• Journal of Fashion Business
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• v.6 no.5
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• pp.136-150
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• 2002

In this study, we proposed a method to be standing customers as the supporting system for the improvement of fashion garment industry which was the marginal growth getting into full maturity of market. As for the customer creation method of Fashion garment company is developing a marketing program to be standing customer as customer scoring to estimate a existing customer‘s buying power, and figure out minimum fixed sales of company to use a future purchasing predict. This study was a result of data from total sixty thousands data to be created for the 11 months from september. 2000 to July. 2001. The data is part of which the company leading the Korean fashion garment industry has a lot of a customer purchasing history data. But this study used only 48,845 refined purchased data to discriminate from sixty thousands data and 21,496 customer case with the exception of overlapping purchased data among of those. The software used to handle sixty thousands data was SAS e-miner. As the analysis process is put in to operation the analysis of the purchasing customer’s profile firstly, and the second come into basket analysis to consider the buying associations for Association goods, the third estimate the customer grade of Customer loyalty by 3 ways of logit regression analysis, decision tree, Artificial Neural Network. The result suggested a method to be estimate the customer loyalty as 3 independent variables, 2 coefficients. The 3 independent variables are total purchasing amount, purchasing items per one purchase, payment amount by one purchasing item. The 2 coefficients are royal and normal for customer segmentation. The result was that this model use a logit regression analysis was valid as the method to be estimate the customer loyalty.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.47-59
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• 1995

The main purpose of this study is identifying the factors which affect the mode choice behavior of work trips. Disaggregate behavioral approach is used for the analysis . The data were collected using the questionnaire survey method in Taegu. Two models were developed in this study which are multinomial logit model(MODEL-1) for auto, taxi and bus and multinomial logit model (MODEL-2) for auto, taxi, bus and subway. The stated preference (SP) data were used for the analysis of the subway mode choice behavior. MODEL-1 provide reasonable results for the future application. A multinomial model (MODEL-2) developed using the stated preference(SP) data was tested for the use of future transportation mode. It is four that the those models provides reasonable results in terms of behavioral and statistical consideration.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.655-673
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• 2004

This paper is concerned with analysing the bankruptcy prediction power of three models: Multivariate Discriminant Analysis(MDA ), Logit Analysis, Neural Network. The after-crisis bankrupted companies were limited to the research data and the listed companies belonging to manufacturing industry was limited to the research data so as to improve prediction accuracy and validity of the model. In order to assure meaningful bankruptcy prediction, training data and testing data were not extracted within the corresponding period. The result is that prediction accuracy of neural network model is more excellent than that of logit analysis and MDA model when considering that execution of testing data was followed by execution of training data.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.493-505
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• 1997

The analysis of binary data appears to many areas such as statistics, biometrics and econometrics. In many cases, data are often collected in which some observations are incomplete. Assume that the missing covariates are missing at random and the responses are completely observed. A method to Bayesian analysis of the binary regression model with incomplete data is presented. In particular, the desired marginal posterior moments of regression parameter are obtained using Meterpolis algorithm (Metropolis et al. 1953) within Gibbs sampler (Gelfand and Smith, 1990). Also, we compare logit model with probit model using Bayes factor which is approximated by importance sampling method. One example is presented.

• Korean Journal of Organic Agriculture
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• v.28 no.2
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• pp.155-170
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• 2020

The objective of this study is to analyze factors affecting purchase intention and conduct price sensitivity analysis of Korean Shine-muscat for Chinese consumers. Logit model has been set up to find purchase intention with survey data which was conducted in Beijing China. The results show that the high-income, unmarried consumers are more sensitive to the price of Korean Shine-muscat than low-income, married consumers, but have higher purchase intention. Also, consumers who perceive Korea positively and those who prefer Korean dramas are more sensitive to the price but have higher purchase intention. Consumers with a high monthly purchase frequency of Shine-muscat have higher purchase intention of Korean Shine-muscat, but are more sensitive to the price. The results of this study can be utilized as basic information for promoting the export of Korean Shine- muscat to China.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.933-945
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• 2012

In this paper we used the KLIPS(Korean Labor and Income Panel tudy) data that surveyed from 2006(wave 9) to 2009(wave 12). Other previous studies are concerned with the panel attrition in the early wave, but this study classifies the response pattern and investigates some factors that influence panel attrition when the panel tends to stabilize. It was revealed that panel attrition was influenced by relocation and housing type through the logit model. Besides it was appeared that panel attrition was affected by the monthly living expenses and the overall household income through the decision tree.

