Artificial intelligence (AI) has the capacity to deliver generative, complex, and powerful functions and decisions. Sport offers a unique site for AI development and implementation, yet the sociological significance of AI in sport remains understudied. We consider sport-based AI applications en route to describing the promise of AI in sport in four ways: (a) the promise of supercharged data parsing at scale, (b) the promise of supercharged precision, (c) the promise of supercharged personalization; and (d) the promise of supercharged prediction. We argue in turn that AI is an emergent cultural form in sport that foregrounds labor automation as a pathway to efficiency but also brings potential for substantial disruption. We further contend that sport is a use case for AI at a moment when the legitimacy of AI is intensely debated.

As sport organizations leverage social media as a critical component of marketing strategy, tools for exploring the large volume of sport consumer social media conversations are vital. This scholarship demonstrates the value of unsupervised latent Dirichlet allocation (LDA) as a tool for exploring consumers' digital conversations. Specifically, unsupervised LDA was applied to derive latent topics among Women's National Basketball Association -related Twitter conversation over the course of the 2020 season. Quantitative (cv and umass scores) and qualitative (two expert reviews) approaches were utilized to delineate topic configurations. Marginal topic distance established topic importance. Results from 118,518 tweets revealed 18 conversation topics spanning two overarching themes: social justice issues and on -court performance. The range and depth of the results highlight the importance of the unsupervised topic modeling method (without semi -supervised predetermined topic leads) for considering holistic rather than subsampled or snapshot datasets. This empirical investigation extends the conversation surrounding natural language processing to sport management research and practice, delivers a foundation for unsupervised LDA application to sport consumer conversation, and explores social media conversations during a critical moment for the WNBA.

Professional sport facility sustainability initiatives offer sport organizations an opportunity to demonstrate congruence with societal concern for the environment, an effort that also affects stadia revenue generation. Guided by diffusion of innovations theory, this study harnessed diffusion modeling and logistic regression to determine how quickly renewable energy source adoption is diffusing across 175 professional sport stadia in the United States and Canada and the factors catalyzing early renewable energy source adoption. Results revealed 86 (49%) facilities adopted at least one type of renewable energy source, with solar emerging as the predominant technology adopted (68 total adoptions). Full diffusion for renewable source adoption was predicted for 2061 ( p = .0094, q = 0.1404, root mean square error = 3.25, mean absolute error = 2.51), while not all renewable energy sources were predicted to fully diffuse (wind; p = .0117, q = −0.0710, root mean square error = .853, mean absolute error = 0.675). New stadia construction during the time of adoption, facility type, and geographical social systems emerged as significant factors catalyzing adoption in the early majority.

The purpose of this study was to analyze the diffusion of one sport innovation to forecast a second. Contextualized within the diffusion of innovations theory, this study investigated cumulative business analytics diffusion as an analog for cumulative natural language processing (NLP) diffusion in professional sport. A total of 89 teams of the 123 teams in the Big Four North American men’s professional sport leagues contributed: 21 from the National Football League, 23 from the National Basketball Association, 22 from Major League Baseball, and 23 from the National Hockey League. Utilizing an analogous forecasting approach, a discrete derivation of the Bass model was applied to cumulative BA adoption data. Parameters were then extended to predict cumulative NLP adoption. Resulting BA-estimated parameters ( p = .0072, q = .3644) determined a close fit to NLP diffusion (root mean square error of approximation = 3.51, mean absolute error = 2.98), thereby validating BA to predict the takeoff and full adoption of NLP. This study illuminates an ongoing and isomorphic process for diffusion of innovations in the professional sport social system and generates a novel application of diffusion of innovations theory to the sport industry.

