• Title, Summary, Keyword: Income prediction

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Evaluating Distress Prediction Models for Food Service Franchise Industry (외식프랜차이즈기업 부실예측모형 예측력 평가)

  • KIM, Si-Joong
    • The Journal of Distribution Science
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    • v.17 no.11
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    • pp.73-79
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    • 2019
  • 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-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 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method 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-six food service franchise industry was tested through t-test in order to extract variables that are classified as 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-leveled food service franchise 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 statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant 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 analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

Evaluation of Distress Prediction Model for Food Service Industry in Korea : Using the Logit Analysis (국내 외식기업의 부실예측모형 평가 : 로짓분석을 적용하여)

  • Kim, Si-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.11
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    • pp.151-156
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    • 2019
  • This study aims to develop a distress prediction model and to evaluate distress prediction power for the food services industry by using 2017 food service industry financial ratios. Samples were collected from 46 food service industries, and we extracted 14 financial ratios from them. The results show that, first, there are eight ratios (financial ratio, current ratio, operating income to sales, net income to assets, ratio of cash flows, income to stockholders' equity, rate of operating income, and total asset turnover) that can discriminate failures in food service industries and the top-level food service industries. Second, by using these eight financial ratios, the logit function classifies the top-level food service industries, and failures in the food service industry can be estimated by using logit analysis. The verification results as to accuracy in the estimated logit analysis indicate that the model's distress-prediction power is 89.1%.

Evaluation of Corporate Distress Prediction Power using the Discriminant Analysis: The Case of First-Class Hotels in Seoul (판별분석에 의한 기업부실예측력 평가: 서울지역 특1급 호텔 사례 분석)

  • Kim, Si-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.10
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    • pp.520-526
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    • 2016
  • This study aims to develop a distress prediction model, in order to evaluate the distress prediction power for first-class hotels and to calculate the average financial ratio in the Seoul area by using the financial ratios of hotels in 2015. The sample data was collected from 19 first-class hotels in Seoul and the financial ratios extracted from 14 of these 19 hotels. The results show firstly that the seven financial ratios, viz. the current ratio, total borrowings and bonds payable to total assets, interest coverage ratio to operating income, operating income to sales, net income to stockholders' equity, ratio of cash flows from operating activities to sales and total assets turnover, enable the top-level corporations to be discriminated from the failed corporations and, secondly, by using these seven financial ratios, a discriminant function which classifies the corporations into top-level and failed ones is estimated by linear multiple discriminant analysis. The accuracy of prediction of this discriminant capability turned out to be 87.9%. The accuracy of the estimates obtained by discriminant analysis indicates that the distress prediction model's distress prediction power is 78.95%. According to the analysis results, hotel management groups which administrate low level corporations need to focus on the classification of these seven financial ratios. Furthermore, hotel corporations have very different financial structures and failure prediction indicators from other industries. In accordance with this finding, for the development of credit evaluation systems for such hotel corporations, there is a need for systems to be developed that reflect hotel corporations' financial features.

A prediction model of low back pain risk: a population based cohort study in Korea

  • Mukasa, David;Sung, Joohon
    • The Korean Journal of Pain
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    • v.33 no.2
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    • pp.153-165
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    • 2020
  • Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service-National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell's C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

The study on insolvency prediction for Korean households across income levels (소득계층별 한국 차입 가계의 부실화 가능성 연구)

  • Lee, Jong-hee
    • Korean Family Resource Management Association
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    • v.22 no.1
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    • pp.63-78
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    • 2018
  • This study examined the insolvency of debtors using multiple-indicator approaches and compared the outcomes across income levels with the 2016 'Household Financial and Welfare Survey'. This study used (1) the total debt to total assets ratio (DTA), (2) the total debt service ratio (DSR), and (3) the Household Default Risk Index (HDRI) recently developed by the Bank of Korea. Households in the lowest income quintile were more likely to be insolvent than any other income group. Demographics, such as age and gender of the household head, and most of the financial variables significantly increased the likelihood of insolvency based on the DTA. The number of household members and job status increased the likelihood of insolvency based on the DSR. Also, age, gender of the household head, and most of the financial variables increased the likelihood of household insolvency based on the HDRI after controlling for other demographics and financial variables.

