Award Date

1-1-2000

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Hotel Administration

First Committee Member

Bernard Fried

Number of Pages

173

Abstract

This study shows the development of a discriminant model to predict failure or non-failure in the casino industry. The objective of the study is to provide a model developed for the casino industry using financial data from a sample of failed and nonfailed casinos. The data was provided by the Nevada Gaming Control Board from information they collect from all licensed casinos with over {dollar}1 million in annual revenue; The theoretical model developed for the study includes five constructs that indicate success or failure in the casino business. The five constructs are: Management, Location, Ambiance, Marketing and Financial Strength. Due to limitations in the data, two of these constructs were not included in the development of the discriminant model; Location and Ambiance; The model includes twelve predictor variables: A&P/Total Revenues, Cash Flow/Liabilities, Net Income/Assets, Sales/Assets, Operating Margin, Payroll/Revenues, Payroll/Assets, % Change in A&P/Total Revenues, % Change in Cash/Liabilities, Change in Sales/Assets, % Change in Operating Margin, % Change in Payroll/Revenue and % Change in Payroll/Assets; The model accurately predicted group membership for 100% of the cases included in the study. The model was shown to be statistically valid using a Wilks' Lambda test. The model was also tested using data that were not included in the development of the model. The classification accuracy of this data set was 100% for failed firms and 89% for the nonfailed firms, with an overall classification accuracy of 92.3%; The model predicted failure more accurately than three traditional models using casino data had done in a previous study. The three models were the Altman Z score model, which had a prediction accuracy rate of 50% one year prior to failure, the Deakin model, which had a prediction accuracy rate of 29% one year prior to failure and the Zavgren model, which had an accuracy prediction rate of 21% one year prior to failure; The study shows that a financial analysis model that is developed specifically for the casino industry provides much more accurate information to its users.

Keywords

Bankruptcy; Casino; Casino Industry; Industry; Model; Prediction

Controlled Subject

Accounting

File Format

pdf

File Size

3440.64 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/ul1e-ec1n


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