Sports clubs in different levels of professionalisation show different organisational problems (Lang et al., 2022). At the same time, one part of the key responsibilities of sports federations as umbrella organisations is the needs-based support of voluntary sports clubs (VSC) as their members. However, different professionalisation levels and heterogeneous organisational problems of member clubs are increasingly challenging the design of appropriate service offerings by sports federations. Thus, services provided by sports federations should be adapted in relation to the expectations and needs of its member clubs. In this way sports clubs also effects with their expectations developments within sports federations to optimise their supporting services in a more targeted manner. This study addresses these challenges by analysing VSCs’ expectations and identify distinct expectation types. The empirical study was carried out in a regional sports federation in tennis, the Bavarian Tennis Federation (BTV). This leads to the research questions: What expectations do VSCs as members generally address to the BTV? To what extent can VSCs be classified in terms of their expectations regarding BTV services? To address these expectations, the performance measurement literature provides a fruitful theoretical frame. In order to base appropriate performance parameters, stakeholders’ expectations need to be identified ex ante (Bayle & Madella, 2002). In the literature it is consensus that measuring the performance of sports federations requires a multidimensional approach (e.g., Winand et al., 2010). To analyse expectations of VSCs an online survey was conducted. Access to the survey was given to BTV member club representatives in a leadership position. For operationalisation, an exploratory factor analysis was performed, which shows the best solution with six reliable factors. The identified factors were used for Ward’s hierarchy cluster analysis with squared Euclidean distances. The analysis showed that an optimal cluster solution can be determined with four clusters. Based on the z-standardised factor values the identified clusters were labelled as follows: (1) “People developer” (n = 57, 32%); (2) “Mass sports clubs” (n = 39, 22%); (3) “Self-governmenters” (n = 40, 23%) and (4) “High expecting communicators” (n = 41, 23%). For validation, the extracted clusters are also reflected by other characteristics of the organisations. The findings reveal that there are heterogeneous expectations of VSCs that need to be addressed more individually by sport federations. The extracted types provide a first empirical step to identify different expectation schemes. These schemes enable managers of sports federations to professionalise their service offer portfolio and at the same time, to design targeted services to contribute to the development and professionalisation of sports clubs.
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