A Study on the Fatigue and Health Promoting Behavior of Public Health Nurses and Hospital Nurses (임상간호사와 보건간호사의 피로와 건강증진행위에 대한 연구)

  • Kim, Sun-Ok;So, Hee-Young;Kim, Hyun-Li
    • Journal of Korean Academy of Community Health Nursing
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    • v.14 no.4
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    • pp.699-706
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    • 2003
  • The objective of this study is to find out the difference in perceptional fatigue and health promoting behavior between hospital nurses and public health nurses. The subjects of this study were 141 hospital nurses and 73 public health nurses in Daejeon. Data were collected using a self-reporting questionnaire during the period from the 5th to 16th of March 2003. Collected data were analyzed using SPSS program. Real number, percentage, mean and standard deviation were calculated, and $x^2$-test and t-test, ANOVA, Pearson's correlation coefficient, stepwise multiple regression procedures were carried out. The findings of this study as follows: 1. The mean score of health promoting behavior was 2.71. 2. There were statistically significant differences in health promoting behavior according to age, marital status, family status, residency, educational level, income, the length of work experience and the field of work. (p<0.05) 3. There were statistically significant differences in fatigue according to age, marital status, family status, educational level, income, the length of work experience, perceived health status and the field of work. (p<0.05) 4. The fatigue was found to be in significant negative correlations with health promoting (r=-0.358, p<0.000) and self efficacy (r=-0.314, p<0.000). On the contrary, a significant positive correlation was found between fatigue and perceived barriers (r=0.210, p<00.01). 5. There were five predictors affecting health promoting behavior, which were self-efficacy, income, perceived benefit, fatigue and family support. The most influential factor was self-efficacy that made 31% of prediction, followed by income (6%), perceived benefit (5.2%), fatigue (2.2%) and family support (1.7%) in their order. As a whole, these factors made 46.1% of prediction of health promotion behavior.

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Mild Cognitive Impairment Prediction Model of Elderly in Korea Using Restricted Boltzmann Machine (제한된 볼츠만 기계학습 알고리즘을 이용한 우리나라 지역사회 노인의 경도인지장애 예측모형)

  • Byeon, Haewon
    • Journal of Convergence for Information Technology
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    • v.9 no.8
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    • pp.248-253
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    • 2019
  • Early diagnosis of mild cognitive impairment (MCI) can reduce the incidence of dementia. This study developed the MCI prediction model for the elderly in Korea. The subjects of this study were 3,240 elderly (1,502 men, 1,738 women) aged 65 and over who participated in the Korean Longitudinal Survey of Aging (KLoSA) in 2012. Outcome variables were defined as MCI prevalence. Explanatory variables were age, marital status, education level, income level, smoking, drinking, regular exercise more than once a week, average participation time of social activities, subjective health, hypertension, diabetes Respectively. The prediction model was developed using Restricted Boltzmann Machine (RBM) neural network. As a result, age, sex, final education, subjective health, marital status, income level, smoking, drinking, regular exercise were significant predictors of MCI prediction model of rural elderly people in Korea using RBM neural network. Based on these results, it is required to develop a customized dementia prevention program considering the characteristics of high risk group of MCI.

