Economic factors undoubtedly play an important role in sports entrepreneurship, especially football, and fans' support helps clubs to increase their revenue and improve their financial status. The aim of this study is to systematically investigate spectator demand in the English Premier League, its interaction with the media and the effects of these variables on club revenue. Questions raised in this study deal with, as far as the variable of spectator demand is concerned, whether or not the system is in a steady state after going through a transition period. This paper studies the relationship between media attention, spectator demand and club revenue, as far as system dynamics is concerned. How the system behaves in the long run and the behavior of each system variable in the future, are other key issues of interest in this paper. Methodology is based on system dynamics modeling. The model developed is based on data collected from the English Premier League from 1995 to 2010. The state of the system and its stability are investigated through analysis of variance and Chow test. This study shows during a transition period, the system goes through normal stages and reaches a stable, steady state, and the system's future behavior will remain consistent; the variables of media attention, spectator demand and club revenue follow an exponential long-term trend. The application of a system dynamics approach is useful not only in exploring, revealing and understanding such significant features, but also in paving the way for subsequent studies to consider more variables introduced into model, simulating the system in a larger scope. This would allow systemic investigation of more parameters, including those affecting demand (e.g., social factors or appeal), and consequently studying system behaviors in a larger dimension. Based on the system dynamics approach presented in this paper, a multi input – multi output state space modeling of the system can be approached, in order to enable transfer function derivations, finding unstable poles in the stability analysis, stabilizing the instabilities, and system optimization. Nonetheless, nonlinear modes and behaviors of the system can also be explored for thorough system identification.
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