recruit these replacements from the ranks of existing members (Thieme et al., 2017). Second, organizations should implement longterm strategies that act as guidelines for executive volunteers and (potential) members, and that help to prevent or re-solve discrepancies (Fink, 2020). Third, as the presence of paid staff is associated with more severe problems (which are not caused by more members and their higher heterogeneity of opinions), sports clubs should be mindful of the financing and training of paid staff. In addition, clear separation of duties between fulltime and volunteer staff could prevent emerging disagreements. Fourth, NPOs are encouraged to closely consider their finances, as financial stability supports organizations' continued existence. Financial problems could be avoided by diversifying revenue sources or by identifying and emphasizing key revenue sources, which can stabilize finances in the long term (Wicker & Breuer, 2013). To evaluate diversification, the Herfindahl index could be used, a statistical measure of concentration initially used to measure the market concentration of companies (Carroll & Stater, 2009).
The present findings indicate that sports facilities are another crucial aspect of performance. As organizations can rarely independently finance facilities, sports clubs should initiate communication with municipalities and professional associations to discuss subsidy programs or reduce conflicts arising from the use of communal facilities. Municipalities and professional associations should receive equal weight in this regard since both could offer support for sports clubs. Finally, as the OCF, because of its affordance of customization, can represent a useful tool for identifying strengths and weaknesses in NPOs and has been proven to identify success predictors for sports clubs, the SBR is encouraged to consider its use for informing advisory services.

Future research
Future research is needed to understand the complex influences on the performance of sports clubs as, in the present study, multiple regression only provided a low percentage of explained variance. Longitudinal studies provide more meaningful data on the development of resources (Elmose-Østerlund et al., 2021), facilitating the development of more precise conclusions. Further-more, as this study focused on internally collected data, future research should approach performance by including subjective and objective data from different stakeholder groups, for example, the inclusion of data capturing the club's own perception of success, volunteers' commitment and their motives or member satisfaction.
Regarding the results provided here, the lack of cooperation observed among sports clubs in Rhineland when compared to the findings of Wicker and Breuer (2011) should be investigated; however, this discrepancy may be due to the rural nature of Rhineland. Moreover, this paper contradicts previous findings regarding the connection between paid staff and problems, showing an additional focus for further investigation.