Network structure and governance in sport clusters: a mixed methods analysis

ABSTRACT

Research question

This study contributes to our understanding of how network structures influence cluster governance and consequently cluster outcomes. We investigate the relational structure of cross-sectoral sport clusters and how these influence network governance.

Research methods

We employed a mixed methods approach, combining qualitative research data and social network analysis (SNA). Forty-nine interviews were conducted with employees from the surfing clusters in Aquitaine (France) and Torquay (Australia). The interview transcripts were subjected to two rounds of coding prior to SNA on an aggregated actor level.

Results and findings

Findings from both show the core is comprised of five actor types, while five other actor types are peripheral. The French case is a Network Administrative Organisation-governed Network while the Australian case is a Leading Group-governed Network.

Implications

This article contributes to knowledge on network governance, more specifically on network governance in sport clusters. We extend existing theory on network governance by suggesting a fourth, intermediate mode of network governance, the leading group-governed network. Furthermore, our research provides insights for sport clusters, an under-researched context in interorganisational sport networks.

KEYWORDS:

• Network governance
• interorganisational
• sport cluster
• mixed methods
• network analysis

Disclosure statement

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

Notes

1 Sport clusters are ‘geographical concentrations of interconnected organisations that provide different products or services related to a sport, professional and amateur sport entities, sport-related education/ research institutes and governing bodies that exert control or influence over these organisations’ (Gerke et al., 2020, p. 201)

2 Brokerage in Social Network Analysis refers to a mechanism ‘whereby actors connect different components of the network’ that would be otherwise disconnected (i.e., structural holes) (Burt, 1992)

3 Middle-range theories bridge the gap between general theory and empirical findings as they have a lower level of abstraction than general theories (Brodie et al., 2011, p. 76)