Abstract:Social media has become an important frontier in the sport sponsorship paradigm (Dees, 2011), offering brands a powerful mechanism to stimulate consumer engagement (Vale & Fernandes, 2018). Despite this potential, the extent to which social media content, as part of a sport sponsorship’s leveraging activities, can yield consumer engagement behaviors is unknown. Thus, the purpose of this study was to examine the impact of integrating sponsors into the social media posts of sport organizations on fan engagement. A total of 13,542 Instagram posts from four professional sports teams were extracted from 2017–2019. A regression analysis revealed that sponsored content negatively affected engagement levels. Consequently, brands need to be more cognizant that simply sponsoring content in an inauthentic, forceable manner may not yield the results they are seeking through their association. Furthermore, sport organizations need to reconsider their social media strategy, working with partners to organically embed sponsors into content.

Framed by the diffusion of innovations theory, this paper explored the adoption of natural language processing (NLP) in professional sport. NLP, the ability for computer algorithms to be trained for pattern recognition in text data, is of key interest given the surge in text data available for sport business use. Ninety-one teams (73.98%) from the "Big Four" North American professional sports leagues: the National Football League (NFL; 68.75%), the National Basketball Association (NBA; 76.67%), Major League Baseball (MLB; 73.33%), and the National Hockey League (NHL; 77.42%) participated. A multiple methods approach utilizing a discrete derivative of the Bass model, integrative literature review and qualitative description uncovered the mechanisms, timing and key influences surrounding NLP diffusion. The findings highlight NLP diffusion at near peak adoption for the professional sport industry, reveal the organizational influences catalyzing the adoption timing, and create the context for academics and practitioners to embrace NLP.

The sport industry is no stranger to the pursuit of innovation (Slack & Thurston, 2021). The sport analytics realm represents the continual emergence of innovation diffusion curves. This essay shows how innovating both research and education in response to diffusion curves in sport analytics, we can create the space to not only keep but also generate pace.

Successfully adopting sport business analytics to enhance organization-wide business processes necessitates a combination of business acumen, modeling expertise, personnel coordination, and organizational support. Although the development of technical skills has been well mapped in analytics curricula, informing future leadership and affiliated nontechnical personnel about the sport business analytics process, specifically, remains a gap in sport management curricula. This acknowledgment should compel sport management programs to explore strategies for sport analytics training geared toward this population. Guided by experiential learning and foundational business analytics frameworks, a seven-module approach to teaching sport business analytics in sport management is advanced with a particular focus for future executives, managers, and nontechnical users in the sport industry. Concomitantly, the approach presents learning goals and outcomes, sources for instructors to review and consider, and sample assessments designed to fit within the existing sport management curricula.

Current accounting methods in intercollegiate athletics make it difficult for leaders to assess and understand the true cost of each sport team operations. Institutional and athletics leaders often make decisions concerning sport sponsorship/offerings, budget allocations, overall program operations, and review Title IX compliance based on information that may not truly capture the cost of each sport. Additionally, intercollegiate athletics reform groups and the federal government are calling for athletic departments to report more consistent, accurate, and transparent financial data. The purpose of this paper is to respond to the call for accounting reform in intercollegiate athletics via an innovative application of activity-based costing (ABC) to one NCAA Football Bowl Subdivision (FBS) athletics department. ABC was applied to the athletic department budget report with results showing how previously established ABC cost drivers for intercollegiate athletics (Lawrence, Gabriel, & Tuttle, 2010) and reallocation of expenses back to specific sports allow for a greater understanding of the cost of each sport.

Purpose Although sports fans have increased their use of digital media to consume sport, especially at professional sport venues, it is unknown the extent to which patrons of said venues are utilizing venue services for these activities. As such, this study asks: (1) How much data do patrons at a sports venue consume via the provided Wi–Fi? and (2) What types of online activity behaviors do Wi–Fi users at sports venues exhibit? Design/methodology/approach This empirical study reports stadia Wi–Fi data usage and consumer behavior from three National Basketball Association venues in the United States: Amway Center in Orlando, FL, Barclays Center in Brooklyn, NY and Target Center in Minneapolis, MN, over a course of 7 games per venue. Findings The findings suggest that Wi–Fi usage is more limited than anticipated. Users who do utilize the venue Wi–Fi do so for very short periods, with the vast majority of user duration lasting between 1 and 10 min. Additionally, the halftime period of games experiences the peak of Wi–Fi usage. Originality/value By increasing our understanding of Wi–Fi usage in venues, this study informs relationship marketing theory research and contributes to the sport management literature. Practically, a better knowledge of Wi–Fi usage is critical, as it constitutes a critical antecedent to develop online marketing strategies.

