Evaluating Distress Prediction Models for Food Service Franchise Industry
- 한국유통과학회
- 유통과학연구(JDS)
- 제17권 제11호
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2019.1173 - 79 (7 pages)
- 15
Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology : Forty Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 stateme nt of financial po sition and income statement of forty forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t t-test. As a result seven statistically significant independent variables were chosen. The analysis me thod of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results : The difference between the average value of fourteen financial ratios of forty forty-six food service franchise industry was tested through t t-test in order to extract variables that are classified as top top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top top-leveled food service franchis e industry to failure food service industry are income to stockholders’ equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistica l significances of the seven financial ratio independent variables were also confirmed by logit analysis and dis criminant analysis. Conclusions : The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit ana
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