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Rate of Physical Activity and Community Health: Evidence From U.S. Counties

Mikihiro Sato, James Du, and Yuhei Inoue

Background:

Although previous studies supported the health benefits of physical activity, these studies were limited to individual-level research designs. Building upon a social-ecological model, we examined the relationship between physical activity and community health—the health status of a defined group of people—while accounting for the potential endogeneity of physical activity to health.

Methods:

We obtained U.S. county-level data from the 2012 Behavioral Risk Factor Surveillance System survey and the 2014 County Health Ranking Database. We first conducted an ordinary least squares (OLS) regression analysis to examine the relationship between the rate of physical activity and community health measured by the average perceived health score for each county. We then conducted a 2-stage least squares (2SLS) regression analysis to investigate this relationship after accounting for potential endogeneity.

Results:

Results from the OLS analysis indicated that the rate of physical activity was positively associated with community health. Results from the 2SLS analysis confirmed that the physical activity rate remained positively associated with community health.

Conclusions:

In line with the social-ecological model, our findings provide the first evidence for the health benefits of county-level physical activity. Our results support extant research that has shown relationships between physical activity and individual-level, health-related outcomes.

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Leveraging Event Participation Benefits Beyond the Running Course: Deciphering the Motivational Basis of Event Satisfaction

James Du, Heather Kennedy, Jeffrey D. James, and Daniel C. Funk

To combat the declining number of finishers plaguing the distance-running industry, it is increasingly important for organizers to optimize event satisfaction levels. Participants’ survey responses from two distance-running events (n 1 = 2,324 and n 2 = 2,526) were analyzed to challenge the traditional managerial scope and theoretical lens through which event satisfaction is conventionally examined. Results revealed five event benefits that capture key motivational antecedents of event satisfaction. Collectively, these benefits, including euphoric, fitness, competition, social, and entertainment benefits, influenced event satisfaction levels (R 2 = 43%) and repeat consumption intentions (R 2 = 23%). For event organizers to foster event satisfaction, it is central to encourage event preparation and participation that promotes the enjoyment of physical activity, fitness and appearance enhancement, socialization, competition, and excitement among registrants. Academics should also extend their scope of event satisfaction to fully capture the entirety of event experience lifecycles (e.g., from registration through event participation).

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Managing Mass Sport Participation: Adding a Personal Performance Perspective to Remodel Antecedents and Consequences of Participant Sport Event Satisfaction

James Du, Jeremy S. Jordan, and Daniel C. Funk

The current study was an investigation of the role of personal performance, an internal assessment of timegoal achievement, on participants’ event satisfaction that would contribute to positive outcomes. Multiattribute online surveys were distributed to participants at two distance participant sport events held in the Southeast and Northeast United States (N = 3,476 and 4,828). A multidimensional Participant Sport Event Attribute and Service Delivery (PSEASD) scale was developed to capture a spectrum of service touch points encountered during the event experience. Empirical results using covariance-based structural equation modeling was used to test and support a proposed model revealing that personal performance was a stronger positive determinant of event satisfaction than traditional service quality and perceived value. A significant negative interaction effect between service quality and personal performance was also revealed. Collectively, the model explained 41% of variance in event satisfaction, and 26% of behavioral intentions. Based on the findings, we suggest managing personal performance expectations is important to holistically manage and promote overall event satisfaction in a participant sport event setting.

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Sport Spectatorship and Life Satisfaction: A Multicountry Investigation

Yuhei Inoue, Mikihiro Sato, Kevin Filo, James Du, and Daniel C. Funk

Elite and professional sport events have been recognized as potential mechanisms to enhance well-being. This multicountry study investigates how engagement in such events, behaviorally through live spectating and psychologically through team identification, is associated with life satisfaction. Data from Australia (N = 268) revealed a positive association between live spectating and life satisfaction through a two-wave design measuring live spectating and life satisfaction in separate surveys. Data from the United States (N = 564) confirmed the live spectating–life satisfaction relationship found in Study 1. Additionally, Study 2 revealed individuals with higher levels of team identification perceived greater emotional support from other fans, and this perception, in turn, predicted life satisfaction. Our findings provide sport managers with implications for positioning appeals in support of sport programs and designing events that facilitate engagement to promote life satisfaction in the community.

