What Makes Sports Clubs Successful at Recruiting and Retaining Members from the Perspective of Managers? Results from a Random Forest Analysis

The goal of this study is to investigate the relative importance of several predictors of nonprofit sports clubs’ success in recruiting new, and keeping existing, members from the perspective of club managers. Using a random forest analysis known from machine learning, the study takes into account relevant predictors of successful member recruitment and retention. Data were collected via a survey with managers from 284 German sports clubs. The results reveal that service quality and trust are the two most important predictors for recruiting and retaining members. Furthermore, innovation activity, among others, has positive effects on recruiting and retaining members. It also provides suggestive evidence for adverse effects of coopetition—that is, the collaboration with competitors—because high-level (vs. medium-level) collaboration with the clubs’ competitors had a negative impact on recruiting and retaining members. The study derives several implications for the customer relationship management in nonprofit sports clubs.