Interorganizational cooperation in sport tourism: A social network analysis

The author would like to thank Viviana Amati for her support and helpful comments in writing this paper.

Highlights

•	Network formation and mechanisms for interorganizational cooperation are analyzed.
•	Exponential random graph modeling for analyzing sport tourism networks is introduced.
•	Structurally central and peripheral network actors are identified.
•	Triad closure, network brokerage and aim homophily are significant mechanisms.
•	The results provide implications for managing sport tourism networks.

Abstract

Cooperation among organizations is crucial in many fields of sport management. However, little is known about how and why interorganizational cooperation occurs. In this study, cooperative relations among organizations were investigated in an informal sport tourism network in a German community and its surrounding area to explore the structure of interorganizational cooperation and demonstrate the value of social network analysis methods for understanding mechanisms of interorganizational cooperation. Statistical network analyses based on relational data revealed that the network of cooperation is sparse but characterized by substantial clustering, indicating a tendency for cooperation to occur in triangular structures. The most central network actor was a local sports agency, but there was no mechanism of preferential attachment. Other significant mechanisms for cooperative tie formation were brokerage and homophily regarding organizational aims. Lack of time and incompatible goals are the most important barriers to cooperation. The results add to prior qualitative studies and provide implications for managing sport tourism networks.

Keywords:

• Collaboration
• Coordination
• Destination management
• Tie formation
• Exponential random graph model

Notes

The author would like to thank Viviana Amati for her support and helpful comments in writing this paper.

1 See Borgatti et al. (2013), Wasserman and Faust (1994), or Hennig et al. (2012) for detailed introductions to SNA methodology.

2 Fourie and Santana-Gallego (2011) analyzed the impact of six different mega events (Summer and Winter Olympic Games, FIFA World Cup, Rugby World Cup, Cricket World Cup, British/Irish Lions Tour) from 1995 and 2006 and found that tourist arrivals in the hosting countries increased by 8.1%.

3 Due to ethical considerations, actual names and information from which analyzed actors and their identities could be inferred are not presented.

4 The software programs Ucinet (Borgatti, Everett, & Freeman, 2002), Visone (Brandes & Wagner, 2004), PNet (Wang, Robins, & Pattison, 2009a) and Microsoft Excel were used for data management and analysis.

5 The core business of the sports agency is event organization and marketing.