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The authors integrate the established literature on corporate entrepreneurship with the expanding inquiry into sport entrepreneurship by examining professional teams and leagues across North America. By situating the discussion in the context of organizational theory on competition, the authors argue for how teams (contestants) and leagues (organizers) uniquely apply the different forms of corporate entrepreneurship, providing contemporary examples of each. Additionally, the authors identify notable challenges of entrepreneurship within a sport context, emphasizing components that allowed organizations to overcome these concerns. By shining a light on the occurrences and challenges of corporate entrepreneurship within the sport industry, the authors hope to continue the push for greater interest in and examination of sport-related innovation and entrepreneurship.

This work researches and shares numerous examples across the North American sport landscape to illustrate corporate innovation and venturing by sport entities.

This research identifies innovation, sourced from different competitive actors, involving new products, new services, new processes and new administrative structures and approaches, and even includes the development of new businesses.

In looking at the entrepreneurial efforts of established sport teams and leagues, the authors highlight the impressive efforts of these entities to innovate, grow and evolve their products, service offerings and markets despite unique industrial constraints.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

As artificial intelligence (AI) continues to influence sports league and team operations, the brands providing these services are sponsoring sports properties to demonstrate and communicate their performance capabilities. This article examines Amazon Web Services (AWS) sponsorship with the National Football League (NFL). This sponsorship features functional congruence, which is when a sponsor has a participatory role in performing services for the property.

The AWS sponsorship with the NFL is captured by examining specially created websites, in-game sponsored elements, and television commercials aired during the broadcast of NFL games. The AWS website focuses on the services profiled in this article.

AWS provides the NFL with performance-based (on-the-field) and business-based (off-the-field) services. Of particular note, AWS capabilities help the NFL create the game schedule and address the issue of player health and safety. Demonstrating functional congruence appears to be especially valuable in business-to-business marketing where purchase decisions are more focused on brand reliability. AWS television commercials feature the tagline, “if AWS can do this for the NFL, imagine what it can do for your business.”

With the role of AI in sports in its relative infancy, it is imperative to document what services AI brands are performing for a professional sports league. Examining AWS sponsorship with the NFL provides a timely, practical example of how an AI brand communicates and positions itself using sponsorship as a marketing strategy.

Previous studies focused predominantly on wage dispersion within men’ sports teams. This study aims to reveal how the relationship between wage dispersion and team performance applies for women’s sport.

The sample comprises 168 observations of four consecutive National Basketball Association (NBA) and Women’s National Basketball Association (WNBA) regular seasons (2018–2021). Eight econometric models are performed for comparing the leagues.

The findings indicate that the wage dispersion within the squads affects the women’s and men’s basketball teams differently. Cohesiveness theory is applicable for WNBA teams, while NBA teams follow the tournament theory.

To the best of the authors’ knowledge, this is the first paper which inspects the relationship between wage dispersion and team performance using data from women’s sports. Further research may examine whether the differences found in sports also apply in different labor markets.

This study aims to investigate how sports customers adopted over-the-top (OTT) services to consume sport content. Inspired by the technology acceptance model (TAM), the study aims to understand users' behavior when consuming sporting events and users' perceptions toward OTT services.

The participants of the study are Chinese sports consumers that use streaming services to watch live sport content. An online survey was distributed through HUPU Sports, a Chinese online communication community where sports fans can share opinions. To make sure all responses qualified to take part in the study, skip logic questions were added at the beginning of the questionnaire to ask participants to answer whether they used streaming services for watching sports. A total of 352 responses were received and there were 327 useable questionnaires.

The results revealed that viewing convenience, free of commercials and viewing quality were the main reasons impacting them to adopt OTT services. In terms of users' perceptions, paid users rated higher in perceived enjoyment, perceived value, perceived usefulness (PU) and ease of use than nonpaid users. OTT users' fandom and PU could predict the time the users spent on using these services, while the users' fandom and perceived value are positively related to the money users spent on these services. In addition, this study also found that users' fandom, perceived value, content quality, and ease of use are positively associated with users' intention to continue to use the service.

The study is one of the first attempts to explore how sports audiences adopted OTT services to consume sport content and explore the audiences' perceptions toward OTT usage. Previous studies have already investigated how users adopted music streaming services (Fernandes and Guerra, 2019) and other online streaming services (Shin and Park, 2021), but little attention has been given to sports streaming services specifically. Therefore, the findings of the study fill the gap in the extant knowledge of sport consumers' behavior and provide more insights to their online behaviors. Moreover, the authors also contribute to the growing digital media literature by advancing our understanding perceptional differences between paid users and unpaid users. The streaming services literature has primarily focused on general users (Fernandes and Guerra, 2019), but the services neglect to understand the differences in between paid and unpaid users.