The sport industry has become increasingly more complex with the expanse of digital technology such as fiber optic internet access, 5G wireless communication, and blockchain, just to name a few. These advancements have shifted the amount and variety of data produced and available for analysis by sport organizations. Yet, sport organization front offices remain well behind other industry segments (e.g., retail, communications) in regard to handling, processing, and analyzing the volume and variety of data to advance business objectives. In this brief, we introduce the notion of artificial intelligence (AI) to sport management. While AI, as a concept, has been discussed for more than 50 years, this article provides a definition and overview of its historical trajectory for sport managers. Concurrently, the article also identifies the value proposition for AI capability, notably the natural language processing across four customer-centered domains: 1) listening to the public narrative, 2) automating the sales process, 3) computerized consumer content, and 4) self-operating service. Integration challenges are also addressed for sport organizations as they seek to increase their digital competence, achieve competitive advantage through technical innovations, and ultimately become more efficient in a data-driven world.

While managing the intercollegiate athletic development office is critical to contributions generation, the nearly 40 years of research modeling intercollegiate athletic fundraising emphasized limited factors external to this department. Both theoretical and statistical justification warrants a broader scope in contemporary factor identification. With a resource-based view as the theoretical foundation, a list of 43 variables both internal and external to the intercollegiate athletic development office was generated through an extensive literature review and semistructured interviews with athletic and nonathletic fundraising professionals. Based on the factors identified, random and fixed effects regression models were developed via test statistic model reduction across a 5-year panel (FY2011–FY2015). Ninety-three schools were included, representing 73% of the Football Bowl Subdivision (FBS) membership (85% of public FBS institutions). The results highlight the role of both internal and external factors in explaining intercollegiate athletic fundraising procurement.

Experiential learning is a critical component of sport management education and industry preparation; however, the inclusion of time-intensive experiential projects can displace content learning. Blended learning integrates face-to-face and online instruction to enable the space to maximize multiple learning types. This article proposes an innovative experiential project that integrates blended learning-implemented in a sport event management course-with reflection and scholarship supporting the pedagogical strategies. The article concludes with implications to optimize blended learning (e.g., multimedia, pedagogical workshops, course evaluation), enhance communication (e.g., office hours, discussion forum, orientation video), and expand student learning outcomes (e.g., reading outlines, video lectures, student assessment).

Despite the increased adoption of data-driven strategies to enhance sport business operations, academic scholarship leveraging advanced analytics to inform sport customer relationship management lags behind. Thus, this project applies survival analysis modeling to quantitatively analyze and predict the potential dissolution of the intercollegiate athletic department-donor relationship, utilizing 10 years of data from a mid-sized National Collegiate Athletic Association (NCAA) Football Bowl Subdivision (FBS) athletic program. Results indicate donors are most susceptible to dissolution within the first two years, while the probability of persistence increases over time. When controlling for economic conditions and the amount donated, residing in the same state as the institution and the act of retiring decrease the probability of the donor relationship ending. The frequency of contact from the athletic department and the advancement of men's basketball into post-season play also decrease the probability of relationship dissolution, while football post-season success was non-significant. Study results inform a data-driven approach to donor relationship marketing and provide meaningful implications for athletic donor retention strategy.

The purpose of this investigation was to identify best practices in intercollegiate athletic donor relations for the National Collegiate Athletic Association (NCAA) Football Bowl Subdivision (FBS). Neither philanthropy research nor athletic fund-raising research presents a contemporary model of donor relations best practices. Additionally, athletic development tactics are given little attention in evidence-based literature. To investigate this topic, three rounds of the Delphi method were completed by 17 intercollegiate athletic development directors in the FBS. Forty-two best practices for donor acquisition and 38 best practices for donor retention and upgrade emerged. Implications for intercollegiate athletic development campaigns are addressed. Subscribe to JASM