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.
Daniel Weimar, Brian P. Soebbing, and Pamela Wicker
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.
Katherine Sveinson, Larena Hoeber, and Caroline Heffernan
Critical discourse analysis (CDA) is a theory, methodology, and type of analysis used across various fields, including linguistics, sociology, and philosophy. CDA focuses on how language is used; discourses are found within language, and knowledge is created through these discourses. CDA can be beneficial to sport management scholars who seek to question existing power structures. The purpose of this paper was to highlight the value and appropriateness of CDA for Journal of Sport Management readers in an effort to see this approach become more prevalent in the journal. The authors shared their perspectives about the lack of critical qualitative methodologies in Journal of Sport Management, presented theoretical foundations of CDA, showcased its application in sport management studies, and explored four theoretical, methodological, and analytical approaches for future use. The authors also provided suggestions for scholars to adopt discourse-related methodologies to enhance knowledge creation in their field. Finally, the authors acknowledged the limitations of this approach.
Jason Doyle, Kevin Filo, Alana Thomson, and Thilo Kunkel
Delivering community-based benefits is oftentimes cited to justify the high costs associated with hosting large-scale events. The current research is embedded in positive psychology to examine how an event impacts host community members’ PERMA domains, reflected through positive emotions, engagement, relationships, meaning, and accomplishment. Adopting a longitudinal approach, the authors interviewed 15 host community members before and after a large-scale sport event to determine if and how the event impacted their well-being. The findings uncovered evidence that the event activated positive emotions, relationships, and meaning across both phases, and evidence of accomplishment within the postevent phase. The findings contribute to the knowledge by examining the links between large-scale sport events and well-being throughout the event lifecycle. This research forwards implications for event bidding committees, event organizers, and host community officials to maximize community well-being through hosting large-scale events and to help justify associated expenses from a social–psychological perspective.
Markus Schäfer and Catharina Vögele
Content analysis is a popular method in communication and media research. However, to what extent and in which contexts it is used in sport communication research has hardly been investigated. In order to provide empirically grounded insight, the authors conducted a quantitative content analysis of scholarly journal articles using content analysis as a research method, focusing on three major international sport communication journals during the 10 years between 2010 and 2019 (N = 267). Results indicate that qualitative and quantitative methods are used equally while combinations with other methods are comparatively rare. The studies cover a broad portfolio of different topics. Social media as communication channels becomes an increasingly central issue of scientific exploration. Although the studies deal with 31 different sports in total, most of them focus on popular team sports such as football, basketball, soccer, baseball, and ice hockey.
This paper explores how emotional cues from unexpected sports outcomes impact consumers’ perception of their experience at local businesses. Using nearly 1 million Yelp reviews from the Phoenix area, I empirically test for the presence of loss aversion and reference-dependent preferences in reviewer behavior. Consistent with loss aversion, unexpected losses lead to worse reviews while there is no effect for unexpected wins. The impact of unexpected losses is concentrated in home games, with no effect for away games. The results also reflect reference-dependent preferences since wins and losses in games predicted to be close do not impact reviewer behavior. Consumer services that cater to National Basketball Association fans (e.g., sports bars) experience pronounced effects.
Hua Gong, Nicholas M. Watanabe, Brian P. Soebbing, Matthew T. Brown, and Mark S. Nagel
The use of big data in sport and sport management research is increasing in popularity. Prior research generally includes one of the many characteristics of big data, such as volume or velocity. The present study presents big data in a multidimensional lens by considering the use of sentiment analysis. Specifically focusing on the phenomenon of tanking, the purposeful underperformance in sport competitions, the present study considers the impact that consumers’ sentiment regarding tanking has on game attendance in the National Basketball Association. Collecting social media posts for each National Basketball Association team, the authors create an algorithm to measure the volume and sentiment of consumer discussions related to tanking. These measures are included in a predictive model for National Basketball Association home game attendance between the 2013–2014 and 2017–2018 seasons. Our results find that the volume of discussions for the home team and sentiment toward tanking by the away team impact game attendance.