Demand Analysis of Fresh-fish in the Urban Communities (도시지역에 있어서 선어의 수요분석 -육류와의 대체관계를 중심으로-)

  • 김수관
    • The Journal of Fisheries Business Administration
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    • v.15 no.1
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    • pp.114-130
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    • 1984
  • The structure of food demand is being changed according to the improvement of living standard. Moreover, the intake of animal protein is stepping up. This paper considers how much fresh-fish is consumed as source of animal protein and what extent fresh-fish have substitutive relation for meat with special reference to the change of income and price of fresh-fish and meat. And it is thought to be important work to estimate demand of fresh-fish in attemps to the prediction of food consume pattern and fishing industries in the future. For this estimation, the substitutive relation of fresh-fish and meat is essentially studied. The main conclusions of this study can be drawn as follows: 1. Fresh-fish and meat have substitutive relation on price axis. By the way, increase in demand of A (fresh-fish which have comparatively low price) can be expected according to the low of it's price against meat, but B (fresh-fish wihich have comparatively middle-high price) have peculiar demand without substitutive relation for meat. 2. Demand of A and B rise according to the income increases. 3. It is not sufficient to explain substutive relation of fresh-fish and meat without income variable. 4. Income increases bring about the more increase in demand of B than A. By the way, price increases bring about the decrease of it's consume expenditure, but A have fundamental demand as the source of animal protein. 5. In future, the intake of animal protein will step up. By the way, meat will occupy the more portion of the source of animal protein than fresh-fish.

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Analysis of The Management of Three Tertiary General Hospital(2011 to 2013)

  • Park, Hyun-Suk
    • Journal of Korean Clinical Health Science
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    • v.4 no.2
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    • pp.582-592
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    • 2016
  • Purpose. For more effective hospital management, it analyzes the trend through general characteristics, balance sheet, income statement, and financial ratio analysis, grasps the causes of the problems, and analyzes management of the hospital in order to use the result as baseline data for development of the hospital in the future. Methods. The collected data of 3 years from 2011 to 2013 about 3 tertiary hospitals in metropolitan cities from Alio (provider of public institution information; www.alio.go.kr), Health Insurance Review & Assessment Service (www.hira.or.kr), and the website of the Ministry of Health and Welfare (www.mw.go.kr) were analyzed and general characteristics, balance sheet, income statement, and financial ratio, analysis are used as data. Results & Conclusions. From the result of data analysis from 2011 to 2013, general characteristics, balance sheet, income statement, financial ratio analysis, and pie charts could lead to conclusions as follows. In the result of comprehensive analysis, the 3 tertiary hospitals showed increase of fixed expense due to extension of the buildings and so did the scale of fund and asset. Although medical revenue increased, the margin of increase for medical expense was greater than that of medical revenue, which consequently led to loss. In prediction for the 3 tertiary hospitals based on characteristics so far, it is expected to see improved revenue structure after building extension is completed, but it is necessary to exert management effort to maintain its optimal level by enhancement in stability of management and inventory turnover through management of inventories.

The Usefulness of Other Comprehensive Income for Predicting Future Earnings

  • LEE, Joonil;LEE, Su Jeong;CHOI, Sera;KIM, Seunghwan
    • The Journal of Asian Finance, Economics, and Business
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    • v.7 no.5
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    • pp.31-40
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    • 2020
  • This study investigates whether other comprehensive income (OCI) reported in the statement of comprehensive income (one of the main financial statements after the adoption of K-IFRS) predicts a firm's future performance. Using the quarterly data of Korean listed companies, we examine the association between OCI estimates and future earnings. First of all, we find that OCI is positively associated with earnings in both 1- and 2-quarter ahead, supporting the predictive value of OCI. When we break down OCI into its individual components, our results suggest that the net unrealized gains/losses on available-for-sale (AFS) investment securities are positively associated with future earnings, while the other components (e.g., net unrealized gains/losses on valuation of cash flow hedge derivatives) present insignificant results. In addition, we investigate whether the reliability in OCI estimates enhances the predictive value of OCI to predict future performance. We find that the predictive ability of OCI, in particular the net unrealized gains/losses on available-for-sale (AFS) investment securities, becomes more pronounced when firms are audited by the Big 4 audit firms. Overall, our study suggests that information content embedded in OCI can provide decision-useful information that is helpful for the prediction of future firm performance.