| The purpose of this study was to develop a more precise casino revenue prediction model. According to the literature, seven concepts were hypothesized to explain the variance in revenues: market region, demographics, facility characteristics, political environment, tourism activity, access and competition. The operationalization of these concepts resulted in 25 independent variables. Multiple regression techniques were used to incorporate these variables into a casino revenue prediction model. Due to the first model's multicollinearity, two additional models were necessary.;To test the models' utility and predictive accuracy, three cases were removed prior to model development. The Initial and Reduced Variable Models were tested for the ability to predict casino revenues. Two of the three test cases were accurately estimated within one standard error of the estimate. As stand alone prediction tools, the models developed in this study do not yield useful revenue estimates. More comparable measures of the dependent variable and the development and inclusion of relative attractiveness measures of casinos were a few of several refinements identified to improve the models. In summary, it is unlikely that even a much improved single model will prove to be a total solution to predicting casino revenues, but such a model offers considerable promise as an additional tool for integrative feasibility analysis.;The Initial Casino Revenue Prediction Model contained 15 independent variables and explained 97% of the variance in revenues; however, due to assumption violations, assessing the relative role of each independent variable proved to be problematic. A Reduced Variable Prediction Model explained 83% of the variance and included six independent variables associated with four of the seven concepts. The four concepts included: physical characteristics, competition, existing tourism activity and demographics. The independent variables included are listed from most to least influential: (1) number of mechanical devices per person for the intermediate market region, (2) distance from Las Vegas, (3) level of tourism activity within the county of the casino, (4) distance from the closest competitor casino, (5) number of competitor casinos within a 150 mile radius and (6) the mean income for the tourist market region. |
