The purpose of this study was to investigate how Donald Trump used Twitter to position sport within the greater sociopolitical landscape. An inductive analysis of Trump’s sport-related tweets revealed four themes including (a) sport as self-promotion, (b) sport as fandom, (c) sport as battleground, and (d) sport as American identity. This study found that Trump positioned sport as a status symbol. In doing so, he leveraged his power, wealth, and connections to the industry to belittle and champion sport entities. Trump simultaneously leveraged Twitter to display how sport relationships can further one’s business ventures and build a personal brand. In addition, Trump’s discourse shifted sport away from fulfilling a central role in society, as a beacon where social inequities can be critiqued and perhaps elevated into the public consciousness.
Evan Frederick, Ann Pegoraro, and Jimmy Sanderson
Éric Claverie, Julien Krier, and Jean-François Loudcher
Cette recherche se propose d'éclairer la renaissance d’une fédération affinitaire sous la Quatrième République française, l’UFOLEP. Elle met l’accent sur les difficultés de reconstruction, puis sur la réussite à trouver un espace de développement. Celui-ci prend la voie de l'école élémentaire, par le biais de son ancienne commission scolaire : l’USEP. Dans ce cadre parascolaire, qui rayonne peu à peu à l’enseignement de l’EPS lui-même, l’USEP développe des innovations conformes à son éthique en faveur d’une éducation physique et d’un sport éducatif protégé des voies fédérales classiques. Cette orientation sportive (et non voie) s’accorde bien avec le registre doctrinal de la Ligue de l’Enseignement qui héberge ce mouvement sportif, autour d’une idée laïque repensée dans cette France d’après-guerre. En revanche l’UFOLEP peine à développer sa voie postscolaire qui, après s'être redressée, stagne.
Nancy L. Malcom, Shaun Edmonds, Christina Gipson, Caitlyn Hauff, and Hannah Bennett
While there have been dramatic increases in women’s participation in sport and physical activity following the implementation of Title IX in the United States, many women still face challenges negotiating societal expectations of femininity with the muscularity developed through exercise. In this study, the authors used focus group interviews with 47 women who participate in CrossFit to explore how female athletes understand their developing athletic identity through social interactions. Even as the participants expressed high levels of self-confidence and personal growth, which they attributed to their instrumental involvement with CrossFit, their discussions of what other people think of their nontraditional fitness activities and concomitant body changes were a constant source of frustration. Using the identity-building framework of Cooley’s theory of the looking glass self, the authors find that women are faced with not merely reflections, but distorted funhouse mirrors; reflections that are heavily warped by gendered patriarchal societal norms. Surrounded by an array of potentially confusing and distracting “funhouse” mirrors, these female athletes used CrossFit’s local and expanded community, as well as their own burgeoning self-efficacy, to navigate their changing bodies and identities.
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.
Adam Karg, Jeremy Nguyen, and Heath McDonald
Predicting attendance at events is important for efficient facility management and marketing to maximize crowds. Most work to date is conducted at the aggregate level; however, the large crowd size being predicted often means important individual decisions are masked. In many markets, increased nonattendance by season ticket holders (STHs) is being reported, which is troubling given they have prepaid and are expected to be highly loyal. To understand who attends, rather than just how many, the authors analyze the “no-show” behavior of over 5,900 individual STH of one professional team over a season. Results show that in addition to game viewing and quality conditions, age, tenure, expenditure, and prior game attendance are predictors of individual attendance decisions, with differences in how individuals are influenced by winning and uncertainty of outcome. The paper expands understanding of drivers of STH attendance decisions and provides guidance toward managerial strategies for STH management.
Nicholas M. Watanabe, Stephen Shapiro, and Joris Drayer
Big data and analytics have become an essential component of organizational operations. The ability to collect and interpret significantly large data sets has provided a wealth of knowledge to guide decision makers in all facets of society. This is no different in sport management where big data has been used on and off the field to guide decision making across the industry. As big data evolves, there are concerns regarding the use of enhanced analytic techniques and their advancement of knowledge and theory. This special issue addresses these concerns by advancing our understanding of the use of big data in sport management research and how it can be used to further scholarship in the sport industry. The six articles in this special issue each play a role in advancing sport analytics theory, producing new knowledge, and developing new inquiries. The implications discussed in these articles provide a foundation for future research on this evolving area within the field of sport management.
Timothy D. DeSchriver, Timothy Webb, Scott Tainsky, and Adrian Simion
The impact of sporting events on local economies has been a focus of academic research for many years. Sporting events create externalities within the local economies in the form of spillover effects. This study investigates the role of Southeastern Conference collegiate football games on local hotel demand from 2003 to 2017. Fixed effects models are used to expand upon previous research by incorporating six data sources to analyze the impact of team, game, hotel, and market characteristics on hotel performance. Results indicate that the demand for hotels varies greatly according to team and opponent quality. A number of sport marketing, sport economics, hospitality, and tourism management implications are discussed for universities and industry in their communities regarding scheduling and the potential for revenue growth.
Vered Elishar-Malka, Yaron Ariel, and Dana Weimann-Saks
The World Cup is among the most popular televised sport events. This case study examined how enjoyment from and transportation into World Cup broadcasts affected WhatsApp use on a second screen. The authors hypothesized a negative correlation between World Cup enjoyment and WhatsApp use (both match related and unrelated), mediated by transportation into the match. Based on an online survey of 454 participants, they found that the more enjoyment the viewers experienced, the less they used WhatsApp for non-match-related purposes and (contrary to their hypothesis) the more they used it for match-related purposes. It was also found that the more enjoyment viewers experienced, the more transported they were into the match, leading to higher match-related and lower non-match-related WhatsApp use.