Research Team Members: Jonathan A. Jensen*, Brian A. Turner†, Natalie Caneja*, David Head*, Akash Mishra*, and Tyler Wisniewski*
* University of North Carolina, Chapel Hill, NC; † The Ohio State University, Columbus, OH
Why did you do this study?
One of the more important evolutions in the sport industry over the past decade has been the marked increase in the application of advanced methodologies to ascertain patterns in data, or analytics. Numerous new methodological approaches are now being applied to assist sport organizations in decision-making relative to scouting, player development, and resource allocation. However, analytics are just now beginning to be applied off of the field to the business side of sport organizations, in areas such as ticket pricing and sales.
One area that has yet to be impacted by this trend in the application of analytics is revenue projections and forecasting. Despite monumental gains in other areas, revenue forecasts for many sport organizations still largely depend on the renewal rate, simply the annual percentage of sponsors or ticket holders who renew their relationship with the organization.
This research offers a new approach to the analysis and forecasting of revenue from an increasingly important revenue source for sport organizations, commercial sponsorship. Many non-profit sport organizations, such as the International Olympic Committee (IOC), the United States Olympic Committee (USOC) and their many National Governing Bodies (NGBs), as well as the National Collegiate Athletic Association (NCAA) and intercollegiate athletic departments at its member institutions, depend on commercial sponsorship for an increasingly larger portion of their annual revenue.
What did you do and what did you find in this study?
Given these challenges, the purpose of this research is to apply advanced methodological approaches to assist these various types of organizations
in sponsorship revenue forecasting. Specifically, this research represents the first application of survival analysis modeling approaches in an empirical investigation of the duration of sponsorships. Typically utilized in the biostatistics and medical fields, survival analysis approaches can provide a wealth of additional information about the duration of sponsorships. For example, rather than simply providing information on how many sponsors typically renew, this approach unearths a variety of additional information, including when the probability of a sponsor ending its relationship is the highest and the median lifetime of the sponsorships.
Initial results of the research, which was named a finalist in the research paper competition at the 2016 MIT Sloan Sports Analytics Conference and is slated to be published in Sport Marketing Quarterly, has utilized the context of global sport organizations, such as the International Olympic Committee (IOC) and the Fédération Internationale de Football Association (FIFA). Current research being performed in conjunction with students in the UNC Sport Administration program extends the research to the context of intercollegiate athletics, including athletic apparel sponsorships, multimedia rights agreements, title sponsorships of postseason bowl games, and naming rights agreements of facilities. Future research involves the insertion of covariates into the models, to ascertain whether there are certain conditions or factors that can actually predict the end of these partnerships.
How do these findings impact the public?
The impact of the research involves assisting non-profit sport organizations in particular in improving their understanding of when these marketing partnerships are most susceptible to dissolution and their ultimate duration, as well as what factors may be predictive of the end of such partnerships. Given that many non-profit sport organizations depend on sponsorship revenue for their survival, these efforts help them to better forecast revenue they receive from this increasingly important source. In addition, the identification of covariates that may be statistically significant predictors of the dissolution of such partnerships may help these organizations isolate certain factors that should be closely monitored throughout the relationship, and identify the types of sponsors more likely to enter into longer-term relationships that can help guarantee the survival of the organization for many years to come.