The authors intend to contribute to the lack of information about corporate social responsibility (CSR) in sports verified in the literature. The main purpose is to understand what the supporters' perceptions of CSR practices in sports clubs are and how these initiatives influence some of their attitudes towards the clubs they support.

Using a total sample of 142 supporters, the study hypotheses were tested with PLS-SEM structural equation modeling.

The authors conclude that CSR initiatives have a positive influence in the supporters' perception of the club and contribute to the positive word-of-mouth communication about the club. The results also show that these initiatives do not have a significant influence on the supporters' intention to become or remain paid members of sports clubs.

It should be noted that research on CSR in the national sports context is scarce, which increases the importance of its contribution to the literature in this area.

Integrating the resource-based view (RBV) with pay dispersion research, the authors examine how the allocation of resources between hiring new employees and compensating current employees, as well as the allocation of resources among new employees, affects organizational performance.

The authors use panel data on Major League Baseball teams. The authors also use system generalized method of moments (GMM) estimations to control for the impact of past performance on current performance, unobserved individual heterogeneity and omitted variable bias.

The authors find that the larger the portion of the human resources (HR) budget allocated to hiring new employees, the poorer organizational performance becomes unless the focal organization has already significantly underperformed. The authors also find that pay concentration among new employees has a positive impact on organizational performance unless the focal organization has already significantly overperformed.

This study extends RBV research by examining how resource allocation patterns affect organizational performance, which has rarely been studied. Moreover, by showing the organizational context's significant effect on the outcome of financial allocation for resource acquisition, this study extends both the RBV research and the pay dispersion research.

Professional sports teams employ highly paid managers and coaches to train players and make tactical and strategic team decisions. A large literature analyzes the impact of manager decisions on team outcomes. Empirical analysis of manager decisions requires a quantifiable proxy variable for manager decisions. Previous research focused on manager dismissals, tenure on teams, the number of substitutions made in games or the number of healthy players on rosters held out of games for rest, generally finding small positive impacts of manager decisions on team success.

The authors quantify manager decisions by developing a novel measure of game-specific coaching decisions: the Herfindahl–Hirschman Index (HHI) of playing-time across players on a team roster over the course of a season.

Evidence from two-way fixed effects regression models explaining observed variation in National Basketball Association team winning percentage over the 1999–2000 to 2018–2019 seasons show a significant association between managers’ allocation of playing time and team success. A one standard deviation change in playing-time HHI that reflects a flattened distribution of player talent is associated with between one and two additional wins per season, holding the talent of players on the team roster constant. Heterogeneity exists in the impact across teams with different player talent.

This is one of the first papers to examine playing-time concentration in the NBA. The results are important for understanding how managerial decisions about resource allocation lead to sustained competitive advantage. Linking coaching decisions to wins can help teams to better promote this core product.

This paper aims to propose an analysis of financial regulation practices, identified thanks to an extensive benchmark carried out in eight European professional sports leagues.

Between 1970 and 2018, 81 French football clubs went bankrupt. The paper proposes an analysis of financial regulation practices in eight European professional sports leagues to enhance the prevention of bankruptcy of French football clubs. Three research questions are addressed: What are the financial and accounting disclosure practices in the main professional leagues? What assessment tools are employed to evaluate the financial risk and budgetary feasibility? What financial support measures exist for clubs and how are insolvency proceedings initiated by clubs? To identify financial regulation practices in professional sport, a selection of leagues was made based on their economic importance, specific regulatory tools used, and their approach to financial difficulties and the handling of insolvency proceedings.

Through an examination of financial regulation practices in other leagues, three main findings are highlighted: The significance of required financial documents and deadlines varies depending on the competition organizer; some leagues utilize ratio-based assessments rather than relying solely on opinions from financial oversight bodies; certain leagues have established assistance processes for troubled clubs as opposed to punitive measures resulting in administrative regulations.

This study proposes new financial regulation modalities to prevent the bankruptcy of French football clubs. Firstly, a reform management control is suggested. Secondly, the engagement of stakeholders in bankruptcy prevention is recommended. Lastly, the implementation of a dedicated policy to support clubs facing difficulties is proposed.

The French football federation and the professional league are important actors in the European football. Many bankruptcies are noted in these championships and since the COVID crisis, the financial situation of the clubs has deteriorated, pointing to a strong risk of bankruptcy in the coming years.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.