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Daniel Weimar, Brian P. Soebbing, and Pamela Wicker

The identification of relevant effects is challenging in Big Data because larger samples are more likely to yield statistically significant effects. Professional sport teams attempting to identify the core drivers behind their follower numbers on social media also face this challenge. The purposes of this study are to examine the effects of game outcomes on the change rate of followers using big social media data and to assess the relative impact of determinants using dominance analysis. The authors collected data of 644 first division football clubs from Facebook (n = 297,042), Twitter (n = 292,186), and Instagram (n = 312,710) over a 19-month period. Our fixed-effects regressions returned significant findings for game outcomes. Therefore, the authors extracted the relative importance of wins, draws, and losses through dominance analysis, indicating that a victory yielded the highest increase in followers. For practitioners, the findings present opportunities to develop fan engagement, increase the number of followers, and enter new markets.

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Brian P. Soebbing, Pamela Wicker, and Daniel Weimar

Previous research has examined the effect of changes in upper management positions on actual organizational performance; however, the influence of leadership changes on performance expectations has been largely neglected. This gap in the literature is surprising given that failure to meet expectations leads to dismissal. The purpose of the present research is to analyze how coaching changes affect expectations of a sports team’s performance. Betting lines are used as performance expectations because they are unbiased forecasts of game outcomes. This study uses data from 13 seasons of the German Football Bundesliga. Significant positive timelagged effects on performance expectations are evident when examining underlying expected performance. These positive effects are evident 8 weeks after the leadership change, indicating that new leaders are expected to need some time before significant performance improvements are expected to occur.