Forecasting the Long-Term Viability of an Enterprise: The Case of a Minor League Baseball Franchise

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J. Thomas Yokum Angelo State University

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Juan J. Gonzalez The University of Texas at San Antonio

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Tom Badgett Angelo State University

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We are interested in forecasting or predicting the long-term viability of a minor league baseball team. The research question is whether this minor league team will be successful in attracting attendance over an extended period of time. An important financial issue is if the team is predicted to fail, then exactly how long will it last? A variety of methods are used in a step-by-step procedure to evaluate this viability. We first test whether attendance is evolving or stable through a unit root test, a test of market persistence. We then use the Bass model to assess whether the projected product life cycle is turning up or down. The Gompertz and logistic (Pearl) diffusion curves are next applied to home stand data of various lengths in order to make forecasts of an eventual dissolution point at which the team would financially collapse. Market saturation is not estimated, but set at the stadium capacity. Forecasting principles involving diffusion models are implemented. Analogies are used as a complementary forecasting technique to assess whether there is long-term potential for survival. Finally, logistic regression on cross-sectional data is used to supplement the forecasts. The results of the triangulation of diffusion curves, analogies, and logistic regression predict a decline in the minor league team’s ability to capture attendance.

Yokum is with Angelo State University, San Angelo, TX; Gonzalez is with The University of Texas at San Antonio, San Antonio, TX; Badgett is with Angelo State University, San Angelo, TX.

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