‘Girls just want to have fun?’ Sex differences in motives of watching the FIFA World Cup and the UEFA European Championship

With global media attention and a global reach, mega-sporting events play a crucial role in sports communication. Although the audience of these events has traditionally been overwhelmingly male, in recent years they have attracted an increasing number of women. The present paper therefore explores women’s and men’s motives for watching three mega-sporting events – FIFA World Cup 2006, the UEFA European Championship 2008 and FIFA World Cup 2010 – and compares the intensities of the three central motives of thrill, entertainment and information, especially as they relate to participants’ levels of general interest in sport. The results indicate that as their interest in sport increases, the differences between the motives of women and men decrease. This finding provides valuable initial insights into the increasing popularity of mega-sporting events among women.     

An Adaptive Bayesian Lasso Approach with Spike-and-Slab Priors to Identify Multiple Linear and Nonlinear Effects in Structural Equation Models

In applied research, such as with motivation theories, typically many variables are theoretically implied predictors of an outcome and several interactions are assumed (e.g., Watt, 2004). However, estimation problems that might arise when several interaction and/or quadratic effects are analyzed simultaneously have not been investigated because simulation studies on interaction effects in the structural equation modeling framework have mainly focused on small models that contain single interaction effects. In this article, we show that traditional approaches can provide estimates with low accuracy when complex models are estimated. We introduce an adaptive Bayesian lasso approach with spike-and-slab priors that overcomes this problem. Using a complex model in a simulation study, we show that the parameter estimates of the proposed approach are more accurate in situations with high multicollinearity or low reliability compared with a standard Bayesian lasso approach and typical frequentist approaches (i.e., unconstrained product indicator approach and latent moderated structures approach).