• Journal of Agricultural Extension & Community Development
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• v.28 no.4
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• pp.215-229
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• 2021

This study aims to identify the factors influencing the registration of managers or co-managers in agricultural management in the field of work and life of female farmers and to derive implications for expanding the registration of female farmers as managers and securing the status of women. In this study, binomial logit analysis was conducted with 1,043 questionnaire responses collected on&offline to achieve the research purpose. As a result of the analysis, it was found that the duration of farming, decision-making initiative, the experience of the supporting policies for farming activity, the activities of the crop group/research or female farmer's group, and the experience of supporting policies for self-development and leisure activities had a statisticallty significant effect on the registration of female farmers.

• Health Policy and Management
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• v.15 no.4
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• pp.81-109
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• 2005

According to many recent studies suggesting that cash flow analysis method tends to be more effective than traditional financial index analysis method to predict corporate bankruptcy, this study applies the cash flow analysis method to hospital business to identify the significant variables which can distinguish between superior hospitals and bankruptcy hospitals. The author analyzed recent 3 years, i.e. from the year of 2000 to the year of 2002, financial statements of 31 bankrupt hospitals In 2003, and the same number of superior hospitals through using Multiple Discriminant Analysis and Logit Analysis. The results are belows; First, the study releases that Logit Analysis is more likely to be effective than Multiple Discriminant Analysis. Second, this research also shows that traditional financial index analysis method is more superior compare to cash flow analysis method for hospital bankruptcy predict model. Finally, this study suggest that the significant variables, which can distinguish superior hospitals from bankrupt hospitals, are Operating/Current Liabilities$(Y_2)$, CFO/Equity$(Y_5)$ for cash flow analysis method and Net Worth to Total Assets Ratio$(X_1)$, Quick Ratio $(X_3)$, Return on Assets$(X_6)$, Growth Rate of Patient Revenues$(X_{16})$ for traditional financial index analysis method.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.360-365
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• 2016

The purpose of this study is to provide the basic information for the early enforcement and extension of the improvement project of management scale of private forest land by understanding the characteristics of forest owners, who have an influence on the participation of the project as one of the private forest management vitalization plans. To achieve this goal, a questionnaire survey targeting 373 forest owners was conducted and analyzed by Binary-Logistic Regression. The variables for binary-logistic regression included gender, age, academic ability, occupation, income, residence, purpose of forest ownership, and status of cooperative membership. As a result of the analysis, 267 forest owners (71.6%) of total 373 forest owners have the intention to participate in the scaling project for private forest management. The rest of forest owners (106 forest owners, 28.4%) would not be willing to participate in the project. As a result of binary-logistic regression, the most important variables, which have an impact on the participation of private forest management scale improvement project, are age, job and forest own purpose.

• Korean Journal of Organic Agriculture
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• v.25 no.4
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• pp.699-710
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• 2017

This study analyze the willingness to pay for customized agricultural products to diabetes. For this purpose, a survey was carried out for patients with diabetes 212 patients. The main results are as follows. First, the survey found that the interest in health and food was found to be very high in 93.9 % and 85.9 % respectively. This means that there is sufficient market potential if customized food and diets for diabetes are developed. Second, the Logit analysis showed that influential factor for the willingness to pay for a customized diet. The higher the risk, the better the health outcomes, the higher the likelihood that the higher the level of income, the more likely it is to purchase a product for a diabetic food package. Third, the average amount of willingness to pay for the customized food for diabetes patients was 7,823.5 won and the truncated average value was 6,953.3 won.