Commercial fitness centres in Denmark: a study on development, determinants of provision and substitution effects

ABSTRACT

The commercial fitness sector in Denmark has boomed over the last decades. The number of for-profit fitness centres has risen from around 350 in the 2000s to more than 800 in 2018. This development indicates that many Danes are now customers of commercial sport for all fitness programmes. In response to this, the non-profit sector in Denmark has started its own fitness activities, giving rise to debates about fair competition. In this paper, we aim to identify the determinants for the provision of for-profit fitness and potential substitution effects between non-profit and for-profit providers of sport for all leisure activities. By deploying regression modelling on cross-sectional data, we find that the presence of non-profit fitness centres does not seem to affect the provision of commercial ones. This indicates that non-profit and commercial sport for all leisure organisations in Denmark have supplemented each other to the benefit of overall sport participation.

KEYWORDS:

• Fitness centres
• substitution effects
• leisure
• Denmark

Acknowledgements

The authors would like to thank the anonymous reviewers and the associate editor for their constructive comments on earlier drafts of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 In the context of this paper, commercial fitness centres are providers of a broad set of leisure physical activities. However, the activities are mainly related to weight training, spinning, aerobics and CrossFit. Some offer running as well.

2 This will be discussed further in the following section.

3 Some studies (e.g. Hallmann, Feiler, and Breuer 2015) have looked at substitution effects at the individual level, but not at the organizational level as is done here.

4 It is important to stress that as we only have cross-sectional data at hand, and no panel data (derived from repeated observations over time), we are only able to identify some relationships that can be further tested when relevant time series data become available.

5 It should be noted that some studies (e.g. Meltzer and Jena 2010) find that higher income groups increase the intensity of their training to compensate for the reduced amount of time they have to exercise.

6 Today this law is called ‘The Act on Non-formal Education and Democratic Voluntary Activity’ (In Danish: ‘Folkeoplysningsloven’). https://ec.europa.eu/epale/en/resource-centre/content/act-non-formal-education-and-democratic-voluntary-activity

7 Priests were employed as civil servants because they were capable of reading and writing.

8 Statistics Denmark is the official public Danish statistics organization. We thank Henrik Husoom from Statistics Denmark for providing us with the parish level database used in this study.

9 Statistics Denmark has data representing five levels of education. We have therefore structured our education variable into five categories, with each being entered into our models as independent variables: Post-doc. & PhD (18–20 years of education), Master (15–17 years of education), Bachelor (13–15 years of education), High school (10–1 of education), and Primary school (9–10 years of education (left out as reference). Each category measures the share of people in the respective parishes based on the individual’s highest level of degree (e.g. if a person has a Master as her highest level of education, then she is part of the share (variable) calculated Master. If a person has a Bachelor as her highest degree, then she is part of the share (variable) calculated for bachelors and so on). The equation for each variable reads: Share=number of inhabitants with the given (highest) degree in the parish/total amount of inhabitants in the parish. The share is calculated in percentages.

10 All per capita values related to centres have been multiplied with 10,000 in order not to get very small coefficient values in the regressions.

11 Such debates are not present in relation to other types of public facilities or services. The fitness sector in Denmark is young and primarily concerned with what is argued to be publicly subsidized activities that the commercial centres see as similar, and thus in direct competition with their own services and products.

12 Collinearity statistics are provided in the appendix: Table A1.

13 In Model 3, PupSpend is significant at the 10%-level.

Additional information

Notes on contributors

Rasmus K. Storm

Rasmus K. Storm - @RasmusKStorm - holds a position as Head of Research at the Danish Institute for Sports Studies (Idan.dk). Moreover, he is Adjunct Associate Professor (20%) at NTNU Business School. He has managed several research projects on Danish elite sport, edited five books on sport, and has published in a variety of international sports science and sport management journals.

Benjamin Ove Riise Hansen

Benjamin Ove Riise Hansen is bachelor in economics and currently working as research assistant at the Danish Institute for Sports Studies.