Organizational capacity building in non-profit sport clubs: exploring the role of competition as a capacity building stimulus

Figures & data

Table 1. Operationalization and summary stats of variables in the model.

Variable	Operationalization	Measurement	2011 Mean (SD)	2013 Mean (SD)	2015 Mean (SD)	2017 Mean (SD)	2020 Mean (SD)
Dependent Variables: Organizational capacity dimensions
HR: volunteers_capita	Total number of volunteers per capita	Metric	.089 (.123)	.140 (.197)	.149 (.210)	.149 (.173)	.178 (.528)
HR: paidstaff_capita	Total number of paid staff per capita	Metric	N/A	.005 (.026)	.016 (.039)	N/A	.010 (.126)
F: ln_revenue_capita	Logged total revenue per capita (in €)	Metric	.120 (.141)	.108 (.125)	.118 (.142)	.121 (.146)	.112 (.137)
F: ln_expenditure_capita	Logged total expenditure per capita (in €)	Metric	.118 (.139)	.106 (.123)	.116 (.140)	.120 (.145)	.110 (.136)
F: breakeven	Club has a positive revenue-expenditure account	Binary (1 = yes)	.778	.759	.765	.727	.738
P: strategy_dummy	Club has a strategic concept	Binary (1 = yes)	.539	.504	.504	N/A	N/A
I: own_facility	Club owns a facility	Binary (1 = yes)	.443	.450	.442	.389	.407
I: own_gym	Club owns a fitness gym	Binary (1 = yes)	.034	N/A	.033	.033	N/A
Independent variables: Organizational capacity building stimulus
comp_club	Level of perceived problem of competition from other clubs	Ordinal (1 = no problem, 5 = a very big problem)	1.948 (1.141)	1.978 (1.146)	1.918 (1.135)	N/A	N/A
comp_commercial	Level of perceived problem of competition from commercial sport providers	Ordinal (1 = no problem, 5 = a very big problem)	1.668 (1.026)	1.664 (1.017)	1.619 (1.005)	N/A	N/A
Control variables: Organizational characteristics
members_thd	Total number of members (in 1,000)	Metric	.310 (.561)	.333 (.882)	.303 (.495)	.286 (.470)	.324 (.509)
multisport	Club offers more than one sport	Binary (1 = yes)	.368	.545	.441	.466	.409
community_hthd	Number of inhabitants in the community (in 100,000)	Metric	2.136 (6.173)	1.848 (5.596)	1.826 (5.449)	1.906 (5.755)	2.026 (6.143)
year	Survey year (reference year: 2011)	Binary (1 = yes)	.161	.228	.216	.184	.212

Table 2. Results of the pooled OLS regression models (displayed are standardized coefficients with cluster-robust standard errors in parentheses).

	Model 1: volunteers_capita	Model 2: paidstaff_capita	Model 3: ln_revenue_capita	Model 4: ln_expenditure_capita
comp_club t-2	-.003 (.002)	-.000 (.000)	-.000 (.001)	.000 (.001)
comp_commercial t-2	-.004 (.003)^+	.001 (.001)*	-.000 (.001)	.000 (.001)
multisport t-2	-.077 (.007)***	-.001 (.000)	-.010 (.003)***	-.010 (.003)***
community_hthd t-2	.000 (.000)	.000 (.000)	-.000 (.000)	-.000 (.000)
volunteers_capita t-2	.068 (.060)	-	-	-
paidstaff_capita t-2	-	.189 (.039)***	-	-
ln_revenue_capita t-2	-	-	.931 (.033)***	-
ln_expenditure_capita t-2	-	-	-	.937 (.034)***
year	Included	Included	Included	Included
constant	.192 (.014)***	.004 (.001)***	.020 (.005)***	.018 (.005)***
F	36.67***	6.38***	320.65***	325.35***
R²	.0722	.0968	.7679	.7783
n (observations)	4897	1987	4023	3830

***p ≤ .001; **p ≤ .01; *p ≤ .05; ⁺p ≤ .1.

Table 3. Results of the logistic regression analysis (displayed are standardized coefficients with cluster-robust standard errors in parentheses).

	Model 5: strategy_dummy	Model 6: breakeven	Model 7: own_facility	Model 8: own_gym
comp_club t-2	-.119 (.062)^+	-.001 (.039)	.040 (.049)	.162 (.234)
comp_commercial t-2	.013 (.069)	-.088 (.044)*	.035 (.053)	-.338 (.302)
multisport t-2	-.285 (.144)*	.156 (.084)^+	-.432 (.104)***	.618 (.486)
community_hthd t-2	.011 (.009)	.002 (.006)	-.013 (.007)^+	.038 (.032)
members_thd t-2	.391 (.132)**	.166 (.080)*	.484 (.107)***	.719 (.153)***
strategy_dummyt-2	1.349 (.123)***	-	-	-
breakeven t-2	-	.402 (.086)***	-	-
own_facility t-2	-	-	4.113 (.102)***	-
own_gym t-2	-	-	-	4.658 (.429)***
year	Included	Included	Included	Included
constant	-.567 (.160)***	.657 (.120)***	−2.768 (.138)***	−5.028 (.634)***
−2LL	−775.09	−2,072.10	−1,673.63	−97.87
χ²	136.09***	39.27***	1800.36***	153.11***
Nagelkerke R²	.0891	.0096	.5007	.4785
n (observations)	1228	3631	4991	1265

***p ≤ .001; **p ≤ .01; *p ≤ .05; ⁺p ≤ .1.