• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.5810-5818
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• 2015

The dissertation presents the portfolio construction method using the score sheet so that general investors can utilize it easily. This study draws the significant variables to contribute the enterprise value and suggests the combined models by applying the single methodology, which private investors can easily utilize. The results of the research can be classified into 2 areas. Firstly, the significantly affecting variables were selected for analyzing the enterprise value. The variables and the method for the enterprise value analysis were studied from the existing researches to choose the optimal variables. The variables were identified by using AHP method and the structure equation method from the investigation of the previous researches. And the critical variables were added extracted from the common denominator of variables which the 3 grue investors used for their investment. The final variables identified are dividend yield, PER, PBR, PCR, EV/EBITDA, ROE, net income, sales growth rate, net current asset, debt ratio, current ratio, rate of operating profits, ratio of operating profit to net sales, ratio of net income to net sales, net profit to total assets, EPS growth rate, inventory turnover ratio, and receivables turnover. Second, the new methodologies for forecasting enterprise value modifying the existing methods were developed. The result of the Logistic regression analysis for forecasting showed that the equation could not be suitable as the accuracy with 91.98%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.329-338
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• 2019

In this study, we analyze consumer preferences based on the agricultural box scheme attributes, and make a suggestion for business revival. We estimate the marginal willingness to pay (MWTP) for box scheme attributes using a choice experiment. Attributes include the bundle method, the delivery method, and price. To select an efficient model for statistical analysis, we evaluate the conditional logit model, heteroscedastic extreme value model(HEV model), multinomial probit model, and mixed logit model under different assumptions. The results of these four models show that the bundle method, the delivery method, and price are statistically significant in explaining the probability of participation in a box scheme. The results of likelihood ratio tests show that the heteroscedastic extreme value model is the most appropriate for our survey data. The results also indicate that MWTP for a change from fixed type to selection type is KRW 7,096.6. MWTP for a change from parcel service to direct delivery and cold-chain delivery are KRW 3,497.5 and KRW 7,532.7, respectively. The results of this study may contribute to the government's local food policies.

• International Journal of Highway Engineering
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• v.15 no.4
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• pp.155-165
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• 2013

PURPOSES : Benefits for improvement of travel time reliability obtained from construction of new highways should be considered as a major factor in the feasibility study for highway constructions. The purpose of this study is to develop a method of estimation for the value of travel time reliability. METHODS : Highway type (urban/rural highway) and traffic flow type(interrupted/uninterrupted) was considered to estimate he value of travel time reliability. And Double-bounded Dichotomous Choice among Contingent Valuation Method(CVM) was applied to survey the willingness-to-pay of drivers when travel time reliability is improved. Finally the value of travel time reliability was estimated using the results of survey and logit model. The value of travel time reliability was estimated considering travel objectives, time constraint travel and non-time constraint travel. RESULTS: The value of travel time reliability of business trip is higher than that of non-business trip. The value of travel time reliability of time constraint travel is higher than that of non-time constraint travel. The value of travel time reliability in urban area is higher than that in rural area. CONCLUSIONS: It was concluded that the proposed method in this study is more realistic and proper to estimate the value of travel time reliability because it reflects the situations of time constraint travel and non-time constraint travel.

• Korean Management Science Review
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• v.25 no.2
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• pp.43-55
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• 2008

Contingent valuation method(hereafter CVM) is generally believed to be one of the most popular methods used for quantifying the value of non-market goods or services particularly by asking respondents of willingness to pay. This study deals with how to use CVM in calculating the value of mobile telephone service by suggesting methodology of estimation and eliminating biases. This study represents an attempt to estimate the WTP(Willingness To Pay) of the mobile telephone service using the face-to-face interview which is the qualitative technique is used. In this study, by using the single bound dichotomous choice model(SBDC) in order to analyze the valuation of mobile telephone service, WTP was estimated. Also we analyze the factors to pay for mobile service in which it becomes the important factor of demanding services. We used logit model. In order to provide robust estimates of WTP, we have used the Method of Montecarlo Simulation. Consequently, consumers showed that WTP about the mobile communications service is generally high. And it could know that the WTP will fell down as the specialized knowledge about the mobile communications frequency was high. It will be able to become the important part to not only the business carrier but also the policy maker to estimate the economic value of mobile telephone service.

• Korean Journal of Organic Agriculture
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• v.16 no.2
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• pp.189-204
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• 2008

The objective of this paper is to analyze consumers' consumption behavior of environment-friendly mandarin and attributes of mandarin in Korea. It is also to measure consumers' marginal willingness to pay by the attributes of mandarin and to estimate the market-share by products of mandarin from the data surveyed by a survey research company. The questionnaires for consumers were given randomly by interview to 500 married women lived in Seoul and to 200 wholesaler in Seoul, Busan, Daegu, Kwangju. The conjoint analysis method was used to analyze consumers' preference and suggest several implications for the rational production and marketing policy of mandarin.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.109-116
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• 2001

The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

• Journal of Labour Economics
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• v.35 no.2
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• pp.117-146
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• 2012

This study demonstrates the gender difference in the factors that affect job changes and the resulting wage changes in the recent Korean labor market. By using the KEAPS (2003-2007), we found that male workers uniquely tend to stay longer at their current jobs when they have families to support. After controlling self-selection bias, we also found that wage changes resulting from switching jobs differ between male and female workers during this studied period.

• Journal of Korean Society for Quality Management
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• v.23 no.2
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• pp.1-9
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• 1995

Two user groups, expert and non-expert, are sampled to measure the image quality of G3 facsimile. A ITU-TS tset chart No. 2 has been transmitted among some selected cities and evaluated by user groups. Their subjective evaluation to the image quality is quantified by Mean Opinion Score method. There is highly significant difference in the image quality between expert and non-expert. From modified logit model, it is concluded that there is no significance in two considered factors, the effects of the number of links and transmission time. The derived percent curves show that 80% of non-experts(90% of expert) is considering the image quality of G3 facsimile "fair, good, or excellent".

• Journal of the Korean Home Economics Association
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• v.39 no.2
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• pp.15-24
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• 2001

The purpose of this research was to investigate the factors affecting the labor supply of married women. Based on the theoretical review of the process for the labor supply of married women and the review of previous research, the emperical specification was deduced as a function of husband's income, assets, education and age, the number of children and home ownership. The data of this research was collected with questionnaire in 1998. The data consisted of the answers by 200 married women. For the measurement of the emperical specification, Logit, Tobit, and Selection Bias Corrected Regression which modifies selection bias were used. Although several different discussions can made depending on the measurement method, the emperical result of this research showed that the labor supply of married women is explained by husband's income, assets, the level of education and work experience.