Analyzing the impact of sport infrastructure on sport participation using geo-coded data: Evidence from multi-level models Pamela Wicker a, *, Kirstin Hallmann b , Christoph Breuer b a Department of Tourism, Leisure, Hotel and Sport Management, Griffith University, Gold Coast Campus, Parklands Drive, Southport, Queensland 4215, Australia b Institute of Sport Economics and Sport Management, German Sport University Cologne, Am Sportpark Muengersdorf 6, 50933 Cologne, Germany 1. Introduction Policies in several countries such as the UK, Australia, and China aim at increasing mass participation in sport and sport participation on a club level (Cabinet Office, 2002; Downward, Dawson, & Dejonghe, 2009; Downward & Rasciute, 2010; Sotiriadou, 2009; Xiong, 2007). Within these policies, the importance of sport infrastructure (sport facilities) for sport participation has been stressed. In the UK, several sport policies have been implemented and sports councils such as Sport England have been founded to address this issue (for an overview of the UK sport policy see Downward et al., 2009; Downward & Rasciute, 2010). In 2002, the Game Plan was introduced where increasing grassroots participation was one of the four main policy goals. According to the Game Plan, all barriers to individual participation (e.g., lack of time and cost) should be tackled as well as failures in provision (facilities). It was recognized that there was ‘‘a pressing need to increase the Sport Management Review 16 (2013) 54–67 A R T I C L E I N F O Article history: Received 30 November 2011 Received in revised form 3 May 2012 Accepted 4 May 2012 Keywords: Sport activity Sport facilities Gauss–Krueger coordinates Hierarchical model Multi-level analysis A B S T R A C T Sport policies aiming at increasing mass participation and club participation have stressed the importance of sport infrastructure. Previous research has mainly analyzed the influence of individual factors (age, income, etc.) on sport participation. Although a few studies have dealt with the impact of sport facilities on sport participation, some methodological shortcomings can be observed regarding the integration of sport infrastructure into the research design. Oftentimes, subjective measures of infrastructure are employed, leading to biased results, for example inactive people have a worse perception of the actual supply of facilities. In fact it is important to measure the available sport infrastructure objectively using a quantitative approach and integrate it into statistical models. Therefore, the purpose of this study is to analyze the impact of individual and infrastructure variables on sport participation in general and in sport clubs using geo-coded data following a multi-level design. For this purpose, both primary data (individual level) and secondary data (infrastructure level) were collected in the city of Munich, Germany. A telephone survey of the resident population was carried out (n = 11,175) and secondary data on the available sport infrastructure in Munich were collected. Both datasets were geo-coded using Gauss–Krueger coordinates and integrated into multi-level analyses. The multi-level models show that swimming pools are of particular importance for sport participation in general and sport fields for participation in sport clubs. Challenges and implications for a more holistic modeling of sport participation including infrastructure variables are discussed. ß 2012 Sport Management Association of Australia and New Zealand. Published by Elsevier Ltd. All rights reserved. * Corresponding author. Tel.: +61 7 555 28552; fax: +61 7 555 28507. E-mail address: p.wicker@griffith.edu.au (P. Wicker). Contents lists available at SciVerse ScienceDirect Sport Management Review jo u rn al h om ep age: w ww.els evier.c o m/lo c ate/s mr 1441-3523/$ – see front matter ß 2012 Sport Management Association of Australia and New Zealand. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.smr.2012.05.001