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Through the Perilous Fight: A Case Analysis of Professional Wrestling During the COVID-19 Pandemic

Nicholas P. Davidson, James Du, and Michael D. Giardina

The rapidly escalating COVID-19 pandemic has forced the sport industry into unchartered territory. Beginning on March 11, 2020, when the National Basketball Association suspended its season, the American sports landscape has consequently encountered an unprecedented number of temporary suspensions, postponements, and cancellations. Although most major leagues and their pertaining sports have halted to a sudden stop, professional wrestling has surprisingly continued on, including World Wrestling Entertainment’s WrestleMania 36, which was held without fans in attendance. The maintenance of professional wrestling during the COVID-19 crisis has presented a unique situation, in which fans and companies involved in the sport have rallied on social media platforms behind the sport’s relative normality in a time of global uncertainty. Leveraging publicly trackable Twitter data, we analyzed public sentiments toward two of the largest companies (e.g., World Wrestling Entertainment and All Elite Wrestling) in the professional wrestling industry and related trends during the widespread onset of the COVID-19 pandemic in the United States. The results represent exploratory insights surrounding the continuation of professional wrestling during the COVID-19 pandemic.

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Machine Learning in Sport Social Media Research: Practical Uses and Opportunities

James Du, Yoseph Z. Mamo, Carter Floyd, Niveditha Karthikeyan, and Jeffrey D. James

In tandem with the burgeoning popularity of social media research in the field of sport communication and marketing, we are witnessing a concomitant rise in its epistemological sophistication. Despite this growth, the field has given less attention to methodological issues and implications. In light of the development of machine learning, the overarching goal of the current research was to answer the call for innovative methodological approaches to advance knowledge in the area of social media research. Specifically, we (a) assess the current state of sport social media research from a methodological perspective, with a particular focus on machine learning; (b) present an empirical illustration to demonstrate how sport scholars can benefit from the advancement in natural language processing and the derivative topic modeling techniques; (c) discuss how machine learning could enhance the rigor of social media research and improve theory development; and (d) offer potential opportunities and directions for the future sport social media research that utilizes machine learning.

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Using Artificial Intelligence to Detect the Relationship Between Social Media Sentiment and Season Ticket Purchases

Nels Popp, James Du, Stephen L. Shapiro, and Jason M. Simmons

Sport marketing researchers and practitioners have suggested that sport organizations that effectively engage in social media conversations with fans are likely to influence fan behavior. Few prior studies have empirically examined the relationship between social media engagement and sport product purchases, particularly event tickets. The current study utilized artificial intelligence to examine eight user sentiments on official sport organizations’ Twitter accounts, then determine if those sentiments were related to season ticket sales. Three years of season ticket data were obtained from 62 NCAA Division I men’s basketball teams and utilized in a regression model, which also identified Twitter sentiment scores from 176,439 posts captured from the official Twitter account of those programs. A final model, which included several control variables, explained 65.7% of the variance in season ticket sales, with the lagged sentiments of “joy” (positive) and “sadness” (negative) having a statistically significant relationship with season tickets sold.

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The Development and Change of Brand Associations and Their Influence on Team Loyalty Over Time

Thilo Kunkel, Jason P. Doyle, Daniel C. Funk, James Du, and Heath McDonald

The importance of team brand associations in sport management research is well documented, but the formation and stability of these associations has not been investigated. The current research tested the development, change, and predictive ability of brand associations over time. Longitudinal quantitative data were collected from consumers of a new Australian Football League (AFL) team (N = 169) at 3 points in time. One-sample t-tests revealed that brand associations had developed through marketing communications and the launch of the team before the team had played its first AFL game. Repeated-measures multivariate analysis of variance and latent growth modeling showed that brand associations changed over time, reflecting consumers’ experiences with the team. A cross-lagged panel model highlighted that brand associations influenced consumer loyalty in the future. Consequently, sport managers are provided with insights on the development of and change in brand associations that new consumers link with sport teams.