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Sport policy Comparative analysis of the effectiveness of sport promotion networks Authors: Steffie Lucidarme*, Mathieu Marlier, Greet Cardon, and Annick Willem Institutions: Ghent University, Faculty of Medicine and Health Sciences, Department of Movement and Sport Sciences E-mail: *Steffie.lucidarme@ugent.be Theoretical background & aims In recent years networks appear everywhere in the public and non-profit sectors. Policy networks gained importance because they are considered to be an organizational form that can address ‘wicked’ problems (Jackson & Stainsby, 2000). From government’s perspective, networks are also more and more seen as a constructive managerial tool to improve cooperation between relevant agents, especially in service provision (Provan & Milward, 2001). Other factors that can lead to the creation of a network are sector failure, aiming to reduce the transaction costs and problems arising from bad coordination (McGuire & Agranoff, 2007). Networks are already fully integrated in health and social care, local development and education. In the sport sector, networks are also existing and worthwhile studying in dept, but until today they are hardly ever examined. What has been lacking most, is the empirically research of the relationship between the network properties and measures of effectiveness. The purpose of this paper is to empirically detect characteristics that influence the effectiveness of sport promotion network outcomes to address the existing research gap. This article hopes to bring new empirical insights to a research field that has been expanding the past decade, but where most work has been conceptual, anecdotal or based on a single descriptive case. Case description & research questions As mentioned before, the history of networks in sport is rather short. Therefore, it is quite difficult to find a sport related, good structured and mature cluster of networks to study empirically. In health promotion, these networks are more available. For this study, we have decided to work with health networks working on the promotion of physical activity. We are convinced that the approaches used in these networks are also suitable for the genuine sport sector. In 2009, the Government of Flanders provided funding for the implementation of a project called ‘10,000-Steps’ in the entire region (Van Acker, De Bourdeaudhuij, De Cocker, Klesges, & Cardon, 2011). This program was developed to stimulate people to be more physically active in all areas of life (transport, work, leisure) by encouraging them to take 10.000 steps a day (Van Acker, et al., 2011). Research has shown that adults should achieve at least 10.000 steps per day to improve health and well-being. The implementation of this project was guided through 13 existing regional networks, called the LOGO’s. For the project the LOGO’s were free select their partners. Considering the unique setting of 13 networks with common goals and a comparable compilation, but with their own approach and network specific characteristics, they form an ideal research set-up to find out more about the functioning of sport promotion networks and more precise which network determinants influence the realization of the network effectiveness. Methodology & data analysis Provan and Milward (2001) argue that network effectiveness should be measured through multilevel analysis. They suggest that networks are evaluated at three levels: the community, the network and the organization level. The community level was already evaluated in 2010 based on the RE-AIM model (Van Acker, et al., 2011). The evaluation at the network level and organization level was performed based on the theoretical model of Parent and Harvey (2009). The model contains 15 constructs that come under 3 groups: attributes of partnership, communication and decision making. Data were collected through semi-structured interviews with the 13 LOGO’s, which were audio-taped, transcribed and coded with NVivo software. During the data-collection, the importance of triangulation was kept in mind; therefore, additional information was gathered through document analysis and questionnaires. Results, discussion and implications/conclusions Preliminary results show a large influence of two exogenous on the functioning of almost all networks: the geographical reduction from 25 to 13 networks and a switch from a bottom-up to a top-down functioning. Networks have an average of 30 partners which are mostly local sport administrations, local welfare centres and primary health care organizations. A carefully-worded conclusion could be that the success factors are a strong identity, the communication between the different partners and the competences of the network staff. Some negative factors are the low responsibility of the network partners and the absence empowered people in the network partner organizations. We are aware that this study relates largely to the health and welfare sector, but taking into account that these sectors have more experience and the sport relevant content of the chosen project , we are convinced that our findings can benefit the functioning of other sport promotion and sport-for-all networks and bring new insights into the whole sport sector. References Jackson, P., & Stainsby, L. (2000). Managing Public Sector networked Organizations. Public Money & Management, 20(1), 11-16. McGuire, M., & Agranoff, R. (2007). Answering the Big Questions, Asking the Bigger Questions: Expanding the Public Network Management Empirical Research Agenda. Paper presented at the 9th Public Management Research Conference. Parent, M., & Harvey, J. (2009). Towards a Management Model for Sport and Physical Activity Community-based Partnerships. European Sport Management Quarterly, 9(1), 23-45. 100 Abstract book
Sport policy Provan, K., & Milward, B. (2001). Do Networks Really Work? A Framework for Evaluating Public-Sector Organisational Networks. Public Administration Review, 61(4), 414-423. Van Acker, R., De Bourdeaudhuij, I., De Cocker, K., Klesges, L. M., & Cardon, G. (2011). The impact of disseminating the whole-community project ‘10,000 Steps’: a RE-AIM analysis. BMC Public Health, 11(3). www.easm2012.com 18-21 September 2012, Aalborg, Denmark 101
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